EP3146076A2 - Gene expression profiles associated with sub-clinical kidney transplant rejection - Google Patents

Gene expression profiles associated with sub-clinical kidney transplant rejection

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Publication number
EP3146076A2
EP3146076A2 EP15795439.7A EP15795439A EP3146076A2 EP 3146076 A2 EP3146076 A2 EP 3146076A2 EP 15795439 A EP15795439 A EP 15795439A EP 3146076 A2 EP3146076 A2 EP 3146076A2
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EP
European Patent Office
Prior art keywords
subject
genes
subar
transplant
sample
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
EP15795439.7A
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German (de)
French (fr)
Other versions
EP3146076A4 (en
Inventor
Daniel Salomon
John FRIEDEWALD
Sunil KURIAN
Michael Abecassis
Steven Head
Phillip Todd ORDOUKHANIAN
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Scripps Research Institute
Northwestern University
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Scripps Research Institute
Northwestern University
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Publication date
Priority claimed from EP14841998.9A external-priority patent/EP3044333A4/en
Application filed by Scripps Research Institute, Northwestern University filed Critical Scripps Research Institute
Priority to EP20193092.2A priority Critical patent/EP3825416A3/en
Publication of EP3146076A2 publication Critical patent/EP3146076A2/en
Publication of EP3146076A4 publication Critical patent/EP3146076A4/en
Ceased legal-status Critical Current

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    • CCHEMISTRY; METALLURGY
    • C12BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12QMEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6881Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for tissue or cell typing, e.g. human leukocyte antigen [HLA] probes
    • CCHEMISTRY; METALLURGY
    • C12BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12QMEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • CCHEMISTRY; METALLURGY
    • C12BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12QMEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00Oligonucleotides characterized by their use
    • C12Q2600/136Screening for pharmacological compounds
    • CCHEMISTRY; METALLURGY
    • C12BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12QMEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00Oligonucleotides characterized by their use
    • C12Q2600/158Expression markers
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00Detection or diagnosis of diseases
    • G01N2800/24Immunology or allergic disorders
    • G01N2800/245Transplantation related diseases, e.g. graft versus host disease

Definitions

  • kidney transplantation offers a significant improvement in life expectancy and quality of life for patients with end stage renal disease.
  • graft losses due to allograft dysfunction or other uncertain etiologies have greatly hampered the therapeutic potential of kidney transplantation.
  • subclinical acute rejection is histologically defined as acute rejection characterized by tubule-interstitial mononuclear infiltration identified from a biopsy specimen, but without concurrent functional deterioration (variably defined as a serum creatinine not exceeding 10%, 20% or 25% of baseline values).
  • a critically important challenge for the future of molecular diagnostics in transplantation based on peripheral blood profiling is to predict a state of adequate immunosuppression with immune mediated kidney injury before there is a change in the serum creatinine. This is the challenge of identifying subclinical acute rejection, which at this time is only occasionally and accidentally picked up by protocol biopsies done at arbitrary time points.
  • subAR and SCAR are used interchangeably herein to refer to subclinical acute rejection.
  • SubAR or SCAR is distinct from clinical acute rejection, which is characterized by acute functional renal impairment.
  • the differences between subAR or SCAR and acute rejection can be explained by real quantitative differences of renal cortex affected, qualitative differences (such as increased perforin, granzyme, c-Bet expression or macrophage markers), or by an increased ability of the allograft to withstand immune injury
  • SubAR or SCAR is often diagnosed only on biopsies taken as per protocol at a fixed time after transplantation, rather than driven by clinical indication. Its diagnosis cannot rely on traditional kidney function measurements like serum creatinine and glomerular filtration rates. Predicting graft outcomes strictly based on the kidney biopsy is difficult and this invasive procedure has significant costs and risks for patients. Organ biopsy results can also be inaccurate, particularly if the area biopsied is not representative of the health of the organ as a whole (e.g., as a result of sampling error). There can be significant differences between individual observers when they read the same biopsies independently and these discrepancies are particularly an issue for complex histologies that can be challenging for clinicians. In addition, the early detection of rejection of a transplant organ may require serial monitoring by obtaining multiple biopsies, thereby multiplying the risks to the patients, as well as the associated costs.
  • Transplant rejection is a marker of ineffective immunosuppression and ultimately if it cannot be resolved, a failure of the chosen therapy.
  • the fact that 50% of kidney transplant patients will lose their grafts by ten years post-transplant reveals the difficulty of maintaining adequate and effective long-term immunosuppression.
  • the disclosure provides methods of detecting, prognosing, diagnosing or monitoring subclinical acute rejection (subAR or SCAR). These methods typically entail obtaining nucleic acids of interest, and then (a) determining or detecting expression levels in a subject of at least 5 genes (e.g., at least 10 genes, at least 20 genes, at least 50 genes, at least 100 genes, at least 300 genes, at least 500 genes, etc.); and (b) detecting, prognosing, diagnosing or monitoring subAR or SCAR in the subject from the expression levels.
  • the nucleic acids of interest comprise mRNA extracted from a sample from the subject or nucleic acids derived from the mRNA extracted from the sample from the subject. The methods are particularly useful for analysis of blood samples.
  • step (b) involves comparing the expression level of the gene in the subject to one or more reference expression levels of the gene associated with subAR or SCAR, acute rejection (AR) or lack of transplant rejection (TX).
  • step (b) further includes, for each of the at least five genes, assigning the expression level of the gene in the subject a value or other designation providing an indication whether the subject has or is at risk of developing SCAR, has acute rejection (AR), or has well- functioning normal transplant (TX).
  • the expression level of each of the at least five genes is assigned a value on a normalized scale of values associated with a range of expression levels in kidney transplant patients with SCAR, with AR, or with TX.
  • the expression level of each of the at least five genes is assigned a value or other designation providing an indication that the subject has or is at risk of SCAR, has or is at risk of AR, has well-functioning normal transplant, or that the expression level is uninformative.
  • step (b) further includes combining the values or designations for each of the genes to provide a combined value or designation providing an indication whether the subject has or is at risk of SCAR, has acute rejection (AR), or has well-functioning normal transplant (TX).
  • the method can be repeated at different times on the subject. Some of these methods are directed to subjects who have been receiving a drug, and a change in the combined value or designation over time provides an indication of the effectiveness of the drug.
  • the expression level is determined in a subject of at least five genes selected from the genes in one or more of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, or 1 8.
  • the methods comprise detecting or determining the expression level of at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 1500, or 2000 genes selected from at least one of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, and 18.
  • the detection of expression levels comprises applying a two-step classifier to the gene expression levels.
  • one step in the two- step classifier distinguishes between normal transplant (TX) and AR+subAR.
  • one step in the two-step classifier distinguishes between AR and subAR.
  • the subjects suitable for methods of the invention are patients who have undergone a kidney transplant. Often, the subject has received the kidney transplant within 1 month, 3 months, 1 year, 2 years, 3 years or 5 years of performing step (a).
  • step (a) is performed on a blood sample of the subject.
  • the sample is a blood sample and comprises whole blood, peripheral blood, serum, plasma, PBLs, PBMCs, T cells, CD4 T cells CDS T cells, or macrophages.
  • step (a) is performed on a urine sample of the subject.
  • step (a) is performed on a biopsy from the subject, preferably a kidney biopsy.
  • step (a) is performed on at least 10, 20, 40, 50, 70, 100, 150, 200, 250, 300, 400, or 500 genes from one or more of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, or 18.
  • Some methods further include changing the treatment regime of the patient responsive to the detecting, prognosing, diagnosing or monitoring step.
  • the subject can be one who has received a drug before performing the methods, and the change comprises administering an additional drug or administering a higher dose of the same drug, or administering a lower dose of the same drug, or stopping administering the same drug.
  • Some methods of the invention further include performing an additional procedure to detect SCAR or risk thereof if the determining step provides an indication the subject has or is at risk of SCAR.
  • the additional procedure can be, e.g., examination of a kidney biopsy sample.
  • expression levels of the genes are determined at the mRNA level or at the protein level.
  • step (b) can be performed by a computer.
  • the at least five genes are selected from one or more of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, or 18.
  • the invention provides methods of detecting, prognosing, diagnosing or monitoring subclinical acute rejection (subAR or SCAR) in a subject having normal serum creatinine level. These methods involve obtaining nucleic acids of interest, and then (a) determining or detecting expression levels in the subject of at least 2 genes; and (b) detecting, prognosing, diagnosing or monitoring subAR or SCAR in the subject from the expression levels. In some of these methods, the methods comprise determining or detecting the expression levels in the subject of at least five genes. In some of these methods, the at least two genes or the at least five genes are selected from the genes in one or more of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, or 18.
  • the nucleic acids of interest comprise mRNA extracted from a sample from a subject or nucleic acids derived from the mRNA extracted from the sample from the subject.
  • the sample is a blood sample.
  • the nucleic acids of interest are contacted with probes, wherein the probes are specific for the at least two genes or the at least five genes.
  • step (b) entails comparing the expression level of the gene in the subject to one or more reference expression levels of the gene associated with SCAR, or lack of transplant rejection (TX).
  • step (b) further includes, for each of the at least two genes or the at least five genes, assigning the expression level of the gene in the subject a value or other designation providing an indication whether the subject has or is at risk of developing SCAR.
  • the expression level of each of the at least two genes or the at least five genes is assigned a value on a normalized scale of values associated with a range of expression levels in kidney transplant patients with and without SCAR.
  • the expression level of each of the at least two genes or at least five genes is assigned a value or other designation providing an indication that the subject has or is at risk of SCAR, lacks and is not at risk of SCAR, or that the expression level is uninformative.
  • step (b) further includes combining the values or designations for each of the genes to provide a combined value or designation providing an indication whether the subject has or is at risk of subAR or SCAR.
  • the method can be repeated at different times on the subject.
  • the subject can be one who is receiving a drug, and a change in the combined value or designation over time provides an indication of the effectiveness of the drug.
  • Some methods of the invention are directed to subjects who have undergone a kidney transplant within 1 month, 3 months, 1 year, 2 years, 3 years or 5 years of performing step (a).
  • step (a) is performed on a blood sample of the subject.
  • the sample is a blood sample and comprises whole blood, peripheral blood, serum, plasma, PBLs, PBMCs, T cells, CD4 T cells CD8 T cells, or macrophages.
  • step (a) is performed on a urine sample of the subject.
  • step (a) is performed on at least 3, 4, 5, 10, 15, 20, 30 or more genes. In some methods, step (a) is performed on at least 10, 20, 40, or 100 or more genes selected from at least one of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, and 18. Some of the methods further include changing the treatment regime of the patient responsive to the detecting, prognosing, diagnosing or monitoring step. In some of these methods, the subject is one who has received a drug before performing the methods, and the change comprises administering an additional drug or administering a higher dose of the same drug, or administering a lower dose of the same drug, or stopping administering the same drug.
  • Some other methods can further include performing an additional procedure to detect SCAR or risk thereof if the determining step provides an indication the subject has or is at risk of SCAR, e.g., a kidney biopsy.
  • expression levels of the genes can be determined at the mRNA level or at the protein level.
  • step (b) is performed by a computer.
  • the methods provided herein compare the gene expression profile in the peripheral blood of patients with acute cellular rejection (AR) on a surveillance protocol biopsy (SCAR-normal creatinine) with that of patients with normal protocol surveillance biopsies (TX - normal creatinine), or with a previously validated peripheral blood profile for patients with clinical acute cellular rejection (CAR-elevated creatinine) found on a "for cause" biopsy.
  • the invention provides arrays which contain a support or supports bearing a plurality of nucleic acid probes complementary to a plurality of mRNAs fewer than 5000 in number.
  • the plurality of mRNAs includes mRNAs expressed by at least five genes selected from one or more of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, or 1 8. In some embodiments, the plurality of mRNAs are fewer than 1000 or fewer than 100 in number. In some embodiments, the plurality of nucleic acid probes are attached to a planar support or to beads. In some embodiments, the at least five genes are selected from one or more of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, or 18. In a related aspect, the invention provides arrays that contain a support or supports bearing a plurality of ligands that specifically bind to a plurality of proteins fewer than 5000 in number.
  • the plurality of proteins typically includes at least five proteins encoded by genes selected from one or more of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, or 18. In some embodiments, the plurality of proteins are fewer than 1000 or fewer than 100 in number. In some embodiments, the plurality of ligands are attached to a planar support or to beads. In some embodiments, the at least five proteins are encoded by genes selected from one or more of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, or 18. In some embodiments, the ligands are different antibodies that bind to different proteins of the plurality of proteins.
  • the invention provides methods of expression analysis. These methods involve determining expression levels of up to 2,000 genes (including at least 5 genes selected from one or more of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, or 18) in a sample from a subject having a kidney transplant. In some methods, the expression levels of up to 100 or 1000 genes are determined. The gene expression levels can be determined at the mRNA level or at the protein level. For example, the expression levels can be determined by quantitative PCR or hybridization to an array or sequencing.
  • the invention additionally provides methods of screening a compound for activity in inhibiting or treating SCAR.
  • the methods involve (a) administering the compound to a subject having or at risk of SCAR; (b) determining, before and after administering the compound to the subject, expression levels of at least five genes in the subject selected from one or more of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 1 5, 17, or 1 8 and species variants thereof, and (c) determining whether the compound has activity in inhibiting or treating SCAR from a change in expression levels of the genes after administering the compound.
  • step (c) entails, for each of the at least five changes, assigning a value or designation depending on whether the change in the expression level of the gene relative to one or more reference levels indicating presence or absence of SCAR. Some methods further include determining a combined value or designation for the at least five genes from the values or designations determined for each gene.
  • the subject is human or a nonhuman animal model of SCAR.
  • the methods disclosed herein have an error rate of less than about 40%. In some embodiments, the method has an error rate of less than about 40%, 35%, 30%, 25%, 20%, 15%, 10%, 5%, 3%, 2%, or 1 %. For example, the method has an error rate of less than about 10%. In some embodiments, the methods disclosed herein have an accuracy of at least about 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, or 99%. For example, the method has an accuracy of at least about 70%. In some embodiments, the methods disclosed herein have a sensitivity of at least about 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, or 99%.
  • the method has a sensitivity of at least about 80%.
  • the methods disclosed herein have a positive predictive value of at least about 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, or 99%.
  • the methods disclosed herein have a negative predictive value of at least about 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, or 99%.
  • the gene expression products described herein are RNA (e.g., mRNA).
  • the gene expression products are polypeptides.
  • the gene expression products are DNA complements of RNA expression products from the transplant recipient.
  • the algorithm described herein is a trained algorithm.
  • the trained algorithm is trained with gene expression data from biological samples from at least three different cohorts.
  • the trained algorithm comprises a linear classifier.
  • the linear classifier comprises one or more linear discriminant analysis, Fisher's linear discriminant, Naive Bayes classifier, Logistic regression, Perceptron, Support vector machine (SVM) or a combination thereof.
  • the algorithm comprises a Diagonal Linear Discriminant Analysis (DLDA) algorithm.
  • the algorithm comprises a Nearest Centroid algorithm.
  • the algorithm comprises a Random Forest algorithm or statistical bootstrapping.
  • the algorithm comprises a Prediction Analysis of Microarrays (PAM) algorithm.
  • the algorithm is not validated by a cohort-based analysis of an entire cohort.
  • the algorithm is validated by a combined analysis with an unknown phenotype and a subset of a cohort with known phenotypes.
  • the sample is a blood sample or is derived from a blood sample.
  • the blood sample is a peripheral blood sample.
  • the blood sample is a whole blood sample.
  • the sample does not comprise tissue from a biopsy of a transplanted organ of the transplant recipient.
  • the sample is not derived from tissue from a biopsy of a transplanted organ of the transplant recipient.
  • the assay is a microarray, SAGE, blotting, RT-PCR, sequencing and/or quantitative PCR assay.
  • the assay is a microarray assay.
  • the microarray assay comprises the use of an Affymetrix Human Genome U 133 Plus 2.0 GeneChip.
  • the mircroarray uses the Hu l 33 Plus 2.0 cartridge arrays plates.
  • the microarray uses the HT HG-U133+ PM array plates.
  • determining the assay is a sequencing assay.
  • the assay is a RNA sequencing assay.
  • the subject or transplant recipient has a serum creatinine level of less than 3.0 mg/dL, less than 2.5 mg/dL, less than 2.0 mg/dL, or less than 1 .5 mg/dL.
  • the subject may have a serum creatinine level that is stable over time.
  • the subject or transplant recipient has a serum creatinine level of at least 0.4 mg/dL, 0.6 mg/dL, 0.8 mg/dL, 1.0 mg/dL, 1 .2 mg/dL, 1.4 mg/dL, 1 .6 mg/dL, 1.8 mg/dL, 2.0 mg/dL, 2.2 mg/dL,
  • the transplant recipient has a serum creatinine level of at least
  • the transplant recipient has a serum creatinine level of at least 3 mg/dL.
  • the invention provides methods of detecting subclinical acute rejection (subAR) in a subject comprising: (a) obtaining nucleic acids of interest, wherein the nucleic acids of interest comprise mRNA extracted from a sample from the subject or nucleic acids derived from the mRNA extracted from the sample from the subject; (b) detecting expression levels in the subject of at least five genes using the nucleic acids of 2202 interest obtained in step (a); and (c) detecting subAR in the subject from the expression levels detected in step (b).
  • the sample from the subject is a blood sample.
  • the method detects subAR with an accuracy of greater than 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90% or 95%. In another aspect, the method detects subAR with a sensitivity of greater than 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90% or 95%. For example, the method detects subAR with an accuracy of greater than 75% or a sensitivity of greater than 75%.
  • the method further comprises contacting the nucleic acids of interest with probes, wherein the probes are specific for the at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 1500, or 2000 genes selected in step (b).
  • detecting subAR comprises detecting a risk of developing subAR, detecting acute rejection (AR), detecting a risk of having acute rejection (AR), or detecting a well-functioning normal transplant (TX).
  • step (c) of the method comprises comparing the expression level of the gene in the subject to one or more reference expression levels of genes associated with subAR, acute rejection (AR) or lack of transplant rejection (TX).
  • Figure 1 shows a schematic overview of certain methods in the disclosure.
  • Figure 2 shows a schematic overview of certain methods of acquiring samples, analyzing results, and transmitting reports over a computer network.
  • Figure 3 is an illustration of hierarchical clustering of gene expression signals of 33 probesets used to differentiate SCAR versus TX.
  • Figure 4 shows a computer system for implementing the methods of the disclosure.
  • Figure 5 shows a correlation of fold-change between microarray and NGS analyses (1066 common genes).
  • Figure 6 shows a heat map and clustering of fold changes (Microarrays vs NGS) of 1066 genes.
  • Figure 7 shows correlation of fold-change between microarray and NGS analyses (all expressed NGS 7076 genes).
  • Sub-clinical acute rejection (referred to herein as “subAR” or “SCAR,” interchangeably) is normally defined as histologic kidney rejection (e.g., histologic acute cellular rejection) with normal serum creatinine, and is associated with worse long term graft survival. In some cases, creatinine can be a lagging indicator of renal injury. Most times acute rejection (AR) of kidney graft is detected only after the initial injury has started. Early detection of subAR or SCAR can avoid unnecessary complications later in the course of graft life. However, normally subAR or SCAR is detected using a protocol kidney biopsy which is invasive, expensive and involves substantial risk.
  • the present invention is predicated in part on the development by the inventors of a peripheral blood gene expression profiling signature that can distinguish Sub-Clinical Acute Rejection (subAR or SCAR), well-functioning normal transplant (TX) and Acute Rejection (AR).
  • SCAR Sub-Clinical Acute Rejection
  • TX well-functioning normal transplant
  • AR Acute Rejection
  • the present inventors have identified consensus sets of gene expression-based molecular biomarkers associated with SCAR. This was accomplished via a genome-wide gene analysis of expression profiles of over 50,000 known or putative gene sequences in peripheral blood. More than 2,000 sequences were found to have differential expressions among the 3 different patient groups (Table 4). Among these sequences, the inventors further identified the top 200 differentially expressed probesets (Table 2), which can provide more focused and better expression profiles for differentiating the three classes of patients.
  • Results from the present inventors' studies provide the basis of a molecular test that can diagnose subAR or SCAR, and also enables minimally invasive methods for monitoring kidney transplant recipients.
  • the value of a blood test for subAR or SCAR is that it allows detection of subclinical immune-mediated transplant rejection prior to clinical evidence of kidney injury and dysfunction.
  • This blood-based test is minimally invasive and amenable to serial monitoring.
  • peripheral blood gene expression profiling may be used to inform when to perform a biopsy in patients with normal renal function and/or to replace surveillance protocol biopsies. Therefore, the invention is useful for post-transplant management of kidney recipients. Additional advantages of the test is that serial monitoring of all patients with a blood test for SCAR and treatment of all patients with SCAR by increasing the level of effective immunosuppression may significantly improve long term graft function and survival.
  • a method comprises obtaining a sample from a transplant recipient in a minimally invasive manner (110), such as via a blood draw.
  • the sample may comprise gene expression products (e.g., polypeptides, RNA, mRNA isolated from within cells or a cell- free source) associated with the status of the transplant (e.g., subAR.).
  • the method may involve reverse-transcribing RNA within the sample to obtain cDNA that can be analyzed using the methods described herein.
  • the method may also comprise assaying the level of the gene expression products (or the corresponding DNA) using methods such as microarray or sequencing technology (120).
  • the method may also comprise applying an algorithm to the assayed gene expression levels (130) in order to detect subAR.
  • a treatment decision may be made.
  • the treatment decision may be that the transplant recipient should be treated more aggressively to mitigate the risk of acute rejection.
  • the treatment decision may be to reduce an existing treatment regimen, particularly if subAR is not detected.
  • the treatment decision may involve a decision to forego or delay obtaining a kidney biopsy from the patient.
  • Transplantation is the transfer of tissues, cells or an organ from a donor into a recipient. If the donor and recipient as the same person, the graft is referred to as an autograft and as is usually the case between different individuals of the same species an allograft. Transfer of tissue between species is referred to as a xenograft.
  • a biopsy is a specimen obtained from a living patient for diagnostic or prognostic evaluation. Kidney biopsies can be obtained with a needle.
  • An average value can refer to any of a mean, median or mode.
  • a gene expression level is associated with a particular phenotype e.g., presence of subAR (SCAR) or AR if the gene is differentially expressed in a patient having the phenotype relative to a patient lacking the phenotype to a statistically significant extent.
  • SCAR subAR
  • a gene expression level can be measured at the mRNA and/or protein level.
  • a target nucleic acid may be a nucleic acid (often derived from a biological sample), to which a polynucleotide probe is designed to specifically hybridize.
  • the probe can detect presence, absence and/or amount of the target.
  • target nucleic acid can refer to the specific subsequence of a larger nucleic acid to which the probe is directed or to the overall sequence (e.g., cDNA or mRNA) whose expression level is to be detected.
  • the term target nucleic acid can also refer to a nucleic acid that is analyzed by any method, including by sequencing, PCR, microarray, or other method known in the art.
  • the term subject or patient can include human or non-human animals.
  • Preferred subjects are "patients," i.e., living humans that are receiving medical care for a disease or condition. This includes persons with no defined illness who are being investigated for signs of pathology.
  • the term subject or patient can include transplant recipients or donors or healthy subjects.
  • the methods can be particularly useful for human subjects who have undergone a kidney transplant although they can also be used for subjects who have gone other types of transplant (e.g., heart, liver, lung, stem cell, etc. ).
  • the subjects may be mammals or non-mammals.
  • the subject is a human but in some cases, the subject is a non-human mammal, such as a non-human primate (e.g., ape, monkey, chimpanzee), cat , dog, rabbit, goat, horse, cow, pig, rodent, mouse, SCID mouse, rat, guinea pig, or sheep.
  • the subject may be male or female; the subject may be and, in some cases, the subject may be an infant, child, adolescent, teenager or adult.
  • the methods provided herein are used on a subject who has not yet received a transplant, such as a subject who is awaiting a tissue or organ transplant.
  • the subject is a transplant donor.
  • the subject has not received a transplant and is not expected to receive such transplant.
  • the subject may be a subject who is suffering from diseases requiring monitoring of certain organs for potential failure or dysfunction.
  • the subject may be a healthy subject.
  • the subject is a patient or other individual undergoing a treatment regimen, or being evaluated for a treatment regimen (e.g., immunosuppressive therapy). However, in some instances, the subject is not undergoing a treatment regimen.
  • a treatment regimen e.g., immunosuppressive therapy
  • a feature of the graft tolerant phenotype detected or identified by the subject methods is that it is a phenotype which occurs without immunosuppressive therapy, e.g., it is present in a subject that is not receiving immunosuppressive therapy.
  • a transplant recipient may be a recipient of a solid organ or a fragment of a solid organ such as a kidney.
  • the transplant recipient is a kidney transplant or allograft recipient.
  • the transplant recipient may be a recipient of a tissue or cell.
  • the transplanted kidney may be a kidney differentiated in vitro from pluripotent stem cell(s) (e.g., induced pluripotent stem cells or embryonic stem cells).
  • the donor organ, tissue, or cells may be derived from a subject who has certain similarities or compatibilities with the recipient subject.
  • the donor organ, tissue, or cells may be derived from a donor subject who is age-matched, ethnicity-matched, gender-matched, blood-type compatible, or HLA-type compatible with the recipient subject.
  • the subjects suitable for methods of the invention are patients who have undergone an organ transplant within 6 hours, 12 hours, 1 day, 2 days, 3 days, 4 days, 5 days, 10 days, 15 days, 20 days, 25 days, 1 month, 2 months, 3 months, 4 months, 5 months, 7 months, 9 months, 1 1 months, 1 year, 2 years, 4 years, 5 years, 10 years, 15 years, 20 years or longer of prior to receiving a classification obtained by the methods disclosed herein, such as detection of subAR.
  • Diagnosis refers to methods of estimating or determining whether or not a patient is suffering from a given disease or condition or severity of the condition. Diagnosis does not require ability to determine the presence or absence of a particular disease with 100% accuracy, or even that a given course or outcome is more likely to occur than not. Instead, the "diagnosis” refers to an increased probability that a certain disease or condition is present in the subject compared to the probability before the diagnostic test was performed.
  • a prognosis signals an increased probability that a given course or outcome will occur in a patient relative to the probability before the prognostic test.
  • a probe or polynucleotide probe is a nucleic acid capable of binding to a target nucleic acid of complementary sequence through one or more types of chemical bonds, usually through complementary base pairing, usually through hydrogen bond formation, thus forming a duplex structure.
  • the probe binds or hybridizes to a "probe binding site.”
  • a probe can include natural (e.g., A, G, C, U, or T) or modified bases (e.g., 7-deazaguanosine, inosine.).
  • a probe can be an oligonucleotide and may be a single-stranded DNA or RNA. Polynucleotide probes can be synthesized or produced from naturally occurring
  • probes can include, for example, peptide nucleic acids in which the constituent bases are joined by peptide bonds rather than phosphodiester linkages (see, e.g., Nielsen et al., Science 254, 1497-1500 ( 1991 )). Some probes can have leading and/or trailing sequences of
  • a perfectly matched probe has a sequence perfectly complementary to a particular target sequence.
  • the probe is typically perfectly complementary to a portion (subsequence) of a target sequence.
  • the term "mismatch probe” refer to probes whose sequence is deliberately selected not to be perfectly complementary to a particular target sequence.
  • isolated means an object species (e.g. , a nucleic acid sequence described herein or a polypeptide encoded thereby) has been at least partially separated from the components with which it is naturally associated.
  • Differential expression refers to a statistically significant difference in expression levels of a gene between two populations of samples (e.g., samples with and without SCAR). The expression levels can differ for example by at least a factor of 1.5 or 2 between such populations of samples. Differential expression includes genes that are expressed in one population and are not expressed (at least at detectable levels) in the other populations.
  • Unique expression refers to detectable expression in one population and undetectable expression (i.e., insignificantly different from background) in the other population using the same technique (e.g., as in the present example for detection).
  • Control populations for comparison with populations undergoing SCAR are usually referred to as being without SCAR.
  • such a control population also means subjects without acute kidney rejection.
  • Hybridization reactions are preferably performed under stringent conditions in which probes or primers hybridize to their intended target with which they have perfect complementarity and not to or at least to a reduced extent to other targets.
  • An example of stringent hybridization conditions are hybridization in 6xsodium chloride/sodium citrate (SSC) at about 45° C, followed by one or more washes in 0.2xSSC, 0.1 % SDS at 50° C, 55° C, 60° C, and even more or 65° C.
  • Table 4 lists more than 2000 probesets with corresponding genes whose expression changes significantly between kidney transplant patients undergoing SCAR compared with patients not undergoing rejection (TX) and also patients undergoing acute rejection (AR) (3-way prediction).
  • the columns in the table have the following meanings: column 1 is a number assigned to a gene, column 2 is an Affymetrix number indicating a set of probes suitable for measuring expression of the gene, column 3 is a gene name
  • column 4 is a further description of the gene
  • column 5 is a raw uncorrected measure of the statistical significance of change in gene expression between the above patient populations
  • column 6 corresponds to a value of the statistical significance after correction for the false discovery rate (FDR)
  • columns 7-9 respectively show mean expression levels of AR, SCAR, and TX patients.
  • Table 2 similarly provides a subset of 200 preferred genes from Table 4.
  • Table 3 provides similar information for a subset of genes from Table 4 which show differential expression between kidney transplant patients undergoing SCAR with kidney transplant patients not undergoing rejection (TX) (2-way prediction).
  • genes referred to in the above tables are human genes.
  • species variants or homologs of these genes are used in a non-human animal model.
  • Species variants are the genes in different species having greatest sequence identity and similarity in functional properties to one another.
  • Many species variants of the above human genes are listed in the Swiss-Prot database.
  • raw gene expression levels are comparable between different genes in the same sample but not necessarily between different samples.
  • values given for gene expression levels can be normalized so that values for particular genes are comparable within and between the populations being analyzed.
  • the normalization eliminates or at least reduces to acceptable levels any sample to sample differences arising from factors other than SCAR (e.g.
  • the normalization effectively applies a correction factor to the measured expression levels from a given array such that a profile of many expression levels in the array are the same between different patient samples.
  • Software for normalizing overall expression patterns between different samples is both commercially and publically available (e.g., XRAY from Biotique Systems or BRB ArrayTools from the National Cancer Institute). After applying appropriate normalizing factors to the measured expression value of a particular gene in different samples, an average or mean value of the expression level is determined for the samples in a population. The average or mean values between different populations are then compared to determine whether expression level has changed significantly between the populations.
  • the changes in expression level indicated for a given gene represent the relative expression level of that gene in samples from a population of individuals with a defined condition (e.g., transplant patients with SCAR) relative to samples from a control population (kidney transplant patients not undergoing rejection).
  • the population of individuals with a defined condition may be transplant recipients with SCAR identified by acute cellular rejection (AR) on a surveillance protocol biopsy (SCAR-normal creatinine) and the control population is patients (e.g., transplant recipients) with normal protocol surveillance biopsies (TX-normal creatine).
  • this SCAR gene expression profile is compared with a previously validated peripheral blood profile/signature for patients with clinical acute cellular rejection (CAR-elevated creatinine), such as a CAR identified with a "for cause" biopsy.
  • CAR-elevated creatinine clinical acute cellular rejection
  • Subclinical rejection (SCR) including subAR generally refers to histologically defined acute rejection - particularly, histologically defined acute cellular rejection -- characterized by tubule-interstitial mononuclear infiltration identified from a biopsy specimen, but without concurrent functional deterioration (variably defined as a serum creatinine not exceeding 10%, 20% or 25% of baseline values).
  • SCR or subAR may represent the beginning or conclusion of an alloimmune infiltrate diagnosed fortuitously by protocol sampling, and some episodes of clinical rejection may actually represent subAR or SCAR with an alternative cause of functional decline, such as concurrent calcineurin inhibitor (CNI) nephrotoxicity
  • a subAR subject may have normal and stable organ function.
  • a subAR subject typically shows normal and/or stable serum creatinine levels or eGFR.
  • SubAR is usually diagnosed through biopsies that are taken at a fixed time after transplantation (e.g., protocol biopsies or serial monitoring biopsies) which are not driven by clinical indications but rather by standards of care. The biopsies may be analyzed histologically in order to detect the subAR.
  • SubAR may be subclassified by some into acute subAR (subAR) or a milder form called borderline subAR (suspicious for acute rejection) based on the biopsy histology. ).
  • a failure to recognize, diagnose and treat subclinical AR before significant tissue injury has occurred and the transplant shows clinical signs of dysfunction could be a major cause of irreversible organ damage.
  • a failure to recognize a chronic, subclinical immune-mediated organ damage and a failure to make appropriate changes in immunosuppressive therapy to restore a state of effective immunosuppression in that patient could contribute to late organ transplant failure.
  • the methods disclosed herein can reduce or eliminate these and other problems associated with transplant rejection or failure.
  • a normal serum creatinine level and/or a normal estimated glomerular filtration rate may indicate or correlate with healthy transplant (TX) or subclinical rejection (SCAR).
  • TX healthy transplant
  • SCAR subclinical rejection
  • typical reference ranges for serum creatinine are 0.5 to 1 .0 mg/dL for women and 0.7 to 1.2 mg/dL for men, though typical kidney transplant patients have creatinines in the 0.8 to 1 .5 mg/dL range for women and 1 .0 to 1 .9 mg/dL range for men. This may be due to the fact that most kidney transplant patients have a single kidney.
  • the trend of serum creatinine levels over time can be used to evaluate the recipient's organ function.
  • the transplant recipient may show signs of a transplant dysfunction or rejection as indicated by an elevated serum creatinine level and/or a decreased eGFR.
  • a transplant subject with a particular transplant condition may have an increase of a serum creatinine level of at least 0.1 mg/dL, 0.2 mg/dL, 0.3 mg/dL, 0.4 mg/dL, 0.5 mg/dL, 0.6 mg/dL, 0.7 mg/dL 0.8 mg/dL, 0.9 mg/dL, 1 .0 mg/dL, 1.1 mg/dL, 1.2 mg/dL, 1.3 mg/dL, 1 .4 mg/dL, 1 .5 mg/dL, 1 .6 mg/dL, 1.7 mg/dL, 1.8 mg/dL, 1.9 mg/dL, 2.0 mg/dL, 2.1 mg/dL, 2.2 mg/dL, 2.3 mg/dL, 2.4 mg/dL, 2.5 mg/dL, 2.6 mg/dL, 2.7 mg/dL, 2.8 mg/dL, 2.9 mg/dL, 3.0 mg/dL,
  • a transplant subject with a certain transplant condition may have an increase of a serum creatinine level of at least 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, or 100% from baseline.
  • a transplant subject with a certain transplant condition e.g., AR,
  • ADNR,etc. may have an increase of a serum creatinine level of at least 1 -fold, 2-fold, 3- fold, 4-fold, 5-fold, 6-fold, 7-fold, 8-fold, 9-fold, or 10-fold from baseline.
  • the increase in serum creatinine (e.g., any increase in the concentration of serum creatinine described herein) may occur over about .25 days, 0.5 days, 0.75 days, 1 day, 1 .25 days, 1 .5 days, 1 .75 days, 2.0 days, 3.0 days, 4.0 days, 5.0 days, 6.0 days, 7.0 days, 8.0 days, 9.0 days, 10.0 days, 15 days, 30 days, 1 month, 2 months, 3 months, 4 months, 5 months, or 6 months, or more.
  • a transplant subject with a particular transplant condition may have a decrease of a eGFR of at least 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, or 100% from baseline.
  • the decrease in eGFR may occur over .25 days, 0.5 days, 0.75 days, 1 day, 1.25 days, 1 .5 days, 1.75 days, 2.0 days, 3.0 days, 4.0 days, 5.0 days, 6.0 days, 7.0 days, 8.0 days, 9.0 days, 10.0 days, 15 days, 30 days, 1 month, 2 months, 3 months, 4 months, 5 months, or 6 months, or more.
  • diagnosing, predicting, or monitoring the status or outcome of a transplant or condition comprises determining transplant recipient-specific baselines and/or thresholds.
  • the methods are particularly useful on human subjects who have undergone a kidney transplant although can also be used on subjects who have undergone other types of transplant (e.g., heart, liver, lungs, stem cell) or on non-humans who have undergone kidney or other transplant.
  • the methods can be employed to distinguish transplant patients who (1 ) have or are at risk of having acute rejection (AR), (2) have or are at risk of having SCAR, and (3) have normal functional transplant (TX).
  • the methods are more practically employed to distinguish patients who either are either transplant excellent (TX) or have existing SCAR (or risk of developing SCAR). This is because patients with acute rejections can usually be easily diagnosed via
  • the methods of the invention can be used in patients who have normal and stable creatinine levels to diagnose or prognose hidden SCAR without depending on invasive biopsies.
  • the serum creatinine levels of the transplant recipient are stable over at least 10 days, 20 days, 30 days, 40 days, 50 days, 60 days, 90 days, 100 days, 200 days, 300 days, 400 days or longer.
  • the transplant recipient has a serum creatinine level of less than 0.2 mg/dL, less than 0.3 mg/dL, less than 0.4 mg/dL, less than 0.5 mg/dL, less than 0.6 mg/dL, less than 0.7 mg/dL less than 0.8 mg/dL, less than 0.9 mg/dL, less than 1 .0 mg/dL, less than 1 .1 mg/dL, less than 1.2 mg/dL, less than 1.3 mg/dL, 1 .4 mg/dL, less than 1 .5 mg/dL, less than 1 .6 mg/dL, less than 1 .7 mg/dL, less than 1 .8 mg/dL, less than 1 .9 mg/dL, less than 2.0 mg/dL, less than 2.1 mg/dL, less than 2.2 mg/dL, less than 2.3 mg/dL, less than 2.4 mg/dL, less than 2.5 mg/dL, less than 2.6 mg/dL, less than
  • Acute rejection (AR) or clinical acute rejection may occur when transplanted tissue is rejected by the recipient's immune system, which damages or destroys the transplanted tissue unless immunosuppression is achieved.
  • T-cells, B-cells and other immune cells as well as possibly antibodies of the recipient may cause the graft cells to lyse or produce cytokines that recruit other inflammatory cells, eventually causing necrosis of allograft tissue.
  • AR may be diagnosed by a biopsy of the transplanted organ. In the case of kidney transplant recipients, AR may be associated with an increase in serum creatinine levels.
  • the treatment of AR may include using immunosuppressive agents, corticosteroids, polyclonal and monoclonal antibodies, engineered and naturally occurring biological molecules,and antiproliferatives. AR more frequently occurs in the first three to 12 months after transplantation but there is a continued risk and incidence of AR for the first five years post transplant and whenever a patient's immunosuppression becomes inadequate for any reason for the life of the transplant.
  • the methods herein may also be used to distinguish between a kidney transplant patient with subAR and a normally functioning kidney transplant.
  • a kidney transplant patient with subAR typically, when the patient does not exhibit symptoms or test results of organ dysfunction or rejection, the transplant is considered a normal functioning transplant (TX: Transplant excellent).
  • TX Transplant excellent
  • An unhealthy transplant recipient may exhibit signs of organ dysfunction and/or rejection (e.g., an increasing serum creatinine
  • gene expression levels in the patients can be measured, for example, within, one month, three months, six months, one year, two years, five years or ten years after a kidney transplant.
  • gene expression levels are determined at regular intervals, e.g., every 3 months, 6 months or every year posttransplant, either indefinitely, or until evidence of SCAR is observed, in which case the frequency of monitoring is sometimes increased.
  • baseline values of expression levels are determined in a subject before a kidney transplant in combination with determining expression levels at one or more time points thereafter. Similar methods can be practiced in non-human species, in which cases, the expression levels measured are the species equivalent of the human genes referenced above.
  • the preferred sample type for analysis is a blood sample, which refers to whole blood or fractions thereof, such as plasma, or lymphocytes.
  • Other samples that can be analyzed include urine, feces, saliva, and a kidney biopsy.
  • the samples are typically isolated from a subject, particularly as a peripheral blood sample, and not returned to the subject.
  • the analytes of interests in the samples can be analyzed with or without further processing of the sample, such as purification and amplification. Samples not requiring biopsy to obtain, particularly peripheral blood, are preferred.
  • a sample may be any material containing tissues, cells, nucleic acids, genes, gene fragments, expression products, polypeptides, exosomes, gene expression products, or gene expression product fragments of a subject to be tested.
  • the sample is from a single patient.
  • the method comprises analyzing multiple samples at once, e.g., via massively parallel sequencing.
  • the sample is preferably blood.
  • the sample comprises whole blood, plasma, peripheral blood lymphocytes (PBLs), peripheral blood mononuclear cells (PBMCs), serum, T cells, B Cells, CD3 cells, CD8 cells, CD4 cells, or other immune cells.
  • PBLs peripheral blood lymphocytes
  • PBMCs peripheral blood mononuclear cells
  • the methods, kits, and systems disclosed herein may comprise specifically detecting, profiling, or quantitating molecules (e.g., nucleic acids, DNA, RNA, polypeptides, etc.) that are within the biological samples.
  • genomic expression products including RNA, or polypeptides, may be isolated from the biological samples.
  • nucleic acids, DNA, RNA, polypeptides may be isolated from a cell-free source.
  • nucleic acids, DNA, RNA, polypeptides may be isolated from cells derived from the transplant recipient.
  • the sample may be obtained using any method known to the art that can provide a sample suitable for the analytical methods described herein.
  • the sample may be obtained by a non-invasive method such as a throat swab, buccal swab, bronchial lavage, urine collection, scraping of the skin or cervix, swabbing of the cheek, saliva collection, feces collection, menses collection, or semen collection.
  • the sample may be obtained by a minimally-invasive method such as a blood draw.
  • the sample may be obtained by venipuncture.
  • the sample is obtained by an invasive procedure including but not limited to: biopsy, alveolar or pulmonary lavage, or needle aspiration.
  • the method of biopsy may include surgical biopsy, incisional biopsy, excisional biopsy, punch biopsy, shave biopsy, or skin biopsy.
  • the sample may be formalin fixed sections.
  • the method of needle aspiration may further include fine needle aspiration, core needle biopsy, vacuum assisted biopsy, or large core biopsy.
  • multiple samples may be obtained by the methods herein to ensure a sufficient amount of biological material.
  • the sample is not obtained by biopsy.
  • the sample is not a kidney biopsy.
  • the profiles can contain genes selected from at least one of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, and 18, for example, from Table 2.
  • the genes in the profiles can be selected from at least one of Tables 2, 3, 4, 7, 8, 1 1, 12, 14, 15, 17, and 18, for example, from Table 3.
  • Expression profiles are preferably measured at the nucleic acid level, meaning that levels of mRNA or nucleic acid derived therefrom (e.g., cDNA or cRNA).
  • An expression profile refers to the expression levels of a plurality of genes in a sample.
  • a nucleic acid derived from mRNA means a nucleic acid synthesized using mRNA as a template. Methods of isolation and amplification of mRNA are well known in the art, e.g., as described in WO 97/10365, WO 97/27317, Chapter 3 of Laboratory Techniques in Biochemistry and Molecular Biology: Hybridization With Nucleic Acid Probes, Part 1. Theory and Nucleic Acid Preparation, (P.
  • mRNA or a nucleic acid therefrom is amplified, the amplification is performed under conditions that approximately preserve the relative proportions of mRNA in the original samples, such that the levels of the amplified nucleic acids can be used to establish phenotypic associations representative of the mRNAs.
  • a variety of approaches are available for determining mRNA levels including probe arrays and quantitative PCR.
  • a number of distinct array formats are available. Some arrays, such as an Affymetrix HG-U 133 PM microarray or other Affymetrix GeneChip® array, have different probes occupying discrete known areas of a contiguous support.
  • Exemplary microarrays include but are not limited to the Affymetrix Human Genome U 133 Plus 2.0 GeneChip or the HT HG-U 133+ PM Array Plate.
  • arrays such as arrays from Illumina, have different probes attached to different particles or beads.
  • the identity of which probe is attached to which particle or beads is usually determinable from an encoding system.
  • the probes can be oligonucleotides.
  • typically several match probes are included with perfect complementarity to a given target mRNA together, optionally together with mismatch probes differing from the match probes are a known number of oligonucleotides (Lockhart, et al., Nature Biotechnology 14: 1675-1680 ( 1996); and Lipschutz, et al., Nature Genetics Supplement 21 : 20-24, 1999).
  • arrays including full length cDNA sequences with perfect or near perfect complementarity to a particular cDNA (Schena et al. (Science 270:467-470 (1995); and DeRisi et al. (Nature Genetics 14:457-460 (1996)).
  • Such arrays can also include various control probes, such as a probe complementarity with a house keeping gene likely to be expressed in most samples.
  • an array contains one or more probes either perfectly complementary to a particular target mRNA or sufficiently complementarity to the target mRNA to distinguish it from other mRNAs in the sample, and the presence of such a target mRNA can be determined from the hybridization signal of such probes, optionally by comparison with mismatch or other control probes included in the array.
  • the target bears a fluorescent label, in which case hybridization intensity can be determined by, for example, a scanning confocal microscope in photon counting mode. Appropriate scanning devices are described by e.g., U.S. 5,578,832, and U.S. 5,63 1 ,734. The intensity of labeling of probes hybridizing to a particular mRNA or its amplification product provides a raw measure of expression level.
  • expression levels are determined by so-called "real time amplification” methods also known as quantitative PCR or Taqman (see, e.g., U.S. Pat Nos. 5,210,01 5 to Gelfand, 5,538,848 to Livak, et al., and 5,863,736 to Haaland, as well as Heid, C.A., et al., Genome Research, 6:986-994 (1996); Gibson, U.E.M, et al., Genome Research 6:995- 1001 (1996); Holland, P. M., et al., Proc. Natl. Acad. Sci.
  • the basis for this method of monitoring the formation of amplification product is to measure continuously PCR product accumulation using a dual-labeled fluorogenic oligonucleotide probe.
  • the probe used in such assays is typically a short (ca. 20-25 bases) polynucleotide that is labeled with two different fluorescent dyes.
  • the 5' terminus of the probe is typically attached to a reporter dye and the 3' terminus is attached to a quenching dye
  • the probe is designed to have at least substantial sequence complementarity with a site on the target mRNA or nucleic acid derived from.
  • Upstream and downstream PCR primers that bind to flanking regions of the locus are also added to the reaction mixture.
  • the probe When the probe is intact, energy transfer between the two fluorophors occurs and the quencher quenches emission from the reporter.
  • the probe is cleaved by the 5' nuclease activity of a nucleic acid polymerase such as Taq polymerase, thereby releasing the reporter from the polynucleotide-quencher and resulting in an increase of reporter emission intensity which can be measured by an appropriate detector.
  • the recorded values can then be used to calculate the increase in normalized reporter emission intensity on a continuous basis and ultimately quantify the amount of the mRNA being amplified.
  • mRNA levels can also be measured without amplification by hybridization to a probe, for example, using a branched nucleic acid probe, such as a QuantiGene® Reagent System from Panomics.
  • the expression level of the gene products is determined by sequencing, such as by R A sequencing or by DNA sequencing (e.g., of cDNA generated from reverse-transcribing RNA (e.g., mRNA) from a sample). Sequencing may be performed by any available method or technique.
  • Sequencing methods may include: Next Generation sequencing, high-throughput sequencing, pyrosequencing, classic Sangar sequencing methods, sequencing-by-ligation, sequencing by synthesis, sequencing-by-hybridization, RNA-Seq (Illumina), Digital Gene Expression (Helicos), next generation sequencing, single molecule sequencing by synthesis (SMSS) (Helicos), Ion Torrent Sequencing Machine (Life Technologies/Thermo-Fisher), massively-parallel sequencing, clonal single molecule Array (Solexa), shotgun sequencing, Maxim-Gilbert sequencing, primer walking, and any other sequencing methods known in the art.
  • Measuring gene expression levels may comprise reverse transcribing RNA (e.g., mRNA) within a sample in order to produce cDNA.
  • RNA e.g., mRNA
  • the cDNA may then be measured using any of the methods described herein (e.g., PCR, digital PCR, qPCR, microarray, SAGE, blotting, sequencing, etc.).
  • expression levels of genes can be determined at the protein level, meaning that levels of proteins encoded by the genes discussed above are measured.
  • Several methods and devices are well known for determining levels of proteins including immunoassays such as described in e.g., U.S. Patents 6, 143,576; 6, 1 13,855; 6,019,944; 5,985,579; 5,947, 124; 5,939,272; 5,922,615; 5,885,527; 5,851 ,776; 5,824,799; 5,679,526; 5,525,524; and 5,480,792.
  • These assays include various sandwich, competitive, or non-competitive assay formats, to generate a signal that is related to the presence or amount of an protein analyte of interest.
  • Any suitable immunoassay may be utilized, for example, lateral flow, enzyme-linked immunoassays (ELISA), radioimmunoassays (RIAs), competitive binding assays, and the like.
  • ELISA enzyme-linked immunoassays
  • RIAs radioimmunoassays
  • Numerous formats for antibody arrays have been described proposed employing antibodies. Such arrays typically include different antibodies having specificity for different proteins intended to be detected. For example, usually at least one hundred different antibodies are used to detect one hundred different protein targets, each antibody being specific for one target. Other ligands having specificity for a particular protein target can also be used, such as the synthetic antibodies disclosed in WO/2008/048970.
  • US Patent No. 5,922,615 describes a device that utilizes multiple discrete zones of immobilized antibodies on membranes to detect multiple target antigens in an array.
  • US Patent Nos. 5,458,852, 6,019,944, US 6, 143,576 Microtiter plates or automation can be used to facilitate detection of large numbers of different proteins. Protein levels can also be determined by mass spectrometry as described in the examples.
  • genes for determination of expression levels depends on the particular application. In general, the genes are selected from one of the tables indicated above as appropriate for the application. In some methods, expression levels of at least 2, 3, 4, 5, 10, 20, 25, 50, 100, 150, 250 (e.g. 100-250) genes shown in any of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, or 1 8 are determined. In some methods, expression levels of 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10, 1 1 , 12, 1 3, 14, 15, 16, 17, 18, 19, 20, 50, 100, 200, 300, 400, 500, 1000 or more genes found in Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 1 , 17, or 18 are determined. In some methods, genes are selected such that genes from several different pathways are represented.
  • genes within a pathway tend to be expressed in a coordinated expression whereas genes from different pathways tend to be expressed more independently.
  • changes in expression based on the aggregate changes of genes from different pathways can have greater statistical significance than aggregate changes of genes within a pathway.
  • expression levels of the top 5, top 10, top 15, top 20, top 25, top 30, top 35, top 40, top 45, top 50, top 55, top 60, top 65, top 70, top 75, top 80, top 85, top 90, top 95, top 100, top 150, top 200, top 250 or top 300 genes listed in Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, or 18 are determined.
  • Expression levels of the present genes and/or proteins can be combined with or without determination of expression levels of any other genes or proteins of interest (e.g., genes or proteins associated with rejection of kidneys or other organs in WO 2007/104537, WO 2009/060035), Anglicheau et al., PNAS 106, 5330-5335 (2009)) and references, 16, 20, 21 , 22, 23, 25, 26, 37 and 39.
  • genes or proteins of interest e.g., genes or proteins associated with rejection of kidneys or other organs in WO 2007/104537, WO 2009/060035
  • Anglicheau et al. e.g., genes or proteins associated with rejection of kidneys or other organs in WO 2007/104537, WO 2009/060035
  • Anglicheau et al. PNAS 106, 5330-5335 (2009)
  • references 16, 20, 21 , 22, 23, 25, 26, 37 and 39.
  • the genes in the expression profiles to be measured do not include at least one or all of the genes encoding urinary granzyme A, granzyme B, glyceraldehyde 3-phospate dehydrogenase (GAPDH), perforin, Fas ligand, CXCL9, CXCL10, and other proteins involved in patients' cytolytic attack against the transplant.
  • GPDH glyceraldehyde 3-phospate dehydrogenase
  • the present methods can (but need not) be practiced by detection expression levels of a relatively small number of genes or proteins compared with the whole genome level expression analysis described in the Examples.
  • the total number of genes whose expression levels are determined is less than 5000, 1000, 500, 200, 100, 50, 25, 10, 5 or 3.
  • the total number of genes whose expression level is determined is 100-1500, 100-250, 500-1500 or 750- 1250.
  • the total number of proteins whose expression levels are determined is less than 5000, 1000, 500, 200, 100, 50, 25, 10, 5 or 3.
  • the total number of proteins whose expression level is determined is 100- 1 00, 100-250, 500- 1500 or 750- 1250.
  • the array includes probes or probes sets for less than 5000, 1000, 500, 200, 100, 50, 25, 10, 5 or 3 genes.
  • an Affymetrix GeneChip® expression monitoring array contains a set of about 20-50 oligonucleotide probes (half match and half-mismatch) for monitoring each gene of interest.
  • Such an array design would include less than 5000, 1000, 500, 200, 100, 50, 25, 10, 5 or 3 such probes sets for detecting less than 5000, 1000, 500, 200, 100, 50, 25, 10, 5 or 3 genes.
  • an alternative array including one cDNA for each gene whose expression level is to be detected would contain less than 5000, 1000, 500, 200, 100, 50, 25, 10, 5 or 3 such cDNAs for analyzing less than 5000, 1000, 500, 200, 100, 50, 25, 10, 5 or 3 genes.
  • an array containing a different antibody for each protein to be detected would containing less than 5000, 1000, 500, 200, 100, 50, 25, 10, 5 or 3 different antibodies for analyzing less than 5000, 1000, 500, 200, 100, 50, 25, 10, 5 or 3 gene products.
  • the methods involve obtaining or analyzing a biopsy sample (e.g., kidney biopsy).
  • the biopsy sample may be used for different purposes including to develop an expression profile signature.
  • an analysis described herein may be performed on a biopsy obtained from a transplant recipient in order to predict, monitor, or detect SCAR in the transplant recipient.
  • the biopsies may be processed included by placing the samples in a vessel (e.g., tube, PAX tube, vial, microfuge tube, etc.) and storing them at a specific location such as a vessel
  • a vessel e.g., tube, PAX tube, vial, microfuge tube, etc.
  • biorepository The samples may also be processed by treatment with a specific agent, such as an agent that prevents nucleic acid degradation or deterioration, particularly an agent that protects RNA (e.g., RNALater) or DNA.
  • a specific agent such as an agent that prevents nucleic acid degradation or deterioration, particularly an agent that protects RNA (e.g., RNALater) or DNA.
  • biopsies subjected to histologic analysis including staining (e.g., hematoxylin and eosin (H&E) stain) probing (e.g., a probe attached to a dye, a probe attached to a fluorescent label).
  • the staining e.g., H&E
  • a histologic diagnosis is reconciled with laboratory data and clinical courses by one or more clinicians
  • Analysis of expression levels initially provides a measurement of the expression level of each of several individual genes.
  • the expression level can be absolute in terms of a concentration of an expression product, or relative in terms of a relative concentration of an expression product of interest to another expression product in the sample.
  • relative expression levels of genes can be expressed with respect to the expression level of a house-keeping gene in the sample.
  • Relative expression levels can also be determined by simultaneously analyzing differentially labeled samples hybridized to the same array.
  • Expression levels can also be expressed in arbitrary units, for example, related to signal intensity.
  • the individual expression levels can be converted into values or other designations providing an indication of presence or risk of SCAR by comparison with one or more reference points.
  • genes in Table 2 and/or one or more of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, or 18 are used for such analysis.
  • the reference points can include a measure of an average or mean expression level of a gene in subjects having had a kidney transplant without SCAR, an average or mean value of expression levels in subjects having had a kidney transplant with SCAR, and/or an average/mean value of expression levels in subjects having had a kidney transplant with acute rejection.
  • the reference points can also include a scale of values found in kidney transplant patients including patients having and not having SCAR.
  • the reference points can also or alternatively include a reference value in the subject before kidney transplant, or a reference value in a population of patients who have not undergone kidney transplant. Such reference points can be expressed in terms of absolute or relative concentrations of gene products as for measured values in a sample.
  • the measured level For comparison between a measured expression level and reference level(s), the measured level sometimes needs to be normalized for comparison with the reference level(s) or vice versa.
  • the normalization serves to eliminate or at least minimize changes in expression level unrelated to SCAR (e.g., from differences in overall health of the patient or sample preparation). Normalization can be performed by determining what factor is needed to equalize a profile of expression levels measured from different genes in a sample with expression levels of these genes in a set of reference samples from which the reference levels were determined. Commercial software is available for performing such normalizations between different sets of expression levels.
  • Comparison of the measured expression level of a gene with one or more of the above reference points provides a value (i.e., numerical) or other designation (e.g., symbol or word(s)) of presence or susceptibility to SCAR.
  • a binary system is used; that is a measured expression level of a gene is assigned a value or other designation indicating presence or susceptibility to SCAR or lack thereof without regard to degree.
  • the expression level can be assigned a value of 1 to indicate presence or susceptibility to SCAR and - 1 to indicate absence or lack of susceptibility to SCAR. Such assignment can be based on whether the measured expression level is closer to an average or mean level in kidney transplant patients having or not having SCAR.
  • a ternary system in which an expression level is assigned a value or other designation indicating presence or susceptibility to SCAR or lack thereof or that the expression level is uninformative. Such assignment can be based on whether the expression level is closer to the average or mean level in kidney transplant patient undergoing SCAR, closer to an average or mean level in kidney transplant patients lacking SCAR or intermediate between such levels. For example, the expression level can be assigned a value of +1 , - 1 or 0 depending on whether it is closer to the average or mean level in patients undergoing SCAR, is closer to the average or mean level in patients not undergoing SCAR or is intermediate.
  • a particular expression level is assigned a value on a scale, where the upper level is a measure of the highest expression level found in kidney transplant patients and the lowest level of the scale is a measure of the lowest expression level found in kidney transplant patients at a defined time point at which patients may be susceptible to SCAR (e.g., one year post transplant).
  • SCAR SCAR
  • a scale is normalized scale (e.g., from 0- 1 ) such that the same scale can be used for different genes.
  • the value of a measured expression level on such a scale is indicated as being positive or negative depending on whether the upper level of the scale associates with presence or susceptibility to SCAR or lack thereof. It does not matter whether a positive or negative sign is used for SCAR or lack thereof as long as the usage is consistent for different genes.
  • Values or other designation can also be assigned based on a change in expression level of a gene relative to a previous measurement of the expression level of gene in the same patient.
  • expression level of a gene can be measured at the protein or nucleic acid level.
  • Such a change can be characterized as being toward, away from or neutral with respect to average or mean expression levels of the gene in kidney transplant patients undergoing or not undergoing SCAR.
  • a gene whose expression level changes toward an average or mean expression level in kidney transplant patients undergoing SCAR can be assigned a value of 1 and a gene whose express level changes way from an average or mean expression level in kidney transplant patients undergoing SCAR and toward an average or mean expression level in kidney transplant patients not undergoing SCAR can be assigned a value -1.
  • more sophisticated systems of assigning values are possible based on the magnitude of changes in expression of a gene in a patient.
  • the values or designations may be combined to provide an aggregate value for all of the genes in the signature being analyzed. If each gene is assigned a score of + 1 if its expression level indicates presence or susceptibility to subAR (or SCAR) and - 1 if its expression level indicates absence or lack of susceptibility to subAR and optionally zero if uninformative, the different values can be combined by addition. The same approach can be used if each gene is assigned a value on the same normalized scale and assigned as being positive or negative depending whether the upper point of the scale is associate with presence or susceptibility to subAR or lack thereof.
  • the signal intensity for each gene is obtained and used to compute a score.
  • the score may be obtained by adding up the values for the upregulated genes to obtain an upregulated gene value and adding up the values of the downregulated genes to obtain a downregulated gene value; the downregulated gene value may be compared with the upregulated value (e.g., by calculating a ratio) to determine the score.
  • Other methods of combining values for individual markers of disease into a composite value that can be used as a single marker are described in US20040126767 and WO/2004/059293.
  • the score may be used to evaluate severity of a transplant condition, such as by comparing the score with a score normally associated with subAR. In some cases, the score may be used to monitor a subject transplant recipient over time.
  • scores at a plurality of timepoints maybe compared in order to assess the relative condition of the subject. For example, if the subject's score rises over time, that may indicate that the subject has subAR and that his or her condition is worsening over time.
  • the data pertaining to the sample may be compared to data pertaining to one or more control samples, which may be samples from the same patient at different times.
  • the one or more control samples may comprise one or more samples from healthy subjects, unhealthy subjects, or a combination thereof.
  • the one or more control samples may comprise one or more samples from healthy subjects, subjects suffering from transplant dysfunction with no rejection, subjects suffering from transplant rejection, or a combination thereof.
  • the healthy subjects may be subjects with normal transplant function.
  • the data pertaining to the sample may be sequentially compared to two or more classes of samples.
  • the data pertaining to the sample may be sequentially compared to three or more classes of samples.
  • the classes of samples may comprise control samples classified as being from subjects with normal transplant function, control samples classified as being from subjects suffering from transplant dysfunction with no rejection, control samples classified as being from subjects suffering from transplant rejection, or a combination thereof.
  • the methods include using a trained classifier or algorithm to analyze sample data, particularly to detect subAR.
  • the expression levels from sample are used to develop or train an algorithm or classifier provided herein.
  • gene expression levels are measured in a sample from a transplant recipient (or a healthy or transplant excellent control) and a classifier or algorithm (e.g., trained algorithm) is applied to the resulting data in order to detect, predict, monitor, or estimate the risk of a transplant condition (e.g., subAR).
  • Training of multi-dimensional classifiers may be performed using numerous samples. For example, training of the multi-dimensional classifier may be performed using at least about 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 1 10, 120, 130, 140, 1 50, 160, 170, 1 80, 190, 200 or more samples. In some cases, training of the multidimensional classifier may be performed using at least about 200, 210, 220, 230, 240, 250, 260, 270, 280, 290, 300, 350, 400, 450, 500 or more samples.
  • training of the multi-dimensional classifier may be performed using at least about 525, 550, 600, 650, 700, 750, 800, 850, 900, 950, 1000, 1 100, 1200, 1300, 1400, 1500, 1600, 1700, 1 800, 2000 or more samples.
  • the classifier set may comprise one or more genes, particularly genes from Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, or 18. In some cases, the classifier set may comprise 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10, 1 1 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 50, 100, 150, 200, 300 or more genes from Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, or 18. Disclosed herein is the use of a classification system comprises one or more classifiers. In some instances, the classifier is a 2-, 3-, 4-, 5-, 6-, 7-, 8-, 9-, or 10-way classifier.
  • the classifier is a 15-, 20-, 25-, 30-, 35-, 40-, 45-, 50-, 55-, 60-, 65-, 70-, 75-, 80-, 85-, 90-, 95-, or 100-way classifier. In some preferred embodiments, the classifier is a three-way classifier. In some embodiments, the classifier is a four-way classifier.
  • a two-way classifier may classify a sample from a subject into one of two classes.
  • a two-way classifier may classify a sample from an organ transplant recipient into one of two classes comprising subAR and normal transplant function (TX).
  • TX normal transplant function
  • a three-way classifier may classify a sample from a subject into one of three classes.
  • a three-way classifier may classify a sample from an organ transplant recipient into one of three classes comprising AR, subAR, and TX
  • the classifier may work by applying two or more classifiers sequentially.
  • the first classifier may classify AR+subAR and TX, which results in a set of samples that are classified either as ( 1 ) TX or (2) AR or subAR.
  • a second classifier capable of distinguishing between AR and subAR is applied to the samples classified as having AR or subAR in order to detect the subAR samples.
  • Classifiers and/or classifier probe sets may be used to either rule-in or rule-out a sample as healthy.
  • a classifier may be used to classify a sample as being from a healthy subject.
  • a classifier may be used to classify a sample as being from an unhealthy subject.
  • classifiers may be used to either rule-in or rule-out a sample as transplant rejection.
  • a classifier may be used to classify a sample as being from a subject suffering from a transplant rejection.
  • a classifier may be used to classify a sample as being from a subject that is not suffering from a transplant rejection.
  • Classifiers may be used to either rule-in or rule-out a sample as transplant dysfunction with no rejection.
  • a classifier may be used to classify a sample as being from a subject with subAR.
  • a classifier may be used to classify a sample as not being from a subject suffering from transplant dysfunction with no rejection.
  • the samples may be classified simultaneously. In some cases, the samples may be classified sequentially.
  • the two or more samples may be classified at two or more time points.
  • the samples may be obtained at 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10, 1 1 , 12, 13, 14, 15, 16, 17, 1 8, 19, 20, 100 or more time points.
  • the two or more time points may be 1 day, 10 days, 30 days, 60 days, 100 days, 200 days, 1 year, 2 years or more apart.
  • Methods of simultaneous classifier-based analysis of one or more samples may comprise applying one or more algorithm to data from one or more samples to
  • the lists comprise one or more samples classified as being from healthy subjects (e.g. subjects with a normal functioning transplant (TX)), unhealthy subjects, subjects suffering from transplant rejection, subjects suffering from transplant dysfunction, subjects with AR, or subjects withsubAR.
  • healthy subjects e.g. subjects with a normal functioning transplant (TX)
  • unhealthy subjects e.g. subjects suffering from transplant rejection, subjects suffering from transplant dysfunction, subjects with AR, or subjects withsubAR.
  • the methods, kits, and systems disclosed herein may comprise one or more algorithms or uses thereof.
  • the one or more algorithms may be used to classify one or more samples from one or more subjects.
  • the one or more algorithms may be applied to data from one or more samples.
  • the data may comprise gene expression data.
  • the data may comprise sequencing data.
  • the data may comprise array hybridization data.
  • the methods disclosed herein may comprise assigning a classification to one or more samples from one or more subjects. Assigning the classification to the sample may comprise applying an algorithm to the expression level. In some cases, the gene expression levels are inputted to a trained algorithm for classifying the sample as one of the conditions comprising subAR, AR, TX, subAR+AR, or other condition.
  • the algorithm may provide a record of its output including a classification of a sample and/or a confidence level.
  • the output of the algorithm can be the possibility of the subject of having a condition, such as subAR.
  • the output of the algorithm can be the risk of the subject of having a condition, such as AR .
  • the output of the algorithm can be the possibility of the subject of developing into a condition in the future, such as AR.
  • the algorithm may be a trained algorithm.
  • the algorithm may comprise a linear classifier.
  • the linear classifier may comprise one or more linear discriminant analysis, Fisher's linear discriminant, Na ' ive Bayes classifier, Logistic regression, Perceptron, Support vector machine, or a combination thereof.
  • the linear classifier may be a Support vector machine (SVM) algorithm.
  • the algorithm may comprise one or more linear discriminant analysis (LDA), Basic perceptron, Elastic Net, logistic regression, (Kernel) Support Vector Machines (SVM), Diagonal Linear Discriminant Analysis (DLDA), Golub Classifier, Parzen-based, (kernel) Fisher Discriminant Classifier, k-nearest neighbor, Iterative RELIEF, Classification Tree, Maximum Likelihood Classifier, Random Forest, Nearest Centroid, Prediction Analysis of Microarrays (PAM), k-medians clustering, Fuzzy C-Means Clustering, Gaussian mixture models, or a combination thereof.
  • LDA linear discriminant analysis
  • SVM Support Vector Machines
  • DLDA Diagonal Linear Discriminant Analysis
  • Golub Classifier Parzen-based
  • (kernel) Fisher Discriminant Classifier k-nearest neighbor
  • Iterative RELIEF Classification Tree
  • Maximum Likelihood Classifier Random Forest
  • Nearest Centroid Prediction Analysis of Microarrays (PAM
  • the algorithm may comprise a Nearest Centroid algorithm.
  • the algorithm may comprise a Random Forest algorithm.
  • the algorithm may comprise a Prediction Analysis of Microarrays (PAM) algorithm.
  • the methods disclosed herein may comprise use of one or more classifier equations.
  • Classifying the sample may comprise a classifier equation.
  • the classifier equation may be Equation 1 :
  • [00112] k is a number of possible classes
  • ⁇ k ma y be the discriminant score for class k
  • X represents a vector of expression levels for all p genes to be used for classification drawn from the sample to be classified
  • k may be a shrunken centroid calculated from a training data and a shrinkage factor
  • J 'tk may be a component of k corresponding to gene % ;
  • s i is a pooled within-class standard deviation for gene 3 ⁇ 4 in the training data
  • [00120] represents a prior probability of a sample belonging to class k.
  • Assigning the classification may comprise calculating a class probability.
  • Calculating the class probability ⁇ ⁇ X ' may be calculated by Equation 2: prise a classification rule.
  • the above described methods can provide a composite or aggregate value or other designation for a patient, which indicates whether the patient either has or is at enhanced risk of SCAR (or AR), or conversely does not have or is at reduced risk of SCAR (or AR).
  • Risk is a relative term in which risk of one patient is compared with risk of other patients either qualitatively or quantitatively.
  • the value of one patient can be compared with a scale of values for a population of patients having undergone kidney transplant to determine whether the patient's risk relative to that of other patients.
  • diagnosis is the determination of the present condition of a patient (e.g., presence or absence of SCAR) and prognosis is developing future course of the patient (e.g., risk of developing SCAR in the future or likelihood of improvement in response to treatment); however, the analyses contemplated by these terms may overlap or even be the same.
  • the present methods alone do not necessarily distinguish between presence and enhanced risk of SCAR. However, these possibilities can be distinguished by additional testing.
  • the methods provided herein can help determine whether the patient either has or is at enhanced risk of subAR/SCAR (or AR) with a high degree of accuracy, sensitivity, and/or specificity.
  • the predictive accuracy e.g., for predicting subAR/SCAR, for detecting subAR/SCAR, or for distinguishing SCAR versus TX, SCAR versus AR, AR versus TX, and/or any combination thereof
  • the predictive accuracy is greater than 75%, 85%, 90%, 91 %, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 98.5%, 99.0%, 99.1%, 99.2%, 99.3%, 99.4%, 99.5%, 99.6%, 99.7%, 99.8%, 99.9%, 99.95%, or 99.99%.
  • the predictive accuracy is 100%.
  • the sensitivity e.g., for detecting or predicting SCAR or for distinguishing SCAR versus TX, SCAR versus AR, AR versus TX, and/or any combination thereof
  • the sensitivity is greater than 75%, 85%, 90%, 91 %, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 98.5%, 99.0%, 99.1 %, 99.2%, 99.3%, 99.4%, 99.5%, 99.6%, 99.7%, 99.8%, 99.9%, 99.95%), or 99.99%o.
  • the sensitivity is 100%.
  • the specificity (e.g., for detecting or predicting SCAR or for distinguishing SCAR versus TX, SCAR versus AR, AR versus TX, and/or any combination thereof) is greater than 75%, 85%, 90%, 91 %, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 98.5%, 99.0%, 99.1 %, 99.2%, 99.3%, 99.4%, 99.5%, 99.6%, 99.7%, 99.8%, 99.9%, 99.95%, or 99.99%. In some cases, the specificity is 100%.
  • the positive predictive value (e.g., for detecting or predicting SCAR or for distinguishing SCAR versus TX, SCAR versus AR, AR versus TX, and/or any combination thereof) of the method is greater than 75%, 85%, 90%, 91 >, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 98.5%, 99.0%, 99.1 %, 99.2%, 99.3%, 99.4%, 99.5%, 99.6%, 99.7%, 99.8%, 99.9%, 99.95%, or 99.99%. In some cases the positive predictive value is 100%.
  • the AUC after thresholding in any of the methods provided herein may be greater than 0.9, 0.91 , 0.92, 0.93, 0.94, 0.95. 0.96, 0.97, 0.98, 0.99, 0.995, or 0.999.
  • the method may predict or determine whether a transplant recipient does not have or is at reduced risk of SCAR (or AR).
  • the negative predictive value (e.g., for predicting or determining that transplant recipient does not have SCAR or is at reduced risk for SCAR or for distinguishing SCAR versus TX, SCAR versus AR, AR versus TX, and/or any combination thereof) may be greater than 85%, 90%, 91 %, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 98.5%, 99.0%, 99.1 %, 99.2%, 99.3%, 99.4%, 99.5%, 99.6%, 99.7%, 99.8%, 99.9%, 99.95%, or 99.99%. In some cases, the negative predictive value is 100%.
  • the methods, compositions, systems and kits described herein provide information to a medical practitioner that can be useful in making a therapeutic decision.
  • Therapeutic decisions may include decisions to: continue with a particular therapy, modify a particular therapy, alter the dosage of a particular therapy, stop or terminate a particular therapy, altering the frequency of a therapy, introduce a new therapy, introduce a new therapy to be used in combination with a current therapy, or any combination of the above.
  • the results of diagnosing, predicting, or monitoring a condition of a transplant recipient may be useful for informing a therapeutic decision such as removal of the transplant.
  • the removal of the transplant can be an immediate removal.
  • the therapeutic decision can be a retransplant.
  • Other examples of therapeutic regimen can include a blood transfusion in instances where the transplant recipient is refractory to immunosuppressive or antibody therapy.
  • a patient is indicated as having or being at enhanced risk of subAR or SCAR
  • the physician can subject the patient to additional testing including performing a kidney biopsy or performing other analyses such as creatinine, BUN or glomerular filtration rate at increased frequency. Additionally or alternatively, the physician can change the treatment regime being administered to the patient.
  • a change in treatment regime can include administering an additional or different drug to a patient, or administering a higher dosage or frequency of a drug already being administered to the patient.
  • immunosuppressive drugs used to treat transplant rejection calcineurin inhibitors (e.g., cyclosporine, tacrolimus), mTOR inhibitors (e.g., sirolimus and everolimus ), anti-proliferatives (e.g., azathioprine, mycophenolic acid), corticosteroids (e.g., prednisolone and hydrocortisone) and antibodies (e.g., basiliximab, daclizumab, Orthoclone, anti-thymocyte globulin and anti-lymphocyte globulin).
  • immunosuppressive drugs used to treat transplant rejection calcineurin inhibitors
  • mTOR inhibitors e.g., sirolimus and everolimus
  • anti-proliferatives e.g., azathioprine, mycophenolic acid
  • corticosteroids e.g., prednisolone and hydrocortisone
  • antibodies e.g., basilix
  • the physician can continue an existing treatment regime, or even decrease the dose or frequency of an administered drug.
  • expression levels are determined at intervals in a particular patient (i.e., monitoring).
  • the monitoring is conducted by serial minimally- invasive tests such as blood draws; but, in some cases, the monitoring may also involve analyzing a kidney biopsy, either histologically or by analyzing a molecular profile.
  • the monitoring may occur at different intervals, for example the monitoring may be hourly, daily, weekly, monthly, yearly, or some other time period, such as twice a month, three times a month, every two months, every three months, etc..
  • Such methods can provide a series of values changing over time indicating whether the aggregate expression levels in a particular patient are more like the expression levels in patients undergoing subAR or SCAR or not undergoing subAR or SCAR.
  • Movement in value toward or away from subAR or SCAR can provide an indication whether an existing immunosuppressive regime is working, whether the immunosuppressive regime should be changed or whether a biopsy or increased monitoring by markers such as creatinine or glomerular filtration rate should be performed.
  • the methods provided herein include administering a blood test (e.g., a test to detect subclinical acute rejection) to a transplant recipient who has already undergone a surveillance or protocol biopsy of the kidney and received a biopsy result in the form of a histological analysis or a molecular profiling analysis.
  • a blood test e.g., a test to detect subclinical acute rejection
  • the analysis of the kidney biopsy may result in ambiguous, inconclusive or borderline results.
  • a blood test provided herein may assist a caregiver with determining whether the transplant recipient has subclinical acute rejection or with interpreting the biopsy.
  • the biopsy itself may be inconclusive or ambiguous, and in such cases the molecular analysis of the biopsy may be used in adjunct with the histology to confirm a diagnosis.
  • the analysis of the kidney biopsy may yield a negative result.
  • the subject may receive a blood test provided herein in order to confirm the negative result, or to detect subclinical acute rejection.
  • the patient after receiving any type of biopsy result (e.g., negative result, ambiguous, inconclusive, borderline, positive), the patient may receive multiple, serial blood tests to monitor changes in molecular markers correlated with subclinical acute rejection.
  • the methods provided herein also include administering a biopsy test (e.g., histology or molecular profiling) to a transplant recipient who has received a molecular blood profiling test.
