US20080076134A1 - Gene and protein expression profiles associated with the therapeutic efficacy of irinotecan - Google Patents

Gene and protein expression profiles associated with the therapeutic efficacy of irinotecan Download PDF

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US20080076134A1
US20080076134A1 US11/903,470 US90347007A US2008076134A1 US 20080076134 A1 US20080076134 A1 US 20080076134A1 US 90347007 A US90347007 A US 90347007A US 2008076134 A1 US2008076134 A1 US 2008076134A1
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genes
irinotecan
gene
patients
protein
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Patrick Muraca
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Nuclea Biomarkers LLC
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Publication of US20080076134A1 publication Critical patent/US20080076134A1/en
Priority to US12/284,387 priority patent/US7763438B2/en
Priority to US12/487,061 priority patent/US8580926B2/en
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
    • G01N33/6803—General methods of protein analysis not limited to specific proteins or families of proteins
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING 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
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING 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
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/106—Pharmacogenomics, i.e. genetic variability in individual responses to drugs and drug metabolism
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING 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
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/158—Expression markers
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/52—Predicting or monitoring the response to treatment, e.g. for selection of therapy based on assay results in personalised medicine; Prognosis

Definitions

  • Ineffective treatment also is problematic because time is a key variable when treating cancer.
  • a treatment provider has a far greater chance of containing and managing the disease if the cancer is diagnosed at an early stage and treated with a therapeutically effective agent.
  • An agent may provide great therapeutic benefits if administered at an early stage of the disease; however, with the passage of time, the same agent may cease to be effective.
  • Colorectal cancer is an example of a condition where early diagnosis is key for effective treatment.
  • Colorectal cancer is cancer that develops in the colon or the rectum.
  • the walls of the colon and rectum have several layers of tissue.
  • Colorectal cancer often starts in the innermost layer and can grow through some or all of the other layers; the stage (extent of spread) of a colorectal cancer depends to a great degree on how deeply it has grown into these layers.
  • Irinotecan hydrochloride is a chemotherapeutic agent indicated for first-line therapy of colorectal cancers.
  • administration of irinotecan hydrochloride (“irinotecan”) often causes deleterious side effects for the patient, and some patients do not respond well to the treatment.
  • Some patients thus undergo treatment with irinotecan and suffer the painful side effects only to later realize that the agent has not been therapeutically beneficial to their condition. In addition to the unnecessary suffering, critical time is lost in determining an alternative treatment.
  • the present invention provides gene and protein expression profiles and methods of using them to identify those patients who are likely to respond to treatment with irinotecan (these patients are referred to as “responders”), as well as those patients who are not likely to benefit from such treatment (these patients are referred to as “non-responders”).
  • the present invention allows a treatment provider to identify those patients who are responders to irinotecan treatment, and those who are not non-responders to such treatment, prior to administration of the agent.
  • the present invention comprises gene expression profiles, also referred to as “gene signatures,” that are indicative of a cancer patient's tendency to respond to treatment with irinotecan.
  • the gene expression profile comprises at least one, and preferably a plurality, of genes selected from the group consisting of ERBB2, GRB7, Erk1 kinase, JNK1 kinase, BCL2, phospho-GSK-3beta, MMP11, CTSL2, CCNB1, BIRC5, MK167, STK6, MRP14, phospho-Akt, CD68, BAG1 and GSTM1.
  • the gene signature may further include reference or control genes.
  • the currently preferred reference genes are ACTB, GAPD, GUSB, RPLP0 and TFRC. According to the invention, some or all of theses genes are differentially expressed (e.g., up-regulated or down-regulated) in patients who are responders to irinotecan therapy. Specifically, ERBB2, GRB7, JNK1 kinase, BCL2, MK167, phospho-Akt, CD68 and BAG1 are up-regulated (over-expressed) and Erk1 kinase, phospho-GSK-3beta, MMP11, CTSL2, CCNB1, BIRC5, STK6, MRP14 and GSTM1 are down-regulated (under-expressed) in patients who are responders to irinotecan. Reference genes ACTB, GAPD, GUSB, RPLP0 and TFRC are up-regulated (over-expressed).
  • the present invention further comprises protein expression profiles that are indicative of a cancer patient's tendency to respond to treatment with irinotecan.
  • the protein expression profiles comprise those proteins encoded by the genes of the GEP that also are differentially expressed in colon cancers that are responsive to irinotecan therapy.
  • the present protein expression profile comprises at least one, and preferably a plurality, of proteins encoded by the genes selected from the group consisting of ERBB2, GRB7, Erk1 kinase, JNK1 kinase, BCL2, phospho-GSK-3beta, MMP11, CTSL2, CCNB1, BIRC5, MK167, STK6, MRP14, phospho-Akt, CD68, BAG1 and GSTM1.
  • the protein expression profile may further include proteins encoded by reference genes.
  • the currently preferred reference genes are ACTB, GAPD, GUSB, RPLP0 and TFRC. According to the invention, some or all of theses proteins are differentially expressed (e.g., up-regulated or down-regulated) in patients who are responders to irinotecan therapy.
  • proteins encoded by the following genes are up-regulated (over-expressed): ERBB2, GRB7, JNK1 kinase, BCL2, MK167, phospho-Akt, CD68 and BAG1; and proteins encoded by the following genes are down-regulated (under expressed): Erk1 kinase, phospho-GSK-3beta, MMP11, CTSL2, CCNB1, BIRC5, STK6, MRP14 and GSTM1, in patients who are responders to irinotecan.
  • Reference proteins ACTB, GAPD, GUSB, RPLP0 and TFRC are up-regulated (over-expressed).
  • the gene and protein expression profiles of the present invention comprise a group of genes and proteins that are differentially expressed (e.g., up-regulated or down-regulated) in patients who are responders to irinotecan therapy relative to expression of the same genes in patients who are non-responders to this therapy.
  • Patients having tumors that are non-responsive to irinotecan often experience recurrence of their disease or disease-related death.
  • the GPEPs of the present invention thus can be used to predict not only responsiveness of a colon cancer to irinotecan therapy, but also the likelihood of recurrence of the cancer and/or disease-related death.
  • the present invention further comprises a method of determining if a patient is a responder or non-responder to treatment with irinotecan.
  • the method comprises obtaining a tumor sample from the patient, determining the gene and/or protein expression profile of the sample, and determining from the gene or protein expression profile whether at least one, preferably at least 4, more preferably at least 10, and most preferably at least 16 of the genes selected from the group consisting of ERBB2, GRB7, Erk 1 kinase, JNK1 kinase, BCL2, phospho-GSK-3beta, MMP11, CTSL2, CCNB1, BIRC5, MK167, STK6, MRP14, phospho-Akt, CD68, BAG1 and GSTM1, or at least one protein selected from the proteins encoded by these genes, is differentially expressed in the sample. From this information, the treatment provider can ascertain whether the patient is likely to benefit from irinotecan therapy.
