Compositions and methods for detecting gynecological cancer

Abstract

The present disclosure relates to detecting one or more types of gynecological cancer in a biological sample from a subject. In particular, the present disclosure provides compositions and methods for detecting the presence or absence of one or more types of gynecological cancer (e.g., cervical cancer, ovarian cancer, endometrial cancer) in a biological sample of a subject suffering from or suspected of suffering from gynecological cancer.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to and the benefit of U.S. Provisional Patent Application No. 63 / 374,415, filed September 2, 2022, which is incorporated herein by reference in its entirety for all purposes.

[0003] Electronically Submitted Materials Incorporated by Reference

[0004] Incorporated herein by reference in its entirety is the computer-readable nucleotide / amino acid sequence listing filed concurrently herewith, and identified as follows: a 57,580-byte ASCII (text) file named "40960-601_SEQUENCE_LISTING" created on September 1, 2023. Technical Field

[0005] The present disclosure relates to detecting one or more types of gynecological cancers in a biological sample from a subject. Specifically, the present disclosure provides compositions and methods for detecting the presence or absence of one or more types of gynecological cancers (e.g., cervical cancer, ovarian cancer, endometrial cancer) in a biological sample from a subject having or suspected of having a gynecological cancer. Background Art

[0006] Compared to other types of cancer, such as breast or colon cancer, gynecological cancers are less common, affecting approximately 100,000 women in the United States each year. However, all women are at risk for developing gynecological cancer, and the risk increases with age. The five main types of gynecological cancer are cervical, ovarian, uterine, vaginal, and vulvar. A sixth, extremely rare, type of gynecological cancer is fallopian tube cancer. Among gynecological cancers, despite evidence that early detection is particularly important for improving survival, current clinically relevant screening tests are only for cervical cancer. Because there is no simple and reliable method to screen for many gynecological cancers, recognizing warning signs to reduce risk is particularly important. Furthermore, while gynecological cancer screening programs (e.g., HPV testing, Pap tests) aim to improve survival through early detection, these tests are typically only available for a small subset of the population (e.g., those at highest risk) and are limited to a few cancers (e.g., cervical cancer). As a result, medical professionals often cannot make an accurate cancer diagnosis until symptoms appear, which can be too late for effective treatment. Therefore, there is an urgent need for improved diagnostic tools to detect multiple types or subtypes of gynecological cancers in a single biological sample, thereby providing not only early detection but also more accurate patient stratification and deeper insights into treatment strategies. Summary of the Invention

[0007] Embodiments of the present disclosure provide methods, compositions and systems for screening various types of gynecological cancers from biological samples. According to these embodiments, the present disclosure includes but is not limited to methods and compositions for detecting the presence of various types or subclasses of gynecological cancers from biological samples. In some embodiments, the biological sample is a tissue sample, a blood sample, a plasma sample, a serum sample, a whole blood sample, a secretion sample, an organ secretion sample, a cerebrospinal fluid (CSF) sample, a saliva sample, a urine sample and / or a fecal sample. In some embodiments, the tissue sample is a gynecological tissue sample, which includes one or more of the following: vaginal tissue, vaginal cells, cervical tissue, cervical cells, endometrial tissue, endometrial cells, ovarian tissue and ovarian cells. In some embodiments, the tissue sample is an ovarian tissue sample, an endometrial tissue sample or a cervical tissue sample. In some embodiments, the secretion sample is a gynecological secretion sample. In some embodiments, the subject is a human being.

[0008] As further described herein, embodiments of the present disclosure include novel differentially methylated regions (DMRs), each of which is capable of individually distinguishing a specific type of gynecological cancer, namely endometrial cancer (EC) or ovarian cancer (OC) or cervical cancer (CC), from benign gynecological tissue samples. According to these embodiments, these novel DMRs comprise one or more CpG sites of: ADAM8, ADHFE1, AES, AGBL2, AIM1, AK5, ALKBH3, ARAP1, ARHGAP20, ASCL2, BCAT1, BEGAIN, BEND4_3696, BMP6, C12orf68, C13orf18, C14orf169_7694, C14orf169_8382, C18orf18, C1orf61, C20orf195, C4orf31, C5orf52, C6orf 147, C7orf51, CD14, CELF2, CHCHD5, CHMP2A, CHST10, CLIC6, CLIP4, COL13A1, COL19A1, COL6A2, COPZ2, CREB3L1, CXCL2, CXXC5, CYTH 2. DAB2IP, DGKZ, DLGAP3, DNASE2, DSCAML1, EBF1, EDARADD, EGR2, EIF5A2, ELMO1, ELMOD1, ELOVL4, EME2, EML6, EPSTI1, FADS2, FAM10 9B, FAM126A, FAM174B, FGF18, FKBP11, FLI1, FLOT1, FOXD3, FYN, GAL3ST2, GALR3, GAS7, GATA2_5878, GLT25D2, GNB2, HDAC7, HIC1, HL A-F, HNRNPF, HPDL, HS3ST4, HSPA1A, IDUA, IGSF9B, IL12RB2, IRAK3, IRF7, IRF8, ITPKA, KCNA2, KCNC3_6487, KCNC3_7105, KCNC4, KCN H8, KDM2B, LBX2, LCMT2, LOC100129726, LOC100287216, LOC255130, LOC339290, LOC729678, LPPR3, LRRC41, LRRC8D_8856, LTBP2, LY PLAL1, MAST4, MAX.chr1.2152, HIVEP3, GRAMD1B, MAX.chr11.0394, MAX.chr11.3750, FAT3, SLC16A7, MTUS2, LINC02323, MAX.chr14.7696、MCTP2、LOC107984974、TRIM80P、MAX.chr19.5552、ZNF433-AS1、ZNF254、MAX.chr19.0548、B3GALT1、MAX.chr2.8918、MAX.chr2.4778、MAX.chr20.3853、MAX.chr20.2903、MAX.chr21.5011、DSCR9、MAX.chr22.5665、MAX.chr3.6408、LINC02028、LINC02084、MAX.chr5.3588、CTD-2532K18.1、HS3ST5、ARHGAP18、GRM4、LINC01004、MAX.chr8.5938、MAX.chr9.4007、MAX.chr9.2025, TRPM3, MED12L, MIAT, MLH1_4513, MLH1_5193, MMP16, MRPS21, MSI1, MT1E, MX1, MYC, MYH10, MYO15B, N4BP2L1, NBR1 , NDRG2, NEGR1, NEU1, NOL3, NR3C1_2223, NR3C1_4614, NRP2, NTN1, NTNG1, PAPL, PAQR9, PDE10A, PDE3B, PDE4A, PDXK, PER 1. PISD, PLEC, PLIN2, PLXND1, PPM1E, PPP1R9A, PPP2R5C, PRDM5, PTP4A3, PYCARD, RAB3C, RAI1, RARG, RASA3, RPRM, RREB1 , S100A6, SAMD5, SBNO2, SDC2, SDK2, SELM, SERP2, SFMBT2_2029, SHF, SHH, SLC16A11, SLC16A5, SLC25A22, SLCO3A1, SMTN , SPDYA, SPINK2, SPOCK2, SPON1, SQSTM1_4156, ST8SIA1, TAF4B, TAF7, TEAD3, TERC, TIAM1, TLE4, TMEM101, TMEM106A, TR IM9, TRPC3, TSC22D4, TSPAN2, TSPAN5, TTC14, UBB_4001, UBB_4646, UST, VAMP5, VIM, VSTM2B, ZBTB7B, ZEB2, ZFP3, ZFP36 L2, ZIC2, ZMIZ1, ZNF14, ZNF211, ZNF280B, ZNF302, ZNF382, ZNF480, ZNF483, ZNF491, ZNF569, ZNF610, ZNF702P, ZNF709, ZNF773, ZNF845, ZNF91, CDH4, LRRC34, MAX.chr10.4460, NBPF24, OBSCN, SEPT9, ZNF323, ZNF506, and / or ZNF90 (Table 1), including any combination thereof. In some embodiments, the novel DMR is from any gene or region selected from Table 1, including any combination thereof. Each novel DMR alone is capable of distinguishing one or more gynecological cancers from a control sample, and combining two or more novel DMRs can provide increased sensitivity. Thus, combinations of two or more novel DMRs selected from Table 1 are provided.

[0009] Embodiments of the present disclosure also include novel differentially methylated regions (DMRs), each of which is capable of individually distinguishing gynecological cancers from benign gynecological tissue samples; these DMRs are prevalent in all three types of gynecological cancer (i.e., endometrial cancer (EC), ovarian cancer (OC), and cervical cancer (CC)). According to these embodiments, these novel DMRs comprise one or more CpG sites among the following: ACSF2, AJAP1, ARL10, ARL5C, ASCL4, ATP6V1B1, BARHL1, BEND4_2963, C17orf64, C1QL3, C2orf55, C4orf48, CA3, CDO1, CELF2, CLEC14A, CSDAP1, CYTH2_4197, DLGAP1, DSCR6, EPS8L1_2819, EPS8L1_8496, FAIM2, FGF12, GATA2, H IST1H2BE, IRF4, IRX4, ITGA5, KCNA1, LECT1, LHX1, LOC440925, LPHN1, LINC02767, MAX.chr1.2533, SOX1-OT, MAX.chr13.3357, MAX. chr14.2093, MAX.chr17.2455, MAX.chr18.4390, MAX.chr19.2732, MAX.chr19.4467, PANTR1, MAX.chr2.0490, MAX.chr2.8148, MAX. chr2.3137, RIPOR3, SCRG1, MAX.chr4.4210, HMX1, CTC-359M8.1, MAX.chr5.0931, MAX.chr5.9924, LIN28B, MAX.chr6.9522, TTLL2, RNA5SP243, DLGAP2, MEX3B, MNX1, NEFL, NETO1, PAX2, PDX1, psiTPTE22, RASGEF1A, SALL3_9136, SALL3_0615, SEZ6L2, SHANK2, SHANK 3, SKI, SLC35D3, SORCS3_0305, SORCS3_1038, SOX1, SQSTM1, TBXT, TCERG1L, TERT, TNFSF11, TUBB6, ULBP1, VAC14, VWC2, WDR69, ZBTB16, ZNF132, ZSCAN12, ZSCAN23, KRT86, CYP26C1, GYPC, DIDO1, EEF1A2, EMX2OS, GDF7, JSRP1, SMPD5, MDFI, MPZ, and / or VILL (Table 2), including any combination thereof.In some embodiments, the novel DMR is from any gene or region selected from Table 2, including any combination thereof. Each novel DMR alone is capable of distinguishing one or more gynecological cancers from control samples, and combining two or more novel DMRs can provide increased sensitivity. Thus, a combination of two or more novel DMRs selected from Table 2 is provided.