  • a biopsy test e.g., histology or molecular profiling
  • the transplant recipient may receive an ambiguous, inconclusive or borderline result on a blood molecular profiling test.
  • the patient's healthcare worker may use the results of a kidney biopsy test as a complement to the blood test to determine whether the subject is experiencing subclinical acute rejection.
  • the transplant recipient may have received a positive result on a blood molecular profiling test, indicating that the transplant recipient has, or likely has, subclinical acute rejection, or even multiple positive results over time.
  • the patient's physician or other healthcare worker may decide to biopsy the patient's kidney in order to detect subAR.
  • Such kidney biopsy test may be a molecular profiling analysis of the patient's kidney, as described herein.
  • a histological analysis of the kidney biopsy may be performed instead of, or in addition to, the molecular analysis of the biopsy.
  • the physician may decide to wait a certain period of time after receiving the positive blood result to perform the biopsy test.
  • the methods provided herein may often provide early detection of subAR and may help a patient to obtain early treatment such as receiving immunosuppressive therapy or increasing an existing immunosuppressive regimen.
  • Such early treatment may enable the patient to avoid more serious consequences associated with acute rejection later in time, such as allograft loss or procedures such as kidney dialysis.
  • such early treatments may be administered after the patient receives both a molecular profiling blood test and a biopsy analyzed either by molecular profiling or histologically.
  • the diagnosis or detection of condition of a transplant recipient may be particularly useful in limiting the number of invasive diagnostic interventions that are administered to the patient.
  • the methods provided herein may limit or eliminate the need for a transplant recipient (e.g., kidney transplant recipient) to receive a biopsy (e.g., kidney biopsies) or to receive multiple biopsies.
  • the methods provided herein can be used alone or in combination with other standard diagnosis methods currently used to detect or diagnose a condition of a transplant recipient, such as but not limited to results of biopsy analysis for kidney allograft rejection, results of histopathology of the biopsy sample, serum creatinine level, creatinine clearance, ultrasound, radiological imaging results for the kidney, urinalysis results, elevated levels of inflammatory molecules such as neopterin, and lymphokines, elevated plasma interleukin (IL)-l in azathioprine- treated patients, elevated IL-2 in cyclosporine-treated patients, elevated IL-6 in serum and urine, intrarenal expression of cytotoxic molecules (granzyme B and perforin) and immunoregulatory cytokines (IL-2, -4, -10, interferon gamma and transforming growth factor-b l).
  • IL interleukin
  • IL-6 immunoregulatory cytokines
  • kidney function tests such as complete blood count (CBC), serum electrolytes tests (including sodium, potassium, chloride, bicarbonate, calcium, and phosphorus), blood urea test, blood nitrogen test, serum creatinine test, urine electrolytes tests, urine creatinine test, urine protein test, urine fractional excretion of sodium (FENA) test, glomerular filtration rate (GFR) test.
  • Kidney function may also be assessed by a renal biopsy. Kidney function may also be assessed by one or more gene expression tests.
  • TX Drug screening
  • the expression profiles associated with SCAR or lack thereof (TX) provided by the invention are useful in screening drugs, either in clinical trials or in animal models of SCAR.
  • a clinical trial can be performed on a drug in similar fashion to the monitoring of an individual patient described above, except that drug is administered in parallel to a population of kidney transplant patients, usually in comparison with a control population administered a placebo.
  • the changes in expression levels of genes can be analyzed in individual patients and across a treated or control population. Analysis at the level of an individual patient provides an indication of the overall status of the patient at the end of the trial (i.e., whether gene expression profile indicates presence or enhanced susceptibility to SCAR) and/or an indication whether that profile has changed toward or away from such indication in the course of the trial. Results for individual patients can be aggregated for a population allowing comparison between treated and control population.
  • the expression profile of individual animals in a trial can provide an indication of the status of the animal at the end of the trial with respect to presence or susceptibility to SCAR and/or change in such status during the trial.
  • Results from individual animals can be aggregated across a population and treated and control populations compared. Average changes in the expression levels of genes can then be compared between the two populations.
  • Expression levels can be analyzed and associated with status of a subject (e.g., presence or susceptibility to SCAR) in a digital computer.
  • a computer is directly linked to a scanner or the like receiving experimentally determined signals related to expression levels.
  • expression levels can be input by other means.
  • the computer can be programmed to convert raw signals into expression levels (absolute or relative), compare measured expression levels with one or more reference expression levels, or a scale of such values, as described above.
  • the computer can also be programmed to assign values or other designations to expression levels based on the comparison with one or more reference expression levels, and to aggregate such values or designations for multiple genes in an expression profile.
  • the computer can also be programmed to output a value or other designation providing an indication of presence or susceptibility to SCAR as well as any of the raw or intermediate data used in determining such a value or designation.
  • a typically computer includes a bus which interconnects major subsystems such as a central processor, a system memory, an input/output controller, an external device such as a printer via a parallel port, a display screen via a display adapter, a serial port, a keyboard, a fixed disk drive and a floppy disk drive operative to receive a floppy disk. Many other devices can be connected such as a scanner via I/O controller, a mouse connected to serial port or a network interface.
  • the computer contains computer readable media holding codes to allow the computer to perform a variety of functions. These functions include controlling automated apparatus, receiving input and delivering output as described above.
  • the automated apparatus can include a robotic arm for delivering reagents for determining expression levels, as well as small vessels, e.g., microtiter wells for performing the expression analysis.
  • the methods, systems, kits and compositions provided herein may also be capable of generating and transmitting results through a computer network.
  • a sample (220) is first collected from a subject (e.g. transplant recipient, 210).
  • the sample is assayed (230) and gene expression products are generated.
  • a computer system (240) is used in analyzing the data and making classification of the sample.
  • the result is capable of being transmitted to different types of end users via a computer network (250).
  • the subject e.g. patient
  • the subject may be able to access the result by using a standalone software and/or a web-based application on a local computer capable of accessing the internet (260).
  • the result can be accessed via a mobile application (270) provided to a mobile digital processing device (e.g. mobile phone, tablet, etc.).
  • a mobile digital processing device e.g. mobile phone, tablet, etc.
  • the result may be accessed by physicians and help them identify and track conditions of their patients (280).
  • the result may be used for other purposes (290) such as education and research.
  • the methods, kits, and systems disclosed herein may include at least one computer program, or use of the same.
  • a computer program may include a sequence of instructions, executable in the digital processing device's CPU, written to perform a specified task.
  • Computer readable instructions may be implemented as program modules, such as functions, objects, Application Programming Interfaces (APIs), data structures, and the like, that perform particular tasks or implement particular abstract data types.
  • APIs Application Programming Interfaces
  • a computer program includes, in part or in whole, one or more web applications, one or more mobile applications, one or more standalone applications, one or more web browser plug-ins, extensions, add-ins, or add-ons, or combinations thereof.
  • the system may comprise (a) a digital processing device comprising an operating system configured to perform executable instructions and a memory device; (b) a computer program including instructions executable by the digital processing device to classify a sample from a subject comprising: (i) a first software module configured to receive a gene expression profile of one or more genes from the sample from the subject; (ii) a second software module configured to analyze the gene expression profile from the subject; and (iii) a third software module configured to classify the sample from the subject based on a classification system comprising three or more classes. At least one of the classes may be selected from transplant rejection, transplant dysfunction with no rejection and normal transplant function.
  • At least two of the classes may be selected from transplant rejection, transplant dysfunction with no rejection and normal transplant function. All three of the classes may be selected from transplant rejection, transplant dysfunction with no rejection and normal transplant function.
  • Analyzing the gene expression profile from the subject may comprise applying an algorithm. Analyzing the gene expression profile may comprise normalizing the gene expression profile from the subject. In some instances, normalizing the gene expression profile does not comprise quantile normalization.
  • Figure 4 shows a computer system (also "system” herein) 401 programmed or otherwise configured for implementing the methods of the disclosure, such as producing a selector set and/or for data analysis.
  • the system 401 includes a central processing unit (CPU, also “processor” and “computer processor” herein) 405, which can be a single core or multi core processor, or a plurality of processors for parallel processing.
  • the system 401 also includes memory 410 (e.g., random-access memory, read-only memory, flash memory), electronic storage unit 415 (e.g., hard disk), communications interface 420 (e.g., network adapter) for communicating with one or more other systems, and peripheral devices 425, such as cache, other memory, data storage and/or electronic display adapters.
  • memory 410 e.g., random-access memory, read-only memory, flash memory
  • electronic storage unit 415 e.g., hard disk
  • communications interface 420 e.g., network adapter
  • peripheral devices 425 such as cache,
  • the memory 410, storage unit 415, interface 420 and peripheral devices 425 are in communication with the CPU 405 through a communications bus (solid lines), such as a motherboard.
  • the storage unit 415 can be a data storage unit (or data repository) for storing data.
  • the system 401 is operatively coupled to a computer network ("network") 430 with the aid of the communications interface 420.
  • the network 430 can be the Internet, an internet and/or extranet, or an intranet and/or extranet that is in communication with the Internet.
  • the network 430 in some instances is a telecommunication and/or data network.
  • the network 430 can include one or more computer servers, which can enable distributed computing, such as cloud computing.
  • the network 430 in some instances, with the aid of the system 401, can implement a peer-to-peer network, which may enable devices coupled to the system 401 to behave as a client or a server.
  • the system 401 is in communication with a processing system 435.
  • the processing system 435 can be configured to implement the methods disclosed herein.
  • the processing system 435 is a nucleic acid sequencing system, such as, for example, a next generation sequencing system (e.g., Illumina sequencer, Ion Torrent sequencer, Pacific Biosciences sequencer).
  • the processing system 435 can be in
  • the processing system 435 can be configured for analysis, such as nucleic acid sequence analysis.
  • Methods as described herein can be implemented by way of machine (or computer processor) executable code (or software) stored on an electronic storage location of the system 401, such as, for example, on the memory 410 or electronic storage unit 415.
  • the code can be executed by the processor 405.
  • the code can be retrieved from the storage unit 415 and stored on the memory 410 for ready access by the processor 405.
  • the electronic storage unit 415 can be precluded, and machine-executable instructions are stored on memory 410.
  • the methods, kits, and systems disclosed herein may include a digital processing device, or use of the same.
  • the digital processing device includes one or more hardware central processing units (CPU) that carry out the device's functions.
  • the digital processing device further comprises an operating system configured to perform executable instructions.
  • the digital processing device is optionally connected a computer network.
  • the digital processing device is optionally connected to the Internet such that it accesses the World Wide Web.
  • the digital processing device is optionally connected to a cloud computing infrastructure.
  • the digital processing device is optionally connected to an intranet.
  • the digital processing device is optionally connected to a data storage device.
  • suitable digital processing devices include, by way of non-limiting examples, server computers, desktop computers, laptop computers, notebook computers, sub-notebook computers, netbook computers, netpad computers, set-top computers, handheld computers, Internet appliances, mobile smartphones, tablet computers, personal digital assistants, video game consoles, and vehicles.
  • server computers desktop computers, laptop computers, notebook computers, sub-notebook computers, netbook computers, netpad computers, set-top computers, handheld computers, Internet appliances, mobile smartphones, tablet computers, personal digital assistants, video game consoles, and vehicles.
  • smartphones are suitable for use in the system described herein.
  • Suitable tablet computers include those with booklet, slate, and convertible configurations, known to those of skill in the art.
  • the digital processing device will normally include an operating system configured to perform executable instructions.
  • the operating system is, for example, software, including programs and data, which manages the device's hardware and provides services for execution of applications.
  • suitable server operating systems include, by way of non-limiting examples, FreeBSD, OpenBSD, NetBSD , Linux, Apple ® Mac OS X Server ® , Oracle ® Solaris ® , Windows Server ® , and Novell ® NetWare ® .
  • suitable personal computer operating systems include, by way of non-limiting examples, Microsoft ® Windows ® , Apple ® Mac OS X ® , UNIX ® , and UNIX-like operating systems such as GNU/Linux ® .
  • the operating system is provided by cloud computing.
  • suitable mobile smart phone operating systems include, by way of non-limiting examples, Nokia ® Symbian ® OS, Apple ® iOS ® , Research In Motion ®
  • the device generally includes a storage and/or memory device.
  • the storage and/or memory device is one or more physical apparatuses used to store data or programs on a temporary or permanent basis.
  • the device is volatile memory and requires power to maintain stored information.
  • the device is nonvolatile memory and retains stored information when the digital processing device is not powered.
  • the non-volatile memory comprises flash memory.
  • the non-volatile memory comprises dynamic random-access memory (DRAM).
  • the non-volatile memory comprises ferroelectric random access memory (FRAM).
  • the non-volatile memory comprises phase- change random access memory (PRAM).
  • the device is a storage device including, by way of non-limiting examples, CD-ROMs, DVDs, flash memory devices, magnetic disk drives, magnetic tapes drives, optical disk drives, and cloud computing based storage.
  • the storage and/or memory device is a combination of devices such as those disclosed herein.
  • a display to send visual information to a user will normally be initialized.
  • Examples of displays include a cathode ray tube (CRT, a liquid crystal display (LCD), a thin film transistor liquid crystal display (TFT-LCD, an organic light emitting diode (OLED) display.
  • CTR cathode ray tube
  • LCD liquid crystal display
  • TFT-LCD thin film transistor liquid crystal display
  • OLED organic light emitting diode
  • on OLED display is a passive-matrix OLED (PMOLED) or active-matrix OLED (AMOLED) display.
  • the display may be a plasma display , a video projector or a combination of devices such as those disclosed herein.
  • the digital processing device would normally include an input device to receive information from a user.
  • the input device may be, for example, a keyboard, a pointing device including, by way of non-limiting examples, a mouse, trackball, track pad, joystick, game controller, or stylus; a touch screen, or a multi-touch screen, a microphone to capture voice or other sound input, a video camera to capture motion or visual input or a combination of devices such as those disclosed herein.
  • Non-transitory computer readable storage medium
  • the methods, kits, and systems disclosed herein may include one or more non- transitory computer readable storage media encoded with a program including instructions executable by the operating system to perform and analyze the test described herein;
  • the computer readable storage medium is a tangible component of a digital that is optionally removable from the digital processing device.
  • the computer readable storage medium includes, by way of non- limiting examples, CD-ROMs, DVDs, flash memory devices, solid state memory, magnetic disk drives, magnetic tape drives, optical disk drives, cloud computing systems and services, and the like.
  • the program and instructions are permanently, substantially permanently, semi-permanently, or non-transitorily encoded on the media.
  • a non-transitory computer-readable storage media may be encoded with a computer program including instructions executable by a processor to create or use a classification system.
  • the storage media may comprise (a) a database, in a computer memory, of one or more clinical features of two or more control samples, wherein (i) the two or more control samples may be from two or more subjects; and (ii) the two or more control samples may be differentially classified based on a classification system comprising three or more classes; (b) a first software module configured to compare the one or more clinical features of the two or more control samples; and (c) a second software module configured to produce a classifier set based on the comparison of the one or more clinical features.
  • At least two of the classes may be selected from transplant rejection, transplant dysfunction with no rejection and normal transplant function. All three classes may be selected from transplant rejection, transplant dysfunction with no rejection and normal transplant function.
  • the storage media may further comprise one or more additional software modules configured to classify a sample from a subject. Classifying the sample from the subject may comprise a classification system comprising three or more classes. At least two of the classes may be selected from transplant rejection, transplant dysfunction with no rejection and normal transplant function. All three classes may be selected from transplant rejection, transplant dysfunction with no rejection and normal transplant function.
  • a computer program includes a web application.
  • a web application in various embodiments, utilizes one or more software frameworks and one or more database systems.
  • a web application is created upon a software framework such as Microsoft ® .NET or Ruby on Rails (RoR).
  • a web application utilizes one or more database systems including, by way of non-limiting examples, relational, non-relational, object oriented, associative, and XML database systems.
  • suitable relational database systems include, by way of non-limiting examples, Microsoft ® SQL Server, mySQLTM, and Oracle ® .
  • a web application in various embodiments, is written in one or more versions of one or more languages.
  • a web application may be written in one or more markup languages, presentation definition languages, client-side scripting languages, server-side coding languages, database query languages, or combinations thereof.
  • a web application is written to some extent in a markup language such as Hypertext Markup Language (HTML), Extensible Hypertext Markup Language (XHTML), or extensible Markup Language (XML).
  • a web application is written to some extent in a presentation definition language such as Cascading Style Sheets (CSS).
  • CSS Cascading Style Sheets
  • a web application is written to some extent in a client-side scripting language such as Asynchronous Javascript and XML (AJAX), Flash ® Actionscript, Javascript, or Silverlight ® .
  • AJAX Asynchronous Javascript and XML
  • Flash ® Actionscript Javascript
  • Javascript or Silverlight ®
  • a web application is written to some extent in a server- side coding language such as Active Server Pages (ASP), ColdFusion ® , Perl, JavaTM, JavaServer Pages (JSP), Hypertext Preprocessor (PHP), PythonTM, Ruby, Tel, Smalltalk, WebDNA ® , or Groovy.
  • a web application is written to some extent in a database query language such as Structured Query Language (SQL).
  • SQL Structured Query Language
  • a web application integrates enterprise server products such as IBM ® Lotus Domino ® .
  • a web application includes a media player element.
  • a media player element utilizes one or more of many suitable multimedia technologies including, by way of non-limiting examples, Adobe ® Flash ® , HTML 5, Apple ® QuickTime ® , Microsoft ® Silverlight ® , JavaTM, and Unity ® .
  • a computer program includes a mobile application provided to a mobile digital processing device.
  • the mobile application is provided to a mobile digital processing device at the time it is manufactured.
  • the mobile application is provided to a mobile digital processing device via the computer network described herein.
  • a mobile application is created by techniques known to those of skill in the art using hardware, languages, and development environments known to the art. Those of skill in the art will recognize that mobile applications are written in several languages. Suitable programming languages include, by way of non-limiting examples, C, C++, C#, Objective-C, JavaTM, Javascript, Pascal, Object Pascal, PythonTM, Ruby, VB.NET, WML, and XHTML/HTML with or without CSS, or combinations thereof.
  • Suitable mobile application development environments are available from several sources. Commercially available development environments include, by way of non-limiting examples, AirplaySD , alcheMo, Appcelerator ® , Celsius, Bedrock, Flash Lite, .NET Compact Framework, Rhomobile, and WorkLight Mobile Platform. Other development environments are available without cost including, by way of non-limiting examples, Lazarus, MobiFlex, MoSync, and Phonegap. Also, mobile device manufacturers distribute software developer kits including, by way of non-limiting examples, iPhone and iPad (iOS) SDK, AndroidTM SDK, BlackBerry ® SDK, BREW SDK, Palm ® OS SDK, Symbian SDK, webOS SDK, and Windows ® Mobile SDK.
  • iOS iPhone and iPad
  • a computer program includes a standalone application, which is a program that is run as an independent computer process, not an add-on to an existing process, e.g., not a plug-in.
  • standalone applications are often compiled.
  • a compiler is a computer program(s) that transforms source code written in a programming language into binary object code such as assembly language or machine code. Suitable compiled programming languages include, by way of non-limiting examples, C, C++, Objective-C, COBOL, Delphi, Eiffel, JavaTM, Lisp, PythonTM, Visual Basic, and VB .NET, or combinations thereof. Compilation is often performed, at least in part, to create an executable program.
  • a computer program includes one or more executable complied applications.
  • the computer program includes a web browser plug-in.
  • a plug-in is one or more software components that add specific functionality to a larger software application. Makers of software applications support plug-ins to enable third- party developers to create abilities which extend an application, to support easily adding new features, and to reduce the size of an application. When supported, plug-ins enable customizing the functionality of a software application. For example, plug-ins are commonly used in web browsers to play video, generate interactivity, scan for viruses, and display particular file types. Those of skill in the art will be familiar with several web browser plug- ins including, Adobe ® Flash ® Player, Microsoft ® Silverlight ® , and Apple ® QuickTime ® .
  • the toolbar comprises one or more web browser extensions, add-ins, or add-ons. In some embodiments, the toolbar comprises one or more explorer bars, tool bands, or desk bands.
  • plug-in frameworks are available that enable development of plug-ins in various programming languages, including, by way of non-limiting examples, C++, Delphi, JavaTM, PHP, PythonTM, and VB .NET, or combinations thereof.
  • Web browsers are software applications, designed for use with network-connected digital processing devices, for retrieving, presenting, and traversing information resources on the World Wide Web. Suitable web browsers include, by way of non-limiting examples, Microsoft ® Internet Explorer ® , Mozilla ® Firefox ® , Google ® Chrome, Apple ® Safari ® , Opera Software ® Opera ® , and KDE Konqueror. In some embodiments, the web browser is a mobile web browser.
  • Mobile web browsers are designed for use on mobile digital processing devices including, by way of non-limiting examples, handheld computers, tablet computers, netbook computers, subnotebook computers, smartphones, music players, personal digital assistants (PDAs), and handheld video game systems.
  • Suitable mobile web browsers include, by way of non-limiting examples, Google ® Android ® browser, RIM BlackBerry ® Browser, Apple ® Safari ® , Palm ® Blazer, Palm ® WebOS ® Browser, Mozilla ® Firefox ® for mobile, Microsoft ® Internet Explorer ® Mobile, Amazon ® Kindle ® Basic Web, Nokia ® Browser, Opera Software ® Opera ® Mobile, and Sony ® PSPTM browser.
  • the methods, kits, and systems disclosed herein may include software, server, and/or database modules, or use of the same.
  • software modules are created by techniques known to those of skill in the art using machines, software, and languages known to the art.
  • the software modules disclosed herein are implemented in a multitude of ways.
  • a software module comprises a file, a section of code, a programming object, a programming structure, or combinations thereof.
  • a software module comprises a plurality of files, a plurality of sections of code, a plurality of programming objects, a plurality of programming structures, or combinations thereof.
  • the one or more software modules comprise, by way of non-limiting examples, a web application, a mobile application, and a standalone application.
  • software modules are in one computer program or application. In other embodiments, software modules are in more than one computer program or application. In some embodiments, software modules are hosted on one machine. In other embodiments, software modules are hosted on more than one machine. In further embodiments, software modules are hosted on cloud computing platforms. In some embodiments, software modules are hosted on one or more machines in one location. In other embodiments, software modules are hosted on one or more machines in more than one location.
  • the methods, kits, and systems disclosed herein may comprise one or more databases, or use of the same.
  • suitable databases include, by way of non-limiting examples, relational databases, non-relational databases, object oriented databases, object databases, entity-relationship model databases, associative databases, and XML databases.
  • a database is internet-based.
  • a database is web-based.
  • a database is cloud computing-based.
  • a database is based on one or more local computer storage devices.
  • the methods, kits, and systems disclosed herein may be used to transmit one or more reports.
  • the one or more reports may comprise information pertaining to the classification and/or identification of one or more samples from one or more subjects.
  • the one or more reports may comprise information pertaining to a status or outcome of a transplant in a subject.
  • the one or more reports may comprise information pertaining to therapeutic regimens for use in treating transplant rejection in a subject in need thereof.
  • the one or more reports may comprise information pertaining to therapeutic regimens for use in treating transplant dysfunction in a subject in need thereof.
  • the one or more reports may comprise information pertaining to therapeutic regimens for use in suppressing an immune response in a subject in need thereof.
  • the one or more reports may be transmitted to a subject or a medical representative of the subject.
  • the medical representative of the subject may be a physician, physician's assistant, nurse, or other medical personnel.
  • the medical representative of the subject may be a family member of the subject.
  • a family member of the subject may be a parent, guardian, child, sibling, aunt, uncle, cousin, or spouse.
  • the medical representative of the subject may be a legal representative of the subject.
  • This Example describes some of the materials and methods employed in identification of differentially expressed genes in SCAR.
  • SCAR was defined by a protocol biopsy done on a patient with totally stable kidney function and the light histology revealed unexpected evidence of acute rejection ( 16 "Borderline", 7 Banff 1 A).
  • the SCAR samples consisted of 3 month and 1 year protocol biopsies, whereas the TXs were predominantly 3 month protocol biopsies.
  • the mean age of the patients is 49.3 years (ranging from 22-71 ); 35% female; 52% deceased donors.
  • Table 5 presents time to biopsies where time is defined as days post transplantation. All the AR biopsies were "for cause" where clinical indications like a rise in serum creatinine prompted the need for a biopsy. All patients were induced with Thymoglobulin.
  • a diagnostic signature we used the top 200 differentially expressed probe sets (Table 2) to build predictive models that could differentiate the three classes.
  • the top 200 probesets have FDR values of ⁇ 0.05%.
  • DLDA Diagonal Linear Discriminant Analysis
  • NC Nearest Centroid
  • SVM Support Vector Machines
  • AUC Area Under the Curve
  • SVM, DLDA and NC picked classifier sets of 200, 192 and 188 probesets as the best classifiers. Since there was very little difference in the AUC's we decided to use all 200 probesets as classifiers for all methods.
  • Table 1 shows the performance of these classifier sets using both one-level cross validation as well as the Optimism Corrected Bootstrapping (1000 data sets).
  • This Example describes the identification of differentially expressed genes in SCAR using microarray and next-generation sequencing (NGS) analyses.
  • NGS next-generation sequencing
  • Microarray Analyses - biopsy samples [00191] All samples were processed on the HG-U 133 Plus PM microarrays. All samples were normalized using RMA in Partek Genomics Suite 6.6. To facilitate biomarker discovery by removing probe sets with low signal intensities we used a signal filter cut-off that was data dependent, and therefore expression signals ⁇ Log 2 4.14 (median signals on all arrays) in all samples were eliminated leaving us with 27980 probe sets representing about 13900 genes.
  • the results showed predictive accuracy of 100%, sensitivity of 100%, specificity of 100%, positive predictive value of 100%, negative predictive value of 100%, and AUC of .0.
  • TX vs. SCAR subAR
  • the results showed predictive accuracy of 78%, sensitivity of 81 %, specificity of 75%, positive predictive value of 84%o, negative predictive value of 71%, and AUC of 0.785.
  • AR vs. SCAR subAR 2-way classifier
  • the results showed predictive accuracy of 76%, sensitivity of 76%, specificity of 75%, positive predictive value of 80%, negative predictive value of 71 %, and AUC of 0.768.
  • the results showed predictive accuracy of 97%, sensitivity of 100%, specificity of 94%, positive predictive value of 95%, negative predictive value of 100%, and AUC of 0.965.
  • TX vs. SCAR subAR
  • the results showed predictive accuracy of 95%, sensitivity of 100%, specificity of 90%, positive predictive value of 91 %, negative predictive value of 100%, and AUC of 0.947.
  • AR vs. SCAR subAR 2-way classifier
  • the results showed predictive accuracy of 86%, sensitivity of 90%, specificity of 81%, positive predictive value of 81%, negative predictive value of 90%, and AUC of 0.862.
  • the 3-way 1 -step method has an overall predictive accuracy of 81 %. As shown in Table 10, the method correctly classified most samples. In TX v. AR a, the results showed predictive accuracy of 97%, sensitivity of 100%, specificity of 92%, positive predictive value of 95%, negative predictive value of 100%), and AUC of 0.967. In TX vs. SCAR (subAR), the results showed predictive accuracy of 80%, sensitivity of 72%, specificity of 83%, positive predictive value of 72%, negative predictive value of 91 %, and AUC of 0.795. Similarly, in AR vs.
  • SCAR subAR
  • the results showed predictive accuracy of 69%, sensitivity of 58%>, specificity of 79% positive predictive value of 79%, negative predictive value of 59%o, and AUC of 0.689.
  • we are confident that we can distinguish SCAR, TX and AR from biopsy samples using the next-generation sequencing 3-way 1 -step analysis.
  • the top 200 probe sets (ranked on p-value) of the biopsy NGS signatures for the first step (SCAR+AR vs. TX) is listed in Table 1 1 .
  • the second step was using the SCAR vs AR genes to separate the SCARs from the ARs.
  • the top 160 probe sets (ranked on p-value) of the biopsy NGS signatures for the second step (SCAR vs. AR) is listed in Table 12.
  • NGS Analyses - blood samples [00209] All samples were processed the same way as the biopsy NGS samples. We first performed a 3-way 1 -step ANOVA analysis of AR vs. SCAR (subAR) vs. TX. Nearest Centroid Algorithm in Partek were used to identify best classifier set that can distinguish all three phenotypes. The full 123 probe sets (p ⁇ 0.01 ) ranked by p-value are listed in Table 17 and the best performing 53 probe sets gene signature picked by the Nearest Centroid Algorithm are listed in Table 18.
  • JUP, XCL1 , CRADD, XCL1 /XCL2, PRNP, HHEX, FAM43A, and PSMD6-AS2 Were also differentially expressed (p ⁇ 0.05) in the microarray comparisons.
  • Zinc finger Zinc finger, CCHC
  • Zinc finger ANl-type
  • VAMP vesicle-associated VAMP
  • ARID2 2 (ARID, RFX-like) 2.11E-05 3.97E-03 240.9 185.3 169.2
  • CD164 molecule 1044.
  • VAMP vesicle-associated VAMP

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Abstract

By a genome-wide gene analysis of expression profiles of over 50,000 known or putative gene sequences in peripheral blood, the present inventors have identified a consensus set of gene expression-based molecular biomarkers associated with subclinical acute rejection (subAR). These genes sets are useful for diagnosis, prognosis, monitoring of subAR.

Description

Gene Expression Profiles Associated With Sub-Clinical Kidney
Transplant Rejection
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application claims the benefit of priority to U.S. Application No.
14/481 , 167, filed September 9, 2014; to International Application No. PCT/US2014/054735, filed September 9, 2014; to U.S. Provisional Application No. 62/029,038, filed July 25, 2014; to U.S. Provisional Application No. 62/001 ,889, filed May 22, 2014; to U.S.
Provisional Application No.62/001 ,902, filed May 22, 2014; and to U.S. Provisional Application No.62/001 ,909, filed May 22, 2014, each of which is incorporated by reference herein in their entirety.
COPYRIGHT NOTIFICATION
[0002] Pursuant to 37 C.F.R. § 1 .71 (e), Applicants note that a portion of this disclosure contains material which is subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or patent disclosure, as it appears in the Patent and Trademark Office patent file or records, but otherwise reserves all copyright rights whatsoever.
STATEMENT CONCERNING GOVERNMENT SUPPORT
[0003] This invention was made in part with the U.S. government support by the National Institutes of Health Grant No. AI063603. The U.S. Government therefore may have certain rights in the invention.
BACKGROUND OF THE INVENTION
[0004] Kidney transplantation offers a significant improvement in life expectancy and quality of life for patients with end stage renal disease. Unfortunately, graft losses due to allograft dysfunction or other uncertain etiologies have greatly hampered the therapeutic potential of kidney transplantation. Among various types of graft losses, subclinical acute rejection (subAR or SCAR) is histologically defined as acute rejection characterized by tubule-interstitial mononuclear infiltration identified from a biopsy specimen, but without concurrent functional deterioration (variably defined as a serum creatinine not exceeding 10%, 20% or 25% of baseline values).
[0005] A critically important challenge for the future of molecular diagnostics in transplantation based on peripheral blood profiling is to predict a state of adequate immunosuppression with immune mediated kidney injury before there is a change in the serum creatinine. This is the challenge of identifying subclinical acute rejection, which at this time is only occasionally and accidentally picked up by protocol biopsies done at arbitrary time points.
[0006] The terms subAR and SCAR are used interchangeably herein to refer to subclinical acute rejection. SubAR (or SCAR) is distinct from clinical acute rejection, which is characterized by acute functional renal impairment. The differences between subAR or SCAR and acute rejection (which may appear histologically indistinguishable on a limited sample) can be explained by real quantitative differences of renal cortex affected, qualitative differences (such as increased perforin, granzyme, c-Bet expression or macrophage markers), or by an increased ability of the allograft to withstand immune injury
('accommodation'). SubAR or SCAR is often diagnosed only on biopsies taken as per protocol at a fixed time after transplantation, rather than driven by clinical indication. Its diagnosis cannot rely on traditional kidney function measurements like serum creatinine and glomerular filtration rates. Predicting graft outcomes strictly based on the kidney biopsy is difficult and this invasive procedure has significant costs and risks for patients. Organ biopsy results can also be inaccurate, particularly if the area biopsied is not representative of the health of the organ as a whole (e.g., as a result of sampling error). There can be significant differences between individual observers when they read the same biopsies independently and these discrepancies are particularly an issue for complex histologies that can be challenging for clinicians. In addition, the early detection of rejection of a transplant organ may require serial monitoring by obtaining multiple biopsies, thereby multiplying the risks to the patients, as well as the associated costs.
[0007] Transplant rejection is a marker of ineffective immunosuppression and ultimately if it cannot be resolved, a failure of the chosen therapy. The fact that 50% of kidney transplant patients will lose their grafts by ten years post-transplant reveals the difficulty of maintaining adequate and effective long-term immunosuppression. Currently, there are no other effective and reliable blood-based or any other tests for subAR or SCAR
diagnosis.Thus, there is a pressing medical need to identify minimally invasive biomarkers that are able to identify subAR or SCAR at a time that changes in therapy may alter outcomes. The present invention addresses this and other unfulfilled needs in the art.
SUMMARY OF THE INVENTION
[0008] In one aspect, the disclosure provides methods of detecting, prognosing, diagnosing or monitoring subclinical acute rejection (subAR or SCAR). These methods typically entail obtaining nucleic acids of interest, and then (a) determining or detecting expression levels in a subject of at least 5 genes (e.g., at least 10 genes, at least 20 genes, at least 50 genes, at least 100 genes, at least 300 genes, at least 500 genes, etc.); and (b) detecting, prognosing, diagnosing or monitoring subAR or SCAR in the subject from the expression levels. In some methods, the nucleic acids of interest comprise mRNA extracted from a sample from the subject or nucleic acids derived from the mRNA extracted from the sample from the subject. The methods are particularly useful for analysis of blood samples.
[0009] Some of the methods are directed to subjects who have or are at risk of developing subAR or SCAR or acute rejection (AR), or have well-functioning normal transplant (TX). In some of the methods, the subject has a serum creatinine level of less than 3 mg/dL, less than 2.5 mg/dL, less than 2.0 mg/dL, or less than 1.5 mg/dL. In some methods, the subject has a normal serum creatinine level. In some of the methods, for each of the at least five genes, step (b) involves comparing the expression level of the gene in the subject to one or more reference expression levels of the gene associated with subAR or SCAR, acute rejection (AR) or lack of transplant rejection (TX). In some of these methods, step (b) further includes, for each of the at least five genes, assigning the expression level of the gene in the subject a value or other designation providing an indication whether the subject has or is at risk of developing SCAR, has acute rejection (AR), or has well- functioning normal transplant (TX). In some methods, the expression level of each of the at least five genes is assigned a value on a normalized scale of values associated with a range of expression levels in kidney transplant patients with SCAR, with AR, or with TX. In some methods, the expression level of each of the at least five genes is assigned a value or other designation providing an indication that the subject has or is at risk of SCAR, has or is at risk of AR, has well-functioning normal transplant, or that the expression level is uninformative. In some methods, step (b) further includes combining the values or designations for each of the genes to provide a combined value or designation providing an indication whether the subject has or is at risk of SCAR, has acute rejection (AR), or has well-functioning normal transplant (TX). In some embodiments, the method can be repeated at different times on the subject. Some of these methods are directed to subjects who have been receiving a drug, and a change in the combined value or designation over time provides an indication of the effectiveness of the drug.
[0010] In some embodiments, the expression level is determined in a subject of at least five genes selected from the genes in one or more of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, or 1 8. In another aspect, the methods comprise detecting or determining the expression level of at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 1500, or 2000 genes selected from at least one of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, and 18.
[0011] In some embodiments, the detection of expression levels comprises applying a two-step classifier to the gene expression levels. In some embodiments, one step in the two- step classifier distinguishes between normal transplant (TX) and AR+subAR. In some embodiments, one step in the two-step classifier distinguishes between AR and subAR.
[0012] In various embodiments, the subjects suitable for methods of the invention are patients who have undergone a kidney transplant. Often, the subject has received the kidney transplant within 1 month, 3 months, 1 year, 2 years, 3 years or 5 years of performing step (a). In some methods of the invention, step (a) is performed on a blood sample of the subject. In some methods, the sample is a blood sample and comprises whole blood, peripheral blood, serum, plasma, PBLs, PBMCs, T cells, CD4 T cells CDS T cells, or macrophages. In some methods, step (a) is performed on a urine sample of the subject. In some methods, step (a) is performed on a biopsy from the subject, preferably a kidney biopsy. In some methods, step (a) is performed on at least 10, 20, 40, 50, 70, 100, 150, 200, 250, 300, 400, or 500 genes from one or more of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, or 18. Some methods further include changing the treatment regime of the patient responsive to the detecting, prognosing, diagnosing or monitoring step. In these methods, the subject can be one who has received a drug before performing the methods, and the change comprises administering an additional drug or administering a higher dose of the same drug, or administering a lower dose of the same drug, or stopping administering the same drug.
[0013] Some methods of the invention further include performing an additional procedure to detect SCAR or risk thereof if the determining step provides an indication the subject has or is at risk of SCAR. The additional procedure can be, e.g., examination of a kidney biopsy sample. In some methods of the invention, expression levels of the genes are determined at the mRNA level or at the protein level. In some methods, step (b) can be performed by a computer. In some preferred embodiments, the at least five genes are selected from one or more of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, or 18.
[0014] In a related aspect, the invention provides methods of detecting, prognosing, diagnosing or monitoring subclinical acute rejection (subAR or SCAR) in a subject having normal serum creatinine level. These methods involve obtaining nucleic acids of interest, and then (a) determining or detecting expression levels in the subject of at least 2 genes; and (b) detecting, prognosing, diagnosing or monitoring subAR or SCAR in the subject from the expression levels. In some of these methods, the methods comprise determining or detecting the expression levels in the subject of at least five genes. In some of these methods, the at least two genes or the at least five genes are selected from the genes in one or more of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, or 18. In some of these methods, the nucleic acids of interest comprise mRNA extracted from a sample from a subject or nucleic acids derived from the mRNA extracted from the sample from the subject. In some methods, the sample is a blood sample. In some methods, the nucleic acids of interest are contacted with probes, wherein the probes are specific for the at least two genes or the at least five genes. In some of these methods, for each of the at least two genes or the at least five genes, step (b) entails comparing the expression level of the gene in the subject to one or more reference expression levels of the gene associated with SCAR, or lack of transplant rejection (TX). In some of these methods, step (b) further includes, for each of the at least two genes or the at least five genes, assigning the expression level of the gene in the subject a value or other designation providing an indication whether the subject has or is at risk of developing SCAR. In some methods, the expression level of each of the at least two genes or the at least five genes is assigned a value on a normalized scale of values associated with a range of expression levels in kidney transplant patients with and without SCAR. In some methods, the expression level of each of the at least two genes or at least five genes is assigned a value or other designation providing an indication that the subject has or is at risk of SCAR, lacks and is not at risk of SCAR, or that the expression level is uninformative. In some of these methods, step (b) further includes combining the values or designations for each of the genes to provide a combined value or designation providing an indication whether the subject has or is at risk of subAR or SCAR.
[0015] In various embodiments, the method can be repeated at different times on the subject. In some methods, the subject can be one who is receiving a drug, and a change in the combined value or designation over time provides an indication of the effectiveness of the drug. Some methods of the invention are directed to subjects who have undergone a kidney transplant within 1 month, 3 months, 1 year, 2 years, 3 years or 5 years of performing step (a). In some methods, step (a) is performed on a blood sample of the subject. In some methods, the sample is a blood sample and comprises whole blood, peripheral blood, serum, plasma, PBLs, PBMCs, T cells, CD4 T cells CD8 T cells, or macrophages. In some methods, step (a) is performed on a urine sample of the subject. In some methods, step (a) is performed on at least 3, 4, 5, 10, 15, 20, 30 or more genes. In some methods, step (a) is performed on at least 10, 20, 40, or 100 or more genes selected from at least one of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, and 18. Some of the methods further include changing the treatment regime of the patient responsive to the detecting, prognosing, diagnosing or monitoring step. In some of these methods, the subject is one who has received a drug before performing the methods, and the change comprises administering an additional drug or administering a higher dose of the same drug, or administering a lower dose of the same drug, or stopping administering the same drug. Some other methods can further include performing an additional procedure to detect SCAR or risk thereof if the determining step provides an indication the subject has or is at risk of SCAR, e.g., a kidney biopsy. In various embodiments, expression levels of the genes can be determined at the mRNA level or at the protein level. In some methods, step (b) is performed by a computer.
[0016] In various embodiments, the methods provided herein compare the gene expression profile in the peripheral blood of patients with acute cellular rejection (AR) on a surveillance protocol biopsy (SCAR-normal creatinine) with that of patients with normal protocol surveillance biopsies (TX - normal creatinine), or with a previously validated peripheral blood profile for patients with clinical acute cellular rejection (CAR-elevated creatinine) found on a "for cause" biopsy. [0017] In another aspect, the invention provides arrays which contain a support or supports bearing a plurality of nucleic acid probes complementary to a plurality of mRNAs fewer than 5000 in number. Typically, the plurality of mRNAs includes mRNAs expressed by at least five genes selected from one or more of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, or 1 8. In some embodiments, the plurality of mRNAs are fewer than 1000 or fewer than 100 in number. In some embodiments, the plurality of nucleic acid probes are attached to a planar support or to beads. In some embodiments, the at least five genes are selected from one or more of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, or 18. In a related aspect, the invention provides arrays that contain a support or supports bearing a plurality of ligands that specifically bind to a plurality of proteins fewer than 5000 in number. The plurality of proteins typically includes at least five proteins encoded by genes selected from one or more of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, or 18. In some embodiments, the plurality of proteins are fewer than 1000 or fewer than 100 in number. In some embodiments, the plurality of ligands are attached to a planar support or to beads. In some embodiments, the at least five proteins are encoded by genes selected from one or more of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, or 18. In some embodiments, the ligands are different antibodies that bind to different proteins of the plurality of proteins.
[0018] In still another aspect, the invention provides methods of expression analysis. These methods involve determining expression levels of up to 2,000 genes (including at least 5 genes selected from one or more of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, or 18) in a sample from a subject having a kidney transplant. In some methods, the expression levels of up to 100 or 1000 genes are determined. The gene expression levels can be determined at the mRNA level or at the protein level. For example, the expression levels can be determined by quantitative PCR or hybridization to an array or sequencing.
[0019] The invention additionally provides methods of screening a compound for activity in inhibiting or treating SCAR. The methods involve (a) administering the compound to a subject having or at risk of SCAR; (b) determining, before and after administering the compound to the subject, expression levels of at least five genes in the subject selected from one or more of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 1 5, 17, or 1 8 and species variants thereof, and (c) determining whether the compound has activity in inhibiting or treating SCAR from a change in expression levels of the genes after administering the compound. In some methods, step (c) entails, for each of the at least five changes, assigning a value or designation depending on whether the change in the expression level of the gene relative to one or more reference levels indicating presence or absence of SCAR. Some methods further include determining a combined value or designation for the at least five genes from the values or designations determined for each gene. In some preferred embodiments, the subject is human or a nonhuman animal model of SCAR.
[0020] In another aspect, the methods disclosed herein have an error rate of less than about 40%. In some embodiments, the method has an error rate of less than about 40%, 35%, 30%, 25%, 20%, 15%, 10%, 5%, 3%, 2%, or 1 %. For example, the method has an error rate of less than about 10%. In some embodiments, the methods disclosed herein have an accuracy of at least about 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, or 99%. For example, the method has an accuracy of at least about 70%. In some embodiments, the methods disclosed herein have a sensitivity of at least about 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, or 99%. For example, the method has a sensitivity of at least about 80%. In some embodiments, the methods disclosed herein have a positive predictive value of at least about 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, or 99%. In some embodiments, the methods disclosed herein have a negative predictive value of at least about 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, or 99%.
[0021] In some embodiments, the gene expression products described herein are RNA (e.g., mRNA). In some embodiments, the gene expression products are polypeptides. In some embodiments, the gene expression products are DNA complements of RNA expression products from the transplant recipient.
[0022] In an embodiment, the algorithm described herein is a trained algorithm. In another embodiment, the trained algorithm is trained with gene expression data from biological samples from at least three different cohorts. In another embodiment, the trained algorithm comprises a linear classifier. In another embodiment, the linear classifier comprises one or more linear discriminant analysis, Fisher's linear discriminant, Naive Bayes classifier, Logistic regression, Perceptron, Support vector machine (SVM) or a combination thereof. In another embodiment, the algorithm comprises a Diagonal Linear Discriminant Analysis (DLDA) algorithm. In another embodiment, the algorithm comprises a Nearest Centroid algorithm. In another embodiment, the algorithm comprises a Random Forest algorithm or statistical bootstrapping. In another embodiment, the algorithm comprises a Prediction Analysis of Microarrays (PAM) algorithm. In another embodiment, the algorithm is not validated by a cohort-based analysis of an entire cohort. In another embodiment, the algorithm is validated by a combined analysis with an unknown phenotype and a subset of a cohort with known phenotypes.
[0023] In another aspect, the sample is a blood sample or is derived from a blood sample. In another embodiment, the blood sample is a peripheral blood sample. In another embodiment, the blood sample is a whole blood sample. In another embodiment, the sample does not comprise tissue from a biopsy of a transplanted organ of the transplant recipient. In another embodiment, the sample is not derived from tissue from a biopsy of a transplanted organ of the transplant recipient.
[0024] In another aspect, the assay is a microarray, SAGE, blotting, RT-PCR, sequencing and/or quantitative PCR assay. In another embodiment, the assay is a microarray assay. In another embodiment, the microarray assay comprises the use of an Affymetrix Human Genome U 133 Plus 2.0 GeneChip. In another embodiment, the mircroarray uses the Hu l 33 Plus 2.0 cartridge arrays plates. In another embodiment, the microarray uses the HT HG-U133+ PM array plates. In another embodiment, determining the assay is a sequencing assay. In another embodiment, the assay is a RNA sequencing assay.
[0002] In some embodiments, the subject or transplant recipient has a serum creatinine level of less than 3.0 mg/dL, less than 2.5 mg/dL, less than 2.0 mg/dL, or less than 1 .5 mg/dL. The subject may have a serum creatinine level that is stable over time. In some cases, the subject or transplant recipient has a serum creatinine level of at least 0.4 mg/dL, 0.6 mg/dL, 0.8 mg/dL, 1.0 mg/dL, 1 .2 mg/dL, 1.4 mg/dL, 1 .6 mg/dL, 1.8 mg/dL, 2.0 mg/dL, 2.2 mg/dL,
2.4 mg/dL, 2.6 mg/dL, 2.8 mg/dL, 3.0 mg/dL, 3.2 mg/dL, 3.4 mg/dL, 3.6 mg/dL, 3.8 mg/dL, or 4.0 mg/dL. For example, the transplant recipient has a serum creatinine level of at least
1 .5 mg/dL. In another example, the transplant recipient has a serum creatinine level of at least 3 mg/dL.
[0025] In one aspect, the invention provides methods of detecting subclinical acute rejection (subAR) in a subject comprising: (a) obtaining nucleic acids of interest, wherein the nucleic acids of interest comprise mRNA extracted from a sample from the subject or nucleic acids derived from the mRNA extracted from the sample from the subject; (b) detecting expression levels in the subject of at least five genes using the nucleic acids of 2202 interest obtained in step (a); and (c) detecting subAR in the subject from the expression levels detected in step (b). In an example, the sample from the subject is a blood sample.
[0026] In another aspect, the method detects subAR with an accuracy of greater than 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90% or 95%. In another aspect, the method detects subAR with a sensitivity of greater than 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90% or 95%. For example, the method detects subAR with an accuracy of greater than 75% or a sensitivity of greater than 75%.
[0027] In another aspect, the method further comprises contacting the nucleic acids of interest with probes, wherein the probes are specific for the at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 1500, or 2000 genes selected in step (b).
[0028] In another aspect, detecting subAR comprises detecting a risk of developing subAR, detecting acute rejection (AR), detecting a risk of having acute rejection (AR), or detecting a well-functioning normal transplant (TX). In another aspect, for each of at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 1500, or 2000 genes, step (c) of the method comprises comparing the expression level of the gene in the subject to one or more reference expression levels of genes associated with subAR, acute rejection (AR) or lack of transplant rejection (TX).
[0029] A further understanding of the nature and advantages of the present invention may be realized by reference to the remaining portions of the specification and claims.
BRIEF DESCRIPTION OF THE DRAWINGS
[0030] Figure 1 shows a schematic overview of certain methods in the disclosure.
[0031] Figure 2 shows a schematic overview of certain methods of acquiring samples, analyzing results, and transmitting reports over a computer network.
[0032] Figure 3 is an illustration of hierarchical clustering of gene expression signals of 33 probesets used to differentiate SCAR versus TX.
[0033] Figure 4 shows a computer system for implementing the methods of the disclosure.
[0034] Figure 5 shows a correlation of fold-change between microarray and NGS analyses (1066 common genes). [0035] Figure 6 shows a heat map and clustering of fold changes (Microarrays vs NGS) of 1066 genes.
[0036] Figure 7 shows correlation of fold-change between microarray and NGS analyses (all expressed NGS 7076 genes).
DETAILED DESCRIPTION
[0037] Sub-clinical acute rejection (referred to herein as "subAR" or "SCAR," interchangeably) is normally defined as histologic kidney rejection (e.g., histologic acute cellular rejection) with normal serum creatinine, and is associated with worse long term graft survival. In some cases, creatinine can be a lagging indicator of renal injury. Most times acute rejection (AR) of kidney graft is detected only after the initial injury has started. Early detection of subAR or SCAR can avoid unnecessary complications later in the course of graft life. However, normally subAR or SCAR is detected using a protocol kidney biopsy which is invasive, expensive and involves substantial risk. The present invention is predicated in part on the development by the inventors of a peripheral blood gene expression profiling signature that can distinguish Sub-Clinical Acute Rejection (subAR or SCAR), well-functioning normal transplant (TX) and Acute Rejection (AR). As detailed herein, the present inventors have identified consensus sets of gene expression-based molecular biomarkers associated with SCAR. This was accomplished via a genome-wide gene analysis of expression profiles of over 50,000 known or putative gene sequences in peripheral blood. More than 2,000 sequences were found to have differential expressions among the 3 different patient groups (Table 4). Among these sequences, the inventors further identified the top 200 differentially expressed probesets (Table 2), which can provide more focused and better expression profiles for differentiating the three classes of patients. In addition, a set of genes with differential expression levels only between SCAR and non-rejected transplants (TX) were also identified (Table 3). Expression rotocs based on the genes in this set are predictive in differentiating between transplant patients who will develop SCAR and patients who will maintain non-rejected transplants.
[0038] Results from the present inventors' studies provide the basis of a molecular test that can diagnose subAR or SCAR, and also enables minimally invasive methods for monitoring kidney transplant recipients. The value of a blood test for subAR or SCAR is that it allows detection of subclinical immune-mediated transplant rejection prior to clinical evidence of kidney injury and dysfunction. This blood-based test is minimally invasive and amenable to serial monitoring. Moreover, peripheral blood gene expression profiling may be used to inform when to perform a biopsy in patients with normal renal function and/or to replace surveillance protocol biopsies. Therefore, the invention is useful for post-transplant management of kidney recipients. Additional advantages of the test is that serial monitoring of all patients with a blood test for SCAR and treatment of all patients with SCAR by increasing the level of effective immunosuppression may significantly improve long term graft function and survival.
[0039] An overview of certain methods in the disclosure is provided in Figure 1. In some instances, a method comprises obtaining a sample from a transplant recipient in a minimally invasive manner (110), such as via a blood draw. The sample may comprise gene expression products (e.g., polypeptides, RNA, mRNA isolated from within cells or a cell- free source) associated with the status of the transplant (e.g., subAR.). In some instances, the method may involve reverse-transcribing RNA within the sample to obtain cDNA that can be analyzed using the methods described herein. The method may also comprise assaying the level of the gene expression products (or the corresponding DNA) using methods such as microarray or sequencing technology (120). The method may also comprise applying an algorithm to the assayed gene expression levels (130) in order to detect subAR. After detection of the presence or absence of subAR, a treatment decision may be made. In some cases, the treatment decision may be that the transplant recipient should be treated more aggressively to mitigate the risk of acute rejection. In some cases, the treatment decision may be to reduce an existing treatment regimen, particularly if subAR is not detected. In the event that no subAR is detected, the treatment decision may involve a decision to forego or delay obtaining a kidney biopsy from the patient.
[0040] The following sections provide guidance for carrying out the methods of the invention.
I. Definitions
[0041] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the art to which this invention pertains. The following references provide one of skill with a general definition of many of the terms used in this invention: Academic Press Dictionary of Science and Technology, Morris (Ed.), Academic Press ( 1 st ed., 1992); Illustrated Dictionary of Immunology, Cruse (Ed.), CRC Pr I Lie (2nd ed., 2002); Oxford Dictionary of Biochemistry and Molecular Biology, Smith et al. (Eds.), Oxford University Press (revised ed., 2000); Encyclopaedic Dictionary of Chemistry, Kumar (Ed.), Anmol Publications Pvt. Ltd. (2002); Dictionary of Microbiology and Molecular Biology, Singleton et al. (Eds.), John Wiley & Sons (3rd ed., 2002); Dictionary of Chemistry, Hunt (Ed.), Routledge (1 st ed., 1999);
Dictionary of Pharmaceutical Medicine, Nahler (Ed.), Springer-Verlag Telos (1994);
Dictionary of Organic Chemistry, Kumar and Anandand (Eds.), Anmol Publications Pvt. Ltd. (2002); and A Dictionary of Biology (Oxford Paperback Reference), Martin and Hine (Eds.), Oxford University Press (4th ed., 2000). In addition, the following definitions are provided to assist the reader in the practice of the invention.
[0042] Transplantation is the transfer of tissues, cells or an organ from a donor into a recipient. If the donor and recipient as the same person, the graft is referred to as an autograft and as is usually the case between different individuals of the same species an allograft. Transfer of tissue between species is referred to as a xenograft.
[0043] A biopsy is a specimen obtained from a living patient for diagnostic or prognostic evaluation. Kidney biopsies can be obtained with a needle.
[0044] An average value can refer to any of a mean, median or mode.
[0045] A gene expression level is associated with a particular phenotype e.g., presence of subAR (SCAR) or AR if the gene is differentially expressed in a patient having the phenotype relative to a patient lacking the phenotype to a statistically significant extent.
Unless otherwise apparent from the context a gene expression level can be measured at the mRNA and/or protein level.
[0046] A target nucleic acid may be a nucleic acid (often derived from a biological sample), to which a polynucleotide probe is designed to specifically hybridize. The probe can detect presence, absence and/or amount of the target. The term target nucleic acid can refer to the specific subsequence of a larger nucleic acid to which the probe is directed or to the overall sequence (e.g., cDNA or mRNA) whose expression level is to be detected. The term target nucleic acid can also refer to a nucleic acid that is analyzed by any method, including by sequencing, PCR, microarray, or other method known in the art. [0047] The term subject or patient can include human or non-human animals. Thus, the methods and described herein are applicable to both human and veterinary disease and animal models. Preferred subjects are "patients," i.e., living humans that are receiving medical care for a disease or condition. This includes persons with no defined illness who are being investigated for signs of pathology. The term subject or patient can include transplant recipients or donors or healthy subjects. The methods can be particularly useful for human subjects who have undergone a kidney transplant although they can also be used for subjects who have gone other types of transplant (e.g., heart, liver, lung, stem cell, etc. ). The subjects may be mammals or non-mammals. Preferably, the subject is a human but in some cases, the subject is a non-human mammal, such as a non-human primate (e.g., ape, monkey, chimpanzee), cat , dog, rabbit, goat, horse, cow, pig, rodent, mouse, SCID mouse, rat, guinea pig, or sheep. The subject may be male or female; the subject may be and, in some cases, the subject may be an infant, child, adolescent, teenager or adult. In some cases, the methods provided herein are used on a subject who has not yet received a transplant, such as a subject who is awaiting a tissue or organ transplant. In other cases, the subject is a transplant donor. In some cases, the subject has not received a transplant and is not expected to receive such transplant. In some cases, the subject may be a subject who is suffering from diseases requiring monitoring of certain organs for potential failure or dysfunction. In some cases, the subject may be a healthy subject.
[0048] Often, the subject is a patient or other individual undergoing a treatment regimen, or being evaluated for a treatment regimen (e.g., immunosuppressive therapy). However, in some instances, the subject is not undergoing a treatment regimen. A feature of the graft tolerant phenotype detected or identified by the subject methods is that it is a phenotype which occurs without immunosuppressive therapy, e.g., it is present in a subject that is not receiving immunosuppressive therapy.
[0049] A transplant recipient may be a recipient of a solid organ or a fragment of a solid organ such as a kidney. Preferably, the transplant recipient is a kidney transplant or allograft recipient. In some instances, the transplant recipient may be a recipient of a tissue or cell. In some particular examples, the transplanted kidney may be a kidney differentiated in vitro from pluripotent stem cell(s) (e.g., induced pluripotent stem cells or embryonic stem cells). [0050] The donor organ, tissue, or cells may be derived from a subject who has certain similarities or compatibilities with the recipient subject. For example, the donor organ, tissue, or cells may be derived from a donor subject who is age-matched, ethnicity-matched, gender-matched, blood-type compatible, or HLA-type compatible with the recipient subject.
[0051] In various embodiments, the subjects suitable for methods of the invention are patients who have undergone an organ transplant within 6 hours, 12 hours, 1 day, 2 days, 3 days, 4 days, 5 days, 10 days, 15 days, 20 days, 25 days, 1 month, 2 months, 3 months, 4 months, 5 months, 7 months, 9 months, 1 1 months, 1 year, 2 years, 4 years, 5 years, 10 years, 15 years, 20 years or longer of prior to receiving a classification obtained by the methods disclosed herein, such as detection of subAR.
[0052] Diagnosis refers to methods of estimating or determining whether or not a patient is suffering from a given disease or condition or severity of the condition. Diagnosis does not require ability to determine the presence or absence of a particular disease with 100% accuracy, or even that a given course or outcome is more likely to occur than not. Instead, the "diagnosis" refers to an increased probability that a certain disease or condition is present in the subject compared to the probability before the diagnostic test was performed.
Similarly, a prognosis signals an increased probability that a given course or outcome will occur in a patient relative to the probability before the prognostic test.
[0053] A probe or polynucleotide probe is a nucleic acid capable of binding to a target nucleic acid of complementary sequence through one or more types of chemical bonds, usually through complementary base pairing, usually through hydrogen bond formation, thus forming a duplex structure. The probe binds or hybridizes to a "probe binding site." A probe can include natural (e.g., A, G, C, U, or T) or modified bases (e.g., 7-deazaguanosine, inosine.). A probe can be an oligonucleotide and may be a single-stranded DNA or RNA. Polynucleotide probes can be synthesized or produced from naturally occurring
polynucleotides. In addition, the bases in a probe can be joined by a linkage other than a phosphodiester bond, so long as it does not interfere with hybridization. Thus, probes can include, for example, peptide nucleic acids in which the constituent bases are joined by peptide bonds rather than phosphodiester linkages (see, e.g., Nielsen et al., Science 254, 1497-1500 ( 1991 )). Some probes can have leading and/or trailing sequences of
noncomplementarity flanking a region of complementarity. [0054] A perfectly matched probe has a sequence perfectly complementary to a particular target sequence. The probe is typically perfectly complementary to a portion (subsequence) of a target sequence. The term "mismatch probe" refer to probes whose sequence is deliberately selected not to be perfectly complementary to a particular target sequence.
[0055] The term "isolated," "purified" or "substantially pure" means an object species (e.g. , a nucleic acid sequence described herein or a polypeptide encoded thereby) has been at least partially separated from the components with which it is naturally associated.
[0056] Differential expression refers to a statistically significant difference in expression levels of a gene between two populations of samples (e.g., samples with and without SCAR). The expression levels can differ for example by at least a factor of 1.5 or 2 between such populations of samples. Differential expression includes genes that are expressed in one population and are not expressed (at least at detectable levels) in the other populations.
Unique expression refers to detectable expression in one population and undetectable expression (i.e., insignificantly different from background) in the other population using the same technique (e.g., as in the present example for detection).
[0057] Control populations for comparison with populations undergoing SCAR are usually referred to as being without SCAR. In some embodiments, such a control population also means subjects without acute kidney rejection.
[0058] Hybridization reactions are preferably performed under stringent conditions in which probes or primers hybridize to their intended target with which they have perfect complementarity and not to or at least to a reduced extent to other targets. An example of stringent hybridization conditions are hybridization in 6xsodium chloride/sodium citrate (SSC) at about 45° C, followed by one or more washes in 0.2xSSC, 0.1 % SDS at 50° C, 55° C, 60° C, and even more or 65° C.
[0059] Statistical significance means p < 0.05 or < 0.01 or even < 0.001 level. II. Genes in profiles
[0060] Table 4 lists more than 2000 probesets with corresponding genes whose expression changes significantly between kidney transplant patients undergoing SCAR compared with patients not undergoing rejection (TX) and also patients undergoing acute rejection (AR) (3-way prediction). The columns in the table have the following meanings: column 1 is a number assigned to a gene, column 2 is an Affymetrix number indicating a set of probes suitable for measuring expression of the gene, column 3 is a gene name
(recognized names of HUGO or similar bodies are used when available), column 4 is a further description of the gene, column 5 is a raw uncorrected measure of the statistical significance of change in gene expression between the above patient populations, column 6 corresponds to a value of the statistical significance after correction for the false discovery rate (FDR), and columns 7-9 respectively show mean expression levels of AR, SCAR, and TX patients. Table 2 similarly provides a subset of 200 preferred genes from Table 4. Table 3 provides similar information for a subset of genes from Table 4 which show differential expression between kidney transplant patients undergoing SCAR with kidney transplant patients not undergoing rejection (TX) (2-way prediction).
[0061] The genes referred to in the above tables are human genes. In some methods, species variants or homologs of these genes are used in a non-human animal model. Species variants are the genes in different species having greatest sequence identity and similarity in functional properties to one another. Many species variants of the above human genes are listed in the Swiss-Prot database.
[0062] To identify differentially expressed genes, raw gene expression levels are comparable between different genes in the same sample but not necessarily between different samples. As noted above, values given for gene expression levels can be normalized so that values for particular genes are comparable within and between the populations being analyzed. The normalization eliminates or at least reduces to acceptable levels any sample to sample differences arising from factors other than SCAR (e.g.
differences in overall transcription levels of patients due to general state of health and differences in sample preparation or nucleic acid amplification between samples). The normalization effectively applies a correction factor to the measured expression levels from a given array such that a profile of many expression levels in the array are the same between different patient samples. Software for normalizing overall expression patterns between different samples is both commercially and publically available (e.g., XRAY from Biotique Systems or BRB ArrayTools from the National Cancer Institute). After applying appropriate normalizing factors to the measured expression value of a particular gene in different samples, an average or mean value of the expression level is determined for the samples in a population. The average or mean values between different populations are then compared to determine whether expression level has changed significantly between the populations. The changes in expression level indicated for a given gene represent the relative expression level of that gene in samples from a population of individuals with a defined condition (e.g., transplant patients with SCAR) relative to samples from a control population (kidney transplant patients not undergoing rejection). In some cases, the population of individuals with a defined condition may be transplant recipients with SCAR identified by acute cellular rejection (AR) on a surveillance protocol biopsy (SCAR-normal creatinine) and the control population is patients (e.g., transplant recipients) with normal protocol surveillance biopsies (TX-normal creatine). In some cases, this SCAR gene expression profile is compared with a previously validated peripheral blood profile/signature for patients with clinical acute cellular rejection (CAR-elevated creatinine), such as a CAR identified with a "for cause" biopsy.
[0063] Similar principles apply in normalizing gene expression levels at the mRNA and protein levels. Comparisons between populations are made at the same level (e.g., mRNA levels in one population are compared with mRNA levels in another population or protein levels in one population with protein levels in another population).
III. Subject populations
[0064] The methods are suitable for detecting subAR or SCAR in transplant patients, and are particularly useful for detecting subAR or SCAR without relying on a histologic analysis or obtaining a biopsy. Subclinical rejection (SCR) including subAR generally refers to histologically defined acute rejection - particularly, histologically defined acute cellular rejection -- characterized by tubule-interstitial mononuclear infiltration identified from a biopsy specimen, but without concurrent functional deterioration (variably defined as a serum creatinine not exceeding 10%, 20% or 25% of baseline values). Some instances of SCR or subAR may represent the beginning or conclusion of an alloimmune infiltrate diagnosed fortuitously by protocol sampling, and some episodes of clinical rejection may actually represent subAR or SCAR with an alternative cause of functional decline, such as concurrent calcineurin inhibitor (CNI) nephrotoxicity A subAR subject may have normal and stable organ function. For example, a subAR subject typically shows normal and/or stable serum creatinine levels or eGFR. SubAR is usually diagnosed through biopsies that are taken at a fixed time after transplantation (e.g., protocol biopsies or serial monitoring biopsies) which are not driven by clinical indications but rather by standards of care. The biopsies may be analyzed histologically in order to detect the subAR. SubAR may be subclassified by some into acute subAR (subAR) or a milder form called borderline subAR (suspicious for acute rejection) based on the biopsy histology. ). A failure to recognize, diagnose and treat subclinical AR before significant tissue injury has occurred and the transplant shows clinical signs of dysfunction could be a major cause of irreversible organ damage. Moreover, a failure to recognize a chronic, subclinical immune-mediated organ damage and a failure to make appropriate changes in immunosuppressive therapy to restore a state of effective immunosuppression in that patient could contribute to late organ transplant failure. The methods disclosed herein can reduce or eliminate these and other problems associated with transplant rejection or failure.
[0065] In some instances, a normal serum creatinine level and/or a normal estimated glomerular filtration rate (eGFR) may indicate or correlate with healthy transplant (TX) or subclinical rejection (SCAR). For example, typical reference ranges for serum creatinine are 0.5 to 1 .0 mg/dL for women and 0.7 to 1.2 mg/dL for men, though typical kidney transplant patients have creatinines in the 0.8 to 1 .5 mg/dL range for women and 1 .0 to 1 .9 mg/dL range for men. This may be due to the fact that most kidney transplant patients have a single kidney. In some instances, the trend of serum creatinine levels over time can be used to evaluate the recipient's organ function. This is why it may be important to consider both "normal" serum creatinine levels and "stable" serum creatinine levels in making clinical judgments, interpreting testing results, deciding to do a biopsy or making therapy change decisions including changing immunosuppressive drugs. For example, the transplant recipient may show signs of a transplant dysfunction or rejection as indicated by an elevated serum creatinine level and/or a decreased eGFR. In some instances, a transplant subject with a particular transplant condition (e.g., AR, ADNR) may have an increase of a serum creatinine level of at least 0.1 mg/dL, 0.2 mg/dL, 0.3 mg/dL, 0.4 mg/dL, 0.5 mg/dL, 0.6 mg/dL, 0.7 mg/dL 0.8 mg/dL, 0.9 mg/dL, 1 .0 mg/dL, 1.1 mg/dL, 1.2 mg/dL, 1.3 mg/dL, 1 .4 mg/dL, 1 .5 mg/dL, 1 .6 mg/dL, 1.7 mg/dL, 1.8 mg/dL, 1.9 mg/dL, 2.0 mg/dL, 2.1 mg/dL, 2.2 mg/dL, 2.3 mg/dL, 2.4 mg/dL, 2.5 mg/dL, 2.6 mg/dL, 2.7 mg/dL, 2.8 mg/dL, 2.9 mg/dL, 3.0 mg/dL, 3.1 mg/dL, 3.2 mg/dL, 3.3 mg/dL, 3.4 mg/dL, 3.5 mg/dL, 3.6 mg/dL, 3.7 mg/dL, 3.8 mg/dL, 3.9 mg/dL, or 4.0 mg/dL. In some instances, a transplant subject with a certain transplant condition (e.g., AR, ADNR,) may have an increase of a serum creatinine level of at least 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, or 100% from baseline. In some instances, a transplant subject with a certain transplant condition (e.g., AR,
ADNR,etc.) may have an increase of a serum creatinine level of at least 1 -fold, 2-fold, 3- fold, 4-fold, 5-fold, 6-fold, 7-fold, 8-fold, 9-fold, or 10-fold from baseline. In some cases, the increase in serum creatinine (e.g., any increase in the concentration of serum creatinine described herein) may occur over about .25 days, 0.5 days, 0.75 days, 1 day, 1 .25 days, 1 .5 days, 1 .75 days, 2.0 days, 3.0 days, 4.0 days, 5.0 days, 6.0 days, 7.0 days, 8.0 days, 9.0 days, 10.0 days, 15 days, 30 days, 1 month, 2 months, 3 months, 4 months, 5 months, or 6 months, or more. In some instances, a transplant subject with a particular transplant condition (e.g., AR, ADNR, CAN, etc.) may have a decrease of a eGFR of at least 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, or 100% from baseline. In some cases, the decrease in eGFR may occur over .25 days, 0.5 days, 0.75 days, 1 day, 1.25 days, 1 .5 days, 1.75 days, 2.0 days, 3.0 days, 4.0 days, 5.0 days, 6.0 days, 7.0 days, 8.0 days, 9.0 days, 10.0 days, 15 days, 30 days, 1 month, 2 months, 3 months, 4 months, 5 months, or 6 months, or more. In some instances, diagnosing, predicting, or monitoring the status or outcome of a transplant or condition comprises determining transplant recipient-specific baselines and/or thresholds. The methods are particularly useful on human subjects who have undergone a kidney transplant although can also be used on subjects who have undergone other types of transplant (e.g., heart, liver, lungs, stem cell) or on non-humans who have undergone kidney or other transplant. As detailed herein, the methods can be employed to distinguish transplant patients who (1 ) have or are at risk of having acute rejection (AR), (2) have or are at risk of having SCAR, and (3) have normal functional transplant (TX). In some other applications, the methods are more practically employed to distinguish patients who either are either transplant excellent (TX) or have existing SCAR (or risk of developing SCAR). This is because patients with acute rejections can usually be easily diagnosed via
conventional assays, e.g., those based on serum creatinine level.
[0066] As such, the methods of the invention can be used in patients who have normal and stable creatinine levels to diagnose or prognose hidden SCAR without depending on invasive biopsies. In some cases, the serum creatinine levels of the transplant recipient are stable over at least 10 days, 20 days, 30 days, 40 days, 50 days, 60 days, 90 days, 100 days, 200 days, 300 days, 400 days or longer. In some cases, the transplant recipient has a serum creatinine level of less than 0.2 mg/dL, less than 0.3 mg/dL, less than 0.4 mg/dL, less than 0.5 mg/dL, less than 0.6 mg/dL, less than 0.7 mg/dL less than 0.8 mg/dL, less than 0.9 mg/dL, less than 1 .0 mg/dL, less than 1 .1 mg/dL, less than 1.2 mg/dL, less than 1.3 mg/dL, 1 .4 mg/dL, less than 1 .5 mg/dL, less than 1 .6 mg/dL, less than 1 .7 mg/dL, less than 1 .8 mg/dL, less than 1 .9 mg/dL, less than 2.0 mg/dL, less than 2.1 mg/dL, less than 2.2 mg/dL, less than 2.3 mg/dL, less than 2.4 mg/dL, less than 2.5 mg/dL, less than 2.6 mg/dL, less than 2.7 mg/dL, less than 2.8 mg/dL, less than 2.9 mg/dL, or less than 3.0 mg/dL.
[0067] As mentioned, often the methods provided herein can be used to detect subAR as opposed to a condition such as acute rejection (AR), or to predict whether the subject is at risk of having AR. Acute rejection (AR) or clinical acute rejection may occur when transplanted tissue is rejected by the recipient's immune system, which damages or destroys the transplanted tissue unless immunosuppression is achieved. T-cells, B-cells and other immune cells as well as possibly antibodies of the recipient may cause the graft cells to lyse or produce cytokines that recruit other inflammatory cells, eventually causing necrosis of allograft tissue. In some instances, AR may be diagnosed by a biopsy of the transplanted organ. In the case of kidney transplant recipients, AR may be associated with an increase in serum creatinine levels. The treatment of AR may include using immunosuppressive agents, corticosteroids, polyclonal and monoclonal antibodies, engineered and naturally occurring biological molecules,and antiproliferatives. AR more frequently occurs in the first three to 12 months after transplantation but there is a continued risk and incidence of AR for the first five years post transplant and whenever a patient's immunosuppression becomes inadequate for any reason for the life of the transplant.
[0068] The methods herein may also be used to distinguish between a kidney transplant patient with subAR and a normally functioning kidney transplant. Typically, when the patient does not exhibit symptoms or test results of organ dysfunction or rejection, the transplant is considered a normal functioning transplant (TX: Transplant excellent). An unhealthy transplant recipient may exhibit signs of organ dysfunction and/or rejection (e.g., an increasing serum creatinine
[0069] Regardless of the specific subject population, gene expression levels in the patients can be measured, for example, within, one month, three months, six months, one year, two years, five years or ten years after a kidney transplant. In some methods, gene expression levels are determined at regular intervals, e.g., every 3 months, 6 months or every year posttransplant, either indefinitely, or until evidence of SCAR is observed, in which case the frequency of monitoring is sometimes increased. In some methods, baseline values of expression levels are determined in a subject before a kidney transplant in combination with determining expression levels at one or more time points thereafter. Similar methods can be practiced in non-human species, in which cases, the expression levels measured are the species equivalent of the human genes referenced above.
IV. Methods of measuring profiles
[0070] Samples
[0071] The preferred sample type for analysis is a blood sample, which refers to whole blood or fractions thereof, such as plasma, or lymphocytes. Other samples that can be analyzed include urine, feces, saliva, and a kidney biopsy. The samples are typically isolated from a subject, particularly as a peripheral blood sample, and not returned to the subject. The analytes of interests in the samples can be analyzed with or without further processing of the sample, such as purification and amplification. Samples not requiring biopsy to obtain, particularly peripheral blood, are preferred. However, a sample may be any material containing tissues, cells, nucleic acids, genes, gene fragments, expression products, polypeptides, exosomes, gene expression products, or gene expression product fragments of a subject to be tested. In some cases, the sample is from a single patient. In some cases, the method comprises analyzing multiple samples at once, e.g., via massively parallel sequencing.
[0072] The sample is preferably blood. In some cases, the sample comprises whole blood, plasma, peripheral blood lymphocytes (PBLs), peripheral blood mononuclear cells (PBMCs), serum, T cells, B Cells, CD3 cells, CD8 cells, CD4 cells, or other immune cells.
[0073] The methods, kits, and systems disclosed herein may comprise specifically detecting, profiling, or quantitating molecules (e.g., nucleic acids, DNA, RNA, polypeptides, etc.) that are within the biological samples. In some instances, genomic expression products, including RNA, or polypeptides, may be isolated from the biological samples. In some cases, nucleic acids, DNA, RNA, polypeptides may be isolated from a cell-free source. In some cases, nucleic acids, DNA, RNA, polypeptides may be isolated from cells derived from the transplant recipient.
[0074] The sample may be obtained using any method known to the art that can provide a sample suitable for the analytical methods described herein. The sample may be obtained by a non-invasive method such as a throat swab, buccal swab, bronchial lavage, urine collection, scraping of the skin or cervix, swabbing of the cheek, saliva collection, feces collection, menses collection, or semen collection.
[0075] The sample may be obtained by a minimally-invasive method such as a blood draw. The sample may be obtained by venipuncture. In other instances, the sample is obtained by an invasive procedure including but not limited to: biopsy, alveolar or pulmonary lavage, or needle aspiration. The method of biopsy may include surgical biopsy, incisional biopsy, excisional biopsy, punch biopsy, shave biopsy, or skin biopsy. The sample may be formalin fixed sections. The method of needle aspiration may further include fine needle aspiration, core needle biopsy, vacuum assisted biopsy, or large core biopsy. In some embodiments, multiple samples may be obtained by the methods herein to ensure a sufficient amount of biological material. In some instances, the sample is not obtained by biopsy. In some instances, the sample is not a kidney biopsy.