  • the present method also can be used to predict late recurrence
  • the present invention further comprises assays for determining the gene and/or protein expression profile in a patient's sample, and instructions for using the assay.
  • the assay may be based on detection of nucleic acids (e.g., using nucleic acid probes specific for the nucleic acids of interest) or proteins or peptides (e.g., using antibodies specific for the proteins/peptides of interest).
  • the assay comprises an immunohistochemistry (IHC) test in which tissue samples, preferably arrayed in a tissue microarray (TMA), and are contacted with antibodies specific for the proteins/peptides identified in the GPEP as being indicative of a patient's responsiveness to irinotecan.
  • IHC immunohistochemistry
  • FIG. 1 is a graph showing the survival rates for patients treated with irinotecan HCl correlated with the present gene expression profile predicting responsiveness to irinotecan therapy.
  • the present invention provides gene and protein expression profiles and their use for predicting a patient's responsiveness to a cancer treatment. More specifically, the present GPEPs are indicative of whether a patient is a responder or a non-responder to treatment with irinotecan. Those patients identified as responders using the present GPEP are likely to benefit from irinotecan therapy, whereas those patients identified as non-responders may avoid unnecessary treatment with irinotecan and consider other treatment options in a timely manner. The present GPEPs also can be used to predict the likelihood of recurrence of colon cancer and disease related death associated with irinotecan therapy in some patients.
  • Irinotecan is a chemotherapeutic agent which belongs to the group of medicines called antineoplastics. It is indicated as first-line therapy for treating cancers of the colon or rectum. Irinotecan interferes with the growth of cancer cells, which are eventually destroyed. Because the growth of normal cells may also be affected by the medicine, other effects also may occur. These other effects may include: increased sweating and production of saliva, diarrhea, nausea (feeling sick) and vomiting, loss of appetite, lowered resistance to infection, bruising or bleeding, anemia, hair loss, tiredness and a general feeling of weakness.
  • the present invention enables the treatment provider to determine in advance those patients likely to benefit from irinotecan treatment, and to consider alternative treatment options for non-responders.
  • treatment with irinotecan includes administering irinotecan alone and in combination with other therapeutic agents or adjuvants.
  • the current indications for CAMPTOSAR® include administering irinotecan HCl in combination with 5-fluorouracil (5-FU) and leucovorin (LV) as first-line therapy for metastatic colorectal cancer, and alone as a second-line therapy for patients whose disease has returned or progressed following initial 5-FU therapy.
  • the genes comprising the present GEP include: ERBB2, GRB7, Erk1 kinase, JNK1 kinase, BCL2, phospho-GSK-3beta, MMP11, CTSL2, CCNB1, BIRC5, MK167, STK6, MRP14, phospho-Akt, CD68, BAG1 and GSTM1.
  • the present gene expression profile further includes the following reference genes: ACTB, GAPD, GUSB, RPLP0 and TFRC.
  • NCBI Accession Number of a variant of each of these genes is set forth in Table 1; other variants exist which can be readily ascertained by reference to an appropriate database such as NCBI Entrez (www.ncbi.nlm.nih.gov/gquery), and these variants are encompassed by the present invention.
  • NCBI Entrez www.ncbi.nlm.nih.gov/gquery
  • These genes are either up- or down-regulated in patients that are responsive to irinotecan therapy, and not in in patients that experience late recurrence of their disease or disease related death associated with the therapy.
  • HER2 Amplicon ERBB2 HER2 Up NM_004448 1 GRB7 Up NM_005310 2 ER Expression Cluster Erk1 kinase Down X60188 3 JNK1 kinase Up NM_002750 4 BCL2 Up NM_000633 5 GSK-3-beta Down NM_002093 6 Invasion Group MMP11 STMY3; stromolysin 3 Down NM_005940 7 CTSL2 cathepsin L2 Down NM_001333 8 Proliferation Cluster CCNB1 cyclin B1 Down NM_031966 9 BIRC5 SURV; survivin Down NM_001168 10 MKI67 Ki-67 antigen Up NM_002417 11 STK6 STK15; BTAK Down NM_003600 12 Akt (Ser473) Up NM_005163 13 Other Genes CD68 Up NM_001251 14 BAG1 Up NM_004323 15 GSTM1 glutathi
  • the gene profile of the present invention comprises at least four, preferably between four and ten, more preferably at least ten, and most preferably at least sixteen, of the genes in the present GEP, up- or down-regulated as applicable, together with one or more reference genes.
  • the gene expression profiles of the invention can be used to predict the responsiveness of a colon cancer patient to irinotecan therapy.
  • the present method comprises (a) obtaining a gene expression profile from a biological sample of a patient afflicted with colon cancer; (b) determining from the gene expression profile whether one or more of the following genes are up-regulated (over-expressed): ERBB2, GRB7, JNK1 kinase, BCL2, MK167, phospho-Akt, CD68 and BAG1; and/or whether at least one of the following genes are down-regulated (under-expressed): Erk1 kinase, phospho-GSK-3beta, MMP11, CTSL2, CCNB1, BIRC5, STK6, MRP14 and GSTM1.
  • expression of at least two reference genes also is measured.
  • the predictive value of the gene profile for determining response to irinotecan increases with the number of these genes that are found to be up- or down-regulated in accordance with the invention.
  • at least about four, more preferably at least about ten and most preferably at least about sixteen of the genes in the present GPEP are differentially expressed.
  • the present invention further comprises protein expression profiles that are indicative of a cancer patient's tendency to respond to treatment with irinotecan.
  • the protein expression profile comprises at least one, preferably a plurality, of proteins encoded by the genes selected from the group consisting of ERBB2, GRB7, Erk1 kinase, JNK1 kinase, BCL2, phospho-GSK-3beta, MMP11, CTSL2, CCNB1, BIRC5, MK167, STK6, MRP14, phospho-Akt, CD68, BAG1 and GSTM1.
  • some or all of theses proteins are differentially expressed (e.g., up-regulated or down-regulated) in patients who are responders to irinotecan therapy.
  • the proteins encoded by the following genes are up-regulated (over-expressed): ERBB2, GRB7, JNK1 kinase, BCL2, MK167, phospho-Akt, CD68 and BAG1 and the proteins encoded by the following genes are down-regulated (under expressed): Erk1 kinase, phospho-GSK-3beta, MMP11, CTSL2, CCNB1, BIRC5, STK6, MRP14 and GSTM1, in patients who are responders to irinotecan.
  • the following reference genes may be included: ACTB, GAPD, GUSB, RPLP0 and TFRC.
  • Table 2 lists the genes in the present GPEP and a variant of a protein encoded thereby. Table 2 also indicates whether expression of the protein is up- or down-regulated in patients responsive to irinotecan therapy.