[0010] Embodiments of the present disclosure also include novel differentially methylated regions (DMRs), each of which is capable of individually distinguishing a specific subclass of gynecological cancer (i.e., serous ovarian cancer, clear cell ovarian cancer, endometrioid ovarian cancer, mucinous ovarian cancer, adenocarcinoma cervical cancer, squamous cervical cancer, or endometrioid endometrial cancer) from benign gynecological tissue samples. According to these embodiments, the novel DMRs comprise one or more CpG sites selected from the group consisting of AIM1, AK5, c18orf18, CDO1, DLGAP1, ELMOD1, FKBP11, FLOT1, GAL3ST2, LRRC41, LYPLAL1, MAX.chr11.3750, MLH1_4513, NR3C1_2223, PISD.RABC3, RAI1, TERC, TRPC3, ZIC2, ZMIZ1, ZNF480, ZNF491, ZNF610, and / or ZNF91 (Table 3), including any combination thereof. In some embodiments, the novel DMRs are from any gene or region selected from Table 3, including any combination thereof. Each novel DMR alone is capable of distinguishing one or more gynecological cancers from a control sample, and combining two or more novel DMRs can provide increased sensitivity. Thus, combinations of two or more novel DMRs selected from Table 3 are provided.

[0011] Embodiments of the present disclosure also include novel differentially methylated regions (DMRs), each of which is capable of individually distinguishing a specific subclass of gynecological cancer (i.e., serous ovarian cancer, clear cell ovarian cancer, endometrioid ovarian cancer, mucinous ovarian cancer, adenocarcinoma cervical cancer, squamous cervical cancer, or endometrioid endometrial cancer) from benign gynecological tissue samples. According to these embodiments, these novel DMRs comprise one or more CpG sites of: LBX2, SPDYA, TERC, ZSCAN12, CYP26C1, and / or GYPC (Table 4), including any combination thereof. In some embodiments, the novel DMRs are from any gene or region selected from Table 4, including any combination thereof. Each novel DMR alone is capable of distinguishing one or more gynecological cancers from a control sample, and combining two or more novel DMRs can provide increased sensitivity. Thus, a combination of two or more novel DMRs selected from Table 4 is provided.

[0012] Embodiments of the present disclosure also include novel differentially methylated regions (DMRs), each of which is capable of individually distinguishing a specific subclass of gynecological cancer (i.e., serous ovarian cancer, clear cell ovarian cancer, endometrioid ovarian cancer, mucinous ovarian cancer, adenocarcinoma cervical cancer, squamous cervical cancer, or endometrioid endometrial cancer) from benign gynecological tissue samples. According to these embodiments, the novel DMRs comprise one or more CpG sites in: KRT86, CDH4, c17orf64, EMX2OS, NBPF24, SFMBT2_0970, JSRP1, DIDO1, MAX.chr10.4460, MPZ, ZNF506, GATA2_6370, VILL, LINC02323, CYTH2_4043, LRRC8D_8831, LYPLAL1, SMPD5, SQSTM1_3864, ZNF323, OBSCN, ZNF90, LRRC34, GDF7, MDFI, EEF1A2, LRRC41 and / or SEPT9 (Table 8), including any combination thereof. In some embodiments, the novel DMRs are from any gene or region selected from Table 8, including any combination thereof. Each novel DMR alone is capable of distinguishing one or more gynecological cancers from control samples, and combining two or more novel DMRs may provide increased sensitivity. Thus, a combination of two or more novel DMRs selected from Table 8 is provided.

[0013] Embodiments of the present disclosure include a method of characterizing a biological sample. According to these embodiments, the method comprises determining a methylation profile in at least one differentially methylated region (DMR) of a DNA sample obtained from a subject having or suspected of having a gynecological cancer by treating the sample with an agent that modifies DNA in a methylation-specific manner.

[0014] In some embodiments, the methylation profile in the at least one DMR indicates that the subject has or is suspected of having at least one of ovarian cancer (OC), cervical cancer (CC), and endometrial cancer (EC).

[0015] In some embodiments, at least one DMR comprises one or more CpG sites of: ADAM8, ADHFE1, AES, AGBL2, AIM1, AK5, ALKBH3, ARAPl, ARHGAP20, ASCL2, BCAT1, BEGAIN, BEND4_3696, BMP6, C12orf68, C13orf18, C14orf169_7694, C14orf169_8382, C18orf18, C1orf61, C20orf195, C4orf31, C5orf52, C6orf147, C7orf51, CD14, CELF2, CCHD5, C HMP2A, CHST10, CLIC6, CLIP4, COL13A1, COL19A1, COL6A2, COPZ2, CREB3L1, CXCL2, CXXC5, CYTH2, DAB2IP, DGKZ, DLGAP3, DNASE2, DSCAML1, EBF1, EDARAD D. EGR2, EIF5A2, ELMO1, ELMOD1, ELOVL4, EME2, EML6, EPSTI1, FADS2, FAM109B, FAM126A, FAM174B, FGF18, FKBP11, FLI1, FLOT1, FOXD3, FYN, GAL3ST2, GA LR3, GAS7, GATA2_5878, GLT25D2, GNB2, HDAC7, HIC1, HLA-F, HNRNPF, HPDL, HS3ST4, HSPA1A, IDUA, IGSF9B, IL12RB2, IRAK3, IRF7, IRF8, ITPKA, KCNA2, K CNC3_6487, KCNC3_7105, KCNC4, KCNH8, KDM2B, LBX2, LCMT2, LOC100129726, LOC100287216, LOC255130, LOC339290, LOC729678, LPPR3, LRRC41, LRRC8D _8856, LTBP2, LYPLAL1, MAST4, MAX.chr1.2152, HIVEP3, GRAMD1B, MAX.chr11.0394, MAX.chr11.3750, FAT3, SLC16A7, MTUS2, LINC02323, MAX.chr14.7 696, MCTP2, LOC107984974, TRIM80P, MAX.chr19.5552, ZNF433-AS1, ZNF254, MAX.chr19.0548, B3GALT1, MAX.chr2.8918, MAX.chr2.4778, MAX.chr20.3853, MAX.chr20.2903, MAX.chr21.5011, DSCR9, MAX.chr22.5665, MAX.chr3.6408, LINC02028, LINC02084, MAX.chr5.3588, CTD-2532K18.1, HS3ST5, ARHGAP18, GRM4, LINC01004, MAX.chr8.5938, MAX.chr9.4007, MAX.chr9.2025, TRPM3, MED12L, MIAT, MLH1_4513, MLH1_5193, MMP16, MRPS21, MSI1, MT1E, MX1, MYC, MYH10, MYO15B, N4BP2L1, NBR1, NDRG2, NEGR1, NEU1, NOL3, NR3C1_2223, NR3C1_4614, NRP2, NTN1, NTNG1, PAPL, PAQR9, PDE10A, PDE3B, PDE4A, PDXK, PER1, PISD, PLEC, PLIN2, PLXND1, PPM1E, PPP1R9A, PPP2R5C, PRDM5, PTP4A3, PYCARD, RAB3C, RAI1, RARG, RASA3, RPRM, RREB1, S100A6, SAMD5, SBNO2, SDC2, SDK2, SELM, SERP2, SFMBT2_2029, SHF, SHH, SLC16A11, SLC16A5, SLC25A22, SLCO3A1, SMTN, SPDYA, SPINK2, SPOCK2, SPON1, SQSTM1_4156, ST8SIA1, TAF4B, TAF7, TEAD3, TERC, TIAM1, TLE4, TMEM101, TMEM106A, TRIM9, TRPC3, TSC22D4, TSPAN2, TSPAN5, TTC14, UBB_4001, UBB_4646, UST, VAMP5, VIM, VSTM2B, ZBTB7B, ZEB2, ZFP3, ZFP36L2, ZIC2, ZMIZ1, ZNF14, ZNF211, ZNF280B, ZNF302, ZNF382, ZNF480, ZNF483, ZNF491, ZNF569, ZNF610, ZNF702P, ZNF709, ZNF773, ZNF845, ZNF91, CDH4, LRRC34, MAX.chr10.4460, NBPF24, OBSCN, SEPT9, ZNF323, ZNF506, and / or ZNF90.

[0016] In some embodiments, at least one DMR comprises one or more CpG sites of: ACSF2, AJAP1, ARL10, ARL5C, ASCL4, ATP6V1B1, BARHL1, BEND4_2963, C17orf64, C1QL3, C2orf55, C4orf48, CA3, CDO1, CELF2, CLEC14A, CSDAP1, CYTH2_4197, DLGAP1, DSCR6, EPS8L1_2819, EPS8L1_8496, FAIM2, FGF12, GATA 2. HIST1H2BE, IRF4, IRX4, ITGA5, KCNA1, LECT1, LHX1, LOC440925, LPHN1, LINC02767, MAX.chr1.2533, SOX1-OT, MAX.chr13.3357, MAX.chr14.2093, MAX.chr17.2455, MAX.chr18.4390, MAX.chr19.2732, MAX.chr19.4467, PANTR1, MAX.chr2.0490, MAX.chr2.814 8. MAX.chr2.3137, RIPOR3, SCRG1, MAX.chr4.4210, HMX1, CTC-359M8.1, MAX.chr5.0931, MAX.chr5.9924, LIN28B, MAX.chr6.952 2. TTLL2, RNA5SP243, DLGAP2, MEX3B, MNX1, NEFL, NETO1, PAX2, PDX1, psiTPTE22, RASGEF1A, SALL3_9136, SALL3_0615, SEZ6L2, SHA NK2, SHANK3, SKI, SLC35D3, SORCS3_0305, SORCS3_1038, SOX1, SQSTM1, TBXT, TCERG1L, TERT, TNFSF11, TUBB6, ULBP1, VAC14, VWC2, WDR69, ZBTB16, ZNF132, ZSCAN12, ZSCAN23, KRT86, CYP26C1, GYPC, DIDO1, EEF1A2, EMX2OS, GDF7, JSRP1, SMPD5, MDFI, MPZ and / or VILL.

[0017] In some embodiments, at least one DMR comprises one or more CpG sites among AIM1, FLOT1, GAL3ST2, LRRC41, LYPLAL1, MAX.chr11.3750, PISD, RAI1, ZIC2, ZMIZ1, CDH4, ZNF506, ZNF323, OBSCN, ZNF90, and / or SEPT9; and the subject has or is suspected of having OC. In some embodiments, at least one DMR comprises one or more CpG sites among AIM1, FLOT1, GAL3ST2, and LYPLAL1 and / or OBSCN; and the subject has or is suspected of having serous OC. In some embodiments, at least one DMR comprises one or more CpG sites among LRRC41, PISD, ZIC2, OBSCN, and / or SEPT9; and the subject has or is suspected of having clear cell OC. In some embodiments, at least one DMR comprises one or more CpG sites in MAX.chr11.3750; and the subject has or is suspected of having endometrioid OC. In some embodiments, at least one DMR comprises one or more CpG sites in RAI1 and / or ZMIZ1; and the subject has or is suspected of having mucinous OC. In some embodiments, determining the methylation profile of one or more CpG sites in AIM1, FLOT1, GAL3ST2, LRRC41, LYPLAL1, MAX.chr11.3750, PISD, RAI1, ZIC2, ZMIZ1, CDH4, ZNF506, ZNF323, OBSCN, ZNF90, and / or SEPT9 comprises comparing the methylation profile to corresponding regions in a control DNA sample obtained from a subject who does not have OC.

