WO2017067477A1

WO2017067477A1 - Methods for making diagnosis and/or prognosis of gynecologic neoplasm

Info

Publication number: WO2017067477A1
Application number: PCT/CN2016/102718
Authority: WO
Inventors: Hung-Cheng Lai; Rui-lan HUANG; Yu-ping LIAO; Po-Hsuan SU
Original assignee: Hung-Cheng Lai
Priority date: 2015-10-20
Filing date: 2016-10-20
Publication date: 2017-04-27

Abstract

Methods for assessing the presence of gynecologic neoplasm or the malignancy of the gynecologic neoplasm, based on the hypermethylation of one or more marker genes.

Description

METHODS FOR MAKING DIAGNOSIS AND/OR PROGNOSIS OF GYNECOLOGIC NEOPLASM

BACKGROUND OF THE INVENTION

1. FIELD OF THE INVENTION

The present disclosure relates to cancer diagnosis and/or prognosis. More particularly, the disclosed invention relates to methods for cancer diagnosis and/or prognosis based on the methylation state of selected markers.

2. DESCRIPTION OF RELATED ART

Gynecologic cancer is the uncontrolled growth of abnormal cells that originate from women’s reproductive organs. Main types of gynecologic cancers include cervical, ovarian, endometrial/uterine (hereinafter, endometrial) , vaginal, and vulvar cancers, while some rare gynecologic cancers include gestational trophoblastic disease (GTD) and primary peritoneal cancer.

According to Centers for Disease Control and Prevention (CDC) , approximately 71,500 women in the United States are diagnosed with a gynecologic cancer each year.

Endometrial cancer is the leading cause of gynecologic cancer in the Sates, with approximately 35,000 women being diagnosed each year. Most endometrial cancers are found in women who are going through or have gone through menopause. However, for those who do not have any signs or symptoms, there are no simple and reliable ways to test for uterine cancer. For patients showing symptoms or at a higher risk for endometrial cancer, an endometrial biopsy or a transvaginal ultrasound may be performed to help diagnose or rule out uterine cancer.

Ovarian cancer is second to endometrial cancer as the most common cause of gynecologic cancer, whereas the mortality rate of ovarian cancer is the highest among gynecologic cancers. Ovarian cancer symptoms are often vague during the early stage, and hence ovarian cancer is rarely diagnosed in its early stages. By the time the diagnosis is made, it is usually quite advanced and the tumor has often spread beyond the ovaries. To be specific, about 90 percent of ovarian cancer cases develop from epithelial cells, and up to 70 percent of epithelial ovarian cancer cases are diagnosed at stage III or IV.

If treated early, ovarian cancer may be curable； for women diagnosed with stage I ovarian cancer, the 10-year survival rate is close to 90％. In contrast, the five-year survival rate for women in stage III or IV is only about 15％-20％. Accordingly, a suitable method for screening women for early stage ovarian cancer would be of great benefit. Current tests for screening ovarian cancer include, BRCA testing, transvaginal ultrasonography and serum cancer antigen (CA) –125 testing. However, BRCA testing is primarily used for prognosis. On the other hand, transvaginal ultrasonography and CA-125 testing have a high false-positive rate (about 10％) , thereby leading to unneeded oophorectomy that may cause major complications. As a result, in 2012, the U.S. Preventive Service Task Force recommended against screening for ovarian cancer in asymptomatic, average-risk women using serum CA-125 testing and transvaginal ultrasonography for the harms caused by these screening procedures outweigh the benefits.

In view of the foregoing, there exists a need in the related art for providing methods for use in the diagnosis of gynecologic tumor.

SUMMARY

The following presents a simplified summary of the disclosure in order to provide a basic understanding to the reader. This summary is not an extensive overview of the disclosure and it does not identify key/critical elements of the present invention or delineate the scope of the present invention. Its sole purpose is to present some concepts disclosed herein in a simplified form as a prelude to the more detailed description that is presented later.

In the first aspect, the present invention is directed to a method for assessing whether a subject has a gynecologic neoplasm, whether benign or malignant.

According to one embodiment of the present disclosure, the method comprises the following steps:

(a) obtaining a sample from the subject；

(b) determining the methylation state of at least one target gene in the sample, wherein the at least one target gene is selected from the group consisting of, ADAMTS16 (SEQ ID NO. 1) , APBB1 IP (SEQ ID NO. 4) , CBLN4 (SEQ ID NO. 7) , CCDC140 (SEQ ID NO. 10) , CELF4 (SEQ ID NO. 11) , CNTNAP5 (SEQ ID NO. 14) , EFS (SEQ ID NO. 17) , EMILIN1 (SEQ ID NO. 18) , FERD3L (SEQ ID NO. 23) , FEZF2 (SEQ ID NO. 24) , GALNTL6 (SEQ ID NO. 28) , GRIA4 (SEQ ID NO. 30) , NEFL (SEQ ID NO. 44) , PARP15 (SEQ ID NO. 49) , PAX6 (SEQ ID NO. 50) , PRLHR (SEQ ID NO. 56) , SSTR1 (SEQ ID NO. 64) , ST8SIA5 (SEQ ID NO. 65) , VWC2 (SEQ ID NO. 73) , ZNF300 (SEQ ID NO. 77) , ZNF334 (SEQ ID NO. 78) , ZNF662 (SEQ ID NO. 79) , CCDC105 (SEQ ID NO. 9) , CYP26C1 (SEQ ID NO. 16) , HORMAD2 (SEQ ID NO. 32) , IFFO1 (SEQ ID NO. 33) , LOC100130872 (SEQ ID NO. 39) , NKAPL (SEQ ID NO. 45) , PCDHGA11 (SEQ ID NO. 52) , SLC25A2 (SEQ ID NO. 63) , TCTEX1 D1 (SEQ ID NO. 68) , TMEM101 (SEQ ID NO. 70) , TRIM61 (SEQ ID NO. 71) , WDR69 (SEQ ID NO. 74) , AOX1 (SEQ ID NO. 2) , CACNA2D4 (SEQ ID NO. 6) , COL6A3 (SEQ ID NO. 81) , CPEB1 (SEQ ID NO. 82) , FAM101A (SEQ ID NO. 19) , FAM115A (SEQ ID NO. 20) , FBXL22 (SEQ ID NO. 22) , FIGLA (SEQ ID NO. 25) , FLJ32255 (SEQ ID NO. 26) , FOXB2 (SEQ ID NO. 27) , GIGYF1 (SEQ ID NO. 29) , GSX1 (SEQ ID NO. 21) , KIAA1731 NL (SEQ ID NO. 34) , LBX2 (SEQ ID NO. 35) , LINC00925 (SEQ ID NO. 36) , LINC01210 (SEQ ID NO. 37) , LINC01475 (SEQ ID NO. 38) , LOC283692 (SEQ ID NO. 40) , LOC440982 (SEQ ID NO. 41) , MIR124-2HG (SEQ ID NO. 42) , MKX (SEQ ID NO. 43) , NRN1 (SEQ ID NO. 47) PFN3 (SEQ ID NO. 53) , PHOX2A (SEQ ID NO. 54) , PIP4K2A (SEQ ID NO. 55) , PYGO1 (SEQ ID NO. 57) , SKOR1 (SEQ ID NO. 61) , SKOR2 (SEQ ID NO. 62) , TBX15 (SEQ ID NO. 66) , TBX5-AS1 (SEQ ID NO. 67) , UCKL1 (SEQ ID NO. 72) , WDR86 (SEQ ID NO. 75) , ZDHHC19 (SEQ ID NO. 76) , APBA1 (SEQ ID NO. 3) , CACNA1A (SEQ ID NO. 5) , CBS (SEQ ID NO. 8) , CIDEB (SEQ ID NO. 12) , CKB (SEQ ID NO. 13) , COLQ (SEQ ID NO. 15) , FAM49B (SEQ ID NO. 21) , NR5A2 (SEQ ID NO. 46) , OSBPL2 (SEQ ID NO. 48) , PCDH17 (SEQ ID NO. 51) , RYK (SEQ ID NO. 58) , SDPR (SEQ ID NO. 59) , SKIL (SEQ ID NO. 60) , TEAD1 (SEQ ID NO. 69) , and ZNF669 (SEQ ID NO. 80) ；

(c) determining whether the at least one target gene is hypermethylated； and

(d) assessing whether the subject has the gynecologic neoplasm based on the result of the step (c) , wherein the hypermethylation of the at least one target gene indicates that the subject has the gynecologic neoplasm.

According to some embodiments of the present disclosure, the at least one target gene is selected from the group consisting of, ADAMTS16, APBB1 IP, CBLN4, CCDC140, CELF4, CNTNAP5, EMILIN1, FERD3L, FEZF2, GALNTL6, GRIA4, NEFL, PAX6, PRLHR, SSTR1, ST8SIA5, VWC2, ZNF300, ZNF334, ZNF662, CCDC105, CYP26C1, HORMAD2, IFFO1, LOC100130872, NKAPL, PCDHGA11, SLC25A2, TCTEX1 D1, TMEM101, TRIM61 and WDR69.