  • Table 2 includes the NCBI Accession No. of a variant of each protein; other variants of these proteins exist, which can be readily ascertained by reference to an appropriate database such as NCBI Entrez (www.ncbi.nlm.nih.gov/gquery). Alternate names for the proteins listed in Table 2 also can be determined from the NCBI site. TABLE 2 UP- OR DOWN- REGULATION NCBI Accession SEQ ID NO. GENE NAME PROTEIN NAME(S) of PROTEIN No.
  • genomic is intended to include the entire DNA complement of an organism, including the nuclear DNA component, chromosomal or extrachromosomal DNA, as well as the cytoplasmic domain (e.g., mitochondrial DNA).
  • the term “gene” refers to a nucleic acid sequence that comprises control and coding sequences necessary for producing a polypeptide or precursor.
  • the polypeptide may be encoded by a full length coding sequence or by any portion of the coding sequence.
  • the gene may be derived in whole or in part from any source known to the art, including a plant, a fungus, an animal, a bacterial genome or episome, eukaryotic, nuclear or plasmid DNA, cDNA, viral DNA, or chemically synthesized DNA.
  • a gene may contain one or more modifications in either the coding or the untranslated regions that could affect the biological activity or the chemical structure of the expression product, the rate of expression, or the manner of expression control.
  • Such modifications include, but are not limited to, mutations, insertions, deletions, and substitutions of one or more nucleotides.
  • the gene may constitute an uninterrupted coding sequence or it may include one or more introns, bound by the appropriate splice junctions.
  • the Term “gene” as used herein includes variants of the genes identified in Table 1.
  • gene expression refers to the process by which a nucleic acid sequence undergoes successful transcription and translation such that detectable levels of the nucleotide sequence are expressed.
  • gene expression profile or “gene signature” refer to a group of genes expressed by a particular cell or tissue type wherein presence of the genes taken together or the differential expression of such genes, is indicative/predictive of a certain condition.
  • nucleic acid refers to a molecule comprised of one or more nucleotides, i.e., ribonucleotides, deoxyribonucleotides, or both.
  • the term includes monomers and polymers of ribonucleotides and deoxyribonucleotides, with the ribonucleotides and/or deoxyribonucleotides being bound together, in the case of the polymers, via 5′ to 3′ linkages.
  • the ribonucleotide and deoxyribonucleotide polymers may be single or double-stranded.
  • linkages may include any of the linkages known in the art including, for example, nucleic acids comprising 5′ to 3′ linkages.
  • the nucleotides may be naturally occurring or may be synthetically produced analogs that are capable of forming base-pair relationships with naturally occurring base pairs.
  • Examples of non-naturally occurring bases that are capable of forming base-pairing relationships include, but are not limited to, aza and deaza pyrimidine analogs, aza and deaza purine analogs, and other heterocyclic base analogs, wherein one or more of the carbon and nitrogen atoms of the pyrimidine rings have been substituted by heteroatoms, e.g., oxygen, sulfur, selenium, phosphorus, and the like.
  • the term “nucleic acid sequences” contemplates the complementary sequence and specifically includes any nucleic acid sequence that is substantially homologous to the both the nucleic acid sequence and its complement.
  • array and “microarray” refer to the type of genes or proteins represented on an array by oligonucleotides or protein-capture agents, and where the type of genes or proteins represented on the array is dependent on the intended purpose of the array (e.g., to monitor expression of human genes or proteins).
  • the oligonucleotides or protein-capture agents on a given array may correspond to the same type, category, or group of genes or proteins.
  • Genes or proteins may be considered to be of the same type if they share some common characteristics such as species of origin (e.g., human, mouse, rat); disease state (e.g., cancer); functions (e.g., protein kinases, tumor suppressors); same biological process (e.g., apoptosis, signal transduction, cell cycle regulation, proliferation, differentiation).
  • one array type may be a “cancer array” in which each of the array oligonucleotides or protein-capture agents correspond to a gene or protein associated with a cancer.
  • An “epithelial array” may be an array of oligonucleotides or protein-capture agents corresponding to unique epithelial genes or proteins.
  • a “cell cycle array” may be an array type in which the oligonucleotides or protein-capture agents correspond to unique genes or proteins associated with the cell cycle.
  • cell type refers to a cell from a given source (e.g., a tissue, organ) or a cell in a given state of differentiation, or a cell associated with a given pathology or genetic makeup.
  • activation refers to any alteration of a signaling pathway or biological response including, for example, increases above basal levels, restoration to basal levels from an inhibited state, and stimulation of the pathway above basal levels.
  • differential expression refers to both quantitative as well as qualitative differences in the temporal and tissue expression patterns of a gene or a protein in diseased tissues or cells versus normal adjacent tissue.
  • a differentially expressed gene may have its expression activated or completely inactivated in normal versus disease conditions, or may be up-regulated (over-expressed) or down-regulated (under-expressed) in a disease condition versus a normal condition.
  • Such a qualitatively regulated gene may exhibit an expression pattern within a given tissue or cell type that is detectable in either control or disease conditions, but is not detectable in both.
  • a gene or protein is differentially expressed when expression of the gene or protein occurs at a higher or lower level in the diseased tissues or cells of a patient relative to the level of its expression in the normal (disease-free) tissues or cells of the patient and/or control tissues or cells.
  • RNA expression pattern which is detectable via the standard techniques of polymerase chain reaction (PCR), reverse transcriptase-(RT) PCR, differential display, and Northern analyses, which are well known to those of skill in the art.
  • PCR polymerase chain reaction
  • RT reverse transcriptase-(RT) PCR
  • differential display differential display
  • Northern analyses which are well known to those of skill in the art.
  • protein expression patterns may be “detected” via standard techniques such as Western blots.
  • complementary refers to the topological compatibility or matching together of the interacting surfaces of a probe molecule and its target.
  • the target and its probe can be described as complementary, and furthermore, the contact surface characteristics are complementary to each other.
  • Hybridization or base pairing between nucleotides or nucleic acids, such as, for example, between the two strands of a double-stranded DNA molecule or between an oligonucleotide probe and a target are complementary.
  • biological sample refers to a sample obtained from an organism (e.g., a human patient) or from components (e.g., cells) of an organism.
  • the sample may be of any biological tissue or fluid.
  • the sample may be a “clinical sample” which is a sample derived from a patient.
  • Such samples include, but are not limited to, sputum, blood, blood cells (e.g., white cells), amniotic fluid, plasma, semen, bone marrow, and tissue or fine needle biopsy samples, urine, peritoneal fluid, and pleural fluid, or cells therefrom.
  • Biological samples may also include sections of tissues such as frozen sections taken for histological purposes.
  • a biological sample may also be referred to as a “patient sample.”
  • a “protein” means a polymer of amino acid residues linked together by peptide bonds.