[0076] Expression Profiles
[0077] For prognosis or diagnosis of SCAR in patients as opposed to both patients with acute rejection (AR) and patients without rejection (TX), the profiles can contain genes selected from at least one of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, and 18, for example, from Table 2. In some other methods, when the prognosis or diagnosis is intended to distinguish between patients having or at risk of developing SCAR and patients without rejection (TX), the genes in the profiles can be selected from at least one of Tables 2, 3, 4, 7, 8, 1 1, 12, 14, 15, 17, and 18, for example, from Table 3.
[0078[ Expression profiles are preferably measured at the nucleic acid level, meaning that levels of mRNA or nucleic acid derived therefrom (e.g., cDNA or cRNA). An expression profile refers to the expression levels of a plurality of genes in a sample. A nucleic acid derived from mRNA means a nucleic acid synthesized using mRNA as a template. Methods of isolation and amplification of mRNA are well known in the art, e.g., as described in WO 97/10365, WO 97/27317, Chapter 3 of Laboratory Techniques in Biochemistry and Molecular Biology: Hybridization With Nucleic Acid Probes, Part 1. Theory and Nucleic Acid Preparation, (P. Tijssen, ed.) Elsevier, N.Y. (1993). If mRNA or a nucleic acid therefrom is amplified, the amplification is performed under conditions that approximately preserve the relative proportions of mRNA in the original samples, such that the levels of the amplified nucleic acids can be used to establish phenotypic associations representative of the mRNAs.
[0079] A variety of approaches are available for determining mRNA levels including probe arrays and quantitative PCR. A number of distinct array formats are available. Some arrays, such as an Affymetrix HG-U 133 PM microarray or other Affymetrix GeneChip® array, have different probes occupying discrete known areas of a contiguous support.
Exemplary microarrays include but are not limited to the Affymetrix Human Genome U 133 Plus 2.0 GeneChip or the HT HG-U 133+ PM Array Plate.
[0080] Other arrays, such as arrays from Illumina, have different probes attached to different particles or beads. In such arrays, the identity of which probe is attached to which particle or beads is usually determinable from an encoding system. The probes can be oligonucleotides. In such case, typically several match probes are included with perfect complementarity to a given target mRNA together, optionally together with mismatch probes differing from the match probes are a known number of oligonucleotides (Lockhart, et al., Nature Biotechnology 14: 1675-1680 ( 1996); and Lipschutz, et al., Nature Genetics Supplement 21 : 20-24, 1999). Other arrays including full length cDNA sequences with perfect or near perfect complementarity to a particular cDNA (Schena et al. (Science 270:467-470 (1995); and DeRisi et al. (Nature Genetics 14:457-460 (1996)). Such arrays can also include various control probes, such as a probe complementarity with a house keeping gene likely to be expressed in most samples. Regardless of the specifics of array design, an array contains one or more probes either perfectly complementary to a particular target mRNA or sufficiently complementarity to the target mRNA to distinguish it from other mRNAs in the sample, and the presence of such a target mRNA can be determined from the hybridization signal of such probes, optionally by comparison with mismatch or other control probes included in the array. Typically, the target bears a fluorescent label, in which case hybridization intensity can be determined by, for example, a scanning confocal microscope in photon counting mode. Appropriate scanning devices are described by e.g., U.S. 5,578,832, and U.S. 5,63 1 ,734. The intensity of labeling of probes hybridizing to a particular mRNA or its amplification product provides a raw measure of expression level.
[0081] In other methods, expression levels are determined by so-called "real time amplification" methods also known as quantitative PCR or Taqman (see, e.g., U.S. Pat Nos. 5,210,01 5 to Gelfand, 5,538,848 to Livak, et al., and 5,863,736 to Haaland, as well as Heid, C.A., et al., Genome Research, 6:986-994 (1996); Gibson, U.E.M, et al., Genome Research 6:995- 1001 (1996); Holland, P. M., et al., Proc. Natl. Acad. Sci. USA 88:7276-7280, (1991); and Livak, K.J., et al., PCR Methods and Applications 357-362 (1995)). The basis for this method of monitoring the formation of amplification product is to measure continuously PCR product accumulation using a dual-labeled fluorogenic oligonucleotide probe. The probe used in such assays is typically a short (ca. 20-25 bases) polynucleotide that is labeled with two different fluorescent dyes. The 5' terminus of the probe is typically attached to a reporter dye and the 3' terminus is attached to a quenching dye The probe is designed to have at least substantial sequence complementarity with a site on the target mRNA or nucleic acid derived from. Upstream and downstream PCR primers that bind to flanking regions of the locus are also added to the reaction mixture. When the probe is intact, energy transfer between the two fluorophors occurs and the quencher quenches emission from the reporter. During the extension phase of PCR, the probe is cleaved by the 5' nuclease activity of a nucleic acid polymerase such as Taq polymerase, thereby releasing the reporter from the polynucleotide-quencher and resulting in an increase of reporter emission intensity which can be measured by an appropriate detector. The recorded values can then be used to calculate the increase in normalized reporter emission intensity on a continuous basis and ultimately quantify the amount of the mRNA being amplified. mRNA levels can also be measured without amplification by hybridization to a probe, for example, using a branched nucleic acid probe, such as a QuantiGene® Reagent System from Panomics.
[0082] In certain preferred embodiments, the expression level of the gene products (e.g., RNA) is determined by sequencing, such as by R A sequencing or by DNA sequencing (e.g., of cDNA generated from reverse-transcribing RNA (e.g., mRNA) from a sample). Sequencing may be performed by any available method or technique. Sequencing methods may include: Next Generation sequencing, high-throughput sequencing, pyrosequencing, classic Sangar sequencing methods, sequencing-by-ligation, sequencing by synthesis, sequencing-by-hybridization, RNA-Seq (Illumina), Digital Gene Expression (Helicos), next generation sequencing, single molecule sequencing by synthesis (SMSS) (Helicos), Ion Torrent Sequencing Machine (Life Technologies/Thermo-Fisher), massively-parallel sequencing, clonal single molecule Array (Solexa), shotgun sequencing, Maxim-Gilbert sequencing, primer walking, and any other sequencing methods known in the art.
[0083] Measuring gene expression levels may comprise reverse transcribing RNA (e.g., mRNA) within a sample in order to produce cDNA. The cDNA may then be measured using any of the methods described herein (e.g., PCR, digital PCR, qPCR, microarray, SAGE, blotting, sequencing, etc.).
[0084] Alternatively or additionally, expression levels of genes can be determined at the protein level, meaning that levels of proteins encoded by the genes discussed above are measured. Several methods and devices are well known for determining levels of proteins including immunoassays such as described in e.g., U.S. Patents 6, 143,576; 6, 1 13,855; 6,019,944; 5,985,579; 5,947, 124; 5,939,272; 5,922,615; 5,885,527; 5,851 ,776; 5,824,799; 5,679,526; 5,525,524; and 5,480,792. These assays include various sandwich, competitive, or non-competitive assay formats, to generate a signal that is related to the presence or amount of an protein analyte of interest. Any suitable immunoassay may be utilized, for example, lateral flow, enzyme-linked immunoassays (ELISA), radioimmunoassays (RIAs), competitive binding assays, and the like. Numerous formats for antibody arrays have been described proposed employing antibodies. Such arrays typically include different antibodies having specificity for different proteins intended to be detected. For example, usually at least one hundred different antibodies are used to detect one hundred different protein targets, each antibody being specific for one target. Other ligands having specificity for a particular protein target can also be used, such as the synthetic antibodies disclosed in WO/2008/048970. Other compounds with a desired binding specificity can be selected from random libraries of peptides or small molecules. US Patent No. 5,922,615 describes a device that utilizes multiple discrete zones of immobilized antibodies on membranes to detect multiple target antigens in an array. US Patent Nos. 5,458,852, 6,019,944, US 6, 143,576. Microtiter plates or automation can be used to facilitate detection of large numbers of different proteins. Protein levels can also be determined by mass spectrometry as described in the examples.
[0085] The selection of genes for determination of expression levels depends on the particular application. In general, the genes are selected from one of the tables indicated above as appropriate for the application. In some methods, expression levels of at least 2, 3, 4, 5, 10, 20, 25, 50, 100, 150, 250 (e.g. 100-250) genes shown in any of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, or 1 8 are determined. In some methods, expression levels of 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10, 1 1 , 12, 1 3, 14, 15, 16, 17, 18, 19, 20, 50, 100, 200, 300, 400, 500, 1000 or more genes found in Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 1 , 17, or 18 are determined. In some methods, genes are selected such that genes from several different pathways are represented. The genes within a pathway tend to be expressed in a coordinated expression whereas genes from different pathways tend to be expressed more independently. Thus, changes in expression based on the aggregate changes of genes from different pathways can have greater statistical significance than aggregate changes of genes within a pathway. In some cases, expression levels of the top 5, top 10, top 15, top 20, top 25, top 30, top 35, top 40, top 45, top 50, top 55, top 60, top 65, top 70, top 75, top 80, top 85, top 90, top 95, top 100, top 150, top 200, top 250 or top 300 genes listed in Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, or 18 are determined.
[0086] Expression levels of the present genes and/or proteins can be combined with or without determination of expression levels of any other genes or proteins of interest (e.g., genes or proteins associated with rejection of kidneys or other organs in WO 2007/104537, WO 2009/060035), Anglicheau et al., PNAS 106, 5330-5335 (2009)) and references, 16, 20, 21 , 22, 23, 25, 26, 37 and 39. In some methods, the genes in the expression profiles to be measured do not include at least one or all of the genes encoding urinary granzyme A, granzyme B, glyceraldehyde 3-phospate dehydrogenase (GAPDH), perforin, Fas ligand, CXCL9, CXCL10, and other proteins involved in patients' cytolytic attack against the transplant.
[0087] Regardless of the format adopted, the present methods can (but need not) be practiced by detection expression levels of a relatively small number of genes or proteins compared with the whole genome level expression analysis described in the Examples. In some methods, the total number of genes whose expression levels are determined is less than 5000, 1000, 500, 200, 100, 50, 25, 10, 5 or 3. In some methods, the total number of genes whose expression level is determined is 100-1500, 100-250, 500-1500 or 750- 1250. In some methods, the total number of proteins whose expression levels are determined is less than 5000, 1000, 500, 200, 100, 50, 25, 10, 5 or 3. In some methods, the total number of proteins whose expression level is determined is 100- 1 00, 100-250, 500- 1500 or 750- 1250. Correspondingly, when an array form is used for detection of expression levels, the array includes probes or probes sets for less than 5000, 1000, 500, 200, 100, 50, 25, 10, 5 or 3 genes. Thus, for example, an Affymetrix GeneChip® expression monitoring array contains a set of about 20-50 oligonucleotide probes (half match and half-mismatch) for monitoring each gene of interest. Such an array design would include less than 5000, 1000, 500, 200, 100, 50, 25, 10, 5 or 3 such probes sets for detecting less than 5000, 1000, 500, 200, 100, 50, 25, 10, 5 or 3 genes. By further example, an alternative array including one cDNA for each gene whose expression level is to be detected would contain less than 5000, 1000, 500, 200, 100, 50, 25, 10, 5 or 3 such cDNAs for analyzing less than 5000, 1000, 500, 200, 100, 50, 25, 10, 5 or 3 genes. By further example, an array containing a different antibody for each protein to be detected would containing less than 5000, 1000, 500, 200, 100, 50, 25, 10, 5 or 3 different antibodies for analyzing less than 5000, 1000, 500, 200, 100, 50, 25, 10, 5 or 3 gene products.
[0088] As described herein, in some cases the methods involve obtaining or analyzing a biopsy sample (e.g., kidney biopsy). The biopsy sample may be used for different purposes including to develop an expression profile signature. In some cases, an analysis described herein may be performed on a biopsy obtained from a transplant recipient in order to predict, monitor, or detect SCAR in the transplant recipient. In cases where biopsies are obtained, the biopsies may be processed included by placing the samples in a vessel (e.g., tube, PAX tube, vial, microfuge tube, etc.) and storing them at a specific location such as a
biorepository. The samples may also be processed by treatment with a specific agent, such as an agent that prevents nucleic acid degradation or deterioration, particularly an agent that protects RNA (e.g., RNALater) or DNA. In some cases, biopsies subjected to histologic analysis including staining (e.g., hematoxylin and eosin (H&E) stain) probing (e.g., a probe attached to a dye, a probe attached to a fluorescent label). In some cases, the staining (e.g., H&E) may be analyzed by a blinded physician such as a blinded pathologist, or at least two blinded pathologists, using criteria such as BANFF criteria. In some cases, a histologic diagnosis is reconciled with laboratory data and clinical courses by one or more clinicians (e.g., at least two clinicians) prior to biomarker analyses.
V. Analysis of expression levels 2202
[0089] Analysis of expression levels initially provides a measurement of the expression level of each of several individual genes. The expression level can be absolute in terms of a concentration of an expression product, or relative in terms of a relative concentration of an expression product of interest to another expression product in the sample. For example, relative expression levels of genes can be expressed with respect to the expression level of a house-keeping gene in the sample. Relative expression levels can also be determined by simultaneously analyzing differentially labeled samples hybridized to the same array.
Expression levels can also be expressed in arbitrary units, for example, related to signal intensity.
[0090] The individual expression levels, whether absolute or relative, can be converted into values or other designations providing an indication of presence or risk of SCAR by comparison with one or more reference points. Preferably, genes in Table 2 and/or one or more of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, or 18 are used for such analysis. The reference points can include a measure of an average or mean expression level of a gene in subjects having had a kidney transplant without SCAR, an average or mean value of expression levels in subjects having had a kidney transplant with SCAR, and/or an average/mean value of expression levels in subjects having had a kidney transplant with acute rejection. The reference points can also include a scale of values found in kidney transplant patients including patients having and not having SCAR. The reference points can also or alternatively include a reference value in the subject before kidney transplant, or a reference value in a population of patients who have not undergone kidney transplant. Such reference points can be expressed in terms of absolute or relative concentrations of gene products as for measured values in a sample.
[0091] For comparison between a measured expression level and reference level(s), the measured level sometimes needs to be normalized for comparison with the reference level(s) or vice versa. The normalization serves to eliminate or at least minimize changes in expression level unrelated to SCAR (e.g., from differences in overall health of the patient or sample preparation). Normalization can be performed by determining what factor is needed to equalize a profile of expression levels measured from different genes in a sample with expression levels of these genes in a set of reference samples from which the reference levels were determined. Commercial software is available for performing such normalizations between different sets of expression levels. [0092] Comparison of the measured expression level of a gene with one or more of the above reference points provides a value (i.e., numerical) or other designation (e.g., symbol or word(s)) of presence or susceptibility to SCAR. In some methods, a binary system is used; that is a measured expression level of a gene is assigned a value or other designation indicating presence or susceptibility to SCAR or lack thereof without regard to degree. For example, the expression level can be assigned a value of 1 to indicate presence or susceptibility to SCAR and - 1 to indicate absence or lack of susceptibility to SCAR. Such assignment can be based on whether the measured expression level is closer to an average or mean level in kidney transplant patients having or not having SCAR. In other methods, a ternary system is used in which an expression level is assigned a value or other designation indicating presence or susceptibility to SCAR or lack thereof or that the expression level is uninformative. Such assignment can be based on whether the expression level is closer to the average or mean level in kidney transplant patient undergoing SCAR, closer to an average or mean level in kidney transplant patients lacking SCAR or intermediate between such levels. For example, the expression level can be assigned a value of +1 , - 1 or 0 depending on whether it is closer to the average or mean level in patients undergoing SCAR, is closer to the average or mean level in patients not undergoing SCAR or is intermediate. In other methods, a particular expression level is assigned a value on a scale, where the upper level is a measure of the highest expression level found in kidney transplant patients and the lowest level of the scale is a measure of the lowest expression level found in kidney transplant patients at a defined time point at which patients may be susceptible to SCAR (e.g., one year post transplant). Preferably, such a scale is normalized scale (e.g., from 0- 1 ) such that the same scale can be used for different genes. Optionally, the value of a measured expression level on such a scale is indicated as being positive or negative depending on whether the upper level of the scale associates with presence or susceptibility to SCAR or lack thereof. It does not matter whether a positive or negative sign is used for SCAR or lack thereof as long as the usage is consistent for different genes.
[0093] Values or other designation can also be assigned based on a change in expression level of a gene relative to a previous measurement of the expression level of gene in the same patient. Here as elsewhere expression level of a gene can be measured at the protein or nucleic acid level. Such a change can be characterized as being toward, away from or neutral with respect to average or mean expression levels of the gene in kidney transplant patients undergoing or not undergoing SCAR. For example, a gene whose expression level changes toward an average or mean expression level in kidney transplant patients undergoing SCAR can be assigned a value of 1 and a gene whose express level changes way from an average or mean expression level in kidney transplant patients undergoing SCAR and toward an average or mean expression level in kidney transplant patients not undergoing SCAR can be assigned a value -1. Of course, more sophisticated systems of assigning values are possible based on the magnitude of changes in expression of a gene in a patient.
[0094] Having determined values or other designations of expression levels of individual genes providing an indication of presence or susceptibility to subAR (or SCAR) or lack thereof, the values or designations may be combined to provide an aggregate value for all of the genes in the signature being analyzed. If each gene is assigned a score of + 1 if its expression level indicates presence or susceptibility to subAR (or SCAR) and - 1 if its expression level indicates absence or lack of susceptibility to subAR and optionally zero if uninformative, the different values can be combined by addition. The same approach can be used if each gene is assigned a value on the same normalized scale and assigned as being positive or negative depending whether the upper point of the scale is associate with presence or susceptibility to subAR or lack thereof. In some cases, the signal intensity for each gene is obtained and used to compute a score. The score may be obtained by adding up the values for the upregulated genes to obtain an upregulated gene value and adding up the values of the downregulated genes to obtain a downregulated gene value; the downregulated gene value may be compared with the upregulated value (e.g., by calculating a ratio) to determine the score. Other methods of combining values for individual markers of disease into a composite value that can be used as a single marker are described in US20040126767 and WO/2004/059293. In some cases, the score may be used to evaluate severity of a transplant condition, such as by comparing the score with a score normally associated with subAR. In some cases, the score may be used to monitor a subject transplant recipient over time. In such case, scores at a plurality of timepoints maybe compared in order to assess the relative condition of the subject. For example, if the subject's score rises over time, that may indicate that the subject has subAR and that his or her condition is worsening over time.
[0095] Sample Data
[0096] The data pertaining to the sample may be compared to data pertaining to one or more control samples, which may be samples from the same patient at different times. In some cases, the one or more control samples may comprise one or more samples from healthy subjects, unhealthy subjects, or a combination thereof. The one or more control samples may comprise one or more samples from healthy subjects, subjects suffering from transplant dysfunction with no rejection, subjects suffering from transplant rejection, or a combination thereof. The healthy subjects may be subjects with normal transplant function. The data pertaining to the sample may be sequentially compared to two or more classes of samples. The data pertaining to the sample may be sequentially compared to three or more classes of samples. The classes of samples may comprise control samples classified as being from subjects with normal transplant function, control samples classified as being from subjects suffering from transplant dysfunction with no rejection, control samples classified as being from subjects suffering from transplant rejection, or a combination thereof.
[0097] Classifiers
[0098] The methods include using a trained classifier or algorithm to analyze sample data, particularly to detect subAR. In some instances, the expression levels from sample are used to develop or train an algorithm or classifier provided herein. In some instances, gene expression levels are measured in a sample from a transplant recipient (or a healthy or transplant excellent control) and a classifier or algorithm (e.g., trained algorithm) is applied to the resulting data in order to detect, predict, monitor, or estimate the risk of a transplant condition (e.g., subAR).
[0099] Training of multi-dimensional classifiers (e.g., algorithms) may be performed using numerous samples. For example, training of the multi-dimensional classifier may be performed using at least about 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 1 10, 120, 130, 140, 1 50, 160, 170, 1 80, 190, 200 or more samples. In some cases, training of the multidimensional classifier may be performed using at least about 200, 210, 220, 230, 240, 250, 260, 270, 280, 290, 300, 350, 400, 450, 500 or more samples. In some cases, training of the multi-dimensional classifier may be performed using at least about 525, 550, 600, 650, 700, 750, 800, 850, 900, 950, 1000, 1 100, 1200, 1300, 1400, 1500, 1600, 1700, 1 800, 2000 or more samples.
[00100] Further disclosed herein are classifier sets and methods of producing one or more classifier sets. The classifier set may comprise one or more genes, particularly genes from Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, or 18. In some cases, the classifier set may comprise 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10, 1 1 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 50, 100, 150, 200, 300 or more genes from Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, or 18. Disclosed herein is the use of a classification system comprises one or more classifiers. In some instances, the classifier is a 2-, 3-, 4-, 5-, 6-, 7-, 8-, 9-, or 10-way classifier. In some instances, the classifier is a 15-, 20-, 25-, 30-, 35-, 40-, 45-, 50-, 55-, 60-, 65-, 70-, 75-, 80-, 85-, 90-, 95-, or 100-way classifier. In some preferred embodiments, the classifier is a three-way classifier. In some embodiments, the classifier is a four-way classifier.
[00101] A two-way classifier may classify a sample from a subject into one of two classes. In some instances, a two-way classifier may classify a sample from an organ transplant recipient into one of two classes comprising subAR and normal transplant function (TX). In some instances, a three-way classifier may classify a sample from a subject into one of three classes. A three-way classifier may classify a sample from an organ transplant recipient into one of three classes comprising AR, subAR, and TX In some cases, the classifier may work by applying two or more classifiers sequentially. For example, the first classifier may classify AR+subAR and TX, which results in a set of samples that are classified either as ( 1 ) TX or (2) AR or subAR. In some cases, a second classifier capable of distinguishing between AR and subAR is applied to the samples classified as having AR or subAR in order to detect the subAR samples.
[00102] Classifiers and/or classifier probe sets may be used to either rule-in or rule-out a sample as healthy. For example, a classifier may be used to classify a sample as being from a healthy subject. Alternatively, a classifier may be used to classify a sample as being from an unhealthy subject. Alternatively, or additionally, classifiers may be used to either rule-in or rule-out a sample as transplant rejection. For example, a classifier may be used to classify a sample as being from a subject suffering from a transplant rejection. In another example, a classifier may be used to classify a sample as being from a subject that is not suffering from a transplant rejection. Classifiers may be used to either rule-in or rule-out a sample as transplant dysfunction with no rejection. For example, a classifier may be used to classify a sample as being from a subject with subAR. In another example, a classifier may be used to classify a sample as not being from a subject suffering from transplant dysfunction with no rejection. [00103] The samples may be classified simultaneously. In some cases, the samples may be classified sequentially. The two or more samples may be classified at two or more time points. The samples may be obtained at 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10, 1 1 , 12, 13, 14, 15, 16, 17, 1 8, 19, 20, 100 or more time points. The two or more time points may be 1 day, 10 days, 30 days, 60 days, 100 days, 200 days, 1 year, 2 years or more apart.
[00104] Methods of simultaneous classifier-based analysis of one or more samples may comprise applying one or more algorithm to data from one or more samples to
simultaneously produce one or more lists, wherein the lists comprise one or more samples classified as being from healthy subjects (e.g. subjects with a normal functioning transplant (TX)), unhealthy subjects, subjects suffering from transplant rejection, subjects suffering from transplant dysfunction, subjects with AR, or subjects withsubAR.
[00105] The methods, kits, and systems disclosed herein may comprise one or more algorithms or uses thereof. The one or more algorithms may be used to classify one or more samples from one or more subjects. The one or more algorithms may be applied to data from one or more samples. The data may comprise gene expression data. The data may comprise sequencing data. The data may comprise array hybridization data.
[00106] The methods disclosed herein may comprise assigning a classification to one or more samples from one or more subjects. Assigning the classification to the sample may comprise applying an algorithm to the expression level. In some cases, the gene expression levels are inputted to a trained algorithm for classifying the sample as one of the conditions comprising subAR, AR, TX, subAR+AR, or other condition.
[00107] The algorithm may provide a record of its output including a classification of a sample and/or a confidence level. In some instances, the output of the algorithm can be the possibility of the subject of having a condition, such as subAR. In some instances, the output of the algorithm can be the risk of the subject of having a condition, such as AR . In some instances, the output of the algorithm can be the possibility of the subject of developing into a condition in the future, such as AR.
[00108] The algorithm may be a trained algorithm. The algorithm may comprise a linear classifier. The linear classifier may comprise one or more linear discriminant analysis, Fisher's linear discriminant, Na'ive Bayes classifier, Logistic regression, Perceptron, Support vector machine, or a combination thereof. The linear classifier may be a Support vector machine (SVM) algorithm. [00109] The algorithm may comprise one or more linear discriminant analysis (LDA), Basic perceptron, Elastic Net, logistic regression, (Kernel) Support Vector Machines (SVM), Diagonal Linear Discriminant Analysis (DLDA), Golub Classifier, Parzen-based, (kernel) Fisher Discriminant Classifier, k-nearest neighbor, Iterative RELIEF, Classification Tree, Maximum Likelihood Classifier, Random Forest, Nearest Centroid, Prediction Analysis of Microarrays (PAM), k-medians clustering, Fuzzy C-Means Clustering, Gaussian mixture models, or a combination thereof. The algorithm may comprise a Diagonal Linear
Discriminant Analysis (DLDA) algorithm. The algorithm may comprise a Nearest Centroid algorithm. The algorithm may comprise a Random Forest algorithm. The algorithm may comprise a Prediction Analysis of Microarrays (PAM) algorithm.
[00110] The methods disclosed herein may comprise use of one or more classifier equations. Classifying the sample may comprise a classifier equation. The classifier equation may be Equation 1 :
[00111] 1- 1 , wherein:
[00112] k is a number of possible classes;
[00113] ^k, may be the discriminant score for class k;
[00114] represents the expression level of gene
[00115] X represents a vector of expression levels for all p genes to be used for classification drawn from the sample to be classified;
f'
[00116] k may be a shrunken centroid calculated from a training data and a shrinkage factor;
[00117] J'tk may be a component of k corresponding to gene %;
[00118] si is a pooled within-class standard deviation for gene ¾ in the training data;
[00119] So is a specified positive constant; and
[00120] represents a prior probability of a sample belonging to class k.
[00121 ] Assigning the classification may comprise calculating a class probability.
" ( X* ~)
Calculating the class probability ^ ^X ' may be calculated by Equation 2: prise a classification rule. The classification
C (x* ) = arg max p¾ (x* )
[00124]
[00125]
VI. Diagnosis, prognosis and monitoring
[00126] The above described methods can provide a composite or aggregate value or other designation for a patient, which indicates whether the patient either has or is at enhanced risk of SCAR (or AR), or conversely does not have or is at reduced risk of SCAR (or AR). Risk is a relative term in which risk of one patient is compared with risk of other patients either qualitatively or quantitatively. For example, the value of one patient can be compared with a scale of values for a population of patients having undergone kidney transplant to determine whether the patient's risk relative to that of other patients. In general, diagnosis is the determination of the present condition of a patient (e.g., presence or absence of SCAR) and prognosis is developing future course of the patient (e.g., risk of developing SCAR in the future or likelihood of improvement in response to treatment); however, the analyses contemplated by these terms may overlap or even be the same. For example, the present methods alone do not necessarily distinguish between presence and enhanced risk of SCAR. However, these possibilities can be distinguished by additional testing.
[00127] The methods provided herein can help determine whether the patient either has or is at enhanced risk of subAR/SCAR (or AR) with a high degree of accuracy, sensitivity, and/or specificity. In some cases, the predictive accuracy (e.g., for predicting subAR/SCAR, for detecting subAR/SCAR, or for distinguishing SCAR versus TX, SCAR versus AR, AR versus TX, and/or any combination thereof) is greater than 75%, 85%, 90%, 91 %, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 98.5%, 99.0%, 99.1%, 99.2%, 99.3%, 99.4%, 99.5%, 99.6%, 99.7%, 99.8%, 99.9%, 99.95%, or 99.99%. In some embodiments, the predictive accuracy is 100%. In some cases, the sensitivity (e.g., for detecting or predicting SCAR or for distinguishing SCAR versus TX, SCAR versus AR, AR versus TX, and/or any combination thereof) is greater than 75%, 85%, 90%, 91 %, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 98.5%, 99.0%, 99.1 %, 99.2%, 99.3%, 99.4%, 99.5%, 99.6%, 99.7%, 99.8%, 99.9%, 99.95%), or 99.99%o. In some embodiments the sensitivity is 100%. In some cases, the specificity (e.g., for detecting or predicting SCAR or for distinguishing SCAR versus TX, SCAR versus AR, AR versus TX, and/or any combination thereof) is greater than 75%, 85%, 90%, 91 %, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 98.5%, 99.0%, 99.1 %, 99.2%, 99.3%, 99.4%, 99.5%, 99.6%, 99.7%, 99.8%, 99.9%, 99.95%, or 99.99%. In some cases, the specificity is 100%. In some cases, the positive predictive value (e.g., for detecting or predicting SCAR or for distinguishing SCAR versus TX, SCAR versus AR, AR versus TX, and/or any combination thereof) of the method is greater than 75%, 85%, 90%, 91 >, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 98.5%, 99.0%, 99.1 %, 99.2%, 99.3%, 99.4%, 99.5%, 99.6%, 99.7%, 99.8%, 99.9%, 99.95%, or 99.99%. In some cases the positive predictive value is 100%. The AUC after thresholding in any of the methods provided herein may be greater than 0.9, 0.91 , 0.92, 0.93, 0.94, 0.95. 0.96, 0.97, 0.98, 0.99, 0.995, or 0.999.
Conversely, the method may predict or determine whether a transplant recipient does not have or is at reduced risk of SCAR (or AR). The negative predictive value (e.g., for predicting or determining that transplant recipient does not have SCAR or is at reduced risk for SCAR or for distinguishing SCAR versus TX, SCAR versus AR, AR versus TX, and/or any combination thereof) may be greater than 85%, 90%, 91 %, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 98.5%, 99.0%, 99.1 %, 99.2%, 99.3%, 99.4%, 99.5%, 99.6%, 99.7%, 99.8%, 99.9%, 99.95%, or 99.99%. In some cases, the negative predictive value is 100%.
[00128] In some instances, the methods, compositions, systems and kits described herein provide information to a medical practitioner that can be useful in making a therapeutic decision. Therapeutic decisions may include decisions to: continue with a particular therapy, modify a particular therapy, alter the dosage of a particular therapy, stop or terminate a particular therapy, altering the frequency of a therapy, introduce a new therapy, introduce a new therapy to be used in combination with a current therapy, or any combination of the above. . In some instances, the results of diagnosing, predicting, or monitoring a condition of a transplant recipient may be useful for informing a therapeutic decision such as removal of the transplant. In some instances, the removal of the transplant can be an immediate removal. In other instances, the therapeutic decision can be a retransplant. Other examples of therapeutic regimen can include a blood transfusion in instances where the transplant recipient is refractory to immunosuppressive or antibody therapy.
[00129] If a patient is indicated as having or being at enhanced risk of subAR or SCAR, the physician can subject the patient to additional testing including performing a kidney biopsy or performing other analyses such as creatinine, BUN or glomerular filtration rate at increased frequency. Additionally or alternatively, the physician can change the treatment regime being administered to the patient. A change in treatment regime can include administering an additional or different drug to a patient, or administering a higher dosage or frequency of a drug already being administered to the patient. Many different drugs are available for treating rejection, such as immunosuppressive drugs used to treat transplant rejection calcineurin inhibitors (e.g., cyclosporine, tacrolimus), mTOR inhibitors (e.g., sirolimus and everolimus ), anti-proliferatives (e.g., azathioprine, mycophenolic acid), corticosteroids (e.g., prednisolone and hydrocortisone) and antibodies (e.g., basiliximab, daclizumab, Orthoclone, anti-thymocyte globulin and anti-lymphocyte globulin).
[00130] Conversely, if the value or other designation of aggregate expression levels of a patient indicates the patient does not have or is at reduced risk of SCAR, the physician need not order further diagnostic procedures, particularly not invasive ones such as biopsy.
Further, the physician can continue an existing treatment regime, or even decrease the dose or frequency of an administered drug.
[00131] In some methods, expression levels are determined at intervals in a particular patient (i.e., monitoring). Preferably, the monitoring is conducted by serial minimally- invasive tests such as blood draws; but, in some cases, the monitoring may also involve analyzing a kidney biopsy, either histologically or by analyzing a molecular profile. The monitoring may occur at different intervals, for example the monitoring may be hourly, daily, weekly, monthly, yearly, or some other time period, such as twice a month, three times a month, every two months, every three months, etc..
[00132] Such methods can provide a series of values changing over time indicating whether the aggregate expression levels in a particular patient are more like the expression levels in patients undergoing subAR or SCAR or not undergoing subAR or SCAR.
Movement in value toward or away from subAR or SCAR can provide an indication whether an existing immunosuppressive regime is working, whether the immunosuppressive regime should be changed or whether a biopsy or increased monitoring by markers such as creatinine or glomerular filtration rate should be performed.
[00133] The methods provided herein include administering a blood test (e.g., a test to detect subclinical acute rejection) to a transplant recipient who has already undergone a surveillance or protocol biopsy of the kidney and received a biopsy result in the form of a histological analysis or a molecular profiling analysis. In some particular instances, the analysis of the kidney biopsy (e.g., by histology or molecular profiling) may result in ambiguous, inconclusive or borderline results. In such cases, a blood test provided herein may assist a caregiver with determining whether the transplant recipient has subclinical acute rejection or with interpreting the biopsy. In other cases the biopsy itself may be inconclusive or ambiguous, and in such cases the molecular analysis of the biopsy may be used in adjunct with the histology to confirm a diagnosis. In some instances, the analysis of the kidney biopsy may yield a negative result. In such cases, the subject may receive a blood test provided herein in order to confirm the negative result, or to detect subclinical acute rejection. In some cases, after receiving any type of biopsy result (e.g., negative result, ambiguous, inconclusive, borderline, positive), the patient may receive multiple, serial blood tests to monitor changes in molecular markers correlated with subclinical acute rejection.
[00134] The methods provided herein also include administering a biopsy test (e.g., histology or molecular profiling) to a transplant recipient who has received a molecular blood profiling test. For example, the transplant recipient may receive an ambiguous, inconclusive or borderline result on a blood molecular profiling test. In such cases, the patient's healthcare worker may use the results of a kidney biopsy test as a complement to the blood test to determine whether the subject is experiencing subclinical acute rejection. In another example, the transplant recipient may have received a positive result on a blood molecular profiling test, indicating that the transplant recipient has, or likely has, subclinical acute rejection, or even multiple positive results over time. In such cases, the patient's physician or other healthcare worker may decide to biopsy the patient's kidney in order to detect subAR. Such kidney biopsy test may be a molecular profiling analysis of the patient's kidney, as described herein. In some cases, a histological analysis of the kidney biopsy may be performed instead of, or in addition to, the molecular analysis of the biopsy. In some cases, the physician may decide to wait a certain period of time after receiving the positive blood result to perform the biopsy test. [00135] The methods provided herein may often provide early detection of subAR and may help a patient to obtain early treatment such as receiving immunosuppressive therapy or increasing an existing immunosuppressive regimen. Such early treatment may enable the patient to avoid more serious consequences associated with acute rejection later in time, such as allograft loss or procedures such as kidney dialysis. In some cases, such early treatments may be administered after the patient receives both a molecular profiling blood test and a biopsy analyzed either by molecular profiling or histologically.
[00136] The diagnosis or detection of condition of a transplant recipient may be particularly useful in limiting the number of invasive diagnostic interventions that are administered to the patient. For example, the methods provided herein may limit or eliminate the need for a transplant recipient (e.g., kidney transplant recipient) to receive a biopsy (e.g., kidney biopsies) or to receive multiple biopsies. In a further embodiment, the methods provided herein can be used alone or in combination with other standard diagnosis methods currently used to detect or diagnose a condition of a transplant recipient, such as but not limited to results of biopsy analysis for kidney allograft rejection, results of histopathology of the biopsy sample, serum creatinine level, creatinine clearance, ultrasound, radiological imaging results for the kidney, urinalysis results, elevated levels of inflammatory molecules such as neopterin, and lymphokines, elevated plasma interleukin (IL)-l in azathioprine- treated patients, elevated IL-2 in cyclosporine-treated patients, elevated IL-6 in serum and urine, intrarenal expression of cytotoxic molecules (granzyme B and perforin) and immunoregulatory cytokines (IL-2, -4, -10, interferon gamma and transforming growth factor-b l).
[00137] The methods herein may be used in conjunction with kidney function tests, such as complete blood count (CBC), serum electrolytes tests (including sodium, potassium, chloride, bicarbonate, calcium, and phosphorus), blood urea test, blood nitrogen test, serum creatinine test, urine electrolytes tests, urine creatinine test, urine protein test, urine fractional excretion of sodium (FENA) test, glomerular filtration rate (GFR) test. Kidney function may also be assessed by a renal biopsy. Kidney function may also be assessed by one or more gene expression tests.
VII. Drug screening [00138] The expression profiles associated with SCAR or lack thereof (TX) provided by the invention are useful in screening drugs, either in clinical trials or in animal models of SCAR. A clinical trial can be performed on a drug in similar fashion to the monitoring of an individual patient described above, except that drug is administered in parallel to a population of kidney transplant patients, usually in comparison with a control population administered a placebo.
[00139] The changes in expression levels of genes can be analyzed in individual patients and across a treated or control population. Analysis at the level of an individual patient provides an indication of the overall status of the patient at the end of the trial (i.e., whether gene expression profile indicates presence or enhanced susceptibility to SCAR) and/or an indication whether that profile has changed toward or away from such indication in the course of the trial. Results for individual patients can be aggregated for a population allowing comparison between treated and control population.
[00140] Similar trials can be performed in non-human animal models of chronic kidney disease, e.g., the mouse model of Mannon et al., Kidney International 55 : 1935-1944, 1999, In this case, the expression levels of genes detected are the species variants or homologs of the human genes referenced above in whatever species of non-human animal on which tests are being conducted. Although the average or mean expression levels of human genes determined in human kidney transplant patients undergoing or not undergoing SCAR are not necessarily directly comparable to those of homolog genes in an animal model, the human values can nevertheless be used to provide an indication whether a change in expression level of a non-human homolog is in a direction toward or away from SCAR or susceptibility thereto. The expression profile of individual animals in a trial can provide an indication of the status of the animal at the end of the trial with respect to presence or susceptibility to SCAR and/or change in such status during the trial. Results from individual animals can be aggregated across a population and treated and control populations compared. Average changes in the expression levels of genes can then be compared between the two populations.
VIII. Computer implemented methods
[00141] Expression levels can be analyzed and associated with status of a subject (e.g., presence or susceptibility to SCAR) in a digital computer. Optionally, such a computer is directly linked to a scanner or the like receiving experimentally determined signals related to expression levels. Alternatively, expression levels can be input by other means. The computer can be programmed to convert raw signals into expression levels (absolute or relative), compare measured expression levels with one or more reference expression levels, or a scale of such values, as described above. The computer can also be programmed to assign values or other designations to expression levels based on the comparison with one or more reference expression levels, and to aggregate such values or designations for multiple genes in an expression profile. The computer can also be programmed to output a value or other designation providing an indication of presence or susceptibility to SCAR as well as any of the raw or intermediate data used in determining such a value or designation.
[00142] A typically computer (see US 6,785,613 Figs. 4 and 5) includes a bus which interconnects major subsystems such as a central processor, a system memory, an input/output controller, an external device such as a printer via a parallel port, a display screen via a display adapter, a serial port, a keyboard, a fixed disk drive and a floppy disk drive operative to receive a floppy disk. Many other devices can be connected such as a scanner via I/O controller, a mouse connected to serial port or a network interface. The computer contains computer readable media holding codes to allow the computer to perform a variety of functions. These functions include controlling automated apparatus, receiving input and delivering output as described above. The automated apparatus can include a robotic arm for delivering reagents for determining expression levels, as well as small vessels, e.g., microtiter wells for performing the expression analysis.
[00143] The methods, systems, kits and compositions provided herein may also be capable of generating and transmitting results through a computer network. As shown in Figure 2, a sample (220) is first collected from a subject (e.g. transplant recipient, 210). The sample is assayed (230) and gene expression products are generated. A computer system (240) is used in analyzing the data and making classification of the sample. The result is capable of being transmitted to different types of end users via a computer network (250). In some instances, the subject (e.g. patient) may be able to access the result by using a standalone software and/or a web-based application on a local computer capable of accessing the internet (260). In some instances, the result can be accessed via a mobile application (270) provided to a mobile digital processing device (e.g. mobile phone, tablet, etc.). In some instances, the result may be accessed by physicians and help them identify and track conditions of their patients (280). In some instances, the result may be used for other purposes (290) such as education and research.
[00144] Computer program
[00145] The methods, kits, and systems disclosed herein may include at least one computer program, or use of the same. A computer program may include a sequence of instructions, executable in the digital processing device's CPU, written to perform a specified task. Computer readable instructions may be implemented as program modules, such as functions, objects, Application Programming Interfaces (APIs), data structures, and the like, that perform particular tasks or implement particular abstract data types. In light of the disclosure provided herein, those of skill in the art will recognize that a computer program may be written in various versions of various languages.
[00146] The functionality of the computer readable instructions may be combined or distributed as desired in various environments. The computer program will normally provide a sequence of instructions from one location or a plurality of locations. In various embodiments, a computer program includes, in part or in whole, one or more web applications, one or more mobile applications, one or more standalone applications, one or more web browser plug-ins, extensions, add-ins, or add-ons, or combinations thereof.
[00147] Further disclosed herein are systems for classifying one or more samples and uses thereof. The system may comprise (a) a digital processing device comprising an operating system configured to perform executable instructions and a memory device; (b) a computer program including instructions executable by the digital processing device to classify a sample from a subject comprising: (i) a first software module configured to receive a gene expression profile of one or more genes from the sample from the subject; (ii) a second software module configured to analyze the gene expression profile from the subject; and (iii) a third software module configured to classify the sample from the subject based on a classification system comprising three or more classes. At least one of the classes may be selected from transplant rejection, transplant dysfunction with no rejection and normal transplant function. At least two of the classes may be selected from transplant rejection, transplant dysfunction with no rejection and normal transplant function. All three of the classes may be selected from transplant rejection, transplant dysfunction with no rejection and normal transplant function. Analyzing the gene expression profile from the subject may comprise applying an algorithm. Analyzing the gene expression profile may comprise normalizing the gene expression profile from the subject. In some instances, normalizing the gene expression profile does not comprise quantile normalization.
[00148] Figure 4 shows a computer system (also "system" herein) 401 programmed or otherwise configured for implementing the methods of the disclosure, such as producing a selector set and/or for data analysis. The system 401 includes a central processing unit (CPU, also "processor" and "computer processor" herein) 405, which can be a single core or multi core processor, or a plurality of processors for parallel processing. The system 401 also includes memory 410 (e.g., random-access memory, read-only memory, flash memory), electronic storage unit 415 (e.g., hard disk), communications interface 420 (e.g., network adapter) for communicating with one or more other systems, and peripheral devices 425, such as cache, other memory, data storage and/or electronic display adapters. The memory 410, storage unit 415, interface 420 and peripheral devices 425 are in communication with the CPU 405 through a communications bus (solid lines), such as a motherboard. The storage unit 415 can be a data storage unit (or data repository) for storing data. The system 401 is operatively coupled to a computer network ("network") 430 with the aid of the communications interface 420. The network 430 can be the Internet, an internet and/or extranet, or an intranet and/or extranet that is in communication with the Internet. The network 430 in some instances is a telecommunication and/or data network. The network 430 can include one or more computer servers, which can enable distributed computing, such as cloud computing. The network 430 in some instances, with the aid of the system 401, can implement a peer-to-peer network, which may enable devices coupled to the system 401 to behave as a client or a server.
[00149] The system 401 is in communication with a processing system 435. The processing system 435 can be configured to implement the methods disclosed herein. In some examples, the processing system 435 is a nucleic acid sequencing system, such as, for example, a next generation sequencing system (e.g., Illumina sequencer, Ion Torrent sequencer, Pacific Biosciences sequencer). The processing system 435 can be in
communication with the system 401 through the network 430, or by direct (e.g., wired, wireless) connection. The processing system 435 can be configured for analysis, such as nucleic acid sequence analysis.
[00150] Methods as described herein can be implemented by way of machine (or computer processor) executable code (or software) stored on an electronic storage location of the system 401, such as, for example, on the memory 410 or electronic storage unit 415. During use, the code can be executed by the processor 405. In some examples, the code can be retrieved from the storage unit 415 and stored on the memory 410 for ready access by the processor 405. In some situations, the electronic storage unit 415 can be precluded, and machine-executable instructions are stored on memory 410.
[00151] Digital processing device
[00152] The methods, kits, and systems disclosed herein may include a digital processing device, or use of the same. In further embodiments, the digital processing device includes one or more hardware central processing units (CPU) that carry out the device's functions. In still further embodiments, the digital processing device further comprises an operating system configured to perform executable instructions. In some embodiments, the digital processing device is optionally connected a computer network. In further embodiments, the digital processing device is optionally connected to the Internet such that it accesses the World Wide Web. In still further embodiments, the digital processing device is optionally connected to a cloud computing infrastructure. In other embodiments, the digital processing device is optionally connected to an intranet. In other embodiments, the digital processing device is optionally connected to a data storage device.
[00153] In accordance with the description herein, suitable digital processing devices include, by way of non-limiting examples, server computers, desktop computers, laptop computers, notebook computers, sub-notebook computers, netbook computers, netpad computers, set-top computers, handheld computers, Internet appliances, mobile smartphones, tablet computers, personal digital assistants, video game consoles, and vehicles. Those of skill in the art will recognize that many smartphones are suitable for use in the system described herein. Those of skill in the art will also recognize that select televisions, video players, and digital music players with optional computer network connectivity are suitable for use in the system described herein. Suitable tablet computers include those with booklet, slate, and convertible configurations, known to those of skill in the art.
[00154] The digital processing device will normally include an operating system configured to perform executable instructions. The operating system is, for example, software, including programs and data, which manages the device's hardware and provides services for execution of applications. Those of skill in the art will recognize that suitable server operating systems include, by way of non-limiting examples, FreeBSD, OpenBSD, NetBSD , Linux, Apple® Mac OS X Server®, Oracle® Solaris®, Windows Server®, and Novell® NetWare®. Those of skill in the art will recognize that suitable personal computer operating systems include, by way of non-limiting examples, Microsoft® Windows®, Apple® Mac OS X®, UNIX®, and UNIX-like operating systems such as GNU/Linux®. In some embodiments, the operating system is provided by cloud computing. Those of skill in the art will also recognize that suitable mobile smart phone operating systems include, by way of non-limiting examples, Nokia® Symbian® OS, Apple® iOS®, Research In Motion®
BlackBerry OS®, Google® Android®, Microsoft® Windows Phone® OS, Microsoft® Windows Mobile® OS, Linux®, and Palm® WebOS®
[00155] The device generally includes a storage and/or memory device. The storage and/or memory device is one or more physical apparatuses used to store data or programs on a temporary or permanent basis. In some embodiments, the device is volatile memory and requires power to maintain stored information. In some embodiments, the device is nonvolatile memory and retains stored information when the digital processing device is not powered. In further embodiments, the non-volatile memory comprises flash memory. In some embodiments, the non-volatile memory comprises dynamic random-access memory (DRAM). In some embodiments, the non-volatile memory comprises ferroelectric random access memory (FRAM). In some embodiments, the non-volatile memory comprises phase- change random access memory (PRAM). In other embodiments, the device is a storage device including, by way of non-limiting examples, CD-ROMs, DVDs, flash memory devices, magnetic disk drives, magnetic tapes drives, optical disk drives, and cloud computing based storage. In further embodiments, the storage and/or memory device is a combination of devices such as those disclosed herein.
[00156] A display to send visual information to a user will normally be initialized.
Examples of displays include a cathode ray tube (CRT, a liquid crystal display (LCD), a thin film transistor liquid crystal display (TFT-LCD, an organic light emitting diode (OLED) display. In various further embodiments, on OLED display is a passive-matrix OLED (PMOLED) or active-matrix OLED (AMOLED) display. In some embodiments, the display may be a plasma display , a video projector or a combination of devices such as those disclosed herein.
[00157] The digital processing device would normally include an input device to receive information from a user. The input device may be, for example, a keyboard, a pointing device including, by way of non-limiting examples, a mouse, trackball, track pad, joystick, game controller, or stylus;a touch screen, or a multi-touch screen, a microphone to capture voice or other sound input, a video camera to capture motion or visual input or a combination of devices such as those disclosed herein.
[00158] Non-transitory computer readable storage medium
[00159] The methods, kits, and systems disclosed herein may include one or more non- transitory computer readable storage media encoded with a program including instructions executable by the operating system to perform and analyze the test described herein;
preferably connected to a networked digital processing device. The computer readable storage medium is a tangible component of a digital that is optionally removable from the digital processing device. The computer readable storage medium includes, by way of non- limiting examples, CD-ROMs, DVDs, flash memory devices, solid state memory, magnetic disk drives, magnetic tape drives, optical disk drives, cloud computing systems and services, and the like. In some instances, the program and instructions are permanently, substantially permanently, semi-permanently, or non-transitorily encoded on the media.
[00160] A non-transitory computer-readable storage media may be encoded with a computer program including instructions executable by a processor to create or use a classification system. The storage media may comprise (a) a database, in a computer memory, of one or more clinical features of two or more control samples, wherein (i) the two or more control samples may be from two or more subjects; and (ii) the two or more control samples may be differentially classified based on a classification system comprising three or more classes; (b) a first software module configured to compare the one or more clinical features of the two or more control samples; and (c) a second software module configured to produce a classifier set based on the comparison of the one or more clinical features.
[00161 ] At least two of the classes may be selected from transplant rejection, transplant dysfunction with no rejection and normal transplant function. All three classes may be selected from transplant rejection, transplant dysfunction with no rejection and normal transplant function. The storage media may further comprise one or more additional software modules configured to classify a sample from a subject. Classifying the sample from the subject may comprise a classification system comprising three or more classes. At least two of the classes may be selected from transplant rejection, transplant dysfunction with no rejection and normal transplant function. All three classes may be selected from transplant rejection, transplant dysfunction with no rejection and normal transplant function.
[00162] Web application
[00163] In some embodiments, a computer program includes a web application. In light of the disclosure provided herein, those of skill in the art will recognize that a web application, in various embodiments, utilizes one or more software frameworks and one or more database systems. In some embodiments, a web application is created upon a software framework such as Microsoft® .NET or Ruby on Rails (RoR). In some embodiments, a web application utilizes one or more database systems including, by way of non-limiting examples, relational, non-relational, object oriented, associative, and XML database systems. In further embodiments, suitable relational database systems include, by way of non-limiting examples, Microsoft® SQL Server, mySQL™, and Oracle®. Those of skill in the art will also recognize that a web application, in various embodiments, is written in one or more versions of one or more languages. A web application may be written in one or more markup languages, presentation definition languages, client-side scripting languages, server-side coding languages, database query languages, or combinations thereof. In some embodiments, a web application is written to some extent in a markup language such as Hypertext Markup Language (HTML), Extensible Hypertext Markup Language (XHTML), or extensible Markup Language (XML). In some embodiments, a web application is written to some extent in a presentation definition language such as Cascading Style Sheets (CSS). In some embodiments, a web application is written to some extent in a client-side scripting language such as Asynchronous Javascript and XML (AJAX), Flash® Actionscript, Javascript, or Silverlight®. In some embodiments, a web application is written to some extent in a server- side coding language such as Active Server Pages (ASP), ColdFusion®, Perl, Java™, JavaServer Pages (JSP), Hypertext Preprocessor (PHP), Python™, Ruby, Tel, Smalltalk, WebDNA®, or Groovy. In some embodiments, a web application is written to some extent in a database query language such as Structured Query Language (SQL). In some
embodiments, a web application integrates enterprise server products such as IBM® Lotus Domino®. In some embodiments, a web application includes a media player element. In various further embodiments, a media player element utilizes one or more of many suitable multimedia technologies including, by way of non-limiting examples, Adobe® Flash®, HTML 5, Apple® QuickTime®, Microsoft® Silverlight®, Java™, and Unity®. [00164] Mobile application
[00165] In some embodiments, a computer program includes a mobile application provided to a mobile digital processing device. In some embodiments, the mobile application is provided to a mobile digital processing device at the time it is manufactured. In other embodiments, the mobile application is provided to a mobile digital processing device via the computer network described herein.
[00166] In view of the disclosure provided herein, a mobile application is created by techniques known to those of skill in the art using hardware, languages, and development environments known to the art. Those of skill in the art will recognize that mobile applications are written in several languages. Suitable programming languages include, by way of non-limiting examples, C, C++, C#, Objective-C, Java™, Javascript, Pascal, Object Pascal, Python™, Ruby, VB.NET, WML, and XHTML/HTML with or without CSS, or combinations thereof.
[00167] Suitable mobile application development environments are available from several sources. Commercially available development environments include, by way of non-limiting examples, AirplaySD , alcheMo, Appcelerator®, Celsius, Bedrock, Flash Lite, .NET Compact Framework, Rhomobile, and WorkLight Mobile Platform. Other development environments are available without cost including, by way of non-limiting examples, Lazarus, MobiFlex, MoSync, and Phonegap. Also, mobile device manufacturers distribute software developer kits including, by way of non-limiting examples, iPhone and iPad (iOS) SDK, Android™ SDK, BlackBerry® SDK, BREW SDK, Palm® OS SDK, Symbian SDK, webOS SDK, and Windows® Mobile SDK.
[00168] Those of skill in the art will recognize that several commercial forums are available for distribution of mobile applications including, by way of non-limiting examples, Apple® App Store, Android™ Market, BlackBerry® App World, App Store for Palm devices, App Catalog for webOS, Windows® Marketplace for Mobile, Ovi Store for Nokia® devices, Samsung® Apps, and Nintendo® DSi Shop.
[00169] Standalone application
[00170] In some embodiments, a computer program includes a standalone application, which is a program that is run as an independent computer process, not an add-on to an existing process, e.g., not a plug-in. Those of skill in the art will recognize that standalone applications are often compiled. A compiler is a computer program(s) that transforms source code written in a programming language into binary object code such as assembly language or machine code. Suitable compiled programming languages include, by way of non-limiting examples, C, C++, Objective-C, COBOL, Delphi, Eiffel, Java™, Lisp, Python™, Visual Basic, and VB .NET, or combinations thereof. Compilation is often performed, at least in part, to create an executable program. In some embodiments, a computer program includes one or more executable complied applications.
[00171 ] Web browser plug-in
[00172] In some embodiments, the computer program includes a web browser plug-in. In computing, a plug-in is one or more software components that add specific functionality to a larger software application. Makers of software applications support plug-ins to enable third- party developers to create abilities which extend an application, to support easily adding new features, and to reduce the size of an application. When supported, plug-ins enable customizing the functionality of a software application. For example, plug-ins are commonly used in web browsers to play video, generate interactivity, scan for viruses, and display particular file types. Those of skill in the art will be familiar with several web browser plug- ins including, Adobe® Flash® Player, Microsoft® Silverlight®, and Apple® QuickTime®. In some embodiments, the toolbar comprises one or more web browser extensions, add-ins, or add-ons. In some embodiments, the toolbar comprises one or more explorer bars, tool bands, or desk bands.
[00173] In view of the disclosure provided herein, those of skill in the art will recognize that several plug-in frameworks are available that enable development of plug-ins in various programming languages, including, by way of non-limiting examples, C++, Delphi, Java™, PHP, Python™, and VB .NET, or combinations thereof.
[00174] Web browsers (also called Internet browsers) are software applications, designed for use with network-connected digital processing devices, for retrieving, presenting, and traversing information resources on the World Wide Web. Suitable web browsers include, by way of non-limiting examples, Microsoft® Internet Explorer®, Mozilla® Firefox®, Google® Chrome, Apple® Safari®, Opera Software® Opera®, and KDE Konqueror. In some embodiments, the web browser is a mobile web browser. Mobile web browsers (also called mircrobrowsers, mini-browsers, and wireless browsers) are designed for use on mobile digital processing devices including, by way of non-limiting examples, handheld computers, tablet computers, netbook computers, subnotebook computers, smartphones, music players, personal digital assistants (PDAs), and handheld video game systems. Suitable mobile web browsers include, by way of non-limiting examples, Google® Android® browser, RIM BlackBerry® Browser, Apple® Safari®, Palm® Blazer, Palm® WebOS® Browser, Mozilla® Firefox® for mobile, Microsoft® Internet Explorer® Mobile, Amazon® Kindle® Basic Web, Nokia® Browser, Opera Software® Opera® Mobile, and Sony® PSP™ browser.
[00175] Software modules
[00176] The methods, kits, and systems disclosed herein may include software, server, and/or database modules, or use of the same. In view of the disclosure provided herein, software modules are created by techniques known to those of skill in the art using machines, software, and languages known to the art. The software modules disclosed herein are implemented in a multitude of ways. In various embodiments, a software module comprises a file, a section of code, a programming object, a programming structure, or combinations thereof. In further various embodiments, a software module comprises a plurality of files, a plurality of sections of code, a plurality of programming objects, a plurality of programming structures, or combinations thereof. In various embodiments, the one or more software modules comprise, by way of non-limiting examples, a web application, a mobile application, and a standalone application. In some embodiments, software modules are in one computer program or application. In other embodiments, software modules are in more than one computer program or application. In some embodiments, software modules are hosted on one machine. In other embodiments, software modules are hosted on more than one machine. In further embodiments, software modules are hosted on cloud computing platforms. In some embodiments, software modules are hosted on one or more machines in one location. In other embodiments, software modules are hosted on one or more machines in more than one location.
[00177] Databases
[00178] The methods, kits, and systems disclosed herein may comprise one or more databases, or use of the same. In view of the disclosure provided herein, those of skill in the art will recognize that many databases are suitable for storage and retrieval of information pertaining to gene expression profiles, sequencing data, classifiers, classification systems, therapeutic regimens, or a combination thereof. In various embodiments, suitable databases include, by way of non-limiting examples, relational databases, non-relational databases, object oriented databases, object databases, entity-relationship model databases, associative databases, and XML databases. In some embodiments, a database is internet-based. In further embodiments, a database is web-based. In still further embodiments, a database is cloud computing-based. In other embodiments, a database is based on one or more local computer storage devices.
[00179] Data transmission
[00180] The methods, kits, and systems disclosed herein may be used to transmit one or more reports. The one or more reports may comprise information pertaining to the classification and/or identification of one or more samples from one or more subjects. The one or more reports may comprise information pertaining to a status or outcome of a transplant in a subject. The one or more reports may comprise information pertaining to therapeutic regimens for use in treating transplant rejection in a subject in need thereof. The one or more reports may comprise information pertaining to therapeutic regimens for use in treating transplant dysfunction in a subject in need thereof. The one or more reports may comprise information pertaining to therapeutic regimens for use in suppressing an immune response in a subject in need thereof.
[00181] The one or more reports may be transmitted to a subject or a medical representative of the subject. The medical representative of the subject may be a physician, physician's assistant, nurse, or other medical personnel. The medical representative of the subject may be a family member of the subject. A family member of the subject may be a parent, guardian, child, sibling, aunt, uncle, cousin, or spouse. The medical representative of the subject may be a legal representative of the subject.
EXAMPLES
[00182] The following examples are offered to illustrate, but not to limit the present invention.
Example 1 Materials and methods
[00183] This Example describes some of the materials and methods employed in identification of differentially expressed genes in SCAR. [00184] The discovery set of samples consisted of the following biopsy-documented peripheral blood samples. 69 PAXgene whole blood samples were collected from kidney transplant patients. The samples were histology confirmed, and comprised 3 different phenotypes: (1 ) Acute Rejection (AR; n=21 ); (2) Sub-Clinical Acute Rejection (SCAR; n=23); and (3) Transplant Excellent (TX; n=25). Specifically, SCAR was defined by a protocol biopsy done on a patient with totally stable kidney function and the light histology revealed unexpected evidence of acute rejection ( 16 "Borderline", 7 Banff 1 A). The SCAR samples consisted of 3 month and 1 year protocol biopsies, whereas the TXs were predominantly 3 month protocol biopsies. The mean age of the patients is 49.3 years (ranging from 22-71 ); 35% female; 52% deceased donors. Table 5 presents time to biopsies where time is defined as days post transplantation. All the AR biopsies were "for cause" where clinical indications like a rise in serum creatinine prompted the need for a biopsy. All patients were induced with Thymoglobulin.
Example 2 Gene expression profiling and data analysis
[00185] All samples were processed on the Affymetrix HG-U 133 PM only peg microarrays. To eliminate low expressed signals we used a signal filter cut-off that was data dependent, and therefore expression signals < Log2 3.74 (median signals on all arrays) in all samples were eliminated leaving us with 48734 probe sets from a total of 54721 probe sets. We performed a 3-way ANOVA analysis of AR vs. ADNR vs. TX. This yielded over 6000 differentially expressed probesets at a p-value O.001 . Even when a False Discovery rate cut-off of (FDR <10%), was used it gave us over 2700 probesets. The corresponding genes for 2156 probes are listed in Table 4. Therefore for the purpose of a diagnostic signature we used the top 200 differentially expressed probe sets (Table 2) to build predictive models that could differentiate the three classes. The top 200 probesets have FDR values of <0.05%. We used three different predictive algorithms, namely Diagonal Linear Discriminant Analysis (DLDA), Nearest Centroid (NC) and Support Vector Machines (SVM) to build the predictive models. We ran the predictive models using two different methodologies and calculated the Area Under the Curve (AUC). SVM, DLDA and NC picked classifier sets of 200, 192 and 188 probesets as the best classifiers. Since there was very little difference in the AUC's we decided to use all 200 probesets as classifiers for all methods. We also demonstrated that these results were not the consequence of statistical over-fitting by using the replacement method of Harrell to perform a version of 1000-test cross-validation. Table 1 shows the performance of these classifier sets using both one-level cross validation as well as the Optimism Corrected Bootstrapping (1000 data sets).
[00186] An important point here is that in real clinical practice the challenge is actually not to distinguish SCAR from AR because generally only AR presents with a significant increase in baseline serum creatinine. The real challenge is to take a patient with normal and stable creatinine and diagnose the hidden SCAR without having to depend on invasive and expensive protocol biopsies that cannot be done frequently in any case. Though we have already successfully done this using our 3-way analysis, we also tested a 2-way prediction of SCAR vs. TX. The point was to further validate that a phenotype as potentially subtle clinically as SCAR can be truly distinguished from TX. At a p-value <0.001 , there were 33 probesets whose expression signals highly differentiated SCAR and TX, a result in marked contrast with the >2500 probesets differentially expressed between AR vs. TX at that same p-value. (Figure 3 shows the hierarchical clustering of gene expression profiling of these 33 probesets. ) However, when these 33 probesets (Table 3) were used in NC to predict SCAR and TX creating a 2-way classifier, the predictive accuracies with a one-level cross- validation was 96% and with the Harrell 1000 test optimism correction it was 94%. Thus, we are confident that we can distinguish SCAR, TX and AR by peripheral blood gene expression profiling using this proof of principle data set.
Example 3 Microarray and NGS analyses
[00187] This Example describes the identification of differentially expressed genes in SCAR using microarray and next-generation sequencing (NGS) analyses.
[00188] Biopsy samples
[00189] To compare the methods using blood and biopsy samples, we performed microarray and NGS analyses on the blood and biopsy samples from the same kidney transplant patients. The discovery set of blood samples consisted of the following biopsy samples. 68 biopsy samples were collected from kidney transplant patients. The samples were histology confirmed, and comprised 3 different phenotypes: (1) Acute Rejection (AR; n=21 ); (2) Sub-Clinical Acute Rejection (SCAR; n=22); and (3) Transplant Excellent (TX; n=25). The specific sample characterizations and methods were described in Example 1.
[00190] Microarray Analyses - biopsy samples [00191] All samples were processed on the HG-U 133 Plus PM microarrays. All samples were normalized using RMA in Partek Genomics Suite 6.6. To facilitate biomarker discovery by removing probe sets with low signal intensities we used a signal filter cut-off that was data dependent, and therefore expression signals < Log2 4.14 (median signals on all arrays) in all samples were eliminated leaving us with 27980 probe sets representing about 13900 genes.
[00192] We first performed a 3-way 1 -step ANOVA analysis of AR vs. SCAR (subAR) vs. TX. A False Discovery rate cut-off of (FDR) 1% was set, and after Bonferroni correction of Phenotype (AR vs. SCAR vs. TX) p-values, 1 195 genes were selected. Nearest Centroid Algorithm in Partek were used to identify best classifier set that can distinguish all three phenotypes. We demonstrated that the method has an overall predictive accuracy of 85%. As shown in Table 6, the method correctly classified most samples. When Nearest Centroid (NC) was used to predict TX vs. AR, the results showed predictive accuracy of 100%, sensitivity of 100%, specificity of 100%, positive predictive value of 100%, negative predictive value of 100%, and AUC of .0. In TX vs. SCAR (subAR), the results showed predictive accuracy of 78%, sensitivity of 81 %, specificity of 75%, positive predictive value of 84%o, negative predictive value of 71%, and AUC of 0.785. Similarly, in AR vs. SCAR (subAR) 2-way classifier, the results showed predictive accuracy of 76%, sensitivity of 76%, specificity of 75%, positive predictive value of 80%, negative predictive value of 71 %, and AUC of 0.768. Thus, we are confident that we can distinguish SCAR, TX and AR by biopsy sample gene expression profiling using the 3-way 1-step analysis.
[00193] We then performed a 2-way 2-step ANOVA analysis. Because of the
disproportionate distribution (only 46 probesets that differentiate SCAR from TX compared to AR vs. TX (10834 probesets) and AR vs. SCAR (2067 probesets)), we decided to test a 2- step approach where we combined SCAR+AR vs. TX to clearly separate a SCAR or AR from TX as the first step. The second step was using the SCAR vs AR genes to separate the SCARs from the ARs.
[00194] We used the 4598 (SCAR+AR vs TX) and the 745 (SCAR vs. AR) unique genes (1322 genes were common between the two groups) to build 2-way classifiers. Nearest Centroid (NC) was used as a two-step prediction. The top 300 genes (based on p-value) for the first step (AR+subAR vs. TX) are listed in Table 7. The top 300 genes (based on p-value) for the second step (AR vs. subAR) are listed in Table 8. [00195] The method correctly classified most samples with an overall predictive accuracy of 94%. As shown in Table 9, in TX vs. AR, the results showed predictive accuracy of 97%, sensitivity of 100%, specificity of 94%, positive predictive value of 95%, negative predictive value of 100%, and AUC of 0.965. In TX vs. SCAR (subAR), the results showed predictive accuracy of 95%, sensitivity of 100%, specificity of 90%, positive predictive value of 91 %, negative predictive value of 100%, and AUC of 0.947. Similarly, in AR vs. SCAR (subAR) 2-way classifier, the results showed predictive accuracy of 86%, sensitivity of 90%, specificity of 81%, positive predictive value of 81%, negative predictive value of 90%, and AUC of 0.862. Thus, we are confident that we can distinguish SCAR, TX and AR by biopsy sample gene expression profiling using the 2-way 2-step analysis.
[00196] NGS Analyses - biopsy samples
[00197] All samples were processed on the ION PROTON™ System. Only runs with > 10 million reads were used for analysis. There was an average of 16 million reads across all samples. Samples were aligned using the STAR aligner (Dobin et al, Bioinformatics 2012). Differential expression of noramlized (DESeq2 Values) was done using ANOVA in Partek. Samples were first filtered for a minimum of 5 cpm per gene. After filtering, 13191 genes (56%) were eligible for analysis. The same 1 and 2 step methodologies described in the microarray section were tested. When comparing microarray with NGS analyses using biopsy samples at FDR < 10% in both cases , 8862 probe sets were identified in microarray analysis, while only 2058 probe sets were identified.
[00198] Briefly, the 3-way 1 -step method has an overall predictive accuracy of 81 %. As shown in Table 10, the method correctly classified most samples. In TX v. AR a, the results showed predictive accuracy of 97%, sensitivity of 100%, specificity of 92%, positive predictive value of 95%, negative predictive value of 100%), and AUC of 0.967. In TX vs. SCAR (subAR), the results showed predictive accuracy of 80%, sensitivity of 72%, specificity of 83%, positive predictive value of 72%, negative predictive value of 91 %, and AUC of 0.795. Similarly, in AR vs. SCAR (subAR), the results showed predictive accuracy of 69%, sensitivity of 58%>, specificity of 79% positive predictive value of 79%, negative predictive value of 59%o, and AUC of 0.689. Thus, we are confident that we can distinguish SCAR, TX and AR from biopsy samples using the next-generation sequencing 3-way 1 -step analysis. [00199] We then performed a 2-way 2-step analysis. Similar to the microarray 2-way 2- step analysis, there was a disproportionate distribution: there are only 5 genes that differentiate SCAR from TX compared to AR vs. TX (1510 genes) and AR vs. SCAR (132 genes). And thus, we decided to test a 2-step approach where we combined SCAR+AR vs. TX to clearly separate a SCAR or AR from TX as the first step. The top 200 probe sets (ranked on p-value) of the biopsy NGS signatures for the first step (SCAR+AR vs. TX) is listed in Table 1 1 . The second step was using the SCAR vs AR genes to separate the SCARs from the ARs. The top 160 probe sets (ranked on p-value) of the biopsy NGS signatures for the second step (SCAR vs. AR) is listed in Table 12. As shown in Table 13, when Nearest Centroid (NC) was used as a two-step prediction in the AR and TX 2-way classifier, the results showed predictive accuracy of 95%, sensitivity of 100%, specificity of 88%o, positive predictive value of 92%, negative predictive value of 100%, and AUC of 0.943. In the SCAR (subAR) and TX 2-way classifier, the results showed predictive accuracy of 100%, sensitivity of 100%), specificity of 100%, positive predictive value of 100%, negative predictive value of 100%, and AUC of 1.000. Similarly, in the AR and SCAR (subAR) 2- way classifier, the results showed predictive accuracy of 79%, sensitivity of 76%, specificity of 83%, positive predictive value of 83%, negative predictive value of 72%, and AUC of 0.792. The method correctly classified most samples with an overall predictive accuracy of 91 %. Thus, we are confident that we can distinguish SCAR, TX and AR by biopsy sample gene expression profiling using the 2-way 2-step analysis.
[00200] Next, to show the correlation between the probe sets identified in microarray and NGS analyses, we performed correlation analyses on 1 ) the 1066 genes common to both microarray and NGS (both differentially expressed at FDR < 1 %); and 2) all the 7076 NGS expressed genes (above threshold).
[00201] We first performed correlation analyses on the 1066 genes common to both microarray and NGS. The genes were found to be highly correlated in correlation of fold- change in directionality analysis, 1063 out of the 1066 genes (99.8%) were found in agreement for AR vs. TX; 1063 out of the 1066 genes (99.8%>) were found in agreement for AR vs. SCAR; 1 042 out of the 1066 genes (97.8%) were found in agreement for AR vs. TX. We also plotted correlation of absolute fold changes of the 1066 genes in Figure 5 and generated the heat map showing the clustering of this high correlation in Figure 6. [00202] We then performed correlation analyses on all the 7076 NGS expressed genes. In correlation of fold-change in directionality analysis, 5747 out of the 7076 genes (81.2%) were found in agreement for AR vs. TX; 6080 out of the 7076 genes (85.9%) were found in agreement for AR vs. SCAR; 5652 out of the 7076 genes (79.8%>) were found in agreement for AR vs. TX. We also plotted correlation of absolute fold changes of the 7076 NGS expressed genes in Figure 7.
[00203] Blood samples
[00204] To compare the methods using blood and biopsy samples, we also performed the microarray and NGS analyses on the blood samples from the same kidney transplant patients. Specifically, 68 PAXgene whole blood samples were collected from kidney transplant patients. As described earlier, the samples were histology confirmed, and comprised 3 different phenotypes: (1 ) Acute Rejection (AR; n=21); (2) Sub-Clinical Acute Rejection (SCAR; n=22); and (3) Transplant Excellent (TX; n=25).
[00205] Microarray Analyses - blood samples
[00206] All samples were processed the same way as the biopsy microarray samples. We first performed a 3-way 1 -step ANOVA analysis of AR vs. SCAR (subAR) vs. TX. Nearest Centroid Algorithm in Partek were used to identify best classifier set that can distinguish all three phenotypes. The full 818 probe sets ranked by p-value are listed in Table 14 and the best performing 61 probe sets gene signature picked by the Nearest Centroid Algorithm are listed in Table 15.
[00207] We demonstrated that the 3-way 1 -step analysis has an overall predictive accuracy of 91%>. As shown in Table 16, the method correctly classified most samples. In the AR and TX 2-way classifier, the results showed predictive accuracy of 90%, sensitivity of 95%, specificity of 85%, positive predictive value of 86%, negative predictive value of 94%, and AUC of 0.898. In the SCAR (subAR) and TX 2-way classifier, the results showed predictive accuracy of 91 %), sensitivity of 95%>, specificity of 87%, positive predictive value of 86%, negative predictive value of 95%, and AUC of 0.912. Similarly, in the AR and SCAR (subAR) 2-way classifier, the results showed predictive accuracy of 91%), sensitivity of 88%, specificity of 94%, positive predictive value of 95%, negative predictive value of 85%, and AUC of 0.905. Thus, we are confident that we can distinguish SCAR, TX and AR by peripheral blood gene expression profiling using this data set.
[00208] NGS Analyses - blood samples [00209] All samples were processed the same way as the biopsy NGS samples. We first performed a 3-way 1 -step ANOVA analysis of AR vs. SCAR (subAR) vs. TX. Nearest Centroid Algorithm in Partek were used to identify best classifier set that can distinguish all three phenotypes. The full 123 probe sets (p<0.01 ) ranked by p-value are listed in Table 17 and the best performing 53 probe sets gene signature picked by the Nearest Centroid Algorithm are listed in Table 18. Among the gene signatures in Table 18, JUP, XCL1 , CRADD, XCL1 /XCL2, PRNP, HHEX, FAM43A, and PSMD6-AS2 Were also differentially expressed (p<0.05) in the microarray comparisons.
[00210] We demonstrated that the 3-way 1 -step analysis has an overall predictive accuracy of 89%. As shown in Table 19, the method correctly classified most samples. In the AR and TX 2-way classifier, the results showed predictive accuracy of 92%, sensitivity of 95%, specificity of 90%, positive predictive value of 90%, negative predictive value of 95%, and AUC of 0.921 . In the SCAR (subAR) and TX 2-way classifier, the results showed predictive accuracy of 83%, sensitivity of 83%, specificity of 82%, positive predictive value of 83%, negative predictive value of 82%, and AUC of 0.829. Similarly, in the AR and SCAR (subAR) 2-way classifier, the results showed predictive accuracy of 93%, sensitivity of 94%, specificity of 95%, positive predictive value of 94%, negative predictive value of 95%, and AUC of 0.943. Thus, we are confident that we can distinguish SCAR, TX and AR by peripheral blood gene expression profiling using this data set.
[00211] Next, similar to the biopsy sample analyses, to show the correlation between the probe sets identified in microarray and NGS analyses, we performed correlation analyses on 1 ) the 101 genes differentially expressed in both microarray and NGS; and 2) all the 7076 NGS expressed genes (above threshold).
[00212] We performed correlation analyses on the 101 genes common to both microarray and NGS. The genes were found to be highly correlated in correlation of fold-change in directionality analysis, 94 out of the 101 genes (93.8%) were found in agreement for AR vs. TX; 100 out of the 101 genes (99.0%) were found in agreement for AR vs. SCAR; 79 out of the 101 genes (78.2%) were found in agreement for AR vs. TX.
[00213] Conclusions - microarray vs. NGS
[00214] The comparison demonstrated that microarrays and NGS perform similarly with respect to predictions of phenotypes. Both methods have very high correlation with fold- change especially amongst significantly differentially expressed genes. [00215] It is understood that the examples and embodiments described herein are for il lustrative purposes only and that various modifications or changes in light thereof will be suggested to persons skilled in the art and are to be included within the spirit and purview of this application and scope of the appended claims. Although any methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention, the preferred methods and materials are described.
[00216] All publications, GenBank sequences, ATCC deposits, patents and patent applications cited herein are hereby expressly incorporated by reference in their entirety and for all purposes as if each is individual ly so denoted.