[0018] In some embodiments, at least one DMR comprises one or more CpG sites selected from the group consisting of AK5, ELMOD1, RABC3, TRPC3, ZNF480, ZNF491, ZNF610, ZNF91, and / or NBPF24, and the subject has or is suspected of having CC. In some embodiments, at least one DMR comprises one or more CpG sites selected from the group consisting of AK5, ELMOD1, TRPC3, and / or ZNF480, and the subject has or is suspected of having adenocarcinoma CC. In some embodiments, at least one DMR comprises one or more CpG sites selected from the group consisting of ZNF491, ZNF610, ZNF91, and / or NBPF24, and the subject has or is suspected of having squamous cell CC. In some embodiments, determining the methylation profile of one or more CpG sites selected from the group consisting of AK5, ELMOD1, RABC3, TRPC3, ZNF480, ZNF491, ZNF610, and / or ZNF91 comprises comparing the methylation profile to corresponding regions of a control DNA sample obtained from a subject who does not have CC.

[0019] In some embodiments, at least one DMR comprises one or more CpG sites in c18orf18, FKBP11, MLH1, NR3C1, and / or TERC; and the subject has or is suspected of having EC. In some embodiments, at least one DMR comprises one or more CpG sites in MLH1 and / or SEPT9; and the subject has or is suspected of having clear cell EC. In some embodiments, at least one DMR comprises one or more CpG sites in NR3C1; and the subject has or is suspected of having endometrioid EC.

[0020] In some embodiments, determining the methylation profile of one or more CpG sites in c18orf18, FKBP11, MLH1, NR3C1, and / or TERC comprises comparing the methylation profile to corresponding regions of a control DNA sample obtained from a subject not having EC.

[0021] In some embodiments, at least one DMR comprises one or more CpG sites in CDO1 and / or DLGAP1; and wherein the subject has or is suspected of having CC, OC, or EC. In some embodiments, determining the methylation profile of the one or more CpG sites in CDO1 and / or DLGAP1 comprises comparing the methylation profile to corresponding regions in a control DNA sample obtained from a subject who does not have CC, OC, or EC.

[0022] In some embodiments, the method further comprises determining the methylation profile of one or more CpG sites in AIM1, FLOT1, GAL3ST2, LRRC41, LYPLAL1, MAX.chr11.3750, PISD, RAI1, ZIC2, and / or ZMIZ1. In some embodiments, the method further comprises determining the methylation profile of one or more CpG sites in AK5, ELMOD1, RABC3, TRPC3, ZNF480, ZNF491, ZNF610, and / or ZNF91. In some embodiments, the method further comprises determining the methylation profile of one or more CpG sites in c18orf18, FKBP11, MLH1, NR3C1, and / or TERC.

[0023] In some embodiments, at least one DMR comprises one or more CpG sites in NBPF24, and wherein the subject has or is suspected of having CC. In some embodiments, determining the methylation profile of the one or more CpG sites in NBPF24 comprises comparing the methylation profile to corresponding regions of a control DNA sample obtained from a subject who does not have CC.

[0024] In some embodiments, the at least one DMR comprises one or more CpG sites in CDH4, NBPF24, MAX.chr10.4460, ZNF506, ZNF323, OBSCN, ZNF90, LRRC34, SFMBT2, LINC02323, CYTH2, LRRC8D, LYPLAL1, LRRC41, and / or SEPT9, and wherein the subject has or is suspected of having EC. In some embodiments, determining the methylation profile of one or more CpG sites in CDH4, NBPF24, MAX.chr10.4460, ZNF506, ZNF323, OBSCN, ZNF90, LRRC34, SFMBT2, LINC02323, CYTH2, LRRC8D, LYPLAL1, LRRC41, and / or SEPT9 comprises comparing the methylation profile to corresponding regions in a control DNA sample obtained from a subject not having EC.

[0025] In some embodiments, the at least one DMR comprises one or more CpG sites in CDH4, ZNF506, ZNF323, OBSCN, ZNF90, SFMBT2, LINC02323, CYTH2, LRRC8D, LYPLAL1, LRRC41, and / or SEPT9, and wherein the subject has or is suspected of having OC. In some embodiments, determining the methylation profile of one or more CpG sites in CDH4, ZNF506, ZNF323, OBSCN, ZNF90, SFMBT2, LINC02323, CYTH2, LRRC8D, LYPLAL1, LRRC41, and / or SEPT9 comprises comparing the methylation profile to corresponding regions in a control DNA sample obtained from a subject who does not have OC.

[0026] In some embodiments, the at least one DMR comprises one or more CpG sites among KRT86, EMX2OS, JSRP1, DIDO1, MPZ, VILL, SMPD5, GDF7, MDFI, c17orf64, GATA2, SQSTM1, and / or EEF1A2, and wherein the subject has or is suspected of having CC, OC, or EC. In some embodiments, determining the methylation profile of one or more CpG sites among KRT86, EMX2OS, JSRP1, DIDO1, MPZ, VILL, SMPD5, GDF7, MDFI, c17orf64, GATA2, SQSTM1, and / or EEF1A2 comprises comparing the methylation profile to corresponding regions of a control DNA sample obtained from a subject not having CC, OC, or EC.

[0027] In some embodiments, at least one DMR is associated with an area under the ROC curve (AUC) greater than or equal to 0.8, and the ROC curve distinguishes subjects having or suspected of having OC, CC, or EC from control samples.

[0028] In some embodiments, the biological sample is selected from a tissue sample, a blood sample, a plasma sample, a serum sample, a whole blood sample, a secretion sample, an organ secretion sample, a cerebrospinal fluid (CSF) sample, a saliva sample, a urine sample, and a stool sample. In some embodiments, the tissue sample is a gynecological tissue sample. In some embodiments, the gynecological tissue sample includes one or more of the following: vaginal tissue, vaginal cells, cervical tissue, cervical cells, endometrial tissue, endometrial cells, ovarian tissue, and ovarian cells. In some embodiments, the tissue sample is an ovarian tissue sample, an endometrial tissue sample, or a cervical tissue sample. In some embodiments, the secretion sample is a gynecological secretion sample. In some embodiments, the subject is human.

[0029] In some embodiments, the biological sample is obtained from a subject, and the method further comprises extracting a DNA sample from the biological sample. In some embodiments, the biological sample is collected using a collection device having an absorbent member capable of collecting the biological sample upon contact. In some embodiments, the absorbent member is a sponge configured for insertion into an orifice. In some embodiments, the collection device is selected from the group consisting of a tampon, a douche that releases fluid into the vagina and recollects the fluid, a cervical brush, a Fournier cervical self-sampling device, and a swab.

[0030] In some embodiments, the reagent that modifies DNA in a methylation-specific manner is a borane reducing agent. In some embodiments, the reagent that modifies DNA in a methylation-specific manner comprises one or more of a methylation-sensitive restriction enzyme, a methylation-dependent restriction enzyme, and a bisulfite reagent.

[0031] In some embodiments, determining the methylation profile of at least one DMR comprises amplifying at least a portion of the DMR using a set of primers.

[0032] In some embodiments, determining the methylation profile of at least one DMR comprises performing at least one of methylation-specific PCR, quantitative methylation-specific PCR, methylation-specific DNA restriction enzyme analysis, quantitative bisulfite pyrosequencing, a flap endonuclease assay, a PCR-flap assay, and bisulfite genomic sequencing PCR.

[0033] In some embodiments, determining the methylation profile of at least one DMR comprises determining the presence or absence of methylation at a CpG site.

[0034] Embodiments of the present disclosure also include a method for identifying gynecological cancer. According to these embodiments, the method includes determining the methylation profile in at least one differentially methylated region (DMR) of a DNA sample obtained from a subject suffering from or suspected of suffering from gynecological cancer by treating the sample with a reagent that modifies DNA in a methylation-specific manner. In some embodiments, at least one DMR comprises one or more CpG sites in the following: AIM1, FLOT1, GAL3ST2, LRRC41, LYPLAL1, MAX.chr11.3750, PISD, RAI1, ZIC2, and / or ZMIZ1; and the methylation profile indicates that the subject suffers from ovarian cancer. In some embodiments, the method also includes treating the subject with an anti-cancer therapy.

[0035] Embodiments of the present disclosure also include a method for identifying gynecological cancer. According to these embodiments, the method includes determining the methylation profile in at least one differentially methylated region (DMR) of a DNA sample obtained from a subject suffering from or suspected of suffering from gynecological cancer by treating the sample with a reagent that modifies DNA in a methylation-specific manner. In some embodiments, at least one DMR comprises one or more CpG sites in the following: AK5, ELMOD1, RABC3, TRPC3, ZNF480, ZNF491, ZNF610, and / or ZNF91; and the methylation profile indicates that the subject suffers from cervical cancer. In some embodiments, the method further includes treating the subject with an anti-cancer therapy.

[0036] Embodiments of the present disclosure also include a method for identifying gynecological cancer. According to these embodiments, the method comprises determining a methylation profile in at least one differentially methylated region (DMR) of a DNA sample obtained from a subject having or suspected of having a gynecological cancer by treating the sample with an agent that modifies DNA in a methylation-specific manner. In some embodiments, the at least one DMR comprises one or more CpG sites of: c18orf18, FKBP11, MLH1, NR3C1, and / or TERC; and the methylation profile indicates that the subject has endometrial cancer. In some embodiments, the method further comprises treating the subject with an anti-cancer therapy.

[0037] Embodiments of the present disclosure also include a method for identifying gynecological cancer. According to these embodiments, the method comprises determining a methylation profile in at least one differentially methylated region (DMR) of a DNA sample obtained from a subject having or suspected of having a gynecological cancer by treating the sample with an agent that modifies DNA in a methylation-specific manner. In some embodiments, the at least one DMR comprises one or more CpG sites in CDO1 and / or DLGAP1; and the methylation profile indicates that the subject has ovarian cancer, cervical cancer, or endometrial cancer. In some embodiments, the method further comprises treating the subject with an anti-cancer therapy.

[0038] Embodiments of the present disclosure also include a method for identifying gynecological cancer. According to these embodiments, the method comprises determining a methylation profile in at least one differentially methylated region (DMR) of a DNA sample obtained from a subject suffering from or suspected of suffering from a gynecological cancer by treating the sample with an agent that modifies DNA in a methylation-specific manner. In some embodiments, at least one DMR comprises one or more CpG sites in NBPF24; and wherein the methylation profile indicates that the subject suffers from cervical cancer. In some embodiments, the method further comprises treating the subject with an anti-cancer therapy.