According to some embodiments of the present disclosure, the at least one target gene is selected from the group consisting of, AOX1, CACNA2D4, CBLN4, CCDC140, CYP26C1, EMILIN1, FAM101A, FAM115A, FBXL22, FIGLA, FLJ32255, FOXB2, GIGYF1, GSX1, KIAA1731 NL, LBX2, LINC00925, LINC01210, LINC01475, LOC283692, LOC440982, MIR124-2HG, MKX, NRN1, PCDHGA11, PFN3, PHOX2A, PIP4K2A, PRLHR, PYGO1, SKOR1, SKOR2, TBX5-AS1, UCKL1, WDR86, ZDHHC19, APBA1, CACNA1A, CBS, CIDEB, CKB, COLQ, FAM49B, NR5A2, OSBPL2, PCDH17, RYK, SDPR, SKIL, TEAD1 and ZNF669.

According to various embodiments of the present disclosure, the sample is a sample obtained from a subject, preferably a human subject, or present within a subject, preferably a human subject, including a tissue, tissue sample, or cell sample (e.g., a tissue biopsy, for example, an aspiration biopsy, a brush biopsy, a surface biopsy, a needle biopsy, a punch biopsy, an excision biopsy, an open biopsy, an incision biopsy an endoscopic biopsy, cervical scraping cells, uterus scraping cells or a vaginal lavage) , tumor, tumor sample, or biological fluid (e.g., peritoneal fluid, blood (including plasma) , serum, lymph, spinal fluid) . According to certain working examples of the present disclosure, the sample is derived from the ovarian tissue, cell samples (e.g., cervical scraping cells) and body fluid (e.g., serum and plasma) of the subject.

In the second aspect, the present disclosure is directed to a method for assessing whether a subject has a malignant endometrial cancer.

(a) obtaining a sample from the subject；

(b) determining the methylation state of at least one target gene in the sample, wherein the at least one target gene is selected from the group consisting of, ADAMTS16, APBB1 IP, CBLN4, CCDC140, CELF4, CNTNAP5, EFS, EMILIN1, FERD3L, FEZF2, GALNTL6, GRIA4, NEFL, PARP15, PAX6, PRLHR, SSTR1, ST8SIA5, VWC2, ZNF300, ZNF334, ZNF662, CCDC105, CYP26C1, HORMAD2, IFFO1, LOC100130872, NKAPL, PCDHGA11, SLC25A2, TCTEX1 D1, TMEM101, TRIM61 and WDR69；

(c) determining whether the at least one target gene is hypermethylated； and

(d) assessing whether the subject has the malignant endometrial cancer based on the result of the step (c) , wherein the hypermethylation of the at least one target gene indicates the subject has the malignant endometrial cancer.

According to some embodiments of the present disclosure, the at least one target gene is selected from the group consisting of, APBB1 IP, CELF4, EFS, FEZF2, GRIA4, NEFL, PAX6, FERD3L, SSTR1, ZNF300, ZNF334 and ZNF662.

According to some embodiments of the present disclosure, the at least one target gene is selected from the group consisting of, CELF4, FERD3L, FEZF2, EFS, PARP15, ZNF300, ZNF334 and ZNF662.

According to some embodiments of the present disclosure, the at least one target gene is selected from the group consisting of, ZNF300, ZNF334 and ZNF662.

According to some embodiments of the present disclosure, the at least one target gene is selected from the group consisting of, EFS, FEZF2 and ZNF300.

According to some embodiments of the present disclosure, in the step (b) , the methylation states of two or all of EFS, FEZF2 and ZNF300 are determined.

According to some embodiments of the present disclosure, the at least one target gene is selected from the group consisting of, CELF4, EFS, ZNF334 and ZNF662.

According to some embodiments of the present disclosure, in the step (b) , the methylation states of two, three or all of CELF4, EFS, ZNF334 and ZNF662 are determined.

According to various embodiments of the present disclosure, the sample is a sample obtained from a subject, preferably a human subject, or present within a subject, preferably a human subject, including a tissue, tissue sample, or cell sample (e.g., a tissue biopsy, for example, an aspiration biopsy, a brush biopsy, a surface biopsy, a needle biopsy, a punch biopsy, an excision biopsy, an open biopsy, an incision biopsy, an endoscopic biopsy, cervical scraping cells, uterus scraping cells or a vaginal lavage) , tumor, tumor sample, or biological fluid (e.g., peritoneal fluid, blood (including plasma) , serum, lymph, spinal fluid) . According to certain working examples of the present disclosure, the sample is derived from the ovarian tissue, cell samples (e.g., cervical scraping cells) and body fluid (e.g., serum and plasma) of the subject.

In the third aspect, the present disclosure is directed to a method for assessing whether a subject has an ovarian neoplasm.

(a) obtaining a sample from the subject；

(b) determining the methylation state of at least one target gene in the sample, wherein the at least one target gene is selected from the group consisting of, AOX1, CACNA2D4, CBLN4, CCDC140, COL6A3, CPEB1, CYP26C1, EMILIN1, FAM101A, FAM115A, FBXL22, FIGLA, FLJ32255, FOXB2, GIGYF1, GSX1, KIAA1731 NL, LBX2, LINC00925, LINC01210, LINC01475, LOC283692, LOC440982, MIR124-2HG, MKX, NRN1, PCDHGA11, PFN3, PHOX2A, PIP4K2A, PRLHR, PYGO1, SKOR1, SKOR2, TBX15, TBX5-AS1, UCKL1, WDR86, ZDHHC19, APBA1, CACNA1A, CBS, CIDEB, CKB, COLQ, FAM49B, NR5A2, OSBPL2, PCDH17, RYK, SDPR, SKIL, TEAD1 and ZNF669；

(c) determining whether the at least one target gene is hypermethylated； and

(d) assessing whether the subject has the ovarian neoplasm based on the result of the step (c) , wherein the hypermethylation of the at least one target gene indicates that subject has the ovarian neoplasm.

According to some embodiments of the present disclosure, the hypermethylation of the at least one target gene indicates that the ovarian neoplasm is malignant, wherein the at least one target gene is selected from the group consisting of, AOX1, CACNA2D4, CBLN4, CCDC140, COL6A3, CPEB1, CYP26C1, EMILIN1, FAM101A, FAM115A, FBXL22, FIGLA, FLJ32255, FOXB2, GIGYF1, GSX1, KIAA1731 NL, LBX2, LINC00925, LINC01210, LINC01475, LOC283692, LOC440982, MIR124-2HG, MKX, PCDHGA11, PFN3, PHOX2A, PIP4K2A, PRLHR, PYGO1, SKOR1, SKOR2, TBX5-AS1, UCKL1, WDR86, ZDHHC19, APBA1, CACNA1A, CBS, CIDEB, CKB, COLQ, FAM49B, NR5A2, OSBPL2, PCDH17, RYK, SDPR, SKIL, TEAD1 and ZNF669.

According to some embodiments of the present disclosure, the at least one target gene is selected from the group consisting of, AOX1, FAM115A, NRN1, PCDHGA11, PHOX2A, PYGO1, TBX15, UCKL1 and WDR86.

According to some embodiments of the present disclosure, the at least one target gene is NRN1, TBX15, or both.

According to some embodiments of the present disclosure, the at least one target gene is selected from the group consisting of, FEZF2, PAX6 and ZNF662.

According to some embodiments of the present disclosure, the at least one target gene is selected from the group consisting of, AOX1, CACNA2D4, COL6A3, CPEB1, FAM115A, NRN1, TBX15, PCDHGA11, PHOX2A, UCKL1, and WDR86.

According to some embodiments of the present disclosure, the at least one target gene is selected from the group consisting of, NRN1, AOX1, TBX15, and COL6A3.

In the fourth aspect, the present invention is directed to a method for assessing whether a subject has an ovarian neoplasm and the malignancy thereof.

According to one embodiment of the present invention, the method comprises the following steps:

(a) obtaining a sample from the subject；

(b) determining the methylation state of at least one target gene in the sample, wherein the at least one target gene is selected from the group consisting of, NRN1, AOX1, TBX15, COL6A3 and WDR86；

(c) determining whether the at least one target gene is hypermethylated； and

(d) assessing whether the subject has the ovarian neoplasm and the malignancy thereof based on the result of the step (c) , wherein the hypermethylation of the at least one target gene indicates that the subject has the ovarian neoplasm； and the hypermethylation of AOX1, WDR86 or both indicates that the ovarian neoplasm is malignant.

Optionally, the step of determining the methylation state of a gene, as described in the above-mentioned aspects/embodiments of the present disclosure, can be achieved by performing methylation-specific polymerase chain reaction (MSP) , quantitative methylation-specific polymerase chain reaction (qMSP) , bisulfite sequencing (BS) , bisulfite pyrosequencing, microarrays, mass spectrometry, denaturing high-performance liquid chromatography (DHPLC) , pyrosequencing, methylated DNA immunoprecipitation (MeDIP or mDIP) coupled with quantitative polymerase chain reaction, methylated DNA immunoprecipitation sequencing (MeDIP-seq) , or nanopore sequencing.