Table 1 . Blood Expression Profiling of Kidney Transplants: 3-Way Classifier AR vs. SCAR vs. TX
Table 2. 200 Probeset ciassifer for distinguishing AR, SCAR and TX based on a 3-way ANOVA
21 243878 PM at — 2.19E-07 5.08E-04 76.1 39.7 39.5
22 233296 PM x at — 2.33E-07 5.17E-04 347.7 251.5 244.7
DDB1 and CUL4
23 243318 PM at DCAF8 associated factor 8 2.52E-07 5.34E-04 326.2 229.5 230.2
24 236354 PM at — 3.23E-07 6.39E-04 47.1 31.2 27.8
1142.
25 243768 PM at 3.35E-07 6.39E-04 0 730.6 768.5
26 238558 PM at — 3.65E-07 6.39E-04 728.5 409,4 358.4
27 237825 PM x at — 3.66E-07 6.39E-04 34.2 20.9 19.9
28 244414 PM at — 3.67E-07 6.39E-04 548,7 275.2 284.0
29 215221 PM at — 4.06E-07 6.83E-04 327.2 176.7 171.9
30 235912 PM at — 4.46E-07 7.25E-04 114.1 71.4 59.5
31 239348 PM at 4.87E-07 7.54E-04 20.1 14.5 13.4
32 240499 PM at — 5.06E-07 7.54E-04 271.4 180.1 150.2
33 208054 PM at HERC4 hect domain and RLD 4 5.11E-07 7.54E-04 114.9 57.6 60.0
34 240263 PM at — — 5.46E-07 7.81E-04 120.9 78.7 66.6
35 241303 PM x at — — 5.78E-07 7.81E-04 334.5 250.3 261.5
36 233692 PM at 5.92E-07 7.81E-04 22.4 15.5 15.0
37 243561 PM at — 5.93E-07 7.81E-04 341.1 215.1 207.3
38 232778 PM at — 6.91E-07 8.86E-04 46.5 31.0 28.5
39 237632 PM at — 7.09E-07 8.86E-04 108.8 61.0 57.6
40 233690 PM at — 7.30E-07 8.89E-04 351.1 222.7 178.1 vacuolar protein sorting
13 homolog D (S.
41 220221 PM at VPS13D cerevisiae) 7.50E-07 8.89E-04 93.5 60.0 59.9
42 242877 PM at 1 — 7.72E-07 8.89E-04 173.8 108.1 104.0
TSR1, 20S rRNA
accumulation, homolog
43 218155 PM x at TSR1 (S. cerevisiae) 7.86E-07 8.89E-04 217.2 165.6 164.7
44 239603 PM x at 8.24E-07 8.89E-04 120.9 75.5 81.1
45 242859 PM at — 8.48E-07 8.89E-04 221.1 135.4 138.3
46 240866 PM at — 8.54E-07 8.89E-04 65.7 33.8 35.2
47 239661 PM at — 8.72E-07 8.89E-Q4 100.5 48.3 45.2 chromosome 18 open
48 224493 PM x at C18orf45 reading frame 45 8.77E-07 8.89E-04 101.8 78.0 89.7
1569202_PM_x_
49 at 8.98E-07 8.89E-04 23.3 18.5 16.6
50 1560474 PM at — 9.12E-07 8.89E-04 25.2 17.8 18.5
51 232511 PM at 9.48E-07 9.06E-04 77.2 46.1 49.9 leucine-rich repeats
and calponin homology
(CH) domain containing
52 228119 PM at LRCH3 3 1.01E-06 9.51E-04 117.2 84.2 76.1
53 228545 PM at ZNF148 zinc finger protein 148 1.17E-06 9.99E-04 789.9 571.1 579.7
54 232779 PM at — 1.17E-06 9.99E-04 36.7 26.0 20.7
55 239005 PM at FU39739 Hypothetical FLJ39739 1.18E-06 9.99E-04 339.1 203.7 177.7 leucine rich repeat
containing 37, member
56 244478 PM at LRRC37A3 A3 1.20E-06 9.99E-04 15.7 12.6 12.7
57 244535 PM at — 1.28E-06 9.99E-04 261.5 139.5 137.8
58 1562673 PM at — 1.28E-06 9.99E-04 77.4 46.5 51.8
59 240601 PM at — 1.29E-06 9.99E-04 212.6 107.7 97.7
G protein-coupled
60 239533 PM at GPR155 receptor 155 1.30E-06 9.99E-04 656.3 396.7 500.1 61 222358 PM x at 1.32E-06 9.99E-04 355.2 263.1 273.7
62 214707 PM x at ALMS1 Alstrom syndrome 1 1.32E-06 9.99E-04 340.2 255.9 266.0
63 236435 PM at — 1.32E-06 9.99E-04 144.0 92.6 91.1
64 232333 PM at — 1.33E-06 9.99E-04 487.7 243.7 244.3 032202
TUS2015/032202
Ras homolog enriched
140 201453 P x at RHEB in brain 5.76E-06 1.99E-03 453.3 600.0 599.0
141 236802 PM at — — 5.76E-06 1.99E-03 47.9 29.1 29.6
4068. 3073. 2907.
142 232615 PM at 5.82E-06 1.99E-03 5 4 4 protein-L-isoaspartate
(D-aspartate) 0- methyitransferase
143 237179 PM at PCMTD2 domain containing 2 5.84E-06 1.99E-03 48.7 30.2 26.8
144 203255 PM at FBX011 F-box protein 11 5.98E-06 2.02E-03 748.3 529.4 539.6 sphingomyelin synthase
145 212989_PM_at SGMS1 1 6.04E-06 2.03E-03 57.2 93.1 107.9 protein phosphatase 1,
regulatory (inhibitor)
146 236754 PM at PPP1R2 subunit 2 6.17E-06 2.05E-03 505.3 380.7 370.1 pyrophosphatase
147 1559496 PM at PPA2 (inorganic) 2 6.24E-06 2.05E-03 68.8 39.7 39.3
148 236494 PM x at — 6.26E-06 2.05 E-03 135.0 91.1 82.9
149 237554 PM at 6.30E-06 2.05E-03 53.4 31.5 30.1
150 243469 PM at — 6.37E-06 2.05E-03 635.2 308.1 341.5
ZNF493 zinc finger protein 493
III /// zinc finger protein
151 240155 PM x at ZNF738 738 6.45E-06 2.05E-03 483.9 299.9 316.6
ADP-ribosylation factor¬
152 222442 PM at ARL8B like 8B 6.47E-06 2.05E-03 201.5 292.6 268.3
153 240307 PM at — 6.48E-06 2.05E-03 55.4 36.8 33.1
RAB11A, member RAS
154 200864 PM s at RAB11A oncogene family 6.50E-06 2.05E-03 142.1 210.9 233.0
155 235757 PM at — 6.53E-06 2.05E-03 261.4 185.2 158.9 protein phosphatase 2,
regulatory subunit A,
156 222351 PM at PPP2R1B beta 6.58E-06 2.06E-03 75.8 51.1 45.4 round spermatid basic
157 222788 PM s at RSBN1 protein 1 6.63E-06 2.06E-03 389.9 302.7 288.2
158 239815 PM at — 6.70E-06 2.06E-03 216.9 171.4 159.5
1065.
159 219392_PM_x_at PRR11 proline rich 11 6.77E-06 2.07E-03 3 827.5 913.2
160 240458 PM at — 6.80E-06 2.07E-03 414.3 244.6 242.0
Muscleblind-like 1709. 1165. 1098.
161 235879 PM at MBNL1 (Drosophila) 6.88E-06 2.08E-03 2 5 0 headcase homolog
162 230529 PM at HECA (Drosophila) 7.08E-06 2.13E-03 585.1 364.3 418.4
KIAA1245
/// NBPF1
III
NBPF10
III
NBPF11
III KIAA1245 ///
NBPF12 neuroblastoma
III breakpoint family,
NBPF24 member 1 ///
1562063_PM_x_ /// NBPF8 neuroblastoma
163 at /// NBPF9 breakpoint fam 7.35E-06 2.20E-03 350.4 238.8 260.8
1164. 1264.
164 202769 PM at CCNG2 cyclin G2 7.42E-06 2.20E-03 697.1 0 6
1556493_PM_a_ lysine (K)-specific
165 at KDM4C demethylase 4C 7.64E-06 2.24E-03 81.4 49.0 44.5
166 216509 PM x at MLLT10 myeloid/lymphoid or 7.64E-06 2.24E-03 22.4 17.9 19.3 mixed-lineage leukemia
(trithorax homolog,
Drosophila); translocate
chromosome 9 open 1013.
167 223697 PM x at C9orf64 reading frame 64 7.70E-06 2.25E-03 6 771.2 836.8
168 235999 PM _at 7.77E-06 2.25E-03 227.6 174.1 182.1
LOC10027
1836 ///
LOC44035
4 ///
LOC59510 SMG1 homolog,
l lll phosphatidylinositol 3-
LOC64129 kinase-related kinase
8 /// pseudogene /// PI-3-
169 244766, _PM _at SMG1 kinase-r 8.03E-06 2.31E-03 133.4 99.4 87.5
Zinc finger, CCHC
170 230332 PM at ZCCHC7 domain containing 7 8.07E-06 2.31E-03 467.4 265.1 263.2 zinc finger and BTB
171 235308 PM at ZBTB20 domain containing 20 8.17E-06 2.32E-03 256.7 184.2 167.3
Chloride channel,
172 242492 PM _at CLNS1A nucleotide-sensitive, 1A 8.19E-06 2.32E-03 128.5 82.8 79.2 tubulin tyrosine ligase-
173 215898 PM _at TTLLS like family, member 5 8.24E-06 2.32E-03 20.9 14.0 13.8 dedicator of cytokinesis
174 244840 PM x at D0CK4 4 8.65 E-06 2.42E-03 43.1 16.5 21.5 chromosome 1 open
175 220235 PM _s_at Clorfl03 reading frame 103 8.72E-06 2.43E-03 88.4 130.5 143.3
Poly(rC) binding protein
176 229467 PM at PCBP2 2 8.80E-06 2.44E-03 186.5 125.4 135.8
177 232527. . . -at — 8.99E-06 2.48E-03 667.4 453.9 461.3
178 243286 PM at — 9.24E-06 2.53E-03 142.6 98.2 87.2
179 215628 PM _x_at ... 9.28E-06 2.53E-03 49.6 36.3 39.4
180 1556412 PM at 9.45E-06 2.56E-03 34.9 24.7 23.8 interferon (alpha, beta
181 204786 PM s at IFNAR2 and omega) receptor 2 9.64E-06 2.59E-03 795.6 573.0 639.2
182 234258 PM at — 9.73E-06 2.60E-03 27.4 17.8 20.3
183 233274 PM .at — 9.76E-06 2.60E-03 109.9 77.5 79.4
184 239784 PM at ... 9.82E-06 2.60E-03 137.0 80.1 70.1
185 242498. _PM. _x_at ... 1.01E-05 2.65E-03 59.2 40.4 38.9
186 231351 _PM. .at 1.02E-05 2.67E-03 124.8 70.8 60.6
187 222368 PM at ... 1.03E-05 2.67E-03 89.9 54.5 44.3
188 236524 PM at 1.03E-05 2.67E-03 313.2 234.7 214.2 trinucleotide repeat
189 243834 PM at TNRC6A containing 6A 1.04E-05 2.67E-03 211.8 145.1 146.9
190 239167 PM at — 1.04E-05 2.67E-03 287.4 150.2 160.3
191 239238. PM at — 1.05E-05 2.67E-03 136.0 81.6 92.0
192 237194. PM. .at 1.05E-05 2.67E-03 57.2 34.4 27.9
193 242772 PM x at 1.06E-05 2.67E-03 299.2 185.2 189.4
194 243827 PM at 1.06E-05 2.67E-03 115.9 50.1 56.4 vesicle transport
through interaction
with t-SNAREs homolog
195 1552536 PM at VTUA 1A (yeast) 1.10E-05 2.75E-03 61.7 35.1 34.6
196 243696 PM at KIAA0562 KIAA0562 1.12E-05 2.77E-03 19.0 14.8 15.0
197 233648 PM at _„ 1.12E-05 2.77E-03 33.9 21.0 24.1
X-linked inhibitor of 1020.
198 225858 PM s at XIAP apoptosis 1.16E-05 2.85E-03 7 760.3 772.6
REV3-like, catalytic
199 238736 PM at REV3L subunit of DNA 1.19E-05 2.91E-03 214.2 1 135.8 151.6 polymerase zeta (yeast)
major facilitator
superfamily domain
200 221192 PM x at MFSD11 containing 11 1.20E-05 2.92E-03 100.4 74.5 81.2
Table 3. 33 probesets that differentiate SCAR and TX at p-value < 0.001 in PAXGene blood tubes
subtype-like
aspartyl-tRNA
0.0007160
218365_PM_s_at DARS2 synthetase 2, 1.18
35
mitochondrial 218365 PM s at 17.2 14.5 sphingomyelin
phosphodiesterase
0.0003771
219695_PM_at SMPD3 3, neutral membrane -1.47
51
(neutral
sphingomyelinase II) 219695 PM at 12.0 17.6 multiple C2 domains, 0.0009334
220603_P _s_at MCTP2 -1.38
transmembrane 2 12 220603 PM s at 338.5 465.8 solute carrier family
26 (sulfate 0.0009612
224963_PM_at SLC26A2 1.47
transporter), 42
member 2 224963 PM at 94.3 64.0 ubiquitin specific 0.0008910
226729_P _at USP37 1.24
peptidase 37 38 226729 PM at 32.9 26.6 zinc finger protein 0.0005895
228226_PM_s_at Z F775 1.2
775 12 228226 PM s at 20.5 17.1 chromosome 1 open 0.0001534
230608_PM_at Clorfl82 -1.18
reading frame 182 78 230608 PM at 15.9 18.8 zinc finger protein 0.0004475
230756_PM_at ZNF683 1.52
683 1 230756 PM at 26.7 17.6 taste receptor, type 0.0008697
231757_PM_at TAS2R5 -1.12
2, member S 75 231757 PM at 9.3 10.4
Chromosome 3 open
231958_PM_at C3orf31 4.09E-05 1.22
reading frame 31 231958 PM at 20.1 16.4
0.0009483
237290_PM_at — -1.22
18 237290 PM at 10.3 12.5
LOC72929 hypothetical 0.0009223
237806_PM_s_at -1.18
6 LOC729296 4 237806 PM s at 10.2 12.0 spermatogenesis 0.0001165
238459_P _x_at SPATA6 -1.15
associated 6 25 238459 PM x at 9.2 10.5
Src kinase associated 0.0008214
241331_PM_at SKAP2 -1.39
phosphoprotein 2 76 241331 PM at 16.4 22.9
0.0004060
241368_PM_at PLIN5 perilipin 5 -1.61
66 241368 PM at 84.5 136.3
0.0004782
241543_PM_at — -1.17
21 241543 PM at 9.4 11.0
Table 4. List of 2156 differentially expressed probesets between AR, SCAR and TX from a 3-wa ANOVA
9 244341 PM at — 5.75E-08 2.60E-04 398.3 270.7 262.8
10 1558822 PM at 5.84E-08 2.60E-04 108.6 62.9 56.8
11 242175 PM at — 5.87E-08 2.60E-04 69.1 37.2 40.0 zinc finger and BTB
12 222357 PM at ZBTB20 domain containing 20 6.97E-08 2.83E-04 237.4 127.4 109.8 protein
geranylgeranyltransferase
13 206288 PM at PSGT1B type 1, beta subunit 9.42E-08 3.53E-04 20.8 34.7 34.2
14 222306 PM at — 1.03E-07 3.59E-04 23.3 15.8 16.0
15 1569601 PM at 1.67E-07 4.80E-04 49.5 34.1 29.7
16 235138 PM at 1.69E-07 4.80E-04 1169.9 780.0 829.7
17 240452 PM at G5PT1 Gl to S phase transition 1 1.74E-07 4.80E-04 97.7 54.4 48.6
18 243003 PM at — 1.77E-07 4.80E-04 92.8 52.5 51.3 major facilitator
superfamily domain 1881.
19 218109 PM s at MFSD1 containing 1 1.90E-07 4.87E-04 1464.0 0 1886.4
20 241681 PM at 2.00E-07 4.87E-04 1565.7 845.7 794.6
21 243878 PM at 2.19E-07 5.08E-04 76.1 39.7 39.5
22 233296 PM x at 2.33E-07 5.17E-04 347.7 251.5 244.7
DDBl and CUL4 associated
23 243318 PM at DCAF8 factor 8 2.52E-07 5.34E-04 326.2 229.5 230.2
24 236354 PM at — 3.23E-07 6.39E-04 47.1 31.2 27.8
25 243768 PM at — 3.35E-07 6.39E-04 1142.0 730.6 768.5
26 238558 PM at 3.65E-07 6.39E-04 728.5 409.4 358.4
27 237825 PM x at 3.66E-07 6.39E-04 34.2 20.9 19.9
28 244414 PM at — 3.67E-07 6.39E-04 548.7 275.2 284.0
29 215221 PM at 4.06E-07 6.83E-04 327.2 176.7 171.9
30 235912 PM at 4.46E-07 7.25E-04 114.1 71.4 59.5
31 239348 PM at 4.87E-07 7.54E-04 20.1 14.5 13.4
32 240499 PM at 5.06E-07 7.54E-04 271.4 180.1 150.2
33 208054 PM at HERC4 hect domain and RLD 4 5.11E-07 7.54E-04 114.9 57.6 60.0
34 240263 PM at — — 5.46E-07 7.81E-04 120.9 78.7 66.6
35 241303 PM x at — 5.78E-07 7.81E-04 334.5 250.3 261.5
36 233692 PM at 5.92E-07 7.81E-04 22.4 15.5 15.0
37 243561 PM at 5.93E-07 7.81E-04 341.1 215.1 207.3
38 232778_PM_at 6.91E-07 8.86E-04 46.5 31.0 28.5
39 237632 PM at 7.09E-07 8.86E-04 108.8 61.0 57.6
40 233690 PM at 7.30E-07 8.89E-04 351.1 222.7 178.1 vacuolar protein sorting
13 homolog D (S.
41 220221 PM at VPS13D cerevisiae) 7.50E-07 8.89E-04 93.5 60.0 59.9
42 242877 PM at — 7.72E-07 8.89E-04 173.8 108.1 104.0
TSR1, 20S rRNA
accumulation, homolog (S.
43 218155_PM_x_at TSR1 cerevisiae) 7.86E-07 8.89E-04 217.2 165.6 164.7
44 239603 PM x at — 8.24E-07 8.89E-04 120.9 75.5 81.1
45 242859 PM at 8.48E-07 8.89E-04 221.1 135.4 138.3
46 240866 PM at 8.54E-07 8.89E-04 65.7 33.8 35.2
47 239661 PM at 8.72E-07 8.89E-04 100.5 48.3 45.2 chromosome 18 open
48 224493 PM x at C18orf45 reading frame 45 8.77E-07 8.89E-04 101.8 78.0 89.7
1569202_PM_x_a
49 t 8.98E-07 8.89E-04 23.3 18.5 16.6
50 1560474 PM at 9.12E-07 8.89E-04 25.2 17.8 18.5
51 232511 PM at — 9.48E-07 9.06E-04 77.2 46.1 49.9 leucine-rich repeats and
calponin homology (CH)
52 228119 PM at LRCH3 domain containing 3 1.01E-06 9.51E-04 117.2 84.2 76.1
53 228545 PM at ZNF148 zinc finger protein 148 1.17E-06 9.99E-04 789.9 571.1 579.7
54 232779 PM at 1.17E-06 9.99E-04 36.7 26.0 20.7
55 239005 PM at FU39739 Hypothetical FU39739 1.18E-06 9.99E-04 339.1 203.7 177.7
LRRC37A leucine rich repeat
56 244478 PM at 3 containing 37, member A3 1.20E-06 9.99E-04 15.7 12.6 12.7
57 244535_PM_at 1.28E-06 9.99E-04 261.5 139.5 137.8
58 1562673 PM at 1.28E-06 9.99E-04 77.4 46.5 51.8 59 240601 PM at 1.29E-06 9.99E-04 212.6 107.7 97.7
G protein-coupled
60 239533 PM at GPR155 receptor 155 1.30E-06 9.99E-04 656.3 396.7 500.1
61 222358 PM x at 1.32E-06 9.99E-04 355.2 263.1 273.7
62 214707 PM x at ALMS1 Alstrom syndrome 1 1.32E-06 9.99E-04 340.2 255.9 266.0
63 236435 PM at — 1.32E-06 9.99E-04 144.0 92.6 91.1
64 232333 PM at — 1.33E-06 9.99E-04 487.7 243.7 244.3
65 222366 PM at 1.33E-06 9.99E-04 289.1 186.1 192.8
66 215611 PM at TCF12 transcription factor 12 1.38E-06 1.02E-03 45.5 32.4 30.8
Serine/threonine kinase
receptor associated
67 1558002 PM at STRAP protein 1.40E-06 1.02E-03 199.6 146.7 139.7
68 239716 PM at — 1.43E-06 1.02E-03 77.6 49.5 45.5
69 239091 PM at — 1.45E-06 1.02E-03 76.9 44.0 45.0
70 238883 PM at 1.68E-06 1.15E-03 857.1 475.5 495.1 protein
geranylgeranyltransf erase
71 235615 PM at PGGT1B type 1, beta subunit 1.72E-06 1.15E-03 127.0 235.0 245.6
72 204055 PM s at CTAGE5 CTAGE family, member 5 1.77E-06 1.15E-03 178.8 115.2 105.9
Zinc finger, ANl-type
73 239757 PM at ZFAND6 domain 6 1.81E-06 1.15E-03 769.6 483.3 481.9
74 1558409 PM at — 1.82E-06 1.15E-03 14.8 10.9 11.8
75 242688 PM at — 1.85E-06 1.15E-03 610.5 338.4 363.4
THUMPD THUMP domain
76 242377 PM x at 3 containing 3 1.87E-06 1.15E-03 95.5 79.0 81.3
77 242650 PM at 1.88E-06 1.15E-03 86.0 55.5 47.4
KIAA126
T ill
LOC1002 KIAA1267 /// hypothetical
78 243589 PM at 94337 LOC100294337 1.89E-06 1.15E-03 377.8 220.3 210.4
2255.
79 227384 PM s at 1.90E-06 1.15E-03 3257.0 5 2139.7
80 237864 PM at 1.91E-06 1.15E-03 121.0 69.2 73.4
81 243490 PM at 1.92E-06 1.15E-03 24.6 17.5 16.5
82 244383 PM at — 1.96E-06 1.17E-03 141.7 93.0 77.5
83 215908 PM at — 2.06E-06 1.19E-03 98.5 67.9 67.5
84 230651_PM_at — 2.09E-06 1.19E-03 125.9 74.3 71.5
85 1561195 PM at 2.14E-06 1.19E-03 86.6 45.1 43.9
NADH dehydrogenase
(ubiquinone) Fe-S protein
1, 75k0a (NADH-
86 239268 PM at NDUFS1 coenzyme Q reductase) 2.14E-06 1.19E-03 14.0 12.0 11.3
U2-associated SR140
87 236431 PM at SR140 protein 2.16E-06 1.19E-03 69.4 47.9 43.9
88 236978_PM_at — 2.19E-06 1.19E-03 142.4 88.6 88.1
89 1562957 PM at — 2.21E-06 1.19E-03 268.3 181.8 165.4
90 238913 PM at 2.21E-06 1.19E-03 30.9 20.2 20.1
91 239646 PM at 2.23E-06 1.19E-03 100.3 63.1 60.8
92 235701_PM_at 2.34E-06 1.24E-03 133.2 66.1 60.0
93 235601 PM at 2.37E-06 1.24E-03 121.9 75.5 79.0
94 230918 PM at — 2.42E-06 1.25E-03 170.4 114.5 94.4 foHiculin interacting
protein 1 /// Rap guanine
FNIP1 /// nucleotide exchange
95 219112 PM at RAPGEF6 factor (GEF) 6 2.49E-06 1.28E-03 568.2 400.2 393.4
1331.
96 202228 PM s at NPTN neuroplastin 2.52E-06 1.28E-03 1017.7 5 1366.4
97 242839 PM at — 2.78E-06 1.39E-03 17.9 14.0 13.6
98 244778 PM x at — — 2.85E-06 1.42E-03 105.1 68.0 65.9
99 237388 PM at — 2.91E-06 1.42E-03 59.3 38.0 33.0
100 202770 PM s at CCNG2 cyclin G2 2.92E-06 1.42E-03 142.2 269.0 270.0
101 240008 PM at — 2.96E-06 1.42E-03 96.2 65.6 56.2 protein phosphatase 2,
regulatory subunit B',
102 1557718 PM at PPP2R5C gamma 2.97E-06 1.42E-03 615.2 399.8 399.7
103 215528 PM at 3.01E-06 1 1.42E-03 126.8 62.6 69.0 hematopoieticallY
104 204689 P at HHEX expressed homeobox 3.08E-06 1.44E-03 381.0 499.9 567.9
RNA binding motif protein
105 213718 PM at RBM4 4 3.21E-06 1.46E-03 199.3 140.6 132.2
106 243233 PM at — 3.22E-06 1.46E-03 582.3 343.0 337.1
107 239597 PM at — 3.23E-06 1.46E-03 1142.9 706.6 720.8
108 232890 PM at — 3.24E-06 1.46E-03 218.0 148.7 139.9
109 232883 PM at 3.42E-06 1.53E-03 127.5 79.0 73.1
110 241391 PM at — 3.67E-06 1.62E-03 103.8 51.9 48.3
111 244197 PM x at 3.71E-06 1.62E-03 558.0 397.3 418.8
112 205434 PM s at AAK1 AP2 associated kinase 1 3.75E-06 1.62E-03 495.2 339.9 301.2
113 235725 PM at SMAD4 SMAD family member 4 3.75E-06 1.62E-03 147.1 102.1 112.0
Wilms tumor 1 associated
114 203137 PM at WTAP protein 3.89E-06 1.66E-03 424.1 609.4 555.8
Ras association
(RalGDS/AF-6) and
pleckstrin homology
115 231075 PM x at RAPH1 domains 1 3.91E-06 1.66E-03 30.4 19.3 18.2
LOCIOOI hypothetical protein
116 236043 PM at 30175 LOC100130175 3.98E-06 1.67E-03 220.6 146.2 146.5
117 238299 PM at 4.09E-06 1.70E-03 217.1 130.4 130.3
118 243667 PM at 4.12E-06 1.70E-03 314.5 225.3 232.8
119 223937 PM at F0XP1 forkhead box PI 4.20E-06 1.72E-03 147.7 85.5 90.9
120 238666 PM at 4.25E-06 1.72E-03 219.1 148.3 145.5
121 1554771 PM at 4.28E-06 1.72E-03 67.2 41.5 40.8 natural killer-tumor 1170.
122 202379 PM s at N TR recognition sequence 4.34E-06 1.73E-03 1498.2 6 1042.6 ghrelin opposite strand
123 244695 PM at GHRLOS (non-protein coding) 4.56E-06 1.79E-03 78.0 53.0 52.5
124 239393 PM at — 4.58E-06 1.79E-03 852.0 554.2 591.7
125 242920 PM at — 4.60E-06 1.79E-03 392.8 220.9 251.8
126 242405_PM_at — 4.66E-06 1.80E-03 415.8 193.8 207.4
127 1556432 PM at — 4.69E-06 1.80E-03 61.5 43.1 38.1
128 1570299 PM at 4.77E-06 1.81E-03 27.0 18.0 19.8
VAMP (vesicle-associated
membrane protein)- associated protein A,
129 225198 PM at VAPA 33kDa 4.85E-06 1.83E-03 192.0 258.3 273.9
130 230702 PM at 4.94E-06 1.85E-03 28.2 18.4 17.5
131 240262 PM at — — 5.07E-06 1.88E-03 46.9 22.8 28.0
132 232216_PM_at YME1L1 YMEl-like 1 (S. cerevisiae) 5.14E-06 1.89E-03 208.6 146.6 130.1
ARHGAP Rho GTPase activating
133 225171 PM at 18 protein 18 5.16E-06 1.89E-03 65.9 109.1 121.5
134 243992 PM at 5.28E-06 1.92E-03 187.1 116.0 125.6
135 227082 PM at — 5.45E-06 1.96E-03 203.8 140.4 123.0
136 239948 PM at NUP153 nucleoporin 153kDa 5.50E-06 1.96E-03 39.6 26.5 27.8 cylindromatosis (turban
137 221905 PM at CYLD tumor syndrome) 5.51E-06 1.96E-03 433.0 316.8 315.1
Solute carrier family 22
(extraneuronal
monoamine transporter),
138 242578 PM x at SLC22A3 member 3 5.56E-06 1.96E-03 148.4 109.2 120.1
1569238_PM_a_a
139 t 5.73E-06 1.99E-03 71.0 33.0 36.1
Ras homolog enriched in
140 201453 PM x at RHEB brain 5.76E-06 1.99E-03 453.3 600.0 599.0
141 236802 PM at — — 5.76E-06 1.99E-03 47.9 29.1 29.6
3073.
142 232615 PM at 5.82E-06 1.99E-03 4068.5 4 2907.4 protein-L-isoaspartate (D- aspartate) O- methyltransferase domain
143 237179 PM at PCMTD2 containing 2 5.84E-06 1.99E-03 48.7 30.2 26.8
144 203255 PM at FBXOll F-box protein 11 5.98E-06 2.02E-03 748.3 529.4 539.6
145 212989 PM at SGMS1 . sphingomyelin synthase 1 6.04E-06 2.03E-03 57.2 93.1 107.9
146 236754 PM at PPP1R2 protein phosphatase 1, 6.17E-06 2.05E-03 505.3 380.7 370.1 regulatory (inhibitor)
subunit 2
pyrophosphatase
147 1559496 PM at PPA2 (inorganic) 2 6.24E-06 2.05E-03 68.8 39.7 39.3
148 236494 PM x at — 6.26E-06 2.05E-03 135.0 91.1 82.9
149 237554 PM at — 6.30E-06 2.05E-03 53.4 31.5 30.1
150 243469 PM at — 6.37E-06 2.05E-03 635.2 308.1 341.5
Z F493
III zinc finger protein 493 ///
151 240155 PM x at ZNF738 zinc finger protein 738 6.45E-06 2.05E-03 483.9 299.9 316.6
ADP-ribosylation factor¬
152 222442 PM s at ARL8B like 8B 6.47E-06 2.05E-03 201.5 292.6 268.3
153 240307 PM at — 6.48E-06 2.05E-03 55.4 36.8 33.1
RAB11A, member RAS
154 200864 PM s at RAB11A oncogene family 6.50E-06 2.05E-03 142.1 210.9 233.0
155 235757 PM at 6.53E-06 2.05E-03 261.4 185.2 158.9 protein phosphatase 2,
156 222351 PM at PPP2R1B regulatory subunit A, beta 6.58E-06 2.06E-03 75.8 51.1 45.4 round spermatid basic
157 222788 PM s at RSBN1 protein 1 6.63E-06 2.06E-03 389.9 302.7 288.2
158 239815 PM at — 6.70E-06 2.06E-03 216.9 171.4 159.5
159 219392 PM x at PRR11 proline rich 11 6.77E-06 2.07E-03 1065.3 827.5 913.2
160 240458 PM at 6.80E-06 2.07E-03 414.3 244.6 242.0
Muscleblind-like 1165.
161 235879 PM at MBNL1 (Drosophila) 6.88E-06 2.08E-03 1709.2 5 1098.0 headcase homolog
162 230529 PM at HECA (Drosophila) 7.08E-06 2.13E-03 585.1 364.3 418.4
KIAA124
5 ///
NBPF1
III
NBPF10
III
NBPF11
III
NBPF12
III
NBPF24 KIAA1245 ///
III neuroblastoma breakpoint
NBPF8 family, member 1 ///
1562063_PM_x_a III neuroblastoma breakpoint
163 t NBPF9 fam 7.35E-06 2.20E-03 350.4 238.8 260.8
1164.
164 202769 PM at CCNG2 cyclin G2 7.42E-06 2.20E-03 697.1 0 1264.6
1556493_PM_a_a lysine (K)-specific
165 t KDM4C demethylase 4C 7.64E-06 2.24E-03 81.4 49.0 44.5 myeloid/lymphoid or
mixed-lineage leukemia
(trithorax homolog,
166 216509_PM_x_at MLLT10 Drosophila); translocate 7.64E-06 2.24E-03 22.4 17.9 19.3 chromosome 9 open
167 223697 PM x at C9orf64 reading frame 64 7.70E-06 2.25E-03 1013.6 771.2 836.8
168 235999 PM at 7.77E-06 2.25E-03 227.6 174.1 182.1
LOC1002
71836
III
LOC4403
54 ///
LOC5951 SMGl homolog,
01 /// phosphatidylinositol 3-
LOC6412 kinase-related kinase
98 /// pseudogene /// PI-3-
169 244766 PM at SMGl kinase-r 8.03E-06 2.31E-03 133.4 99.4 87.5
Zinc finger, CCHC domain
170 230332 PM at ZCCHC7 containing 7 8.07E-06 2.31E-03 467.4 265.1 263.2 zinc finger and BTB
171 235308 PM at ZBTB20 domain containing 20 8.17E-06 2.32E-03 256.7 184.2 167.3 Integration 1 1
218 235925 PM at — 1.49E-05 3.33E-03 61.2 41.7 35.3
219 243736 PM at 1.50E-05 3.33E-03 131.8 76.7 70.0
Prenyl (decaprenyl)
diphosphate synthase,
220 236298 PM at PDSS1 subunit 1 1.51E-05 3.33E-03 79.7 59.5 60.9
221 1558410 PM s at 1.51E-05 3.33E-03 40.1 24.8 22.6
222 1570621 PM at 1.52E-05 3.33E-03 24.1 16.1 18.0
223 233228 PM at — 1.54E-05 3.35E-03 256.6 149.9 137.1
Proteasome (prosome,
macropain) subunit, beta
224 244801 PM at PSMB7 type, 7 1.54E-05 3.35E-03 71.6 53.7 48.7
Mitochondrial ribosomal
225 236779 PM at MRPS5 protein S5 1.55E-05 3.35E-03 25.4 20.5 17.1
226 241063 PM at — 1.55E-05 3.35E-03 16.8 13.4 12.4
227 239166 PM at — 1.56E-05 3.35E-03 151.4 84.6 79.8
228 222371 PM at — 1.59E-05 3.38E-03 1038.5 638.6 629.2
AT rich interactive domain
229 1553349 PM at ARID2 2 (ARID, RFX-like) 1.59E-05 3.38E-03 98.2 66.1 65.9
230 238894 PM at — 1.60E-05 3.38E-03 95.0 58.9 56.8
231 236621 PM at RPS27 ribosomal protein S27 1.61E-05 3.40E-03 74.6 38.2 41.4 splicing factor,
232 222310 PM at SFRS15 arginine/serine-rich 15 1.62E-05 3.41E-03 154.5 95.5 106.7
233 1569180 PM at — 1.65E-05 3.44E-03 232.8 126.6 126.8
234 240544 PM at — 1.67E-05 3.48E-03 45.3 24.9 25.8 family with sequence
235 226062 PM x at FAM63A similarity 63, member A 1.74E-05 3.61E-03 532.9 375.1 412.3
236 210679 PM x at — 1.75E-05 3.62E-03 167.6 119.6 123.6
FAM178 family with sequence
237 203482 PM at A similarity 178, member A 1.76E-05 3.62E-03 88.2 69.3 66.3
238 203318 PM s at ZNF148 zinc finger protein 148 1.86E-05 3.80E-03 812.1 633.8 647.6
239 233027_PM_at 1.87E-05 3.80E-03 167.2 107.4 119.2 armadillo repeat
240 236966 PM at ARMC8 containing 8 1.87E-05 3.80E-03 373.4 272.2 240.4
241 217446_PM_x_at — 1.89E-05 3.82E-03 204.7 158.6 170.8
242 241508 PM at — 1.91E-05 3.85E-03 106.6 62.3 69.3
243 213940 PM s at FNBP1 formin binding protein 1 1.94E-05 3.87E-03 911.3 766.0 710.7
244 215373 PM x at — 1.94E-05 3.87E-03 77.9 54.4 65.9
245 242480 PM at — — 1.95E-05 3.89E-03 605.9 358.6 393.2
246 228271 PM at — 1.97E-05 3.90E-03 109.8 81.3 64.9
247 216211_PM_at — 1.98E-05 3.90E-O3 182.9 132.4 111.1
248 1557632 PM at 1.99E-05 3.90E-03 576.5 426.5 400.0
249 244826 PM at 2.00E-05 3.90E-03 363.7 257.1 267.9
250 239264 PM at 2.01E-05 3.90E-03 162.6 98.9 89.0
251 227931 PM at INO80D INO80 complex subunit D 2.01E-05 3.90E-03 841.6 635.5 661.8
252 242563 PM at — 2.03E-05 3.93E-03 246.4 126.9 135.0
253 238172 PM at — — 2.05E-05 3.95E-03 88.6 56.1 51.4
254 241893 PM at — 2.06E-05 3.96E-03 123.1 59.6 59.3
255 233323 PM at — 2.08E-05 3.96E-03 223.8 136.7 135.2
256 242865 PM at — 2.08E-05 3.96E-03 382.4 247.8 273.3
257 226252 PM at 2.09E-05 3.97E-03 124.6 91.1 84.0
AT rich interactive domain
258 225490 PM at ARID2 2 (ARID, RFX-like) 2.11E-05 3.97E-03 240.9 185.3 169.2
CD164 molecule, 1044.
259 208654 PM s at CD164 sialomucin 2.12E-05 3.97E-03 676.3 0 939.9 natural killer-tumor
260 215338 PM s at N TR recognition sequence 2.13E-05 3.97E-03 457.1 352.4 328.2
261 242110 PM at — 2.13E-05 3.97E-03 54.2 31.6 29.8
RAB22A, member RAS
262 218360 PM at RAB22A oncogene family 2.15E-05 4.00E-03 78.8 122.7 118.7
1570166_PM_a_a
263 t — 2.16E-05 4.00E-03 38.7 26.0 27.1
RAB1A, member RAS 1688.
264 208724 PM s at RAB1A oncogene family 2.17E-05 4.0OE-03 1357.9 2 1672.7
265 239901 PM at — 2.19E-05 4.03E-03 455.7 255.1 273.1 266 238988 PM _at — 2.21E-05 4.05E-03 315.4 194.7 209.8
Vacuolar protein sorting
13 homolog C (S.
267 235023 PM at VPS13C cerevisiae) 2.23E-05 4.08E-03 649.4 471.9 435.1
268 217619 PM x at — 2.24E-05 4.08E-03 48.0 39.5 43.3
269 215618 PM at RSU1 Ras suppressor protein 1 2.27E-05 4.10E-03 34.5 24.9 25.4 trinucleotide repeat
270 230779 PM at TN RC6B containing 6B 2.27E-05 4.10E-03 767.7 495.5 508.6
271 243981 PM at STK4 serine/threonine kinase 4 2.31E-05 4.16E-03 490.0 312.1 335.1
1569181_PM_x_a
272 t — 2.33E-05 4.17E-03 233.9 127.7 121.5
273 203321 PM s at ADNP2 ADN P homeobox 2 2.34E-05 4.17E-03 150.5 117.4 113.4 centrosomal protein
274 204373 PM s at CEP350 350kDa 2.36E-05 4.19E-03 439.2 350.3 352.4
Retinoblastoma binding
275 239071 PM _at RBBP4 protein 4 2.37E-05 4.20E-03 173.1 131.7 122.9
Vps20-associated 1
276 224437 PM s at VTA1 homolog (S. cerevisiae) 2.38E-05 4.21E-03 229.2 335.9 330.0
277 243522 PM at 2.41E-05 4.24E-03 14.9 12.5 11.7
278 237803 PM x at 2.42E-05 4.24E-03 89.4 65.8 54.7 trinucleotide repeat
279 229036 PM _at TNRC6B containing 6B 2.45E-05 4.28E-03 575.8 426.5 436.5
280 222282 PM at 2.47E-05 4.29E-03 340.4 214.0 230.4
LOCIOOI hypothetical
281 227074 PM at 31564 LOC100131564 2.49E-05 4.32E-03 389.3 291.8 239.7
282 242343 PM x at 2.55E-05 4.38E-03 595.3 403.5 403.1
283 213086 PM s at CSNK1A1 casein kinase 1, alpha 1 2.55E-05 4.38E-03 565.0 667.9 660.5 zinc finger and BTB
284 205383 PM s at ZBTB20 domain containing 20 2.56E-05 4.38E-03 151.5 104.9 92.1 hyaluronan binding
285 233919 PM s at HABP4 protein 4 2.57E-05 4.38E-03 33.3 22.3 20.4
286 231552 PM .at 2.57E-05 4.38E-03 258.2 173.1 182.0
LOC100S collagen alpha-4(Vl chain¬
287 239017 PM at 07273 like 2.58E-05 4.39E-03 75.4 40.3 39.1
Additional sex combs like
288 240072 PM _at ASXL2 2 (Drosophila) 2.61E-05 4.42E-03 81.5 50.0 56.0
289 242362_ PM at — 2.65E-05 4.47E-03 414.8 279.S 307.1
290 238317 PM x at — 2.67E-05 4.49E-03 386.3 284.6 287.8
291 242471 PM at 2.71E-05 4.53E-03 741.8 426.8 386.9
BCL2/adenovirus E1B
19kDa interacting protein
292 209308 PM s at BNIP2 2 2.73E-05 4.55E-03 306.3 444.4 450.1
293 240254 PM at — 2.75E-05 4.57E-03 41.2 27.6 21.5
294 233313 PM .at — 2.80E-05 4.61E-03 46.3 33.3 30.5
1559401_P _a_a
295 t 2.80E-05 4.61E-03 20.0 14.2 13.3
LOC4424
21 /// hypothetical LOC442421
LOC7282 /// prostaglandin E2
296 217158 PM at 97 receptor EP4 subtype-like 2.82E-05 4.61E-03 12.6 14.2 12.0
297 239758 PM at 2.82E-05 4.61E-03 133.3 79.2 78.9
298 232882 PM at 2.82E-05 4.61E-03 203.8 95.0 85.1
299 226250 PM at 2.83E-05 4.61E-03 151.7 105.8 97.6
300 201619 PM at PRDX3 peroxiredoxin 3 2.84E-05 4.62E-03 605.8 852.3 804.1 dicer 1, ribonuclease type
301 213229 PM at DICERl III 2.87E-05 4.62E-03 971.6 652.0 668.8
302 242068 PM at 2.87E-05 4.62E-03 281.2 157.5 152.9
303 243470 PM at 2.87E-05 4.62E-03 60.0 43.1 44.4 solute carrier family 35,
304 218519 PM at SLC35A5 member A5 2.88E-05 4.62E-03 173.2 228.3 234.9
305 240399 PM at — 2.92E-05 4.64E-03 15.6 11.2 12.6
306 241501 PM at — 2.92E-05 4.64E-03 265.7 175.6 164.5
307 228623 PM at 2.93E-05 4.64E-03 369.6 223.4 226.0
GTPase activating protein
(SH3 domain) binding
308 225007 PM at G3BP1 protein 1 2.99E-05 4.72E-03 549.8 423.9 371.4 2015/032202
351 240824_PM_at — 3.85E-05 5.34E-03 300.3 202.7 216.3
352 243640 PM x at 3.86E-05 5.34E-03 36.3 26.9 25.6
353 239902_PM_at — 3.96E-05 5.47E-03 40.7 32.0 25.5 chromosome 18 open
354 244495_PM_x_at C18orf45 reading frame 45 4.00E-05 5.48E-03 111.4 89.7 100.0
355 221176 PM x at 4.02E-05 5.48E-03 135.2 107.7 114.4
Zinc finger, CCHC domain
356 236243 PM at ZCCHC6 containing 6 4.03E-05 5.48E-03 868.0 534.2 530.6
357 243964_PM_at — 4.03E-05 5.48E-03 114.0 75.3 69.3
358 226970 PM at FBX033 F-box protein 33 4.03E-05 5.48E-03 460.9 359.9 344.0 zinc finger CCCH-type
359 206169 PM x at ZC3H7B containing 7B 4.04E-05 5.48E-03 439.3 319.9 341.9
LOC4009
360 227969 PM at 60 hypothetical LOC400960 4.05E-05 5.48E-03 65.4 50.7 46.7 bromodomain PHD finger
361 207186 PM s at BPTF transcription factor 4.09E-05 5.52E-03 1217.2 958.4 894.3
Nuclear autoantigenic
sperm protein (histone-
362 242918 PM at NASP binding) 4.13E-05 5.56E-03 212.8 127.0 158.1
363 241226 PM at 4.14E-05 5.56E-03 32.6 22.4 21.0
1556382 J>M_a_a N(alpha)-acetyltransferase
364 t NAA15 15, NatA auxiliary subunit 4.15E-05 5.56E-03 15.9 12.4 12.3
365 237018 PM at — 4.19E-05 5.58E-03 460.1 322.7 305.5
366 225367 PM at PGM2 phosphoglucomutase 2 4.20E-05 5.58E-03 550.7 709.4 778.0
DDBl and CUL4 associated
367 236134 PM at DCAF7 factor 7 4.20E-05 5.58E-03 120.0 78.1 74.3
368 242143 PM at — 4.24E-05 5.62E-03 295.6 177.4 179.6
369 237881 PM at — 4.31E-05 5.69E-03 128.5 56.6 52.1 chromodomain protein, Y-
370 203100 PM s at CDYL like 4.32E-05 5.69E-03 85.5 116.1 121.1
371 244236_P _at — — 4.34E-05 5.70E-03 22.7 18.1 16.0
372 236561 PM at — — 4.36E-05 5.71E-03 577.8 412.5 389.2
373 236149 PM at 4.38E-05 5.71E-03 52.7 31.8 29.7
374 214715 PM x at ZNF160 zinc finger protein 160 4.38E-05 5.71E-03 860.0 646.3 690.2
UDP-GlcNAc:betaGal beta- 1,3-N- acetylglucosarmnvltvansfe
375 219326 PM s at B3GNT2 rase 2 4.40E-05 5.72E-03 18.1 26.8 28.6
376 201959_PM_s_at MYCBP2 MYC binding protein 2 4.44E-05 5.75E-03 1010.4 762.0 722.2
377 236404 PM at — 4.47E-05 5.77E-03 310.1 182.7 185.3
378 233037 PM at — 4.52E-05 5.83E-03 19.4 14.3 14.8
379 237768 PM x at — 4.55E-05 5.85E-03 531.4 367.3 361.5
VAMP (vesicle-associated
membrane protein)-
380 202549_PM_at VAPB associated protein 8 and C 4.57E-05 5.86E-03 21.9 15.6 18.9
381 237264 PM at — 4.61E-05 5.89E-03 192.5 114.0 115.6
1345.
382 226465 PM s at SON SON DNA binding protein 4.64E-05 5.89E-03 1664.7 0 1359.5 splicing factor,
383 226412 PM at SF S18 arginine/serine-rich 18 4.65E-05 5.89E-03 619.8 443.1 467.6
384 244860 PM at — 4.66E-05 5.89E-03 37.8 22.5 21.1
385 240139 PM at — 4.67E-05 5.89E-03 162.8 110.0 101.9 glyceraldehyde 3
GAPDHP phosphate dehydrogenase
386 238807 PM at 62 pseudogene 62 4.67E-05 5.89E-03 126.7 88.3 78.4 cysteinyl leukotriene
387 230866 PM at CYSLTR1 receptor 1 4.72E-05 5.93E-03 171.2 267.5 284.1
388 236000 PM s at — 4.72E-05 5.93E-03 326.9 240.3 242.0
389 237895 PM at — 4.74E-05 5.94E-03 469.8 258.1 223.3
390 243966 PM at 4.79E-05 5.97E-03 227.7 174.9 165.4
1556060_PM_a_a
391 t ZNF451 zinc finger protein 451 4.80E-05 5.97E-03 550.1 418.5 416.6
392 242598 PM at — 4.81E-05 5.97E-03 465.2 250.1 308.0
393 1569237 PM at — — 4.83E-05 5.97E-03 52.8 35.4 37.1
394 232791 PM at 4.83E-05 5.97E-03 25.2 17.7 16.8
395 1565567 PM at — 4.85E-05 5.97E-03 1032.1 665.2 779.1 396 222252 PM x at UBQLN ubiquilin 4 4.85E-05 5.97E-03 73.1 59.3 61.8
397 229765 PM at ZNF207 zinc finger protein 207 4.90E-05 6.01E-03 722.8 581.6 540.4
398 201302 PM at ANXA4 annexin A4 4.92E-05 6.01E-03 303.7 429.1 454.7
1556783_PM_a_a
399 t — 4.92E-05 6.01E-03 15.2 11.7 11.7
400 215200 PM x at — 4.94E-05 6.02E-03 97.7 79.4 80.4
401 231005 PM at — 4.98E-05 6.04E-03 243.5 155.8 167.8
402 243249 PM at — 4.99E-05 6.04E-03 832.1 598.5 633.0
403 233702 PM x at — 5.00E-05 6.04E-03 381.5 289.0 318.0
404 1564077 PM at 5.01E-05 6.04E-03 99.8 65.3 47.8
405 232613 PM at PB M1 polybromo 1 5.04E-05 6.06E-03 152.3 108.9 117.0
X-linked inhibitor of
406 225859 PM at X1AP apoptosis 5.11E-05 6.13E-03 716.1 535.6 524.7
407 240302 PM at — 5.20E-05 6.23E-03 70.6 46.5 42.3
408 244791 PM at — 5.22E-05 6.24E-03 72.4 41.7 43.0
409 244508 PM at 7-Sep Septin 7 5.26E-05 6.26E-03 80.0 50.2 46.2 heterochromatin protein
410 1554251 PM at HP1BP3 1, binding protein 3 5.28E-05 6.26E-03 192.1 150.9 123.2
411 242862 PM x at — 5.28E-05 6.26E-03 114.4 82.9 88.5
412 243381 PM at — 5.29E-05 6.26E-03 35.7 24.3 23.6
413 1561763 PM at — 5.38E-05 6.35E-03 92.4 56.7 59.8
414 239102 PM s at — 5.41E-05 6.35E-03 1585.7 933.9 1087.2
415 215179 PM x at PGF Placental growth factor 5.41E-05 6.35E-03 820.1 625.4 683.9 protein tyrosine
phosphatase type IVA,
416 200730 PM s at PTP4A1 member 1 5.42E-05 6.35E-03 76.9 120.8 125.1
417 233309 PM at — 5.44E-05 6.35E-03 142.7 89.0 102.0
418 210282 PM at ZMYM2 zinc finger, MYM-type 2 5.48E-05 6.39E-03 246.4 166.5 163.2
419 243025 PM at 5.62E-05 6.53E-03 74.0 52.0 54.7 coiled-coil domain
20 237475 PM x at CCDC152 containing 152 5.72E-05 6.63E-03 830.9 624.3 684.3 spastic paraplegia 20
421 212526_.PM_at SPG20 (Troyer syndrome) 5.73E-05 6.63E-03 150.6 197.3 204.9 leukocyte
immunoglobulin-like
receptor, subfamily B
(with TM and ITIM 1158.
422 210146 PM x at LILRB2 domains), member 5.75E-05 6.64E-03 992.0 5 1393.3 eukaryotic translation
initiation factor 3, subunit
423 236274 PM at EIF3B B 5.76E-05 6.64E-03 30.4 24.7 22.7
424 232383 PM at TFEC transcription factor EC 5.79E-05 6.66E-03 49.6 132.2 94.3
425 235803 PM at — 5.84E-05 6.70E-03 116.0 73.4 66.2
426 208238 PM x at — 5.86E-05 6.70E-03 589.1 460.7 496.6
NADH dehydrogenase
(ubiquinone) Fe-S protein
4, 18kDa (NADH-
427 1555057 PM at NDUFS4 coenzyme Q reductase) 5.87E-05 6.70E-03 27.7 20.0 19.1 down-regulator of
transcription 1, TBP- binding (negative cofactor
428 209188 PM x at DR1 2) 5.88E-0S 6.70E-03 157.9 207.6 214.8
1559020_PM_a_a
429 t — 5.92E-05 6.73E-03 60.4 39.6 38.3 mediator complex subunit
430 212872 PM s at MED20 20 5.95E-05 6.75E-03 65.5 89.8 88.9
431 234032 PM at 5.98E-05 6.76E-03 245.4 134.1 120.3
432 232516 PM x at YY1AP1 YY1 associated protein 1 6.02E-05 6.76E-03 277.0 206.7 227.8 immediate early response
433 218611 PM at IER5 5 6.02E-05 6.76E-03 384.0 516.5 548.6
RANBP2
III
RGPD1 RAN binding protein 2 ///
III RANBP2-like and GRIP
RGP02 domain containing 1 ///
434 242712 PM x at III RANBP2-like and 6.02E-05 6.76E-03 1 92.4 52.4 61.2 RGPD3
III
RGPD4
III
RGPD5
III
RGPD6
III
RGPD8
435 229434 PM at — 6.10E-05 6.81E-03 1281.8 990.5 982.0
436 236379 PM at — 6.11E-05 6.81E-03 489.0 318.7 299.6
437 231495 PM at — 6.12E-05 6.81E-03 261.0 163.0 135.0 calpain 1, (mu/l) large
438 232012 PM at CAPN1 subunit 6.13E-05 6.81E-03 179.6 143.7 133.3
439 1558740 PM s at 6.15E-05 6.81E-03 246.8 179.6 171.8
440 235837 PM at 6.17E-05 6.81E-03 97.7 76.6 73.6 membrane-associated ring
441 201737 PM s at 6-Mar finger (C3HC4) 6 6.18E-05 6.81E-03 558.7 409.2 370.6
442 239561 PM at 6.20E-05 6.81E-03 143.1 75.4 80.9
443 243473 PM at — 6.23E-05 6.81E-03 20.0 15.1 15.1
444 215887 PM at ZNF277 zinc finger protein 277 6.24E-05 6.81E-Q3 144.3 101.2 106.6
445 241155 PM at 6.25E-05 6.81E-03 308.3 207.2 204.8
446 1563455 PM at SIK3 SIK family kinase 3 6.27E-05 6.81E-03 133.1 86.6 90.7
447 243089 PM at 6.27E-05 6.81E-03 49.4 28.7 24.7
448 232726 PM at 6.27E-05 6.81E-03 185.5 77.8 84.3 general transcription
449 238880 PM at GTF3A factor IMA 6.28E-05 6.81E-03 471.0 322.6 305.2 down-regulator of
transcription 1, TBP- binding {negative cofactor
450 216652_PM_s__at DR1 2) 6.30E-05 6.82E-03 110.6 152.5 153.6
Nuclear receptor
451 215605 PM at NC0A2 coactivator 2 6.41E-05 6.92E-03 302.5 184.3 220.5
452 239383 PM at — 6.47E-05 6.98E-03 95.2 62.9 54.6
453 230713 PM at — 6.50E-05 6.99E-03 179.2 116.7 108.1
454 201300 PM s at PRNP prion protein 6.53E-05 7.01E-03 327.7 516.1 538.4
455 232264_PM_at 6.59E-05 7.06E-03 124.7 63.8 62.6
Splicing factor,
456 243759 PM at SFRS15 arginine/serine-rich 15 6.65E-05 7.11E-03 103.6 67.4 71.4
457 235493 PM at — 6.72E-05 7.16E-03 97.5 67.3 66.6
458 1561346 PM at — 6.73E-05 7.16E-03 126.0 89.3 97.7
459 234989 PM at — 6.78E-05 7.19E-03 560.8 300.7 287.5
TAF9B RNA polymerase II,
TATA box binding protein
(TBP]-associated factor,
460 221616 PM s at TAF9B 31kDa 6.87E-05 7.27E-03 241.5 162.4 168.8
KIAA124
ill
NBPF1
III
NBPF10
III
NBPF11
III
NBPF12
III
NBPF24 KIAA1245 ///
III neuroblastoma breakpoint
NBPF8 family, member 1 ///
III neuroblastoma breakpoint
461 1562062 PM at NBPF9 fam 6.93E-05 7.31E-03 345.4 232.4 266.6 vesicle-associated
462 202829 PM s at VAMP7 membrane protein 7 6.93E-05 7.31E-03 563.9 752.2 674.2
463 1557830 PM at — 7.06E-05 7.42E-03 48.1 33.4 29.9 ubiquitin-conjugating 1367.
464 200667 PM at UBE2D3 enzyme E2D 3 (UBC4/5 7.06E-05 7.42E-03 1057.4 1 1384.4 homolog, yeast)
NEDD4 binding protein 2- 3196.
465 221899 P at N4BP2L2 like 2 7.10E-05 7.44E-03 4054.4 6 3171.5
466 236934 PM at — 7.13E-05 7.45E-03 143.5 63.2 56.1
467 1565762 PM at — 7.21E-05 7.50E-03 59.0 40.2 33.8
468 222316 PM at 7.21E-05 7.50E-03 247.1 154.8 164.9
469 239811 PM at 7.26E-05 7.53E-03 1050.3 645.8 708.3 vacuolar protein sorting
13 homolog D (S.
470 212326 PM at VPS13D cerevisiae) 7.26E-05 7.53E-03 30.4 23.0 23.6 protein phosphatase 2,
regulatory subunit B',
471 228070 PM at PPP2R5E epsilon isoform 7.29E-05 7.54E-03 365.2 286.1 275.0
472 1563080 PM at — 7.33E-05 7.56E-03 21.3 16.7 15.5
473 1560082 PM at — 7.41E-05 7.63E-03 39.8 29.5 27.4
474 224778 PM s at 7.44E-05 7.65E-03 1054.6 846.9 906,9
475 240174 PM at 7.48E-05 7.66E-03 249.8 144.1 143.7
1566887_PM_x_a
476 t 7.48E-05 7.66E-03 320.8 247.9 284.8 general transcription
factor IIH, polypeptide 3,
477 222104 PM x at GTF2H3 34kDa 7.54E-05 7.70E-03 468.3 361.7 374,9
478 233427 PM x at — 7.58E-05 7.73E-03 278.5 218.3 236.5
479 241917 PM at — 7.60E-05 7.74E-03 115.7 62.5 64.7
480 230392 PM at 7.63E-05 7.74E-03 119.3 80.5 83.5
V-akt murine thymoma
viral oncogene homolog 3
481 242876 PM at AKT3 (protein kinase B, gamma) 7.74E-05 7.83E-03 29.6 19.3 18.5
482 217482 PM at — 7.74E-05 7.83E-03 53.7 33.0 30.6
RAD52 homolog (S.
483 205647 PM at RAD52 cerevisiae) 7.76E-05 7.83E-03 17.6 15.1 13.8 leucine rich repeat
containing 8 family,
484 1570007 PM at LRRC8C member C 7.80E-05 7.85E-03 21.6 15.4 16.5
LOC1454
485 230505 PM at 74 hypothetical LOC145474 7.81E-05 7.85E-03 302.3 137.3 148.1
486 232929 PM at 7.87E-05 7.89E-03 51.2 28.8 28.1
487 239868 PM at 7.91E-05 7.92E-03 21.5 14.5 14.5
488 236974 PM at 8.05E-05 8.04E-03 245.7 165.1 165.5 solute carrier family 25
(mitochondrial carrier;
SLC25A2 phosphate carrier),
489 204342 PM at 4 member 24 8.09E-05 8.06E-03 281.9 464.1 438.3 transformer 2 alpha
490 229574 PM at TRA2A homolog (Drosophila) 8.10E-05 8.06E-03 850.9 620.8 645.7
491 Γ228694 PM at — 8.13E-05 8.07E-03 167.1 125.4 121.9
492 208082 PM x at — 8.15E-05 8.07E-03 716.5 587.4 601.3
493 235983 PM at 8.28E-05 8.18E-03 121.1 88.8 72.2
NADH dehydrogenase
(ubiquinone) Fe-S protein
8, 23kDa (NADH-
494 232169 PM x at NDUFS8 coenzyme Q reductase) 8.39E-05 8.28E-03 466.1 349.6 373.1
495 237290 PM at — 8.52E-05 8.38E-03 10.1 10.3 12.5
496 244599 PM at — 8.54E-05 8.39E-03 257.4 185.5 169.4
497 1557433 PM at 8.56E-05 8.39E-03 23.1 17.8 16.7
498 244433 PM at — 8.59E-05 8.39E-03 752.7 478.2 540.7 sterol regulatory element
binding transcription
499 242748 PM at SREBF2 factor 2 8.59E-05 8.39E-03 87.0 61.1 61.9
Dual specificity
500 1563505 PM at DUSP16 phosphatase 16 8.73E-05 8.51E-03 14.0 11.0 11.7
501 237987 PM x at — 8.76E-05 8.51E-03 8.4 8.8 9.8
502 239808 PM at — 8.77E-05 8.51E-03 210.2 163.0 137.8
503 232584 PM at 8.82E-05 8.53E-03 21.4 13.1 11.9
504 243993 PM at — 8.82E-05 8.53E-03 194.6 118.3 117.0
505 54051 PM at PKN0X1 PBX/knotted 1 homeobox 8.84E-05 8.53E-03 39.4 30.4 30.7 1
506 225522 PM at AAK1 AP2 associated kinase 1 8.97E-05 8.64E-03 223.6 176.1 151.7 ashl (absent, small, or
homeotic)-like 1288.
507 222667 PM s at ASH1L (Drasophila) 9.02E-05 8.67E-03 1637.7 3 1282.8
LIM domain containing
preferred translocation
508 202822 _PM at LPP partner in lipoma 9.05E-05 8.69E-03 371.8 281.4 299.5
509 242995 PM at 9.10E-05 8.70E-03 59.4 38.9 36.7
510 243512 PM _x_at 9.11E-05 8.70E-03 36.0 22.1 22.0
511 243826 PM at 9.12E-05 8.70E-03 317.0 181.4 215.2
ATPase, H+ transporting,
lysosomal accessory 2195.
512 201443 PM s at ATP6AP2 protein 2 9.16E-05 8.72E-03 1784.1 2 2170.5
513 243578 PM at — 9.20E-05 8.73E-03 26.9 18.2 17.5
514 240971 PM _x_at — 9.21E-05 8.73E-03 215.1 144.4 139.0
RAB3A interacting protein
515 238853 PM _at RAB3IP (rabin3) 9.23E-05 8.73E-03 35.1 22.9 23.6
516 221829 PM s at TNP01 transports 1 9.28E-05 8.76E-03 1035.0 803.0 842.0
517 242529. PM x at 9.30E-05 8.77E-03 34.6 23.5 22.3
518 239301 PM at 9.34E-05 8.78E-03 226.9 128.8 139.8
1570194 PM_x_a
519 t 9.38E-05 8.81E-03 196.3 91.9 121.4
520 233867 PM at 9.49E-05 8.89E-03 863.1 555.6 564.0
521 242479 PM s at 9.52E-05 8.90E-03 9.5 10.4 11.4
522 217679 PM x at 9.54E-05 8.90E-03 680.8 483.9 513.8
MYST histone
acetyltransferase
523 1559142 PM at MYST3 (monocytic leukemia) 3 9.60E-05 8.94E-03 25.5 19.8 21.0
RAB5A, member RAS
524 209089 PM .at RAB5A oncogene family 9.75E-05 9.06E-03 740.4 904.4 950.5
525 232372 PM _at 9.84E-05 9.13E-03 23.3 17.3 17.1 angiogenic factor with G
526 218534. PM s at AGGFl patch and FHA domains 1 9.91E-05 9.18E-03 82.0 118.9 114.9
527 1559723 PM s at — 9.99E-05 9.20E-03 20.1 14.8 14.3
0.0091963
528 232784 PM at — 0.000100001 1 68.2 51.7 46.1
0.0091963
529 242233 PM at 0.000100081 1 614.1 453.5 466.0
DEAD (Asp-Glu-Ala-Asp) 0.0091963
530 223662 PM x at DDX59 box polypeptide 59 0.000100162 1 129.3 106.9 114.9
0.0091963
531 244865 PM at — 0.000100377 1 24.8 19.1 19.7
NCRNAO non-protein coding RNA 0.0091963
532 242121 PM .at 0182 182 0.000100405 1 1332.1 853.7 927.4
BTB (POZ) domain 0.0091988
533 202946 PM s at BTBD3 containing 3 0.000100622 9 26.6 42.1 44.6
Mediator complex subunit 0.0092895
534 244611 PM .at MED13 13 0.000102003 8 65.6 43.8 38.7
0.0092895
535 205992 PM .s_at IL15 interleukin 15 0.000102174 8 177.2 292.0 335.6
LOC6454 0.0092895
536 242889 PM x_at 31 hypothetical LOC645431 0.000102186 8 170.7 141.4 145.9
0.0093389
537 243030 PM at — 0.000102974 5 384.8 242.9 256.3 protein kinase, cAMP- dependent, regulatory,
type 1, alpha (tissue 0.0093389
538 242482 PM at PRKAR1A specific extinguisher 0.000103274 5 131.2 79.8 90.5
0.0093389
539 220085 PM at HELLS helicase, lymphoid-specific 0.000103304 5 18.5 15.4 12.7
0.0093580
540 219017 PM at ET K1 ethanolamine kinase 1 0.000103707 2 52.2 83.1 91.3
541 240665_ PM at — 0.000104299 0.0093768 1121.4 732.2 726.7
542 230097 PM at — 0.0001043 0.0093768 96.4 68.6 58.9
543 237868 PM x at 0.000104648 0.0093907 167.5 123.1 138.3 6
MOB1, Mps One Binder
M0BKL1 kinase activator-like IB 0.0094771 1594.
544 201298 P s at B (yeast) 0.000105824 3 1271.1 0 1649.3
0.0094771
545 236931 PM at — 0.000106187 3 145.2 76.8 65.6 actin-related protein 10 0.0094771
546 222230 PM s at ACTR10 homolog (S, cerevisiae) 0.000106194 3 641.3 778.2 745.3
0.0094799
547 217662 PM x at 0.000106587 7 49.5 41.1 43.3
RAB18, member RAS 0.0094799
548 224787 PM s at RAB18 oncogene family 0.000106745 7 233.3 359.4 359.2
0.0094799
549 240019 PM at — 0.000106882 7 653.3 366.6 385.3 transcription termination 0.0094799
550 204771 PM s at TTF1 factor, RNA polymerase 1 0.000107004 7 468.3 364.4 376.0
0.0097166
551 238875 PM at 0.000109875 6 159.5 114.3 108,4
0.0097326 1142.
552 213574 PM s at 0.000110256 9 1540.5 7 1168.0
1558237_PM_x_a 0.0099088
553 t 0.000112606 2 275.2 206.9 217.7 kelch repeat and BTB
(POZ) domain containing 0.0099088
554 244771 PM at KBTBD12 12 0.000112658 2 11.0 9.1 10.2
0.0099206
555 239049 PM at — 0.000113136 2 357.9 233.0 253.1
0.0099206
556 215191 PM at — 0.000113298 2 _ 30O6_j 196.1 185.8 homer homolog 1 0.0099206
557 226651 PM at H0MER1 (Drosophila) 0.000113403 2 63.4 42.8 43.1 spastic paraplegia 21
(autosomal recessive,
558 215383 PM x at SPG21 Mast syndrome) 0.000114806 0.0100254 666.6 540.4 568.6
KIAA201
559 227435_PM_at 8 KIAA2018 0.000115657 0.0100816 501.0 352.7 394.7
560 205104 PM at SNPH syntaphilin 0.000117244 0.0102017 21.9 17.7 17.0
LOCIOOI Hypothetical
561 1558569 PM_at 31541 LOC100131541 0.00011856 0.0102806 104.4 51.7 55.9
562 243404_PM_at 0.00011868 0.0102806 198.4 140.6 145.0
563 220467J>M_at — 0.000118879 0.0102806 205.4 130.1 107.4
1755.
564 211509 PM s at RTN4 reticulon 4 0.000119113 0.0102806 1430.3 3 1868.7
565 204715 PM at PANX1 pannexin 1 0.000119206 0.0102806 16.5 22.6 21.9
566 235847 PM at 0.000120325 0.0103588 329.6 175.4 160.4
567 239600 PM at 0.000120761 0.010378 281.8 144.6 145.5
568 244457 PM at 0.000121998 0.0104658 241.3 153.0 150.3
569 226140 PM s at 0TUD1 OTU domain containing 1 0.00012251 0.0104913 407.3 538.5 585.7
570 227576 PM at — 0.000123208 0.0105326 377.0 214.1 192.3
571 242739 PM at 0.000123432 0.0105332 41.3 28.0 24.7
572 244625 PM at 0.000123749 0.0105418 39.7 22.7 23.5 adaptor-related protein
complex 1, sigma 2
573 228415 PM at AP1S2 subunit 0.000125275 0.0106532 141.1 213.5 223.3
574 214902 PM x at — 0.000126202 0.0106943 470.2 356.8 390.5
575 241460 PM at — 0.000126341 0.0106943 423.2 274.7 295.1
576 1564733 PM at 0.000126417 0.0106943 137.6 93.8 92,7
577 235959 PM at 0.000126652 0.0106956 309.3 200.7 227.3
578 1556420 PM s at YPEL2 yippee-like 2 (Drosophila) 0.000127836 0.0107739 110.9 77.0 79.7
579 243450 PM at — 0.000128021 0.0107739 51.7 31.2 30.3
KIAA163
580 234048 PM s at 2 KIAA1632 0.000128316 0.0107801 12.9 10.6 11.7
581 201057 PM s at G0LGB1 golgin Bl 0.000129333 0.0108468 196.9 149.2 148.0
582 242827 PM x at — 0.000130436 0.0109205 345.7 226.7 192.8
583 230607 PM at — 0.000131409 0.0109798 29.9 22.3 18.8
584 218379 PM at RBM7 RNA binding motif protein 0.000131656 0.0109798 249.9 336.2 329.5 7
585 241930 P x at 0.00013191 0.0109798 27.0 20.7 20.0
586 235804 PM at 0.000132077 0.0109798 42.3 33.0 28.3
587 241688 PM at — 0.000132271 0.0109798 32.0 21.7 22.8
588 230970 PM at 0.000133316 0.0110392 1228.2 700.6 742.7
589 235613 PM at — — 0.000133562 0.0110392 113.6 77.4 73.3 phosphatidylinositol
glycan anchor
590 214990 PM at PIGO biosynthesis, class O 0.000133666 0.0110392 11.9 9.6 10.3
591 242349 PM at HECTD1 HECT domain containing 1 0.000134359 0.0110777 95.2 68.2 67.4
PTC7 protein phosphatase
592 225204 PM at PPTC7 homolog {S. cerevisiae) 0.000134942 0.011107 790.6 552.0 605.7
593 235660 PM at — 0.000136056 0.0111798 130.3 89.4 97.7
Family with sequence
594 216682 PM s at FAM48A similarity 48, member A 0.000136461 0.0111942 232.3 149.8 165.4
1556373_PM_a_a
595 t 0.000136827 0.0112053 321.3 172.5 180.8
596 1556352 PM at — 0.000137503 0.0112418 256.9 139.8 138.1
597 239655 PM at 0.00013785 0.0112513 110.5 74.2 73.5
598 240600 PM at 0.000138859 0.0113048 324.9 212.7 211.5
1556462_PM_a_a
599 t 0.00013897 0.0113048 99.4 61.8 42.5
CUGBP, Elav-like family
600 1556323 PM at CELF2 member 2 0.000139628 0.0113223 1100.4 748.0 757.0 pyruvate dehydrogenase
601 225207 PM at PDK4 kinase, isozyme 4 0.00013965 0.0113223 85.6 214.9 192.3
602 235811 PM at — 0.000140131 0.0113425 802.0 498.5 381.6
603 226952 PM at EAF1 ELL associated factor 1 0,000141842 0.0114619 129.3 158.6 157.6 methyl-CpG binding
604 202484 PM s at MBD2 domain protein 2 0.000144855 0.011686 799.5 984.4 1005.3 golgi phosphoprotein 3
605 217803 PM at G0LPH3 (coat-protein) 0.000146215 0.0117762 690.0 818.8 813.0 sphingomyelin
SMPDL3 phosphodiesterase, acid¬
606 213624 PM at A like 3A 0.000147195 0.0118356 113.5 213.6 238.0 strawberry notch homolog
607 229528 PM at SBN01 1 (Drosophila) 0.000148186 0.0118956 177.6 129.9 124.2
RAS p21 protein activator
608 230669 PM at ASA2 2 0.00014871 0.0119178 1010.8 776.3 762.2
609 242369 PM x at — 0.000148951 0.0119178 234.7 155.9 163.8
610 239978 PM at — 0.000149912 0.011975 185.5 145.0 134.1
611 235841 PM at 0.000150894 0.0119968 182.1 93.8 106.3 ankyrin repeat and KH
612 229457 PM at ANKHD1 domain containing 1 0.000150905 0.0119968 94.5 65.6 61.7
613 240997 PM at — 0.000150923 0.0119968 25.9 20.3 22.3
614 1554595 PM at SYMPK symplekin 0.000151416 0.0120164 157.9 108.3 107.0
1248.
615 201097 PM s at ARF4 ADP-ribosylation factor 4 0.000151957 0.0120262 1063.5 9 1279.6
616 233319 PM x at — 0.000152034 0.0120262 23.2 18.3 19.5
617 232834 PM at — 0.000153247 0.0121025 84.1 52.9 40.6
RNA binding motif protein
618 225236 PM at RBM18 18 0.000153692 0.0121151 104.6 142.4 140.8
619 239285 PM at — 0.000154204 0.0121151 260.6 184.2 159.7
620 239409 PM at — 0.000154229 0.0121151 694.8 433.8 443.4
621 213860 PM x at CSNK1A1 casein kinase 1, alpha 1 0.000154641 0.0121151 679.8 796.3 765.4
F-box and WD repeat
622 215600 PM x at FBXW12 domain containing 12 0.000154649 0.0121151 449.4 342.1 375.4
623 234043 PM at — 0.000155523 0.012164 16.1 11.7 11.8 leucine rich repeat
624 238214 PM at LRRC69 containing 69 0.000157072 0.0122546 85.9 62.5 59.4
625 243170 PM at 0.000157184 0.0122546 869.6 505.9 573.4
626 241906 PM at 0.000158212 0.012315 315.8 182.8 218.3
627 217713 PM x at 0.000159065 0.0123617 132.7 106.6 120.4
Ras homolog enriched in
628 213404 PM s at RHEB brain 0.000159625 0.0123757 216.5 277.0 267.3
629 1563130 PM a a — 0.000159754 0.0123757 129.8 89.9 95.1 t
630 213936 PM X at SFTPB surfactant protein B 0.00016064 0.0124057 69.3 56.9 57.5
631 222380 PM s at PDCD6 Programmed cell death 6 0.00016065 0.0124057 244.5 160.8 166.0
632 222313 PM at — 0.00016118 0.0124269 284.8 214.1 218.2
LOC1002
633 232420 PM x at 89341 similar to hCG2022304 0.000162106 0.012472 86.6 68.9 77.8
MPHOSP M-phase phosphoprotein
634 225041 PM at H8 8 0.000162277 0.012472 826.1 647.9 621.4
635 243559 PM at — 0.000163991 0.0125745 23.6 16.6 16.1
C-terminal binding protein
636 201218 PM at CTBP2 2 0.000164126 0.0125745 475.6 589.0 644.6
637 244292 PM at 0.000164428 0.0125778 107.0 69.3 60.4
638 232874 PM at D0CK9 dedicator of cytokinesis 9 0.00016535 0.0126285 31.3 19.1 15.3
639 1565886 PM at — 0.000165997 0.0126581 151.6 99.6 94.8 receptor accessory protein
640 208873 PM s at REEP5 5 0.000166895 0.0127067 449.8 656.5 674.1 chromosome 6 open
641 242077 PM x at C6orfl50 reading frame 150 0.000167363 0.0127225 1009.1 819.5 869.4
N0TCH2 1351.