[0039] Embodiments of the present disclosure also include a method for identifying gynecological cancer. According to these embodiments, the method includes determining the methylation profile in at least one differentially methylated region (DMR) of a DNA sample obtained from a subject suffering from or suspected of suffering from gynecological cancer by treating the sample with a reagent that modifies DNA in a methylation-specific manner. In some embodiments, at least one DMR comprises one or more CpG sites in the following: CDH4, NBPF24, MAX.chr10.4460, ZNF506, ZNF323, OBSCN, ZNF90, LRRC34, SFMBT2, LINC02323, CYTH2, LRRC8D, LYPLAL1, LRRC41 and / or SEPT9; and wherein the methylation profile indicates that the subject has endometrial cancer. In some embodiments, the method further includes treating the subject with an anti-cancer therapy.

[0040] Embodiments of the present disclosure also include a method for identifying gynecological cancer. According to these embodiments, the method includes determining the methylation profile in at least one differentially methylated region (DMR) of a DNA sample obtained from a subject suffering from or suspected of suffering from gynecological cancer by treating the sample with a reagent that modifies DNA in a methylation-specific manner. In some embodiments, at least one DMR comprises one or more CpG sites in the following: CDH4, ZNF506, ZNF323, OBSCN, ZNF90, SFMBT2, LINC02323, CYTH2, LRRC8D, LYPLAL1, LRRC41 and / or SEPT9; and wherein the methylation profile indicates that the subject has ovarian cancer. In some embodiments, the method also includes treating the subject with an anti-cancer therapy.

[0041] Embodiments of the present disclosure also include a method for identifying gynecological cancer. According to these embodiments, the method includes determining the methylation profile in at least one differentially methylated region (DMR) of a DNA sample obtained from a subject suffering from or suspected of suffering from gynecological cancer by treating the sample with a reagent that modifies DNA in a methylation-specific manner. In some embodiments, at least one DMR comprises one or more CpG sites in the following: KRT86, EMX2OS, JSRP1, DIDO1, MPZ, VILL, SMPD5, GDF7, MDFI, c17orf64, GATA2, SQSTM1 and / or EEF1A2; and wherein the methylation profile indicates that the subject suffers from ovarian cancer, cervical cancer, or endometrial cancer. In some embodiments, the method also includes treating the subject with an anti-cancer therapy. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1: Representative heatmaps illustrating the ability of candidate methylated DNA signatures to discriminate gynecological cancers from cancer subclasses (see also Table 3).

[0043] Figure 2A-2C : Representative data corresponding to the DNA methylation marker LRRC41, including a calibration plot based on ACTB normalization ( Figure 2A ), and demonstrated a relationship between the three major gynecological cancers ( Figure 2B ), between gynecological cancer subtypes ( Figure 2C ) and the control ( Figure 2A and Figure 2B ) adjusted boxplot of epigenetic relationships.

[0044] Figure 3A-3C : Representative data corresponding to the DNA methylation marker CDO1, including a calibration plot based on ACTB normalization ( Figure 3A ), and demonstrated a relationship between the three major gynecological cancers ( Figure 3B ), between gynecological cancer subtypes ( Figure 3C ) and the control ( Figure 3A and Figure 3B ) adjusted boxplot of epigenetic relationships.

[0045] Figures 4A-4C : Representative data corresponding to the DNA methylation marker ZMIZ1, including a calibration plot based on ACTB normalization ( Figure 4A ), and demonstrated a relationship between the three major gynecological cancers ( Figure 4B ), between gynecological cancer subtypes ( Figure 4C ) and the control ( Figure 4A and Figure 4B ) adjusted boxplot of epigenetic relationships.

[0046] Figures 5A-5C : Representative data corresponding to the DNA methylation marker PISD, including a calibration plot based on ACTB normalization ( Figure 5A ), and demonstrated a relationship between the three major gynecological cancers ( Figure 5B ), between gynecological cancer subtypes ( Figure 5C ) and the control ( Figure 5A and Figure 5B ) adjusted boxplot of epigenetic relationships.

[0047] Figures 6A-6C : Representative data corresponding to the DNA methylation marker AIM1, including a calibration plot based on ACTB normalization ( Figure 6A ), and demonstrated a relationship between the three major gynecological cancers ( Figure 6B ), between gynecological cancer subtypes ( Figure 6C ) and the control ( Figure 6A and Figure 6B ) adjusted boxplot of epigenetic relationships.

[0048] Figures 7A-7C : Representative data corresponding to the DNA methylation marker AK5, including a calibration plot based on ACTB normalization ( Figure 7A ), and demonstrated a relationship between the three major gynecological cancers ( Figure 7B ), between gynecological cancer subtypes ( Figure 7C ) and the control ( Figure 7A and Figure 7B ) adjusted boxplot of epigenetic relationships.

[0049] Figures 8A-8C : Representative data corresponding to the DNA methylation marker c18orf18, including a calibration plot based on ACTB normalization ( Figure 8A ), and demonstrated a relationship between the three major gynecological cancers ( Figure 8B ), between gynecological cancer subtypes ( Figure 8C ) and the control ( Figure 8A and Figure 8B ) adjusted boxplot of epigenetic relationships.

[0050] Figures 9A-9C : Representative data corresponding to the DNA methylation marker ELMOD1, including a calibration plot based on ACTB normalization ( Figure 9A ), and demonstrated a relationship between the three major gynecological cancers ( Figure 9B ), between gynecological cancer subtypes ( Figure 9C ) and the control ( Figure 9A and Figure 9B ) adjusted boxplot of epigenetic relationships.

[0051] Figures 10A-10C : Representative data corresponding to the DNA methylation marker FKBP11, including a calibration plot based on ACTB normalization ( Figure 10A ), and demonstrated a relationship between the three major gynecological cancers ( Figure 10B ), between gynecological cancer subtypes ( Figure 10C ) and the control ( Figure 10A and Figure 10B ) adjusted boxplot of epigenetic relationships.

[0052] Figures 11A-11C : Representative data corresponding to the DNA methylation marker FLOT1, including a calibration plot based on ACTB normalization ( Figure 11A ), and demonstrated a relationship between the three major gynecological cancers ( Figure 11B ), between gynecological cancer subtypes ( Figure 11C ) and the control ( Figure 11A and Figure 11B) adjusted boxplot of epigenetic relationships.

[0053] Figures 12A-12C : Representative data corresponding to the DNA methylation marker GAL3ST2, including a calibration plot based on ACTB normalization ( Figure 12A ), and demonstrated a relationship between the three major gynecological cancers ( Figure 12B ), between gynecological cancer subtypes ( Figure 12C ) and the control ( Figure 12A and Figure 12B ) adjusted boxplot of epigenetic relationships.

[0054] Figures 13A-13C : Representative data corresponding to DNA methylation marker MAX.chr11.593, including a calibration plot based on ACTB normalization ( Figure 13A ), and demonstrated a relationship between the three major gynecological cancers ( Figure 13B ), between gynecological cancer subtypes ( Figure 13C ) and the control ( Figure 13A and Figure 13B ) adjusted boxplot of epigenetic relationships.

[0055] Figures 14A-14C : Representative data corresponding to the DNA methylation marker MLH1, including a calibration plot based on ACTB normalization ( Figure 14A ), and demonstrated a relationship between the three major gynecological cancers ( Figure 14B ), between gynecological cancer subtypes ( Figure 14C ) and the control ( Figure 14A and Figure 14B ) adjusted boxplot of epigenetic relationships.

[0056] Figures 15A-15C : Representative data corresponding to the DNA methylation marker NR3C1, including a calibration plot based on ACTB normalization ( Figure 15A ), and demonstrated a relationship between the three major gynecological cancers ( Figure 15B ), between gynecological cancer subtypes ( Figure 15C ) and the control ( Figure 15A and Figure 15B ) adjusted boxplot of epigenetic relationships.

[0057] Figures 16A-16C : Representative data corresponding to the DNA methylation marker RABC3, including a calibration plot based on ACTB normalization ( Figure 16A ), and demonstrated a relationship between the three major gynecological cancers ( Figure 16B ), between gynecological cancer subtypes ( Figure 16C ) and the control ( Figure 16A and Figure 16B) adjusted boxplot of epigenetic relationships.

[0058] Figures 17A-17C : Representative data corresponding to the DNA methylation marker RAI1, including a calibration plot based on ACTB normalization ( Figure 17A ), and demonstrated a relationship between the three major gynecological cancers ( Figure 17B ), between gynecological cancer subtypes ( Figure 17C ) and the control ( Figure 17A and Figure 17B ) adjusted boxplot of epigenetic relationships.

[0059] Figures 18A-18C : Representative data corresponding to the DNA methylation marker TERC, including a calibration plot based on ACTB normalization ( Figure 18A ), and demonstrated a relationship between the three major gynecological cancers ( Figure 18B ), between gynecological cancer subtypes ( Figure 18C ) and the control ( Figure 18A and Figure 18B ) adjusted boxplot of epigenetic relationships.

[0060] Figures 19A-19C : Representative data corresponding to the DNA methylation marker TRPC3, including a calibration plot based on ACTB normalization ( Figure 19A ), and demonstrated a relationship between the three major gynecological cancers ( Figure 19B ), between gynecological cancer subtypes ( Figure 19C ) and the control ( Figure 19A and Figure 19B ) adjusted boxplot of epigenetic relationships.

[0061] Figures 20A-20C : Representative data corresponding to the DNA methylation marker ZIC2, including a calibration plot based on ACTB normalization ( Figure 20A ), and demonstrated a relationship between the three major gynecological cancers ( Figure 20B ), between gynecological cancer subtypes ( Figure 20C ) and the control ( Figure 20A and Figure 20B ) adjusted boxplot of epigenetic relationships.

[0062] Figures 21A-21C : Representative data corresponding to the DNA methylation marker ZNF480, including a calibration plot based on ACTB normalization ( Figure 21A ), and demonstrated a relationship between the three major gynecological cancers ( Figure 21B ), between gynecological cancer subtypes ( Figure 21C ) and the control ( Figure 21A and Figure 21B ) adjusted boxplot of epigenetic relationships.

[0063] Figures 22A-22C : Representative data corresponding to the DNA methylation marker ZNF491, including a calibration plot based on ACTB normalization ( Figure 22A ), and demonstrated a relationship between the three major gynecological cancers ( Figure 22B ), between gynecological cancer subtypes ( Figure 22C ) and the control ( Figure 22A and Figure 22B ) adjusted boxplot of epigenetic relationships.

[0064] Figures 23A-23C : Representative data corresponding to the DNA methylation marker ZNF610, including a calibration plot based on ACTB normalization ( Figure 23A ), and demonstrated a relationship between the three major gynecological cancers ( Figure 23B ), between gynecological cancer subtypes ( Figure 23C ) and the control ( Figure 23A and Figure 23B ) adjusted boxplot of epigenetic relationships.