Many of the attendant features and advantages of the present disclosure will becomes better understood with reference to the following detailed description considered in connection with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

The present description will be better understood from the following detailed description read in light of the accompanying drawings, where:

Figure 1 summarizes the methylation levels of twelve candidates genes in the endometrial tissue specimens according to one embodiment of the present disclosure；

Figure 2 summarizes the methylation levels of twelve candidates genes in the cervical scraping specimens according to one embodiment of the present disclosure；

Figure 3 summarizes the DNA methylation using individual cervical scrapings for endometrial cancer detection according to one embodiment of the present disclosure；

Figure 4 provides area under the curve (AUC) of three gene combinations for detection endometrial cancer detection using cervical scrapings according to one embodiment of the present disclosure；

Figure 5 summarizes the methylation levels of nine candidates genes in the ovarian tissue specimens according to one embodiment of the present disclosure；

Figure 6 summarizes the DNA methylation level in cervical scrapings from patient diagnosed with ovarian malignant tumor and normal ovary according to one embodiment of the present disclosure；

Figure 7 summarizes the high methylation of NRN1 and TBX15 show in myoma, benign and malignant ovarian tumor according to one embodiment of the present disclosure；

Figure 8 summarizes the results of cross-testing of candidate genes in other gynecological cancers according to one embodiment of the present disclosure； and

Figures 9A to 11 D are drawings summarizing the specificity and sensitivity of some target genes for use in the diagnosis of ovarian neoplasm.

DESCRIPTION

The detailed description provided below in connection with the appended drawings is intended as a description of the present examples and is not intended to represent the only forms in which the present example may be constructed or utilized. The description sets forth the functions of the example and the sequence of steps for constructing and operating the example. However, the same or equivalent functions and sequences may be accomplished by different examples.

For convenience, certain terms employed in the specification, examples and appended claims are collected here. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of the ordinary skill in the art to which this invention belongs.

Unless otherwise required by context, it will be understood that singular terms shall include plural forms of the same and plural terms shall include the singular. Specifically, as used herein and in the claims, the singular forms “a” and “an” include the plural reference unless the context clearly indicates otherwise. Also, as used herein and in the claims, the terms “at least one” and “one or more” have the same meaning and include one, two, three, or more. Furthermore, the phrases “at least one of A, B, and C” , “at least one of A, B, or C” and “at least one of A, B and/or C, ” as use throughout this specification and the appended claims, are intended to cover A alone, B alone, C alone, A and B together, B and C together, A and C together, as well as A, B, and C together.

Notwithstanding that the numerical ranges and parameters setting forth the broad scope of the invention are approximations, the numerical values set forth in the specific examples are reported as precisely as possible. Any numerical value, however, inherently contains certain errors necessarily resulting from the standard deviation found in the respective testing measurements. Also, as used herein, the term “about” generally means within 10％, 5％, 1％, or 0.5％of a given value or range. Alternatively, the term “about” means within an acceptable standard error of the mean when considered by one of ordinary skill in the art. Other than in the operating/working examples, or unless otherwise expressly specified, all of the numerical ranges, amounts, values and percentages such as those for quantities of materials, durations of times, temperatures, operating conditions, ratios of amounts, and the likes thereof disclosed herein should be understood as modified in all instances by the term “about. ” Accordingly, unless indicated to the contrary, the numerical parameters set forth in the present disclosure and attached claims are approximations that can vary as desired. At the very least, each numerical parameter should at least be construed in light of the number of reported significant digits and by applying ordinary rounding techniques. Ranges can be expressed herein as from one endpoint to another endpoint or between two endpoints. All ranges disclosed herein are inclusive of the endpoints, unless specified otherwise.

Throughout the present disclosure, the term “assessing” refers to a process in which the health status of a subject is determined. The health status of the subject may indicate a diagnosis, prognosis, or increased risk of a gynecologic neoplasm in said subject.

As used herein, the term “diagnosis” refers to the identification of a pathological state, disease, or condition, such as neoplasms of various gynecologic tissue origins, including, cervix, ovary, endometrium/uterus, vagina, vulvar, uterus, and peritoneum lining the uterus. In some cases, the term diagnosis also refers to distinguishing between the malignant and benign neoplasms. In some other cases, the term diagnosis refers to distinguishing between the malignant neoplasm and normal tissues.

The term "prognosis" as used herein refers to the prediction of the likelihood of cancer-attributable death or progression, including any of, the recurrence rate and metastatic spread of a neoplastic disease, and the recurrence-free survival time, progression-free time, or the overall survival time of a subject diagnosed with a neoplastic disease. According to certain embodiments of the present application, the term "prognosis" concerns an estimation of the recurrence-free survival (RFS) , progression-free survival (PFS) , or overall survival (OS) . Further, the term "poor prognosis” as used herein means that a subject’s chance of having a given remaining expectancy of life is substantially decreased, as compared with another subject who has a normal methylation profile of one or more markers identified herein. In some instance, a subject with a poor RFS suggests that the subject’s RFS time may be less than 12 or 24 months. Similarly, a poor overall or progression-free survival indicates that the subject’s OS or PFS time may be less than 12 or 24 months. Alternatively, a poor RFS or PFS may suggest that the subject has a higher probability of experiencing tumor recurrence or progression during a given time period, as compared with a reference subject group.

Throughout the present disclosure, the term "neoplasm" refers to a new and abnormal growth of cells or a growth of abnormal cells that reproduce faster than normal. A neoplasm creates an unstructured mass (atumor) , which can be either benign or malignant. The term "benign" refers to a neoplasm or tumor that is noncancerous, e.g. its cells do not invade surrounding tissues or metastasize to distant sites； whereas the term "malignant" refers to a neoplasm or tumor that is metastatic, invades contiguous tissue or no longer under normal cellular growth control.

As used herein, the term "cancer" refers to all types of cancer, or malignant neoplasm or tumor found in animals. The methods according to various embodiments of the present disclosure are directed to the diagnosis one or more carcinoma of gynecologic origin. The term "carcinoma" refers to a malignant tumor originating from epithelial cells. Exemplary gynecologic carcinomas of embodiments of the present disclosure include, but are not limited to, ovarian cancer, cervical cancer, endometrial cancer, vaginal cancer, vulvar cancer, and primary peritoneal cancer.

The term "methylation" as used herein, refers to the covalent attachment of a methyl group at the C5-position of cytosine within the CpG dinucleotides of the core promoter region of a gene. The term "methylation state" refers to the presence or absence of 5-methyl-cytosine (5-mCyt) at one or a plurality of CpG dinucleotides within a gene or nucleic acid sequence of interest. As used herein, the term “methylation level” refers to the amount of methylation in one or more copies of a gene or nucleic acid sequence of interest. The methylation level may be calculated as an absolute measure of methylation within the gene or nucleic acid sequence of interest. Also, a “relative methylation level” may be determined as the amount of methylated DNA, relative to the total amount DNA present or as the number of methylated copies of a gene or nucleic acid sequence of interest, relative to the total number of copies of the gene or nucleic acid sequence. Additionally, the “methylation level” can be determined as the percentage of methylated CpG sites within the DNA stretch of interest.

As used herein, the term "methylation profile" refers to a set of data representing the methylation level of one or more target genes in a sample of interest. In some embodiments, the methylation profile is compared to a reference methylation profile derived from a known type of sample (e.g., cancerous or noncancerous samples or samples from different stages of cancer) .

As used herein, the term "differential methylation" refers to a difference in the methylation level of one or more target genes in one sample or group, as compared with the methylation level of said one or more target genes in another sample or group. The differential methylation can be classified as an increased methylation ( "hypermethylation" ) or a decreased methylation ( "hypomethylation" ) . As used herein, the term "hypermethylation" of a target gene in a test sample refers to an increased methylation level of at least 10％, relative to the average methylation level of the target gene in a reference sample. According to various embodiments of the present disclosure, the increased methylation level may be at least 15, 20, 25, 30, 35, 40, 45, or 50％.

As could be appreciated, all the genes or polynucleotide sequences described herein respectively comprise their variants that have at least 75％nucleotide sequence identity to the named genes or polynucleotide sequences. Further, the target gene sequences also encompass the bisulfite conversion nucleotide sequence thereof. Accordingly, unless otherwise expressly specified, all of the genes or polynucleotide sequences described herein should be understood as modified in all instances by the phrase “and a bisulfite conversion nucleotide sequence thereof, and a polynucleotide sequence having at least 75％nucleotide sequence identity to said gene or said bisulfite conversion nucleotide sequence. ”

“Percentage (％) nucleotide sequence identity” with respect to a gene or nucleotide sequence identified herein is defined as the percentage of nucleotide residues in a candidate sequence that are identical with the nucleotide residues in the referenced polynucleotide sequence, after aligning the sequences and introducing gaps, if necessary, to achieve the maximum percent sequence identity, and not considering any conservative substitutions as part of the sequence identity. Alignment for purposes of determining percentage sequence identity can be achieved in various ways that are within the skill in the art, for instance, using publicly available computer software such as BLAST, BLAST-2, ALIGN or Megalign (DNASTAR) software. Those skilled in the art can determine appropriate parameters for measuring alignment, including any algorithms needed to achieve maximal alignment over the full length of the sequences being compared. The percentage nucleotide sequence identity of a given polynucleotide sequence A to a referenced polynucleotide sequence B (which can alternatively be phrased as a given polynucleotide sequence A that has a certain ％nucleotide sequence identity to a referenced polynucleotide sequence B) is calculated by the formula as follows:

where X is the number of nucleotide residues scored as identical matches by the sequence alignment program BLAST in that program's alignment of A and B, and where Y is the total number of nucleotide residues in A or B, whichever is shorter.