642 214722 PM at NL notch 2 N-terminal like 0.000168102 0.0127587 1850.6 5 1425.5
643 1558014 PM s at FAR1 fatty acyl CoA reductase 1 0.000169744 0.0128455 41.8 79.3 73.2
644 1563204 PM at ZNF627 Zinc finger protein 627 0.000169773 0.0128455 10.5 10.6 12.2 zinc finger and 8TB
645 204181 PM s at ZBTB43 domain containing 43 0.000170738 0.0128985 146.3 112.8 105.2
646 241491 PM at — — 0.000171717 0.0129524 25.9 18.5 18.7
647 206965_PM_at KLF12 Kruppel-like factor 12 0.000173042 0.0130322 72.3 46.6 37.1
GTPase, very large
648 1562364_PM_at GVIN1 interferon inducible 1 0.000174604 0.0131295 43.6 29.8 27.8
649 217810 PM x at LARS leucyl-tRNA synthetase 0.000175517 0.013168 324.3 259.5 248.2 chromosome 20 open
650 225890_PM_at C20orf72 reading frame 72 0.000175656 0.013168 191.3 269.4 253.2
651 241041 PM at 0.000176027 0.0131755 168.1 70.3 79.7
652 226261 PM at ZNRF2 zinc and ring finger 2 0.000176915 0.0132217 34,7 48.9 49.9
653 240134 PM at — 0.000177936 0.0132776 145.1 82.6 89.0 transformer 2 alpha
654 213593 PM s at TRA2A homolog (Drosophila) 0.000178805 0.0133221 1349.1 958.0 977.3
655 244845 PM at 0.000179762 0.0133567 283.3 150.4 159.3
656 236558_PM_at 0.000179818 0.0133567 168.5 97.3 92.2
657 239387 PM at 0.000180312 0.013373 89.7 59.2 68.7
658 215378 PM at 0.000181169 0.0134161 79.3 46.5 53.2
659 204516 PM at ATX ataxin 7 0.000181726 0.013437 948.0 736.1 700.4
660 242337_PM_at — 0.000183073 0.0135161 153.1 102.2 105.5
661 1557707 PM at — 0.00018375 0.0135455 71.2 , 54.3 54.3
Cytidine monophosphate
N-acetylneuraminic acid
662 241065 PM x at CMAS synthetase 0.000187162 0.0137205 146.0 117.7 124.7
1557814_PM_a_a
663 t 0.00018742 0.0137205 153.0 95.7 119.2
664 1559249 PM at ATX 1 ataxin 1 0.000187463 0.0137205 135.3 79.7 78.1
665 236474 PM at — 0.000187832 0.0137205 39.1 26.0 26.2 neurolysin
(metallopeptidase M3
666 234762 PM x at NLN family) 0.000187929 0.0137205 416.0 322.3 333.7
DIP2 disco-interacting
protein 2 homolog A
667 215529 PM x at DIP2A (Drosophila) 0.00018854 0.0137205 359.6 290.1 291.0
668 208648 PM at CP valosin-containing protein 0.000188635 0.0137205 264.7 194.0 192.4
UDP-GlcNAc:betaGal beta- 1,3-N- acetylglucosaminyltransfe
669 225612 PM s at B3GNT5 rase 5 0.00018864 0.0137205 155.2 206.5 290.7
670 234758 PM at — 0.000188803 0.0137205 15.8 12.4 12.3 protein-L-isoaspartate (D- aspartate) 0-
671 208857 PM s at PCMT1 methyltransferase 0.000188939 0.0137205 532.7 785.1 766.5
672 241438 PM at 0.000189877 0.0137681 43.6 28.5 27.2 activating transcription
673 1558233 P s at ATF1 factor 1 0.000192141 0.0139007 47.1 78.5 73.9
674 240168 PM at XP07 exportin 7 0.000192277 0.0139007 27.1 19.5 19.1 tetratricopeptide repeat
675 208662 PM s at TTC3 domain 3 0.000192568 0.0139011 470.2 354.0 311.1
676 230629 PM s at EP400 E1A binding protein p400 0.000192856 0.0139013 77.5 54.0 43.4
677 244610 PM x at 0.000194955 0.013997 26.9 18.4 18.8
LOC7288
678 229429 PM x at 55 hypothetical LOC728855 0.000195003 0.013997 1167.6 986.3 930.5
679 236829 PM at — 0.000195045 0.013997 199.0 138.3 143.6
680 222326 PM at 0.000196028 0.0140277 706.2 438.5 470.9
1556442_PM_x_a
681 t — 0.000196049 0.0140277 333.7 272.2 283.4
682 1569477 PM at 0.000197297 0.0140963 120.8 59.0 58.9 upregulator of cell
683 244046 PM at URGCP proliferation 0.000198236 0.0141427 108.0 76.3 66.7
684 1567044_PM_s_at — 0.000198703 0.0141553 209.9 146.6 159.4
685 1566491 PM at — 0.000199875 0.014191 11.5 9.4 9.6 chromosome 14 open
686 1559097 PM at C14orf64 reading frame 64 0.000199963 0.014191 61.3 42.7 25.5 ribosomal protein S16
687 1566079 PM at RPS16P5 pseudogene 5 0.000200078 0.014191 705.1 416.1 477.2 blocked early in transport
688 202710 PM at BET1 1 homolog (S. cerevisiae) 0.000201418 0.0142653 91.6 140.3 137.2
HAUS augmin-like
689 220071 PM x at HAUS2 complex, subunit 2 0.000201879 0.0142772 262.4 219.6 221.5
690 239274 PM at — — 0.000203017 0.0143368 600.6 310.5 341.3 activating transcription
691 231927 PM at ATF6 factor 6 0.000205596 0.0144979 192.0 140.0 146.2
Inner membrane protein,
692 242361 PM at IMMT mitochondrial (mitofilin) 0.000209917 0.0147813 29.0 23.7 21.6
KIAA036
693 236368 PM at 8 KIAA0368 0.000210329 0.0147889 93.7 59.9 62.1
694 241737 PM x at — 0.000211224 0.0148304 50.3 35.9 33.5
Inositol 1,4,5-
695 235213 PM at ITPKB trisphosphate 3-kinase B 0.000212538 0.0149012 224.7 157.1 139.1
696 1562280 PM at — 0.000213758 0.0149652 43.1 26.7 27.3 uveal autoantigen with
coiled-coil domains and
697 236715 PM x at UACA ankyrin repeats 0.000214698 0.0150095 311.8 251.4 282.5
698 242558 PM at 0.000215749 0.0150613 620.4 465.6 453.1 chromosome 5 open 1538.
699 225957 PM at C5orf41 reading frame 41 0.000216336 0.0150799 2095.9 8 1569.1
700 242494 PM at 0.000216773 0.0150799 28.0 18.8 19.4
701 1557238 PM s at 0.000216944 0.0150799 59.0 41.6 41.6 stress-associated
endoplasmic reticulum
702 200969 PM at SERP1 protein 1 0.000217306 0.0150836 236.0 362.5 361.3
703 234033 PM at 0.000218357 0.015135 201.4 97.1 111.1 nucleosome assembly
704 1556567 PM at NAP1L4 protein 1-like 4 0.000218709 0.0151378 137.9 111.7 109.3
705 244332 PM at — 0.000219503 0.0151712 21.9 15.0 17.2
MOB1, Mps One Binder
M0B L1 kinase activator-like IB
706 201297 PM s at B (yeast) 0.000220874 0.0152444 361.7 467.5 482.8
ATG5 autophagy related 5
707 202511 PM s at ATG5 homolog (S. cerevisiae) 0.000221384 0.015258 92.5 138.8 132.5
708 240759 PM at — 0.OOO223975 0.0154147 245.6 150.7 144.4 stress-associated
endoplasmic reticulum
709 200970 PM s at SERP1 protein 1 0.000225987 0.0155094 473.6 677.3 597.2
TMEM22 transmembrane protein
710 1559687 PM at 1 221 0.000225987 0.0155094 14.4 13.0 15.1 sema domain,
immunoglobulin domain
711 210124 PM x at SEMA4F (Ig), transmembrane 0.000227139 0.0155665 18.3 14.7 15.1 domain (TM) and short
cytoplasmi
fucosidase, alpha-L- 1,
712 202838 PM at FUCA1 tissue 0.000227972 0.0156017 335.3 478.9 509.8 abhydrolase domain
713 222697 PM s at ABHD10 containing 10 0.000228563 0.0156202 33.7 51.1 50.2
714 215067 PM x at PRDX2 peroxiredoxin 2 0.000229843 0.0156857 222.6 180.4 172.9
KIAA163
715 232030 PM at 2 KIAA1632 0.000231505 0.0157696 146.0 87.0 88.2
716 1556818 PM at 0.000231721 0.0157696 256.0 175.5 169.8
717 213684 PM s at PDLIM5 PDZ and LIM domain 5 0.000233554 0.0158667 45.4 33.0 33.3
FA 105 family with sequence
718 229268 PM at B similarity 105, member B 0.000233799 0.0158667 109.1 80.0 85.0
719 241223 PM x at — 0.000239453 0.0162279 97.7 75.5 83.4
720 1560259 PM at — 0.000240266 0.0162603 82.2 53.8 40.2
721 213473 PM at BRAP BRCA1 associated protein 0.000241741 0.0163375 474.0 404.6 393.7
722 221626 PM at ZNF506 zinc finger protein 506 0.000242376 0.0163577 65.0 46.8 47.9
723 233834 PM at — 0.000243937 0.0164403 126.5 70.0 73.5 phosphodiesterase 4C,
724 206792 PM x at PDE4C cAMP-specific 0.000245343 0.0165122 484.6 390.8 415.9 oral-facial-digital
725 241751 PM at 0FD1 syndrome 1 0.000246523 0.0165687 213.3 134.2 138.4 sphingomyelin
phosphodiesterase 3,
neutral membrane
(neutral sphingomyelinase
726 219695 PM at SMPD3 ID 0.000249284 0.0167312 13.0 12.0 17.6
727 232215 PM x at PRR11 proline rich 11 0.00025089 0.0167955 560.9 438.6 461.7
MDN1, midasin homolog
728 1569484 J>M_s_at MDN1 (yeast) 0.000250931 0.0167955 19.2 12.8 12.9
729 243303 PM at — 0.000253404 0.0169377 255.0 170.9 182.6 cycl'in-dependent kinase
730 225697 PM at CDK12 12 0.000253787 0.0169401 256.4 204.5 211.2
1568702_PM_a_a proteasomal ATPase-
731 t PAAF1 associated factor 1 0.00025533 0.0170198 20.3 15.9 15.6 signal sequence receptor,
732 225435 PM at SSR1 alpha 0.000255878 0.017033 234.7 159.6 143.3
733 220969 PM s at 0.00025792 0.0171455 84.5 55.9 53.7 bromodomain PHD finger
734 232909 PM s at BPTF transcription factor 0.000260807 0.0173036 394.0 315.2 313.4
735 230415 PM at — — 0.000261008 0.0173036 227.1 144.1 134.3
736 241724 PM x at — 0.000264391 0.017504 30.4 25.9 27.5
737 244061 PM at 0.000265286 0.0175395 1448.2 941.9 1025.5
738 239496 PM at 0.000268384 0.0177203 66.1 49.8 47.6
739 240367 PM at — 0.000271372 0.0178933 18.6 15.2 14.7
740 240969 PM at 0.000272419 0.0179381 22.1 16.6 16.0
741 244539 PM at 0.000278311 0.0183013 256.0 173.7 154.7
742 1565913 PM at — 0.00028053 0.0184224 116.1 60.3 69.1
743 239545 PM at 0.000281028 0.0184302 157.3 109.5 102.4
Pentatricopeptide repeat
744 228590 PM at PTCD3 domain 3 0.000281682 0.0184332 167.3 129.6 109.1 lysophosphatidic acid
745 204038 PM s at LPAR1 receptor 1 0.000282319 0.0184332 11.6 13.0 16.0
Small nuclear
ribonucleoprotein
746 242146 PM at SNRPA1 polypeptide A' 0.000282356 0.0184332 134.4 91.6 84.9 down-regulator of
transcription 1, TBP- binding (negative cofactor
747 207654 PM x at DR1 2) 0.000282587 0.0184332 153.3 207.5 204.0 trinucleotide repeat
748 213254 PM at TNRC6B containing 6B 0.000285688 0.0185887 278.5 214.6 213.3
1568867_PM_x_a
749 t 0.000286168 0.0185887 11.3 9.4 9.1
750 240315 PM at 0.000286463 0.0185887 67.1 48.5 44.3
751 224740 PM at C5orf43 chromosome 5 open 0.000286497 0.0185887 114.1 197.5 163.1 reading frame 43
glucosidase, alpha; neutral
752 235340 PM at 6ANC C 0.00028733 0.0185987 9.4 8.1 9.3
753 226432 PM at ET K1 ethanolamine kinase 1 0.000287446 0.0185987 58.4 111.9 97.8
754 236462 PM at — 0.000287796 0.0185987 45.8 32.3 31.5
755 232396 PM at — — 0.000288551 0.0186228 611.0 404.4 427.0
756 208185_PM_x_at 0.000288946 0.0186236 24.9 19.3 20.3
757 241786 PM at 0.000290529 0.0187009 332.1 222.1 256.0
P0U5F1
III
P0U5F1
ill
P0U5F1P POU class 5 homeobox 1
3111 /// POU class 5 homeobox
P0U5F1P IB /// POU class 5
758 208286 PM x at 4 homeobox 1 pseudogen 0.000294645 0.0188949 34.0 27.1 27.8
759 238350_PM_at UBN2 ubinuclein 2 0.000294683 0.0188949 159.5 129.5 127.9
760 239451_PM_at — 0.000294888 0.0188949 63.5 46.9 48.3
Numb homolog
761 236930 PM at NUMB (Drosophila) 0.000295483 0.0188949 387.5 234.0 261.8
CUGBP, Elav-like family 1171.
762 242268 PM at CELF2 member 2 0.000295958 0.0188949 1646.3 9 1088.1
763 1556461 PM at — 0.000296154 0.0188949 27.6 17.7 15.6
764 1560492 PM at — 0.000296256 0.0188949 27.0 19.7 20.2
765 227277_PM_at MTDH metadherin 0.000296841 0.0189074 167.6 134.6 123.8
B-cell receptor-associated
766 225674 PM at BCAP29 protein 29 0.000297445 0.0189212 155.2 231.0 231.6
767 242024 PM at — 0.000299844 0.0190371 27.4 19.6 19.0 angiogenic factor with G
768 222661 PM at AGGF1 patch and FHA domains 1 0.000300049 0.0190371 104.8 158.7 143.0 potassium voltage-gated
channel, subfamily G,
769 214595 PM at KCNG1 member 1 0.000301269 0.0190896 12.9 9.4 8.6
770 242431_PM_at — 0.000302138 0.0191198 291.4 220.9 238.4
FAM153 family with sequence
771 1555485 PM s at B similarity 153, member B 0.000304641 0.0192296 12.9 11.0 10.5
1556658_PM_a_a
772 t 0.000304832 0.0192296 234.0 134.6 122.0
773 243997 PM x at 0.000305056 0.0192296 71.2 45.7 42.8
774 216782 PM at 0.000306202 0.0192769 1179.9 554.5 652.8
775 232670 PM at — 0.000306719 0.0192845 40.6 24.4 27.2
776 203457 PM at STX7 syntaxin 7 0.000309226 0.0194171 160.3 198.1 203.8
777 241494_PM_at — 0.000311987 0.0195652 15.7 11.3 12.3
778 231281 PM at — 0.000312819 0.0195832 167.7 103.7 108.9 vacuolar protein sorting
779 218423_PM_x_at VPS54 54 homolog (S. cerevisiae) 0.000313078 0.0195832 71.0 118.1 105.6
780 215587 PM x at — 0.000314098 0.0196219 185.0 134.1 154.6
781 244642 PM at — 0.000315442 0.0196806 162.3 88.4 116.2 protein tyrosine
phosphatase type IVA,
782 200731 PM s at PTP4A1 member 1 0.000317118 0.0197599 111.8 158.4 154.4
783 243006 PM at — 0.000317737 0.0197731 231.8 154.1 127.3 polo-like kinase 1
784 233241 PM at PLK1S1 substrate 1 0.000318798 0.0198139 101.6 66.1 73.3
785 239876 PM at — 0.00031958 0.0198189 200.3 127.8 137.7
786 243509 PM at 0.000319692 0.0198189 187.1 130.6 118.2
787 207657 PM x at TNP01 transports 1 0.00032118 0.0198746 481.0 406.6 389.3
RAB2A, member RAS
788 208731 PM at RAB2A oncogene family 0.000321406 0.0198746 499.3 642.0 675.0
LOC4009
789 235482 PM at 60 hypothetical LOC400960 0.000322138 0.0198946 166.6 126.8 113.8
790 1570021 PM at 0.000322901 0.0199165 105.0 61.6 56.1
SLC25A4 solute carrier family 25,
791 227012 PM at 0 member 40 0.000324196 0.0199607 205.9 347.0 346.6
792 1564236 PM at — 0.00032473 0.0199607 13.3 10.5 9.5
793 237594 PM at 0.000325682 0.0199607 69.8 45.4 40.3 032202
reading frame 53
840 234649 PM at — 0.000395823 0.022961 78.5 51.7 49.3
841 242074 PM at — 0.000397651 0.0230396 145.7 113.1 99.5
842 231109 PM at 0.000399417 0.0231145 778.5 455.6 469.9
843 239923 PM at 0.000400186 0.0231315 615.5 352.9 368.1 guanine nucleotide
binding protein (G
protein), alpha inhibiting 1001.
844 201180 PM s at GNAI3 activity polypeptide 3 0.000404234 0.0233378 830.7 7 978.1 lysine (K)-specific
845 202040 PM s at KDM5A demethylase 5A 0.000405437 0.0233796 824.0 646.3 703.7
846 239969 PM at — 0.000406037 0.0233865 89.6 62.7 62.6
847 228180 PM at — 0.000408895 0.0235042 202.3 158.5 146.2
848 232134 PM at 0.000409046 0.0235042 121.3 96.1 88.1
849 1570192 PM at 0.000410178 0.0235174 222.3 110.7 140.9
JNKl/MAPK8-associated
850 223547 PM at JKAMP membrane protein 0.00041024 0.0235174 57.3 84.1 82.3
CDP-diacylglycerol
CDS2 /// synthase (phosphatidate
LOC1498 cytidylyltransferase) 2 ///
851 228456 PM s at 32 hypothetical pro 0.000412023 0.0235756 473.4 361.8 388.5
852 1561167 PM at 0.000412223 0.0235756 318.7 174.6 180.3
853 237456 PM at 0.000413833 0.0236399 197.6 102.4 107.6
854 215203 PM at G0LGA4 golgin A4 0.000415851 0.0237274 33.5 26.6 27.5
855 244473 PM at — 0.000417637 0.023785 24.6 19.7 17.8
N(alpha)-acetyltransferase
856 217745 PM s at NAA50 50, NatE catalytic subunit 0.000417837 0.023785 342.9 454.8 420.4
857 232096 PM x at — 0.000423244 0.0240647 132.7 93.5 97.3
Smg-7 homolog, nonsense
mediated mRNA decay
858 236367 PM at SMG7 factor (C. elegans) 0.000426413 0.0242038 60.3 43.6 39.9 chromosome 12 open
859 219099 PM at C12orf5 reading frame 5 0.000426684 0.0242038 143.5 195.8 191.5
860 239614 PM x at — 0.000428523 0.0242599 83.0 63.3 57.2
861 1565598_PM_at 0.000429465 0.0242599 219.4 108.9 116.5
862 244548 PM at — 0.000429552 0.0242599 989.0 528.6 550.3
PHD finger protein 20-like
863 222133 PM s at PHF20L1 1 0.000429665 0.0242599 344.9 246.8 263.9 serine/arginine-rich
864 206095 PM s at SRSF10 splicing factor 10 0.000430876 0.0243001 169.2 260.5 244.5
Glutathione S-transferase
865 243325 PM at GSTK1 kappa 1 0.000432321 0.0243534 48.8 34.7 36.0 scaffold attachment factor
866 32099_PM_at SAFB2 82 0.000433362 0.0243839 252.4 183.1 203.6
867 1570200 PM at HELB helicase (DNA) B 0.000434885 0.0244413 78.9 60.2 52.9
868 238651 PM at — 0.000436948 0.024529 298.5 217.3 217.3
869 236617 PM at — 0.00043989 0.0246657 18.3 12.2 13.4
870 240148 PM at M5H6 MutS homolog 6 (E. coli) 0.000440564 0.0246751 26.4 21.5 21.6
ATPase, H+ transporting,
ATP6V1C lysosomal 42kDa, VI
871 202874 PM s at 1 subunit CI 0.000441569 0.024703 180.5 283.6 242.1
C20orfl7 chromosome 20 open
872 225313 PM at 7 reading frame 177 0.00044279 0.0247389 212.6 288.7 286.2
LOC1005 hypothetical
873 237189 PM at 06360 LOC100506360 0.000443225 0.0247389 30.5 18.9 18.4
874 243691 PM at — 0.000444048 0.0247564 30.8 21.6 24.6
875 209684 PM at RIN2 Ras and Rab interactor 2 0.000444718 0.0247648 136.4 227.4 238.7
876 244078 PM at — 0.000445215 0.0247648 35.5 26.5 25.4
877 240939 PM x at — 0.000448669 0.0249274 29.4 21.3 21.6
878 239131 PM at 0.000449161 0.0249274 29.5 20.2 17.8
1560199_PM_x_a LOC7281 similar to FAM133B
879 t 53 protein 0.00044992 0.0249411 400.0 271.5 281.7
880 240108 PM at — 0.000451383 0.0249938 167.6 119.5 119.7
881 239674 PM at 0.00045305 0.0250576 17.3 14.7 14.3
TATA element modulatory
882 214948 PM s at TMF1 factor 1 0.000454991 0.0251364 517.2 389.8 389.4 883 234260 P at — 0.000455932 0.0251599 105.2 74.3 73.8
Structural maintenance of
884 1556925 PM at SMC3 chromosomes 3 0.000459008 0.025301 14.0 11.7 11.9
885 1558922 PM at — — 0.000460623 0.0253613 116.9 86.3 78.3
886 215504 PM x at — 0.000462655 0.0254445 705.6 581.4 607.1
3-phosphoinositide
dependent protein kinase-
887 224986 PM s at PDPK1 1 0.000464555 0.0255201 313.0 372.9 393.7
NSUN5P NOP2/Sun domain family,
888 214100 PM x at 1 member 5 pseudogene 1 0.000466365 0.0255446 217.7 195.5 155.9
889 243458 PM at 0.000467592 0.0255446 44.9 31.2 31.0
TAF11 RNA polymerase II,
TATA box binding protein
(TBP)-associated factor,
890 1558135 PM at TAF11 28kDa 0.000467741 0.0255446 105.9 72.9 80.8
HLA-B associated
891 211947 PM s at BAT2L2 transcript 2-like 2 0.000467783 0.0255446 394.8 277.9 283.8
Bromodomain and WD
repeat domain containing
892 244622_PM_at BRWD1 1 0.000468257 0.0255446 44.1 32.7 32.9 trinucleotide repeat
893 233836 PM at TN C6A containing 6A 0.00046938 0.0255446 19.5 15.2 15.5
894 1555303 PM at — 0.000469387 0.0255446 141.3 79.5 85.0
MPHOSP M-phase phosphoprotein
895 227026_PM_at H8 8 0.000469724 0.0255446 318.7 234.3 248.6
896 244607 PM at 0.000469836 0.0255446 43.4 30.9 33.0
897 227905 PM s at AZI2 5-azacytidine induced 2 0.000470243 0.0255446 24.6 37.2 30.8
898 243300 PM at 0.000472394 0.0256052 15.4 11.8 12.8
899 241891_PM_at — 0.000472887 0.0256052 1177.4 796.8 777.5
900 222514 PM at RRAGC Ras-related GTP binding C 0.000472935 0.0256052 607.8 722.1 691.1 pentatricopeptide repeat
901 219658 PM at PTCD2 domain 2 0.00047383 0.0256252 61.8 52.7 44.8 nuclear factor of activated
T-cells 5, tonicity-
902 215092 PM s at FAT5 responsive 0.000474541 0.0256352 205.3 133.5 151.1 mediator complex subunit
903 207078 PM at MED6 6 0.000475449 0.0256558 58.5 41.8 39.4 chromosome 1 open
904 230608 PM at Clorfl82 reading frame 182 0.000478577 0.025796 17.0 15.9 18.8
FYN oncogene related to
905 1559101 PM_at FYN SRC, FGR, YES 0.000480045 0.0258276 306.8 224.5 184.9
906 1562059 PM at — 0.000480222 0.0258276 125.5 76.2 87.5
UDP-Gal:betaGlcNAc beta
1,4- galactosyltransferase,
907 206233 PM at B4GALT6 polypeptide 6 0.000482556 0.0259245 9.9 11.3 11.9
908 239571 PM at — 0.000484875 0.0260053 352.5 248.8 249.2
LIM domain containing
preferred translocation
909 1558469 PM at LPP partner in lipoma 0.000485128 0.0260053 17.7 14.0 12.8
Coatomer protein
910 233308 PM at C0PB1 complex, subunit beta 1 0.00048641 0.0260266 99.9 68.6 74.7 unc-45 homolog A (C.
911 207499 PM x at UNC45A elegans) 0.000486594 0.0260266 23.4 19.1 20.4
912 241240_PM_at — — 0.000488335 0.0260911 245.3 151.5 178.6
913 215604_PM_x_at — 0.000491675 0.0262191 386.7 308.8 333.0
914 1568866 PM at 0.000491806 0.0262191 46.1 36.8 37.0
915 243801 PM x at — 0.000494418 0.0263295 38.4 31.2 31.7 solute carrier family 26
(sulfate transporter),
916 224963 PM at SLC26A2 member 2 0.000496442 0.0264084 88.6 94.3 64.0 ubiquitin specific
917 223289_PM_s_at USP38 peptidase 38 0.000497818 0.0264325 88.8 121.2 112.3
PAP associated domain
918 226843 PM s at PAPD5 containing 5 0.000498428 0.0264325 449.5 361.7 348.9
ANKRD4 1972.
919 228471 PM at 4 ankyrin repeat domain 44 0.000498876 0.0264325 2457.5 3 2043.1 920 237588 P at — 0.000499064 0.0264325 198.7 112.0 101.2
921 237185 PM at __. — 0.000501862 0.0265442 106.8 41.3 58.3
922 1556416 PM s at ... 0.000502263 0.0265442 49.8 39.0 35.8
923 239926 PM at 0.000505191 0.0266645 82.1 45.7 55.2 cytotoxic T-lymphocyte-
924 231794 PM at CTLA4 associated protein 4 0.000505633 0.0266645 13.8 13.0 11.5
925 225366 PM at PGM2 phosphoglucomutase 2 0.000506926 0.0266801 99.2 146.5 151.2 zinc fingers and
926 1557706 PM at ZHX2 homeoboxes 2 0.000507025 0.0266801 38.1 24.1 25.8
927 1557278 PM s at TNP01 Transports 1 0.00051016 0.0267982 50.6 37.7 35.2 solute carrier family 30
(zinc transporter),
928 212907 PM at SLC30A1 member 1 0.000510575 0.0267982 279.7 452.7 413.3
929 228866 PM at — — 0.00051121 0.0267982 123.7 79.6 76.7
1166.
930 200047 PM s at YY1 YY1 transcription factor 0.000511468 0.0267982 947.2 0 1192.6
931 214405 PM at ... — 0.000512036 0.0267991 378.5 258.8 245.1
Sec23 homolog A (S.
932 204344 PM s at 5EC23A cerevisiae) 0.000513855 0.0268655 18.8 25.8 22.9
933 215592 PM at — 0.000518172 0.0270383 99.2 65.0 61.2
C-type lectin domain 1191.
934 219947 PM at CLEC4A family 4, member A 0.000518808 0.0270383 908.1 3 1202.9 dihydrolipoamide
935 209095_PM_at DLD dehydrogenase 0.000518826 0.0270383 318.4 443.1 400.3
PDS5, regulator of
cohesion maintenance,
936 215888 PM at PDS5B homolog B (S. cerevisiae) 0.000522684 0.0272103 137.4 96.3 92.6 ligase IV, DNA, ATP-
937 206235_PM_at LIG4 dependent 0.000525807 0.0273436 15.7 21.8 19.5 chondroitin sulfate N-
CSGALN acetylgalactosaminyltransf
938 222235 PM s at ACT2 erase 2 0.000527308 0.0273925 309.6 499.7 460.3 small nuclear
ribonucleoprotein
939 226587 PM at SNRPN polypeptide N 0.000528757 0.0274201 74.2 41.9 36.9
940 1556033 PM at FU39739 hypothetical FU39739 0.000528966 0.0274201 229.2 205.4 172.5
RAP2C, member of RAS
941 218669 PM at RAP2C oncogene family 0.000532546 0.0275764 317.5 474.9 457.3
LOClOOl
33445
III hypothetical
L0C1151 LOC100133445 ///
942 232190 PM x at 10 hypothetical LOC115110 0.000534373 0.0276416 33.7 28.3 30.4
SET and MYND domain
943 212921 PM at SMYD2 containing 2 0.000538535 0.0278274 54.8 41.5 34.4
Cyclin-dependent kinase
944 232266 PM x at CDK13 13 0.000539275 0.0278361 960.9 730.0 803.7
945 219027 PM s at MY09A myosin IXA 0.000544917 0.0280839 57.5 46.0 47.1
946 1560332 PM at — 0.000545515 0.0280839 21.5 14.2 17.6
947 240165_PM_at — 0.000546311 0.0280839 231.0 148.7 172.7
948 231205_PM_at — 0.000546629 0.0280839 440.9 251.8 278.3
949 241060 PM x at — 0.000546958 0.0280839 29.1 20.6 17.6
RNA-binding region (RNPl,
950 226975_PM_at RNPC3 RRM) containing 3 0.000548452 0.028131 660.2 526.7 538.6
951 226419 PM s at FU44342 hypothetical LOC645460 0.000552685 0.02829 291.7 195.4 218.9
952 203261_PM_at DCTN6 dynactin 6 0.000552713 0.02829 106.4 155.4 155.1 chromosome 4 open
953 224990_PM_at C4orf34 reading frame 34 0.000553439 0.0282974 129.9 172.5 178.9
954 227393 PM at AN09 anoctamin 9 0.000554704 0.0283323 17.4 14.9 13.3
955 233099 PM at — 0.000556499 0.0283496 13.0 10.3 10.7
956 1559663 PM at — 0.000556916 0.0283496 36.6 21.5 23.0
957 203077_PM_s_at SMAD2 SMAD family member 2 0.000557342 0.0283496 109.8 1333 139.1
958 232347 PM x at — 0.000557372 0.0283496 149.6 112,3 117.7
LOC1002 hypothetical
959 1559136 PM s at 72228 LOC100272228 0.000557951 0.0283496 10.9 10.5 9.5
960 239333 PM x at GST 1 glutathione S-transferase 0.000560501 0.0284495 225.0 175.7 187.6 kappa 1
DCP2 decapping enzyme
961 244777 PM at DCP2 home-log (S. cerevisiae) 0.000561209 0.0284558 818.1 604.5 698.2
962 237953 PM at — — 0.000564728 0.0286045 24.5 16.1 13.3
963 211084 PM x at PRKD3 protein kinase D3 0.000565658 0.0286218 44.2 35.8 34.1
964 218012 PM at TSPYL2 TSPY-like 2 0.000570721 0.0288481 19.3 16.4 14.8
965 243646 PM at — 0.000572724 0.0289193 31.7 24.4 22.1
ATPase,
aminophospholipid
transporter, class 1, type
966 214594 PM x at ATP8B1 8B, member 1 0.000577893 0.0291079 133.5 93.2 101.8
967 243216 PM x at 0.000578007 0.0291079 125.1 103.4 101.7
968 221523 PM s at RRAGD Ras-related GTP binding D 0.000578251 0.0291079 128.2 205.9 191.1
969 1558877 PM at — — 0.000579125 0.0291218 177.8 89.7 95.9 survival motor neuron
970 200071 PM at SMNDC1 domain containing 1 0.000582434 0.0292484 563.2 694.7 713.0
Rap guanine nucleotide
971 204681 PM s at RAPGEF5 exchange factor (GEF) 5 0.000582843 0.0292484 9.3 9.6 11.3
972 239721 PM at — 0.000584451 0.0292839 143.4 96.3 95.6
LOC1002 Similar to malignancy-
973 217102 PM at 87076 associated protein 0.000585345 0.0292839 10.7 9.3 9.9
ARHGAP Rho GTPase activating
974 215232 PM at 44 protein 44 0.000585353 0.0292839 12.7 11.1 13.1
LOC3888
975 232340 PM at 89 hypothetical LOC388889 0.000589789 0.0294389 69.9 55.0 48.8
976 244358 PM at 0.000589852 0.0294389 304.7 149.5 155.6 cytochrome b5 domain
977 226833 PM at CYB5D1 containing 1 0.000590265 0.0294389 21.1 16.7 16.5
978 234731 PM at — 0.000591523 0.0294715 801.1 622.0 673.2 ubiquitin-conjugating
enzyme E2B (RAD6
979 239163 PM at UBE2B homolog) 0.000593286 0.0295292 442.8 263.6 337.4
E74-like factor 2 (ets
domain transcription
980 242735 PM x at ELF2 factor) 0.000596326 0.0296502 207.9 156.9 168.0
981 234621 PM at — 0.000599272 0.0297358 18.9 12.7 13.6
982 242031 PM at — 0.000599401 0.0297358 55.6 42.0 32.3
Adaptor-related protein
complex 4, sigma 1
983 235647 PM at AP4S1 subunit 0.000599879 0.0297358 66.0 49.9 48.6
UDP-GlcNAc:betaGal beta- 1,3-N- acetylglucosaminyltransfe
984 222870_PM_s_at B3GNT2 rase 2 0.000601513 0.0297865 115.6 176.2 194.0 myeloid/lymphoid or
mixed-lineage leukemia
(trithorax homolog,
985 220546 J>M_at MLL Drosophila) 0.000602412 0.0298007 88.2 69.7 61.7
HLA-B associated
986 214052 PM at BAT2L2 transcript 2-like 2 0.000603516 0.0298251 78.2 55.7 57.5
987 230590 PM at — 0.000604485 0.0298303 474.5 243.9 242.2
1292.
988 218404 PM at SNX10 sorting nexin 10 0.000605146 0.0298303 975.9 9 1317.3
989 236755_PM_at — 0.000605459 0.0298303 81.1 57.7 62.3
990 1560171 PM at 0.000607629 0.0299 78.4 64.9 50.2
991 242374 PM at 0.0006081 0.0299 105.3 74.4 69.9 eukaryotic translation
992 201435_PM_s_at E1F4E initiation factor 4E 0.000609565 0.029922 131.1 192.8 172.8
DNA-damage regulated
993 218627 PM at D AM1 autophagy modulator 1 0.000609775 0.029922 117.1 152.4 184.4
1560552_PM_a_a
994 t 0.000612413 0.0300212 23.0 16.5 15.4
1072.
995 216187 PM x at 0.000613591 0.0300487 1334.9 4 1127.7
996 234753 PM x at — 0.000617785 0.0302237 17.6 13.7 15.4
997 232556 PM at — 0.000623426 0.0304281 32.8 24.8 23.5 998 214705 PM at INADL InaD-like (Drosophila) 0.000624089 0.0304281 27.6 18.1 16.2
GRB2-associated binding
999 207112 PM s at GAB1 protein 1 0.000624139 0.0304281 11.9 13.5 14.0
1000 223886 PM s at NF146 ring finger protein 146 0.000624461 0.0304281 469.8 581.7 633.1
KIAA126
1001 225117 PM at 7 KIAA1267 0.000629473 0.0305965 708.1 567.5 592.4 ring finger protein,
1002 227268 PM at RNFT1 transmembrane 1 0.000630131 0.0305965 100.0 162.8 165.7
1003 235328 PM at PLXNC1 Plexin Cl 0.000630354 0.0305965 27.6 20.9 19.8 activating transcription
1004 222103 PM at ATF1 factor 1 0.000630428 0.0305965 121.6 203.3 197.1
1005 235084 PM x at — 0.000631188 0.0306029 680.3 521.1 548.9
C1D nuclear receptor
1006 200056 PM s at C1D corepressor 0.00063303 0.0306617 383.0 501.9 499.8 chromatin modifying
1007 218178 PM s at CHMP1B protein IB 0.00063573 0.0307619 413.1 622.1 593.8
1008 201876 PM at P0N2 paraoxonase 2 0.000642018 0.0310353 64.4 83.3 103.8 protein phosphatase 1,
regulatory (inhibitor)
1009 227412 PM at PPP1R3E subunit 3E 0.000643748 0.0310881 42.0 31.4 27.0
1010 1560680 PM at — 0.000647985 0.0312507 27.6 24.2 21.1 signal sequence receptor,
1011 226712 PM at SSR1 alpha 0.000648398 0.0312507 146.7 108.2 101.4
DDBl and CUL4 associated
1012 220843 PM s at DCAF13 factor 13 0.000649108 0.031254 14.9 12.4 11.0
1013 243808 PM at 0.000652146 0.0313693 42.7 31.9 26.9
1014 218738_PM_s_at RNF138 ring finger protein 138 0.000655843 0.031516 346.9 514.4 498.2
1015 204185 PM x at PPID peptidylprolyl isomerase D 0.000658305 0.0316032 235.6 290.5 285.7
1016 241081 PM at 0.000660309 0.0316682 19.2 14.2 13.5
KIAA191
1017 242851_PM_at 9 KIAA1919 0.000661733 0.0316927 43.6 31.9 32.3 ubiquinol-cytochrome c
1018 209066 PM x at UQCRB reductase binding protein 0.000662121 0.0316927 170.0 360.1 345.4
1019 238970 PM at — 0.000664525 0.0317609 155.2 114.4 96.2 activating transcription
factor 7 interacting
1020 216197 PM at ATF7IP protein 0.000664849 0.0317609 143.4 109.2 98.8
Lon peptidase 2,
1021 221834_PM_at L0NP2 peroxisomal 0.000666186 0.0317936 451.8 354.8 312.9
G0LGA2 golgin A2 family, member
1022 219876 PM s at B B 0.000669547 0.0319227 12.9 10.7 11.9
1556568_PM_a_a
1023 t 0.000671247 0.0319431 107.8 74.0 74.0
TRAPPC1 trafficking protein particle
1024 215269 PM at 0 complex 10 0.000671285 0.0319431 259.6 180.1 180.4
1025 240568 PM at 0.000674356 0.0320579 23.8 17.8 18.6
1026 236437 PM at — 0.000678439 0.0322206 154.6 89.5 113.1
1027 240690 PM at 0.00067947 0.0322269 102.0 59.2 58.4
1028 242506 PM at 0.000680031 0.0322269 30.2 22.9 22.5
NCRNAO non-protein coding RNA
1029 210711 PM at 0260 260 0.000680577 0.0322269 89.5 63.5 51.5
Na+/H+ exchanger domain
1030 229491 PM at NHEDC2 containing 2 0.000681217 0.0322269 21.2 18.7 15.6
1031 241997 PM at — 0.000687566 0.0324957 140.2 105.5 97.8
1032 1563509 PM at — 0.000693415 0.0326067 1276.9 893.8 849.1
1033 203693 PM s at E2F3 E2F transcription factor 3 0.000694069 0.0326067 129.9 171.1 179.0
RNA terminal phosphate
1034 203594 PM at RTCD1 cyclase domain 1 0.000694477 0.0326067 149.6 205.7 170.5
RAB18, member RAS
1035 229398 PM at RAB18 oncogene family 0.000694934 0.0326067 414.7 289.6 309.1 transmembrane protein
1036 218465 PM at TMEM33 33 0.000695471 0.0326067 77.1 113.0 130.5
Zinc finger, CCHC domain
1037 236155 PM at ZCCHC6 containing 6 0.000695476 0.0326067 1242.2 877.5 826.6
1038 209510 PM at RNF139 ring finger protein 139 0.000695929 0.0326067 387.4 514.6 481.4
1039 1564443_PM_at DLEU2 Deleted in lymphocytic 0.000696802 0.0326067 20.6 14.3 14.7 leukemia 2 (non-protein
coding)
1040 208137 PM x at ZNF611 zinc finger protein 611 0.000697333 0.0326067 75.5 58.4 59.9
1041 234148 PM at 0.000697378 0.0326067 24.2 18.6 17.1
1042 243064 PM at 0.000697497 0.0326067 44.8 31.5 33.5 translocated promoter
region (to activated MET
1043 201730 PM s at TPR oncogene) 0.000697945 0.0326067 759.5 569.8 580.7
CASP8 and FADD-like 1034.
1044 239629 PM at CFLAR apoptosis regulator 0.000699042 0.0326266 1603.5 2 1151.0
1045 242320 PM at — 0.000701964 0.0327287 327.6 186.6 191.3
Discs, large homolog 1
1046 230229 PM at DLG1 (Drosophila) 0.000702654 0.0327287 162.6 134.8 110.5
MOB1, Mps One Binder
M0BKL1 kinase activator-like 1A
1047 225997 PM at A (yeast) 0.000703244 0.0327287 86.8 151.6 150.0
1048 239724 PM at 0.000703974 0.0327314 42.3 28.3 30.1 thyroid hormone receptor
1049 236160 PM at T IP11 interactor 11 0.000706422 0.0327917 67.5 49.3 45.3
LOC1005 hypothetical
1050 236386 PM at 06501 LOC100506501 0.000706617 0.0327917 81.6 57.5 59.8
1051 231896 PM s at DENR density-regulated protein 0.00070898 0.0328701 279.2 383.3 376.1
1052 203159 PM at GLS glutaminase 0.000712753 0.0329977 271.6 224.4 196.8 tRNA splicing
endonuclease 15 homolog
1053 225400 PM at TSEN15 (S. cerevisiae) 0.000713875 0.0329977 25.4 36.7 28.3 additional sex combs like 1
1054 212234 PM at ASXL1 (Drosophila) 0.00071392 0.0329977 55.3 47.0 41.6
1055 237337 PM at 0.000714441 0.0329977 59.0 43.2 42.0 family with sequence
1056 217534 PM at FAM49B similarity 49, member B 0.000717444 0.0331009 138.0 82.9 86.4
1057 238544_PM_at — 0.00071842 0.0331009 72.4 39.7 35.5
TBC1D22 TBC1 domain family,
1058 233430 PM at B member 22B 0.000718714 0.0331009 28.4 22.4 19.9
1059 221155_PM_x_at 0.000722005 0.0332211 62.0 46.7 52.0 chromosome 18 open
1060 244233 PM at C18orfl0 reading frame 10 0.000723209 0.0332264 17.8 14.4 14.9
FAM13A FAM13A opposite strand
1061 1558711 PM at OS (non-protein coding) 0.000723485 0.0332264 558.5 363.4 368.1
KIAA039
1062 202714 PM s at 1 KIAA0391 0.000730644 0.0335236 13.5 12.3 11.1
1063 1565703 PM at SMAD4 SMAD family member 4 0.000733037 0.0335891 43.4 30.8 28.9
1064 216000 PM at — 0.000733449 0.0335891 33.8 28.8 24.2 ubiquitin-conjugating
enzyme E2E 2 (UBC4/5
1065 225651 PM at UBE2E2 homolog, yeast) 0.000735351 0.0336446 178.7 226.0 265.1
1066 209566 PM at INSIG2 insulin induced gene 2 0.000737382 0.0336959 51.0 88.7 79.6
1067 234135 PM x at — 0.000737857 0.0336959 61.0 51.9 54.6
DnaJ (Hsp40) homolog,
1068 212908 PM at DNAJC16 subfamily C, member 16 0.000740783 0.0337979 225.1 188.2 173.3
1069 212158 PM at SDC2 syndecan 2 0.000741594 0.0338032 20.7 20.5 34.6
1070 242652 PM at — 0.00074305 0.0338277 13.5 11.6 11.6
1071 240478 PM at — 0.00074352 0.0338277 176.2 129.2 132.6 chromosome 13 open
1072 44790 PM s at C13orfl8 reading frame 18 0.000744289 0.0338311 452.2 473.1 696.4
1073 233270 PM x at 0.000746251 0.0338887 83.1 61.5 62.7
1074 239740 PM at ETV6 ets variant 6 0.000753532 0.0341875 97.5 60.9 66.4
1075 215588 PM x at RIOK3 RIO kinase 3 (yeast) 0.000754615 0.0342048 473.9 368.9 409.2 chromatin modifying
1076 202536 PM at CHMP2B protein 2B 0.000755843 0.0342286 111.7 163.4 167.2
SDCCAG Serologically defined colon
1077 243963 PM at 8 cancer antigen 8 0.000758246 0.034298 234.5 183.6 179.2
1078 222378 PM at 0.000758784 0.034298 39.0 22.5 24.9
1079 215553 PM x at 0.000760604 0.0343484 21.9 17.8 18.8 anaphase promoting
1080 239651 PM at ANAPC5 complex subunit 5 0.000762903 0.0344203 27.5 20.7 21.2 1081 1562528 PM at — 0.000764376 0.0344549 97.0 67.3 41.5
1082 239748 PM x at 0CIAD1 OCIA domain containing 1 0.000766272 0.0345084 930.4 716.6 775.3
1083 238595 PM at 0.000771117 0.0346946 269.3 167.7 171.4 chromosome 4 open
1084 240465 PM at C4orf32 reading frame 32 0.0007729 0.0347427 20.0 15.6 15.2
1085 236327 PM at 0.000773651 0.0347444 157.1 119.1 121.3
1086 243410 PM at 0.000774723 0.0347605 70.9 55.2 50.7
1087 232588 PM at STAG1 stromal antigen 1 0.000776932 0.0348276 55.5 40.0 36.5
1088 242457 PM at — — 0.000779275 0.0349005 137.5 64.9 58.7
1089 207953 PM at — 0.000780244 0.0349118 18.6 14.9 14.7
LOC1002
1090 215287 PM at 88939 Similar to hCG1987955 0.000782993 0.0350027 238.6 180.7 179.6
1091 1560794 PM at 0.000787684 0.0351801 13.2 10.4 11.3
1092 232565 PM at 0.000790598 0.0352779 36.6 28.1 25.2
1093 222169 PM x at SH2D3A 5H2 domain containing 3A 0.000793064 0.0353556 14.2 12.6 11.8
1094 244868 PM at — 0.000794252 0.0353762 33.5 22.8 22.1
SH3 domain binding
glutamic acid-rich protein 1084.
1095 201311 PM s at SH3BG L like 0.000797082 0.0354698 830.9 3 1071.6
1568815_PM_a_a DEAD (Asp-Glu-Ala-Asp)
1096 t DDX50 box polypeptide 50 0.00079804 0.03548 122.3 86.7 91.9 glutathione S-transferase
1097 227163 PM at GST02 omega 2 0.000814076 0.03616 14.7 12.5 13.5
C14orfl4 chromosome 14 open
1098 212460 PM at 7 reading frame 147 0.000820682 0.0364202 90.2 137.8 134.3 adaptor-related protein
1099 1569053 PM at AP3M2 complex 3, mu 2 subunit 0.00082218 0.0364535 20.4 17.2 16.8
1100 242407 PM at — 0.00082641 0.0365795 637.1 400.3 365.6
1101 239946 PM at — 0.000826524 0.0365795 317.5 187.7 188.9
RABGAP RAB GTPase activating
1102 215070 PM x at 1 protein 1 0.000827856 0.0366052 11.5 9.7 10.3 human immunodeficiency
virus type 1 enhancer
1103 233884 PM at HIVEP3 binding protein 3 0.000832504 0.0367699 31.8 25.8 18.1 mediator complex subunit
1104 217843 PM s at MED4 4 0.000833089 0.0367699 196.9 248.0 257.6
1105 238944 PM at ZNF404 Zinc finger protein 404 0.000835718 0.0368525 34.7 24.3 23.2
1106 1557688 PM at — 0.000837575 0.036901 546.6 314.2 328.6 spastic paraplegia 7 (pure
and complicated
1107 230885 PM at SPG7 autosomal recessive) 0.000838625 0.0369139 372.5 277.2 282.1 sphingosine-l-phosphate
1108 221268 PM s at SGPP1 phosphatase 1 0.000839643 0.0369253 25.1 41.9 39.5
1109 244581 PM at 0.00084432 0.0370975 29.7 22.6 21.0
1110 215626 PM at 0.000846447 0.0371575 13.3 11.3 10.4
FAM18B family with sequence
1111 218446 PM s at 1 similarity 18, member Bl 0.000848307 0.0371994 68.2 108.6 120.4 monocyte to macrophage
1112 203414 PM at MMD differentiation-associated 0.000849671 0.0371994 452.7 712.2 689.2
1113 237218 PM at — 0.000849691 0.0371994 82.8 53.8 54.7
1114 222553 PM x at 0XR1 oxidation resistance 1 0.00085174 0,0372556 100.8 160.4 169.3
1115 242824 PM at 0.000854784 0.0373427 34.5 24.5 23.7
1116 206551 PM x at KLHL24 kelch-like 24 (Drosophila) 0.000855873 0.0373427 211.6 156.3 174.8 tumor necrosis factor,
1117 210260 PM s at TNFAIP8 alpha-induced protein 8 0.000856031 0.0373427 528.5 780.3 666.8
1118 242156 PM at — 0.00086286 0.0375636 15.8 11.6 11.5
Tetratricopeptide repeat
1119 244571 PM s at TTC12 domain 12 0.000863136 0.0375636 14.5 11.4 11.2
1120 233302 PM at — 0.000863406 0.0375636 217.7 146.6 75.8
1121 1558236 PM at 0.000866834 0.0376791 287.5 220.0 226.6
Sec23 homolog A (S.
1122 212887 PM at SEC23A cerevisiae) 0.00087007 0.0377662 162.7 225.6 212.1 protein kinase, DNA- activated, catalytic
1123 208694 PM at PRKDC polypeptide 0.00087039 0.0377662 310.8 194.2 200.2
1124 239917 PM at VPS8 Vacuolar protein sorting 8 0.00087152 0.0377705 261.2 174.0 187.7 homolog (S. cerevisiae)
small nucleolar RNA host
gene 9 (non-protein
1125 228645 PM at SNHG9 coding) 0.000872038 0.0377705 23.9 21.1 17.5
A kinase (PRKA) anchor
1126 236007 PM at AKAP10 protein 10 0.000873781 0.0378124 759.7 582.0 627.1
1127 234604 PM at 0.000876504 0.0378965 76.3 38.0 39.8
1128 244290 PM at — 0.000882117 0.0380845 21.3 15.0 15.4
translin-as50ciated factor
1129 203983 PM at TSNAX X 0.000882415 0.0380845 239.3 365.9 374.5 protein phosphatase 4,
1130 225519 PM at PPP4 2 regulatory subunit 2 0,000885487 0.0380901 258.8 370.4 427.5 ligase IV, DIM A, ATP-
1131 227766 PM at LIG4 dependent 0.00088588 0.0380901 22.7 37.2 39.7
1132 242646 PM at — 0.000885928 0.0380901 249.4 193.5 181.7
KIAA165
1133 215750 PM at 9 KIAA1659 protein 0.000886213 0.0380901 21.6 16.9 15.5 hippocampus abundant
1134 225222 PM at HI ATI transcript 1 0.000886801 0.0380901 479.9 584.0 600.6
1135 240238 PM at 0.000887234 0.0380901 116.7 78.0 73.5
1136 243876 PM at 0.000889423 0.0381505 23.3 18.7 17.0 neuroguidin, EIF4E binding
1137 216263 PM s at NGDN protein 0.000890647 0.0381694 25.4 20.3 18.6
1138 215330 PM at 0.000895074 0.038306 43.2 27.1 23.7
1139 1561720 PM at RECQL5 RecQ protein-like 5 0.000895407 0.038306 15.4 12.6 12.4
1140 232583 PM at — — 0.000897151 0.0383382 247.3 164.7 142.8
1141 1558996 PM at FOX PI forkhead box PI 0.000897734 0.0383382 243.0 177.1 166.9
1142 215615 PM x at 0.000900021 0.0384022 14.7 12.6 13.6
Zinc finger, CCHC domain
1143 238800 PM s at ZCCHC6 containing 6 0.000901045 0.0384123 561.9 379.1 373.7
RNA binding motif protein
1144 217856 PM at RBM8A 8A 0.000902061 0.038422 240.2 196.3 196.1
1145 208370 PM s at RCAN1 regulator of calcineurin 1 0.000904627 0.0384976 56.1 81.4 72.8
1146 222262 PM s at ETNK1 ethanolamine kinase 1 0.000905546 0.0385031 34.9 47.7 50.2
KIAA011
1147 224870 PM at 4 KIAA0114 0.000910077 0.038662 132.2 114.3 77.9
1148 244490 PM at — 0.000914068 0.0387977 17.0 15.1 12.5
1149 233223 PM at — 0.000916204 0.0388545 229.8 126.8 132.5
1150 241294_PM_at 0.000917347 0.0388566 78.9 57.4 53.2
1151 237119 PM at — 0.000917848 0.0388566 275.7 172.7 157.4 thyroid adenoma
1152 54632 PM at THADA associated 0.000918721 0.0388598 65.8 54.9 46.8
1153 215151 PM at DOCK10 dedicator of cytokinesis 10 0.000919627 0.0388644 68.3 52.4 43.4 platelet derived growth
1154 222719 PM s at PDGFC factor C 0.000923078 0.0389764 10.0 11.9 12.8
1155 231890 PM at — 0.000929908 0.0392308 91.0 61.5 63.0
1156 1560706 PM at — — 0.000934795 0.0394027 813.7 489.7 487.1
MYST histone
acetyltransferase
1157 1562236 PM at MYST4 (monocytic leukemia) 4 0.000935599 0.0394027 16.7 14.7 13.4 nuclear undecaprenyl
pyrophosphate synthase 1
homolog (S. cerevisiae)
1158 37079 PM at NUS1P3 pseudogene 3 0.000936954 0.0394257 9.2 10.9 10.2
Src kinase associated
1159 241331 PM at SKAP2 phosphoprotein 2 0.000937938 0.039433 24.9 16.4 22.9 down-regulator of
transcription 1, TBP- binding (negative cofactor
1160 209187 PM at DR1 2) 0.000939306 0.0394565 334.6 522.1 505.2 solute carrier family 30
(zinc transporter),
1161 228181 PM at SLC30A1 member 1 0.000940396 0.0394683 27.7 39.3 38.1 chromosome 17 open
1162 226901 PM at C17orf58 reading frame 58 0.000942438 0.0395199 19.8 26.8 25.8
1163 39313 PM at WNK1 WNK lysine deficient 0.000944928 0.0395903 113.9 80.5 75.3 protein kinase 1
1164 242279 PM at — 0.000947662 0.0396562 124.3 86.5 82.8 bobby sox homolog
1165 223134 PM at BBX (Drosophlla) 0.000948129 0.0396562 594.6 470.1 457.6
KRITl, ankyr'in repeat
1166 204738 PM s at KRITl containing 0.000950724 0.0397306 41.2 41.2 34.0
1167 233914 PM s at SBF2 SET binding factor 2 0.00095246 0.0397369 221.5 144.0 159.3
1168 239449 PM at — 0.000952504 0.0397369 37.2 22.9 23.0
1561166_PM_a_a
1169 t 0.000956757 0.0398802 30.6 21.5 21.2
1170 235786 PM at — 0.000963166 0.040113 228.1 176.8 165.5 phosphatidylinositol
1568986_PM_x_a glycan anchor
1171 t PIGT biosynthesis, class T 0.000967031 0.0402396 22.7 18.0 19.7
1172 233800 PM at 0.000969773 0.0403192 207.8 148.8 142.8 tetratricopeptide repeat
1173 208663 PM s at TTC3 domain 3 0.000977441 0.0405812 454.5 378.8 313.8
1174 1556646 PM at — 0.00097774 0.0405812 104.7 78.1 73.0
RNA binding motif protein
1175 213852 PM at BM8A 8A 0.000978667 0.0405851 408.4 313.7 313.5 pho5pholipase A2, group
IVA (cytosolic, calcium-
1176 210145 PM at PLA2G4A dependent) 0.000984729 0.0408018 50.8 84.4 84.4 ring finger and SPRY
1177 225770 PM at RSPRY1 domain containing 1 0.000988575 0.0408945 233.6 203.8 193.3 carboxymethylenebutenol
idase homolog 1302.
1178 234981 PM x at CMBL (Pseudomonas) 0.000988861 0.0408945 1572.4 0 1387.2
1179 235444 PM at F0XP1 forkhead box PI 0.000990226 0.0408945 426.6 299.7 316.1
1180 218595_PM_s_at HEATR1 HEAT repeat containing 1 0.000990634 0.0408945 131.9 97.8 101.0
1181 242874 PM at — 0.000991162 0.0408945 32.6 23.7 18.1
1182 228315 PM at ZMAT3 zinc finger, matrin-type 3 0.000992797 0.0409273 651.6 538.8 516.1
Protein kinase, DNA- activated, catalytic
1183 215757 PM at PRKDC polypeptide 0.000998001 0.041107 29.5 15.8 17.5
1184 215597 PM x at 0.00100129 0.0412077 13.8 11.9 12.2
1185 1555842 PM at CYTH2 cytohesin 2 0.00100876 0.04148 15.2 12.0 12.2
1186 1556306_PM_at — 0.0010118 0.04157 400.4 248.7 281.5
1187 1569597 PM at — 0.00101421 0.0416339 53.3 47.0 34.4
1188 232614 PM at — 0.00101542 0.0416485 134.2 69.5 48.3
1189 206821_PM_x_at A6F62 ArfGAP with FG repeats 2 0.00101641 0.041654 11.0 11.1 12.4
ΚΙΑΑΓ70
4 III
LOC1005 KIAA1704 /// hypothetical
1190 229078__PM_s_at 07773 LOC100507773 0.00102065 0.0417784 128.1 106.6 89.3
1191 1559822 PM s at MTDH metadherin 0.00102116 0.0417784 135.0 117.7 99.5
1192 206567 PM s at PHF20 PHD finger protein 20 0.00102394 0.041857 379.0 287.3 287.7
RNASEH
1193 218496 PM at 1 ribonuclease HI 0.00102602 0.0419069 100.7 86.0 68.6 protein kinase, AMP- activated, alpha 1 catalytic
1194 214917 PM at PRKAA1 subunit 0.0010283 0.0419648 148.0 103.7 105.4 leucine rich repeat
1195 215063 PM x at LRRC40 containing 40 0.00103399 0.0421379 415.2 351.3 361.9
MORF4L 2398.
1196 217982 PM s at 1 mortality factor 4 like 1 0.00103427 0.0421379 2083.6 1 2340.4
1197 201769_PM_at CLINTl clathrin interactor 1 0.00103627 0.0421841 427.8 569.7 594.9 dihydrolipoamide
branched chain
1198 244687 PM at DBT transacylase E2 0.00103809 0.0422064 49.0 41.3 34.0
1199 221264_PM_s_at TARDBP TAR DNA binding protein 0.00103855 0.0422064 406.9 328.6 302.5
1200 241242 PM at — 0.00104186 0.0423056 198.4 130.9 143.4 adenomatous polyposis
1201 215310 PM at APC coli 0.00104337 0.0423316 227.1 157.6 168.5
Nuclear transcription
1202 238231 PM at NFYC factor Y, gamma 0.00104517 0.0423427 98.2 66.4 62.2 1203 238863 PM x at — 0.00104538 0.0423427 20.3 16.7 17.3
1204 1561310 PM at — 0.0010478 0.0424054 10.7 9.4 10.1
CALCOC calcium binding and
1205 238560 PM at 02 coiled-coil domain 2 0.0010503 0.0424713 146.3 94.4 98.3
1206 243546 PM at 0.00105358 0.0425687 95.8 69.2 64.2
1207 244674 PM at 0.00105727 0.0426823 33.6 22.0 23.0
FAM200 family with sequence
1208 236321 PM at B similarity 200, member B 0.00105871 0.0427051 75.1 108.0 114.6 insulin-like growth factor 1
1209 203628 PM at IGF1R receptor 0.00106019 0.0427294 442.5 240.2 246.7
1210 244312 PM at — — 0.00106183 0.0427602 414.4 295.2 313.4
1211 215589 PM at — 0.0010636 0.0427784 15.4 12.4 11.4 heparan sulfate 2-0-
1212 203283 PM s at HS2ST1 sulfotransferase 1 0.00106404 0.0427784 46.3 55.0 61.5
1106.
1213 217873 PM at CAB39 calcium binding protein 39 0.00106547 0.042788 901.3 4 1107.1
1214 243423 PM at 0.00106721 0.042788 115.9 86.4 73.8 chromosome 6 open
1215 218195 PM at C6orf211 reading frame 211 0.00106818 0.042788 193.8 286.2 278.4
1216 216751 PM at 0.00106819 0.042788 19.1 15.7 15.7 protein-L-isoaspartate (D- aspartate) 0- methyltransferase domain
1217 226119_PM_at PCMTD1 containing 1 0.00106929 0.042788 363.2 622.9 612.1
1218 240621 PM at 0.0010696 0.042788 21.6 18.0 18.0
1219 236610_PM_at 0.00107052 0.042788 43.8 30.3 26.5
TRAPPC1 trafficking protein particle
1220 1555446 PM s at 0 complex 10 0.00107184 0.042788 270.7 178.4 175.9 trinucleotide repeat
1221 238468_PM_at TNRC6B containing 6B 0.00107218 0.042788 494.2 355.2 363.6 pleckstrin homology
domain containing, family
F (with FYVE domain)
1222 222699 PM s at PLEKHF2 member 2 0.00107435 0.0428128 69.9 110.8 101.8 integrator complex
1223 233193 PM x at INTS4 subunit 4 0.00107456 0.0428128 13.9 11.9 12.5
FAM200 family with sequence
1224 227270 PM at B similarity 200, member B 0.00108465 0.0431514 64.3 91.5 106.1
1225 217653 PM x at — 0.00108483 0.0431514 47.2 37.5 39.9
1226 212126 PM at CBX5 chromobox homolog 5 0.00108729 0.043214 156.4 112.9 124.7
1227 240326_PM_at — 0.00108962 0.0432385 182.3 103.5 119.0
1228 232307 PM at — — 0.00108968 0.0432385 113.5 64.6 59.1
Musashi homolog 2
1229 239232 PM at MSI2 (Drosophila) 0.00109848 0.0435522 39.6 28.7 28.2
1230 1552343 PM s at P0E7A phosphodiesterase 7A 0.00109961 0.0435615 51.0 35.9 35.9 protein phosphatase 1,
PPP1R12 regulatory (inhibitor)
1231 1557553 PM at B subunit 126 0.00110324 0.0436698 182.7 94.7 102.2
Mdm4 p53 binding protein 1127.
1232 236814 PM at MDM4 homolog (mouse) 0.00110559 0.0437273 1429.5 2 1112.4
1233 234428_PM_at — — 0.00110678 0.0437389 13.1 10.0 10.5
DNA (cytosine-5-)-
1234 222640 PM at DNMT3A methyltransferase 3 alpha 0.00110857 0.0437741 93.3 73.9 71.7
RNA binding motif protein
1235 212027 PM at RBM25 25 0.0011165 0.0440516 702.5 556.5 540.7
WD repeat and SOCS box- 1310.
1236 210561 PM s at WSB1 containing 1 0.00111899 0.0441141 991.0 4 1331.4
1237 1570089 PM at 0.0011224 0.0441774 24.2 20.6 18.8
1238 241913_PM_at — 0.00112241 0.0441774 56.1 35.6 34.1 transmembrane emp24
protein transport domain 1045.
1239 202194 PM at TMED5 containing 5 0.00112677 0.0442901 705.1 9 972.3 cAMP responsive element
1240 207630 PM s at CREM modulator 0.00112709 0.0442901 28.1 37.5 39.2
1241 237839 PM at — 0.00113444 0.044543 26.4 15.7 13.6
1242 226276 PM at TMEM16 transmembrane protein 0.00113546 0.0445471 426.3 579.1 594.3 7A 167A
1243 234609 PM at — 0.00114012 0.044682 23.3 16.4 16.3
1570210_P _x_a protein phosphatase 6,
1244 t PPP6 2 regulatory subunit 2 0.00114073 0.044682 37.7 28.3 27.6
1245 232628 PM at — 0.00114327 0.0447326 334.1 202.5 202.2 carbohydrate (N- acetylglucosamine-6-O)
1246 203921 PM at CHST2 sulfotransferase 2 0.00114386 0.0447326 235.8 301.3 363.2 glucocorticoid induced
1247 225700 PM at GLCCI1 transcript 1 0.00114929 0.0449089 19.4 29.6 27.0
1248 222589 PM at NLK nemo-like kinase 0.00115377 0.0449844 118.3 159.0 160.3
1249 235894 PM at — 0.00115378 0.0449844 117.3 86.7 98.0
1250 241993 PM x at — 0.00115399 0.0449844 389.1 290.4 301.5
1251 233473 PM x at — 0.00115584 0.0450205 974.0 689.3 713.7 nuclear factor of activated
T-cells 5, tonicity-
1252 224984 PM at FAT5 responsive 0.00116222 0.0452328 857.3 694.2 743.5
1253 1570531 PM at — 0.00116466 0.0452916 12.4 10.5 12.0
1254 234326 PM at — 0.0011656 0.045292 337.1 194.8 209.7 armadillo repeat
1255 222444 PM at ARMCX3 containing, X-linked 3 0.00116672 0.0452994 24.2 32.1 37.0
Protein tyrosine
phosphatase, nonreceptor type 13 (APO- 1/CD95 (Fas)-associated
1256 243792 PM x at PTPN13 phospha 0.0011703 0.0454022 19.1 15.6 16.6 protein-L-isoaspartate (D- aspartate) O-
1257 205202 PM at PCMT1 methyltransferase 0.00117229 0.0454433 509.3 727.1 742.4
1258 243739 PM at — 0.00117713 0.0455946 62.6 40.9 40.3 fasciculation and
elongation protein zeta 2
1259 215000 PM s at FEZ2 (zygin II) 0.00118371 0.0458131 286.2 368.4 385.7
1569815_PM_x_a striatin, calmodulin
1260 t STRN binding protein 0.00118601 0.0458656 28.4 19.4 20.0 ubiquitin specific
1261 207365 PM x at USP34 peptidase 34 0.0011908 0.0460096 258.2 201.7 206.2 ubiquinol-cytochrome c
1262 205849 PM s at UQCRB reductase binding protein 0.00119162 0.0460096 151.4 304.8 294.7
CDC14 cell division cycle
14 homolog A (S.
1263 210743 PM s at CDC14A cerevislae) 0.00119405 0.0460669 21.4 17.3 14.7
Proteasome (prosome,
macropain) activator
1264 237180 PM at PSME4 subunit 4 0.00119818 0.0461896 133.8 95.9 109.5
1265 206056 PM x at SPN sialophorin 0.00120053 0.0462437 422.4 352.8 366.3
1266 234159 PM at 0.00120174 0.0462537 82.6 57.7 55.6
1267 224104 PM at 0.00120531 0.0463545 9.8 9.7 11.1
FAM105 family with sequence
1268 219694 PM at A similarity 105, member A 0.00120711 0.0463871 123.2 175.8 167.3
1269 237184 PM at 0.001209 0.0464218 26.6 20.2 19.7 sprouty homolog 2
1270 204011 PM at SPRY2 (Drosophila) 0.00121023 0.0464218 11.0 14.5 13.6
1271 218303 PM x at KRCC1 lysine-rich coiled-coil 1 0.00121087 0.0464218 165.2 258.0 253.6
1272 1559391 PM s at — 0.00121924 0.0467059 740.8 414.6 457.1 chromosome 12 open
1273 225837 PM at C12orf32 reading frame 32 0.00122486 0.0468451 36.3 53.4 40.6 chromosome 1 open
1274 232469 PM x at Clorfl91 reading frame 191 0.0012259 0.0468451 92.0 77.4 71.0
1275 237216 PM at — 0.00122711 0.0468451 23.5 17.6 17.0
1276 1559282 PM at 0.00122737 0.0468451 28.0 21.0 21.3 solute carrier family 33
1554148_PM_a_a (acetyl-CoA transporter),
1277 t SLC33A1 member 1 0.00122768 0.0468451 14.7 20.1 16.8 jumonji domain containing
1278 228793 PM at JMJD1C 1C 0.00122969 0.0468593 994.7 644.1 725.0 1279 242611 PM at — — 0.00123041 0.0468593 16.4 13.4 13.5
1280 230086 PM at FNBP1 formin binding protein 1 0.00123107 0.0468593 18.6 15.0 14.5
1281 215212 PM at — 0.0012319 0.0468593 122.8 79.5 79.0
1282 230099 PM at — — 0.00123347 0.0468824 370.8 275.0 251.1
CAMP responsive element
1283 232555 PM at CREB5 binding protein 5 0.00124092 0.0471288 1517.2 924.2 1042.4
1284 241036 PM at — 0.00124392 0.047206 224.0 169.5 158.1
PRP38 pre-mRNA
processing factor 38
(yeast) domain containing
1285 230270 PM at P PF38B B 0.00124844 0.0473407 806.4 593.9 635.5
1286 235730 PM at 0.00125167 0.0474262 239.8 174.3 192.8
1287 234423 PM x at — 0.00125281 0.0474325 280.4 230.9 229.0
1288 224751 PM at PL-5283 PL-5283 protein 0.00125969 0.047656 617.3 876.2 848.8
1289 241368 PM at PLIN5 perilipin 5 0.00126593 0.0478549 123.5 84.5 136.3
Proteasome (prosome,
macropain) 26S subunit,
1290 232284 PM at PSMD6 non-ATPase, 6 0.0012684 0.0479111 198.2 124.3 123.6
1291 233909 PM at — 0.00127099 0.0479718 12.7 10.8 10.8 solute carrier family 5
(sodium/myo-inositol
1292 213164 PM at SLC5A3 cotransporter), member 3 0.00127396 0.0480466 613.0 462.3 491.5 chromosome 14 open
1293 1553644 PM at C14orf49 reading frame 49 0.00127584 0.0480803 10.5 10.1 11.7
1294 241750 PM x at — 0.00127776 0.0481155 109.8 72.7 81.1
1295 1560926 PM at _„ 0.00127908 0.048128 249.4 159.7 191.7
1559589_PM_a_a
1296 t 0.00128515 0.0483191 28.9 21.7 22.7
1297 237626 PM at — 0.00129452 0.0486338 295.5 211.0 216.1 signal peptide peptidase-
1298 226353 PM at SPPL2A like 2A 0.00130512 0.0489943 789.5 991.8 943.1 amyloid beta (A4)
1299 211277 PM at APP precursor protein 0.00130823 0.0490732 24.3 21.9 21.7 capping protein (actin
filament) muscle Z-line,
1300 1569450 PM at CAPZA2 alpha 2 0.00131042 0.0491176 30.2 21.4 23.8 chromosome 8 open
1301 225600 PM at C8orf83 reading frame 83 0.00131519 0.0492585 59.8 94.1 96.0 retinaldehyde binding
1302 206154 PM at RLBP1 protein 1 0.00131658 0.0492727 12.5 11.0 12.4 high mobility group AT-
1303 1561633_PM_at HMGA2 hook 2 0.00132318 0.0494817 12.7 11.4 10.8
KIAA089
1304 207436 PM x at 4 KIAA0894 protein 0.00132539 0.0495263 354.6 306.9 318.7
GTPase activating protein
(SH3 domain) binding
1305 1557350 PM at G3BP1 protein 1 0.00132688 0.049544 44.8 32.4 29.4 aminoadipate- semialdeh de
dehydrogenase-
AASDHP phosphopantetheinyl
1306 202169 PM s at PT transferase 0.00132799 0.0495474 178.6 260.1 242.2
1307 232210 PM at 0.00132904 0.0495487 391.2 221.5 144.3
1558691_PM_a_a
1308 t D0CK4 dedicator of cytokinesis 4 0.00133158 0.0496054 13.8 12.1 11.3
CASP2 and RIPK1 domain
containing adaptor with
1309 209833 PM at CRADD death domain 0.00133577 0.04967 35.8 45.8 42.0
1310 1554963 PM at — 0.00133636 0.04967 13.8 11.1 11.8
1311 234131 PM at — — 0.00133696 0.04967 106.2 76.1 76.5
1559054_PM_a_a
1312 t 0.00133739 0.04967 68.0 47.8 50.7
1313 242467 PM at 0.00134002 0.0496908 280.3 218.5 215.2
1314 238733 PM at 0.00134142 0.0496908 143.7 88.7 105.1
RAB9A, member RAS
1315 221808 PM at RAB9A oncogene family 0.00134149 0.0496908 307.4 375.4 369.8 neuroepithelial cell
1316 201830 M s at N ET1 transforming 1 0.00134203 0.0496908 18.7 24.9 18.2
TMEM21 transmembrane protein
1317 217D16_PM_x_at 2 212 0.00134421 0.0497337 18.0 14.8 17.0 splicing regulatory
glutamine/lysine-rich
1318 212721 PM at SREK1 protein 1 0.00134616 0.0497681 105.3 175.8 182.7
1319 224105_PM_x_at — — 0.00134808 0.0498013 56.2 47.9 51.4
1320 232978 PM at — 0.00135736 0.0501061 27.9 24.4 19.4
1321 236370 PM at — 0.00136023 0.0501741 40.7 30.8 28.3
1458.
1322 208246 PM x at 0.00136454 0.050295 1858.8 0 1576.1
1323 239701 PM at — 0.00136972 0.0504477 202,0 111.2 112.8
1324 224644 PM at — 0.0013769 0.0506184 521.7 670.3 638.6
TORIAIP torsin A interacting 1446.
1325 212408 PM at 1 protein 1 0.00137762 0.0506184 1217.4 6 1448.5 cytochrome P450, family
3, subfamily A,
1326 205998_PM_x_at CYP3A4 polypeptide 4 0.00137763 0.0506184 21.6 18.8 20.6 mediator complex subunit
1327 224416 PM s at ME028 28 0.00137851 0.0506184 66.6 85.5 90.3
ASAP1 intronic transcript
1328 220694 PM at ASAP1-1T (non-protein coding) 0.00137967 0.0506229 314.9 161.1 189.3
1329 1556728 PM at 0.00138078 0.0506255 75.9 54.2 47.9
1330 236417_PM_at — 0.00138772 0.0508134 188.3 124.2 115.5 alkylglycerone phosphate
1331 205401__PM_at AGPS synthase 0.00138799 0.0508134 26.7 36.6 28.6 chromosome 12 open
1332 1561130 PM at C12orf51 reading frame 51 0.00139089 0.0508306 29.8 22.8 23.3 calmodulin regulated
CAMSAP spectrin-associated
1333 220410 PM s at 1 protein 1 0.00139091 0.0508306 21.8 16.6 16.2
JMJD7- JMJD7-PLA2G4B
PLA2G4B readthrough ///
III phospholipase A2, group
1334 219095_PM_at PLA2G4B IVB (cytosolic) 0.00139159 0.0508306 25.6 20.9 20.2 ubiquitin-conjugating
1335 209096 PM at UBE2V2 enzyme E2 variant 2 0.00139729 0.0510006 89.4 132.0 126.3 v-maf
musculoaponeurotic
fibrosarcoma oncogene
1336 218559_PM_s_at MAFB homolog B (avian) 0.00140241 0.0511491 592.3 883.7 939.1
1337 242793 PM at 0.00140523 0.0512136 50.0 32.8 31.7
1047.