[0065] Figures 24A-24C : Representative data corresponding to the DNA methylation marker ZNF91, including a calibration plot based on ACTB normalization ( Figure 24A ), and demonstrated a relationship between the three major gynecological cancers ( Figure 24B ), between gynecological cancer subtypes ( Figure 24C ) and the control ( Figure 24A and Figure 24B ) adjusted boxplot of epigenetic relationships.

[0066] Figures 25A-25C : Representative data corresponding to the DNA methylation marker DLGAP1, including a calibration plot based on ACTB normalization ( Figure 25A ), and demonstrated a relationship between the three major gynecological cancers ( Figure 25B ), between gynecological cancer subtypes ( Figure 25C ) and the control ( Figure 25A and Figure 25B ) adjusted boxplot of epigenetic relationships.

[0067] Figures 26A-26C : Representative data corresponding to the DNA methylation marker LYPLAP_2, including a calibration plot based on ACTB normalization ( Figure 26A ), and demonstrated a relationship between the three major gynecological cancers ( Figure 26B ), between gynecological cancer subtypes ( Figure 26C ) and the control ( Figure 26A and Figure 26B ) adjusted boxplot of epigenetic relationships. DETAILED DESCRIPTION

[0068] The present disclosure relates to detecting one or more types of gynecological cancers in a biological sample from a subject. Specifically, the present disclosure provides compositions and methods for detecting the presence or absence of one or more types of gynecological cancers (e.g., cervical cancer, ovarian cancer, endometrial cancer) in a biological sample from a subject having or suspected of having a gynecological cancer.

[0069] The section headings as used in this section and the entire disclosure herein are for organizational purposes only and are not intended to be limiting.

[0070] 1. Definition

[0071] Throughout the specification and claims, unless the context clearly dictates otherwise, the following terms have the meanings clearly associated herein. As used herein, the phrase "in one embodiment" does not necessarily refer to the same embodiment, although it may refer to the same embodiment. In addition, as used herein, the phrase "in another embodiment" does not necessarily refer to a different embodiment, although it may refer to a different embodiment. Therefore, as described below, various embodiments of the present invention can be easily combined without departing from the scope or spirit of the present invention.

[0072] In addition, as used herein, the term "or" is an inclusive "or" operator and is equivalent to the term "and / or" unless the context clearly dictates otherwise. The term "based on" is not exclusive and allows for being based on other factors not described unless the context clearly dictates otherwise. In addition, throughout the specification, the meanings of "a," "an," and "the" include plural meanings. The meaning of "in..." includes "in..." and "on..."

[0073] The transition phrase "consisting essentially of" as used in the claims of this application limits the scope of the claim to the specified materials or steps "and those that do not materially affect" the "basic and novel characteristics" of the claimed invention, as discussed in In re Herz, 537 F.2d 549, 551-52, 190 USPQ 461, 463 (CCPA 1976). For example, a composition that "consists essentially of" the recited elements may contain unrecited contaminants in amounts that, while present, do not alter the function of the recited composition as compared to the pure composition (i.e., a composition "consisting of" the recited ingredients).

[0074] As used herein, the term "one or more" refers to a number greater than one. For example, the term "one or more" encompasses any of two or more, three or more, four or more, five or more, six or more, seven or more, eight or more, nine or more, ten or more, twelve or more, thirteen or more, fourteen or more, fifteen or more, twenty or more, fifty or more, one hundred or more, or even more.

[0075] The terms "one or more but less than a higher number," "two or more but less than a higher number," "three or more but less than a higher number," "four or more but less than a higher number," "five or more but less than a higher number," "six or more but less than a higher number," "seven or more but less than a higher number," "eight or more but less than a higher number," "nine or more but less than a higher number," "ten or more but less than a higher number," "eleven or more but less than a higher number," "twelve or more but less than a higher number," "thirteen or more but less than a higher number," "fourteen or more but less than a higher number," or "fifteen or more but less than a higher number" are not limited to higher numbers. For example, the higher number may be 10,000, 1,000, 100, 50, etc. For example, the higher number can be about 50 (e.g., 50, 49, 48, 47, 46, 45, 44, 43, 42, 41, 40, 39, 38, 37, 36, 35, 34, 33, 32, 31, 32, 30, 29, 28, 27, 26, 25, 24, 23, 22, 21, 20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, or 2).

[0076] The terms "one or more methylation marks" or "one or more DMRs" or "one or more genes" or "one or more markers" or "multiple methylation marks" or "multiple markers" or "multiple genes" or "multiple DMRs" are likewise not limited to a specific numerical combination. In fact, any numerical combination of methylation marks (e.g., 1-2 methylation marks, 1-3, 1-4, 1-5, 1-6, 1-7, 1-8, 1-9, 1-10, 1-11, 1-12, 1-13, 1-14, 1-15, 1-16, 1-17, 1-18, 1-19, 1-20, 1-21, 1-22, 1-23, 1-24, 1-25, 1-26, 1-27, 1-28, 1-29, 1-30, 1-31, 1-32, 1-33, 1-34, 1-35, 1-36, 1-37, 1-38) is contemplated. -6, 2-7, 2-8, 2-9, 2-10, 2-11, 2-12, 2-13, 2-14, 2-15, 2-16, 2-17, 2-18, 2-19, 2-20, 2-21, 2-22, 2-23, 2-24, 2-25, 2-26, 2-27, 2-28, 2-29, 2-30, 2-31, 2-32, 2-33, 2-34, 2-35, 2-36, 2-37, 2-38) (e.g., 3-4, 3-5, 3-6, 3-7, 3-8, 3-9, 3-10, 3-11, 3-12, 3-13, 3-14, 3-15, 3-16, 3-3 -17, 3-18, 3-19, 3-20, 3-21, 3-22, 3-23, 3-24, 3-25, 3-26, 3-27, 3-28, 3-29, 3-30, 3-31, 3-32, 3-33, 3-34, 3-35, 3-36, 3-37, 3-38) (e.g., 4-5, 4-6, 4-7, 4-8, 4-9, 4-10, 4-11, 4-12, 4-13, 4-14, 4-15, 4-16, 4-17, 4-18, 4-19, 4-20, 4-21, 4-22, 4-23, 4-24, 4-25, 4-26, 4-27, 4-28, 4-29, 4-30, 4-31, 4-32, 4-33, 4-34, 4-35, 4-36, 4-37, 4-38) (e.g., 5-6, 5-7, 5-8, 5-9, 5-10, 5-11, 5-12, 5-13, 5-14, 5-15, 5-16, 5-17, 5-18, 5-19, 5-20, 5-21, 5-22, 5-23, 5-24, 5-25, 5-26, 5-27, 5-28, 5-29, 5-30, 5-31, 5-32, 5-33, 5-34, 5-35, 5-36, 5-37, 5-38) (e.g.,6-7, 6-8, 6-9, 6-10, 6-11, 6-12, 6-13, 6-14, 6-15, 6-16, 6-17, 6-18, 6-19, 6-20, 6-21, 6-22, 6-23, 6-24, 6-25, 6-26, 6-27, 6-28, 6-29, 6-30, 6-31, 6-32, 6-33, 6-34, 6-35, 6-36, 6-37, 6-38) (e.g., 7-8, 7-9, 7-10, 7-11, 7-12, 7-13, 7-14, 7-15, 7-16, 7-17, 7-18, 7-19, 7-20, 7-21, 7-22, 7-23, 7-24, 7-25, 7-26, 7-27, 7-28, 7-29, 7-30, 7-31, 7-32, 7-33, 7-34, 7-35, 7-36, 7-37, 7-38) (e.g., 8-9, 8-10, 8-11, 8-12, 8-13, 8-14, 8-15, 8-16, 8-17, 8-18, 8-19, 8-20, 8-21, 8-22, 8-23, 8-24, 8-25, 8-26, 8-27, 8-28, 8-29, 8-30, 8-31, 8-32, 8-33, 8-34, 8-35, 8-36, 8-37, 8-38) (e.g., 9-10, 9-1 1, 9-12, 9-13, 9-14, 9-15, 9-16, 9-17, 9-18, 9-19, 9-20, 9-21, 9-22, 9-23, 9-24, 9-25, 9-26, 9-27, 9-28, 9-29, 9-30, 9-31, 9-32, 9-33, 9-34, 9-35, 9-36, 9-37, 9-38) (e.g., 10-11, 10-12, 10-13, 10-14, 10-15, 10-16, 10-17, 10-18, 10-19, 10-20, 10-21, 10-22, 10-23, 10-24, 10-25, 10-26, 10 -27, 10-28, 10-29, 10-30, 10-31, 10-32, 10-33, 10-34, 10-35, 10-36, 10-37, 10-38) (e.g., 11-12, 11-13, 11-14, 11-15, 11-16, 11-17, 11-18, 11-19, 11-20, 11-21, 11-22, 11-23, 11-24, 11-25, 11-26, 11-27, 11-28, 11-29, 11-30, 11-31, 11-32, 11-33, 11-34, 11-35, 11-36, 11-37, 11-38) (e.g.,12-13, 12-14, 12-15, 12-16, 12-17, 12-18, 12-19, 12-20, 12-21, 12-22, 12-23, 12-24, 12-25, 12-26, 12-27, 12-28, 12-29, 12-30, 12-31, 12-32, 12-3 3, 12-34, 12-35, 12-36, 12-37, 12-38) (e.g., 13-14, 13-15, 13-16, 13-17, 13-18, 13-19, 13-20, 13-21, 13-22, 13-23, 13-24, 13-25, 13-26, 13-27, 13-28, 13-29, 13-30, 13-31, 13-32, 13-33, 13-34, 13-35, 13-36, 13-37, 13-38) (e.g., 14-15, 14-16, 14-17, 14-18, 14-19, 14-20, 14-21, 14-22, 14-23, 14-24 4, 14-25, 14-26, 14-27, 14-28, 14-29, 14-30, 14-31, 14-32, 14-33, 14-34, 14-35, 14-36, 14-37, 14-38) (e.g., 15-16, 15-17, 15-18, 15-19, 15-20, 15-21 , 15-22, 15-23, 15-24, 15-25, 15-26, 15-27, 15-28, 15-29, 15-30, 15-31, 15-32, 15-33, 15-34, 15-35, 15-36, 15-37, 15-38) (e.g., 16-17, 16-18, 16-19, 16-20, 16-21, 16-22, 16-23, 16-24, 16-25, 16-26, 16-27, 16-28, 16-29, 16-30, 16-31, 16-32, 16-33, 16-34, 16-35, 16-36, 16-37, 16-38) (e.g., 17-18 , 17-19, 17-20, 17-21, 17-22, 17-23, 17-24, 17-25, 17-26, 17-27, 17-28, 17-29, 17-30, 17-31, 17-32, 17-33, 17-34, 17-35, 17-36, 17-37, 17-38) (e.g. , 18-19, 18-20, 18-21, 18-22, 18-23, 18-24, 18-25, 18-26, 18-27, 18-28, 18-29, 18-30, 18-31, 18-32, 18-33, 18-34, 18-35, 18-36, 18-37, 18-38) (e.g.,19-20, 19-21, 19-22, 19-23, 19-24, 19-25, 19-26, 19-27, 19-28, 19-29, 19-30, 19-31, 19-32, 19-33, 19-34, 19-35, 19-36, 19-37, 19-38) (e.g., 20-21, 20-22, 20-23, 20-24, 20-25, 20-26, 20-27, 20-28, 20-29, 20-30, 20-31, 20-32, 20-33, 20-34, 20-35, 20-36, 20-37, 20-38) (e.g., 21-22, 21-23, 21-24, 21-25, 21-26, 21-27, 21-28, 21-29, 21-30, 21-31, 21-32, 21-33, 21-34, 21-35, 21-36, 21-37, 21-38) (e.g., 22-23, 22-24, 22-25, 22-26, 22-27, 22-28, 22-29, 22-30, 22-31, 22-32, 22-33, 22-34, 22-35, 22-36, 22-37, 22-38) (e.g., 23-24, 23-25, 23-26, 23-27, 23-28, 23-29, 23-30, 23-31, 23-32, 23-33, 23-34, 23-35, 23-36, 23-37, 23-38) (e.g., 24-25, 24-26, 24-27, 24-28, 24-29, 24-30, 24-31, 24-32, 24-33, 24-34, 24-35, 24-36, 24-37, 24-38) (e.g., 25-26, 25-27, 25-28, 25-29, 25-30, 25-31, 25-32, 25-33, 25-34, 25-35, 25-36, 25-37, 25-38) (e.g., 26-27, 26-28, 26-29, 26-30, 26 -31, 26-32, 26-33, 26-34, 26-35, 26-36, 26-37, 26-38) (e.g., 27-28, 27-29, 27-30, 27-31, 27-32, 27-33, 27-34, 27-35, 27-36, 27-37, 27-38) (e.g., 28-29, 28-30, 28-31, 28-32, 28-33, 28-34, 28-35, 28-36, 28-37, 28-38) (e.g., 29-30, 29-31, 29-32, 29-33, 29-34, 29-35, 29-36, 29-37, 29-38) (e.g.,30-31, 30-32, 30-33, 30-34, 30-35, 30-36, 30-37, 30-38) (e.g., 31-32, 31-33, 31-34, 31-35, 31-36, 31-37, 31-38) (e.g., 32-33, 32-34, 32-35, 32-36, 32-37, 32-38) (e.g., 33-34, 33-35, 33-36, 33-37, 33-38) (e.g., 34-35, 34-36, 34-37, 34-38) (e.g., 35-36, 35-37, 35-38) (e.g., 36-37, 36- 38) (e.g., 37-38) (e.g., 38 or less; 37 or less; 36 or less; 35 or less; 34 or less; 33 or less; 32 or less; 31 or less; 30 or less; 29 or less; 28 or less; 27 or less; 26 or less; 25 or less; 24 or less; 23 or less; 22 or less; 21 or less; 20 or less; 19 or less; 18 or less; 17 or less; 16 or less; 15 or less; 14 or less; 13 or less; 12 or less; 11 or less; 10 or less; 9 or less; 8 or less; 7 or less; 6 or less; 5 or less; 4 or less; 3 or less; 2 or 1).