[1] The terms “subject” and “patient” are used interchangeably herein and are intended to mean an animal including the human species that can be subjected to the diagnosis methods of the present invention. Accordingly, the term “subject” or “patient” comprises any mammal, which may benefit from the method of the present disclosure. The term “mammal” refers to all members of the class Mammalia, including humans, primates, domestic and farm animals, such as rabbit, pig, sheep, and cattle； as well as zoo, sports or pet animals； and rodents, such as mouse and rat. The term “non-human mammal” refers to all members of the class Mammalis except human. In one exemplary embodiment, the patient is a human.

The term “sample” used herein comprises any samples obtained from a patient. According to embodiments of the present disclosure, the sample contains DNA molecules and the methylation level thereof can be determined. Examples of such body samples include, but are not limited to, blood, smears, sputum, urine, stool, liquor, bile, gastrointestinal secretions, lymph fluid, osteosarcoma marrow, organ aspirates and organ or tissue biopsies. These body samples can be obtained from the patient by routine measures known to persons having ordinary skill in the art. Further, persons having ordinary skill in the art are also familiar with methods and reagents for the DNA isolation from the sample, e.g. extraction with phenol/chloroform or by means of commercial kits.

The present disclosure is based, at least in part, on the finding that differential methylation (in particular, hypermethylation) of one or more target genes, as identified hereinbelow, relates to the tumor progression, or the absence thereof, in a subject. Accordingly, these target genes, alone or in combination, can be used as biomarkers for the prediction of risk or susceptibility of a subject developing a neoplasm, the determination of the malignancy of the neoplasm, and/or making prognosis of the patient being diagnosed with said neoplasm. Further, the methylation profile of relevant genes of the patient can be used as a guide for tailoring suitable therapy regime individually. For example, for patients with one or more hypermethylated target genes listed herein, de-methylation agents or other epigenetic drugs can be administered to the patients to treat the neoplasm.

In view of the foregoing, the present disclosure provides various diagnostic and/or prognostic methods, which will be separately addressed below. For example, all methods involve the determination of the methylation state or methylation level of at least one target gene. Hence, the steps common to most, if not all, claimed methods are first described in the following paragraph. [0067]According to various aspects and/or embodiments of the present disclosure, for methods that involves a live subject, common steps include, at least, a sampling step (a) , in which a biological sample is obtained from the subject； at least one methylation determination step (b) , in which the methylation state of at least one target gene in the sample is determined； and at least one determining step (c) , in which the presence or absence of hypermethylation of said at least one target gene is determined. As to methods that are directly practiced on biological samples, such as tissue biopsy samples, cervical scraping cells, and body fluid samples (e.g., blood or urine) , the afore-mentioned sampling step (a) is omitted. The methylation profile thus obtained is then used in making the diagnostic assessments, as respectively described below in connection with each aspect and representative embodiments of the present disclosure.

Regarding the step (b) , the methylation state is determined using qMSP or bisulfite pyrosequencing, according to working examples provided below. However, as could be appreciated, the present method is not limited to the methods described above； rather, the scope of the claimed invention encompasses the use of other equivalent methods for quantitatively determining the methylation state or level of a particular gene. Further, the above-mentioned methods and equivalents thereof are also applicable to the embodiments described hereinbelow, hence, the method suitable for determining the methylation state or methylation level of the gene is not repeated in the following aspects/embodiments, for the sake of brevity.

In the first aspect, the present disclosure provides a method for assessing whether a subject has a gynecologic neoplasm, which comprises the common steps (a) , (b) and (c) as described above, and an assessement step (d) , in which the presence or absence of the gynecologic neoplasm in the subject is determined based on the result of the step (c) . Specifically, the hypermethylation of the at least one target gene indicates that the subject has the gynecologic neoplasm. According to some embodiments of the present disclosure, the absence of the hypermethylation of the at least one target gene indicates that the subject does not have the gynecologic neoplasm or the gynecologic neoplasm is benign.

According to various embodiments of the present disclosure, the at least one target gene is selected from the group consisting of, ADAMTS16, APBB1 IP, CBLN4, CCDC140, CELF4, CNTNAP5, EFS, EMILIN1, FERD3L, FEZF2, GALNTL6, GRIA4, NEFL, PARP15, PAX6, PRLHR, SSTR1, ST8SIA5, VWC2, ZNF300, ZNF334, ZNF662, CCDC105, CYP26C1, HORMAD2, IFFO1, LOC100130872, NKAPL, PCDHGA11, SLC25A2, TCTEX1 D1, TMEM101, TRIM61, WDR69, AOX1, CACNA2D4, COL6A3, CPEB1, FAM101A, FAM115A, FBXL22, FIGLA, FLJ32255, FOXB2, GIGYF1, GSX1, KIAA1731 NL, LBX2, LINC00925, LINC01210, LINC01475, LOC283692, LOC440982, MIR124-2HG, MKX, NRN1 PFN3, PHOX2A, PIP4K2A, PYGO1, SKOR1, SKOR2, TBX15, TBX5-AS1, UCKL1, WDR86, ZDHHC19, APBA1, CACNA1A, CBS, CIDEB, CKB, COLQ, FAM49B, NR5A2, OSBPL2, PCDH17, RYK, SDPR, SKIL, TEAD1, and ZNF669.

Still optionally, the at least one target gene is selected from the group consisting of, ADAMTS16, APBB1 IP, CBLN4, CCDC140, CELF4, CNTNAP5, EMILIN1, FERD3L, FEZF2, GALNTL6, GRIA4, NEFL, PAX6, PRLHR, SSTR1, ST8SIA5, VWC2, ZNF300, ZNF334, ZNF662, CCDC105, CYP26C1, HORMAD2, IFFO1, LOC100130872, NKAPL, PCDHGA11, SLC25A2, TCTEX1 D1, TMEM101, TRIM61 and WDR69.

Alternatively, the at least one target gene is selected from the group consisting of, AOX1, CACNA2D4, CBLN4, CCDC140, CYP26C1, EMILIN1, FAM101A, FAM115A, FBXL22, FIGLA, FLJ32255, FOXB2, GIGYF1, GSX1, KIAA1731 NL, LBX2, LINC00925, LINC01210, LINC01475, LOC283692, LOC440982, MIR124-2HG, MKX, NRN1, PCDHGA11, PFN3, PHOX2A, PIP4K2A, PRLHR, PYGO1, SKOR1, SKOR2, TBX5-AS1, UCKL1, WDR86, ZDHHC19, APBA1, CACNA1A, CBS, CIDEB, CKB, COLQ, FAM49B, NR5A2, OSBPL2, PCDH17, RYK, SDPR, SKIL, TEAD1 and ZNF669.

In the second aspect, the present disclosure provides a method for assessing whether the subject has a malignant endometrial cancer. The method also comprises the common steps (a) , (b) and (c) as described above, and an assessement step (d) in which the presence of the malignant endometrial cancer in the subject is determined based on the result of the step (c) . In particular, the hypermethylation of the at least one target gene indicates that the subject has the malignant endometrial cancer. According to some embodiments of the present disclosure, the absence of the hypermethylation of the at least one target gene indicates that the subject does not have an endometrial neoplasm or the endometrial neoplasm is benign.

According to various embodiments of the present disclosure, the at least one target gene is selected from the group consisting of, ADAMTS16, APBB1 IP, CBLN4, CCDC140, CELF4, CNTNAP5, EFS, EMILIN1, FERD3L, FEZF2, GALNTL6, GRIA4, NEFL, PARP15, PAX6, PRLHR, SSTR1, ST8SIA5, VWC2, ZNF300, ZNF334, ZNF662, CCDC105, CYP26C1, HORMAD2, IFFO1, LOC100130872, NKAPL, PCDHGA11, SLC25A2, TCTEX1 D1, TMEM101, TRIM61 and WDR69.

According to various embodiments, the at least one target gene is selected from the group consisting of, APBB1 IP, CELF4, EFS, FEZF2, GRIA4, NEFL, PAX6, FERD3L, SSTR1, ZNF300, ZNF334 and ZNF662.

According to various embodiments, the at least one target gene is selected from the group consisting of, CELF4, FERD3L, FEZF2, EFS, PARP15, ZNF300, ZNF334 and ZNF662.

In alternative embodiments, the at least one target gene is selected from the group consisting of, ZNF300, ZNF334 and ZNF662.

Still alternatively, the at least one target gene is selected from the group consisting of, EFS, FEZF2 and ZNF300.

In a third aspect, the present disclosure directs to a method for assessing whether a subject has an ovarian neoplasm. According to various embodiments of the present disclosure, the presence or absence of the ovarian neoplasm is determined based on the result of the step (c) . In particular, the hypermethylation of the at least one target gene indicates that the subject has the ovarian neoplasm.