  • a protein may be naturally occurring, recombinant, or synthetic, or any combination of these.
  • a protein may also comprise a fragment of a naturally occurring protein or peptide.
  • a protein may be a single molecule or may be a multi-molecular complex.
  • the term protein may also apply to amino acid polymers in which one or more amino acid residues is an artificial chemical analogue of a corresponding naturally occurring amino acid.
  • fragment of a protein refers to a protein that is a portion of another protein.
  • fragments of proteins may comprise polypeptides obtained by digesting full-length protein isolated from cultured cells.
  • a protein fragment comprises at least about six amino acids.
  • the fragment comprises at least about ten amino acids.
  • the protein fragment comprises at least about sixteen amino acids.
  • an “expression product” is a biomolecule, such as a protein, which is produced when a gene in an organism is expressed.
  • An expression product may comprise post-translational modifications.
  • protein expression refers to the process by which a nucleic acid sequence undergoes successful transcription and translation such that detectable levels of the amino acid sequence or protein are expressed.
  • protein expression profile or “protein expression signature” refer to a group of proteins expressed by a particular cell or tissue type (e.g., neuron, coronary artery endothelium, or disease tissue), wherein presence of the proteins taken together or the differential expression of such proteins, is indicative/predictive of a certain condition.
  • a particular cell or tissue type e.g., neuron, coronary artery endothelium, or disease tissue
  • antibody means an immunoglobulin, whether natural or partially or wholly synthetically produced. All derivatives thereof that maintain specific binding ability are also included in the term. The term also covers any protein having a binding domain that is homologous or largely homologous to an immunoglobulin binding domain.
  • An antibody may be monoclonal or polyclonal. The antibody may be a member of any immunoglobulin class, including any of the human classes: IgG, IgM, IgA, IgD, and IgE.
  • antibody fragment refers to any derivative of an antibody that is less than full-length. In one aspect, the antibody fragment retains at least a significant portion of the full-length antibody's specific binding ability, specifically, as a binding partner. Examples of antibody fragments include, but are not limited to, Fab, Fab′, F(ab′) 2 , scFv, Fv, dsFv diabody, and Fd fragments.
  • the antibody fragment may be produced by any means. For example, the antibody fragment may be enzymatically or chemically produced by fragmentation of an intact antibody or it may be recombinantly produced from a gene encoding the partial antibody sequence. Alternatively, the antibody fragment may be wholly or partially synthetically produced.
  • the antibody fragment may comprise a single chain antibody fragment.
  • the fragment may comprise multiple chains that are linked together, for example, by disulfide linkages.
  • the fragment may also comprise a multimolecular complex.
  • a functional antibody fragment may typically comprise at least about 50 amino acids and more typically will comprise at least about 200 amino acids.
  • the present method utilizes parallel testing in which, in one track, those genes which are over-/under-expressed as compared to normal (non-cancerous) tissue samples are identified, and, in a second track, those genes comprising chromosomal insertions or deletions as compared to normal samples are identified, from the same samples.
  • These two tracks of analysis produce two sets of data.
  • the data are analyzed using an algorithm which identifies the genes of the gene expression profile (i.e., those genes that are differentially expressed in cancer tissue). Positive and negative controls may be employed to normalize the results, including eliminating those genes and proteins that also are differentially expressed in normal tissues from the same patients, and confirming that the gene expression profile is unique to the cancer of interest.
  • tissue samples were acquired from patients afflicted with colorectal cancer.
  • tissue samples obtained from colorectal cancer patients were used, including tumor tissue and adjacent normal (undiseased) colon tissue.
  • the tissue samples were obtained from patients suffering from various stages of colon cancer, and included those obtained from patients who have been treated with irinotecan. All of the patients were responders to irinotecan therapy.
  • Clinical information also includes information such as age, sex, medical history, treatment history, symptoms, family history, recurrence (yes/no), etc.
  • Control samples including samples of normal (non-cancerous) tissue also were acquired from the same patients. Samples of normal undiseased colon tissue from a set of healthy individuals were used as positive controls, and colon tumor samples from patients who were non-responders to irinotecan therapy were used as negative controls.
  • GEPs Gene expression profiles then were generated from the biological samples based on total RNA according to well-established methods. Briefly, a typical method involves isolating total RNA from the biological sample, amplifying the RNA, synthesizing cDNA, labeling the cDNA with a detectable label, hybridizing the cDNA with a genomic array, such as the Affymetrix U133 GeneChip, and determining binding of the labeled cDNA with the genomic array by measuring the intensity of the signal from the detectable label bound to the array. See, e.g., the methods described in Lu, et al., Chen, et al. and Golub, et al., supra, and the references cited therein, which are incorporated herein by reference. The resulting expression data are input into a database.
  • MRNAs in the tissue samples can be analyzed using commercially available or customized probes or oligonucleotide arrays, such as cDNA or oligonucleotide arrays.
  • probes or oligonucleotide arrays such as cDNA or oligonucleotide arrays.
  • the use of these arrays allows for the measurement of steady-state mRNA levels of thousands of genes simultaneously, thereby presenting a powerful tool for identifying effects such as the onset, arrest or modulation of uncontrolled cell proliferation.
  • Hybridization and/or binding of the probes on the arrays to the nucleic acids of interest from the cells can be determined by detecting and/or measuring the location and intensity of the signal received from the labeled probe or used to detect a DNA/RNA sequence from the sample that hybridizes to a nucleic acid sequence at a known location on the microarray.
  • the intensity of the signal is proportional to the quantity of cDNA or mRNA present in the sample tissue.
  • Numerous arrays and techniques are available and useful. Methods for determining gene and/or protein expression in sample tissues are described, for example, in U.S. Pat. No. 6,271,002; U.S. Pat. No. 6,218,122; U.S. Pat. No. 6,218,114; and U.S. Pat. No. 6,004,755; and in Wang et al., J. Clin. Oncol., 22(9):1564-1671 (2004); Golub et al, (supra); and Schena et al., Science, 270:467-470 (1995); all of which are incorporated herein by reference.
  • RNA was isolated from the tissue samples and labeled. Parallel processes were run on the sample to develop two sets of data: (1) over-/under-expression of genes based on mRNA levels; and (2) chromosomal insertion/deletion data. These two sets of data were then correlated by means of an algorithm. Over-/under-expression of the genes in each cancer tissue sample were compared to gene expression in the normal (non-cancerous) samples, and a subset of genes that were differentially expressed in the cancer tissue was identified. Preferably, levels of up- and down-regulation are distinguished based on fold changes of the intensity measurements of hybridized microarray probes.
  • a difference of about 2.0 fold or greater is preferred for making such distinctions, or a p-value of less than about 0.05. That is, before a gene is said to be differentially expressed in diseased versus normal cells, the diseased cell is found to yield at least about 2 times greater or less intensity of expression than the normal cells. Generally, the greater the fold difference (or the lower the p-value), the more preferred is the gene for use as a diagnostic or prognostic tool.