[0077] The terms "multiple types of cancer" or "one or more types of cancer" or "one or more subtypes of cancer" or "multiple different types or subtypes of cancer" are similarly not limited to a specific numerical combination. The DNA methylation signatures of the present disclosure can be used to identify any numerical combination of gynecological cancer types or subtypes, including but not limited to ovarian cancer, serous ovarian cancer, clear cell ovarian cancer, endometrioid ovarian cancer, mucinous ovarian cancer, cervical cancer, adenocarcinoma cervical cancer, squamous cervical cancer, endometrial cancer, and endometrioid endometrial cancer.

[0078] As used herein, "nucleic acid" or "nucleic acid molecule" generally refers to any ribonucleic acid or deoxyribonucleic acid, which can be unmodified or modified DNA or RNA. "Nucleic acid" includes but is not limited to single-stranded and double-stranded nucleic acids. As used herein, the term "nucleic acid" also includes DNA as described above containing one or more modified bases. Therefore, DNA whose backbone is modified for stability or other reasons is a "nucleic acid". As used herein, the term "nucleic acid" encompasses such chemically, enzymatically or metabolically modified forms of nucleic acids, as well as chemical forms of DNA characteristic of viruses and cells (including, for example, simple and complex cells).

[0079] The term "oligonucleotide" or "polynucleotide" or "nucleotide" or "nucleic acid" refers to a molecule having two or more, preferably more than three and usually more than ten deoxyribonucleotides or ribonucleotides. The exact size will depend on many factors, which in turn depend on the ultimate function or use of the oligonucleotide. Oligonucleotides can be produced in any manner, including chemical synthesis, DNA replication, reverse transcription, or a combination thereof. The typical deoxyribonucleotides of DNA are thymine, adenine, cytosine, and guanine. The typical ribonucleotides of RNA are uracil, adenine, cytosine, and guanine.

[0080] As used herein, the term "locus" or "region" of a nucleic acid refers to a subregion of a nucleic acid, such as a gene on a chromosome, a single nucleotide, a CpG island, and the like.

[0081] The terms "complementary" and "complementarity" refer to nucleotides (e.g., one nucleotide) or polynucleotides (e.g., a sequence of nucleotides) that are related by the base pairing rules. For example, the sequence 5'-AGT-3' is complementary to the sequence 3'-TCA-5'. Complementarity can be "partial," in which only some of the nucleic acid bases match according to the base pairing rules. Alternatively, there can be "complete" or "total" complementarity between nucleic acids. The degree of complementarity between nucleic acid chains affects the efficiency and intensity of hybridization between nucleic acid chains. This is particularly important in amplification reactions and detection methods that depend on binding between nucleic acids.

[0082] The term "gene" refers to a nucleic acid (e.g., DNA or RNA) sequence comprising a coding sequence necessary to produce an RNA or polypeptide or its precursor. A functional polypeptide can be encoded by the full-length coding sequence or by any portion of the coding sequence, as long as the desired activity or functional properties of the polypeptide (e.g., enzymatic activity, ligand binding, signal transduction, etc.) are retained. When used to refer to a gene, the term "portion" refers to a fragment of the gene. The size of a fragment can vary from a few nucleotides to the entire gene sequence minus one nucleotide. Therefore, "nucleotides comprising at least a portion of a gene" can include a gene fragment or the entire gene.

[0083] The term "gene" encompasses the coding region of a structural gene and sequences adjacent to the coding region at both the 5' and 3' ends, such that the gene corresponds to the length of the full-length mRNA (e.g., including coding, regulatory, structural, and other sequences). Sequences located 5' to the coding region and present on the mRNA are referred to as 5' non-translated or untranslated sequences. Sequences located 3' or downstream of the coding region and present on the mRNA are referred to as 3' non-translated or 3' untranslated sequences. The term "gene" encompasses both cDNA and genomic forms of a gene. In some organisms (e.g., eukaryotes), the genomic form or clone of a gene contains coding regions interrupted by non-coding sequences called "introns," "insertion regions," or "insertion sequences." Introns are segments of a gene that are transcribed into nuclear RNA (hnRNA); introns may contain regulatory elements, such as enhancers. Introns are removed or "spliced ​​out" from the nuclear transcript or primary transcript; therefore, they are not present in the messenger RNA (mRNA) transcript. mRNA functions during translation to specify the sequence or order of amino acids in a nascent polypeptide. Based on the present disclosure, it will be understood by those skilled in the art that one or more CpG sites in a DMR can be located in the coding region of a gene, the non-coding regulatory region of a gene, or a non-coding region unknown to be associated with a specific gene, such as a region containing a long non-coding RNA (lncRNA). In some embodiments, sequences corresponding to these regions can be obtained using accession numbers corresponding to genomic databases (e.g., GenBank, NCBI, UniProt, etc.) (see, e.g., Tables 1 and 2). In some embodiments, one or more CpG sites in a DMR can be located in an unannotated genomic region. As further provided herein, SEQ ID NOs (see, e.g., Tables 1 and 2; SEQ ID NOs: 1-32) can be used to describe an unannotated genomic region containing one or more CpG sites in a DMR.

[0084] Based on the present disclosure, one of ordinary skill in the art will recognize that a variety of techniques can be used to determine the location of one or more CpG sites (e.g., CpG islands) within a gene or region and their association with a disease or disorder, including but not limited to those disclosed in Chen et al., “Methods for identifying differentially methylated regions for sequence-and array-based data,” Briefings in Functional Genomics, Vol. 15, No. 6, November 2016, pp. 485-490, which is incorporated herein by reference in its entirety for all purposes.

[0085] In addition to containing introns, the genomic form of a gene can also include sequences at 5' and 3' ends of the sequence present on the RNA transcript. These sequences are referred to as "flanking" sequences or regions (these flanking sequences are positioned at 5' or 3' of the non-translated sequence present on the mRNA transcript). The 5' flanking region can contain regulatory sequences, such as promoters and enhancers, which control or influence the transcription of the gene. The 3' flanking region can contain sequences that instruct transcription termination, post-transcriptional cracking and polyadenylation. These flanking regions may be non-coding, and therefore may not be present in the mRNA transcript.

[0086] The term "wild-type" when referring to a gene refers to a gene that has the characteristics of a gene isolated from a naturally occurring source. The term "wild-type" when referring to a gene product refers to a gene product that has the characteristics of a gene product isolated from a naturally occurring source. The term "wild-type" when referring to a protein refers to a protein that has the characteristics of a naturally occurring protein. The term "naturally occurring" as applied to an object refers to the fact that the object can be found in nature. For example, a polypeptide or polynucleotide sequence present in an organism (including a virus) that can be isolated from a natural source and has not been intentionally modified by a laboratory worker is naturally occurring. A wild-type gene is generally the gene or allele most commonly observed in a population and is therefore arbitrarily designated as the "normal" or "wild-type" form of a gene. In contrast, the terms "modified" or "mutated" when referring to a gene or gene product refer to a gene or gene product that exhibits modifications in sequence and / or functional properties (e.g., altered characteristics) compared to the wild-type gene or gene product, respectively. Note that naturally occurring mutants can be isolated; these are identified by the fact that they have altered characteristics compared to the wild-type gene or gene product.

[0087] The term "allele" refers to a variation of a gene; said variation includes, but is not limited to, variants and mutants, polymorphic loci and single nucleotide polymorphic loci, frameshift and splice mutations. An allele may occur naturally in a population or may occur during the lifetime of any particular individual in a population.