1338 242008 PM at 0.00140833 0.0512516 1505.6 9 1116.4
LOClOOl hypothetical
1339 228913 PM at 90939 LOC100190939 0.00140855 J) 5Jt2516 | 42.8 29.7 29.3
RAB18, member RAS
1340 223336 PM s at RAB18 oncogene family 0.00140948 0.0512516 229.6 362.7 345.9
1341 225147 PM at CYTH3 cytohesin 3 0.00141048 0.0512516 32.7 36.9 45,9
1342 208278 PM s at — 0.00141367 0.0513293 53.2 31.8 33,6
1343 233678 PM at — 0.00141576 0.0513669 14.5 12.9 12,1
1344 244357_PM_at — 0.00141804 0.0514113 621.3 320.1 324.5
1345 240205_PM_x_ at — — 0.00141966 0.0514318 115.2 85.3 88.1 potassium channel
tetramerisation domain
1346 226493 PM at CTD18 containing 18 0.00142551 0.0516054 121.5 161.6 157.9
1347 216745 PM x at — 0.00142692 39.0 32.0 34.4
1348 233007 PM at — 0.00142903 0.05162 60.1 43.8 43.0 tripartite motif-containing
1349 1568594 PM s at T IM52 52 0.00143095 0.05162 92.5 86.8 71.2
1554564_PM_a_a
1350 t SPPL3 signal peptide peptidase 3 0.00143162 0.05162 29.5 23.7 24.3
FAM103 family with sequence
1351 225210 PM s at Al similarity 103, member Al 0.00143168 0.05162 444.6 500.7 522.9
1352 243587_PM_x_at — 0.00143227 0.05162 85.5 61.0 59.5 1353 1563075 PM s at 0.00143366 0.0516319 678.1 437.5 494.0
5'-nucleotidase, cytosolic
1354 236703 PM at NT5C2 II 0.00143781 0.0517431 425.1 268.3 297.8
1355 239227 PM at 0.00144381 0.0519158 65.8 36.7 38.9 chromosome 10 open
1356 244165 PM at C10orfl8 reading frame 18 0.00144474 0.0519158 161.6 97.3 90.3
1357 231087 PM at — 0.00144663 0.0519454 35.7 30.6 25.4
LOC1516 hypothetical protein
1358 1560928 PM at 57 LOC151657 0.00144829 0.0519667 42.0 32.2 31.3
KIAA163
1359 232031 PM s at 2 KIAA1632 0.00145151 0.0520286 33.8 24.3 24.0
1360 1570108 PM at — 0.00145234 0.0520286 33.3 24.4 24.3
RABllFl RAB11 family Interacting
1361 203883 PM s at P2 protein 2 (class 1) 0.00145364 0.0520286 433.2 330.8 343.2
1362 230489 PM_at CD5 CD5 molecule 0.00145462 0.0520286 41.7 37.5 23.5
MGC708 C-terminal binding protein
1363 242136 PM x at 70 2 pseudogene 0.00145553 0.0520286 35.7 42.5 47.0
1364 235288 PM at 0.O0145642 0.0520286 209.1 145.5 158.8
1365 243016 PM at — 0.00145891 0.052078 26.2 19.4 17.0 chromosome 1 open
1366 222720 PM_x_at Clorf27 reading frame 27 0.00145994 O.052078 12.3 15.7 15.0 .
1367 236607 PM at 0.00146319 0.052145 86.5 64.5 64.7
FERM domain containing
1368 213056 PM at F MD4B 4B 0.00146422 0.052145 75.3 96.5 128.6
1369 1557895 PM at FU35934 FU35934 0.00146503 0.052145 25.2 18.1 18.2
1059.
1370 218059 PM at ZNF706 zinc finger protein 706 0.00147057 0.052304 824.7 4 921.0
5TT3, subunit of the
oligosaccharyltransferase
complex, homolog B (S.
1371 238303 PM_at STT38 cerevisiae) 0.00147382 0.0523813 57.8 43.7 37.9 fucose-l-phosphate
1372 205140 PM at FPGT guanylyltransferase 0.00147672 0.0524307 29.9 47.3 47.5
1373 227916_PM_x_at EX0SC3 exosome component 3 0.00147736 0.0524307 219.2 275.0 268.7 chromosome 7 open
reading frame 28B ///
C7orf28B CCZ1 vacuolar protein
1374 201973 PM s at /// CCZ1 trafficking and biogenesi 0.00148545 0.0526794 809.5 979.5 901.4
F-box and WD repeat
1375 209455 PM at FBXW11 domain containing 11 0.00149798 0.0530851 129.5 150.0 146.2 nuclear receptor subfamily
3, group C, member 1 1715.
1376 201865 PM x at NR3C1 (glucocorticoid receptor) 0.00150008 0.0531209 2013.9 9 1694.7 tumor suppressor
1377 209228 PM at TUSC3 candidate 3 0.00150159 0.0531358 9.4 8.9 10.1
1378 240498 PM_at — 0.0015065 0.0532708 54.8 29.9 31.3
1379 230987 PM at — 0.00150865 0.0533082 264.9 153.4 172.8
1380 240626 PM at 0.00150978 0.0533095 15.1 12.7 12.6
1381 231069 PM at 0.0015111 0.0533135 36.6 28.9 29.9 cAMP-regulated
1382 214553 PM s at ARPP19 phosphoprotein, 19kDa 0.0015131 0.0533135 24.5 36.0 33.9
1383 1561060 PM at — 0.00151345 0.0533135 11.6 9.9 10.9
1384 242256 PM x at — 0.00151427 0.0533135 34.1 26.5 31.1
1385 233017 PM x at — 0.00151651 0.0533487 141.5 120.1 130.7 tetratricopeptide repeat
1386 208073 PM x at TTC3 domain 3 0.00151746 0.0533487 378.1 300.5 254.2 regulator of G-protein 1686.
1387 223809 PM at RGS18 signaling 18 0.00152081 0.0534279 1124.9 1 1664.1
1388 236546 PM at — 0.00152367 0.0534898 15.1 12.3 13.2
1389 1557300 PM s at — — 0.00152525 0.0534991 45.8 33.1 31.9
1390 232744 PM x at — 0.00152613 0.0534991 147.6 89.9 84.2
TMEM16 transmembrane protein
1391 238783 PM at IB 161B 0.0015277 0.0535156 158.6 125.3 119.1
1392 218107 PM at WDR26 WD repeat domain 26 0.00153315 0.0536511 826.4 974.5 1036.8 mitogen-activated protein
1393 1558732 PM at MAP4K4 kinase kinase kinase 0.00153377 0.0536511 244.7 154.4 174.4 kinase 4
1394 229360 PM at ZNF280B zinc finger protein 280B 0.00153761 0.0537469 15.3 12.5 12.1
1395 225324 PM at CRLS1 cardiolipin synthase 1 0.00154301 0.053897 61.9 108.9 91.7 fucosyltransferase 4
(alpha (1,3)
fucosyltransferase,
1396 209893 PM s at FUT4 myeloid-specific) 0.00154586 0.0539405 54.5 81.2 64.4
1397 1567045 PM at — 0.00154647 0.0539405 33.2 24.5 25.5
1398 227986 PM at ZNF343 zinc finger protein 343 0.0015482 0.0539622 17.5 14.0 14.8
1399 239788 PM at 0.00154997 0.05397 34.9 25.6 25.0
LOClOOl hypothetical
1400 241851 PM x at 30429 LOC100130429 0.00155064 0.05397 29.1 20.7 22.3
1401 232375 PM at — 0.0015584 0.0541008 468.2 294.9 276.6 peptidyl-prolyl cis-trans
LOC1002 isomerase A-like ///
93160 peptidylprolyl isomerase A
1402 217346 PM at /// PPIA (cyclophilin 0.00155947 0.0541008 55.0 46.5 47.8 activating transcription
1403 226941 PM at ATF6 factor 6 0.00155955 0.0541008 622.1 497.8 535.6 ring finger and CHY zinc
1404 212749 PM s at RCHY1 finger domain containing 1 0.00155965 0.0541008 197.3 276.9 253.5 hexosaminidase B (beta 1061.
1405 201944_PM_at HEXB polypeptide) 0.00155995 0.0541008 847.7 3 1043.5
1406 1570227 PM at — — 0.00156173 0.0541241 27.0 22.6 22.1
1407 217152 PM at — 0.00156614 0.0542135 158.2 111.0 105.3
1408 211374 PM x at 0.00156833 0.0542135 26.8 21.7 22.9
TROVE domain family,
1409 210438 PM x at TR0VE2 member 2 0.00156842 0.0542135 693.6 597.4 559.3
T-cell lymphoma invasion
1410 222942 PM s at TIAM2 and metastasis 2 0.00156876 0.0542135 90.6 50.1 51.0
1411 236883_PM_at — 0.00157206 0.0542719 205.7 153.4 149.9
1412 216006 PM at — 0.00157268 0.0542719 108.6 68.0 73.3
Chromosome 6 open
1413 1556359_PM_at C6orf89 reading frame 89 0.00157408 0.0542724 54.2 40.5 41.7
1414 242171 PM at — 0.00157492 0.0542724 15.5 12.6 13.4 chromosome 22 open
1415 236941 PM at C22orf30 reading frame 30 0.00157693 0.0543003 110.5 74.9 75.2
1416 232769_PM_at — — 0.00157796 0.0543003 44.4 27.0 34.9
LSM14A, SCD6 homolog A
1417 212132 PM at LSM14A (S. cerevisiae) 0.00158011 0.0543067 314.5 358.5 375.3 forty-two-three domain
1418 224642 PM at FYTTD1 containing 1 0.00158105 0.0543067 44.2 63.9 56.4
SH3 domain binding
glutamic acid-rich protein 2827.
1419 201312 PM s at SH3BGRL like 0.00158149 0.0543067 2316.5 1 2855.1
1420 228654 PM at SPIN4 spindlin family, member 4 0.00159134 0.0545691 24.3 41.3 45.5
1421 232580 PM x at — 0.0015921 0.0545691 129.6 96.6 94.3
1422 206175 PM x at ZNF222 zinc finger protein 222 0.00159338 0.0545691 19.6 24.1 25.3
1423 208866_PM_at CSN K1A1 casein kinase 1, alpha 1 0.00159406 0.0545691 401.6 342.0 314.0 aspartyl-tRNA synthetase
1424 218365 PM s at DARS2 2, mitochondrial 0.00159473 0.0545691 16.4 17.2 14.5 vacuolar protein sorting
1425 236254 PM at VPS13B 13 homolog B (yeast) 0.00160153 0.0547633 1169.4 933.1 958.7
1426 244691 PM at SETD5 SET domain containing 5 0.00160515 0.0548486 22.0 17.4 15.7 chromosome 12 open
1427 1557529 PM at C12orf51 reading frame 51 0.0016064 0.0548529 58.8 46.9 44.1 ligand dependent nuclear
1428 228454 PM at LCOR receptor corepressor 0.00161199 0.0550052 703.4 514.4 559.2
1429 243554 PM at 0.00161638 0.0551164 77.7 53.9 54.3
1430 221509 PM at DENR density-regulated protein 0.00162004 0.0551499 219.1 296.9 302.8
1431 237703 PM at — 0.0016203 0.0551499 40.8 29.4 30.2
ELK4, ETS-domain protein
1432 205994 PM at EL 4 (SRF accessory protein 1) 0.00162089 0.0551499 10.3 11.5 10.7 solute carrier family 39
SLC39A1 (metal ion transporter),
1433 227046 PM at 1 member 11 0.00162189 0.0551499 62.4 87.0 77.7 1434 240527_PM_at — 0.00162319 0.0551556 71.1 52.2 54.9
1435 240154 PM at — 0.00163371 0.0554633 1222.2 811.2 806.3
1564773_P _x_a
1436 t 0.00163452 0.0554633 20.0 17.0 16.3 hyaluronan binding
1437 232341 PM x at HABP4 protein 4 0.00163784 0.0555373 28.7 20.8 19.4
1438 215595 PM x at — 0.00163972 0.0555623 29.2 23.4 25.2 chromosome 7 open
1439 224452 PM s at C7orf7D reading frame 70 0.00164229 0.0555725 244.0 320.1 298.0 solute carrier family 38,
1440 243709 PM at SLC38A9 member 9 0.0016423 0.0555725 76.1 54.1 57.5
1441 236592 PM at — — 0.00164591 0.0556184 119.9 56.1 57.6
1442 236453 PM at — 0.00164594 0.0556184 10.7 11.7 14.4
1443 242111 PM at METTL3 methyltransferase like 3 0.00166042 0.0560644 33.3 25.6 23.6
1560445_PM_x_a ARHGEF Rho guanine nucleotide
1444 t 1 exchange factor (GEF) 1 0.0016618 0.0560644 93.5 71.0 75.4
1445 239175 PM at — 0.00166259 0.0560644 533.1 407.2 435.4
Peptidylprolyl isomerase
1446 243414 PM at PPIL2 (cyclophilin)-like 2 0.0016666 0.0561576 36.8 31.1 27.5
1447 232659 PM_at — 0.00166766 0.0561576 41.8 27.6 27.2 glioblastoma amplified
1448 201816 PM s at GBAS sequence 0.00167064 0.0562191 322.9 439.5 389.3
LOC7290 Hypothetical protein
1449 225332 PM at 82 LOC729082 0.0016728 0.056253 684.2 569.3 532.4
1450 242106 PM at 0.00167411 0.0562582 52.7 30.1 31.5
1451 239173 PM at INAOL InaD-like (Drosophila) 0.00167659 0.0563027 22.4 16.8 14.6
1452 1562194 PM at — 0.00168148 0.0564239 389.6 240.5 242.9 cAMP responsive element
1453 205931 PM s at CREB5 binding protein 5 0.0016834 0.0564239 1458.6 949.7 1263.1 metal response element
binding transcription
1454 203347_PM_s_at MTF2 factor 2 0.00168467 0.0564239 34.7 52.0 50.7
1455 244181 PM at — 0.0016858 0.0564239 82.8 61.8 58.4
1456 217586 PM x at — 0.00168599 0.0564239 23.3 18.5 19.1
1457 233369 PM at 0.00168731 0.0564293 589.3 362.9 442.4 ras homolog gene family,
1458 223169 PM s at RHOU member U 0.00169084 0.0565086 11.3 14.8 15.3
1459 232796 PM at 0.00169555 0.0566272 15.9 12.8 12.3
1460 212250 PM at MTDH metadherin 0.00169897 0.0566921 268.8 395.3 343.4
1461 227017 PM at ERICH1 glutamate-rich 1 0.00169982 0.0566921 183.7 214.7 242.6
HEATR7B HEAT repeat family
1462 1569730 PM at 2 member 7B2 0.00170215 0.056731 11.5 10.0 10.8
1463 240446 PM at 0.00170444 0.0567551 25.2 26.0
1464 239892 PM at — 0.0017053 0.0567551 48.7 38.8 35.8 inositol 1,4,5-triphosphate
1465 240052 PM at ITPR1 receptor, type 1 0.00170637 0.0567551 105.7 71.7 73.7
1466 244100 PM at 0.00171135 0.056882 29.4 22.5 23.2
FAM161 Family with sequence
1467 242608 PM x at B similarity 161, member a 0.00171743 0.0569937 603.0 486.0 517.6
1468 216022 PM at — 0.00171835 0.0569937 16.0 13.4 12.6
1469 238436 PM s at ZNF805 zinc finger protein 805 0.00171856 0.0569937 143.2 124.8 102.8 serine/arginine-rich
1470 200753 PM x at SR5F2 splicing factor 2 0.00171939 0.0569937 162.5 218.7 197.1
1471 213922 PM at TTBK2 tau tubulin kinase 2 0.00172865 0.0572617 164.7 119.5 127.7 ubiquitin specific
1472 226729 PM at USP37 peptidase 37 0.00173066 0.0572706 35.0 32.9 26.6
1473 204483 PM at EN03 enolase 3 (beta, muscle) 0.00173146 0.0572706 15.3 13.5 12.9
1474 240260 PM at 0.00173258 0.0572706 45.6 34.2 31.8 mitotic spindle organizing
1475 220720 PM x at MZT2B protein 2B 0.00173362 0.0572706 150.8 118.6 118.7
1476 1562529 PM s at — 0.00173646 0.0573255 508.3 342.7 224.4
1564736_PM_a_a caspase 12
1477 t CASP12 (gene/pseudogene) 0.00173894 0.0573685 10.3 10.3 12.0 congenital
dyserythropoietic anemia,
1478 228516 PM at CDAN1 type 1 0.00174063 0.0573854 51.1 44.5 38.4 1479 241995 PM at DGUOK deoxyguanosine kinase 0.00174243 0.0574059 37.8 28.6 28.5
1480 244594 PM x at — 0.00175136 0.0576159 78.1 59.4 61.6 serpin peptidase inhibitor,
clade E (nexin,
SERPINE plasminogen activator
1481 212190 PM at 2 inhibitor type 1), me 0.00175198 0.0576159 25.8 26.4 36.5
1482 243474 PM at 0.00175235 0.0576159 147.6 84.9 88.8
1483 216278 PM at 0.00175491 0.0576612 38.8 34.0 28.3
1484 234118 PM at 0.00175682 0.0576836 12.4 9.6 10.0
1485 242983 PM at — 0.00175796 0.0576836 37.0 31.1 27.2 centrosomal protein
1486 213956 PM at CEP350 350kDa 0.00176171 0.0577677 154.0 117.9 111.9
1487 232626 PM at 0.00176762 0.0578856 24.1 17.2 20.6
1488 236005 PM at — 0.00176768 0.0578856 23.9 18.0 16.5 chromosome 4 open
1489 222336 PM at C4orf34 reading frame 34 0.00177041 0.0579315 22.6 15.2 17.7 chloride intracellular
1490 213317 PM at CLIC5 channel 5 0.00177146 0.0579315 14.6 12.5 11.7 chromosome X open
1491 231377 PM at CXorf65 reading frame 65 0.00177794 0.0580906 87.7 64.8 56.2
C20orfll chromosome 20 open
1492 215852 PM x at 7 reading frame 117 0.00177871 0.0580906 13.9 12.2 12.5
1493 239778 PM x at 0.0017819 0.0581223 67.7 45.2 46.6
1494 242732 PM at 0.00178484 0.0581223 38.6 24.2 25.0
PHD finger protein 20-like
1495 227523 PM s at PHF20L1 1 0.00178487 0.0581223 1104.7 904.2 905.0
1495 232344 PM at — 0.00178515 0.0581223 112.5 76.2 76.8 protein tyrosine
phosphatase, non¬
1497 205438 PM at PTPN21 receptor type 21 0.00178672 0.0581223 9.7 9.7 11.6
1498 244208 PM at 0.00178756 0.0581223 26.7 18.7 19.4
1499 243860 PM at 0.00178803 0.0581223 157.5 104.9 113.1
1500 1561139 PM at 0.00179722 0.0583549 31.0 24.3 24.3 protein phosphatase 3,
1501 231304 PM at PPP3R2 regulatory subunit B, beta 0.00179758 0.0583549 9.5 9.1 10.6
1502 230777 PM s at PRDM15 PR domain containing 15 0.0017995 0.0583783 43.9 35.9 33.0
1503 242664_PM_at — 0.00180506 0.0584844 11.6 9.9 9.6
1504 233399 PM x at ZNF252 Zinc finger protein 252 0.00180517 0.0584844 73.9 59.8 63.5
1505 1566166 PM at 0.00181697 0.0588276 27.6 21.2 20.1
1506 238548 PM at 0.00181899 0.0588287 20.6 15.4 16.4 adenomatosis polyposis
1507 225016 PM at APCDD1 coli down-regulated 1 0.00182182 0.0588287 15.8 18.2 22.0
1508 244032 PM at 0.00182239 0.0588287 17.7 14.9 14.6 succinate dehydrogenase
complex, subunit D,
integral membrane
1509 202026_PM_at SDHD protein 0.00182256 0.0588287 403.6 505.0 510.6
1510 232466 PM at CUL4A Cullin 4A 0.00182304 0.0588287 16.7 16.3 13.3 nucleolar protein 3
(apoptosis repressor with
1511 221566 PM s at N0L3 CARD domain) 0.00182839 0.0589481 10.0 10.4 11.8
1512 1560342 PM at — 0.00182916 0.0589481 51.7 32.7 34.1
1513 240593 PM x at 0.00183593 0.0591167 21.4 14.8 15.7
1514 242968 PM at — 0.00183682 0.0591167 354.7 260.4 265.7 transmembrane 6
1515 219892 PM at TM6SF1 superfamily member 1 0.00184024 0.0591877 295.4 402.3 432.6 tetratricopeptide repeat
1516 230747 PM s at TTC39C domain 39C 0.0018479 0.0593924 72.8 57.6 45.9
F-box and leucine-rich
1517 239223 PM s at FBXL20 repeat protein 20 0.00184921 0.0593924 124.3 87.3 81.9
1518 243819 PM at — 0.00185026 0.0593924 593.4 471.6 404.2
FAM199 family with sequence
1519 227133 PM at X similarity 199, X-linked 0.0018569 0.0594225 120.2 146.3 158.7 bobby sox homolog
1520 1557239 PM at BBX (Drosophila) 0.00185786 0.0594225 55.9 38.2 37.6
1521 230350 PM at 0.00185917 0.0594225 255.5 195.1 184.9 PRP18 pre-mRNA
processing factor 18
1522 221547 PM at PRPF18 homolog (S. cerevisiae) 0.00185948 0.0594225 65.0 88.7 82.7
Aminopeptidase
1523 214101 PM s at NPEPPS puromycin sensitive 0.0018602 0.0594225 120.2 81.0 81.3 zinc finger, ANl-type
1524 221613 PM s at ZFAND6 domain 6 0.00186232 0.0594225 479.2 578.4 589.9 ubiquitin specific
1525 223288 PM at USP38 peptidase 38 0.00186358 0.0594225 179.4 221.9 237.0
1526 239258 PM at — — 0.00186474 0.0594225 176.4 111.1 121.8
1527 239096 PM at — 0.00186551 0.0594225 215.0 167.5 187.3
1528 81811 PM at 0.00186608 0.0594225 55.3 41.5 40.7 unc-51-like kinase 4 (C.
1529 231149 PM s at ULK4 elegans) 0.0018674 0.0594225 17.7 13.3 13.1 v-akt murine thymoma
1530 236664 PM at AKT2 viral oncogene homolog 2 0.00186813 0.0594225 28.9 24.1 22.8 transmembrane and
tetratricopeptide repeat
1531 226322 PM at TMTC1 containing 1 0.00186893 0.0594225 46.2 92.9 143.5
1532 207923_PM_x_at PAX8 paired box 8 0.00186921 0.0594225 10.9 9.3 10.3 calmodulin regulated
CAMSAP spectrin-associated
1533 244682 PM at 1 protein 1 0.00186949 0.0594225 13.5 10.9 11.9 nuclear receptor binding
1534 243612 PM at NSD1 SET domain protein 1 0.00187215 0.0594609 148.1 110.2 117.1
1535 232205 PM at 0.00187314 0.0594609 53.3 39.8 39.2 serpin peptidase inhibitor,
MGC393 clade B (ovalbumin),
1536 239186 PM at 72 member 9 pseudogene 0.0018809 0.0596684 32.5 21.0 20.9
1537 240351 PM at 0.00188672 0.0598141 18.5 14.8 15.3 mediator complex subunit
1538 209363 PM s at MED21 21 0.00189018 0.059861 22.3 31.2 25.3
1539 236216 PM at — 0.00189247 0.059861 76.6 42.3 45.1
1540 207730 PM x at — 0.0018927 0.059861 528.9 425.8 475.0
ST3 beta-galactoside
alpha-2,3-sialyltransferase
1541 210942 PM s at ST3GAL6 6 0.00189461 0.059861 77.6 113.7 124.9 mannosyl (alpha-1,6-)- glycoprotein beta-l,2-N- acetylglucosaminyltransfe
1542 203102_PM_s_at MGAT2 rase 0.00189569 0.059861 302.8 410.8 387.0
LOC1002 hypothetical
1543 215057 PM at 72228 LOC100272228 0.00189599 0.059861 49.5 34.6 35.9
1544 1569871 PM at LMF1 lipase maturation factor 1 0.0018968 0.059861 29.9 23.1 24.2
LOCIOOI
1545 235990 PM at 30987 similar to hCG1815675 0.00190152 0.0599711 24.4 19.1 19.4
TMEM20 transmembrane protein
1546 222752 PM s at 6 206 0.00190406 0.0600124 69.6 103.3 105.9
1547 242311 PM x at — 0.00190812 0.0600907 46.6 38.8 40.4
1548 232150 PM at 0.00190901 0.0600907 688.6 493.5 539.7
LOC7278 Hypothetical protein
1549 231247 PM s at 20 LOC727820 0.00191175 0.0601381 87.0 61.5 68.7 progestin and adipoQ
receptor family member
1550 227626 PM at PAQR8 VIII 0.00191435 0.0601495 171.2 132.9 117.8
1021.
1551 212449 PM s at LYPLA1 lysophospholipase 1 0.00191734 0.0601495 730.3 2 965.0 teashirt zinc finger
1552 235616 PM at TSHZ2 homeobox 2 0.00191751 0.0601495 16.9 12.5 12.9
1553 225445 PM at UBN2 ubinuclein 2 0.00191834 0.0601495 220.9 171.9 186.6
1313.
1554 234151 PM at 0.00191915 0.0601495 1955.4 1 1262.3 tetratricopeptide repeat
1555 208661 PM s at TTC3 domain 3 0.00191952 0.0601495 329.1 269.7 222.6 numb homolog
1556 242195 PM x at NUMBL (Drosophila)-like 0.00192097 0.0601562 610.5 523.6 550.5 U 2015/032202
homolog, yeast)
1599 200829 P x at ZNF207 zinc finger protein 207 0.00204523 0.0623252 492.3 600.0 596.9
1600 225239 PM at 0.00204808 0.0623651 1535.8 882.2 876.0
1601 224838 PM at F0XP1 forkhead box PI 0.0020491 0.0623651 1161.4 888.0 915.3
3-hydroxy-3- methylglutaryl-CoA
1602 202540 PM s at HMGC reductase 0.00205127 0.0623922 117.9 144.8 163.6
P0U5F1P POU class 5 homeobox 1
1603 210905 PM x at 4 pseudogene 4 0.00205558 0.0624842 12.7 10.5 11.1
FAM102 family with sequence
1604 226568 PM at B similarity 102, member B 0.00205805 O.O62S203 155.4 219.4 221.5 phosphoinositide-3-kinase
1605 221756 PM at PIK3IP1 interacting protein 1 0.00206058 0.0625582 315.4 242.7 187.0
1606 241988 PM x at — 0.0020683 0.0627535 30.5 22.7 21.8 basic leucine zipper and
1607 200777 PM s at BZW1 W2 domains 1 0.00207506 0.0628699 590.6 782.6 676.4
Sfil homolog, spindle
assembly associated
1608 214402 PM s at SFI1 (yeast) 0.00207518 0.0628699 30.9 25.5 22.7
1556203_PM_a_a SLIT-ROBO Rho GTPase
1609 t SRGAP2 activating protein 2 0.00207655 0.0628699 246.0 183.7 157.1 amyotrophic lateral
1610 232184 PM at ALS2 sclerosis 2 (juvenile) 0.0020773 0.0628699 9.5 10.3 11.4 additional sex combs like 2
1611 218659 PM at ASXL2 (Drosophila) 0.00207993 0.0629105 485.2 373.5 403.3
1612 233289 PM at — 0.00208249 0.0629488 66.7 49.3 45.9
G protein-coupled
1613 204137_PM_at GPR137B receptor 137B 0.00208751 0.0630614 106.7 150.6 169.9 transmembrane and
1614 226050 PM at TMC03 coiled-coil domains 3 0.00209242 0.0631706 253.6 311.0 353.6
RAB18, member RAS
1615 224377 PM s at RAB18 oncogene family 0.0020964 0.0632399 367.1 499.6 515.7 tankyrase, TRF1- interacting ankyrin-related
1616 216695 PM s at TNKS ADP-ribose polymerase 0.00209731 0.0632399 13.0 11.1 11.9
VGF nerve growth factor
1617 205586_PM_x_at VGF inducible 0.00210124 0.0632482 11.1 9.6 9.6
1618 1556657_PM_at — 0.00210147 0.0632482 221.5 133.9 124.3 interferon-related
1619 202147 PM s at IFRD1 developmental regulator 1 0.00210148 0.0632482 283.9 372.9 436.2 anaphase promoting
1620 200098 PM s at ANAPC5 complex subunit 5 0.00211129 0.0635042 688.6 614.3 556.9
FA 115 family with sequence
1621 204403 PM x at A similarity 115, member A 0.00212582 0.0638777 28.1 24.0 25.7
Clq and tumor necrosis
1622 1561263 PM at C1QTNF3 factor related protein 3 0.00212633 0.0638777 14.6 12.3 11.9 ankyrin 3, node of Ranvier
1623 209442 PM x at ANK3 (ankyrin G) 0.00212886 0.0639143 29.8 18.7 16.4
Tetratricopeptide repeat
1624 232646 PM at HC17 domain 17 0.00213201 0.0639695 37.5 27.3 26.4
Lysophosphatidylcholine
1625 213615 PM at LPCAT3 acyltransferase 3 0.00213472 0.0640114 21.7 19.8 16.8 human immunodeficiency
virus type 1 enhancer
1626 212642 PM s at HIVEP2 binding protein 2 0.00213796 0.064059 75.5 55.7 55.2 multiple C2 domains,
1627 235740 PM at MCTP1 transmembrane 1 0.00213967 0.064059 109.0 168.0 163.5
1628 221145 PM at 0.00214126 0.064059 10.9 10.3 12.1
1629 236924 PM at 0.00214209 0.064059 45.1 30.4 28.4
1630 1560443 PM at 0.00214288 0.064059 246.7 150.8 169.6
1631 244301 PM at 0.0021528 0.0643161 8.9 10.0 10.1 myeloid/lymphoid or
mixed-lineage leukemia
(trithorax homolog,
1632 225992 PM at MLLT10 Drosophila); translocate 0.00215843 0.0643965 51.9 74.9 64.5
1633 221786 PM at C6orfl20 chromosome 6 open 0.00215863 0.0643965 162.4 223.2 214.2 02
member 2
1673 203007 PM x at LYPLA1 lysophospholipase 1 0.00228733 0.0665968 556.2 723.5 626.0
1674 217671 PM at — 0.00228791 0.0665968 88.4 62.1 55.2 small proline-rich protein
1675 236119 PM s at SPRR2G 2G 0.00229039 0.066609 12.0 10.8 10.4
NIPA-like domain
1676 225876 PM at NIPAL3 containing 3 0.00229168 0.066609 168.8 142.1 113.1 coiled-coil domain
1677 222432 PM s at CCDC47 containing 47 0.00229243 0.066609 149.3 169.9 192.9
D-2-hydroxyglutarate
1678 228738 PM at D2HGDH dehydrogenase 0.00229436 0.0666253 28.1 25.3 20.3 neuroblastoma breakpoint
1679 230712 PM at NBPF1 family, member 1 0.0022965 0.0666477 157.3 107.3 103.5
VAMP (vesicle-associated
membrane protein)- associated protein A,
1680 242780 PM at VAPA 33kDa 0.00229898 0.0666526 60.8 41.4 47.4 chromosome 5 open
1681 1553107 PM s at C5orf24 reading frame 24 0.00230072 0.0666526 130.7 108.4 108.2
RAB21, member RAS
1682 203885 PM at RAB21 oncogene family 0.00230077 0.0666526 184.2 236.8 240.0
1683 243005 PM at — 0.0023065 0.0667789 43.4 32.7 30.0
LOC2829
1684 222307 PM at 97 hypothetical LOC282997 0.00231381 0.0669231 100.3 68.8 65.1
1685 243182_PM_at 0.00231423 0.0669231 135.3 83.7 81.2 chromosome 11 open
1686 228249 PM at Cllorf74 reading frame 74 0.00231604 0.0669358 13.3 15.3 17.3
DNA-damage regulated
1687 225228 PM at D AM 2 autophagy modulator 2 0.0023257 0.0671751 111.9 158.2 147.6
Smith-Magenis syndrome
chromosome region,
1688 204594 PM s at SMCR7L candidate 7-like 0.0023287 0.0672219 90.8 78.2 67.1
1689 238393 PM at — 0.00233582 0.0673875 10.2 8.6 9.2
BTS (POZ) domain
1690 217945 PM at BTBD1 containing 1 0.00233926 0.0674236 226.9 290.8 294.2 cytoplasmic
polyadenylation element
1691 226939 PM at CPEB2 binding protein 2 0.00233984 0.0674236 263.3 395.7 474.0
1692 227116__PM_at M0IM1B MON1 homolog B (yeast) 0.00234772 0.0675747 296.8 367.9 364.0
1693 242759 PM at — 0.00234837 0.0675747 31.3 25.3 24.0 endogenous retroviral
1553352_PM_x_a family W, env(C7),
1694 t ERVWEl member 1 0.00234941 0.0675747 18.5 15.5 19.6
Thyroid adenoma
1695 1566889 PM at THADA associated 0.00235063 0.0675747 21.6 17.7 16.3 activity-dependent
1696 226426 PM at ADNP neuroprotector homeobox 0.00235345 0.0676159 173.2 140.4 137.5
Nicotinamide 4363.
1697 243296 PM at NAMPT phosphoribosyltransferase 0.00235557 0.0676369 6234.7 4 5001.5
1698 232330 PM at 0.00235802 0.0676674 353.4 276.0 237.6 coagulation factor II
1699 230147 PM at F2RL2 (thrombin) receptor-like 2 0.00236341 0.0677822 8.9 9.8 10.3 serine
palmitoyltransferase, long
1700 227752 PM at SPTLC3 chain base subunit 3 0.00236684 0.0678239 9.6 9.4 10.7 ras responsive element
1701 242297 PM at RREB1 binding protein 1 0.00236765 0.0678239 263.6 209.9 203.7 sphingosine-l-phosphate
1702 223391 PM at SGPP1 phosphatase 1 0.0023695 0.067837 98.1 146.7 144.4
1703 215612 PM at 0.00238305 0.068164 39.4 30.1 28.8
1570078_PM_a_a
1704 t D0CK5 dedicator of cytokinesis 5 0.00238372 0.068164 238.5 134.7 130.1
1705 226085 PM at CBX5 chromobox homolog 5 0.00238525 0.0681678 45.1 32.5 29.3
1706 237943 PM at — 0.00238947 0.0682484 206.3 121.3 134.9
1707 241159 PM x at — 0.00239578 0.0683885 34.0 28.0 27.2
1708 1555561 PM a a UGGT2 UDP-glucose glycoprotein 0.00240013 0.0684726 8.8 10.5 9.9 t glucosyltransferase 2
ribulose-5-phosphate-3-
1709 225040 P s at PE epimerase 0.0024137 0.0687956 66.9 108.6 104.9
1710 1570335 PM at 0.00241512 0.0687956 15.0 12.2 12.1
1711 201534 PM s at UBL3 ubiquitsn-like 3 0.00241611 0.0687956 333.0 456.3 410.9
1557283_PM_a_a
1712 t 2NF519 zinc finger protein 519 0.0024171 0.0687956 15.0 12.1 11.7
1713 237544 PM at — 0.00242071 0.0688581 256.5 186.1 171.6
1714 238888 PM at 0.00242768 0.0690161 126.5 88.2 90.5
1715 232763 PM at TLN1 Tal'in 1 0.00243337 0.069137 68.8 42.3 52.9
LOC1005 hypothetical
1716 236645 PM at 06312 LOC100506312 0.00243477 0.069137 176.0 119.5 113.9 enhancer of yellow 2
1717 218482 PM at ENY2 homolog (Drosophila) 0.00244156 0.0692326 279.5 381.1 398.2
1718 237176 PM at — 0.00244236 0.0692326 755.4 544.8 580.0 ubiquitin specific
1719 226176 PM s at USP42 peptidase 42 0.0024424 0.0692326 250.5 200.0 196.3
NGFI-A binding protein 1
1720 211139 PM s at NAB1 (EGR1 binding protein 1) 0.00244949 0.0693932 122.4 87.3 88.4 neuroblastoma RAS viral
1721 202647 PM s at AS (v-ras) oncogene homolog 0.00245174 0.0694166 50.4 71.1 64.3 cornichon homolog
1722 201653 PM at CNIH (Drosophila) 0.00245348 0.0694255 395.5 542.0 471.3
1723 201800 PM s at OSBP oxysterol binding protein 0.00245706 0.0694865 145.1 130.5 123.8
1724 234565 PM x at — 0.00246042 0.0695411 23.7 20.0 20.8
1725 242235 PM x at — 0.0024639 0.069563 514.7 396.2 447.4
1726 239063 PM at 0.00246405 0.069563 23.6 21.9 15.8 sema domain,
immunoglobulin domain
(Ig), transmembrane
domain (TM) and short
1727 228660 PM x at SEMA4F cytoplasmi 0,00246807 0.0696004 17.0 14.8 14.1
1728 1569041 PM at — 0.00246823 0.0696004 15.9 12.4 13.4
Synaptosomal-associated
1729 229773_PM_at SNAP23 protein, 23kDa 0.0024732 0.0697002 176.6 119.6 128.5
1730 221735 PM at WDR48 WO repeat domain 48 0.00247658 0.0697551 383.4 349.4 325.4
1731 228902_PM_at NUP214 nucleoporin 214kDa 0.00248086 0.0698353 74.2 97.1 99.1
RAP1B, member of RAS 3042.
1732 200833 PM s at RAP1B oncogene family 0.00248892 0.0700217 2219.0 4 2647.5
Pentatricopeptide repeat
1733 228512 PM at PTCD3 domain 3 0.00249085 0.0700356 85.7 69.5 61.6
1734 232653 PM at — 0.00249628 0.0701385 200.2 122.6 134.9
Integrin alpha FG-GAP
1735 1556151 PM at ITFG1 repeat containing 1 0.00249739 0.0701385 311.4 371.2 395.4
1736 224098 PM at — 0.00250148 0.0702129 78.9 55.1 46.8 trafficking protein, kinesin
1737 202079 PM s at TRAK1 binding 1 0.00251159 0.0704561 52.9 72.4 70.4
1738 241642 PM x at TLK1 tousled-like kinase 1 0.00251368 0.0704742 113.5 94.7 97.3
THAP domain containing,
apoptosis associated
1739 219292 PM at THAP1 protein 1 0.00251533 0.0704799 44.0 65.0 61.5
1740 206862 PM at ZNF254 zinc finger protein 254 0.00251742 0.0704979 11.5 12.9 14.8 chromosome 1 open
1741 223511 PM at Clorfl24 reading frame 124 0.0025221 0.0705884 17.1 23.8 23.8
1742 242728 PM at — 0.00252386 0.0705971 44.3 36.2 34.5 uroporphyrinogen III
1743 232560 PM at UROS synthase 0.00252897 0.0706265 9.4 . 10.4 10.5
1744 241435 PM at — 0.00252939 0.0706265 1042.7 727.8 585.8
1745 243280 PM at 0.00253007 0.0706265 106.8 75.9 76.7 kelch-like 2, Mayven
1746 219157 PM at KLHL2 (Drosophila) 0.00253071 0.0706265 479.7 694.1 769.2
1747 1569512 PM at — 0.00253461 0.0706949 253.0 138.5 149.2
1748 244425 PM at — — 0.00253824 0.0707556 202.7 139.5 142.0 solute carrier family 30
(zinc transporter),
1749 226217 PM at SLC30A7 member 7 0.00254144 0.0708043 549.2 467.6 440.6 neuroblastoma RAS viral
1750 224985 PM at RAS (v-ras) oncogene homolog 0.00254497 0.0708515 260.7 368.1 329.9
LFNG O-fucosylpeptide 3- beta-N- acetYlglucosaminyltransfe
1751 215270 PM at LFNG rase 0.00254604 0.0708515 23.6 33.9 32.4
X-prolyl aminopeptidase
(aminopeptidase P) 3,
1752 237750 PM at XPNPEP3 putative 0.00255399 0.0709593 29.5 22.7 21.5
Heterogeneous nuclear
ribonucleoprotein D (AU- rich element RNA binding
1753 227744 PM s at HNRNPD protein 1, 37kDa 0.00255406 0.0709593 10.4 10.5 11.9 osteopetrosis associated
1754 218196 PM at 0STM1 transmembrane protein 1 0.00255465 0.0709593 257.5 381.6 339.6
NIMA (never in mitosis
1755 204634 PM at NEK4 gene a)-related kinase 4 0.00255574 0.0709593 48.5 71.9 73.7 coiled-coil domain
1756 1568834 PM s at CCDC90B containing 90B 0.00255881 0.0710041 119.1 88.9 86.5
1757 212660 PM at PHF15 PHD finger protein 15 0.00256264 0.0710677 172.7 144.7 116.6
1758 233976 PM at — 0.00256539 0.0710677 198.4 152.6 158.3
1759 237239 PM at — 0.00256548 0.0710677 369.0 258.8 281.9
T cell receptor beta
1760 234883 PM x at TRBV7-3 variable 7-3 0.00257058 0.0711686 23.7 21.9 15.7
1761 237412 PM at — 0.00257386 0.0711823 21.6 18.3 17.0
STARD3
1762 223065 PM s at NL STARD3 N-terminal like 0.002574 0.0711823 370.9 489.3 516.4
1763 233300 PM at — 0.00258302 0.0713305 145.5 99.1 99.1
1764 241219 PM at 0.00258359 0.0713305 43.4 32.8 31.5
LOC1002 hypothetical
1765 238473 PM at 16545 LOC100216545 0.00258375 0.0713305 17.1 13.9 14.2
1766 218754 PM at N0L9 nucleolar protein 9 0.00258597 0.0713514 136.3 122.6 96.6
SLC25A4 solute carrier family 25,
1767 212833 PM at 6 member 46 0.00259083 0.0714078 259.1 361.0 335.9 runt-related transcription
1768 216994 PM s at RUNX2 factor 2 0.00259224 0.0714078 10.7 9.4 9.4
1556672_PM_a_a RNA binding motif protein
1769 t RBM6 6 0.00259241 0.0714078 24.7 17.4 17.9
1770 231212 PM x at 0.00259651 0.0714803 17.2 14.5 16.7
1771 231035 PM s at 0.00260088 0.0715432 42.1 59.5 67.4
1772 230756 PM at ZNF683 zinc finger protein 683 0.00260173 0.0715432 21.2 26.7 17.6
1773 241448 PM at — 0.00260385 0.0715611 29.1 23.2 22.8 chromosome 1 open
1774 233693 PM at Clorf201 reading frame 201 0.00260717 0.0716119 17.0 14.0 15.6
1557505_PM_a_a
1775 t 0.0026167 0.0718332 85.3 58.4 61.0
1776 234657 PM at 0.0026244 0.072004 22.8 17.7 19.2
1777 225383 PM at ZNF275 zinc finger protein 275 0.00263161 0.0721612 158.4 133.1 96.6
1778 213292 PM s at SNX13 sorting nexin 13 0.00263732 0.0722771 101.7 141.5 138.5
1779 218265 PM at SECISBP2 SECIS binding protein 2 0.00264018 0.0723148 167.1 135.1 136.3 spermatogenesis
1780 238459 PM x at SPATA6 associated 6 0.0026484 0.0724992 9.8 9.2 10.5
TROVE domain family,
1781 212852 PM s at TR0VE2 member 2 0.00265056 0.0725176 1001.7 839.5 867.1
1782 236963 PM at 0.00265207 0.0725182 22.9 15.9 15.2
1783 1560771 PM at 0.00265437 0.0725404 10.6 9.6 11.4
Ral GTPase activating
RALGAP protein, alpha subunit 2
1784 232500 PM at A2 (catalytic) 0.00265586 0.0725404 844.3 552.7 563.1
Hexamethylene bis-
1785 214188 PM at HEXIM1 acetamide inducible 1 0.00267308 0.0729698 92.1 62.0 69.8
LOC7290 Hypothetical protein
1786 225225 PM at 82 LOC729082 0.00268123 0.0731513 816.1 728.6 684.3 spectrin, alpha, non- erythrocytic 1 (alpha-
1787 214925 PM s at SPTAN1 fodrin) 0.00268359 0.0731748 18.5 14.9 13.7 hyaluronoglucosaminidase
1788 210619 P s at HYAL1 1 0.00268625 0.0732063 12.3 12.5 14.6 receptor accessory protein
1789 225785 PM at EEP3 3 0.00269026 0.0732746 155.5 216.8 220.9
1790 203248_PM_at 7.NF24 zinc finger protein 24 0.00269663 0.0734071 25.1 32.1 31.7
1791 236946 PM at — 0.00270089 0.0734562 35.5 25.9 29.2
ANAPC1 anaphase promoting
1792 224667 PM x at 6 complex subunit 16 0.00270145 0.0734562 965.2 789.1 852.8 chromatin modifying
1793 202538 PM s at CHMP2B protein 2B 0.00271151 0.0736886 261.4 335.9 311.5 ring finger and SPRY
1794 225774 PM at RSPRY1 domain containing 1 0.00271833 0.0738328 79.8 108.0 94.2
1795 219482_PM_at SETD4 SET domain containing 4 0.00272531 0.0739812 48.4 43.1 36.7
LOClOOl hypothetical
1796 216107 PM at 29503 LOC100129503 0.00272787 0.0740094 11.0 10.6 12.2
1797 243931 PM at — 0.00273033 0.0740349 1040.1 794.8 804.1 multiple C2 domains,
1798 220603 PM s at MCT 2 transmembrane 2 0.00273533 0.0741293 330.0 338.5 465.8 splicing regulatory
glutamine/lysine-rich
1799 243361 PM at SRE 1 protein 1 0.00274347 0.0742805 44.4 35.3 35.6
1800 225484 PM at TSGA14 testis specific, 14 0.00274396 0.0742805 39.7 33.5 29.7
1801 244249 PM at — 0.00274878 0.0743697 31.1 22.7 25.8 potassium channel
tetramerisation domain
1802 218474 PM s at KCTD5 containing 5 0.00275283 0.0744379 141.9 210.2 182.5
PR domain containing 2,
1803 205277 PM at PRDM2 with ZNF domain 0.00275856 0.0744924 102.5 78.6 66.3
1804 221013 PM s at AP0L2 apolipoprotein L, 2 0.00276054 0.0744924 25.7 21.7 20.9 major intrinsic protein of
1805 220863 PM at MIP lens fiber 0.00276109 0.0744924 10.7 11.0 12.3 chromosome 22 open
1806 216555 PM at C22orf30 reading frame 30 0.00276119 0.0744924 334.7 263.2 302.6
1807 203132 PM at RBI retinoblastoma 1 0.00276249 0.0744924 123.5 169.0 178.7
RAB11FI RAB11 family interacting
1808 228613 PM at P3 protein 3 (class II) 0.00277251 0.0747213 88.9 60.0 52.1
1809 241588 PM at 0.00277507 0.0747489 18.3 15.8 14.4
1810 242216_PM_at — — 0.00279169 0.0751551 41.1 31.4 28.1
1811 243442 PM x at 0.00279361 0.0751652 35.2 29.8 31.8 chromosome 6 open
1812 238860 PM at C6orfl30 reading frame 130 0.00280565 0.0754475 145.8 120.8 112.2
1813 217164 PM at — 0.00281545 0.0756693 309.4 245.1 197.5
X-prolyl aminopeptidase
(aminopeptidase P) 3,
1814 226501 PM at XPNPEP3 putative 0.00281717 0.0756738 133.0 96.7 98.4
1815 230324 PM at — — 0.00282409 0.0757882 123.6 91.1 88.4 tripartite motif-containing
1816 210266 PM s at TRIM33 33 0.00282454 0.0757882 891.0 758.8 761.0
1817 231302 PM at 0.00282886 0.0758491 137.7 86.0 97.4
1557733_PM_a_a
1818 t 0.00283039 0.0758491 55.2 30.3 27.6
1819 204325 PM s at NF1 neurofibroma 1 0.00283195 0.0758491 11.3 9.6 9.6 staufen, RNA binding
protein, homolog 2
1820 204226 PM at STAU2 (Drosophila) 0.00283353 0.0758491 41.7 62.6 57.3
DnaJ (Hsp40) homolog,
1821 1556053 PM at DNAJC7 subfamily C, member 7 0.00283528 0.0758491 263.2 211.4 219.2
WAS protein family,
1822 204165 PM at WASF1 member 1 0.00283615 0.0758491 20.1 23.2 32.0
Pellino homolog 1 1045.
1823 232304 PM at PELI1 (Drosophila) 0.00283972 0.0759029 1637.9 8 1096.8
1824 221841 PM s at KLF4 Kruppel-like factor 4 (gut) 0.00284676 0.0760384 365.1 487.7 528.4
1825 242440_PM_at — 0.00284916 0.0760384 30.0 19.9 20.9
1826 239726 PM at — — 0.00284947 0.0760384 40.2 26.5 21.4
1827 1563320 PM at 0.00285747 0.0761441 26.6 21.5 21.1
1828 242854 PM x at DLEU2 deleted in lymphocytic 0.00285768 0.0761441 161.6 125.0 112.2 leukemia 2 (non-protein
coding)
eukaryotic translation
initiation factor 4E binding
1829 224645 PM at EIF4EBP2 protein 2 0.00285812 0.0761441 210,2 174.5 159.1 mediator complex subunit
1830 203496 PM s at MED1 1 0.0028614 0.0761498 171.9 145.5 134.9
C21orfl2 chromosome 21 open
1831 1553282 PM at 8 reading frame 128 0.00286146 0.0761498 9.8 9.2 8.6
LOC7284
1832 242070 PM at 85 hypothetical LOC728485 0.00286444 0.0761872 10.9 11.4 12.7 coiled-coil domain
1833 227208 PM at CCDC84 containing 84 0.00286599 0.0761872 216.6 174.9 168.8
1557797_PM_a_a
1834 t 0.00286808 0.0762012 309.0 220.5 223.1 coenzyme Q7 homolog,
1835 210820 PM x at C0Q7 ubiquinone (yeast) 0.00287385 0.0762795 13.0 16.6 17.4 tumor necrosis factor
TNF SF1 receptor superfamily,
1836 231775 PM at OA member 10a 0.00287422 0.0762795 180.6 145.4 125.6
1837 219520 PM s at WWC3 WWC family member 3 0.00287674 0.0762795 756.0 570.8 589.3
1838 228983 PM at — 0.00287729 0.0762795 33.4 25.1 27.5
METTL7 1303.
1839 207761 PM s at A methyltransferase like 7A 0.00287972 0.0763024 1051.5 3 1344.0
1840 218873 PM at G0N4L gon-4-like (C. elegans) 0.0028832 0.0763331 142.0 122.9 109.0
1841 242357 PM at — 0.00288474 0.0763331 19.9 16.4 16.2
NFKB activating protein
1842 236493 PM at NKAPP1 pseudogene 1 0.00288558 0.0763331 17.0 14.8 13.7
LOC1002 Hypothetical protein
1843 233775 PM x at 89333 LOC100289333 0.00289763 0.0766103 769.1 631.0 679.7 agmatine ureohydrolase
1844 222930 PM s at AG MAT (agmatinase) 0.00290397 0.0767363 14.1 13.0 11.6
1845 217885 PM at IP09 importin 9 0.00290642 0.0767594 227.8 183.0 171.3
LOC1002
1846 244354 PM at 88939 Similar to hCG1987955 0.00291439 0.0768645 262.1 211.6 206.8
1847 240410 PM at 0.00291445 0.0768645 252.9 193.0 189.1
1848 230018 PM at DPP9 dipeptidyl-peptidase 9 0.00291513 0.0768645 49.0 42.2 46.2
1849 217579 PM x at — — 0.00291775 0.0768919 217.6 178.8 186.1
FAM160 family with sequence
1850 218337 PM at B2 similarity 160, member B2 0.00292068 0.0769276 53.1 50.8 43.0 myotubularin related
1851 225232 PM at MTMR12 protein 12 0.00292317 0.0769515 305.0 361.8 389.4
GORASP Golgi reassembly stacking
1852 243677 PM at 1 protein 1, 65kDa 0.00293066 0.0771071 9.7 10.1 10.9 bromodomain and WD
repeat domain containing
1853 225446 PM at BRWD1 1 0.00293424 0.0771219 47.9 62.2 47.6 dihydrofolate reductase-
1854 241727 PM x at DHFRL1 like 1 0.00293439 0.0771219 82.0 68.9 70.9
Wilms tumor 1 associated
1855 210285 PM x at WTAP protein 0.00294086 0.0772503 94.4 149.5 115.1 solute carrier family 30
(zinc transporter),
1856 232432 PM s at SLC30A5 member 5 0.00294546 0.0773294 79.1 113.1 86.3 diacylglycerol kinase,
1857 238694 PM at DGKE epsilon 64kDa 0.00294979 0.0774014 27.3 22.0 18.3 trinucleotide repeat
1858 1558142 PM at TNRC6B containing 6B 0.00295374 0.0774477 435.3 330.1 377.1
RAB guanine nucleotide
1569296_PM_a_a LOC4937 exchange factor (GEF) 1
1859 t 54 pseudogene 0.00295656 0.0774477 28.2 22.8 22.7
CCR4-NOT transcription
1860 217970 PM s at CN0T6 complex, subunit 6 0.00295761 0.0774477 69.0 101.6 83.5
RFT1 homolog (5.
1861 1558289 PM at RFT1 cerevisiae) 0.00295791 0.0774477 22.6 19.9 18.4
1862 1570496 PM at — 0.00295955 0.077449 14.2 12.3 12.4 Hermansky-Pudlak
1863 1552652 PM at HPS4 syndrome 4 0.00296203 0.0774723 16.6 14.0 14.6 chromosome X open
1864 1553466 PM at CXorf59 reading frame 59 0.00297091 0.0776165 10.4 9.4 9.3
1865 1557486 PM at 0.00297149 0.0776165 13.7 10.8 11.7
SRY (sex determining
1866 201417 PM at S0X4 region Y)-box 4 0.00297303 0.0776165 122.3 169.0 185.8
ANKHD1 ankyrin repeat and KH
III domain containing 1 ///
ANKHD1- ANKHD1-EIF4EBP3
1867 208772 PM at EIF4EBP3 readthrough 0.00297463 0.0776165 546.6 459.2 414.6
1868 207133 PM x at ALPK1 alpha-kinase 1 0.00297551 0.0776165 217.3 173.6 181.1
1869 1560512 PM at — 0.0029797 0.0776842 18.8 13.9 12.4
1870 238064 PM at — 0.00298875 0.0778785 669.2 441.3 512.2
1871 1559949 PM at 0.002993 0.0779476 38.0 26.2 30.0
1872 236116 PM at 0.00300046 0.0781001 26.7 21.8 20.0 inhibitor of growth family,
1873 223871 PM x at ING5 member 5 0.00300704 0.0782296 22.2 18.5 20.9
1874 1561606 PM at — 0.00302995 0.0787613 11.8 11.5 13.3
1875 222345 PM at 0.00303071 0.0787613 11.6 10.7 9.9 myeloid/lymphoid or
mixed-lineage leukemia
(trithorax homolog,
1876 212079_PM_s_at MIL Drosophila) 0.00303461 0.0787729 155.0 119.7 104.9
1877 244579 PM at — 0.00303534 0.0787729 397.7 260.5 288.6 unc-51-like kinase 4 (C.
1878 244168 PM s at ULK4 elegans) 0.003037 0.0787729 20.5 16.5 16.7 protein kinase, cAMP- dependent, regulatory,
1879 204842 PM x at PRKAR2A type II, alpha 0.00303806 0.0787729 535.4 456.5 466.2 metal response element
binding transcription
1880 209704 PM at MTF2 factor 2 0.00303924 0.0787729 37.4 53.0 48.2
FAM120 family with sequence
1881 1555908_PM_at A similarity 120A 0.00304219 0.0788074 14.4 15.8 17.8
1882 243178 PM at — 0.00304966 0.0789333 1388.5 913.1 948.5 tRNA aspartic acid
1883 206308 PM at TRDMT1 methyltransferase 1 0.00305143 0.0789333 16.4 21.0 20.6
MAPKSP
1884 217971 PM at 1 MAPK scaffold protein 1 0.00305191 0.0789333 366.5 504.9 497.5
1885 226808 PM at ZNF862 zinc finger protein 862 0.00305746 0.0790349 392.1 308.8 321.6
1886 243988 PM at 0.00306374 0.0791106 13.0 10.8 11.0 solute carrier family 22
SLC22A1 (organic cation/carnitine
1887 232232 PM s at 6 transporter), member 16 0.00306384 0.0791106 30.7 45.8 53.9
1888 232532_PM_at QRICH2 glutamine rich 2 0.00306539 0.0791106 11.5 11.3 10.3
1889 215854 PM at — 0.00306688 0.0791106 18.7 14.7 15.3
1890 236919 PM at — 0.00306986 0.0791455 24.1 18.3 18.2 isocitrate dehydrogenase
1891 202069 PM s at I0H3A 3 (NAD+) alpha 0.00307338 0.0791944 63.0 85.5 79.3 ankyrin repeat and SOCS
1892 212818 PM s at ASB1 box-containing 1 0.00308003 0.0793069 52.1 47.2 41.4 cadherin 2, type 1, N-
1893 203440 PM at CDH2 cadherin (neuronal) 0.003081 0.0793069 11.9 11.5 16.0 coiled-coil domain
1894 233326 PM at CCDC39 containing 39 0.00309364 0.0795902 9.0 8.8 10.4 chromosome 5 open 1010.
1895 225956 PM at C5orf41 reading frame 41 0.00309558 0.0795981 1312.0 4 1112.8
1896 242875 PM at 0.00310427 0.0797794 207.1 137.4 142.5
1897 215208 PM x at RPL35A Ribosomal protein L35a 0.00311137 0.0799079 77.7 61.4 64.7
1898 244035 PM at — 0.00311297 0.0799079 66.4 42.0 31.3 chromosome 19 open
1899 226379 PM s at C19orf25 reading frame 25 0.00311564 0.0799079 16.9 14.6 14.8
1900 219345 PM at B0LA1 bolA homolog 1 (E. coli) 0.00311784 0.0799079 35.6 37.0 29.7 transmembrane emp24
1901 202195 PM s at TMED5 protein transport domain 0.00311821 0.0799079 81.8 107.9 107.9 containing 5
1902 1560861 PM at 0.00311953 0.0799079 12.6 11.0 10.5 exocyst complex
1903 240528 PM s at EX0C4 component 4 0.00312075 0.0799079 47.4 42.9 33.2
RNA binding motif protein
1904 243295 PM at RBM27 27 0.00312686 0.0800223 342.8 282.8 288.6
LOCIOOI Hypothetical
1905 1557235 PM at 28002 LOC100128002 0.00312941 0.080026 9.2 9.5 10.5
KIDINS22 kinase D-interacting
1906 1557246 PM at 0 substrate, 220kDa 0,00313029 0.080026 347.0 245.0 265.2 endo-beta-N-
1907 220349 PM s at ENGASE acetylglucosaminidase 0.00314235 0.0802887 63.2 48.8 42.8 protein tyrosine
phosphatase type IVA,
1908 200732 PM s at PTP4A1 member 1 0.00314386 0.0802887 310.1 384.3 363.2
1909 240016 PM at — 0.00314629 0.0803087 117.2 79.4 76.8
N(alpha)-acetyltransferase
1910 222393 PM s at NAA50 50, NatE catalytic subunit 0.00315072 0.0803577 118.2 157.8 139.5 olfactory receptor, family
OR7E126 7, subfamily E, member
1911 232586 PM x at P 126 pseudogene 0.00315151 0.0803577 25.8 24.5 20.0
2-aminoethanethiol
1912 212500 PM at ADO (cysteamine) dioxygenase 0.00315656 0.0804444 63.4 94.0 88.7
1913 240613 PM at JAK1 Janus kinase 1 0.00316752 0.0806815 18.1 13.9 15.0
1914 215577 PM at — 0.00317601 0.0808555 22.3 17.0 16.7 natural killer-tumor
1915 231235 PM at NKTR recognition sequence 0.00317914 0.0808929 120.6 88.6 75.7
1916 213666 PM at 6-Sep septin 6 0.00318269 0.0809166 261.2 200.3 180.0
1917 237317 PM at 0.00318339 0.0809166 26.6 24.2 19.8
N(alpha)-acetyltransferase
1918 220925 PM at NAA35 35, NatC auxiliary subunit 0.00319274 0.0811119 111.8 106.3 90.3 hypothetical
LOC1005 LOC100506168 /// splicing
06168 factor proline/glutamine-
1919 214016 PM s at ///SFPQ rich 0.00319481 0.0811222 873.4 726.2 724.4
Membrane-associated ring
1920 232371_PM_at 7-Mar finger (C3HC4) 7 0.00319954 0.0812 148.4 101.0 98.8
1921 1557504 PM at 0.00320409 0.0812322 26.5 19.4 20.2 armadillo repeat
1922 223328 PM at ARMC10 containing 10 0.00320626 0.0812322 131.8 172.1 139.9 inositol monophosphatase
1923 218516 PM s at IMPAD1 domain containing 1 0.0032072 0.0812322 18.5 25.3 24.2
1924 233674 PM at 0.00320811 0.0812322 170.7 95.5 91.3 proteasome (prosome,
macropain) 26S subunit,
1925 219485 PM s at PSMD10 non-ATPase, 10 0.00321022 0.0812322 289.3 263.0
1926 231316 PM at 0.00321081 0.0812322 78.9 65.9 58.9
1927 233333 PM x at AVIL advillin 0.00321804 0.0812981 32.2 24.6 26.4
Zinc finger, DHHC-type
1928 1563502 PM at ZDHHC2 containing 2 0.00321858 0.0812981 29.9 23.3 20.9 hypothetical LOC151162
L0C1511 /// mannosyl (alpha-1,6-)-
62 /// glycoprotein beta-l,6-N-
1929 212098 PM at MGAT5 acetyl-glucosa 0.00321918 0.0812981 284.9 209.3 215.4
Beclin 1, autophagy
1930 1561652 PM at BECN1 related 0.00322009 0.0812981 15.0 12.6 13.4
1931 201339 PM s at SCP2 sterol carrier protein 2 0.00322271 0.0813062 379.6 504.0 439.2
1932 236066 PM at — 0.00322375 0.0813062 30.3 27.6 24.5
F-box and leucine-rich
1933 220127 PM s at FBXL12 repeat protein 12 0.00322582 0.0813164 97.4 121.1 111.0 sperm associated antigen
1934 206748 PM s at SPAG9 9 0.00323155 0.0814013 23.2 17.0 18.7
3726.
1935 211795 PM s at FYB FYN binding protein 0.00323253 0.0814013 4480.5 3 3726.9
UDP-N-acetyl-alpha-D-
1936 218313 PM s at GALNT7 galactosamine:polypeptid 0.00324116 0.0815764 213.4 276.0 290.7 e N- acetylgalactosaminyltransf
erase 7 (Gal
1937 1564753 PM at 0.00324528 0.081591 12.9 10.7 11.8
1938 226544 PM x at MUTED muted homolog (mouse) 0.00324648 0.081591 343.5 298.8 310.5 myosin regulatory light
1939 228097 PM at MYUP chain interacting protein 0.00324676 0.081591 129.4 87.6 80.9
1940 224047 PM at 0.00325581 0.081766 8.6 8.4 9.5
Nipped-B homolog
1941 242352 PM at NIPBL (Drosophila) 0.00325708 0.081766 1020.9 808.3 835.7
1942 227121 PM at — 0.00326653 0.081961 67.1 48.7 47.0
1943 232174 PM at — 0.00327857 0.0821646 369.3 203.0 212.0
LOCIOOI hypothetical
1944 230526 PM at 31096 LOC100131096 0.0032788 0.0821646 85.3 79.7 62.4
1945 244347 PM at — 0.00328111 0.0821646 37.1 25.3 24.0
1562591_PM_a_a orofacial cleft 1 candidate
1946 t 0FCC1 1 0.00328139 0.0821646 10.8 9.9 11.4 component of oligomeric
1947 243608 PM at C0G2 golgi complex 2 0.00328364 0.0821787 33.9 27.7 25.7
1948 207027 PM at HGFAC HGF activator 0.00330422 0.0826513 10.0 9.8 10.9
1949 235513 PM at — 0.00330961 0.0827436 296.4 212.1 239.3
1950 230821 PM at Z F148 zinc finger protein 148 0.00331766 0.0829024 90.4 79.7 67.9
NCRNAO non-protein coding RNA
1951 237591 PM at 0173 173 0.0033227 0.0829809 623.6 365.2 524.8 nuclear undecaprenyl
pyrophosphate synthase 1
NUS1 /// homolog (S. cerevisiae) ///
1952 215207 PM x at NUS1P3 nuclear undec 0.00332421 0.0829809 26.0 34.8 32.8
1953 1560395 PM at — 0.00333835 0.0832578 11.3 9.8 9.4 echinoderm microtubule
1954 232587 PM at EML4 associated protein like 4 0.00333872 0.0832578 42.6 32.3 28.3
1955 234059 PM at — 0.00334076 0.0832661 10.7 9.3 10.4 zinc finger, CW type with
1956 220618_PM_s_at ZCWPW1 PWWP domain 1 0.00334668 0.083371 15.6 12.7 14.0
1957 238735 PM at _„ 0.00336694 0.0838328 34.3 26.7 23.4
1958 1562028 PM at CCND3 Cyclin D3 0.00337137 0.0839003 15.6 11.7 11.9
1959 1565689 PM at — 0.00337532 0.0839557 46.8 35.6 37.0 farnesyl diphosphate
1960 217344_PM_at FDPS synthase 0.00338219 0.0840837 9.4 9.9 10.7 solute carrier family 46,
1961 214719_PM_at SLC46A3 member 3 0.00338423 0.0840915 419.8 342.3 348.5 leucine zipper-EF-hand
containing
1962 233439 PM at LETM1 transmembrane protein 1 0.00338723 0.0840983 13.4 12.3 11.6
1963 203803 PM at PCY0X1 prenylcysteine oxidase 1 0.0033906 0.0840983 20.7 18.8 15.6
1964 239296 PM at 0.00339104 0.0840983 104.3 66.0 80.3 transmembrane and
1965 213351 PM s at TMCC1 coiled-coil domain family 1 0.00339141 0.0840983 446.1 281.1 311.4
1966 237181 PM at — 0.00339341 0.0841051 27.0 19.7 17.2
Aryl hydrocarbon receptor
1967 231016 PM s at ARNT nuclear translocator 0.00339928 0.0842078 21.4 21.6 26.7
1968 233713 PM at 0.00340118 0.084212 65.9 51.2 43.3
SUMOl/sentrin specific
1969 220735 PM s at SENP7 peptidase 7 0.00341419 0.0844912 12.4 17.4 16.1
FAM131 family with sequence
1970 221904 PM at A similarity 131, member A 0.00341688 0.0845149 125.6 152.3 169.4 protein kinase, AMP- activated, gamma 2 non-
1971 218292 PM s at PRKAG2 catalytic subunit 0.00342353 0.0846231 78.7 107.9 100.2 solute carrier family 6
(neurotransmitter
transporter, glycine),
1972 210810 PM s at SLC6A5 member 5 0.00342473 0.0846231 10.4 9.2 9.9
1973 240865 PM at — 0.00343655 0.0848722 29.3 22.0 17.9 vacuolar protein sorting
1974 233656 PM s at VPS54 54 homolog |S. cerevisiae) 0.00344076 0.0849061 72.2 119.2 100.9 1975 244813 PM at 0.00344188 0.0849061 19.5 15.2 15.1
1976 211565 PM at SH36L3 SH3-domain GRB2-like 3 0.00344315 0.0849061 10.8 11.8 12.9 nephroblastoma
1977 214321 PM at NOV overexpressed gene 0.00345461 0.0851456 77.2 88.5 163.6
Chromosome 19 open
1978 222266 PM at C19orf2 reading frame 2 0.00345958 0.0851917 321.2 256.1 206.0
LOC1005 hypothetical
1979 239307 PM at 09703 LOC100509703 0.00345998 0.0851917 255.5 155.4 188.5
1980 200624 PM s at AT 3 matrin 3 0.00347416 0.0854977 255.1 378.0 322.4
CRYBB2P crystallin, beta B2
1981 222048 PM at 1 pseudogene 1 0.0034836 0.0856867 30.4 25.6 23.7
1982 226756 PM at ... ... 0.00348639 0.0857087 53.5 77.9 91.0
Family with sequence
FAM120 similarity 120A opposite
1983 239391 PM at AOS strand 0.00348801 0.0857087 53.8 43.6 50.8 ubiquitin-conjugattng
enzyme E2D 1 (UBC4/5 2015.
1984 211764 PM s at UBE2D1 homolog, yeast) 0.00349414 0.0857522 1682.5 0 2192.3 thrombospondin, type 1,
1985 222835 PM at THSD4 domain containing 4 0.00349443 0.0857522 10.6 9.8 11.2
TMEM13 transmembrane protein
1986 232313 PM at 2C 132C 0.00349506 0.0857522 11.7 11.0 12.5
1987 230735 PM at _.- ... 0.00350442 0.0859385 921.5 683.6 628.9
1988 1555536 PM at ANTXR2 anthrax toxin receptor 2 0.00350943 0.0860181 65.7 55.0 53.3
Phosphoinositide-3- kinase, class 2, alpha
1989 241905 PM at PIK3C2A polypeptide 0.00351172 0.086031 127.2 95.1 96.4 chromosome 11 open
1990 201784 PM s at Cllorf58 reading frame 58 0.00351433 0.0860516 484.3 641.2 610.2
1991 203224 PM at RFK riboflavin kinase 0.0035255 0.0862084 127.7 179.7 175.5
1992 1566897 PM at — ... 0.00352577 0.0862084 40.5 30.3 28.5
C20orfl8 chromosome 20 open
1993 233598 PM at 7 reading frame 187 0.00352604 0.0862084 9.3 9.4 10.3 ubiquitin-conjugating
enzyme E2E 1 (UBC4/5
1994 212519 PM at UBE2E1 homolog, yeast) 0.00353349 0.0863142 694.7 905.4 845.0 potassium inwardly- rectifying channel, 1462.
1995 210119 PM at KCNJ15 subfamily J, member 15 0.00353391 0.0863142 2213.3 5 1794.1
1996 241932 PM at ... 0.00353801 0.0863346 27.5 20.4 20.2
ST8 alpha-N-acetyl- neuraminide alpha-2,8-
1997 230261 PM at ST8SIA4 sialyltransferase 4 0.00353829 0.0863346 223.7 281.2 329.5
1998 204725_PM_s_at NCK1 NCK adaptor protein 1 0.00354863 0.0865436 62.3 93.1 83.9
1999 235965 PM at ... ... 0.00355144 0.0865688 8.7 9.1 10.5
PCDHGA protocadherin gamma
2000 210368 PM at 8 subfamily A, 8 0.0035662 0.0868851 12.4 10.6 11.6
2001 231107_PM_at — ... 0.00357367 0.0870236 47.2 37.3 35.4
2002 234439 PM at — — 0.0035897 0.0873703 11.5 10.0 10.0
2003 243869 PM at ... ... 0.0035929 0.0874045 214.0 183.6 147.6
RAB27A, member RAS 1438.
2004 235766 PM x at RAB27A oncogene family 0.00359922 0.0875146 1165.1 5 1374.3
2005 242853 PM at — ... 0.00360722 0.0876653 52.3 38.3 41.2
2006 40446 PM at PHF1 PHD finger protein 1 0.0036114 0.0876843 263.3 227.3 227.3
2007 244646_PM_at — — 0.0036116 0.0876843 113.5 85.0 87.2
TOX high mobility group
2008 232097 PM at T0X4 box family member 4 0.00361452 0.0877115 159.7 112.9 128.3
GC-rich promoter binding
2009 217877 PM s at GPBP1L1 protein l-l'ike 1 0.00361929 0.0877835 327.8 387.8 381.1
2010 1557452 PM at ... ... 0.00362626 0.0879088 46.4 33.4 36.8
2011 222214 PM at ... ... 0.00364195 0.0882453 40.0 27.0 26.2 chromosome 21 open
2012 220918 PM at C21orf96 reading frame 96 0.00364716 0.0883276 364.2 294.9 224.1
1552563_PM_a_a
2013 t 0.00365851 0.0885585 14.2 12.3 11.9
2014 1568857 PM a a NBR1 Neighbor of BRCAl gene 1 0.00366507 0.0886732 134.8 97.1 98.6 t
1557501_PM_a_a
2015 t 0.00366836 0.0887088 38.9 31.1 30.6
CCR4-N0T transcription
2016 222182 PM s at CN0T2 complex, subunit 2 0.00367216 0.0887566 466.6 388.5 402.9
2017 1560144 PM at — 0.00367869 0.0888704 9.5 9.1 10.2
2018 202704 PM at T0B1 transducer of ERBB2, 1 0.00368242 0.0889164 337.2 449.9 455.5
2019 223490 PM s at EX0SC3 exosome component 3 0.00368908 0.0890331 60.7 88.7 71.7
G protein-coupled
receptor associated
2020 228027 PM at GP ASP2 sorting protein 2 0.00369478 0.0891265 11.1 10.3 9.4 heterogeneous nuclear
ribonucleoprotein U
(scaffold attachment
2021 225805 PM at HNRNPU factor A) 0.00369714 0.0891393 22.1 31.7 25.1
SLIT-ROBO Rho GTPase
SRGAP2P activating protein 2
2022 228628 PM at 1 pseudogene 1 0.00371487 0.0894886 461.9 362.6 338.6 golgi-associated PDZ and
coiled-coil motif
2023 225023 PM at 60PC containing 0.0037153 0.0894886 33.6 42.6 42.5 solute carrier family 35,
2024 215169 PM at SLC35E2 member E2 0.00372164 0.089597 157.6 108.2 117.3
2025 230856 PM at — 0.00372727 0.0896882 113.2 84.2 84.6
EP300 interacting inhibitor
2026 208669 PM s at EID1 of differentiation 1 0.00373918 0.0899183 553.2 801.6 679.5
2027 203226 PM s at TSPA 31 tetraspanin 31 0.00374052 0.0899183 64.9 90.1 76.5
2028 j 243765 PM at — 0.00375004 0.0901027 19.5 17.2 16.2
2029 1562468 PM at — 0.00376362 0.0903403 24.4 17.4 17.0
2030 209076 PM s at WDR45L WDR45-like 0.00376364 0.0903403 142.3 162.8 167.8
2031 241543 PM at — 0.00376716 0.0903803 10.4 9.4 11.0
1559201_PM_a_a
2032 t 0.00378405 0.0906794 613.6 450.2 499.4
ArfGAP with SH3 domain,
ankyrin repeat and PH 1328.
2033 224796 PM at ASAP1 domain 1 0.00378442 0.0906794 1795.7 9 1478.4
2034 233041 PM x at — 0.00378521 0.0906794 855.4 706.6 739.4 serine/arginine-rich
splicing factor 2,
2035 232597 PM x at SRSF2IP interacting protein 0.00378854 0.090698 766.8 615.4 621.3 activating transcription
2036 217550 PM at ATF6 factor 6 0.00378971 0.090698 220.4 149.4 200.6
2037 233476 PM at — 0.00379655 0.0908171 420.4 284.9 293.1
G protein-coupled
2038 1554559 PM at GPR62 receptor 62 0.00382185 0.0913775 13.4 11.6 12.1
CASP8 and FADD-like
2039 217654_PM_at CFLAR apoptosis regulator 0.00382481 0.0914006 42.1 26.0 26.3 tweety homolog 3
2040 224674 PM at TTYH3 (Drosophila) 0.00382657 0.0914006 31.7 40.5 41.7
2041 232773_PM_at — 0.00383209 0.091467 107.9 81.8 78.2
2042 242232 PM at — — 0.00383319 0.091467 27.9 19.9 20.0
F-box and leucine-rich
2043 239224_PM__at FBXL20 repeat protein 20 0.00383498 0.091467 38.6 31.3 31.1 cellular repressor of E1A-
2044 1552714 PM at CREG2 stimulated genes 2 0.00385834 0.0919468 10.2 9.7 11.5
B-cell receptor-associated
2045 225677 PM at BCAP29 protein 29 0.00386012 0.0919468 49.1 69.2 74.5 transmembrane emp24- like trafficking protein 10
2046 238886 PM at TMED10 (yeast) 0.00386076 0.0919468 45.5 32.9 33.1
2047 237426 PM at SP100 SP100 nuclear antigen 0.00386538 0.0919651 344.2 223.2 258.5
TICAM2
III toll-like receptor adaptor
TMED7- molecule 2 /// TMED7-
2048 239431 PM at TICAM2 TICAM2 readthrough 0.00386718 0.0919651 42.0 59.7 60.8
2049 243013 PM at — 0.00386719 0.0919651 68.1 53.2 48.5 2050 236612 P at 0.00387911 0.092128 14.2 12.0 13.1 protein kinase, AMP- activated, gamma 2 non-
2051 222582 PM at PRKAG2 catalytic subunit 0.00387911 0.092128 158.1 194.8 206.7
TAF1 RNA polymerase II,
TATA box binding protein
(TBP)-associated factor,
2052 227205 PM at TAF1 250kDa 0.00387971 0.092128 45.6 60.0 51.5
2053 236836 PM at — 0.00388617 0.0922081 85.6 72.4 60.0 protein phosphatase 2,
catalytic subunit, beta
2054 201375 PM s at PPP2CB isozyme 0.00388709 0.0922081 410.6 507.3 496.6
SYnaptosomal-associated 1776.