  • Genes selected for the gene signatures of the present invention have expression levels that result in the generation of a signal that is distinguishable from those of the normal or non-modulated genes by an amount that exceeds background using clinical laboratory instrumentation.
  • Statistical values can be used to confidently distinguish modulated from non-modulated genes and noise.
  • Statistical tests can identify the genes most significantly differentially expressed between diverse groups of samples.
  • the Student's t-test is an example of a robust statistical test that can be used to find significant differences between two groups. The lower the p-value, the more compelling the evidence that the gene is showing a difference between the different groups. Nevertheless, since microarrays allow measurement of more than one gene at a time, tens of thousands of statistical tests may be asked at one time. Because of this, it is unlikely to observe small p-values just by chance, and adjustments using a Sidak correction or similar step as well as a randomization/permutation experiment can be made.
  • a p-value less than about 0.05 by the t-test is evidence that the expression level of the gene is significantly different. More compelling evidence is a p-value less then about 0.05 after the Sidak correction is factored in. For a large number of samples in each group, a p-value less than about 0.05 after the randomization/permutation test is the most compelling evidence of a significant difference.
  • Another parameter that can be used to select genes that generate a signal that is greater than that of the non-modulated gene or noise is the measurement of absolute signal difference.
  • the signal generated by the differentially expressed genes differs by at least about 20% from those of the normal or non-modulated gene (on an absolute basis). It is even more preferred that such genes produce expression patterns that are at least about 30% different than those of normal or non-modulated genes.
  • This differential expression analysis can be performed using commercially available arrays, for example, Affymetrix U133 GeneChip® arrays (Affymetrix, Inc., www.affymetrix.com). These arrays have probe sets for the whole human genome immobilized on the chip, and can be used to determine up- and down-regulation of genes in test samples. Other substrates having affixed thereon human genomic DNA or probes capable of detecting expression products, such as those available from Affymetrix, Agilent Technologies, Inc. (www.agilent.com) or Illumina, Inc. (www.illumina.com), also may be used.
  • Currently preferred gene microarrays for use in the present invention include Affymetrix U133 GeneChip® arrays and Agilent Technologies genomic cDNA microarrays. Instruments and reagents for performing gene expression analysis are commercially available. See, e.g., Affymetrix GeneChip® System (www.affymetrix.com). The expression data obtained from the analysis then is input into the database.
  • chromosomal insertion/deletion data for the genes of each sample as compared to samples of normal tissue was obtained.
  • the insertion/deletion analysis was generated using an array-based comparative genomic hybridization (“CGH”).
  • CGH comparative genomic hybridization
  • Array CGH measures copy-number variations at multiple loci simultaneously, providing an important tool for studying cancer and developmental disorders and for developing diagnostic and therapeutic targets.
  • Microchips for performing array CGH are commercially available, e.g., from Agilent Technologies.
  • the Agilent chip is a chromosomal array which shows the location of genes on the chromosomes and provides additional data for the gene signature.
  • the insertion/deletion data from this testing is input into the database.
  • the analyses are carried out on the same samples from the same patients to generate parallel data.
  • the same chips and sample preparation are used to reduce variability.
  • Reference genes are genes that are consistently expressed in many tissue types, including cancerous and normal tissues, and thus are useful to normalize gene expression profiles. See, e.g., Silvia et al., BMC Cancer, 6:200 (2006); Lee et al., Genome Research, 12(2):292-297 (2002); Zhang et al., BMC Mol. Biol., 6:4 (2005). Determining the expression of reference genes in parallel with the genes in the unique gene expression profile provides further assurance that the techniques used for determination of the gene expression profile are working properly.
  • the expression data relating to the reference genes also is input into the database. In a currently preferred embodiment, the following genes are used as reference genes: ACTB, GAPD, GUSB, RPLP0 and/or TRFC.
  • the differential expression data and the insertion/deletion data in the database are correlated with the clinical outcomes information associated with each tissue sample also in the database by means of an algorithm to determine a gene expression profile for determining therapeutic efficacy of irinotecan, as well as late recurrence of disease and/or disease-related death associated with irinotecan therapy.
  • Various algorithms are available which are useful for correlating the data and identifying the predictive gene signatures. For example, algorithms such as those identified in Xu et al., A Smooth Response Surface Algorithm For Constructing A Gene Regulatory Network, Physiol. Genomics 11:11-20 (2002), the entirety of which is incorporated herein by reference, may be used for the practice of the embodiments disclosed herein.
  • Another method for identifying gene expression profiles is through the use of optimization algorithms such as the mean variance algorithm widely used in establishing stock portfolios.
  • optimization algorithms such as the mean variance algorithm widely used in establishing stock portfolios.
  • One such method is described in detail in the patent application US Patent Application Publication No. 2003/0194734.
  • the method calls for the establishment of a set of inputs expression as measured by intensity) that will optimize the return (signal that is generated) one receives for using it while minimizing the variability of the return.
  • the algorithm described in Irizarry et al., Nucleic Acids Res., 31:e15 (2003) also may be used.
  • the currently preferred algorithm is the JMP Genomics algorithm available from JMP Software (www.jmp.com).
  • the process of selecting gene expression profiles also may include the application of heuristic rules.
  • Such rules are formulated based on biology and an understanding of the technology used to produce clinical results, and are applied to output from the optimization method.
  • the mean variance method of gene signature identification can be applied to microarray data for a number of genes differentially expressed in subjects with colorectal cancer. Output from the method would be an optimized set of genes that could include some genes that are expressed in peripheral blood as well as in diseased tissue. If samples used in the testing method are obtained from peripheral blood and certain genes differentially expressed in instances of cancer could also be differentially expressed in peripheral blood, then a heuristic rule can be applied in which a portfolio is selected from the efficient frontier excluding those that are differentially expressed in peripheral blood.
  • the rule can be applied prior to the formation of the efficient frontier by, for example, applying the rule during data pre-selection.
  • heuristic rules can be applied that are not necessarily related to the biology in question. For example, one can apply a rule that only a certain percentage of the portfolio can be represented by a particular gene or group of genes.
  • Commercially available software such as the Wagner software readily accommodates these types of heuristics (Wagner Associates Mean-Variance Optimization Application, www.wagner.com). This can be useful, for example, when factors other than accuracy and precision have an impact on the desirability of including one or more genes.
  • the algorithm may be used for comparing gene expression profiles for various genes (or portfolios) to ascribe prognoses.
  • the gene expression profiles of each of the genes comprising the portfolio are fixed in a medium such as a computer readable medium.
  • a medium such as a computer readable medium.