[0088] Thus, the terms "variant" and "mutant" when used in reference to nucleotide sequences refer to a nucleic acid sequence that differs from another, generally related, nucleotide sequence by one or more nucleotides. A "variation" is a difference between two different nucleotide sequences; typically, one sequence is a reference sequence.

[0089] The term "primer" refers to an oligonucleotide, whether naturally occurring (e.g., a nucleic acid fragment from a restriction digest) or synthetically produced, which can serve as a starting point for synthesis when placed under conditions that induce the synthesis of a primer extension product complementary to a nucleic acid template strand (e.g., in the presence of nucleotides and an inducing agent such as a DNA polymerase, and at a suitable temperature and pH). In order to achieve maximum amplification efficiency, the primer is preferably single-stranded, but may also be double-stranded. If double-stranded, the primer is first treated to separate its chain before it can be used to prepare an extension product. Preferably, the primer is an oligodeoxyribonucleotide. The primer must be long enough to initiate the synthesis of an extension product in the presence of an inducing agent. The exact length of the primer will depend on many factors, including the use of temperature, primer source, and method. In some embodiments, the primer is specific to a specific differentially methylated region (e.g., the DMR in Table 1 and Table 2) and specifically binds to at least a portion of the genetic region comprising the DMR.

[0090] The term "probe" refers to an oligonucleotide (e.g., a nucleotide sequence), whether naturally occurring (e.g., in a purified restriction digest) or synthesized, recombinant, or produced by PCR amplification, which is capable of hybridizing to another oligonucleotide of interest. The probe can be single-stranded or double-stranded. The probe can be used to detect, identify, and isolate a specific gene sequence (e.g., a "capture probe"). It is envisioned that in some embodiments, any probe used in the embodiments of the present disclosure may be labeled with any "reporter molecule" so that it can be detected in any detection system, including but not limited to enzymes (e.g., ELISA, and enzyme-based histochemical assays), fluorescence, radioactivity, and luminescence systems. The various embodiments of the present disclosure are not limited to any particular detection system or label.

[0091] As used herein, the term "target" refers to a nucleic acid that is sought to be separated from other nucleic acids, such as by probe binding, amplification, separation, capture, etc. For example, when used in reference to a polymerase chain reaction, "target" refers to the region of nucleic acid to which the primers used in the polymerase chain reaction bind, while when used in an assay that does not amplify target DNA, such as in some embodiments of an invasive cleavage assay, the target includes the site where the probe and invasive oligonucleotide (e.g., INVADER oligonucleotide) bind to form an invasive cleavage structure, thereby detecting the presence of the target nucleic acid. A "segment" is defined as a region of nucleic acid within a target sequence.

[0092] Thus, as used herein, "non-target," for example, when used to describe nucleic acids (e.g., DNA), refers to nucleic acids that may be present in a reaction but are not the subject of detection or characterization by the reaction. In some embodiments, non-target nucleic acids can refer to nucleic acids present in a sample that do not contain, for example, a target sequence, while in some embodiments, non-target can refer to exogenous nucleic acids, i.e., nucleic acids that are not derived from a sample containing or suspected of containing a target nucleic acid, and that are added to a reaction, for example, to normalize the activity of an enzyme (e.g., a polymerase) to reduce variation in enzyme performance in the reaction.

[0093] As used herein, "methylation" refers to methylation of cytosine at positions C5 or N4 of cytosine, N6 of adenine, or other types of nucleic acid methylation. In vitro amplified DNA is typically non-methylated because typical in vitro DNA amplification methods do not retain the methylation pattern of the amplified template. However, "unmethylated DNA" or "methylated DNA" may also refer to amplified DNA that is unmethylated or methylated, respectively, from the original template.

[0094] As used herein, the term "amplification reagents" refers to reagents required for amplification (deoxyribonucleoside triphosphates, buffer, etc.) excluding primers, nucleic acid templates, and amplification enzymes. Typically, amplification reagents are placed together with other reaction components and contained in a reaction vessel.

[0095] As used herein, the term "control" when used to refer to nucleic acid detection or analysis refers to a nucleic acid with known characteristics (e.g., a known sequence, a known number of copies per cell) for comparison with an experimental target (e.g., a nucleic acid of unknown concentration). The control can be an endogenous, preferably unchanging gene, against which the test nucleic acid or target nucleic acid in the assay can be standardized. This standardization controls for inter-sample variations that may occur, for example, in sample processing, assay efficiency, etc., and allows accurate inter-sample data comparison. Genes that can be used to standardize nucleic acid detection assays for human samples include, for example, b-actin, ZDHHC1, and B3GALT6 (see, for example, U.S. patent application serial numbers 14 / 966,617 and 62 / 364,082, each of which is incorporated herein by reference). As used herein, "ZDHHC1" refers to a gene encoding a protein characterized by zinc finger DHHC type 1, which is located on Chr 16 (16q22.1) in human DNA and belongs to the DHHC palmitoyltransferase family. In some embodiments, reference genes include, but are not limited to, FNBP1, NCOR2, and S1PR4 (see Table 4).

[0096] The control can also be external. For example, in quantitative assays (such as qPCR, QuARTS, etc.), "calibrator" or "calibration control" is a nucleic acid that has a known sequence, for example, a sequence identical to a portion of an experimental target nucleic acid, and has a known concentration or a range of concentrations (for example, a serial dilution control target for generating a calibration curve in quantitative PCR). Typically, the calibration control is analyzed using the same reagents and reaction conditions as the experimental DNA. In certain embodiments, the measurement of the calibrator is carried out simultaneously with the experimental assay, for example, in the same thermal cycler. In a preferred embodiment, a plurality of calibrators can be included in a single plasmid so that different calibrator sequences are easily provided in equimolar amounts. In a particularly preferred embodiment, the plasmid calibrator is digested, for example, with one or more restriction enzymes, to release the calibrator portion from the plasmid vector. See, for example, WO 2015 / 066695, which is incorporated herein by reference.

[0097] As used herein, "methylated nucleotide" or "methylated nucleotide base" refers to the presence of a methyl moiety on a nucleotide base, wherein the methyl moiety is not present in recognized typical nucleotide bases. For example, cytosine does not contain a methyl moiety on its pyrimidine ring, but 5-methylcytosine contains a methyl moiety at position 5 of its pyrimidine ring. Therefore, cytosine is not a methylated nucleotide, and 5-methylcytosine is a methylated nucleotide. In another example, thymine contains a methyl moiety at position 5 of its pyrimidine ring; however, for the purposes of this article, when thymine is present in DNA, it is not considered a methylated nucleotide because thymine is a typical nucleotide base of DNA.

[0098] As used herein, a "methylated nucleic acid molecule" refers to a nucleic acid molecule containing one or more methylated nucleotides.

[0099] As used herein, the "methylation state," "methylation profile," and "methylation status" of a nucleic acid molecule refers to the presence or absence of one or more methylated nucleotide bases in a nucleic acid molecule. For example, a nucleic acid molecule containing methylated cytosine is considered methylated (e.g., the methylation state of the nucleic acid molecule is methylated). A nucleic acid molecule that does not contain any methylated nucleotides is considered unmethylated.

[0100] As used herein, the term "methylation level" as applied to a methylation marker refers to the amount of methylation within a particular methylation marker. Methylation level can also refer to the amount of methylation within a particular methylation marker compared to a defined standard or control. Methylation level can also refer to whether one or more cytosine residues present in a CpG environment have or do not have a methylated group. Methylation level can also refer to the proportion of cells in a sample that have or do not have a methylated group on these cytosines. Methylation level can also alternatively describe whether a single CpG dinucleotide is methylated.

[0101] The methylation state of a particular nucleic acid sequence (e.g., a gene marker or DNA region as described herein) can indicate the methylation state of each base in the sequence, or can indicate the methylation state of a subset of bases within the sequence (e.g., one or more cytosines), or can indicate information about the methylation density of a region within the sequence, with or without providing precise information about the location within the sequence where methylation occurs.

[0102] The methylation state of a nucleotide locus in a nucleic acid molecule refers to the presence or absence of a methylated nucleotide at a specific locus in the nucleic acid molecule. For example, when the nucleotide present at the 7th nucleotide in a nucleic acid molecule is 5-methylcytosine, the methylation state of the cytosine at the 7th nucleotide in the nucleic acid molecule is methylated. Similarly, when the nucleotide present at the 7th nucleotide in a nucleic acid molecule is cytosine (rather than 5-methylcytosine), the methylation state of the cytosine at the 7th nucleotide in the nucleic acid molecule is unmethylated.

[0103] The methylation status can optionally be expressed or indicated using a "methylation value" (e.g., representing a methylation frequency, score, ratio, percentage, etc.). A methylation value can be generated, for example, by quantifying the amount of intact nucleic acid present after restriction digestion with a methylation-dependent restriction enzyme, or by comparing amplification profiles after a sulfite reaction, or by comparing the sequences of sulfite-treated and untreated nucleic acids, or by comparing TET-treated and untreated nucleic acids. Thus, a value, such as a methylation value, represents the methylation status and can therefore be used as a quantitative indicator of the methylation status of multiple copies across a locus. This is particularly useful when it is necessary to compare the methylation status of a sequence in a sample to a threshold or reference value.

[0104] As used herein, "methylation frequency" or "percent (%) methylation" refers to the number of instances in which a molecule or locus is methylated relative to the number of instances in which the molecule or locus is unmethylated.

[0105] As used herein, the term "methylation score" is a score indicating the methylation events detected in a marker or marker panel compared to the median methylation event of a marker or marker panel from a random population of mammals that do not have the specific neoplasm of interest (e.g., a random population of 10, 20, 30, 40, 50, 100, or 500 mammals). The methylation score that is elevated in a marker or marker panel can be any score as long as the score is greater than the corresponding reference score. For example, the methylation score that is elevated in a marker or marker panel can be 0.5, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more times higher than the reference methylation score.

[0106] Therefore, methylation state describes the methylation state of nucleic acid (such as genomic sequence). In addition, methylation state refers to the characteristics of the nucleic acid segment associated with methylation on a specific genomic locus. Such characteristics include, but are not limited to, whether any cytosine (C) residue in this DNA sequence is methylated, the position of the methylated C residue, the frequency or percentage of methylated C in any specific region of the nucleic acid, and the allelic differences of methylation due to, for example, differences in allelic origin. The terms "methylation state", "methylation overview" and "methylation status" also refer to the relative concentration, absolute concentration or pattern of methylated C or unmethylated C in any specific region of the nucleic acid in a biological sample. For example, if the cytosine (C) residue in the nucleic acid sequence is methylated, it can be referred to as "hypermethylation" or with "increased methylation", and if the cytosine (C) residue in the DNA sequence is not methylated, it can be referred to as "hypomethylation" or with "reduced methylation". In some embodiments, the present invention provides the methylation pattern of the present invention.For example, the methylation pattern of the present invention is the methylation pattern of the present invention.For example, the methylation pattern of the present invention is the methylation pattern of the present invention. For ... The term "differential methylation" refers to the difference in the level or pattern of nucleic acid methylation in a cancer-positive sample compared to the level or pattern of nucleic acid methylation in a cancer-negative sample. It may also refer to the difference in level or pattern between patients whose cancer relapsed after surgery and those who did not. Differential methylation and specific levels or patterns of DNA methylation are biomarkers for prognosis and prediction (e.g., once the correct cutoff or prediction features are defined). DMRs can be located in any region of a gene. In some embodiments, a DMR comprises, is derived from, or is located in one or more regions of a gene, including but not limited to coding regions, non-coding regions, regulatory regions, introns, exons, promoters, enhancers, termination sequences, 3'UTRs, and 5'UTRs.In some embodiments, one or more CpG sites in a DMR may be located in a non-coding region, such as a region corresponding to a long non-coding RNA (lncRNA).