2055 209130 PM at SNAP23 protein, 23kDa 0.00389024 0.0922081 1604.7 5 1930.4 chromosome X open
2056 224177 PM s at CXorf26 reading frame 26 0.00389364 0.0922081 51.1 76.8 57.5 small nuclear
ribonucleoprotein
2057 202505 PM at SNRPB2 polypeptide B 0.00389463 0.0922081 392.0 508.0 467.4
2058 1570124 PM at — 0.00389516 0.0922081 11.6 10.6 12.2
UOP-glucose glycoprotein
2059 231968 PM at UGGT1 glucosyltransferase 1 0.00389633 0.0922081 302.7 247.7 259.2 phosphatidylinositol 4-
2060 222631 PM at PI4K2B kinase type 2 beta 0.00390047 0.0922427 42.2 64.7 62.0
2061 235805 PM at — 0.00390158 0.0922427 48.0 30.8 32.9
Headcase homolog
2062 230582 PM at HECA (Drosophila) 0.00390887 0.0923703 15.5 13.2 13.6
2063 223011 PM s at 0CIAD1 OCIA domain containing 1 0.00391975 0.0925825 608.3 727.8 657.3
2064 232135 PM at SAP 30 L SAP30-like 0.00392804 0.0927333 309.6 233.1 252.6 chemokine (C motif)
2065 206366 PM x at XCL1 ligand 1 0.00393296 0.0928045 205.2 302.0 368.0 carbohydrate (chondroitin
2066 226368 PM at CHST11 4) sulfotransferase 11 0.00395067 0.0931773 1079.8 818.7 836.0
ARHGAP Rho GTPase activating
2067 205068 PM s at 26 protein 26 0.00396416 0.0933895 1314.3 888.0 1031.9 lysophosphatidic acid
2068 204037 PM at LPAR1 receptor 1 0.00396514 0.0933895 20.3 23.4 27.6 regulator of chromosome
2069 206499 PM s at RCC1 condensation 1 0.00396759 0.0933895 24.4 32.1 25.4
2070 239955 PM at — 0.00396859 0.0933895 166.5 121.4 113.9
TATA box binding protein
(TBP)-associated factor,
RNA polymerase 1, D,
2071 222728 PM s at TAF1D 41kDa 0.00397247 0.0933895 591.8 472.2 470.7 breast carcinoma
2072 228787 PM s at BCAS4 amplified sequence 4 0.00397319 0.0933895 24.3 22.9 19.6
GTPase activating protein
2073 212802 PM s at GAPVD1 and VPS9 domains 1 0.00397442 0.0933895 482.4 412.6 428.7 tumor necrosis factor
TNFSF13 (ligand) superfamily, 2619.
2074 223501 PM at B member 13b 0.00397788 0.0933895 2123.6 4 2925.4
2075 241425 PM at NUPL1 nucleoporin like 1 0.00397867 0.0933895 506.9 376.8 406.3
2076 208853 PM s at CANX calnexin 0.00398028 0.0933895 142.7 193.8 170.5
2077 1557813 PM at — 0.00398075 0.0933895 161.6 103.7 117.7 phosphoprotein
associated with
glycosphingolipid 1353.
2078 225626 PM at PAG1 microdomains 1 0.00398708 0.0934504 1834.4 6 1349.3
AFFX-r2-Pl-cre- 10155. 9861. 10591.
2079 5 at 0.00398718 0.0934504 6 1 3 zinc finger, CCHC domain
2080 225091 PM at ZCCHC3 containing 3 0.00400655 0.0938592 106.6 132.3 117.4 tripartite motif-containing
2081 233669 PM s at TRIM54 54 0.00401166 0.0939338 12.0 10.7 11.8 death inducer-obliterator
2082 218325 PM s at D1D01 1 0.00401405 0.0939446 122.7 106.7 98.9 2083 1558486 PM at ZNF493 zinc finger protein 493 0.00402068 0.0940546 404.2 284.3 271.1 tyrosyl-DNA
2084 219715 PM s at TOPI phosphodiesterase 1 0.00402559 0.0941242 51.5 46.8 39.4
1554806_PM_a_a
2085 t FBX08 F-box protein 8 0.00402917 0.0941438 64.3 91.0 72.2
2086 215545 PM at — 0.00403029 0.0941438 69.3 56.4 55.5
2087 232835 PM at — 0.004036 0.0941915 361.6 219.4 215.7
LOC1002 hypothetical
2088 229556 PM at 88893 LOC100288893 0.0040362 0.0941915 12.6 14.9 16.1
PBX/knotted 1 homeobox
2089 221883 PM at PKN0X1 1 0.00404237 0.0942721 67.9 51.4 46.6 transmembrane protein
2090 241018 PM at TMEM59 59 0.00404702 0.0942721 52.1 39.9 37.4 leukocyte receptor cluster
2091 224673 PM at LEN68 (LRC) member s 0.00404728 0.0942721 30.1 22.9 22.0 immediate early response
2092 211406 PM at IER3IP1 3 interacting protein 1 0.00404739 0.0942721 15.9 18.5 19.5
2093 201056 PM at GOLGB1 golgin Bl 0.00405091 0.094309 89.6 70.1 71.1
BCL2-associated
2094 217911 PM s at BAG3 athanogene 3 0.00405374 0.0943298 43.6 31.9 25.2 protein kinase, interferon- inducible double stranded
2095 237107 PM at PRK A RNA dependent activator 0.00407199 0.0946579 56.7 37.6 39.8 adaptor-related protein
complex 3, sigma 1
2096 202442 PM at AP3S1 subunit 0.00407287 0.0946579 783.8 948.8 953.9 adaptor-related protein
2097 203410 PM at AP3M2 complex 3, mu 2 subunit 0.00407367 0.0946579 58.6 45.9 40.2
2098 235985 PM at — 0.00407823 0.0947187 110.9 84.1 75.6
2099 242371_PM_x_at — 0.00408809 0.094856 16.5 13.9 14.0
ATG4 autophagy related 4
homolog C (S, cerevisiae)
ATG4C /// Ctr9, Pafl/RNA
2100 228190_PM_at /// CTR9 polymerase II com 0.00408993 0.094856 51.6 70.4 78.4 chromosome 5 open
2101 203024 PM s at C5orfl5 reading frame 15 0.00409089 0.094856 418.3 545.0 531.4
ATPase, H+ transporting,
ATP6V1C lysosomal 42kDa, VI
2102 202872 PM at 1 subunit CI 0.00409559 0.094856 81.6 115.8 118.9
2103 233496 PM s at CFL2 cofilin 2 (muscle) 0.0040962 0.094856 9.5 9.6 10.8 trafficking protein, kinesin
2104 202080 PM s at TRAK1 binding 1 0.00409747 0.094856 135.4 162.1 171.8
2105 243262 PM at — 0.00409802 0.094856 19.5 15.0 15.8 coiled-coil domain
2106 228087 PM at CCDC126 containing 126 0.00410037 0.094856 80.0 119.2 136.9
2107 230630 PM at AK4 adenylate kinase 4 0.00410166 0.094856 14.0 12.2 13.2
SLC2A4R
2108 218494 PM s at G SLC2A4 regulator 0.00410524 0.0948938 69.3 73.8 48.0
RNA guanylyltransferase
2109 211387 PM x at RIMGTT and 5'-phosphatase 0.00411271 0.0950213 24.5 19.9 22.1
2110 230980 PM x at — 0.00412014 0.0951479 27.7 22.3 22.1
2111 236562 PM at Z F439 zinc finger protein 439 0.00413239 0.0953856 25.7 36.6 43.4
2112 239848 PM at — 0.00413966 0.0955082 24.9 18.6 18.5 phosphoinositide-3-kinase 2494.
2113 226459 PM at PIK3AP1 adaptor protein 1 0.00415318 0.0957598 2062.2 4 2596.3
2114 224837 PM at FOXP1 forkhead box PI 0.00415683 0.0957598 688.1 567.3 535.8
2115 213500 PM at — 0.00415703 0.0957598 75.5 61.9 62.1
TAF8 RNA polymerase II,
TATA box binding protein
1556178_PM_x_a (TBP)-associated factor,
2116 t TAF8 43kDa 0.00416035 0.0957598 33.1 39.2 31.7 myotubularin related
2117 204837 PM at MTMR9 protein 9 0.00416123 0.0957598 315.8 269.5 270.1
2118 238812 PM at — 0.00416236 0.0957598 153.0 105.4 101.1
RNA binding motif, single 1825.
2119 215127 PM s at RBMS1 stranded interacting 0.00416626 0.0957867 2167.2 2 2003.6 protein 1
2120 222202 P at 0.00416849 0.0957867 11.0 9.9 11.2 syntrophin, beta 1
(dystrophin-associated
protein Al, 59kDa, basic
2121 226438 PM at SNTB1 component 1) 0.0041701 0.0957867 83.2 129.3 116.4 ubiquitin specific
peptidase 7 (herpes virus-
2122 222032 PM s at USP7 associated) 0.00417139 0.0957867 22.9 18.3 20.0
2123 238631 PM at ZNF140 Zinc finger protein 140 0.0041831 0.0960103 15.9 13.6 12.3 chromosome 17 open
2124 218514 PM at C17orf71 reading frame 71 0.00419327 0.0961984 94.3 118.2 111.3 cadherin-related family
2125 213369 PM at CDHR1 member 1 0.00419612 0.0962185 11.9 10.8 12.3
2126 240737 PM at — 0.00420555 0.0963894 143.2 116.6 115.7
2127 216626 PM at — 0.00423185 0.0969466 11.9 10.1 10.2
2128 241351 PM at 0.00423575 0.0969903 48.6 39.4 37.1
1554964_PM_x_a
2129 t 0.00423798 0.0969958 13.8 11.0 11.9
LOC1005 hypothetical
2130 231601 PM at 07224 LOC100507224 0.0042559 0.0973602 10.4 10.1 11.3 basic leucine zipper and
2131 200776 PM s at BZW1 W2 domains 1 0.00426985 0.0975934 196.4 240.6 239.9
2132 239861 PM at 0.0042701 0.0975934 360.5 261.9 284.1
2133 1561006_PM_at 0.00427945 0.0977613 13.5 12.8 11.9
Echinoderm microtubule
2134 242443 PM at EML5 associated protein like 5 0.00428213 0.0977766 25.4 18.7 18.7 myeloid/lymphoid or
mixed-lineage leukemia
(trithorax homolog,
2135 212078 PM s at MLL Drosophila) 0.0042932 0.0979835 186.7 143.2 117.3 general transcription
2136 215470 PM at GTF2H2B factor IIH, polypeptide 2B 0.00429999 0.0980854 246.2 184.6 138.8 forty-two-three domain
2137 224641 PM at FYTTD1 containing 1 0.00430169 0.0980854 330.1 444.5 371.2
2138 209027 PM s at ABI1 abl-interactor 1 0.00430504 0.0981158 537.3 673.6 648.2 extended synaptotagmin-
2139 224698 PM at ESYT2 like protein 2 0.00431319 0.0982556 437.9 373.9 323.4 ubiquitin-conjugating
2140 225783 PM at UBE2F enzyme E2F (putative) 0.00431806 0.0983206 262.9 338.1 367.5
2141 230742 PM at — 0.00432039 0.098321 161.8 115.4 106.3
Neutral sphingomyelinase
(N-SMase) activation
2142 232148 PM at NSMAF associated factor 0.00432334 0.098321 144.0 94.9 94.9
2143 244636 PM at 0.00432413 0.098321 31.1 22.7 20.7
Treacher Collins-
2144 244686 PM at TC0F1 Franceschetti syndrome 1 0.00433006 0.0984099 14.2 12.6 14.4
2145 1569806 PM at 0.00435008 0.0987818 13.3 11.7 13.1
Elongation protein 2
2146 235623 PM at ELP2 homolog (S. cerevisiae) 0.00435048 0.0987818 148.9 119.0 117.2
2147 222207 PM x at — 0.00435892 0.0989274 752.8 633.6 673.2 glia maturation factor,
2148 202544 PM at GMFB beta 0.00436196 0.0989503 350.5 476.6 471.2
2149 1553176 PM at SH2D1B SH2 domain containing IB 0.00436721 0.0990233 11.4 12.7 13.5 thioesterase superfamily
2150 243492 PM at THEM4 member 4 0.00437206 0.0990871 28.2 20.9 17.9
DDHD domain containing
2151 244154 PM at DDHD1 1 0.00437947 0.0992089 110.5 83.5 83.9
1788.
2152 242946 PM at 0.00438297 0.0992421 2226.9 3 1732.9
2153 232665 PM x at — 0.00438865 0.0993245 17.4 14.9 16.1
2154 222035 PM s at PA POL A poly(A) polymerase alpha 0.00440072 0.0994865 299.9 376.9 346.1
2155 1566958 PM at 0.00440104 0.0994865 15.9 12.8 13.8
2156 215978 PM x at ZNF721 zinc finger protein 721 0.00440193 0.0994865 1251.4 972.1 1042.4 Table 5. Time to biopsy (days post transplant).
Table 6. 3-Way 1 -Step Microarray Analysis (AR v. subAR v. TX) using biopsy samples Results
Table 7. Biopsy Microarray Signatures for subAR using a 2-way 2-Step approach - first step
212588_PM_at PTP C protein tyrosine phosphatase, receptor type, C 2.06E-10
205831_P _at CD2 CD2 molecule 2.10E-10
224356_PM_x_at MS4A6A membrane-spanning 4-domains, subfamily A, 2.11E-10 member 6A
206011_PM_at CAS PI caspase 1, apoptosis-related cysteine peptidase 2.51E-10
(interleukin 1, beta, convertase)
223280_PM_x_at MS4A6A membrane-spanning 4-domains, subfamily A, 3.37E-10 member 6A
229041_PM_s_at EST — 4.24E-10
229041 PM s at
213566_PM_at RNASE6 ribonuclease, RNase A family, k6 4.26E-10
213603_PM_s_at RAC2 ras-related C3 botulinum toxin substrate 2 (rho 4.52E-10 family, small GTP binding protein Rac2)
210972_PM_x_at TRAC /// TRAJ17 T cell receptor alpha constant /// T cell receptor 4.73E-10
/// TRAV20 alpha joining 17 /// T cell receptor
211742_PM_s_at EVI2B ecotropic viral integration site 2B 4.95E-10
205488_P _at GZ A granzyme A (granzyme 1, cytotoxic T-lymphocyte- 5.04E-10 associated serine esterase 3)
202957_PM_at HCLS1 hematopoietic cell-specific Lyn substrate 1 6.04E-10
223922_PM_x_at MS4A6A membrane-spanning 4-domains, subfamily A, 6.82E-10 member 6A
206978_PM_at CCR2 chemokine (C-C motif) receptor 2 7.07E-10
219666_P _at MS4A6A membrane-spanning 4-domains, subfamily A, 7.80E-10 member 6A
209671_PM_x_at TRAC T cell receptor alpha constant 8.57E-10
226818_P _at MPEG1 Macrophage expressed 1 8.65E-1D
212671_PM_s_at HLA-DQA1 /// major histocompatibility complex, class II, DQ alpha 1 9.14E-10
HLA-DQA2 /// major histocompatibility com
228532_PM_at Clorfl62 chromosome 1 open reading frame 162 9.60E-10
204912_P _at IllORA interleukin 10 receptor, alpha 1.01E-09
205821_PM_at KLRK1 killer cell lectin-like receptor subfamily K, member 1 1.19E-09
204205_PM_at AP0BEC3G apolipoprotein B mRNA editing enzyme, catalytic 1.19E-09 poiypeptide-l'ike 3G
214181_P _x_at LST1 leukocyte specific transcript 1 1.20E-09
214470_PM_at KLRBl killer cell lectin-like receptor subfamily B, member 1 1.35E-09
201137_PM_s_at HLA-DPB1 major histocompatibility complex, class II, DP beta 1 1.35E-09
211902_PM_x_at TRD@ T cell receptor delta locus 1.50E-09
210982_PM_s_at HLA-DRA major histocompatibility complex, class II, DR alpha 1.74E-09
209835_PM_x_at CD44 CD44 molecule (Indian blood group) 2.10E-09
206666_PM_at GZMK granzyme K (granzyme 3; tryptase II) 2.13E-09
203760_PM_s_at SLA Src-like-adaptor 2.13E-09
202644_PM_s_at TNFAIP3 tumor necrosis factor, alpha-induced protein 3 2.24E-09
204446_PM_s_at AL0X5 arachidonate 5-lipoxygenase 2.34E-09
213416_PM_at ITGA4 integrin, alpha 4 (antigen CD49D, alpha 4 subunit of 2.40E-09
VLA-4 receptor)
209083_PM_at C0R01A coronin, actin binding protein, 1A 2.41E-09
225701_P _at AKNA AT-hook transcription factor 2.49E-09
224927_PM_at KIAA1949 KIAA1949 2.95E-09
211991_PM_s_at HLA-DPA1 major histocompatibility complex, class II, DP alpha 1 3.00E-09 235964_PM_x_at SAMHD1 SAM domain and HD domain 1 3.04E-09
202207_PM_at ARL4C ADP-ribosylation factor-like 4C 3.09E-09
210895_PM_s_at CD86 CD86 molecule 3.43E-09
1555691_P _a_at KLRK1 killer cell lectin-like receptor subfamily K, member 1 3.43E-09
226841_PM_at PEG1 macrophage expressed 1 3.66E-09
205269_PM_at LCP2 lymphocyte cytosolic protein 2 (SH2 domain 3.68E-09 containing leukocyte protein of 76kDa)
203416_P _at CD53 CD53 molecule 3.82E-09
204959_PM_at NDA myeloid cell nuclear differentiation antigen 3.96E-09
223322_PM_at RASSF5 Ras association (RalGDS/AF-6) domain family 4.29E-09 member 5
209970_PM_x_at CAS PI caspase 1, apoptosis-related cysteine peptidase 4.61E-09
(interleukin 1, beta, convertase)
1552703_P _s_at CARD16 /// caspase recruitment domain family, member 16 /// 4.62E-09
CASP1 caspase 1, apoptosis-related cysteine
221698_PM_s_at CLEC7A C-type lectin domain family 7, member A 4.92E-09
1559584_PM_a_at C16orf54 chromosome 16 open reading frame 54 5.09E-09
205270_P _s_at LCP2 lymphocyte cytosolic protein 2 (SH2 domain 5.ΠΕ-09 containing leukocyte protein of 76kDa)
209670_P _at TRAC T cell receptor alpha constant 5.15E-09
209606_PM_at CYTIP cytohesin 1 interacting protein 5.42E-09
204891_PM_s_at LCK lymphocyte-specific protein tyrosine kinase 5.54E-09
1553906_PM_s_at FGD2 FYVE, RhoGEF and PH domain containing 2 5.99E-09
223344_PM_s_at S4A7 membrane-spanning 4-domains, subfamily A, 6.00E-09 member 7
236295_PM_s_at NLRC3 NLR family, CARD domain containing 3 6.07E-09
217733_PM_s_at T SB10 thymosin beta 10 6.08E-09
205081_PM_at CRIPl cysteine-rich protein 1 (intestinal) 6.14E-09
208885_PM_at LCP1 lymphocyte cytosolic protein 1 (L-plastin) 6.27E-09
219161_PM_s_at CKLF chemokine-like factor 6.34E-09
227346_PM_at IKZF1 IKAROS family zinc finger 1 (Ikaros) 6.48E-09
223620_P _at GPR34 G protein-coupled receptor 34 6.60E-09
213888_P _s_at TRAF3IP3 TRAF3 interacting protein 3 6.77E-09
232024_PM_at GIMAP2 GTPase, IMAP family member 2 6.89E-09
206682_PM_at CLECIOA C-type lectin domain family 10, member A 7.07E-09
208894_PM_at HLA-DRA major histocompatibility complex, class II, DR alpha 7.95E-09
204971_PM_at CSTA cystatin A (stefin A) 8.19E-09
202208_P _s_at ARL4C ADP-ribosylation factor-like 4C 8.47E-09
226218_PM_at IL7R interleukin 7 receptor 8.48E-09
211368_P _s_at CAS PI caspase 1, apoptosis-related cysteine peptidase 8.75E-09
(interleukin 1, beta, convertase)
211366_PM_x_at CAS PI caspase 1, apoptosis-related cysteine peptidase 8.89E-09
(interleukin 1, beta, convertase)
205789_P _at CD1D CDld molecule 9.29E-09
1554240_PM_a_at ITGAL integrin, alpha L (antigen CDllA (pl80), lymphocyte 9.60E-09 function-associated antigen 1; alph
211367_PM_s_at CASP1 caspase 1, apoptosis-related cysteine peptidase 1.01E-08
(interleukin 1, beta, convertase) 226525_PM_at STK17B serine/threonine kinase 17b 1.04E-08
218223_PM_s_at PLEKHOl pleckstrin homology domain containing, family 0 1.06E-08 member 1
214574_PM_x_at LST1 leukocyte specific transcript 1 1.10E-08
209732_PM_at CLEC2B C-type lectin domain family 2, member B 1.10E-08
210538_PM_s_at BIRC3 baculoviral IAP repeat-containing 3 1.1 E-08
202157_PM_s_at CELF2 CUGBP, Elav-like family member 2 1.17E-08
217456_PM_x_at HLA-E major histocompatibility complex, class 1, E 1.23E-08
211582_PM_x_at LST1 leukocyte specific transcript 1 1.27E-08
223451_PM_s_at CKLF chemokine-like factor 1.30E-08
226474_PM_at NLRC5 NLR family, CARD domain containing 5 1.31E-08
229390_P _at FAM26F family with sequence similarity 26, member F 1.47E-08
201721_PM_s_at LAPTM5 lysosomal protein transmembrane 5 1.56E-08
202206_PM_at ARL4C ADP-ribosylation factor-like 4C 1.64E-08
201666_PM_at TIMP1 TIMP metallopeptidase inhibitor 1 1.69E-08
205898_PM_at CX3CR1 chemokine (C-X3-C motif) receptor 1 1.74E-08
204336_PM_s_at RGS19 regulator of G-protein signaling 19 1.82E-08
208306_PM_x_at HLA-DRB1 Major histocompatibility complex, class II, DR beta 1 1.84E-08
227353_PM_at TMC8 transmembrane channel-like 8 1.85E-08
201288_PM_at ARHGDIB Rho GDP dissociation inhibitor (GDI) beta 1.90E-08
224964_PM_s_at GNG2 guanine nucleotide binding protein (G protein), 1.93 -08 gamma 2
202643_PM_s_at TNFAIP3 tumor necrosis factor, alpha-induced protein 3 1.96E-08
209846_PM_s_at BTN3A2 butyrophilin, subfamily 3, member A2 2.07E-08
222858_PM_s_at DAPP1 dual adaptor of phosphotyrosine and 3- 2.08E-08 phospho'mos'it'ides
201858_PM_s_at SRGN serglycin 2.30E-08
204924_PM_at TLR2 toll-like receptor 2 2.35E-08
203741_PM_s_at ADCY7 adenylate cyclase 7 2.37E-08
213160_PM_at DOCK2 dedicator of cytokinesis 2 2.38E-08
213975_PM_s_at LYZ lysozyme 2.39E-08
1552316_PM_a_at GIMAP1 GTPase, IMAP family member 1 2.40E-08
200905_PM_x_at HLA-E major histocompatibility complex, class 1, E 2.50E-08
226219_PM_at ARHGAP30 Rho GTPase activating protein 30 2.52E-08
209312_PM_x_at HLA-DRB1 /// major histocompatibility complex, class II, DR beta 1 2.S3E-08
HLA-DRB4 /// major histocompatibility comp
202803_PM_s_at ITGB2 integrin, beta 2 (complement component 3 receptor 2.55E-08
3 and 4 subunit)
33304_PM_at ISG20 interferon stimulated exonuclease gene 20kDa 2.56E-08
228071_PM_at GIMAP7 GTPase, IMAP family member 7 2.57E-08
201720_PM_s_at LAPTM5 lysosomal protein transmembrane 5 2.59E-08
219033_PM_at PARP8 poly (ADP-ribose) polymerase family, member 8 2.70E-08
200833_PM_s_at RAP1B RAP1B, member of RAS oncogene family 2.72E-08
227184_PM_at PTAFR platelet-activating factor receptor 2.73E-08
222217_PM_s_at SLC27A3 solute carrier family 27 (fatty acid transporter), 2.74E-08 member 3 22445 l_PM_x_at A HGAP9 Rho GTPase activating protein 9 2.76E-08
206118_PM_at STAT4 signal transducer and activator of transcription 4 2.78E-08
229391_PM_s_at FAM26F family with sequence similarity 26, member F 2.81E-08
218870_PM_at ARHGAP15 Rho GTPase activating protein 15 2.83E-08
224916_PM_at TMEM173 transmembrane protein 173 2.83E-08
209795_PM_at CD69 CD69 molecule 2.89E-08
208965_PM_s_at IFI16 interferon, gamma-inducible protein 16 2.91E-08
209723_PM_at SERPINB9 serpin peptidase inhibitor, clade B (ovalbumin), 2.91E-08 member 9
1555852_PM_at LOC100507463 hypothetical LOC100507463 2.93E-08
1552701_PM_a_at CARD16 caspase recruitment domain family, member 16 3.05E-08
201859_P _at SRGN serglycin 3.07E-08
219574_P _at MAR1 membrane-associated ring finger (C3HC4) 1 3.20E-08
23039 l_PM_at CD84 CD84 molecule 3.30E-08
235529_PM_x_at SAMHD1 SAM domain and HD domain 1 3.35E-08
228055_PM_at NAPSB napsin B aspartic peptidase pseudogene 3.36E-08
212014_P _x_at CD44 CD44 molecule (Indian blood group) 3.46E-08
211656_PM_x_at HLA-DQBl /// major histocompatibility complex, class II, DQ beta 1 3.52E-08
LOC100133583 /// HLA class II histocompatibili
203761_PM_at SLA Src-like-adaptor 3.53E-08
209933_PM_s_at CD300A CD300a molecule 3.53E-08
203233_PM_at IL4R interleukin 4 receptor 3.54E-08
204563_PM_at SELL selectin L 3.58E-08
215633_P _x_at LST1 leukocyte specific transcript 1 3.61E-08
234987_PM_at SAMHD1 SAM domain and HD domain 1 3.61E-08
242946_P _at EST — 3.63E-08
242946 PM at
235385_PM_at AR2 membrane-associated ring finger (C3HC4) 1 3.67E-08
210113_PM_s_at NLRP1 NLR family, pyrin domain containing 1 3.67E-08
228376_PM_at GGTA1 glycoprotein, alpha-galactosyltransferase 1 3.68E-08 pseudogene
205039_PM_s_at IKZF1 IKAROS family zinc finger 1 (Ikaros) 3.69E-08
217362_PM_x_at HLA-DRB6 major histocompatibility complex, class II, DR beta 6 3.71E-08
(pseudogene)
209879_PM_at SELPLG selectin P ligand 3.77E-08
204698_P _at ISG20 interferon stimulated exonuclease gene 20kDa 3.87E-08
215493_PM_x_at BTN2A1 butyrophilin, subfamily 2, member Al 3.95E-08
211395_PM_x_at FCGR2C Fc fragment of IgG, low affinity lie, receptor for 4.15E-08
(CD32) (gene/pseudogene)
223773_PM_s_at SNHG12 small nucleolar RNA host gene 12 (non-protein 4.22E-08 coding)
219279_PM_at DOCK10 dedicator of cytokinesis 10 4.25E-08
225353_PM_s_at C1QC complement component 1, q subcomponent, C chain 4.33E-08
216920_P _s_at TARP /// TRGC2 TCR gamma alternate reading frame protein /// T cell 4.35E-08 receptor gamma constant 2
207651_PM_at GPR171 G protein-coupled receptor 171 4.42E-08
227178_PM_at CELF2 CUGBP, Elav-like family member 2 4.42E-08 202510_PM_s_at TNFAIP2 tumor necrosis factor, alpha-induced protein 2 4.50E-08
209823_PM_x_at HLA-DQB1 major histocompatibility complex, class II, DQ beta 1 4.63E-08
1555756_PM_a_at CLEC7A C-type lectin domain family 7, member A 4.72E-08
223809_P _at RGS18 regulator of G-protein signaling 18 4.72E-08
243366_PM_s_at EST — 4.75E-08
243366 PM s at
204222_P _s_at GLIPR1 GLI pathogenesis-related 1 4.82E-08
204220_P _at G FG glia maturation factor, gamma 4.92E-08
1557905_PM_s_at CD44 CD44 molecule (Indian blood group) 5.25E-08
229625_PM_at GBP5 guanylate binding protein 5 5.25E-08
213414_PM_s_at RPS19 ribosomal protein S19 5.30E-08
230499_PM_at EST — 5.38E-08
230499 PM at
215193_PM_x_at HLA-DRB1 /// major histocompatibility complex, class II, DR beta 1 5.40E-08
HLA-DRB3 /// /// major histocompatibility comp
HLA-DRB4 ///
HLA-DRB5 ///
LOC100133661
III
LOC100294036
III
LOC100509582
III
LOC10051049S
III
LOC 100510519
232724_PM_at MS4A6A membrane-spanning 4-domains, subfamily A, 5.40E-08 member 6A
210140_P _at CST7 cystatin F (leukocystatin) 5.42E-08
224252_P _s_at FXYD5 FXYD domain containing ion transport regulator 5 5.47E-08
219191_PM_s_at BIN2 bridging integrator 2 5.50E-08
206991_PM_s_at CCR5 chemokine (C-C motif) receptor 5 5.54E-08
208966_P _x_at IFI16 interferon, gamma-inducible protein 16 5.60E-08
210785_PM_s_at Clorf38 chromosome 1 open reading frame 38 5.62E-08
242814_PM_at SERPINB9 serpin peptidase inhibitor, clade B (ovalbumin), 5.71E-08 member 9
232543_P _x_at ARHGAP9 Rho GTPase activating protein 9 5.73E-08
213418_P _at HSPA6 heat shock 70kDa protein 6 (HSP70B1) 5.80E-08
212829_PM_at PIP4K2A phosphatidylinositol-5-phosphate 4-kinase, type II, 5.85E-08 alpha
223501_PM_at TNFSF13B tumor necrosis factor (ligand) superfamily, member 5.88E-08
13b
211581_PM_x_at LST1 leukocyte specific transcript 1 5.92E-08
202748_P _at GBP2 guanylate binding protein 2, interferon-inducible 6.11E-08
230925_PM_at APBB1IP amyloid beta (A4) precursor protein-binding, family 6.25E-08
B, member 1 interacting protein
209827_P _s_at IL16 interleukin 16 (lymphocyte chemoattractant factor) 6.49E-08
204882_PM_at ARHGAP25 Rho GTPase activating protein 25 7.19E-08
204319_P _s_at RGS10 regulator of G-protein signaling 10 7.27E-08
217985_PM_s_at BAZ1A bromodomain adjacent to zinc finger domain, 1A 7.33E-08 230550_PM_at S4A6A membrane-spanning 4-domains, subfamily A, 1.23E-07 member 6A
222859_PM_s_at DAPP1 dual adaptor of phosphotyrosine and 3- 1.24E-07 phosphoinositides
226810_P _at OGFRL1 opioid growth factor receptor-like 1 1.28E-07
221666_PM_s_at PYCARD PYD and CARD domain containing 1.29E-07
203729_PM_at E P3 epithelial membrane protein 3 1.29E-07
211990_PM_at HLA-DPA1 major histocompatibility complex, class II, DP alpha 1 1.29E-07
226136_PM_at GUPR1 GLI pathogenesis-related 1 1.32E-07
201426_P _s_at VIM vimentin 1.32E-07
205298_PM_s_at BTN2A2 butyrophilin, subfamily 2, member A2 1.33E-07
206332_PM_s_at IFI16 interferon, gamma-inducible protein 16 1.36E-07
211339_PM_s_at ITK IL2-inducible T-cell kinase 1.37E-07
204490_PM_s_at CD44 CD44 molecule (Indian blood group) 1.38E-07
230669_PM_at RASA2 RAS p21 protein activator 2 1.39E-07
200003_PM_s_at RPL28 ribosomal protein L28 1.39E-07
217478_PM_s_at HLA-DMA major histocompatibility complex, class II, DM alpha 1.40E-07
236280_P _at EST — 1.41E-07
236280 PM at
222976_P _s_at TP 3 tropomyosin 3 1.42E-07
232311_PM_at B2M Beta-2-microglobulin 1.42E-07
220577_PM_at GVINP1 GTPase, very large interferon inducible pseudogene 1 1.43E-07
238668_PM_at EST — 1.44E-07
238668 PM at
232617_P _at CTSS cathepsin S 1.45E-07
224833_PM_at ETS1 v-ets erythroblastosis virus E26 oncogene homolog 1 1.46E-07
(avian)
219014_PM_at PLAC8 placenta-specific 8 1.49E-07
219243_P _at GIMAP4 GTPase, IMAP family member 4 1.49E-07
209829_P _at FAM65B family with sequence similarity 65, member B 1.50E-07
203471_PM_s_at PLEK pleckstrin 1.53E-07
211144_PM_x_at TARP /// TRGC2 TCR gamma alternate reading frame protein /// T cell 1.54E-07 receptor gamma constant 2
211528_PM_x_at HLA-G major histocompatibility complex, class 1, G 1.55E-07
206584_PM_at LY96 lymphocyte antigen 96 1.57E-07
231747_P _at CYSLTR1 cysteinyl leukotriene receptor 1 1.59E-07
230735_PM_at EST — 1.61E-07
230735 PM at
225604_PM_s_at GLIPR2 GLI pathogenesis-related 2 1.62E-07
210072_P _at CCL19 chemokine (C-C motif) ligand 19 1.63E-07
221058_P _s_at C LF chemokine-like factor 1.63E-07
204923_PM_at SASH3 SAM and SH3 domain containing 3 1.68E-07
227677_PM_at JA 3 Janus kinase 3 1.69E-07
201012_PM_at ANXA1 annexin Al 1.70E-07
229155_P _at EST — 1.72E-07
229155 PM at
205101_PM_at CIITA class II, major histocompatibility complex, 1.74E-07 transactivator 216438_P _s_at TMSB4X /// thymosin beta 4, X-linked /// thymosin-like 3 1.75E-07 TMSL3
1552318_P _at GIMAP1 GTPase, IMAP family member 1 1.77E-07
213095_PM_x_at AIF1 allograft inflammatory factor 1 1.80E-07
204316_PM_at RGS10 regulator of G-protein signaling 10 1.82E-07
203927_PM_at NFKBIE nuclear factor of kappa light polypeptide gene 1.83E-07 enhancer in B-cells inhibitor, epsilon
217523_PM_at CD44 CD44 molecule (Indian blood group) 1.84E-07
209901_PM_x_at AIF1 allograft inflammatory factor 1 1.84E-07
203508_PM_at TNFRSF1B tumor necrosis factor receptor superfamily, member 1.85E-07
IB
208944_PM_at TGFBR2 transforming growth factor, beta receptor II 1.86E-07
(70/80kDa)
210031_P _at CD247 CD247 molecule 1.87E-07
202953_PM_at C1QB complement component 1, q subcomponent, B chain 1.87E-07
213733_PM_at MY01F myosin IF 1.88E-07
201738_PM_at EIF1B eukaryotic translation initiation factor IB 1.88E-07
205884_PM_at ITGA4 integrin, alpha 4 (antigen CD49D, alpha 4 subunit of 1.93E-07
VLA-4 receptor)
204820_PM_s_at BTN3A2 /// butyrophilin, subfamily 3, member A2 /// 1.99E-07
BTN3A3 butyrophilin, subfamily 3, member A3
218805_PM_at GIMAP5 GTPase, IMAP family member 5 1.99E-07
212873_P _at HMHA1 histocompatibility (minor) HA-1 1.99E-07
217979_PM_at TSPAN 13 tetraspanin 13 2.02E-07
228471_PM_at ANKRD44 ankyrin repeat domain 44 2.03E-07
218322_PM_s_at ACSL5 acyl-CoA synthetase long-chain family member 5 2.03E-07
215051_P _x_at AIF1 allograft inflammatory factor 1 2.04E-07
213398_PM_s_at SDR39U 1 short chain dehydrogenase/reductase family 39U, 2.04E-07 member 1
206637_P _at P2RY14 purinergic receptor P2Y, G-protein coupled, 14 2.05E-07
Table 8. Biopsy Microarray Signatures for subAR using a 2-way 2-Step approach - second
202242_PM_at TSPAN7 tetraspanin 7 2.17E-07
213857_PM_s_at CD47 CD47 molecule 2.57E-07
205105_PM_at MAN2A1 mannosidase, alpha, class 2A, member 1 2.62E-07
204924_PM_at TLR2 toll-like receptor 2 2.69E-07
204470_PM_at CXCL1 chemokine (C-X-C motif) ligand 1 (melanoma growth 3.07E-07 stimulating activity, alpha)
204108_PM_at NFYA nuclear transcription factor Y, alpha 3.20E-07
236155_PM_at ZCCHC6 Zinc finger, CCHC domain containing 6 4.22E-07
212950_PM_at GPR116 G protein-coupled receptor 116 4.37E-07
209774_PM_x_at CXCL2 chemokine (C-X-C motif) ligand 2 5.78E-07
207966_PM_s_at GLG1 golgi glycoprotein 1 6.24E-07
211758_PM_x_at TXNDC9 thioredoxin domain containing 9 6.38E-07
238178_PM_at EST — 7.69E-07
238178 PM at
202334_PM_s_at UBE2B ubiquitin-conjugating enzyme E2B (RAD6 homolog) 7.75E-07
231334_PM_at EST — 8.26E-07
231334 PM at
223809_PM_at RGS18 regulator of G-protein signaling 18 8.34E-07
210405_PM_x_at TNFRSF10B tumor necrosis factor receptor superfamily, member 9.02E-07
10b
230777_PM_s_at PRDM15 PR domain containing 15 9.91E-07
202907_PM_s_at NBN nibrin 1.02E-06
202621_PM_at IRF3 interferon regulatory factor 3 1.04E-06
219938_PM_s_at PSTPIP2 proline-serine-threonine phosphatase interacting 1.07E-06 protein 2
223047_PM_at CMTM6 CKLF-like MARVEL transmembrane domain containing 1.08E-06
6
202018_PM_s_at LTF lactotransferrin 1.10E-06
233878_PM_s_at XRN2 5'-3' exoribonuclease 2 1.19E-06
244353_PM_s_at SLC2A12 solute carrier family 2 (facilitated glucose transporter), 1.20E-06 member 12
204785_PM_x_at IFNAR2 interferon (alpha, beta and omega) receptor 2 1.21E-06
226000_PM_at CTTNBP2NL CTTIMBP2 N-terminal like 1.24E-06
241891_PM_at EST — 1.30E-06
241891 PM at
208791_PM_at CLU clusterin 1.38E-06
233047_PM_at FRMD7 FERM domain containing ? 1.39E-06
226538_PM_at MAN2A1 mannosidase, alpha, class 2A, member 1 1.44E-06
208792_PM_s_at CLU clusterin 1.48E-06
218313_PM_s_at GALNT7 UDP-N-acetyl-alpha-D-galactosamine:polypeptide N- 1.60E-06 acetylgalactosaminyltransferase 7 (Gal
203568_PM_s_at TRIM38 tripartite motif-containing 38 1.62E-06
223218_PM_s_at NFKBIZ nuclear factor of kappa light polypeptide gene 1.69E-06 enhancer in B-cells inhibitor, zeta
224358_PM_s_at MS4A7 membrane-spanning 4-domains, subfamily A, member 1.76E-06
7
227125_PM_at IFNAR2 interferon (alpha, beta and omega) receptor 2 1.78E-06
1552615_PM_at ACACB acetyl-CoA carboxylase beta 1.84E-06
218865_PM_at M0SC1 MOCO sulphurase C-terminal domain containing 1 1.87E-06 210031_PM_at CD247 CD247 molecule 1.91E-06
212226_PM_s_at PPAP2B phosphatide acid phosphatase type 2B 1.95E-06
230912_PM_at ASPDH aspartate dehydrogenase domain containing 2.08E-06
201042_PM_at TGM2 transglutaminase 2 (C polypeptide, protein-glutamine- 2.14E-06 gamma-glutamyltransferase)
203513_PM_at SPG11 spastic paraplegia 11 (autosomal recessive) 2.39E-06
243088_PM_at EST — 2.58E-06
243088 PM at
204324_PM_s_at G0LIM4 golgi integral membrane protein 4 2.58E-06
235905_PM_at ZNF704 zinc finger protein 704 2.65E-06
1564679_PM_at ASB15 ankyrin repeat and SOCS box-containing 15 2.71E-06
203868_PM_s_at VCAM1 vascular cell adhesion molecule 1 2.72E-06
212695_PM_at CRY2 cryptochrome 2 (photolyase-like) 2.77E-06
223217_PM_s_at NFKBIZ nuclear factor of kappa light polypeptide gene 2.78E-06 enhancer in B-cells inhibitor, zeta
227213_PM_at ADAT2 adenosine deaminase, tRNA-specific 2, TAD2 homolog 2.91E-06
(S. cerevisiae)
206513_PM_at AIM2 absent in melanoma 2 2.96E-06
1552749_PM_a_at KLC3 kines'in light chain 3 2.96E-06
240413_PM_at PYHIN1 pyrin and HIN domain family, member 1 3.05E-06
238960_PM_s_at LARP4 La ribonucleoprotein domain family, member 4 3.06E-06
1562966_PM_at KIAA1217 KIAA1217 3.10E-06
202898_PM_at SDC3 syndecan 3 3.16E-06
229872_P _s_at LOC100132999 hypothetical LOC100132999 3.22E-06
218404_PM_at SNX10 sorting nexin 10 3.44E-06
219998_PM_at HSPC159 galectin-related protein . 3.50E-06
211003_PM_x_at TGM2 transglutaminase 2 (C polypeptide, protein-glutamine- 3.52E-06 gamma-glutamyltransferase)
203008_PM_x_at TXNDC9 thioredoxin domain containing 9 3.59E-06
213513_PM_x_at ARPC2 act'm related protein 2/3 complex, subunit 2, 34kDa 3.77E-06
203765_PM_at GCA grancalcin, EF-hand calcium binding protein 3.83E-06
221510_PM_s_at GLS glutaminase 3.91E-06
214791_PM_at SP140L SP140 nuclear body protein-like 4.01E-06
217947_PM_at CMTM6 CKLF-like MARVEL transmembrane domain containing 4.12E-06
6
206503_PM_x_at PML promyelocytic leukemia 4.26E-06
222033_PM_s_at FLT1 fms-related tyrosine kinase 1 (vascular endothelial 4.32E-06 growth factor/vascular permeability
20265 l_PM_at LPGAT1 lysophosphatidylglycerol acyltransferase 1 4.48E-06
237587_PM_at EST — 4.55E-06
237587 PM at
209970_PM_x_at CASP1 caspase 1, apoptosis-related cysteine peptidase 4.57E-06
(interleukin 1, beta, convertase)
222976_PM_s_at TPM3 tropomyosin 3 4.61E-06
227678_PM_at XRCC6BP1 XRCC6 binding protein 1 4.64E-06
209035_PM_at MDK midkine (neurite growth-promoting factor 2) 4.78E-06
205624_PM_at CPA3 carboxypeptidase A3 (mast cell) 4.78E-06
203332_PM_s_at INPP5D inositol polyphosphate-5-phosphatase, 145kDa 4.82E-06 211917_PM_s_at PRLR prolactin receptor 4.86E-06
219283_PM_at C1GALT1C1 CIGALTl-specific chaperone 1 4.94E-06
239005_PM_at FU39739 Hypothetical FU39739 4.99E-06
228114_PM_x_at C16orfl3 chromosome 16 open reading frame 13 5.00E-06
205295_PM_at CKMT2 creatine kinase, mitochondrial 2 (sarcomeric) 5.19E-06
242131_PM_at ATP6 ATP synthase FO subunit 6 5.23E-06
202688_PM_at TNFSF10 tumor necrosis factor (ligand) superfamily, member 10 5.33E-06
235536_P _at SNORD89 small nucleolar RNA, C/D box 89 5.35E-06
214212_PM_x_at FERMT2 fermitin family member 2 5.35E-06
212148_P _at PBX1 pre-B-cell leukemia homeobox 1 5.38E-06
212504_PM_at DIP2C DIP2 disco-interacting protein 2 homolog C 5.51E-06
(Drosophila)
201697_PM_s_at DNMT1 DNA (cytosine-S-)-methyltransferase 1 5.53E-06
212501_PM_at CEBPB CCAAT/enhancer binding protein (C/EBP), beta 5.54E-06
204446_PM_6_at AL0X5 arachidonate 5-lipoxygenase 5.57E-06
20601 l_PM_at CAS PI caspase 1, apoptosis-related cysteine peptidase 5.63E-06
(interleukin 1, beta, convertase)
224663_PM_s_at CFL2 cofilin 2 (muscle) 5.75E-06
201949_P _x_at CAPZB capping protein (actin filament) muscle Z-line, beta 5.91E-06
219436_PM_s_at EMCN endomucin 5.96E-06
220146_PM_at TLR7 toll-like receptor 7 6.03E-06
209310_PM_S_at CASP4 caspase 4, apoptosis-related cysteine peptidase 6.11E-06
207702_PM_s_at MAGI2 membrane associated guanylate kinase, WW and PDZ 6.12E-06 domain containing 2
204794_PM_at DUSP2 dual specificity phosphatase 2 6.14E-06
219202_PM_at RHBDF2 rhomboid 5 homolog 2 (Drosophila) 6.28E-06
233496_PM_s_at CFL2 cofilin 2 (muscle) 6.38E-06
224578_PM_at RCC2 regulator of chromosome condensation 2 6.46E-06
223104_PM_at JAGN1 jagunal homolog 1 (Drosophila) 6.54E-06
219161_PM_s_at CKLF chemokine-like factor 6.57E-06
226612_PM_at UBE2QL1 ubiquitin-conjugating enzyme E2Q family-like 1 6.62E-06
204974_PM_at RAB3A RAB3A, member RAS oncogene family 6.66E-06
223002_P _s_at XRN2 5'-3' exoribonuclease 2 6.67E-06
242601_PM_at HEPACAM2 HEPACAM family member 2 6.71E-06
205102_P _at TMPRSS2 transmembrane protease, serine 2 6.93E-06
1569926_PM_s_at SLC34A3 solute carrier family 34 (sodium phosphate), member 7.01E-06
3
213596_PM_at CASP4 caspase 4, apoptosis-related cysteine peptidase 7.18E-06
200713_PM_s_at MAPRE1 microtubule-associated protein, RP/EB family, 7.54E-06 member 1
203132_P _at RBI retinoblastoma 1 7.60E-06
209752_P _at REG1A regenerating islet-derived 1 alpha 7.65E-06
211573_P _x_at TGM2 transglutaminase 2 (C polypeptide, protein-glutamine- 7.82E-06 gamma-glutamyltransferase)
207213_P _s_at USP2 ubiquitin specific peptidase 2 7.87 E -06
217984_PM_at RNASET2 ribonuclease T2 7.97E-06 2015/032202
228740_PM_at EST — 1.12E-05
228740 PM at
216323_PM_x_at TUBA3C /// tubulin, alpha 3c /// tubulin, alpha 3d /// tubulin, 1.13E-05
TUBA3D /// alpha 3e
TUBA3E
205068_PM_s_at ARHGAP26 Rho GTPase activating protein 26 1.13E-05
217983_PM_s_at RNASET2 ribonuclease T2 1.14E-05
206059_PM_at ZNF91 zinc finger protein 91 1.15E-05
206944_PM_at HTR6 5-hydroxytryptamine (serotonin) receptor 6 1.17E-05
215264_P _at EMX1 empty spiracles homeobox 1 1.18E-05
213551_PM_x_at PCGF2 polycomb group ring finger 2 1.18E-05
218194_PM_at REX02 REX2, RNA exonuclease 2 homolog (S. cerevisiae) 1.18E-05
227438_PM_at ALPK1 alpha-kinase 1 1.19E-05
1053_PM_at RFC2 replication factor C (activator 1) 2, 40kDa 1.20E-05
227874_P _at E CN endomucin 1.20E-05
201918_PM_at SLC25A36 solute carrier family 25, member 36 1.20E-05
213355_PM_at ST3GAL6 ST3 beta-galactoside alpha-2,3-sialyltransferase 6 1.21E-05
213923_PM_at RAP2B RAP2B, member of RAS oncogene family 1.23E-05
220990_PM_s_at MIR21 /// microRNA 21 /// transmembrane protein 49 1.24E-05
TMEM49
213535_P _s_at UBE2I ubiquitin-conjugating enzyme E2I (UBC9 homolog, 1.25E-05 yeast)
205910_PM_s_at CEL /// carboxyl ester lipase (bile salt-stimulated lipase) /// 1.25E-05
LOC100508206 bile salt-activated lipase-like
204702_PM_s_at NFE2L3 nuclear factor (erythroid-derived 2)-like 3 1.27E-05
230550_PM_at MS4A6A membrane-spanning 4-domains, subfamily A, member 1.29E-05
6A
205027_PM_s_at MAP3K8 mitogen-activated protein kinase kinase kinase 8 1.30E-05
209476_P _at TMX1 thioredoxin-related transmembrane protein 1 1.30E-05
209422_PM_at PHF20 PHD finger protein 20 1.32E-05
207754_P _at RASSF8 Ras association (RalGDS/AF-6) domain family (N- 1.33E-05 terminai) member 8
35150_PM_at CD40 CD40 molecule, TNF receptor superfamily member 5 1.34E-05
41220_PM_at SEPT9 septin 9 1.35E-05
227730_PM_at EST — 1.40E-05
227730 PM at
206613_PM_s_at TAFIA TATA box binding protein (TBP)-associated factor, RNA 1.40E-05 polymerase 1, A, 48kDa
201179_PM_s_at GNAI3 guanine nucleotide binding protein (G protein), alpha 1.41E-05 inhibiting activity polypeptide 3
208850_PM_s_at THY1 Thy-1 cell surface antigen 1.43E-05
217985_PM_s_at BAZ1A bromodomain adjacent to zinc finger domain, 1A 1.44E-05
200798_PM_x_at MCL1 myeloid cell leukemia sequence 1 (BCL2-related) 1.45 E-05
1555486_PM_a_at PRR5L proline rich 5 like 1.45E-05
221932_P _s_at GLRX5 glutaredoxin 5 1.45E-05
2Q5079_P _s_at PDZ multiple PDZ domain protein 1.46E-05
241154_PM_x_at EST — 1.47E-05
241154 PM x at
219089_PM_s_at ZNF576 zinc finger protein 576 1.50E-05 206219_P _s_at VAV1 vav 1 guanine nucleotide exchange factor 1.52E-05
1553153_PM_at ATP6V0D2 ATPase, H+ transporting, lysosomal 38kDa, VO subunit 1.54E-05 d2
208540_PM_x_at S100A11 S100 calcium binding protein All 1.56E-05
223318_PM_s_at ALKBH7 alkB, alkylation repair homolog 7 (E. coli) 1.56E-05
226618_PM_at UBE2QL1 ubiquitin-conjugating enzyme E2Q family-like 1 1.57E-05
218092_PM_s_at AGFG1 ArfGAP with FG repeats 1 1.65E-05
229041_PM_s_at EST — 1.66E-0S
229041 PM s at
214366_PM_s_at ALOX5 arachidonate 5-lipoxygenase 1.66E-05
226820_PM_at ZNF362 zinc finger protein 362 1.68E-05
210426_PM_x_at ORA RAR-related orphan receptor A 1.68E-05
209545_PM_s_at RIPK2 receptor-interacting serine-threonine kinase 2 1.68E-05
214329_PM_x_at TNFSF10 tumor necrosis factor (ligand) superfamily, member 10 1.69E-05
210l76_PM_at TLR1 toll-like receptor 1 1.72E-05
242l67_PM_at EST — 1.73E-05
242167 PM at
224352_PM_s_at CFL2 cofilin 2 (muscle) 1.73E-05
2234Sl_PM_s_at CKLF chemokine-like factor 1.76E-0S
202625_PM_at LYN v-yes-i Yamaguchi sarcoma viral related oncogene 1.79E-05 homolog
202748_PM_at GBP2 guanylate binding protein 2, interferon-inducible 1.81E-05
209906_P _at C3AR1 complement component 3a receptor 1 1.81E-05
213869_P _x_at THY1 Thy-1 cell surface antigen 1.84E-05
225994_PM_at CPSF2 cleavage and polyadenylation specific factor 2, lOOkDa 1.84E-05
226048_PM_at MAPK8 mitogen-activated protein kinase 8 1.85E-05
203828_PM_s_at IL32 interleukin 32 1.88E-05
203947_PM_at CSTF3 cleavage stimulation factor, 3' pre-RNA, subunit 3, 1.88E-05
77kDa
244811_PM_at PHIP pleckstrin homology domain interacting protein 1.88E-05
236293_PM_at RHOH ras homolog gene family, member H 1.90E-05
214467_PM_at GPR65 G protein-coupled receptor 65 1.91E-05
235309_PM_at RPS15A ribosomal protein S15a 1.91E-05
212024_PM_x_at FLU flightless 1 homolog (Drosophila) 1.93E-05
205841_PM_at JAK2 Janus kinase 2 1.94E-05
205887_PM_x_at SH3 mutS homolog 3 (E. coli) 1.95E-05
208743_PM_s_at YWHAB tyrosine 3-monooxygenase/tryptophan 5- 1.98E-05 monooxYgenase activation protein, beta polvpeptid
238668_PM_at EST — 1.98E-05
238668 PM at
205809_PM_s_at WASL Wiskott-Aldrich syndrome-like 1.99E-05
218008_PM_at C7orf42 chromosome 7 open reading frame 42 1.99E-05
204l98_P _s_at RUNX3 runt-related transcription factor 3 2.00E-05
201040_PM_at GNAI2 guanine nucleotide binding protein (G protein), alpha 2.01E-05 inhibiting activity polypeptide 2
223010_PM_s_at OCIAD1 OCIA domain containing 1 2.03E-05
225511_PM_at GPRC5B G protein-coupled receptor, family C, group 5, 2.04E-05 member B 226748_PM_at LYSMD2 LysM, putative peptidoglycan-binding, domain 2.05E-05 containing 2
206150_PM_at CD27 CD27 molecule 2.06E-05
213l36_PM_at PTPN2 protein tyrosine phosphatase, non-receptor type 2 2.07E-05
202238_PM_s_at NNMT nicotinamide N-methyltransferase 2.07E-05
203079_PM_s_at CUL2 cullin 2 2.07E-05
201724_PM_s_at GALNTl UDP-N-acetyl-alpha-D-galactosam'ine:polypeptide N- 2.08E-05 acetylgalactosaminyltransferase 1 (Gal
226147_PM_s_at PIGR polymeric immunoglobulin receptor 2.08E-05
20309 l_PM_at FUBP1 far upstream element (FUSE) binding protein 1 2.11E-05
219033 J> _at PARP8 poly (ADP-ribose) polymerase family, member 8 2.12E-05
22S924__PM_at FNIP2 folliculin interacting protein 2 2.14E-05
230565_PM_at ATP6V1G3 ATPase, H+ transporting, lysosomal 13kDa, VI subunit 2.14E-05
G3
1553906_PM_s_at FGD2 FYVE, RhoGEF and PH domain containing 2 2.16E-05
208296_PM_x_at TNFAIP8 tumor necrosis factor, alpha-induced protein 8 2.18E-05
209787_PM_s_at H GN4 high mobility group nucleosomal binding domain 4 2.18E-05
202957_PM_at HCLS1 hematopoietic cell-specific Lyn substrate 1 2.19E-05
210785_PM_s_at Clorf38 chromosome 1 open reading frame 38 2.20E-05
228770_PM_at GPR146 G protein-coupled receptor 146 2.23E-05
200829_P _x_at ZNF207 zinc finger protein 207 2.26E-05
223344_PM_S_at MS4A7 membrane-spanning 4-domains, subfamily A, member 2.28E-05
7
222885_PM_at E CN endomucin 2.30E-05
202211_P _at ARFGAP3 ADP-ribosylation factor GTPase activating protein 3 2.32E-05
238581_PM_at GBP5 guanylate binding protein 5 2.36E-05
208821_PM_at SNRPB small nuclear ribonucleoproteln polypeptides B and Bl 2.38E-05
203137_PM_at WTAP Wilms tumor 1 associated protein 2.38E-05
213l02_PM_at ACTR3 ARP3 actin-related protein 3 homolog (yeast) 2.40E-05
227384_PM_s_at EST 2.41E-05
227384 PM s at
233632_PM_s_at XRN1 5 -3' exoribonuclease 1 2.42E-05
220742_PM_s_at NGLY1 N-glycanase 1 2.44E-05
208642_PM_s_at XRCC5 X-ray repair complementing defective repair in 2.46E-05
Chinese hamster cells 5 (double-strand-b
225814_PM_at XRN1 5'-3' exoribonuclease 1 2.46E-05
209295_PM_at TNFRSF10B tumor necrosis factor receptor superfamily, member 2.47E-05
10b
21866S_PM_at FZD4 frizzled homolog 4 (Drosophila) 2.48E-05
219023_PM_at AP1AR adaptor-related protein complex 1 associated 2.50E-05 regulatory protein
202510_PM_s_at TNFAIP2 tumor necrosis factor, alpha-induced protein 2 2.53E-05
221477_P _s_at S0D2 superoxide dismutase 2, mitochondrial 2.57E-05
203182_P _s_at SRPK2 SRSF protein kinase 2 2.59E-05
209189_PM_at FOS FBJ murine osteosarcoma viral oncogene homolog 2.61E-05
219574_PM_at MARCH1 membrane-associated ring finger (C3HC4) 1 2.62E-05
217549_PM_at EST — 2.62E-05
217549 PM at 210106_PM_at RDH5 retinol dehydrogenase 5 (ll-cis/9-cis) 2.64E-05
33760_PM_at PEX14 peroxisomal biogenesis factor 14 2.65E-05
238423_PM_at SYTL3 synaptotagmin-like 3 2.65E-05
230176_PM_at EST — 2.66E-05
230176 PM at
218546_P _at Clorfll5 chromosome 1 open reading frame 115 2.70E-05
1558702_PM_at TEX10 testis expressed 10 2.75E-05
212733_P _at KIAA0226 KIAA0226 2.75E-05
229659_PM_s_at EST — 2.76E-05
229659 PM s at
207809_PM_s_at ATP6AP1 ATPase, H+ transporting, lysosomal accessory protein 2.77E-05
1
202431_PM_s_at MYC v-myc myelocytomatosis viral oncogene homolog 2.79E-05
(avian)
212433_PM_x_at RPS2 ribosomal protein S2 2.80E-05
223086_PM_x_at MRPL51 mitochondrial ribosomal protein L51 2.81E-05
228162_P _at ESD esterase D 2.84E-05
214770_PM_at MSR1 macrophage scavenger receptor 1 2.84E-05
201830_PM_s_at NET1 neuroepithelial cell transforming 1 2.85E-05
212314_P _at SEL1L3 sel-1 suppressor of Ιίη-12-like 3 (C. elegans) 2.86E-05
209360_PM_s_at RUNX1 runt-related transcription factor 1 2.89E-05
221698_PM_s_at CLEC7A C-type lectin domain family 7, member A 2.90E-05
201359_PM_at C0PB1 coatomer protein complex, subunit beta 1 2.91E-05
217157_PM_x_at I6K@ /// 1GKC immunoglobulin kappa locus /// immunoglobulin 2.92E-05 kappa constant
Table 9. 2- Way 2-Step Microarray Analysis (AR v. subAR; AR v. TX; and subAR v. TX) using biopsy samples - Results
Table 10. 3-Way 1-Step NGS Analysis (AR v. subAR v. TX) using biopsy samples - Results
Table 1 1 . Biopsy NGS Signatures for subAR using a 2-Step approach (AR+subAR vs. TX and subAR vs TX) - first ste : AR+subAR vs. TX
Cd96 CD96 molecule 1.27E-09
Ptprc protein tyrosine phosphatase, receptor 1.61E-09 ikzfl IKAROS family zinc finger 1 (Ikaros) 2.45E-09
PTPN22 protein tyrosine phosphatase, non-recep 2.51E-09
EMB embigin homolog (mouse) 2.94E-09 runx3 runt-related transcription factor 3 3.00E-09
MNDA myeloid cell nuclear differentiation an 3.08E-09
Arl4c ADP-ribosylation factor-like 4C 3.41E-09
IL16 interleukin 16 (lymphocyte chemoattract 4.57 E-09
D0CK2 dedicator of cytokinesis 2 5.47E-09
ITGAL integrin, alpha L (antigen CD11A (pl80) 6.07E-09
Fgd2 FYVE, RhoGEF and PH domain containing 2 6.43E-09
PARVG parvin, gamma 6.49E-09
CD3D CD3d molecule, delta (CD3-TCR complex) 6.50E-09
Mpegl macrophage expressed 1 6.53E-09
LCP1 lymphocyte cytosolic protein 1 (L-plast 6.58E-09
ARHGAP15 Rho GTPase activating protein 15 7.55E-09
NLRC5 NLR family, CARD domain containing 5 7.70E-09
GZMK granzyme K (granzyme 3; tryptase II) 7.96E-09
BIRC3 baculoviral IAP repeat-containing 3 8.08E-09
TMC8 transmembrane channel-like 8 8.56E-09
RGS18 regulator of G-protein signaling 18 1.00E-08
Cd3g CD3g molecule, gamma (CD3-TCR complex) 1.00E-08
Amical adhesion molecule, interacts with CXADR 1.04E-08 i!2rg interleukin 2 receptor, gamma (severe c 1.19E-08
Inpp5d inositol polyphosphate-5-phosphatase, 1 1.25E-08 cstA cystatin A (stefin A) 1.26E-08
LI D2 LIM domain containing 2 1.44E-08 dappl dual adaptor of phosphotyrosine and 3-p 1.65E-08
NCKAP1L NC -associated protein 1-like 1.68E-08
Ms4a7 membrane-spanning 4-domains, subfamily 1.80E-08
TNFAIP3 tumor necrosis factor, alpha-induced pr 1.87E-08
IL7R interleukin 7 receptor 1.88E-08
EVI2B ecotropic viral integration site 2B 1.88E-08
Clorfl62 chromosome 1 open reading frame 162 1.98E-08
SLAMF7 SLAM family member 7 2.09E-08
RNASE6 ribonuclease, RNase A family, k6 2.20E-O8
CXorf21 chromosome X open reading frame 21 2.38E-08
SCML4 sex comb on midleg-like 4 (Drosophila) 2.42E-08
CCL5 chemokine (C-C motif) ligand 5 2.44E-08
EST EST2 2.52E-08
Pyhinl pyrin and HIN domain family, member 1 2.64E-08
Cd8a CD8a molecule 2.79E-08 Cd52 CD52 molecule 2.99E-08
SA D3 sterile alpha motif domain containing 3 3.16E-08 btk Bruton agammaglobulinemia tyrosine kina 3.18E-08
IRF4 interferon regulatory factor 4 3.24E-08
GAB3 GRB2-associated binding protein 3 3.25E-08
CSF2RA colony stimulating factor 2 receptor, a 3.36E-08
P2RY13 purinergic receptor P2Y, G-protein coup 3.46E-08
FYB FYN binding protein (FYB-120/130) 3.58E-08
TRAF3IP3 TRAF3 interacting protein 3 3.86E-08
PTAFR platelet-activating factor receptor 3.94E-08
Arhgap25 Rho GTPase activating protein 25 3.99E-08 myolf myosin IF 4.09E-08
CELF2 CUG triplet repeat, RNA binding protein 4.18E-08
MS4A6A membrane-spanning 4-domains, subfamily 4.18E-08 kcna3 potassium voltage-gated channel, shaker 4.30E-08
CLIC2 chloride intracellular channel 2 4.33E-08
IL10RA interleukin 10 receptor, alpha 4.73E-08
NHEDC2 Na+/H+ exchanger domain containing 2 4.76E-08
THEMIS thymocyte selection pathway associated 4.88E-08
ARHGAP30 Rho GTPase activating protein 30 4.97E-08
PRKCB protein kinase C, beta 5.03E-08
HCLS1 hematopoietic cell-specific Lyn substra 5.08E-08
RgslO regulator of G-protein signaling 10 5.66E-08
Evi2a ecotropic viral integration site 2A 5.83E-08
Spn sialophorin 5.84E-08
IL1B interleukin 1, beta 5.88E-08
LOC100133678 similar to hCG2042724; similar to HLA c 6.41E-08
ITGA4 integrin, alpha 4 (antigen CD49D, alpha 6.94E-08
CCDC109B coiled-coil domain containing 109B 7.03E-08
Gapt GRB2-binding adaptor protein, transmemb 7.43E-08
APBB1IP amyloid beta (A4) precursor protein-bin 7.51E-08 arhgdib Rho GDP dissociation inhibitor (GDI) be 7.69E-08
CD180 CD180 molecule 7.79E-08
PIK3CG phosphoinositide-3-kinase, catalytic, g 7.94E-08
CCR5 chemokine (C-C motif) receptor 5 8.05E-08 dgkA diacylglycerol kinase, alpha 80kDa 8.25E-08
RASSF2 Ras association (RalGDS/AF-6) domain fa 8.52E-08
TAGAP T-cell activation RhoGTPase activating 8.59E-08
CAS PI caspase 1, apoptosis-related cysteine p 8.74E-08
LOC606724 coronin, actin binding protein, 1A pseu 9.01E-08
REEP4 receptor accessory protein 4 9.04E-08
GIMAP7 GTPase, IMAP family member 7 9.16E-08
KLRB1 killer cell lectin-like receptor subfam 9.85E-08 97 Icp2 lymphocyte cytosolic protein 2 (SH2 dom 9.99E-08
98 Lairl leukocyte-associated immunoglobulin-lik 1.01E-07
99 CD44 CD44 molecule (Indian blood group) 1.02E-07
100 GZMA granzyme A (granzyme 1, cytotoxic T-lym 1.03E-07
101 rac2 ras-related C3 botulinum toxin substrat 1.13E-07
102 STA BPL1 STA binding protein-like 1 1.17E-07
103 FAM78A family with sequence similarity 78, mem 1.33E-07
104 FAIM3 Fas apoptotic inhibitory molecule 3 1.35E-07
105 Cd6 CD6 molecule 1.39E-07
106 EST EST9 1.42E-07
107 MAP4K1 mitogen-activated protein kinase kinase 1.47E-07
108 CLECIOA C-type lectin domain family 10, member 1.52E-07
109 SP140 SP140 nuclear body protein 1.52E-07
110 SELL selectin L 1.59E-07
111 CRTAM cytotoxic and regulatory T cell molecul 1.60E-07
112 FCER1G Fc fragment of IgE, high affinity 1, re 1.64E-07
113 CP ceruloplasmin (ferroxidase) 1.73E-07
114 GPR171 G protein-coupled receptor 171 1.82E-07
115 Cx3crl chemokine (C-X3-C motif) receptor 1 1.87E-07
116 TBXAS1 thromboxane A synthase 1 (platelet) 1.87E-07
117 SLAMF1 signaling lymphocytic activation molecu 1.88E-07
118 P2RX7 purinergic receptor P2X, ligand-gated i 1.93E-07
119 SAMHD1 SAM domain and HD domain 1 1.94E-07
120 EST EST16 2.00E-07
121 Miat myocardial infarction associated transc 2.01E-07
122 gmfg glia maturation factor, gamma 2.07E-07
123 LCK lymphocyte-specific protein tyrosine ki 2.11E-07
124 SLA Src-like-adaptor 2.14E-07
125 CARD16 caspase recruitment domain family, memb 2.15E-07
126 ETS1 v-ets erythroblastosis virus E26 oncoge 2.17E-07
127 BAZ1A bromodomain adjacent to zinc finger dom 2.20E-07
128 Selplg selectin P ligand 2.28E-07
129 IFI16 interferon, gamma-inducible protein 16 2.29E-07
130 rassf5 Ras association (RalGDS/AF-6) domain fa 2.51E-07
131 ADCY7 adenylate cyclase 7 2.58E-07
132 PLCB2 phospholipase C, beta 2 2.59E-07
133 kcnjlO potassium inwardly-rectifying channel, 2.60E-07
134 STAT4 signal transducer and activator of tran 2.62E-07
135 GPR65 G protein-coupled receptor 65 2.66E-07
136 AI 2 absent in melanoma 2 2.69E-07
137 SERPINB9 serpin peptidase inhibitor, clade B (ov 2.69E-07
138 Ccdc88b coiled-coil domain containing 88B 2.71E-07
139 FECH ferrochelatase (protoporphyria) 2.91E-07 140 Akna AT-hook transcription factor 2.99E-07
141 APOBEC3D apolipoprotein B mRNA editing enzyme, c 3.00E-07
142 BTN3A2 butyrophilin, subfamily 3, member A2 3.01E-07
143 A HGAP9 Rho GTPase activating protein 9 3.20E-07
144 AGl phosphoprotein associated with glycosph 3.23E-07
145 SIGLEC10 sialic acid binding Ig-like lectin 10 3.26E-07
146 FGL2 fibrinogen-like 2 3.30E-07
147 Pou2f2 POU class 2 homeobox 2 3.43E-07
148 CYTIP cytohesin 1 interacting protein 3.44E-07
149 Gadl glutamate decarboxylase 1 (brain, 67kDa 3.56E-07
150 TLR10 toll-like receptor 10 3.56E-07
151 WAS Wiskott-Aldrich syndrome (eczema-thromb 3.59E-07
152 prexl phosphatidylinositol-3,4,5-trisphosphat 3.64E-07
153 C069 CD69 molecule 3.68E-07
154 SLAMF6 SLAM family member 6 3.74E-07
155 CD37 CD37 molecule 3.80E-07
156 ST8SIA4 ST8 alpha-N-acetyl-neuraminide alpha-2, 3.83E-07
157 ANKRD44 ankyrin repeat domain 44 3.90E-07
158 RASAL3 RAS protein activator like 3 3.92E-07
159 KLRDl killer cell lectin-like receptor subfam 3.93E-07
160 SMAP2 small ArfGAP2 4.13E-07
161 pstpip2 proline-serine-threonine phosphatase in 4.24E-07
162 FAM65B family with sequence similarity 65, mem 4.25E-07
163 GI AP4 GTPase, IMAP family member 4 4.36E-07
164 LY86 lymphocyte antigen 86 4.42E-07
165 FMNL1 formin-like 1 4.63E-07
166 fermt3 fermitin family homolog 3 (Drosophila) 4.70E-07
167 Cls complement component 1, s subcomponent 4.78E-07
168 BTN2A2 butyrophilin, subfamily 2, member A2 4.78E-07
169 EST EST17 4.92E-07
170 TLR6 toll-like receptor 6 4.94E-07
171 IRF8 interferon regulatory factor 8 4.98E-07
172 CD163 CD163 molecule 5.02E-07
173 LILRB1 leukocyte immunoglobulin-like receptor, 5.03E-07
174 AP0BEC3F apolipoprotein 8 mRNA editing enzyme, c 5.14E-07
175 Itgax integrin, alpha X (complement component 5.19E-07
176 CTSS cathepsin S 5.54E-07
177 HCST hematopoietic cell signal transducer 5.65E-07
178 ccdc69 coiled-coil domain containing 69 5.66E-07
179 Clr complement component 1, r subcomponent 5.67E-07
180 Nkg7 natural killer cell group 7 sequence 5.70E-07
181 csfl colony stimulating factor 1 (macrophage 5.82E-07
182 pycard PYD and CARD domain containing 5.87E-07 183 SP140L SP140 nuclear body protein-like 5.93E-07
184 Cd53 CD53 molecule 6.01E-07
185 srgn serglycin 6.09E-07
186 SERPINB8 serpin peptidase inhibitor, clade B (ov 6.15E-07
187 IL4R interleukin 4 receptor 6.30E-07
188 6BP2 guanylate binding protein 2, interferon 6.39E-07
189 Fcgr2b Fc fragment of IgG, low affinity lib, r 6.49E-07
190 TIMP1 TIMP metallopeptidase inhibitor 1 6.55E-07
191 C17orf87 chromosome 17 open reading frame 87 6.64E-07
192 GLIPR2 GLI pathogenesis-related 2 6.65E-07
193 LYZ lysozyme (renal amyloidosis) 7.18E-07
194 KIAA0748 KIAA0748 7.30E-07
195 mybll v-myb myeloblastosis viral oncogene horn 7.48E-07
196 CLEC7A C-type lectin domain family 7, member A 7.62E-07
197 KLHL6 kelch-like 6 (Drosophila) 7.67E-07
198 IL4I1 interleukin 4 induced 1 7.87E-07
199 AP0BEC3G apolipoprotein B mRNA editing enzyme, c 8.00E-07
200 TRANK1 lupus brain antigen 1 8.20E-07
Table 12. Biopsy NGS Signatures for subAR using a 2-Step approach (AR+subAR vs. TX and AR v. subAR) - second step: AR vs. subAR
942 CD86 CD86 molecule 3.51E-05
112597 LOC541471 hypothetical LOC541471; non-protein cod 3.57E-05
58191 CXCL16 chemokine (C-X-C motif) ligand 16 3.58E-05
22982 dip2c DIP2 disco-interacting protein 2 homolo 3.66E-05
11177 BAZ1A bromodomain adjacent to zinc finger dom 3.79E-05
8635 RNASET2 ribonuclease T2 3.82E-05
3273 H G histidine-rich glycoprotein 3.85E-05
10346 TRI 22 tripartite motif-containing 22 4.00E-05
83988 NCALD neurocalcin delta 4.07E-05
639 PRDM1 PR domain containing 1, with ZNF domain 4.10E-05
83660 TLN2 talin 2 4.11E-05
284996 Rnfl49 ring finger protein 149 4.12E-05
4773 NFATC2 nuclear factor of activated T-cells, cy 4.20E-05
5967 REG1A regenerating islet-derived 1 alpha; reg 4.25E-05
9235 IL32 interleukin 32 4.45E-05
27071 dappl dual adaptor of phosphotyrosine and 3-p 4.52E-05
7127 TNFAIP2 tumor necrosis factor, alpha-induced pr 4.64E-05
4064 CD180 CD180 molecule 4.81E-05
10859 LILRB1 leukocyte immunoglobulin-like receptor, 4.87E-05
132160 PPM1M protein phosphatase IM (PP2C domain con 4.95E-05
10381 MC1R tubulin, beta 3; melanocortin 1 recepto 4.96E-05
7049 Tgfbr3 transforming growth factor, beta recept 5.48E-05
8322 FZD4 frizzled homolog 4 (Drosophila) 5.59E-05
25816 TNFAIP8 tumor necrosis factor, alpha-induced pr 5.72E-05
3574 117 interleukin 7 5.74E-05
7097 TLR2 toll-like receptor 2 5.81E-05
55016 1-Mar membrane-associated ring finger (C3HC4) 5.85E-05
93349 SP140L SP140 nuclear body protein-like 5.86E-05
3587 IL10RA interleukin 10 receptor, alpha 5.87E-05
9672 sdc3 syndecan 3 5.87E-05
6648 Sod2 superoxide dismutase 2, mitochondrial 5.88E-05
30817 E R2 egf-like module containing, mucin-like, 5.92E-05
5724 PTAFR platelet-activating factor receptor 5.94E-05
2650 GCNT1 glucosaminyl (N-acetyl) transferase 1, 6.00E-05
441168 fam26f family with sequence similarity 26, mem 6.06E-05
56253 CRTAM cytotoxic and regulatory T cell molecul 6.08E-05
149773 LOC149773 hypothetical protein LOC149773 6.22E-05
115761 ARL11 ADP-ribosylation factor-like 11 6.25E-05
6775 STAT4 signal transducer and activator of tran 6.39E-05
7008 tef thyrotrophic embryonic factor 6.44E-05
222236 NAPEPLD N-acyl phosphatidylethanolamine phospho 6.47E-05
3158 HMGCS2 3-hydroxy-3-methylglutaryl-Coenzyme A s 6.52E-05
1356 CP ceruloplasmin (ferroxidase) 6.55E-05 57224 nhsll NHS-like 1 6.56E-05
9535 gmfg glia maturation factor, gamma 7.16E-05
114905 Clqtnf7 Clq and tumor necrosis factor related p 7.18E-05
10123 Arl4c ADP-ribosylation factor-like 4C 7.33E-05
51706 CYB5R1 cytochrome b5 reductase 1 7.42E-05
5552 srgn serglycin 7.47E-05
81619 TSPAN14 tetraspanin 14 7.64E-05
151295 SLC23A3 solute carrier family 23 (nucleobase tr 7.72E-05
55013 CCDC109B coiled-coil domain containing 109B 7.88E-05
6916 TBXAS1 thromboxane A synthase 1 (platelet) 7.88E-05
917 Cd3g CD3g molecule, gamma (CD3-TCR complex) 8.00E-05
55423 SIRPG signal-regulatory protein gamma 8.02E-05
441108 C5orf56 chromosome 5 open reading frame 56 8.13E-05
90826 PR T10 protein arginine methyltransferase 10 ( 8.32E-05
23231 Selll3 KIAA0746 protein 8.35E-05
115330 GPR146 G protein-coupled receptor 146 8.65E-05
84465 Megfll multiple EGF-like-domains 11 8.72E-05
2634 GBP2 guanylate binding protein 2, interferon 8.89E-05
83416 FCRL5 Fc receptor-like 5 9.17E-05
1326 MAP3K8 mitogen-activated protein kinase kinase 9.36E-05
10585 pomtl protein-O-mannosyltransferase 1 9.46E-05
80709 Akna AT-hook transcription factor 9.52E-05
5583 PRKCH protein kinase C, eta 9.56E-05
2533 FYB FYN binding protein (FYB-120/130) 0.000101095
710 SERPING1 serpin peptidase inhibitor, clade G (CI 0.000101427
57545 CC2D2A coiled-coil and C2 domain containing 2A 0.000101929
57477 Shroom4 shroom family member 4 0.000102322
27113 BBC3 BCL2 binding component 3 0.000104668
257019 frmd3 FERM domain containing 3 0.000105901
915 CD3D CD3d molecule, delta (CD3-TCR complex) 0.000108676
29851 ICOS inducible T-cell co-stimulator 0.000114201
387357 THEMIS thymocyte selection pathway associated 0.00011469
4065 Ly75 CD302 molecule; lymphocyte antigen 75 0.000116227
4794 Nfkbie nuclear factor of kappa light polypepti 0.000117246
64407 RGS18 regulator of G-protein signaling 18 0.000118196
7052 tgm2 transglutaminase 2 (C polypeptide, prot 0.000120567
2857 GPR34 G protein-coupled receptor 34 0.000120768
128346 Clorfl62 chromosome 1 open reading frame 162 0.000123894
3683 ITGAL integrin, alpha L (antigen CD11A (pl80) 0.00012454
2123 Evi2a ecotropic viral integration site 2A 0.000127081
55784 MCTP2 multiple C2 domains, transmembrane 2 0.000127734
919 Cd247 CD247 molecule 0.000130792
3226 HOXC10 homeobox CIO 0.000133565 83706 fermt3 fermitin family omolog 3 (Drosophila) 0.000135104
7412 Vcaml vascular cell adhesion molecule 1 0.000136061
9372 zfyve9 zinc finger, FYVE domain containing 9 0.000136444
55920 RCC2 regulator of chromosome condensation 2 0.000136649
5359 plscrl phospholipid scramblase 1 0.000140346
837 Casp4 caspase 4, apoptosis-related cysteine p 0.000141051
57685 CACHD1 cache domain containing 1 0.00014644
51809 Galnt7 UDP-N-acetyl-alpha-D-galactosamine:poly 0.000149312
29992 PILRA paired immunoglobin-like type 2 recepto 0.000149525
259307 IL4I1 interleukin 4 induced 1 0.000151253
162394 Slfn5 schlafen family member 5 0.000153617
2124 EVI2B ecotropic viral integration site 2B 0.000154185
57580 prexl phosphatidylinositol-3,4,5-trisphosphat 0.000156406
114614 MIR155 microRNA host gene 2 (non-protein codin 0.000158216
51411 Bin2 bridging integrator 2 0.000159986