  • This can take a number of forms. For example, a table can be established into which the range of signals (e.g., intensity measurements) indicative of disease is input. Actual patient data can then be compared to the values in the table to determine whether the patient samples are normal or diseased.
  • patterns of the expression signals e.g., fluorescent intensity
  • the gene expression patterns from the gene portfolios used in conjunction with patient samples are then compared to the expression patterns.
  • Pattern comparison software can then be used to determine whether the patient samples have a pattern indicative of recurrence of the disease. Of course, these comparisons can also be used to determine whether the patient is not likely to experience disease recurrence.
  • the expression profiles of the samples are then compared to the portfolio of a control cell. If the sample expression patterns are consistent with the expression pattern for recurrence of a colorectal cancer then (in the absence of countervailing medical considerations) the patient is treated as one would treat a relapse patient. If the sample expression patterns are consistent with the expression pattern from the normal/control cell then the patient is diagnosed negative for colorectal cancer.
  • a method for analyzing the gene signatures of a patient to determine prognosis of cancer is through the use of a Cox hazard analysis program.
  • the analysis may be conducted using S-Plus software (commercially available from Insightful Corporation, www.insightful.com).
  • S-Plus software commercially available from Insightful Corporation, www.insightful.com.
  • a gene expression profile is compared to that of a profile that confidently represents relapse (i.e., expression levels for the combination of genes in the profile is indicative of relapse).
  • the Cox hazard model with the established threshold is used to compare the similarity of the two profiles (known relapse versus patient) and then determines whether the patient profile exceeds the threshold. If it does, then the patient is classified as one who will relapse and is accorded treatment such as adjuvant therapy.
  • patient profile does not exceed the threshold then they are classified as a non-relapsing patient.
  • Other analytical tools can also be used to answer the same question such as, linear discriminate analysis, logistic regression and neural network approaches. See, e.g., software available from JMP statistical software (wwwjmp.com).
  • Weighted Voting Golub, T R., Slonim, D K., Tamaya, P., Huard, C., Gaasenbeek, M., Mesirov, J P., Coller, H., Loh, L., Downing, J R., Caligiuri, M A., Bloomfield, C D., Lander, E S. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 286:531-537, 1999.
  • Support Vector Machines Su, A I., Welsh, J B., Sapinoso, L M., Kern, S G., Dimitrov, P., Lapp, H., Schultz, P G., Powell, S M., Moskaluk, C A., Frierson, H F. Jr., Hampton, G M. Molecular classification of human carcinomas by use of gene expression signatures. Cancer Research 61:7388-93, 2001.
  • K-nearest Neighbors Ramaswamy, S., Tamayo, P., Rifkin, R., Mukherjee, S., Yeang, C H., Angelo, M., Ladd, C., Reich, M., Latulippe, E., Mesirov, J P., Poggio, T., Gerald, W., Loda, M., Lander, E S., Gould, T R. Multiclass cancer diagnosis using tumor gene expression signatures Proceedings of the National Academy of Sciences of the USA 98:15149-15154, 2001.
  • the gene expression analysis identifies a gene expression profile (GEP) unique to the cancer samples, that is, those genes which are differentially expressed by the cancer cells.
  • GEP gene expression profile
  • RT-qPCR real-time quantitative polymerase chain reaction
  • the results of the gene expression analysis showed that in colon cancer patients who were responsive to treatment with irinotecan, the following genes were up-regulated: ERBB2, GRB7, JNK1 kinase, BCL2, MK167, phospho-Akt, CD-68 and BAG1, and the following genes were down-regulated: Erk1 kinase, pospho-GSK-3beta, MMP11, CTSL2, CCNB1, BIRC5, STK6, MRP14 and GSTM1, compared with expression of these genes in the normal colon tissue samples from these patients, and from the negative control patients, i.e., the tissue samples from patients that had experienced a recurrence of their cancer after treatment with irinotecan.
  • Reference genes ACTB, GAPD, GUSB, RPLP0 and TFRC all were up-regulated.
  • PEPs protein expression profiles
  • the preferred method for generating PEPs according to the present invention is by immunohistochemistry (IHC) analysis.
  • IHC immunohistochemistry
  • antibodies specific for the proteins in the PEP are used to interrogate tissue samples from colon cancer patients.
  • Other methods for identifying PEPs are known, e.g. in situ hybridization (ISH) using protein-specific nucleic acid probes. See, e.g., Hofer et al., Clin. Can. Res., 11(16):5722 (2005); Volm et al., Clin. Exp. Metas., 19(5):385 (2002). Any of these alternative methods also could be used.
  • samples of colon tumor tissue and normal colon tissue were obtained from patients afflicted with colon cancer who had undergone successful treatment with irinotecan; these are the same samples used for identifying the GEP.
  • the tissue samples were arrayed on tissue microarrays (TMAs) to enable simultaneous analysis.
  • TMAs consist of substrates, such as glass slides, on which up to about 1000 separate tissue samples are assembled in array fashion to allow simultaneous histological analysis.
  • the tissue samples may comprise tissue obtained from preserved biopsy samples, e.g., paraffin-embedded or frozen tissues. Techniques for making tissue microarrays are well-known in the art.
  • tissue cores as small as 0.6 mm in diameter from regions of interest in paraffin embedded tissues.
  • the “regions of interest” are those that have been identified by a pathologist as containing the desired diseased or normal tissue. These tissue cores then were inserted in a recipient paraffin block in a precisely spaced array pattern. Sections from this block were cut using a microtome, mounted on a microscope slide and then analyzed by standard histological analysis. Each microarray block can be cut into approximately 100 to approximately 500 sections, which can be subjected to independent tests.
  • the TMAs were prepared using two tissue samples from each patient: one of colon tumor tissue and one of normal colon tissue. Control arrays also were prepared; in a currently preferred embodiment, the following control TMAs were used: an array containing normal colon tissue samples from healthy, cancer-free individuals; an array of “positive controls” containing tumor tissues from cancer patients afflicted with cancers other than colon cancer, e.g., breast cancer, lung cancer, prostate cancer, etc; and an array of “negative controls” containing tumor samples from colon cancer patients that had experienced recurrences of the cancer after treatment with irinotecan—that is, patients who were “non-responders” to the therapy.
  • Proteins in the tissue samples may be analyzed by interrogating the TMAs using protein-specific agents, such as antibodies or nucleic acid probes, such as aptamers.
  • Antibodies are preferred for this purpose due to their specificity and availability.
  • the antibodies may be monoclonal or polyclonal antibodies, antibody fragments, and/or various types of synthetic antibodies, including chimeric antibodies, or fragments thereof.
  • Antibodies are commercially available from a number of sources (e.g., Abcam (www.abcam.com), Cell Signaling Technology (www.cellsignal.com), Santa Cruz Biotechnology (www.santacruz.com)), or may be generated using techniques well-known to those skilled in the art.