According to various embodiments, the at least one target gene is selected from the group consisting of, AOX1, CACNA2D4, CBLN4, CCDC140, COL6A3, CPEB1, CYP26C1, EMILIN1, FAM101A, FAM115A, FBXL22, FIGLA, FLJ32255, FOXB2, GIGYF1, GSX1, KIAA1731 NL, LBX2, LINC00925, LINC01210, LINC01475, LOC283692, LOC440982, MIR124-2HG, MKX, NRN1, PCDHGA11, PFN3, PHOX2A, PIP4K2A, PRLHR, PYGO1, SKOR1, SKOR2, TBX15, TBX5-AS1, UCKL1, WDR86, ZDHHC19, APBA1, CACNA1A, CBS, CIDEB, CKB, COLQ, FAM49B, NR5A2, OSBPL2, PCDH17, RYK, SDPR, SKIL, TEAD1 and ZNF669.

In some embodiments, the at least one target gene is selected from the group consisting of, AOX1, CACNA2D4, CBLN4, CCDC140, COL6A3, CPEB1, CYP26C1, EMILIN1, FAM101A, FAM115A, FBXL22, FIGLA, FLJ32255, FOXB2, GIGYF1, GSX1, KIAA1731 NL, LBX2, LINC00925, LINC01210, LINC01475, LOC283692, LOC440982, MIR124-2HG, MKX, PCDHGA11, PFN3, PHOX2A, PIP4K2A, PRLHR, PYGO1, SKOR1, SKOR2, TBX5-AS1, UCKL1, WDR86, ZDHHC19, APBA1, CACNA1A, CBS, CIDEB, CKB, COLQ, FAM49B, NR5A2, OSBPL2, PCDH17, RYK, SDPR, SKIL, TEAD1 and ZNF669.

In the fourth aspect, the present invention is directed to a method for assessing whether a subject has an ovarian neoplasm and whether the ovarian neoplasm is malignant, in which the assessment is based on the hypermethylation of the at least one target gene as determined in the step (c) . [0120]According to various embodiments, the at least one target gene is selected from the group consisting of, NRN1, AOX1, TBX15, COL6A3 and WDR86.

According to an optional embodiment of the present disclosure, the method further comprises an assessment step (d) , in which the hypermethylation of the at least one target gene indicates that the subject has the ovarian neoplasm； and the hypermethylation of AOX1, WDR86 or both indicates that the ovarian neoplasm is malignant.

The following Examples are provided to elucidate certain aspects of the present invention and to aid those of skilled in the art in practicing this invention. These Examples are in no way to be considered to limit the scope of the invention in any manner. Without further elaboration, it is believed that one skilled in the art can, based on the description herein, utilize the present invention fully. All publications cited herein are hereby incorporated by reference in their entirety.

Materials and Methods

1. Tissue Specimens

All tissue specimens were collected from Taipei Medical University-Shuang Ho Hospital, New Taipei, Taiwan. A total of 233 adult subjects were enrolled under the approval of the Institutional Review Board of the Taipei Medical University-Shuang Ho Hospital with written informed consent of the patients.

The ovarian or tumor specimens were obtained during surgery and were frozen immediately in liquid nitrogen and stored at -80℃ until further use. The pathological diagnosis of each sample was confirmed with histological examination by gynecologic pathologists. Normal epithelial ovarian tissue was collected by scraping the ovarian epithelium from patients diagnosed with uterine leiomyoma.

SAMPLING of endometrial tumor specimens and normal endometrial tissue.

To investigate target genes of carnival neoplasm, cervical scraping cells were collected from patients diagnosed with benign ovarian tumor or malignant tumors, and female patients were free of ovarian and cervical diseases at the sampling time. As to endometrial neoplasm, cervical scraping cells were collected from patients diagnosed with myoma or malignant endometrial tumors, and female patients were free of ovarian and cervical diseases at the sampling time. The endocervical scraping cells were collected as follows. Inserting a new endocervical brush into the endocervical canal and gently rotating the brush three to five times to ensure appropriate sampling. The brush was then plunged into a centrifuge tube (15 ml) containing 2 ml

(Ambion, Life technologies, USA) , and closed the cap of the centrifuge tube. The endocervical scraping cells specimens were stored at 4℃. After vortexing for 10 seconds, the swab cells-containing sample was aliquoted into three microcentrifuge tubes (1 ml per tube) , which were stored at -80℃ until further analysis.

In the discovery cohort, 75 malignant ovarian tumor specimens, 20 benign ovarian tumor specimens, and 6 normal ovarian tissue specimens, all from independent patients, were used for investigating the genome-wide methylation profiles. Additionally, for the endometrial neoplasm, public data from The Cancer Genome Atlas (TCGA) data (including 371 malignant endometrial tumor tissues and 46 normal endometrial tissues) and Em-MethylCap-seq (including 80 malignant endometrial tumor tissues and 10 normal endometrial tissues) were used.

In the validation cohort, 20 malignant ovarian tumor specimens, 5 normal ovarian tissue specimens, 15 cervical scrapings collected from subjects with malignant ovarian tumor and 15 cervical scrapings collected from subjects with normal ovary, all from independent patients, were used to validate the differential methylation profiles regarding the ovarian neoplasm. Also, 24 malignant endometrial tumor specimens, 20 normal endometrial tissue specimens, and 31, 40 and 56 cervical scrapings respectively collected from subjects with malignant endometrial tumor, myoma and normal endometrium, all from independent patients, were used to validate the differential methylation profiles regarding the endometrial neoplasm.

To validate the methylation biomarker of abnormal cervical scrapings, 5 scrapings samples from each of the following groups were used: normal, cervical intraepithelial neoplasia 1 (CIN1) , CIN2, CIN3/cervical carcinoma in situ (CIS) or squamous cell carcinoma of the cervix (SCC) .

To validate methylation biomarker of benign tumors (including endometrial hyperplasia, benign ovarian tumors and myoma) , 10 myoma tumor tissues, 10 benign ovarian tumors, 6 cervical scrapings collected from subjects with myoma, 11 cervical scrapings collected from subjects with benign ovarian tumor, and 5 cervical scrapings collected from subjects with endometrial hyperplasia were used.

2. Genome-wild DNA methylomics analysis

2.1. MethylCap Sequencing

Methylated DNA was enriched from 2 μg genomic DNA using the MethylMiner methylated DNA Enrichment Kit (Invitrogen, Carlsbad, CA) following the manufacturer’s instructions. Briefly, genomic DNA was sonicated to about 200-bp, captured by MBD proteins and precipitated using 1 M salt buffer. Enriched methylated DNA was used to generate libraries for sequencing following the standard protocols from Illumina (San Diego, CA) . MethylCap-seq libraries were sequenced using the Illumina Genome Analyzer IIx System. Image analysis and base calling were performed using the standard Illumina pipeline. Unique reads (up to 36-bp reads) were mapped to the human reference genome (hg18) using the ELAND algorithm, with up to two base-pair mismatches.

The uniquely mapped reads were used for additional linear normalization and differential methylation analysis. The methylation level was calculated by accumulating the number of reads using the following Equations 1 and 2.

N_ (Read, i) is the number of normalized reads at the ith bin； U_ (Read, i) is the number of uniquely mapped reads at the ith bin, and N_U is the number of total uniquely mapped reads. “INT” rounds the element to the nearest integers towards minus infinity, “^” means the power operator. A region of methylation level is represented by the average of the normalized of uniquely reads. Comparison of group A and B (G ＝ A or B) , the average methylation level (AVGR, G ) was calculated separately at two groups in a given region R (which includes m bin size, and start at the sth bin) . The number of sample is S_Afor group A, and S_B for group B.

AVG_R, _G means the average methylation level of group G at the R region. M_R, _G is the methylation levels of each sample of group G at the R region. The statistical significance of different methylation at the R region was identified using two-tailed and Mann–Whitney U test (P ≤ 0.001) . Differentially methylated loci were analyzed between case and control samples.

2.2. 450K Methylation Bead Array

TCGA data portal used 450K methylation Chip array to analyze the tissue samples, and the data portal contained datasets from 417 endometrial tissues. Among them, 371 cancer cases with ≥ 40％neoplastic cellularity were chosen for this study. Non-parametric test was used to investigate the differential methylated CpG sites between case and control groups. Probes with P≤ 0.001 and the top 5％differential methylation of high β-values were initially selected. Then, significant probes located within the region spanning -1000 to +1000 relative to the transcription start site of coding genes were identified. Hypermethylated genes with at least five of the identified probes were selected per our selection criteria.

2.3. Preparation of Genomic DNA and Bisulfite Conversion

Genomic DNA was extracted from specimens using QIAmp DNA Mini Kit (QIAGEN GmbH, Hilden, Germany) . The genomic DNA (1 μg) was bisulfite modified using the EZ DNA Methylation Kit (ZYMO RESEARCH, CA, USA) , according to the manufacturer's recommendations, and dissolved in 70 μL of nuclease-free water. The bisulfite DNA was used as the temple for the DNA methylation analysis.

3. Quantitative DNA Methylation Polymerase Chain Reaction

3.1. qMSP

Quantitative methylation-specific PCR (qMSP) using specific probes and primers was performed to identify the relative DNA methylation level by making reference to the un-methylated (COL2A1) total input DNA.