4481 Msrl macrophage scavenger receptor 1 0.000161335
26157 GIMAP2 GTPase, IMAP family member 2 0.000163916
92241 Rcsdl RCSD domain containing 1 0.000164738
123920 Cmtm3 CKLF-like MARVEL transmembrane domain c 0.000165918
51284 TLR7 toll-like receptor 7 0.000170376
3796 KIF2A kinesin heavy chain member 2A 0.000170538
961 CD47 CD47 molecule 0.000170747
54900 LAX1 lymphocyte transmembrane adaptor 1 0.000173443
23670 Tmem2 transmembrane protein 2 0.000174023
1475 cstA cystatin A (stefin A) 0.00017513
4067 LYN v-yes-1 Yamaguchi sarcoma viral related 0.000175578
10406 WFDC2 WAP four-disulfide core domain 2 0.000180471
7913 Dek DEK oncogene 0.000180846
346389 Maccl metastasis associated in colon cancer 1 0.000181678
84230 LRRC8C leucine rich repeat containing 8 family 0.000181977
10460 TACC3 transforming, acidic coiled-coil contai 0.000182925
1051 CEBPB CCAAT/enhancer binding protein (C/EBP), 0.000184525
114793 FMNL2 formin-like 2 0.000185065
1794 D0CK2 dedicator of cytokinesis 2 0.000199278
7305 TYROBP TYRO protein tyrosine kinase binding pr 0.00019956
9180 OSMR oncostatin M receptor 0.000202103
Table 13. 2-Way 2-Step NGS Analysis (AR v. subAR; AR v. TX; and subAR v. TX) usin biopsy samples - Results
Table 14. Blood Microarray Signatures for subAR using a 3-Way 1 -Step approach (AR vs. subAR vs. TX): full gene list (818 genes) at FDR < 5%
214 96_PM_x_at MYST4 MYST histone acetyltransferase (monocytic 1.35E-07 leukemia) 4
222406_PM_s_at PNRC2 proline-rich nuclear receptor coactivator 2 1.43E-07
212417_P _at SCAMPI secretory carrier membrane protein 1 1.78E-07
227144_PM_at C22orf9 chromosome 22 open reading frame 9 1.98E-07
244611_P _at MED13 Mediator complex subunit 13 2.23E-07
219024_PM_at PLEKHA1 pleckstrin homology domain containing, 2.62E-07 family A (phosphoinositide binding specific) mem
1559051_P _s_at C6orfl50 chromosome 6 open reading frame 150 2.78E-07
231418_PM_at EST231418_PM_at — 2.88E-07
202818_PM_s_at TCEB3 transcription elongation factor B (Sill), 3.30E-07 polypeptide 3 (HOkDa, elongin A)
201728_P _s_at IAA0100 KIAA0100 3.32E-07
201083_P _s_at BCLAF1 BCL2-associated transcription factor 1 3.64E-07
208615_PM_s_at PTP4A2 protein tyrosine phosphatase type IVA, 3.88E-07 member 2
200745_PM_s_at GNB1 guanine nucleotide binding protein (G 4.45E-07 protein), beta polypeptide 1
215586_PM_at EST215586_PM_at — 4.62E-07
228801_PM_at 0RMDL1 ORMl-like 1 (S. cerevisiae) 5.52E-07
208879_P _x_at PRPF6 PRP6 pre-mRNA processing factor 6 homolog 5.70E-07
(S. cerevisiae)
208003_PM_s_at NFAT5 nuclear factor of activated T-cells 5, tonicity- 6.96E-07 responsive
216449_PM_x_at HSP90B1 heat shock protein 90kDa beta (Grp94), 7.21E-07 member 1
201235_PM_s_at BT62 BTG family, member 2 8.31E-07
236484_PM_at EST236484_PM_at — 1.02E-06
227082_PM_at EST227082_PM_at — 1.21E-06
236841_PM_at LOC100134445 hypothetical LOC100134445 1.27E-06
236207_PM_at SSFA2 sperm specific antigen 2 1.28E-06
215282_PM_at ANAPC13 anaphase promoting complex subunit 13 1.58E-06
1555568_PM_at GUSBL1 glucuronidase, beta-like 1 1.60E-06
236512_PM_at EST236512_PM_at — 1.85E-06
224687_PM_at AN IB1 ankyrin repeat and IBR domain containing 1 2.08E-06
202719_P _s_at TES testis derived transcript (3 UM domains) 2.27E-06
213311_PM_s_at TCF25 transcription factor 25 (basic helix-loop-helix) 2.29E-06
229193_PM_at LUC7L3 LUC7-like 3 (S. cerevisiae) 2.33E-06
221905_PM_at CYLD cylindromatosis (turban tumor syndrome) 2.48E-06
217418_PM_x_at MS4A1 membrane-spanning 4-domains, subfamily A, 2.73E-06 member 1
217234_P _s_at EZR ezrin 2.75E-06
222866_PM_s_at FLVC 2 feline leukemia virus subgroup C cellular 2.78E-06 receptor family, member 2
209207_PM_s_at SEC22B SEC22 vesicle trafficking protein homolog B (S. 2.80E-06 cerevisiae) (gene/pseudogene)
232127_PM_at CLCN5 chloride channel 5 2.82E-06
243559_PM_at EST243559_PM_at — 3.05 E-06 241668_PM_s_at EST241668_P _s_at — 3.13E-06
203145_PM_at SPAG5 sperm associated antigen 5 3.17E-06
235430_PM_at C14orf43 chromosome 14 open reading frame 43 4.05 E-06
222628_PM _at REV1 REV1 homolog (S. cerevisiae) 4.08E-06
209920_PM_at BMPR2 bone morphogenetic protein receptor, type II 4.18E-06
(serine/threonine kinase)
206668_PM_s_at SCAMPI secretory carrier membrane protein 1 4.29E-06
1555562_PM_a_at ZCCHC7 zinc finger, CCHC domain containing 7 4.31E-06
1562031_P _at JAK2 Janus kinase 2 4.42E-06
236109_PM_at EST236109_PM_at — 4.50E-06
200598_PM_s_at HSP90B1 heat shock protein 90kDa beta (Grp94), 4.92E-06 member 1
210356_PM_x_at MS4A1 membrane-spanning 4-domains, subfamily A, 5.02E-06 member 1
240859_PM_at EST240859_PM_at — 5.15E-06
202173_PM_s_at VEZF1 vascular endothelial zinc finger 1 5.21E-06
200900_PM_s_at M6PR mannose-6-phosphate receptor (cation 5.75E-06 dependent)
212027_PM_at RBM25 RNA binding motif protein 25 5.96E-06
222915_PM_s_at BANK1 B-cell scaffold protein with ankyrin repeats 1 6.07E-06
230028_PM_at EST230028_PM_at — 6.08E-06
200950_PM_at ARPC1A actin related protein 2/3 complex, subunit 1A, 6.24E-06
41kDa
240220_PM_at EST240220_PM_at 6.48E-06
204565_PM_at AC0T13 acyl-CoA thioesterase 13 6.48E-06
210172_PM_at SF1 splicing factor 1 6.66E-06
1554249_PM_a_at ZNF638 zinc finger protein 638 6.73E-06
228818_PM_at EST228818_PM_at 6.88E-06
212574_PM_x_at C19orf6 chromosome 19 open reading frame 6 7.23E-06
239077_PM_at CSGALNACT2 chondroitin sulfate N- 7.51E-06 acetylgalactosaminyltransferase 2
209281_PM_s_at ATP2B1 ATPase, Ca++ transporting, plasma membrane 7.92E-06
1
224989_PM_at EST224989_PM_at 7.93E-06
240718_PM_at LRMP Lymphoid-restricted membrane protein 8.17E-06
229268_P _at FAM105B family with sequence similarity 105, member 8.39E-06
B
203141_PM_s_at AP3B1 adaptor-related protein complex 3, beta 1 8.46E-06 subunit
236254_PM_at VPS13B vacuolar protein sorting 13 homolog B (yeast) 8.55E-06
216263_PM_s_at NGDN neuroguidin, EIF4E binding protein 8.70E-06
235119_PM_at TAF3 TAF3 RNA polymerase II, TATA box binding 8.72E-06 protein (TBP)-associated factor, 140kDa
213649_PM_at SRSF7 serine/arginine-rich splicing factor 7 8.73E-06
1559485_PM_at ATG2B ATG2 autophagy related 2 homolog B (S. 9.15E-06 cerevisiae)
243414_PM_at PPIL2 Peptidylprolyl isomerase (cyclophilin)-like 2 9.30E-06
212658_PM_at LHFPL2 lipoma HMGIC fusion partner-like 2 9.40E-06
AFFX-r2-Bs-dap-5_at ESTAFFX-r2-Bs-da p- — 9.55E-06 236524_PM_at EST236524_PM_at — 2.16E-05
235547_PM_at N4BP2L2 NEDD4 binding protein 2-like 2 2.20E-05
224684_PM_at SNX12 sorting nexin 12 2.22E-05
212467_P _at DNAJC13 DnaJ (Hsp40) homolog, subfamily C, member 2.23E-05
13
1553304_PM_at LSM14B LSM14B, SCD6 homolog B (S. cerevisiae) 2.44E-05
215489_PM_x_at HOME 3 homer homolog 3 (Drosophila) 2.44E-05
220843_PM_s_at DCAF13 DDB1 and CUL4 associated factor 13 2.52E-05
223217_PM_s_at NFKBIZ nuclear factor of kappa light polypeptide gene 2.59E-05 enhancer in B-cells inhibitor, zeta
232323_PM_s_at TTC17 tetratricopeptide repeat domain 17 2.60E-05
232353_PM_s_at STYXL1 serine/threonine/tyrosine interacting-like 1 2.65E-05
1563674_P _at FCRL2 Fc receptor-like 2 2.69E-05
208325_PM_s_at AKAP13 A kinase (PRKA) anchor protein 13 2.71E-05
1560814_P _a_at C15orfS7 chromosome 15 open reading frame 57 2.77E-05
201085_PM_s_at SON SON DNA binding protein 2.77E-05
1568680_PM_s_at YTHDC2 YTH domain containing 2 2.80E-05
217979_PM_at TSPAN13 tetraspanin 13 2.82E-05
241237_P _at EST241237_PM_at — 2.85E-05
243739_PM_at EST243739_P _at — 5.74E-05
212022_PM_s_at MKI67 antigen identified by monoclonal antibody Ki- 3.10E-05
67
236562_P _at ZNF439 zinc finger protein 439 3.12E-05
214869_PM_x_at GAPVD1 GTPase activating protein and VPS9 domains 1 3.14E-05
1553961_P _s_at SNX21 sorting nexin family member 21 3.17E-05
203958_PM _at ZBTB40 zinc finger and BTB domain containing 40 3.24E-05
240593_PM_x_at EST240593_PM_x_at — 3.31E-05
216901_PM_s_at IKZF1 IKAROS family zinc finger 1 (Ikaros) 3.34E-05
225878_PM_at IF1B kinesin family member IB 3.42 E-05
224818_PM_at SORT1 sortilin 1 3.47E-05
225240_PM_s_at MSI2 musashi homolog 2 (Drosophila) 3.51E-05
222522_PM_x_at MRPS10 mitochondrial ribosomal protein S10 3.56E-05
228147_PM_at EST228147_P _at — 3.62E-05
222575_PM_at SETD5 SET domain containing 5 3.75E-05
214474_PM_at PR AB2 protein kinase, AMP-activated, beta 2 non- 3.80E-05 catalytic subunit
233409_PM_at RHBDL3 rhomboid, veinlet-like 3 (Drosophila) 3.84E-05
239815_PM_at EST239815_PM_at — 3.95E-05
213998_PM_s_at DDX17 DEAD (Asp-Glu-Ala-Asp) box polypeptide 17 4.03E-05
AFFX-DapX-5_at ESTAFFX-DapX-5_at — 4.20E-05
1567045_PM_at EST1567045_PM_at — 4.23E-05
204324_PM_s_at GOUM4 golgi integral membrane protein 4 4.27E-05
208835_PM_s_at LUC7L3 LUC7-like 3 (S. cerevisiae) 4.40E-05
210214_PM_s_at BMPR2 bone morphogenetic protein receptor, type II 4.41E-05
(serine/threonine kinase) 210282_PM_at ZMY 2 zinc finger, YM-type 2 4.44E-05
222873_PM_s_at EHMT1 euchromatic histone-lysine N- 4.44E-0S methyltransferase 1
243932_PM_at EST243932_P _at — 4.63E-05
1568907_PM_at EST1568907_PM_at — 4.65E-05
208797_P _s_at GOLGA8A golgin A8 family, member A 4.69E-05
218393_PM_s_at S U1 smu-1 suppressor of mec-8 and unc-52 4.69E-05 homolog (C. elegans)
239027_PM_at DOC 8 dedicator of cytokinesis 8 4.74E-05
215894_PM_at PTGD prostaglandin D2 receptor (DP) 4.82E-05
208114_PM_s_at ISG20L2 interferon stimulated exonuclease gene 4.83E-05
20kDa-like 2
212076_PM_at MLL myeloid/lymphoid or mixed-lineage leukemia 4.90E-05
(trithorax homolog, Drosophila)
222326_P _at EST222326_PM_at — 5.04E-05
215603_PM_x_at GGT2 gamma-glutamyltransferase 2 5.04E-05
224933_PM_s_at J JD1C jumonji domain containing 1C 5.08E-05
242197_PM_x_at CD36 CD36 molecule (thrombospondin receptor) 5.28E-05
230629_P _s_at EP400 E1A binding protein p400 5.31E-05
243361_PM_at SREK1 splicing regulatory glutamine/lysine-rich 5.32E-05 protein 1
237884_PM_x_at TRPM7 transient receptor potential cation channel, 5.35E-05 subfamily M, member 7
236557_PM_at ZBTB38 zinc finger and BTB domain containing 38 5.36E-05
223307_PM_at CDCA3 cell division cycle associated 3 5.42E-05
218321_P _x_at STYXL1 serine/threonine/tyrosine interacting-like 1 5.48E-05
205179_P _s_at ADAM8 ADAM metallopeptidase domain 8 5.49E-05
227329_P _at ZBTB46 zinc finger and BTB domain containing 46 5.67E-05
222395_PM_s_at UBE2Z ubiquitin-conjugating enzyme E2Z 5.69E-05
201488_PM_x_at KHDRBS1 KH domain containing, RNA binding, signal 5.72E-05 transduction associated 1
200806_PM_s_at HSPD1 heat shock 60kDa protein 1 (chaperonin) 5.73E-05
244233_PM_at C18orfl0 chromosome 18 open reading frame 10 0.000168658
225098_PM_at ABI2 abl-interactor 2 5.74E-05
222540_PM_s_at RSF1 remodeling and spacing factor 1 5.82E-05
242422_P _at G3BP1 GTPase activating protein (SH3 domain) 5.85E-05 binding protein 1
206371_PM_at F0LR3 folate receptor 3 (gamma) 5.98E-05
204270_PM_at SKI v-ski sarcoma viral oncogene homolog (avian) 5.99E-05
207826_PM_s_at ID3 inhibitor of DNA binding 3, dominant negative 6.00E-05 helix-loop-helix protein
235216_PM_at ESCOl establishment of cohesion 1 homolog 1 (S. 6.01E-05 cerevisiae)
1558088_PM_a_at UBE2I ubiquitin-conjugating enzyme E2I (UBC9 6.18E-05 homolog, yeast)
206521_PM_s_at GTF2A1 general transcription factor IIA, 1, 19/37kDa 6.21E-05
210693_PM_at SPPL2B signal peptide peptidase-like 2B 6.27E-05
202953_PM_at C1QB complement component 1, q subcomponent, 6.31E-05
B chain 2279l8_PM_s_at ZYG11B zyg-11 homolog B (C. elegans) 6.37E-05
223569_PM_at PPAPDC1B phosphatidic acid phosphatase type 2 domain 6.43E-05 containing IB
215667_PM_x_at LOC441259 /// PMS2L2 PMS2 postmeiotic segregation increased 2 (S. 6.50E-05
/// PMS2P1 /// cerevisiae)-like /// postmeiotic segregati
PMS2P6
222563_PM_s_at TNKS2 tankyrase, TRFl-interacting ankyrin-related 6.50E-05
ADP-ribose polymerase 2
209076_PM_s_at WDR45L WDR45-like 6.56E-05
233261_PM_at EBF1 Early B-cell factor 1 6.68E-05
229389_PM_at ATG16L2 ATG16 autophagy related 16-like 2 (S. 6.70E-05 cerevisiae)
223969_PM_s_at RETNLB resistin like beta 6.72E-05
228868_P _x_at CDT1 Chromatin licensing and DNA replication 6.80E-05 factor 1
1558173_PM_a_at LUZP1 leucine zipper protein 1 6.90E-05
2433l9_P _at EST243319_PM_at — 6.92E-05
203479_PM_s_at 0TUD4 OTU domain containing 4 7.03E-05
35201_PM_at HNRNPL heterogeneous nuclear ribonucleoprotein L 7.13E-05
244696_P _at EST244696_PM_at — 7.18E-05
202705_PM_at CCNB2 cy in B2 7.25E-05
239154_PM_at EST239154P _at — 7.31E-05
230270_PM_at PRPF38B PRP38 pre-mRNA processing factor 38 (yeast) 7.31E-05 domain containing B
209583_PM_s_at CD 200 CD200 molecule 7.37E-05
214250_PM_at NUMA1 nuclear mitotic apparatus protein 1 7.37E-05
222508_PM_s_at ARGLU1 arginine and glutamate rich 1 7.38E-05
20134 _PM_x_at GRHPR gtyoxylate reductase/hydroxypyruvate 7.44E-05 reductase
1552812_P _a_at SENP1 SUMOl/sentrin specific peptidase 1 7.83E-05
202773_PM_s_at SFSWAP splicing factor, suppressor of white-apricot 8.00E-05 homolog (Drosophila)
AFFX-r2-Bs-dap-M_at ESTAFFX-r2-Bs-dap- — 8.02E-05
M at
218474_P _s_at CTD5 potassium channel tetramerisation domain 0.000187936 containing 5
209582_PM_s_at CD200 CD200 molecule 8.08E-05
211417_PM_x_at GGT1 gamma-glutamyltransferase 1 8.10E-05
201996_P _s_at SPEN spen homolog, transcriptional regulator 8.45E-05
(Drosophila)
222996_PM_s_at CXXC5 CXXC finger protein 5 8.51E-05
215937_PM_at PTGDR prostaglandin D2 receptor (DP) 8.56E-05
230424_PM_at C5orfl3 chromosome 5 open reading frame 13 8.66E-05
203796_PM_s_at BCL7A B-cell CLl/lymphoma 7A 8.88E-05
2416l9_PM_at CALM1 calmodulin 1 (phosphorylase kinase, delta) 8.90E-05
238277_PM_at EST238277_PM_at — 9.06E-05
208268_PM_at ADAM28 ADAM metallopeptidase domain 28 9.25E-05
226079_P _at FLYWCH2 FLYWCH family member 2 9.43E-05
212119_PM_at RHOQ ras homolog gene family, member Q 9.49E-05 235956_PM_at IAA1377 KIAA1377 9.61E-05
230245_PM_s_at LOC283663 hypothetical LOC283663 9.61E-05
1559589_PM_a_at EST1559S89_PM_a_at — 9.62E-05
AFFX- 27830_5_at ESTAFFX-M27830_5_at — 9.63E-05
219751_PM_at SETD6 SET domain containing 6 9.94E-05
207655_PM_s_at BLNK B-cell linker 0.000100294
227849_P _at RP9 Retinitis pigmentosa 9 (autosomal dominant) 0.000100349
243236_P _at EST243236_PM_at — 0.000100441
1556983_P _a_at EST1556983_P _a_at — 0.000101358
201537_P _s_at DUSP3 dual specificity phosphatase 3 0.000102353
203276_PM_at L NB1 lamin Bl 0.000103605
1555913_PM_at G0N4L gon-4-like (C. elegans) 0.00010638
244011_PM_at PPM1K protein phosphatase, Mg2+/Mn2+ 0.000106418 dependent, IK
226647_PM_at TMEM25 transmembrane protein 25 0.000107452
221220_PM_s_at SCYL2 SCYl-like 2 (S. cerevisiae) 0.000109068
227101_PM_at ZNF800 zinc finger protein 800 0.000109971
23123S_PM_at N TR natural killer-tumor recognition sequence 0.000112022
235112_PM_at EST235112_P _at — 0.000112143
215270_P _at LFNG LFNG O-fucosylpeptide 3-beta-N- 0.000113268 acetylg!ucosaminyltransferase
224918_PM_x_at M6ST1 microsomal glutathione S-transferase 1 0.000120191
243381_P _at EST243381_P _at — 0.000121699
227173_P _s_at BACH 2 BTB and CNC homology 1, basic leucine zipper 0.000122183 transcription factor 2
201236_PM_s_at BTG2 BTG family, member 2 0.000124084
235003_PM_at UH 1 U2AF homology motif (UHM) kinase 1 0.000124901
206983_PM_at CCR6 chemokine (C-C motif) receptor 6 0.000129751
206708_P _at F0XN2 forkhead box N2 0.000130568
233955_PM_x_at CXXC5 CXXC finger protein 5 0.000132557
238743_PM_at EST238743_PM_at — 0.000133124
239130_PM_at IRlOl-1 microRNA 101-1 0.000133903
208478_PM_s_at BAX BCL2-associated X protein 0.000134313
213315_PM_x_at CXorf40A chromosome X open reading frame 40A 0.000134499
227894_PM_at WDR90 WD repeat domain 90 0.000134921
212382_P _at TCF4 transcription factor 4 0.000135201
209773_P _s_at RRM2 ribonucleotide reductase 2 0.000137305
1561872_PM_at EST1561872_PM_at — 0.000138018
212961_PM_x_at CXorf40B chromosome X open reading frame 40B 0.000140653
240521_P _at EST24Q521_PM_at — 0.000142199
222922_PM_at KCNE3 potassium voltage-gated channel, Isk-related 0.000142431 family, member 3
232070_PM_at LOC100499193 hypothetical LOC100499193 0.000144063
217230_PM_at EZR ezrin 0.000144366
233252_P _s_at STRBP spermatid perinuclear RNA binding protein 0.000145405 242225_PM_at EST242225_PM_at — 0.000191962
231736_PM_x_at MGST1 microsomal glutathione S-transferase 1 0.000192368
207165_PM_at H MR hyaluronan-mediated motility receptor 0.000192879
(RHA )
1555978_P _s_at EST1555978_P _s_at — 0.000201472
226879_PM_at HVCN1 hydrogen voltage-gated channel 1 0.00020194
221234_PM_s_at BACH2 BTB and CNC homology 1, basic leucine zipper 0.000202403 transcription factor 2
AFFX-r2-Bs-lys-3_at ESTAFFX-r2-Bs-lys-3_at 0.000203767
226968_PM_at KIF1B kinesin family member IB 0.000204386
210384_P _at PR T2 protein arginine methyltransferase 2 0.000207517
219667_PM_s_at BAN 1 B-cell scaffold protein with ankyrin repeats 1 0.000209859
202723_PM_s_at F0X01 forkhead box 01 0.000210019
211217_PM_s_at KCNQ1 potassium voltage-gated channel, KQT-like 0.000210371 subfamily, member 1
238511_PM_at LOC440288 similar to FU16518 protein 0.000211154
221601_PM_s_at FAIM3 Fas apoptotic inhibitory molecule 3 0.000212934
219806_PM_s_at Cllorf75 chromosome 11 open reading frame 75 0.000213004
210596_PM_at MAGT1 magnesium transporter 1 0.000217053
226008_PM_at NDNL2 necdin-like 2 0.000219345
213517_PM_at PCBP2 poly(rC) binding protein 2 0.000220506
1569894_PM_at PPP2R3C protein phosphatase 2, regulatory subunit B", 0.000220967 gamma
211074_P _at FOLR1 folate receptor 1 (adult) 0.000225092
226094_PM_at PIK3C2A phosphoinositide-3-kinase, class 2, alpha 0.0002278 polypeptide
202371_PM_at TCEAL4 transcription elongation factor A (Sll)-like 4 0.000228612
201072_PM_s_at S ARCC1 SWI/SNF related, matrix associated, actin 0.000229302 dependent regulator of chromatin, subfamily
c
215457_PM_at EST215457_P _at 0.000230542
220436_PM_at CNTNAP3B similar to cell recognition molecule CASPR3 0.000231163
200810_PM_s_at CIRBP cold inducible RNA binding protein 0.000233312
201073_PM_s_at SMARCC1 SWI/SNF related, matrix associated, actin 0.000233789 dependent regulator of chromatin, subfamily
c
235852_PM_at STON2 Stonin 2 0.000236399
1569385_PM_s_at TET2 tet oncogene family member 2 0.000237687
228592_PM_at MS4A1 membrane-spanning 4-domains, subfamily A, 0.000238044 member 1
205726_PM_at DIAPH2 diaphanous homolog 2 (Drosophila) 0.000239122
223766_PM_at LOC100133130 PRO1102 0.000240505
228487_PM_s_at EST228487_P _s_at 0.000243645
231340_PM_at EST231340_P _at 0.000244821
222228_PM_s_at AL BH4 alkB, alkyiation repair homolog 4 (E. coli) 0.000246256
202072_PM_at HNRNPL heterogeneous nuclear ribonucleoprotein L 0.000246632
206881 PM s at LILRA3 leukocyte immunoglobulin-like receptor, 0.000247423 subfamily A (without TM domain), member 3 230128_PM_at IGL@ Immunoglobulin lambda locus 0.000247531
209060_P _x_at NCOA3 nuclear receptor coactivator 3 0.000247993
15S7270_PM_at EST1557270_P _at — 0.000249224
233078_PM_at API5 apoptosis inhibitor 5 0.000253409
1553793_PM_a_at KIAA1109 KIAA1109 0.000254467
215339_P _at NKTR natural killer-tumor recognition sequence 0.000255637
1556314_PM_a_at EST1556314_P _a_at — 0.000255826
208079_P _s_at AUR A aurora kinase A 0.000257743
218300_PM_at C16orf53 chromosome 16 open reading frame 53 0.000258687
1556461_PM_at EST1556461_P _at — 0.000259468
1558733_PM_at ZBTB38 zinc finger and BTB domain containing 38 0.000260942
225742_PM_at MDM4 Mdm4 p53 binding protein homolog (mouse) 0.000264828
204028_PM_s_at RABGAP1 RAB GTPase activating protein 1 0.000265807
1559618_PM_at LOC100129447 hypothetical protein LOC100129447 0.000268803
1564494_PM_s_at P4HB prolyl 4-hydroxylase, beta polypeptide 0.000269853
212452_PM_x_at MYST4 MYST histone acetyltransferase (monocytic 0.000270084 leukemia) 4
201960_PM_s_at MYCBP2 MYC binding protein 2 0.000275031
1561286_P _a_at DIP2A DIP2 disco-interacting protein 2 homolog A 0.000276434
(Drosophila)
219581_PM_at TSE 2 tRNA splicing endonuclease 2 homolog (S. 0.000276518 cerevisiae)
242946_PM_at EST242946_P _at — 0.000277157
212684_PM_at ZNF3 zinc finger protein 3 0.00028112
214669_PM_x_at IG @ /// IGKC immunoglobulin kappa locus /// 0.000282936 immunoglobulin kappa constant
217613_PM_at TMEM144 transmembrane protein 144 0.000285003
238811_PM_at ATP11B ATPase, class VI, type 11B 0.000286178
218039_PM_at NUSAP1 nucleolar and spindle associated protein 1 0.000287635
225095_P _at SPTLC2 serine palmitoyltransferase, long chain base 0.000289913 subunit 2
208799_PM_at PSMB5 proteasome (prosome, macropain) subunit, 0.00029164 beta type, 5
230897_PM_at CCDC30 /// coiled-coil domain containing 30 /// 0.000292704
LOC100507214 hypothetical LOC100507214
214735_PM_at IPCEF1 interaction protein for cytohesin exchange 0.00029714 factors 1
239545_PM_at EST239545_PM_at — 0.000297175
243780_P _at EST243780_P _at — 0.000297494
201689_PM_s_at TPD52 tumor protein D52 0.000298768
209919_PM_x_at GGT1 gamma-glutamyltransferase 1 0.000299895
210052_PM_s_at TPX2 TPX2, microtubule-associated, homolog 0.000301428
(Xenopus laevis)
209994_PM_s_at ABCB1 /// ABCB4 ATP-binding cassette, sub-family B 0.000302891
(MDR/TAP), member 1 /// ATP-binding
cassette, sub-fa
227466_PM_at FA 200B family with sequence similarity 200, member 0.000303971
B
209797_PM_at CNPY2 canopy 2 homolog (zebrafish) 0.000304017 229157_P _at LOC100505483 hypothetical LOC100505483 0.000307218
201805_PM_at P KAG1 protein kinase, AMP-activated, gamma 1 non- 0.000307861 catalytic subunit
AFFX-r2-Pl-cre-3_at ESTAFFX-r2-Pl-cre-3_at — 0.000472245
200607_PM_s_at RAD21 RAD21 homolog (S. pombe) 0.00031137
212113_P _at ATXN7L3B ataxin 7-like 3B 0.000314652
236327_P _at EST236327_PM_at — 0.000315612
224795_PM_x_at IGK@ /// IGKC immunoglobulin kappa locus /// 0.000316664 immunoglobulin kappa constant
240826_PM_at EST240826_PM_at — 0.000318564
237560_PM_at MRPS5 Mitochondrial ribosomal protein S5 0.000320215
239902_PM_at EST239902_PM_at — 0.000322709
201825_PM_s_at SCCPDH saccharopine dehydrogenase (putative) 0.00032353
240965_PM_at EST240965_PM_at — 0.000324754
217813_PM_s_at SPIN1 spindlin 1 0,00032924
205770_PM_at GSR glutathione reductase 0.000330346
214263_PM_x_at P0LR2C polymerase (RNA) II (DNA directed) 0.000331556 polypeptide C, 33kDa
214677_PM_x_at IGL@ /// Immunoglobulin lambda locus /// 0.000332453
LOC100287927 Hypothetical protein LOC100287927
244456_P _at EST244456_PM_at — 0.000333092
221651_PM_x_at IGK@ /// IGKC immunoglobulin kappa locus /// 0.000333367 immunoglobulin kappa constant
236650_PM_at EST236650_PM_at — 0.000337191
220946_PM_s_at SETD2 SET domain containing 2 0.000337367
224516_PM_s_at CXXC5 CXXC finger protein 5 0.000337471
212581_P _x_at GAPOH glyceraldehyde-3-phosphate dehydrogenase 0.000338308
212492_P _s_at DM4B lysine (K)-specific demethylase 4B 0.000338683
221969_P _at PAX5 paired box 5 0.000340498
242498_PM_x_at EST242498_PM_x_at — 0.000342507
222737_PM_s_at BRD7 bromodomain containing 7 0.00034288
204714_PM_s_at F5 coagulation factor V (proaccelerin, labile 0.000343146 factor)
203671_PM_at TPMT thiopurine S-methyltransferase 0.000344362
225353_PM_s_at C1QC complement component 1, q subcomponent, 0.000345493
C chain
225709_PM_at ARL6IP6 ADP-ribosylation-like factor 6 interacting 0.000345892 protein 6
237040_PM_at CWF19L2 CWF19-like 2, cell cycle control (S. pombe) 0.000346442
226731_PM_at ITGA1 integrin, alpha 1 0.000348057
AFFX-r2-Bs-phe-5_at ESTAFFX-r2-Bs-phe- — 0.000348063
5 at
205467_P _at CAS P 10 caspase 10, apoptosis-related cysteine 0.000348547 peptidase
209001_PM_s_at ANAPC13 anaphase promoting complex subunit 13 0.000349407
233982_PM_x_at STYXL1 serine/threonine/tyrosine interacting-like 1 0.000350724
239040_PM_at HNRNPD Heterogeneous nuclear ribonucleoprotein D 0.00035153
(AU-rich element RNA binding protein 1,
37kDa 205756_PM_s_at F8 coagulation factor VIII, procoagulant 0.000357136 component
1554229_PM_at C5orf41 chromosome 5 open reading frame 41 0.00035719
1568877_P _a_at ACBD5 acyl-CoA binding domain containing 5 0.000360867
207707_PM_s_at SEC13 SEC13 homolog (S. cerevisiae) 0.000360921
241403_PM_at CLK4 CDC-like kinase 4 0.00036609
208664_PM_s_at TTC3 tetratricopeptide repeat domain 3 0.000366897
225206_P _s_at MTRF1L mitochondrial translational release factor 1- 0.000367409 like
201336_PM_at VA P3 vesicle-associated membrane protein 3 0.000371211
(cellubrevin)
215121_PM_x_at IGLC7 /// IGLV1-44 /// immunoglobulin lambda constant 7 /// 0.000374949
LOC100290481 immunoglobulin lambda variable 1-44 ///
immunoglob
210996_PM_s_at YWHAE tyrosine 3-monooxygenase/tryptophan 5- 0.000377721 monooxygenase activation protein, epsilon
polypep
220590_PM_at ITFG2 integrin alpha FG-GAP repeat containing 2 0.000378104
1554745_PM_at RALGPS1 Ral GEF with PH domain and SH3 binding 0.000379212 motif 1
239833_PM_at EST239833_PM_at — 0.000379421
1553107_PM_s_at C5orf24 chromosome 5 open reading frame 24 0.000381869
216843_P _x_at LOC441259 /// PMS2L2 P S2 postmeiotic segregation increased 2 (S. 0.000384462
/// PMS2P1 /// cerevisiae)-like /// postmeiotic segregati
PMS2P5 /// PMS2P6
202262_PM_x_at DDAH2 dimethyiarginine dimethylaminohydrolase 2 0.000385193
236428_PM_at EST236428^PM_at — 0.000385729
230648_PM_at LOC283663 hypothetical LOC283663 0.000386276
243745_PM_at EST243745_P _at — 0.000392422
212827_PM_at IGHM immunoglobulin heavy constant mu 0.000397367
212547_PM_at BRD3 bromodomain containing 3 0.000397485
214901_PM_at ZNF8 zinc finger protein 8 0.000397826
233031_PM_at ZEB2 zinc finger E-box binding homeobox 2 0.000401666
206370_PM_at PIK3CG phosphoinositide-3-kinase, catalytic, gamma 0.000403616 polypeptide
243005_PM_at EST243005_PM_at — 0.000404995
204562_PM_at IRF4 interferon regulatory factor 4 0.000405376
AFFX-r2-Pl-cre-5_at ESTAFFX-r2-Pl-cre-5_at — 0.000692881
1553313_PM_s_at SLC5A3 solute carrier family 5 (sodium/myo-inositol 0.000406242 cotransporter), member 3
239645_PM_at EST239645_PM_at — 0.00040727
35160_PM_at LDB1 LIM domain binding 1 0.000410024
225920_PM_at LOC148413 hypothetical LOC148413 0.000410869
205611_PM_at TNFSF12 tumor necrosis factor (ligand) superfamily, 0.000410968 member 12
227055_PM_at METTL7B methyltransferase like 7B 0.000413609
216308_PM_x_at GRHPR glyoxylate reductase/hydroxypyruvate 0.000414211 reductase
222858_PM_s_at DAPP1 dual adaptor of phosphotyrosine and 3- 0.000415151 phosphoinositides 1565162_PM_s_at GST1 microsomal glutathione s-transferase 1 0.000421907
221602_PM_s_at FAIM3 Fas apoptotic inhibitory molecule 3 0.000427899
221671_P _x_at IGK@ /// IGKC immunoglobulin kappa locus /// 0.000428838 immunoglobulin kappa constant
215176_P _x_at IGK@ /// IGKC immunoglobulin kappa locus /// 0.000431177 immunoglobulin kappa constant
239001_PM_at MGST1 Microsomal glutathione S-transferase 1 0.000438289
232095_PM_at EST232095_PM_at — 0.00044223
1557780_PM_at EST1557780_PM_at — 0.000447614
221586_P _s_at E2F5 E2F transcription factor 5, pl30-binding 0.000451682
215359_PM_x_at ZNF44 zinc finger protein 44 0.000459167
205863_PM_at S100A12 S100 calcium binding protein A12 0.000462242
209226_P _s_at TNPOl transportin 1 0.000464987
21S338_PM_s_at NKTR natural killer-tumor recognition sequence 0.000468526
201674_PM_s_at A AP1 A kinase (PRKA) anchor protein 1 0.0004691
216591_PM_s_at SDHC succinate dehydrogenase complex, subunit C, 0.000471684 integral membrane protein, 15kDa
1555779_P _a_at CD79A CD79a molecule, immunoglobulin-associated 0.000473019 alpha
207983_PM_s_at STAG 2 stromal antigen 2 0.00047413
1554696_PM_s_at TYMS thymidylate synthetase 0.000477028
226286_PM_at ELMOD3 ELMO/CED-12 domain containing 3 0.000481236
213986_PM_s_at C19orf6 chromosome 19 open reading frame 6 0.000485839
222343_PM_at BCL2L11 BCL2-like 11 (apoptosis facilitator) 0.000486282
218078_PM_s_at ZDHHC3 zinc finger, DHHC-type containing 3 0.000490729
223488_PM_s_at GNB4 guanine nucleotide binding protein (G 0.000490757 protein), beta polypeptide 4
206034_P _at SERPINB8 serpin peptidase inhibitor, clade B 0.000490816
(ovalbumin), member 8
243771_P _at EST243771_PM_at — 0.000491776
2448Q4_P _at SQST l sequestosome 1 0.000491966
215012_PM_at ZNF451 zinc finger protein 451 0.000492264
225447_P _at GPD2 glycerol-3-phosphate dehydrogenase 2 0.000494271
(mitochondrial)
239651_PM_at ANAPC5 anaphase promoting complex subunit 5 0.000497135
222728_PM_s_at TAF1D TATA box binding protein (TBP)-associated 0.000499059 factor, RNA polymerase 1, D, 41kDa
1563253_PM_s_at ERBB3 v-erb-b2 erythroblastic leukemia viral 0.000499088 oncogene homolog 3 (avian)
224969_PM_at ATXN7L3 ataxin 7-like 3 0.000501076
235984_P _at EST235984_PM_at — 0.000504457
231939_PM_s_at BDP1 B double prime 1, subunit of RNA polymerase 0.000505035
III transcription initiation factor IIIB
219420_PM_s_at Clorfl63 chromosome 1 open reading frame 163 0.000505672
212804_PM_s_at GAPVD1 GTPase activating protein and VPS9 domains 1 0.000505681
243434_PM_at EST243434_P _at — 0.000506264
201291_PM_s_at TOP2A topoisomerase (DNA) II alpha 170kDa 0.000507872
209138_PM_x_at IGL@ Immunoglobulin lambda locus 0.000508704 1559263_PM_s_at PPIL4 /// ZC3H12D peptidylprolyl isomerase (cyclophiiin)-like 4 0.000511201
/// zinc finger CCCH-type containing 12D
212994_PM_at THOC2 THO complex 2 0.000512681
209013_PM_x_at TRIO triple functional domain (PTPRF interacting) 0.000514112
208936_PM_x_at LGALS8 lectin, galactoside-binding, soluble, 8 0.000514485
215357_PM_s_at POLDIP3 polymerase (DNA-directed), delta interacting 0.000516138 protein 3
204970_PM_s_at MAFG v-maf musculoaponeurotic fibrosarcoma 0.00051907 oncogene homolog G (avian)
239780_P _at EST239780_PM_at — 0.000519847
213648_PM_at EX0SC7 exosome component 7 0.000522394
238365_PM_s_at Clorf228 chromosome 1 open reading frame 228 0.000524946
238627_P _at TRAPPC2L trafficking protein particle complex 2-like 0.000531608
224563_P _at WASF2 WAS protein family, member 2 0.000531756
211310_PM_at EZH1 enhancer of zeste homolog 1 (Drosophila) 0.000535033
219497_PM_s_at BCL11A B-cell CLL/lymphoma 11A (zinc finger protein) 0.000536239
242115_PM_at EST242115_PM_at — 0.000536939
239486_P _at EST239486_PM_at — 0.000538967
227057_PM_at ARHGAP27 Rho GTPase activating protein 27 0.000558167
243490_PM_at EST243490_P _at — 0.000559582
208752_PM_x_at NAP1L1 nucleosome assembly protein 1-like 1 0.000559875
1554822_PM_at PHTF2 putative homeodomain transcription factor 2 0.000562813
33148_PM_at ZFR zinc finger RNA binding protein 0.000563495
226384_PM_at PPAPDC1B phosphatidic acid phosphatase type 2 domain 0.000567195 containing IB
222158_PM_s_at PPPDE1 PPPDE peptidase domain containing 1 0.000568969
AFFX-r2-Bs-dap-3_at ESTAFFX-r2-Bs-dap- — 0.00D56963
3 at
242916_P _at CEP110 centrosomal protein HOkDa 0.000570647
224877_PM_s_at MRPS5 mitochondrial ribosomal protein S5 0.000570714
23S728_P _at ZFP3 zinc finger protein 3 homolog (mouse) 0.000574739
233089_PM_at QRSL1 glutaminyl-tRNA synthase (glutamine- 0.000574905 hydrolyzing)-like 1
238602_P _at DIS3L2 DIS3 mitotic control homolog (S. cerevisiae)- 0.000575483
Iike 2
207131_PM_x_at GGT1 gamma-glutamyltransferase 1 0.000581613
215942_P _s_at GTS El G-2 and S-phase expressed 1 0.000584379
203485_PM_at RTN1 reticulon 1 0.000586494
1562364_PM_at GVIN1 GTPase, very large interferon inducible 1 0.000587505
224733_PM_at C T 3 CKLF-like MARVEL transmembrane domain 0.000589647 containing 3
217898_PM_at C15orf24 chromosome 15 open reading frame 24 0.00059102
201401_PM_s_at ADRBK1 adrenergic, beta, receptor kinase 1 0.000595924
240174_P _at EST240174_PM_at — 0.000598439
200623_PM_s_at CALM3 calmodulin 3 (phosphorylase kinase, delta) 0.000601157
206562_PM_s_at CSNK1A1 casein kinase 1, alpha 1 0.000602948
215495_P _s_at SAMD4A sterile alpha motif domain containing 4A 0.000606 32202
1554453_PM_at HNRPLL heterogeneous nuclear ribonucleoprotein L- 0.000778138 like
1554516_P _at LOC100288109 /// Hypothetical protein LOC100288109 /// 0.000779538
LOC203274 Hypothetical protein LOC203274
233745_P _at EST233745_PM_at — 0.000780591
230370_P _x_at STYXL1 serine/threonine/tyrosine interacting-like 1 0.000781146
211611_PM_s_at ATF6B /// TNXB activating transcription factor 6 beta /// 0.000784184 tenascin XB
206114_PM_at EPHA4 EPH receptor A4 0.00078538
225880_PM_at T0R1AIP2 torsin A interacting protein 2 0.000786899
217198_PM_x_at IGHA2 /// IGHD /// immunoglobulin heavy constant alpha 2 (A2m 0.000788023
IGHG1 /// marker) /// immunoglobulin heavy constant
LOC100126583 /// de
LOC100510361
215379_PM_x_at IGLC7 /// IGLV1-44 immunoglobulin lambda constant 7 /// 0.000796455 immunoglobulin lambda variable 1-44
208757_PM_at T ED9 transmembrane emp24 protein transport 0.000796492 domain containing 9
212979_PM_s_at FAM115A family with sequence similarity 115, member 0.000796767
A
213450__P _s_at ICOSLG inducible T-cell co-stimulator ligand 0.000801819
244429_PM_at EST244429_P _at — 0.000801949
211453_PM_s_at A T2 v-akt murine thymoma viral oncogene 0.00080311 homolog 2
211352_PM_s_at NCOA3 nuclear receptor coactivator 3 0.000805416
239450_PM_at EST239450_PM_at — 0.000808718
226679_PM_at SLC26A11 solute carrier family 26, member 11 0.000810101
209567_PM_at RRSl RRSl ribosome biogenesis regulator homolog 0.000810395
(S. cerevisiae)
244498_PM_x_at LOC100505679 hypothetical protein LOC100S05679 0.0008122
205731_P _s_at NCOA2 nuclear receptor coactivator 2 0.000813451
212421_PM_at C22orf9 chromosome 22 open reading frame 9 0.000819733
1568702_PM_a_at PAAF1 proteasomal ATPase-associated factor 1 0.000820736
226160_PM_at H6PD hexose-6-phosphate dehydrogenase (glucose 0.000829239
--dehydrogenase)
227882_PM_at FKRP fukutin related protein 0.000831453
211275_P _s_at GYG1 glycogenin 1 0.000837756
240392_PM_at EST240392_PM_at — 0.000837778
214615_PM_at P2RY10 purinergic receptor P2Y, G-protein coupled, 0.000839839
10
219933_PM_at GLRX2 glutaredoxin 2 0.000844012
210264_PM_at GPR35 G protein-coupled receptor 35 0.000844817
236250_P _at AFG3L1P AFG3 ATPase family gene 3-like 1 (S. 0.000853458 cerevisiae), pseudogene
201690_PM_s_at TPD52 tumor protein D52 0.000856129
230434_PM_at PHOSPH02 phosphatase, orphan 2 0.000856483
205267_P _at POU2AF1 POU class 2 associating factor 1 0.000857053
223234_PM_at MAD2L2 MAD2 mitotic arrest deficient-like 2 (yeast) 0.000860917
201259_P _s_at SYPL1 synaptophysin-like 1 0.000861326
222387_PM_s_at VPS35 vacuolar protein sorting 35 homolog (S. 0.000862194 015032202
39318_P _at TCL1A T-cell leukemia/lymphoma 1A 0.0010181
222292_P _at CD40 CD40 molecule, TNF receptor superfamily 0.00102743 member 5
217398_PM_x_at GAPDH glyceraldehyde-3-phosphate dehydrogenase 0.00102797
228599_PM_at S4A1 membrane-spanning 4-domains, subfamily A, 0.00103001 member 1
240861_P _at EST240861_PM_at — 0.00103147
202065_P _s_at PPFIA1 protein tyrosine phosphatase, receptor type, f 0.0010369 polypeptide (PTPRF), interacting protein
234488_PM_s_at GMCL1 /// GMCL1L germ cell-less homolog 1 (Drosophila) /// 0.00104025 germ cell-less homolog 1 (Drosophila)-like
233375_PM_at EFCAB2 EF-hand calcium binding domain 2 0.00104248
1560724_PM_at EST1560724_PM_at — 0.00104357
209006_P _s_at Clorf63 chromosome 1 open reading frame 63 0.00104379
214992_PM_s_at DNASE2 deoxyribonuclease II, lysosomal 0.00104413
218391_PM_at SNF8 SNF8, ESCRT-II complex subunit, homolog (S. 0.00104546 cerevisiae)
242288_PM_s_at E ILIN2 elastin microfibril interfacer 2 0.00104673
239926_PM_at EST239926_P _at — 0.00105049
243699_PM_at LOC100507006 hypothetical LOC100507006 0.00105279
202016_P _at MEST mesoderm specific transcript homolog 0.00105615
(mouse)
201211_P _s_at DDX3X DEAD (Asp-Glu-Ala-Asp) box polypeptide 3, X- 0.00105627 linked
238130_PM_at NFATC2IP nuclear factor of activated T-cells, 0.00105997 cytoplasmic, calcineurin-dependent 2
interacting p
217378_P _x_at EST217378_PM_x_at — 0.00106017
200868_PM_s_at RNF114 ring finger protein 114 0.00106168
209699_P _x_at A 1C2 aldo-keto reductase family 1, member C2 0.00106498
(dihydrodiol dehydrogenase 2; bile acid
binding
225052_PM_at TMEM203 transmembrane protein 203 0.00106532
237464_PM_at EST237464_PM_at — 0.00106804
201944_PM_at HEXB hexosaminidase B (beta polypeptide) 0.00107107
234764_PM_x_at IGLV1-36 immunoglobulin lambda variable 1-36 0.00107144
223393_PM_s_at TSHZ3 teashirt zinc finger homeobox 3 0.00107465
240652_PM_at EST240652_PM_at — 0.00108224
231672_PM_at EST231672J> _at — 0.00108448
230486_PM_at EST230486_PM_at — 0.00108996
212967_P _x_at NAP1L1 nucleosome assembly protein 1-like 1 0.00109982
220068_PM_at VPREB3 pre-B lymphocyte 3 0.0011043
228250_PM_at FNIP1 folliculin interacting protein 1 0.00111525
222388_PM_s_at VPS35 vacuolar protein sorting 35 homolog (S. 0.00111739 cerevisiae)
241885_P _at EST241885_PM_at — 0.00111828
229852_P _at NMNAT1 nicotinamide nucleotide adenylyltransferase 1 0.0011245
232906_P _at EST232906_PM_at — 0.00112623
213082_PM_s_at SLC35D2 solute carrier family 35, member D2 0.00112801 1569189_PM_at TTC9C tetratricopeptide repeat domain 9C 0.00113081
200709_PM_at F BP1A F 506 binding protein 1A, 12kDa 0.00113213
238860_PM_at C6orfl30 chromosome 6 open reading frame 130 0.00113294
218149_PM_s_at ZNF395 zinc finger protein 395 0.00113365
226663_PM_at AN RD10 ankyrin repeat domain 10 0.00113647
221837_PM_at KLHL22 kelch-like 22 (Drosophila) 0.00113942
222193_PM_at C2orf43 chromosome 2 open reading frame 43 0.00114481
201698_PM_s_at SRSF9 serine/arginine-rich splicing factor 9 0.00115792
209042_P _s_at UBE2G2 ubiquitin-conjugating enzyme E2G 2 (UBC7 0.00115961 homolog, yeast)
235231_P _at ZNF789 zinc finger protein 789 0.00116259
236799_P _at EST236799_PM_at — 0.00116393
235409_PM_at MGA MAX gene associated 0.00116667
201456_PM_s_at BUB3 budding uninhibited by benzimidazoles 3 0.00116683 homolog (yeast)
226825_P _s_at T E 165 transmembrane protein 165 0.00117042
1556462_P _a_at EST1556462_PM_a_at — 0.00117146
243667_PM_at EST243667_PM_at — 0.00117303
1566824_PM_at EST1566824_PM_at — 0.00117375
217078_PM_s_at CD300A CD300a molecule 0.00117516
208610_PM_s_at SRRM2 serine/arginine repetitive matrix 2 0.00117811
215954__PM_s_at C19orf29 chromosome 19 open reading frame 29 0.00117964
219443_PM_at TASP1 taspase, threonine aspartase, 1 0.00118869
207188_PM_at CD 3 cyclin-dependent kinase 3 0.00119927
235526_PM_at SOX6 SRY (sex determining region Y)-box 6 0.00119931
217927_PM_at SPCS1 signal peptidase complex subunit 1 homolog 0.00120191
(S. cerevisiae)
203096_PM_s_at RAPGEF2 Rap guanine nucleotide exchange factor (GEF) 0.00120412
2
243968_PM_x_at FCRL1 Fc receptor-like 1 0.00120435
235469_PM_at FA 133B /// family with sequence similarity 133, member 0.00120671
LOC728066 B /// family with sequence similarity 133,
205297_PM_s_at CD79B CD79b molecule, immunoglobulin-associated 0.00121583 beta
212177_PM_at SFRS18 splicing factor, arginine/serine-rich 18 0.00122218
203554_PM_x_at PTTG1 pituitary tumor-transforming 1 0.00122388
230533_P _at Z YND8 zinc finger, MYND-type containing 8 0.00122749
223161_P _at KIAA1147 KIAA1147 0.00122827
208652_PM_at PPP2CA protein phosphatase 2, catalytic subunit, 0.0012327 alpha isozyme
235577_PM_at ZNF652 zinc finger protein 652 0.00123352
203222_PM_s_at TLE1 transducin-like enhancer of split 1 (E(spl) 0.001235 homolog, Drosophila)
202871_P _at TRAF4 TNF receptor-associated factor 4 0.00123923
223887_P _at GPR132 G protein-coupled receptor 132 0.00123983
244015_PM_at EST244015_PM_at — 0.00124998
1558438_PM_a_at IGHA1 Immunoglobulin heavy constant alpha 1 0.00125035 202696_PM_at OXSR1 oxidative-stress responsive 1 0.00125038
228083_PM_at CACNA2D4 calcium channel, voltage-dependent, alpha 0.00125662
2/delta subunit 4
242712_PM_x_at RANBP2 /// RGPD1 /// RAN binding protein 2 /// RANBP2-like and 0.00126544
RGPD2 /// RGPD3 /// GRIP domain containing 1 /// RANBP2-like
RGPD4 /// RGP05 /// and
RGPD6 /// RGPD8
221850_PM_x_at AGAP4 /// AGAP6 /// ArfGAP with GTPase domain, ankyrin repeat 0.00126719
AGAP7 /// AGAP8 and PH domain 4 /// ArfGAP with GTPase
domain
236700_P _at EIF3C eukaryotic translation initiation factor 3, 0.00126801 subunit C
208466_PM_at RAB3D RAB3D, member RAS oncogene family 0.00127517
243492_PM_at THEM4 thioesterase superfamily member 4 0.0012775
213448_PM_at EST213448_PM_at 0.00128088
222800_PM_at TRNAU 1AP tRNA seienocysteine 1 associated protein 1 0.00128375
232236_P _at EST232236_PM_at 0.00129017
213891_PM_s_at TCF4 transcription factor 4 0.00129164
202166_PM_s_at PPP1R2 protein phosphatase 1, regulatory (inhibitor) 0.00129303 subunit 2
228273_PM_at PRR11 proline rich 11 0.00129725
206896_P _s_at GNG7 guanine nucleotide binding protein (G 0.00129953 protein), gamma 7
227616_PM_at BCL9L B-cell CLL/lymphoma 9-like 0.00130003
237778_P _at EST237778_P _at 0.00130027
235662_PM_at EST235662_PM_at 0.00130307
1554670_PM_at GGA1 golgi-associated, gamma adaptin ear 0.00130507 containing, ARF binding protein 1
236621_PM_at RPS27 ribosomal protein S27 0.00130665
2l4052_PM_x_at BAT2L2 HLA-B associated transcript 2-like 2 0.00130805
2l9382_PM_at SERTAD3 SERTA domain containing 3 0.00131171
211645_PM_x_at EST211645_PM_x_at 0.00131608
242261_PM_at EST242261_P _at 0.00131609
201896_PM_s_at PSRC1 proline/serine-rich coiled-coil 1 0.00132007
202589_P _at TYMS thymidylate synthetase 0.00132608
225602_P _at GUPR2 GLI pathogenesis-related 2 0.0013347
239760_P _at EST239760_PM_at 0.00133591
230O00_P _at RNF213 ring finger protein 213 0.00133665
238485_PM_at EST238485_P _at 0.00133773
1569320_PM_at GPBP1L1 GC-rich promoter binding protein 1-like 1 0.00134606
224766_P _at LOC100506548 /// hypothetical LOC100506548 /// ribosomal 0.0013474
RPL37 protein L37
227062_P _at EST227062_P _at 0.00134993
243919_PM_at EST243919_PM_at 0.00135277
202942_PM_at ETFB electron-transfer-flavoprotein, beta 0.00135862 polypeptide
239266_Plvl_at EST239266_P _at 0.00135979
225259_PM_at RAB6B RAB6B, member RAS oncogene family 0.00136 239764_PM_at EST239764_PM_at — 0.00137061
234767_P _at FAR1 fatty acyl CoA reductase 1 8.02E-0S
Table 15. Blood Microarray Signatures for subAR using a 3-Way 1 -Step approach (AR vs. subAR vs. TX): best performing gene si nature (61 enes)
subunit
225509_PM_at SAP30L SAP30-like
226975_PM_at RNPC3 RNA-binding region (RNP1, RR ) containing 3
227410_PM_at FAM43A family with sequence similarity 43, member A
228476_P _at KIAA1407 KIAA1407
229243_P _at RP11-111 22.4 —
230505_P _at LOC145474 uncharacterized LOC145474
232031_PM_s_at EPG5 ectopic P-granules autophagy protein 5 homolog (C. elegans)
232284_PM_at PSMD6-AS2 PSMD6 antisense RNA 2
236168_PM_at EST3 —
236404_PM_at EST4 —
236883_PM_at ESTS —
237176_P _at EST6 —
237544_PM_at CTD-2165H16.3 —
238317_PM_x_at EST7 —
239227_PM_at EST8 —
239404_PM_at EST9 —
239600_PM_at EST10 —
240498_PM_at EST11 —
241688_PM_at EST12 —
242060_PM_x_at PHF11 PHD finger protein 11
242352_PM_at NIPBL Nipped-B homolog (Drosophila)
242390_P _at EST13 —
242824_PM_at EST14 —
242877_PM_at EST15 —
243739_PM_at EST16 —
244233_P _at TPGS2 tubulin polyglutamylase complex subunit 2
244840_P _x_at D0CK4 dedicator of cytokinesis 4
AFFX-CreX-5_at EST17 —
AFFX-r2-Pl-cre-3_at EST18 —
AFFX-r2-Pl-cre-5_at EST19 —
Table 16. Blood Microarray analysis results for subAR using a 3-Way 1-Step approach (AR vs. subAR vs. TX)
Table 17. Blood PAXgene NGS Signatures for subAR using a 3-Way 1 -Step approach (AR vs. subAR vs. TX): full gene list ( 123 enes) at < 0.01
NM_001040440>CCDC112 CCDC112 NM_001040440 0.0015703
NM_001243878>FHL3 FHL3 NM_001243878 0.00172631
NM_001290222>NQO2 NQ02 NM_001290222 0.00181379
NR_029478>MIRLET7A3 MIRLET7A3 NR_029478 0.00183984
NM_001197234>BTN2A1 BTN2A1 NM_001197234 0.00193406
NR_002605>DLEU1 DLEU1 NR_002605 0.00195495
NR_028505>M!R22HG MIR22HG NRJD28505 0.00200373
NR_051980>MINOS1P1 MINOS1P1 NR_051980 0.00201321
NM_001244898>PTBP3 PTBP3 NM_001244898 0.00217963
NM_152889>CHST13 CH5T13 N _152889 0.00224819
NM_001277224>TAGLN2 TAGL 2 NM_001277224 0.00229155
NR_037937>SCNM1 SCNM1 NRJB7937 0.00233534
NM_138730>HMGN3 HMGN3 NM_138730 0.00235072
NM_148962>0XER1 OXER1 NM_148962 0.00240808
NM_002729>HHEX HHEX NM_002729 0.00254469
NR_040030>CFLAR-AS1 CFIAR-ASI NR_040030 0.00289549
NR_110146>VNN2 VNN2 NR_110146 0.00294559
NM_018993>RIN2 RIN2 NM_018993 0.00302295
NM_002514>NOV NOV NM_002514 0.00304015
NM_173527>REM2 REM2 NM_173527 0.00356599
NR_103549>LUCAT1 LUCAT1 NR_103549 0.00379271
NR_036503>PRKCQ-AS1 PR CQ-AS1 NR_036503 0.00382665
NM_001666>ARHGAP4 ARHGAP4 NM_001666 0.00392569
NM_001164741>ARHGAP4 ARHGAP4 NM_001164741 0.00392606
NR_120600>PRMT5-AS1 PRMT5-AS1 NR_120600 0.00399138
NM_001012959>DISC1 DISCI NM_001012959 0.00412158
NM_003104>SORD SORD NM_003104 0.00440187
NM_005461>MAFB MAFB NM_005461 0.00461273
NM_207354>AN RD13D ANKRD13D NM_207354 0.00462185
NM_017723>TOR4A TOR4A NM_017723 0.00473781
NM_001567>INPPL1 INPPL1 NM_001567 0.00513417
NM_002068>GNA15 GNA15 NM_002068 0.00516178
N _006480>RGS14 RGS14 NM_006480 0.00528027
NR_003042>SNORD45C SNORD45C NR_003042 0.00533478
NM_014098>PRDX3 PRDX3 NM_014098 0.00534763
NM_153690>FAM43A FA 43A NM_153690 0.0053505
NM_001127586>ING4 ING4 NM_001127586 0.00547331
NM_017628>TET2 TET2 NM_017628 0.00547411
N _182491>ZFAND2A ZFAND2A NM_182491 0.00559846
NM_032353>VPS25 VPS25 NM_032353 0.00564435
NM_016538>SIRT7 SIRT7 NM_016538 0.00570906
NM_001242831>ELOVL5 ELOVL5 NM_001242831 0.00579687
NR_120485>IL7R IL7R NR_120485 0.00603421 TU 2015/032202
202
Table 18. Blood PAXgene NGS for subAR using a 3-Way 1-Step approach (AR vs. subAR vs. TX): best erformin gene signature (53 genes)
NM_001243878>FHL3 FHL3 NM_001243878
NM_001290222>NQO2 NQ02 NM_001290222
NR_029478>MIRLET7A3 MIRLET7A3 NR_029478
NM_001197234>BTN2A1 BTN2A1 NM_001197234
NR_002605>DLEU1 DLEU1 NR_002605
NR_028505>MIR22HG MIR22HG NR_028505
NR_051980>MINOS1P1 MINOS1P1 NR_051980
NM_001244898>PTBP3 PTBP3 NM_001244898
NM_152889>CHST13 CHST13 NM_152889
NM_001277224>TAGLN2 TAGL 2 NM_001277224
NR_037937>SCNM1 SCNM1 NR_037937
NM_138730>HMGN3 HMGN3 NM_138730
N _148962>0XER1 OXER1 NM_148962
NM_002729>HHEX HHEX NMJD02729
NR_040030>CFLAR-AS1 CFUR-ASl NR_040030
NR_110146>VNN2 VNN2 NR_110146
NM_018993>RIN2 RIN2 NM_018993
NM_002514>NOV NOV NM_002514
NM_173527>REM2 REM2 NM_173527
NR_103549>LUCAT1 LUCAT1 NR_103549
NR_036503>PRKCQ-AS1 PRKCQ-AS1 NR_0365O3
NM_001666>ARHGAP4 ARHGAP4 NM_001666
NM_001164741>ARHGAP4 ARHGAP4 NM_001164741
NR_120600>PRMT5-AS1 PRMT5-AS1 NR_120600
NM_001012959>DISC1 DISCI NM_001012959
N _003104>SORD SORD NM_003104
NM_005461>MAFB MAFB NM_005461
NM_207354>ANKRD13D ANKRD13D NM_207354
NM_017723>TOR4A TOR4A NM_017723
Table 19. Blood PAXgene NGS analysis results for subAR using a 3-Way 1-Step approach (AR vs. subAR vs. TX)

Claims

WE CLAIM:
1. A method of detecting subclinical acute rejection (subAR) in a subject comprising:
(a) obtaining nucleic acids of interest, wherein the nucleic acids of interest comprise mRNA extracted from a sample from the subject or nucleic acids derived from the mRNA extracted from the sample from the subject;
(b) detecting expression levels in the subject of at least five genes using the nucleic acids of interest obtained in step (a); and
(c) detecting subAR in the subject from the expression levels detected in step (b).
2. The method of claim 1 , wherein the sample from the subject is a blood sample.
3. The method of claim 1 , wherein the method detects subAR with an accuracy of greater than 75% or a sensitivity of greater than 75%.
4. The method of claim 1 or 3, wherein the subject has a serum creatinine level of less than 3.0 mg/dL.
5. The method of claim 1 , wherein the at least five genes are selected from at least one of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, and 18.
6. The method of claim 1 , further comprising contacting the nucleic acids of interest with probes, wherein the probes are specific for the at least five genes selected in step (b).
7. The method of claim 1 , wherein detecting subAR comprises detecting a risk of developing subAR, detecting acute rejection (AR), detecting a risk of having acute rejection (AR),or detecting a well-functioning normal transplant (TX).
8. The method of claim 1 , wherein for each of the at least five genes, step (c) comprises comparing the expression level of the gene in the subject to one or more reference expression levels of genes associated with subAR, acute rejection (AR) or lack of transplant rejection (TX).
9. The method of claim 7, wherein step (c) further comprises for each of the at least five genes assigning the expression level of the gene in the subject a value or other designation providing an indication whether the subject has or is at risk of developing subAR, has or is at risk of having acute rejection (AR), or has a well-functioning normal transplant (TX).
10. The method of claim 1 , wherein the detecting comprises applying a two-step
classifier to the gene expression levels.
1 1 . The method of claim 10, wherein one step in the two-step classifier distinguishes between normal transplant (TX) and AR+subAR.
12. The method of claim 10, wherein one step in the two-step classifier distinguishes between AR and subAR.
13. The method of claim 8, wherein the expression level of each of the at least five genes is assigned a value on a normalized scale of values associated with a range of expression levels in kidney transplant patients with subAR, with AR, or with TX.
14. The method of claim 8, wherein the expression level of each of the at least five genes is assigned a value or other designation providing an indication that the subject has or is at risk of having subAR, has or is at risk of AR, has a well-functioning normal transplant, or that the expression level is uninformative.
15. The method of claim 8, wherein step (c) further comprises, combining the values or designations for each of the genes to provide a combined value or designation providing an indication whether the subject has or is at risk of subAR, has acute rejection (AR), or has a well-functioning normal transplant (TX).
16. The method of claim 1 , wherein the method is repeated at different times on the subject.
17. The method of claim 1 , wherein the subject is receiving a drug, and a change in the combined value or designation over time provides an indication of the effectiveness of the drug.
1 8. The method of claim 1 , wherein the subject has received a kidney transplant within 10 years of performing step (a).
19. The method of claim 1 , wherein the sample from the subject in step (a) is a blood sample or urine sample.
20. The method of claim 1 , wherein the sample is a blood sample and comprises whole blood, peripheral blood, serum, plasma, PBLs, PBMCs, T cells, CD4 T cells CD8 T cells, or macrophages.
21. The method of claim 1 , wherein step (b) is performed on at least 10, 20, 40, or 100 genes selected from at least one of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, and 1 8.
22. The method of claim 1 , further comprising changing the treatment regime of the subject responsive to the detecting step.
23. The method of claim 22, wherein the subject has received a drug before performing the methods, and the changing the treatment regime comprises administering an additional drug, administering a higher dose of the same drug, administering a lower dose of the same drug or stopping administering the same drug.
24. The method of claim 1 , further comprising performing an additional procedure to detect subAR or risk thereof if the detecting step (c) provides an indication the subject has or is at risk of subAR.
25. The method of claim 24, wherein the additional procedure is a kidney biopsy.
26. The method of claim 1 , wherein step (c) is performed by a computer.
27. A method of detecting subclinical acute rejection (subAR) in a subject having normal serum creatinine level, comprising:
(a) obtaining nucleic acids of interest, wherein the nucleic acids of interest comprise mRNA extracted from a sample from a subject or nucleic acids derived from the mRNA extracted from the sample from the subject;
(b) detecting expression levels in the subject of at least five genes using the nucleic acids of interest obtained in step (a); and
(c) detecting subAR in the subject from the expression levels detected in step (b).
28. The method of claim 27, wherein the sample is a blood sample.
29. The method of claim 27, further comprising contacting the nucleic acids of interest with probes, wherein the probes are specific for the at least five genes selected in step (b).
30. The method of claim 27, wherein for each of the at least five genes, step (c)
comprises comparing the expression level of the gene in the subject to one or more reference expression levels of the gene associated with subAR, or lack of transplant rejection (TX).
3 1. The method of claim 27, wherein step (c) further comprises for each of the at least five genes assigning the expression level of the gene in the subject a value or other designation providing an indication whether the subject has or is at risk of developing subAR.
32. The method of claim 30, wherein the expression level of each of the at least five genes is assigned a value on a normalized scale of values associated with a range of expression levels in kidney transplant patients with and without subAR.
33. The method of claim 30, wherein the expression level of each of the at least five genes is assigned a value or other designation providing an indication that the subject has or is at risk of subAR, lacks and is not at risk of subAR, or that the expression level is uninformative.
34. The method of claim 27, wherein the at least five genes are selected from at least one of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, and 18
35. The method of claim 27, wherein step (c) further comprises, combining the values or designations for each of the genes to provide a combined value or designation providing an indication whether the subject has or is at risk of subAR.
36. The method of claim 27, wherein the method is repeated at different times on the subject.
37. The method of claim 27, wherein the subject is receiving a drug, and a change in the combined value or designation over time provides an indication of the effectiveness of the drug.
38. The method of claim 27, wherein the subject has undergone a kidney transplant within 1 month, 3 months, 1 year, 2 years, 3 years or 5 years of performing step (a).
39. The method of claim 27, wherein the sample from the subject in step (a) is a blood sample or urine sample.
40. The method of claim 28, wherein the blood sample comprises whole blood,
peripheral blood, serum, plasma, PBLs, PBMCs, T cells, CD4 T cells CD8 T cells, or macrophages.
41 . The method of claim 27, wherein step (b) is performed on at least 10, 20, 40, or 100 or more genes selected from at least one of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 1 5, 17, and 18.
42. The method of claim 27, further comprising changing the treatment regime of the patient responsive to the detecting step.
43. The method of claim 27, wherein the subject has received a drug before performing the methods, and the changing the treatment regime comprises administering an additional drug, administering a higher dose of the same drug, administering a lower dose of the same drug or stopping administering the same drug.
44. The method of claim 27, further comprising performing an additional procedure to detect subAR or risk thereof if the determining step provides an indication the subject has or is at risk of subAR.
45. The method of claim 44, wherein the additional procedure is a kidney biopsy.
46. The method of claim 27, wherein step (c) is performed by a computer.
47. The method of claim 27, wherein the method detects subAR with an accuracy of greater than 75% or a sensitivity of greater than 75%.
48. An array, comprising a support or supports bearing a plurality of nucleic acid probes complementary to a plurality of mRNAs fewer than 5000 in number, wherein the plurality of mRNAs includes mRNAs expressed by at least five genes specifically selected from at least one of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, and 18.
49. The array of claim 48, wherein the plurality of mRNAs are fewer than 1000 or fewer than 100 in number.
50. The array of claim 48, wherein the plurality of nucleic acid probes are attached to a planar support or to beads.
51 . An array, comprising a support or supports bearing a plurality of ligands that
specifically bind to a plurality of proteins fewer than 5000 in number, wherein the plurality of proteins includes at least five proteins encoded by genes specifically selected from at least one of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, and 18.
52. The array of claim 51 , wherein the plurality of proteins are fewer than 1000 or fewer than 100 in number.
53. The array of claim 51 , wherein the plurality of ligands are attached to a planar
support or to beads.
54. The array of claim 51 , wherein the at least five proteins are encoded by genes
selected from at least one ofTables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, and 1 8.
55. The array of claim 51 , wherein the ligands are different antibodies, wherein the
different antibodies bind to different proteins of the plurality of proteins.
56. A method of expression analysis, comprising determining expression levels of up to 2,000 genes in a sample from a subject having a kidney transplant, wherein the genes include at least five genes selected from at least one of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 15, 17, and 18.
57. The method of claim 56, wherein the expression levels of up to 100 or 1000 genes are determined.
58. The method of claim 56, wherein the expression levels are determined at the mRNA level or at the protein level.
59. The method of claim 56, wherein the expression levels are determined by
quantitative PCR, hybridization to an array or sequencing.
60. A method of screening a compound for activity in inhibiting or treating subAR, comprising:
(a) administering the compound to a subject having or at risk of subAR;
(b) determining, before and after administering the compound to the subject, expression levels of at least five genes in the subject selected from at least one of Tables 2, 3, 4, 7, 8, 1 1 , 12, 14, 1 , 17, and 1 8, and species variants thereof; and
(c) determining whether the compound has activity in inhibiting or treating subAR from a change in expression levels of the genes after administering the compound.
61 . The method of claim 60, wherein step (c) comprises, for each of the at least five changes, assigning a value or designation depending on whether the change in the expression level of the gene relative to one or more reference levels indicating presence or absence of subAR.
62. The method of claim 60, further comprising determining a combined value or
designation for the at least five genes from the values or designations determined for each gene.
63. The method of claim 60, wherein the subject is human or a nonhuman animal model of subAR.
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