  • the antibodies typically are equipped with detectable labels, such as enzymes, chromogens or quantum dots, that permit the antibodies to be detected.
  • detectable labels such as enzymes, chromogens or quantum dots, that permit the antibodies to be detected.
  • the antibodies may be conjugated or tagged directly with a detectable label, or indirectly with one member of a binding pair, of which the other member contains a detectable label.
  • Detection systems for use with are described, for example, in the website of Ventana Medical Systems, Inc. (www.ventanamed.com).
  • Quantum dots are particularly useful as detectable labels. The use of quantum dots is described, for example, in the following references: Jaiswal et al., Nat. Biotechnol., 21:47-51 (2003); Chan et al., Curr. Opin. Biotechnol., 13:40-46 (2002); Chan et al., Science, 281:435-446 (1998).
  • immunohistochemistry The use of antibodies to identify proteins of interest in the cells of a tissue, referred to as immunohistochemistry (IHC), is well established. See, e.g., Simon et al., BioTechniques, 36(1):98 (2004); Haedicke et al., BioTechniques, 35(1):164 (2003), which are hereby incorporated by reference.
  • the IHC assay can be automated using commercially available instruments, such as the Benchmark instruments available from Ventana Medical Systems, Inc. (www.ventanamed.com).
  • the TMAs were contacted with antibodies specific for the proteins encoded by the genes identified in the gene expression study as being up- or down-regulated in colon cancer patients who were responders to therapy with irinotecan in order to determine expression of these proteins in each type of tissue.
  • the results of the IHC assay showed that in colon cancer patients who were responsive to treatment with irinotecan, the following proteins were up-regulated: ERBB2, GRB7, JNK1 kinase, BCL2, MK167, phospho-Akt, CD-68 and BAG1, and the following proteins were down-regulated: Erk1 kinase, pospho-GSK-3beta, MMP11, CTSL2, CCNB1, BIRC5, STK6, MRP14 and GSTM1, compared with expression of these proteins in the normal colon tissue samples from these patients, and in the negative control samples, i.e., colon tumor samples from patients that had experienced a recurrence of their cancer after treatment with irinotecan (non-responders). Additionally, IHC analysis showed that a majority of these proteins were not up- or down-regulated in the positive control tissue samples.
  • the reference proteins ACTB, GAPD, GUSB, RPLP0 and TFRC all were up-regulated.
  • the present invention further comprises methods and assays for determining whether a colon cancer patient is likely to respond to treatment with irinotecan, and/or to predict whether the cancer is likely to recur, or disease-related death.
  • a formatted IHC assay can be used for determining if a colon cancer tumor exhibits the present GPEP.
  • the assays may be formulated into kits that include all or some of the materials needed to conduct the analysis, including reagents (antibodies, detectable labels, etc.) and instructions.
  • the assay method of the invention comprises contacting a tumor sample from a colon cancer patient with a group of antibodies specific for some or all of the genes or proteins in the present GPEP, and determining the occurrence of up- or down-regulation of these genes or proteins in the sample.
  • TMAs allows numerous samples, including control samples, to be assayed simultaneously.
  • the method comprises contacting a tumor sample from a colon cancer patient and control samples with a group of antibodies specific for some or all of the proteins in the present GPEP, and determining the occurrence of up- or down-regulation of these proteins.
  • at least about four, preferably between about four and ten, and most preferably between about ten and sixteen (or more) antibodies are used in the present method.
  • the method preferably also includes detecting and/or quantitating control or “reference proteins”. Detecting and/or quantitating the reference proteins in the samples normalizes the results and thus provides further assurance that the assay is working properly.
  • antibodies specific for one or more of the following reference proteins are included: ACTB, GAPD, GUSB, RPLP0 and/or TRFC.
  • the present invention further comprises a kit containing reagents for conducting an IHC analysis of tissue samples or cells from colon cancer patients, including antibodies specific for at least four of the proteins in the GPEP and for any reference proteins.
  • the antibodies are preferably tagged with means for detecting the binding of the antibodies to the proteins of interest, e.g., detectable labels.
  • detectable labels include fluorescent compounds or quantum dots, however other types of detectable labels may be used.
  • Detectable labels for antibodies are commercially available, e.g. from Ventana Medical Systems, Inc. (www.ventanamed.com).
  • Immunohistochemical methods for detecting and quantitating protein expression in tissue samples are well known. Any method that permits the determination of expression of several different proteins can be used. See. e.g., Signoretti et al., “Her-2-neu Expression and Progression Toward Androgen Independence in Human Prostate Cancer,” J. Natl. Cancer Instit., 92(23):1918-25 (2000); Gu et al., “Prostate stem cell antigen (PSCA) expression increases with high gleason score, advanced stage and bone metastasis in prostate cancer,” Oncogene, 19:1288-96 (2000). Such methods can be efficiently carried out using automated instruments designed for immunohistochemical (IHC) analysis.
  • IHC immunohistochemical
  • Instruments for rapidly performing such assays are commercially available, e.g., from Ventana Molecular Discovery Systems (www.ventanadiscovery.com) or Lab Vision Corporation (www.labvision.com). Methods according to the present invention using such instruments are carried out according to the manufacturer's instructions.
  • Protein-specific antibodies for use in such methods or assays are readily available or can be prepared using well-established techniques.
  • Antibodies specific for the proteins in the GPEP disclosed herein can be obtained, for example, from Cell Signaling Technology, Inc. (www.cellsignal.com), Santa Cruz Biotechnology, Inc. (www.santacruzbiotechnology.com) or Abcam (www.abcam.com).
  • GPEP gene/protein expression profile
  • the expression levels of these factors consisting of the twenty-two (22) proteins in the present GPEP listed in Table 2 (which includes seventeen differentially expressed proteins and five reference proteins), was determined by an immunohistochemical methodology in biopsy tissue samples obtained from late-stage colon cancer patients whose treatment with irinotecan had been successful, as well as samples from patients whose treatment was unsuccessful, e.g., who had experienced late recurrence (LRec) or disease-related death (DRD) associated with the therapy.
  • LRec late recurrence
  • DTD disease-related death
  • irinotecan currently is indicated for first line therapy of colon cancer in combination with 5-fluorouracil (5-FU) and leucovorin, or following initial 5-FU therapy in late stage colon cancer patients.
  • the patients in the study had been treated using the combination therapy according to the prescribing information for CAMPTOSAR®.
  • a GPEP was generated, consisting of the following seventeen genes and encoded proteins: ERBB2, GRB7, JNK1 kinase, BCL2, MK167, phospho-Akt, CD68, BAG1, Erk1 kinase, phospho-GSK-3beta, MMP11, CTSL2, CCNB1, BIRC5, STK6, MRP14 and GSTM1, and five reference genes and proteins: ACTB, GAPD, GUSB, RPLP0 and TRFC.