3.2. Bisulfite Pyrosequencing

Bisulfite pyrosequencing was used to quantitate the DNA methylation level, in which the methylation level is expressed as the percentage of methylation (e.g., 0％to 100％) for each CpG site of the pyrosequencing amplicons.

4 Statistics

4.1. Differential Methylation Analysis

Non-parametric test and percentile rank of differential median between two groups were carried out. Mann-Whitney U test was used to test whether the means of two unpaired groups are equal or not. Wilcoxon signed-rank test was used to compare paired samples of two groups.

4.2. AUC

In an independence cohort, the true positive rate (i.e., the sensitivity) was plotted against the false positive rate (that is, 1–specificity) to obtain a receiver operating characteristic (ROC) curve. To assess the best accuracy, the area under the curve (AUC) of the ROC was used to identify the optimal cut-off value for distinguishing two groups of samples. The best accuracy and optimal cut-off value were identified using 100 times of bootstrapping and cloest. left methods of pROC package using R version 3.1.1.

Example 1

Identification of Hypermethylated Genes Associated with Malignant Endometrial Cancer

In the discovery cohort, novel hypermethylated genes in endometrial cancer were identified using datasets from Em-MethyCap-seq and TCGA methylation bead chip. Differential methylation regions (DMRs) , which locate at ±1 kb spanning from the transcription start site (TSS) of each gene were identified. In the first analytic stage, the methylation levels of genes between tumor and normal samples from the Em-MethyCap-seq datasets were compared, thereby identifying 400 genes. Additionally, the methylation levels of genes between tumor and normal samples from the TCGA datasets were compared to identify candidate genes. A total of 466 genes consistently exhibiting high methylation levels are identified from endometrial tumor (n ＝ 372) vs. normal tissue (n ＝ 46) and the same subjects’ (n ＝ 33) tumor vs. normal sample. From these two genome-wide data, 176 consistently high-methylation genes were identified. After filtering with our selection criteria, 56 genes are selected. In the second analytic stage, 70 consistently high-methylation genes are identified from type I endometrial tumor (n ＝ 271) vs. normal (n ＝ 40) and type II endometrial tumor (n ＝ 82) vs. normal (n ＝ 18) . After fitting with further selection criteria, 59 genes are selected. 109 candidate genes were selected from the first and second analytic strategies； among them, 35 genes in which the hypermethylation thereof had never been reported to be associated with malignant endometrial cancer were identified (see, Table 1) . In particular, the accuracy of these 35 genes in distinguishing malignant and non-malignant endometrial tissues is about 75％to 99.04％.

The 35 candidate genes identified in the discovery cohort were subject to further verification in which pooled DNA from normal endometrial tissues (N, n ＝20) and malignant endometrial cancer tissues (T, n ＝ 24) were subject to bisulfite pyrosequencing. The results (Figure 1) indicate that twelve of the candidate genes exhibit significant hypermethylation in malignant endometrial cancer tissues. Said twelve genes are, APBB1 IP, CELF4, EFS, FEZF2, GRIA4, NEFL, PAX6, FERD3L, SSTR1, ZNF300, ZNF334 and ZNF662.

The candidate genes were also subject to further verification in which pooled DNA from cervical scrapings from patient diagnosed with malignant endometrial tumor (Tswab, n ＝ 15) and from subjects with normal endometrial tissues (Nswab, n ＝ 10) were subject to bisulfite pyrosequencing. The results (Figure 2) indicate that the above-mentioned twelve genes are also capable of distinguishing subjects with malignant tumor and normal endometrial tissue using cervical scrapings samples.

Table 1

＊The best accuracy calculated from Em-Methylcap seq data. The threshold is the optimal cut-off calculated from the close. left method of pROC package. The methylation level is higher than threshold is positive. vice versa is negative to compute the sensitivity， specificity and accuracy using data of TCGA 450k methylation array

The methylation profiles of said twelve candidate genes were further investigated. Results provided in Figure 3 indicate that for CELF4, EFS, ZNF334, and ZNF662, the methylation profiles thereof differ among normal subject (N, n ＝ 56) , patients with myoma (M, n ＝ 40) and patients with malignant endometrial cancer tissues (T, n ＝ 31) .

These four genes, namely, CELF4, EFS, ZNF334, and ZNF662 were used in the subsequent independent cohort to determine the best accuracy for the diagnostic and/or prognostic stratification power.

Example 2

Best Accuracy for Distinguishing between Subjects with Benign Endometiral Neoplasm and Malignant Endometiral Neoplasm

In the independent cohort, the ROC graph was plotted； also, the cut-off point, AUC, and 95％confidence interval (CI) of the four genes identified in Example 1, as well as ZNF200, were determined, and the results are summarized in Table 2 below.

Tale 2

Sen， sensitivity； Spe， specificity； ACC， accuracy； AUC， the area under the receiver operating characteristic (ROC) curve， CI， confidence interval

The data in Table 2 indicates that these five genes (CELF4, EFS, ZNF330, ZNF334, and ZNF662) exhibited significant accuracies (71％to 80.2％) in distinguishing subjects with the normal endometrial tissues (N) from those with malignant endometrial tumor tissues (T) . Further, the AUC values of these five genes are quite close to 1, indicating a better cluster. The four genes with the better accuracy, namely CELF4, EFS, ZNF334, and ZNF662, were selected for subsequent analysis regarding the performance of gene combinations.

Example 3

Best Gene Combinations for Distinguishing between Subjects with Benign Endometiral Neoplasm and Malignant Endometiral Neoplasm

The pROC package was used to identify the best threshold of each gene. The methylation level higher than the threshold was determined to be positive, whereas the methylation level lower than the threshold was determined to be negative. The results, as summarized in Figure 4 indicate that three types of gene combinations resulted in an area under the curve (AUC) value of at least 90％. In particular, the three-gene combinations, CELF4/ZNF662/EFS and CELF4/ZNF662/ZNF334, can be used to distinguish between subjects with malignant endometrial tumor (EC, n ＝ 31) and non-malignant endometrial tumor (including normal (N, n ＝ 56) and myoma (Myo, n ＝ 40) ) with an AUC of 0.95 AUC. The three-gene signatures are better than any single gene.

Example 4

Identification of Hypermethylated Genes Associated with Diagnosis of Ovarian Cancer

In the discovery cohort, novel hypermethylated genes in endometrial cancer were identified using data from Ov-MethyCap sequencing to identify DMRs that locate at ±1 kb spanning from the TSS of each gene. In the first analytic stage, the methylation levels of genes between tumor (n ＝ 75) and normal (n ＝ 10) samples from the Ov-MethyCap-seq datasets were compared, thereby identifying 964 genes. After filtering with our selection criteria, 66 genes were selected. There are four major subtype of ovarian tumor, i.e., serous, endometrioid, mucinous and clear cell type. Accordingly, in the second analytic stage, 124 consistently high-methylation genes present in any two subtypes of the malignant ovarian tumor were identified. After filtering with our further selection criteria, 52 genes were selected. A total of 130 genes were identified； among them, 51 genes in which the hypermethylation thereof had never been reported to be associated with malignant ovarian cancer were identified (see, Table 3) . In particular, the accuracy of these 51 genes in distinguishing malignant and non-malignant ovarian tissues is about 71％to 95.12％.

Table 3

The threshold is the optimal cut-off calculated from the close. left method of pROC package. The methylation level is higher than threshold is positive， vice versa is negative to compute the sensitivity, specificity and accuracy using data of Ov

The 51 candidate genes identified in the discovery cohort were subject to further verification in which pooled DNA from normal ovarian tissues (N, n ＝ 5) and malignant ovarian cancer tissues (T, n ＝ 20) were subject to bisulfite pyrosequencing. The results (Figure 5) indicate that nine of the candidate genes distinguish between the malignant ovarian tumor and normal ovarian tissue. Said nine genes are, AXO1, FAM115A, NRN1, PCDHGA11, PHOX2A, PYGO1, TBX15, UCKL1 and WDR86.

The candidate genes were also subject to further verification in which pooled DNA from cervical scrapings from patient diagnosed with malignant ovarian tumor (Tswab, n ＝ 15) and from subjects with normal ovarian tissues (Nswab, n ＝ 15) were subject to bisulfite pyrosequencing. The results (Figure 6) indicate that the above-mentioned nine genes are also capable of distinguishing subjects with malignant ovarian tumor and normal ovarian tissue using cervical scrapings samples.

The methylation profiles of said nine genes were further investigated. Results provided in Figure 7 indicate that for NRN1 and TBX15, the methylation profiles thereof differ among normal subject (n ＝ 5) , patients with myoma (n ＝ 10) and patients with malignant ovarian cancer tissues (n ＝ 20) using tissue samples. Moreover, the methylation profiles of NRN1 and TBX15 also differ among normal subject (n ＝ 15) , patients with myoma (n ＝ 10) , patients with benign ovarian tumor (n ＝ 10) and patients with malignant ovarian cancer (n ＝ 15) using samples from cervical scrapings.