  • Tissue microarrays were prepared using the colon adenocarcinomas and normal (non-cancerous) colon tissue from patients described above having late stage cancers who were treated with irinotecan. TMAs also were prepared containing positive and negative control samples. The TMAs used in this study are described in Table A: TABLE A Tissue Micro Arrays Normal This array contained samples of normal (non- Screening cancerous) colon tissue from 200 patients (2 Array samples per patient). Colon This array contained 280 patient samples Treatment obtained from the patients afflicted with late- Irinotecan stage colon adenocarcinoma who had been treated with CAMPTOSAR ® together with normal colon tissue samples from each patient.
  • Cancer This array contained 200 tumor samples for Screening cancers other than colon cancer, including Survey Array breast cancer, pancreatic cancer, prostate (Positive cancer, ovarian cancer, salivary gland cancer, control array) lung cancer and brain tumor.
  • Colon Cancer This array contained samples of colon cancer Progression tissue from thirty patients who had progressed (Negative control to the next stage of cancer or experienced a array - recurrence of cancer after treatment with TE30 array) CAMPTOSAR ®.
  • the TMAs were constructed according to the following procedure:
  • TMA sections were cut at 4 microns and mounted on positively charged glass microslides. Individual elements are 0.6 mm in diameter, spaced 0.2 mm apart.
  • the TMAs were designed for use with specialty staining and immunohistochemical methods for gene expression screening purposes by using monoclonal and polyclonal antibodies over a wide range of characterized tissue types.
  • each array was an array locator map and spreadsheet containing patient diagnostic, histologic and demographic data for each element.
  • Immunohistochemical staining techniques were used for the visualization of tissue (cell) proteins present in the tissue samples on the TMAs. These techniques were based on the immunoreactivity of antibodies and the chemical properties of enzyme or enzyme complexes, which react with colorless substrate-chromogens to produce a colored end product.
  • Initial immunoenzymatic stains utilized the direct method, which conjugated directly to an antibody with known antigenic specificity (primary antibody).
  • a modified labeled avidin-biotin technique was employed in which a biotinylated secondary antibody formed a complex with peroxidase-conjugated strepavidin molecules. Endogenous peroxidase activity was quenched by the addition of 3% hydrogen peroxide. The specimens then were incubate with the primary antibodies followed by sequential incubations with the biotinylated secondary link antibody (containing anti-rabbit or anti-mouse immunoglobulins) and peroidase labeled strepavidin. The primary antibody, secondary antibody, and avidin enzyme complex is then visualized utilizing a substrate-chromogen that produces a brown pigment at the antigen site that is visible by light microscopy.
  • the antibodies utilized in this study were antibodies specific for the proteins in the present protein expression profile, i.e., ERBB2, GRB7, JNK1 kinase, BCL2, MK167, phospho-Akt, CD68, BAG1, Erk1 kinase, phospho-GSK-3beta, MMP11, CTSL2, CCNB1, BIRC5, STK6, MRP14 and GSTM1, and reference proteins ACTB, GAPD, GUSB, RPLP0 and TRFC. All antibodies were obtained from Cell Signaling Technology, Inc., and Abcam.
  • Positive tissue controls were defined via standard Western Blot analysis. This experiment was performed to confirm the level of protein expression in each of the control tissues. Negative controls also were defined by the same methodology. The positive controls consisted of breast, prostate, bung, salivary gland, pancreas and ovarian adenocarcinomas and brain tumor tissue samples unrelated to the colon cancer patients who were the subjects of the study. Colon cancer tissue samples from patients who were non-responsive to irinotecan therapy (i.e., who experienced recurrence of the disease or death from the disease after treatment) were used as negative controls.
  • irinotecan therapy i.e., who experienced recurrence of the disease or death from the disease after treatment
  • mice were injected with tumor cells derived from patients who were responsive to treatment with irinotecan, and the tumors were allowed to grow in the mice. Once the tumors were established, the mice were injected with 200 mg/kg of irinotecan, and the mice were monitored to observe responsiveness to the drug. As a result of treatment with irinotecan, the tumors formed in the SCID mice were reduced or eliminated. Prior to treatment with the drug, samples of the tumors were extracted from the mice and used to make a TMA. IHC assay of the TMA containing the mouse xenograft tumor tissue showed that the xenograft tumors have the same GPEP as that identified in the human patients who were responsive to irinotecan therapy.
  • results from this study demonstrate that in late stage colon cancer patients, GPEP positivity by immunohistochemistry accurately predicted irinotecan therapy response, late disease recurrence and disease related death independent of tumor size, grade and Duke's status.
  • the test accurately detected ninety-two percent (92%) of non-responders to irinotecan therapy (less than 1.5% error rate or mis-classification).
  • the test sensitivity rate was determined to be about ninety-six percent (96%), and the test specificity rate to be about ninety-eight percent (98%).
  • GEP positivity means that in the tumor samples from patients who were responders to irinotecan therapy, the following proteins were up-regulated: ERBB2, GRB7, JNK1 kinase, BCL2, MK167, phospho-Akt, CD-68 and BAG1, and the following genes and encoded proteins were down-regulated: Erk1 kinase, phospho-GSK-3beta, MMP11, CTSL2, CCNB1, BIRC5, STK6, MRP14 and GSTM1, compared with expression of these genes and proteins in normal colon tissue from these patients and the normal colon tissue and non-colon cancer tissues from other patients.
  • Reference proteins ACTB, GAPD, GUSB, RPLP0 and TFRC were up-regulated in all tissues.
  • FIG. 1 is a graph showing the survival rates of colorectal cancer patients treated with irinotecan plotted against the presence of a GPEP of the invention.
  • patients with tumors having a gene expression profile in which at least sixteen of the genes in the present GPEP were differentially expressed and had the longest survival rates after treatment with irinotecan.
  • the survival rates of patients whose gene expression profiles indicated that four or fewer of these genes were differentially expressed had the lowest survival rates after irinotecan therapy.
  • the twenty genes noted in the legend to FIG. 1 include five reference proteins.
  • test sensitivity rate was determined to be about ninety-six percent (96%), and the test specificity rate to be about ninety-eight percent (98%).

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EP2881472A1 (fr) * 2013-12-09 2015-06-10 Université Pierre et Marie Curie (Paris 6) Procédé de prédiction d'une réponse à un traitement antitumoral
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EP2081950B1 (fr) 2013-03-20
WO2008073177A2 (fr) 2008-06-19
EP2081950A2 (fr) 2009-07-29
WO2008073177A3 (fr) 2008-11-06
US20090298084A1 (en) 2009-12-03
US20090047684A1 (en) 2009-02-19
EP2081950A4 (fr) 2010-03-17
US7763438B2 (en) 2010-07-27
DK2081950T3 (da) 2013-06-03
ES2405654T3 (es) 2013-05-31

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