EXAMPLE 5

CROSSED TEST CANDIATE GENES IN OTHER GYNECOLOGICAL CANCERS

FEZF2, PAX6 and ZNF662 were further investigated for their ability in distinguishing abnormal gynecologic diseases, and the results are summarized in Figure 8 (each symbol represents the data from the pooled DNA of 5 people) . In ovarian tissue samples, FEZF2 and PAX6 respectively exhibited a higher methylation level in the malignant ovarian tumor, as compared with the methylation level in normal ovarian tissue. In scrapings samples, FEZF2 and PAX6 also exhibited a higher methylation in patients with malignant ovarian tumor, cervical intraepithelial neoplasia 3 (CIN3) or squamous cell carcinoma of the cervix (SCC) , as compared with the methylation level of samples from normal subject or those with cervical intraepithelial neoplasia 1 (CIN1) .

EXAMPLE 6

DETERMINATION OF THRESHOLD VALUE

To determine the threshold value for the hypermethylation of the targeted genes, the close. left method of pROC package was used to calculate the optimal cut-off value. When the methylation level of a target gene is higher than the threshold, said target gene is hypermethylated, whereas when the methylation level of a gene is less than the threshold, said gene is not hypermethylated. The sensitivity , specify and accuracy of some target genes were also determined using the data from Ov MethyCap-seq, and the results are summarized in Table 4 below.

Table 4

The threshold values (i.e., the optimal cut-off values) of target genes or target gene combinations capable of distinguishing between the cancerous sample (n ＝ 21) and the normal sample (n ＝ 23) were calculated using the ROC method, and the sensitivity and specificity of these genes or gene combinations were determined using the M-index data from qMSP； the results summarized in Table 5 and Figures 9A to 9D.

Table 5

For distinguishing between the tumorous sample (n ＝ 29) and the normal sample (n ＝ 23) , the threshold values (i.e., the optimal cut-off values) of target genes or target gene combinations were determined using the M-index data from qMSP； the results summarized in Table 6 and Figures 10A to 10D.

Table 6

For distinguishing between the benign tumorous sample (n ＝ 10) and the malignant tumorous sample (n ＝ 19) , the threshold values (i.e., the optimal cut-off values) of target genes or target gene combinations were determined using the M-index data from qMSP； the results summarized in Table 7 and Figures 11A to 11 D.

Table 7

EXAMPLE 7

DIAGNOSIS OF OVARIAN NEOPLASM

In this example, the sample is derived from cervical testing, and the diagnosis procedure was as follows. First, the samples were stratified as positive (i.e., with ovarian neoplasm) when of at least one of NRN1, AOX, TBX15, and COL6A3 was hypermethylated, and negative when none of NRN1, AOX, TBX15, and COL6A3 was hypermethylated (sensitivity 88.5％； specificity 95％) . Then, the positive samples were further stratified as malignant ovarian neoplasm when WDR86 or AOX1, or both was/were hypermethylated, whereas positive samples without hypermethylation of WDR86 and/or AOX1 were stratified as benign ovarian neoplasm (sensitivity 90％； specificity 81.8％) .

It will be understood that the above description of embodiments is given by way of example only and that various modifications may be made by those with ordinary skill in the art. The above specification, examples, and data provide a complete description of the structure and use of exemplary embodiments of the invention. Although various embodiments of the invention have been described above with a certain degree of particularity, or with reference to one or more individual embodiments, those with ordinary skill in the art could make numerous alterations to the disclosed embodiments without departing from the spirit or scope of this invention.

Claims

A method for assessing whether a subject has a gynecologic neoplasm, comprising the steps of,

(a) obtaining a sample from the subject；

(b) determining the methylation state of at least one target gene in the sample, wherein the at least one target gene is selected from the group consisting of, ADAMTS16 (SEQ ID NO. 1) , APBB1IP (SEQ ID NO. 4) , CBLN4 (SEQ ID NO. 7) , CCDC140 (SEQ ID NO. 10) , CELF4 (SEQ ID NO. 11) , CNTNAP5 (SEQ ID NO. 14) , EFS (SEQ ID NO. 17) , EMILIN1 (SEQ ID NO. 18) , FERD3L (SEQ ID NO. 23) , FEZF2 (SEQ ID NO. 24) , GALNTL6 (SEQ ID NO. 28) , GRIA4 (SEQ ID NO. 30) , NEFL (SEQ ID NO. 44) , PARP15 (SEQ ID NO. 49) , PAX6 (SEQ ID NO. 50) , PRLHR (SEQ ID NO. 56) , SSTR1 (SEQ ID NO. 64) , ST8SIA5 (SEQ ID NO. 65) , VWC2 (SEQ ID NO. 73) , ZNF300 (SEQ ID NO. 77) , ZNF334 (SEQ ID NO. 78) , ZNF662 (SEQ ID NO. 79) , CCDC105 (SEQ ID NO. 9) , CYP26C1 (SEQ ID NO. 16) , HORMAD2 (SEQ ID NO. 32) , IFFO1 (SEQ ID NO. 33) , LOC100130872 (SEQ ID NO. 39) , NKAPL (SEQ ID NO. 45) , PCDHGA11 (SEQ ID NO. 52) , SLC25A2 (SEQ ID NO. 63) , TCTEX1D1 (SEQ ID NO. 68) , TMEM101 (SEQ ID NO. 70) , TRIM61 (SEQ ID NO. 71) , WDR69 (SEQ ID NO. 74) , AOX1 (SEQ ID NO. 2) , CACNA2D4 (SEQ ID NO. 6) , COL6A3 (SEQ ID NO. 81) , CPEB1 (SEQ ID NO. 82) , FAM101A (SEQ ID NO. 19) , FAM115A (SEQ ID NO. 20) , FBXL22 (SEQ ID NO. 22) , FIGLA (SEQ ID NO. 25) , FLJ32255 (SEQ ID NO. 26) , FOXB2 (SEQ ID NO. 27) , GIGYF1 (SEQ ID NO. 29) , GSX1 (SEQ ID NO. 21) , KIAA1731NL (SEQ ID NO. 34) , LBX2 (SEQ ID NO. 35) , LINC00925 (SEQ ID NO. 36) , LINC01210 (SEQ ID NO. 37) , LINC01475 (SEQ ID NO. 38) , LOC283692 (SEQ ID NO. 40) , LOC440982 (SEQ ID NO. 41) , MIR124-2HG (SEQ ID NO. 42) , MKX (SEQ ID NO. 43) , NRN1 (SEQ ID NO. 47) , PFN3 (SEQ ID NO. 53) , PHOX2A (SEQ ID NO. 54) , PIP4K2A (SEQ ID NO. 55) , PYGO1 (SEQ ID NO. 57) , SKOR1 (SEQ ID NO. 61) , SKOR2 (SEQ ID NO. 62) , TBX15 (SEQ ID NO. 66) , TBX5-AS1 (SEQ ID NO. 67) , UCKL1 (SEQ ID NO. 72) , WDR86 (SEQ ID NO. 75) , ZDHHC19 (SEQ ID NO. 76) , APBA1 (SEQ ID NO. 3) , CACNA1A (SEQ ID NO. 5) , CBS (SEQ ID NO. 8) , CIDEB (SEQ ID NO. 12) , CKB (SEQ ID NO. 13) , COLQ (SEQ ID NO. 15) , FAM49B (SEQ ID NO. 21) , NR5A2 (SEQ ID NO. 46) , OSBPL2 (SEQ ID NO. 48) , PCDH17 (SEQ ID NO. 51) , RYK (SEQ ID NO. 58) , SDPR (SEQ ID NO. 59) , SKIL (SEQ ID NO. 60) , TEAD1 (SEQ ID NO. 69) , and ZNF669 (SEQ ID NO. 80) ；

(c) determining whether the at least one target gene is hypermethylated； and

(d) assessing whether the subject has the gynecologic neoplasm based on the result of the step (c) , wherein the hypermethylation of the at least one target gene indicates that the subject has the gynecologic neoplasm.
The method of claim 1, wherein the at least one target gene is selected from the group consisting of, ADAMTS16, APBB1IP, CBLN4, CCDC140, CELF4, CNTNAP5, EMILIN1, FERD3L, FEZF2, GALNTL6, GRIA4, NEFL, PAX6, PRLHR, SSTR1, ST8SIA5, VWC2, ZNF300, ZNF334, ZNF662, CCDC105, CYP26C1, HORMAD2, IFFO1, LOC100130872, NKAPL, PCDHGA11, SLC25A2, TCTEX1D1, TMEM101, TRIM61 and WDR69.
The method of claim 1, wherein the at least one target gene is selected from the group consisting of, AOX1, CACNA2D4, CBLN4, CCDC140, CYP26C1, EMILIN1, FAM101A, FAM115A, FBXL22, FIGLA, FLJ32255, FOXB2, GIGYF1, GSX1, KIAA1731NL, LBX2, LINC00925, LINC01210, LINC01475, LOC283692, LOC440982, MIR124-2HG, MKX, NRN1, PCDHGA11, PFN3, PHOX2A, PIP4K2A, PRLHR, PYGO1, SKOR1, SKOR2, TBX5-AS1, UCKL1, WDR86, ZDHHC19, APBA1, CACNA1A, CBS, CIDEB, CKB, COLQ, FAM49B, NR5A2, OSBPL2, PCDH17, RYK, SDPR, SKIL, TEAD1 and ZNF669.
The method of claim 1, wherein the sample is derived from a tissue, cell, tumor, or biological fluid of the subject.
The method of claim 4, wherein the sample is derivedfrom serum or plasma.
The method of claim 4, wherein the sample is derived from cervical scraping cells.
The method of claim 1, wherein the methylation state is measured by methylation-specific polymerase chain reaction (MSP) , quantitative methylation-specific polymerase chain reaction (qMSP) , bisulfite sequencing (BS) , bisulfite pyrosequencing, microarrays, mass spectrometry, denaturing high-performance liquid chromatography (DHPLC) , pyrosequencing, methylated DNA immunoprecipitation (MeDIP or mDIP) coupled with quantitative polymerase chain reaction, methylated DNA immunoprecipitation sequencing (MeDIP-seq) or nanopore sequencing.
The method of claim 1, wherein the gynecologic neoplasm is cervical neoplasm, ovarian neoplasm, endometrial neoplasm, vaginal neoplasm, vulvar neoplasm, gestational trophoblastic disease (GTD) and primary peritoneal neoplasm.
A method for assessing whether the subject has a malignant endometrial cancer, comprising the steps of,

(a) obtaining a sample from the subject；

(b) determining the methylation state of at least one target gene in the sample, wherein the at least one target gene is selected from the group consisting of, ADAMTS16, APBB1IP, CBLN4, CCDC140, CELF4, CNTNAP5, EFS, EMILIN1, FERD3L, FEZF2, GALNTL6, GRIA4, NEFL, PARP15, PAX6, PRLHR, SSTR1, ST8SIA5, VWC2, ZNF300, ZNF334, ZNF662, CCDC105, CYP26C1, HORMAD2, IFFO1, LOC100130872, NKAPL, PCDHGA11, SLC25A2, TCTEX1D1, TMEM101, TRIM61 and WDR69； and

(c) determining whether the at least one target gene is hypermethylated； and

(d) assessing whether the subject has the malignant endometrial cancer based on the result of the step (c) , wherein the hypermethylation of the at least one target gene indicates the subject has the malignant endometrial cancer.
The method of claim 9, wherein the at least one target gene is selected from the group consisting of, APBB1IP, CELF4, EFS, FEZF2, GRIA4, NEFL, PAX6, FERD3L, SSTR1, ZNF300, ZNF334 and ZNF662.
The method of claim 9, wherein the at least one target gene is selected from the group consisting of, CELF4, FERD3L, FEZF2, EFS, PARP15, ZNF300, ZNF334 and ZNF662.
The method of claim 9, wherein the at least one target gene is selected from the group consisting of, ZNF300, ZNF334 and ZNF662.
The method of claim 9, wherein the at least one target gene is selected from the group consisting of, EFS, FEZF2 and ZNF300.
The method of claim 13, wherein in the step (b) , the methylation states of two or all of EFS, FEZF2 and ZNF300 are determined.
The method of claim 9, wherein the at least one target gene is selected from the group consisting of, CELF4, EFS, ZNF334 and ZNF662.
The method of claim 15, wherein in the step (b) , the methylation states of two, three or all of CELF4, EFS, ZNF334 and ZNF662 are determined.
The method of claim 9, wherein the sample is derived from a tissue, cell, tumor, or biological fluid of the subject.
The method of claim 17, wherein the sample is derived from serum or plasma.
The method of claim 17, wherein the sample is derived from cervical scraping cells.
The method of claim 9, wherein the methylation state is measured by methylation-specific polymerase chain reaction (MSP) , quantitative methylation-specific polymerase chain reaction (qMSP) , bisulfite sequencing (BS) , bisulfite pyrosequencing, microarrays, mass spectrometry, denaturing high-performance liquid chromatography (DHPLC) , pyrosequencing, methylated DNA immunoprecipitation (MeDIP or mDIP) coupled with quantitative polymerase chain reaction, methylated DNA immunoprecipitation sequencing (MeDIP-seq) or nanopore sequencing.
A method for assessing whether a subject has an ovarian neoplasm, comprising the steps of,

(a) obtaining a sample from the subject；

(b) determining the methylation state of at least one target gene in the sample, wherein the at least one target gene is selected from the group consisting of, AOX1, CACNA2D4, CBLN4, CCDC140, COL6A3, CPEB1, CYP26C1, EMILIN1, FAM101A, FAM115A, FBXL22, FIGLA, FLJ32255, FOXB2, GIGYF1, GSX1, KIAA1731NL, LBX2, LINC00925, LINC01210, LINC01475, LOC283692, LOC440982, MIR124-2HG, MKX, NRN1, PCDHGA11, PFN3, PHOX2A, PIP4K2A, PRLHR, PYGO1, SKOR1, SKOR2, TBX15, TBX5-AS1, UCKL1, WDR86, ZDHHC19, APBA1, CACNA1A, CBS, CIDEB, CKB, COLQ, FAM49B, NR5A2, OSBPL2, PCDH17, RYK, SDPR, SKIL, TEAD1 and ZNF669； and

(c) determining whether the at least one target gene is hypermethylated； and

(d) assessing whether the subject has the ovarian neoplasm based on the result of the step (c) , wherein the hypermethylation of the at least one target gene indicates that subject has the ovarian neoplasm.
The method of claim 21, wherein,

the at least one target gene is selected from the group consisting of, AOX1, CACNA2D4, CBLN4, CCDC140, COL6A3, CPEB1, CYP26C1, EMILIN1, FAM101A, FAM115A, FBXL22, FIGLA, FLJ32255, FOXB2, GIGYF1, GSX1, KIAA1731NL, LBX2, LINC00925, LINC01210, LINC01475, LOC283692, LOC440982, MIR124-2HG, MKX, PCDHGA11, PFN3, PHOX2A, PIP4K2A, PRLHR, PYGO1, SKOR1, SKOR2, TBX5-AS1, UCKL1, WDR86, ZDHHC19, APBA1, CACNA1A, CBS, CIDEB, CKB, COLQ, FAM49B, NR5A2, OSBPL2, PCDH17, RYK, SDPR, SKIL, TEAD1 and ZNF669； and

the hypermethylation of the at least one target gene indicates that the ovarian neoplasm is malignant.
The method of claim 21, wherein the at least one target gene is selected from the group consisting of, AOX1, FAM115A, NRN1, PCDHGA11, PHOX2A, PYGO1, TBX15, UCKL1 and WDR86.
The method of claim 21, wherein the at least one target gene is NRN1, TBX15, or both.
The method of claim 21, wherein the at least one target gene is selected from the group consisting of, FEZF2, PAX6 and ZNF662.
The method of claim 21, wherein the at least one target gene is selected from the group consisting of, AOX1, CACNA2D4, COL6A3, CPEB1, FAM115A, NRN1, TBX15, PCDHGA11, PHOX2A, UCKL1, and WDR86.
The method of claim 21, wherein the at least one target gene is selected from the group consisting of, NRN1, AOX1, TBX15, and COL6A3.
The method of claim 21, wherein the sample is derived from a tissue, cell, tumor, or biological fluid of the subject.
The method of claim 28, wherein the sample is a serum or plasma sample.
The method of claim 28, wherein the sample is derived from cervical scraping cells.
The method of claim 21, wherein the methylation state is measured by methylation-specific polymerase chain reaction (MSP) , quantitative methylation-specific polymerase chain reaction (qMSP) , bisulfite sequencing (BS) , bisulfite pyrosequencing, microarrays, mass spectrometry, denaturing high-performance liquid chromatography (DHPLC) , pyrosequencing, methylated DNA immunoprecipitation (MeDIP or mDIP) coupled with quantitative polymerase chain reaction, methylated DNA immunoprecipitation sequencing (MeDIP-seq) or nanopore sequencing.
A method for assessing whether a subject has an ovarian neoplasm and the malignancy thereof, comprising the steps of,

(a) obtaining a sample from the subject；

(b) determining the methylation state of at least one target gene in the sample, wherein the at least one target gene is selected from the group consisting of, NRN1, AOX1, TBX15, COL6A3 and WDR86； and

(c) determining whether the at least one target gene is hypermethylated；

(d) assessing whether the subject has the ovarian neoplasm and the malignancy thereof based on the result of the step (c) , wherein the hypermethylation of the at least one target gene indicates that the subject has the ovarian neoplasm； and the hypermethylation of AOX1, WDR86 or both indicates that the ovarian neoplasm is malignant.
The method of claim 32, wherein the sample is derived from a tissue, cell, tumor, or biological fluid of the subject.
The method of claim 33, wherein the sample is a serum or plasma sample.
The method of claim 33, wherein the sample is derived from cervical scraping cells.
The method of claim 32, wherein the methylation state is measured by methylation-specific polymerase chain reaction (MSP) , quantitative methylation-specific polymerase chain reaction (qMSP) , bisulfite sequencing (BS) , bisulfite pyrosequencing, microarrays, mass spectrometry, denaturing high-performance liquid chromatography (DHPLC) , pyrosequencing, methylated DNA immunoprecipitation (MeDIP or mDIP) coupled with quantitative polymerase chain reaction, methylated DNA immunoprecipitation sequencing (MeDIP-seq) or nanopore sequencing.