[0107] Methylation state frequency can be used to describe individual populations or samples from a single individual. For example, a nucleotide locus with a methylation state frequency of 50% is methylated in 50% of cases and unmethylated in 50% of cases. Such a frequency can be used to, for example, describe the degree of methylation of a nucleotide locus or nucleic acid region in a population or nucleic acid collection. Therefore, when the methylation in a first population or pool of nucleic acid molecules is different from the methylation in a second population or pool of nucleic acid molecules, the methylation state frequency of the first population or pool will be different from the methylation state frequency of the second population or pool. Such a frequency can also be used to, for example, describe the degree of methylation of a nucleotide locus or nucleic acid region in a single individual. For example, such a frequency can be used to describe the degree of methylation or unmethylation of a group of cells from a tissue sample at a nucleotide locus or nucleic acid region.

[0108] Typically, methylation of human DNA occurs on dinucleotide sequences comprising adjacent guanine and cytosine, wherein cytosine is located 5' to guanine (also referred to as CpG dinucleotide sequences). In the human genome, most cytosines within CpG dinucleotides are methylated, but in specific genomic regions rich in CpG dinucleotides (referred to as CpG islands), some cytosines remain unmethylated (e.g., see Antequera et al. (1990) Cell 62:503–514).

[0109] As used herein, "CpG island" or "cytosine-phosphate-guanine island" refers to a G:C-rich region of genomic DNA that contains an increased amount of CpG dinucleotides relative to the total genomic DNA. A CpG island can be at least 100, 200, or more base pairs in length, wherein the G:C content of the region is at least 50% and the ratio of the observed CpG frequency to the expected frequency is 0.6; in some cases, a CpG island can be at least 500 base pairs in length, wherein the G:C content of the region is at least 55% and the ratio of the observed CpG frequency to the expected frequency is 0.65. The ratio of the observed CpG frequency to the expected frequency can be calculated according to the method provided in Gardiner-Garden et al. (1987) J. Mol. Biol. 196: 261–281. For example, the ratio of the observed CpG frequency to the expected frequency can be calculated according to the formula R=(A×B) / (C×D), where R is the ratio of the observed CpG frequency to the expected frequency, A is the number of CpG dinucleotides in the analyzed sequence, B is the total number of nucleotides in the analyzed sequence, C is the total number of C nucleotides in the analyzed sequence, and D is the total number of G nucleotides in the analyzed sequence. Methylation status is typically determined in CpG islands, such as in promoter regions. However, it should be recognized that other sequences in the human genome are also susceptible to DNA methylation, such as CpA and CpT (see Ramsahoye (2000) Proc. Natl. Acad. Sci. USA 97:5237–5242; Salmon and Kaye (1970) Biochim. Biophys. Acta. 204:340-351; Grafstrom (1985) Nucleic Acids Res. 13:2827-2842; Nyce (1986) Nucleic Acids Res. 14:4353-4367; Woodcock (1987) Biochem. Biophys. Res. Commun. 145:888-894).

[0110] As used herein, "methylation-specific reagent" refers to a reagent that modifies the nucleotides of a nucleic acid molecule according to the methylation state of the nucleic acid molecule, or a methylation-specific reagent refers to a compound or composition or other agent that can change the nucleotide sequence of a nucleic acid molecule in a manner that reflects the methylation state of the nucleic acid molecule. The method for treating a nucleic acid molecule with such a reagent may comprise contacting the nucleic acid molecule with the reagent, and adding additional steps, if necessary, to achieve the desired nucleotide sequence change. Such methods can be applied in a manner that unmethylated nucleotides (e.g., each unmethylated cytosine) are modified into different nucleotides. For example, in some embodiments, such reagents can deaminize unmethylated cytosine nucleotides to produce deoxyuracil residues. Examples of such reagents include, but are not limited to, methylation-sensitive restriction enzymes, methylation-dependent restriction enzymes, bisulfite reagents, TET enzymes, and borane reducing agents.

[0111] Alteration of the nucleic acid nucleotide sequence by a methylation-specific agent can also result in each methylated nucleotide in the nucleic acid molecule being modified to a different nucleotide.

[0112] The term "methylation assay" refers to any assay used to determine the methylation status of one or more CpG dinucleotide sequences within a nucleic acid sequence.

[0113] The term "MS AP-PCR" (methylation-sensitive arbitrarily primed polymerase chain reaction) refers to an art-recognized technique that allows global scanning of the genome using CG-rich primers to focus on regions most likely to contain CpG dinucleotides, as described in Gonzalgo et al. (1997) Cancer Research 57:594–599.

[0114] The term "MethyLight TM ” refers to the art-recognized fluorescence-based real-time PCR technique described by Eads et al. (1999) Cancer Res. 59:2302–2306.

[0115] The term "Heavy Methyl TM ” refers to an assay in which a methylation-specific blocking probe (also referred to herein as a blocker) covering a CpG position between or covered by amplification primers enables methylation-specific selective amplification of a nucleic acid sample.

[0116] The term "Heavy Methyl TM MethyLight TM "Assay refers to a HeavyMethyl TM MethyLight TM Determination, it is MethyLight TMA variant of the assay in which MethyLight TM The assay is combined with a methylation-specific blocking probe covering the CpG position between the amplification primers.

[0117] The term "Ms-SNuPE" (Methylation-Sensitive Single Nucleotide Primer Extension) refers to the art-recognized assay described by Gonzalgo and Jones (1997) Nucleic Acids Res. 25:2529-2531.

[0118] The term "MSP" (methylation-specific PCR) refers to the art-recognized methylation assay described by Herman et al. (1996) Proc. Natl. Acad. Sci. USA 93:9821-9826 and US Patent No. 5,786,146.

[0119] The term "COBRA" (combined sulfite restriction analysis) refers to the art-recognized methylation assay described by Xiong and Laird (1997) Nucleic Acids Res. 25:2532-2534.

[0120] The term "MCA" (methylated CpG island amplification) refers to the methylation assay described in Toyota et al. (1999) Cancer Res. 59:2307-12 and WO 00 / 26401 A1.

[0121] As used herein, "selected nucleotide" refers to one of the four typically occurring nucleotides in a nucleic acid molecule (C, G, T, and A for DNA and C, G, U, and A for RNA), and may include methylated derivatives of typically occurring nucleotides (e.g., when C is the selected nucleotide, both methylated and unmethylated C are included within the meaning of the selected nucleotide), while a methylated selected nucleotide specifically refers to a methylated typically occurring nucleotide and an unmethylated selected nucleotide specifically refers to an unmethylated typically occurring nucleotide.

[0122] The term "methylation-specific restriction enzyme" refers to a restriction enzyme that selectively digests nucleic acids according to the methylation state of the nucleic acid recognition site. In the case of a restriction enzyme that specifically cuts when the recognition site is not methylated or hemimethylated (methylation-sensitive enzyme), if the recognition site is methylated on one or both chains, cutting will not occur (or the efficiency is significantly reduced). In the case of a restriction enzyme that specifically cuts when only the recognition site is methylated (methylation-dependent enzyme), if the recognition site is not methylated, cutting will not occur (or it will occur, but the efficiency is significantly reduced). Preferably, the methylation-specific restriction enzyme has a recognition sequence containing a CG dinucleotide (for example, a recognition sequence, such as CGCG or CCCGGG). Further preferred for some embodiments is a restriction enzyme that will not cut if the cytosine in this dinucleotide is methylated at the carbon atom C5 place.

[0123] As used herein, the "sensitivity" of a given marker (or a set of markers used together) refers to the percentage of samples reporting DNA methylation values ​​above a threshold value that distinguishes neoplastic samples from non-neoplastic samples. In some embodiments, a positive is defined as a histologically confirmed neoplasm formation with a reported DNA methylation value above a threshold value (e.g., a range associated with the disease), and a false negative is defined as a histologically confirmed neoplasm formation with a reported DNA methylation value below a threshold value (e.g., a range associated with no disease). Thus, the value of sensitivity reflects the probability that the DNA methylation measurement value of a given marker obtained from a known disease sample is within the disease-related measurement range. As defined herein, the clinical relevance of a calculated sensitivity value represents an estimate of the probability of detecting the presence of a given marker when applied to a subject with a clinical disease.

[0124] As used herein, the "specificity" of a given marker (or a set of markers used together) refers to the percentage of non-neoplastic samples that report DNA methylation values ​​below a threshold value that distinguishes neoplastic samples from non-neoplastic samples. In some embodiments, a negative is defined as a histologically confirmed non-neoplastic sample that reports a DNA methylation value below a threshold value (e.g., a range associated with the absence of disease), and a false positive is defined as a histologically confirmed non-neoplastic sample that reports a DNA methylation value above a threshold value (e.g., a range associated with disease). Thus, the value of specificity reflects the probability that a DNA methylation measurement value for a given marker obtained from a known non-neoplastic sample is within a non-disease-related measurement range. As defined herein, the clinical relevance of a calculated specificity value represents an estimate of the probability of detecting the absence of a given disease when the given marker is applied to a patient who does not suffer from the clinical disease.

[0125] As used herein, the term "AUC" is an abbreviation for "area under the curve". It refers in particular to the area under the receiver operating characteristic (ROC) curve. The ROC curve is a graph showing the true positive rate and false positive rate for different possible cut-off points of a diagnostic test. It shows the trade-off between sensitivity and specificity (any increase in sensitivity will be accompanied by a decrease in specificity) according to the selected critical point. The area under the ROC curve (AUC) is a measure of the accuracy of a diagnostic test (the larger the area, the better; the optimal value is 1; the ROC curve for a random test is on the diagonal with an area of ​​0.5; Reference: JPEgan. (1975) Signal Detection Theory and ROC Analysis, Academic Press, New York).

[0126] As used herein, the term "neoplasm" refers to any new abnormal growth of tissue. Thus, a neoplasm can be a precancerous neoplasm or a malignant neoplasm.

[0127] The term "vegetation-specific marker" as used herein refers to any biological material or element that can be used to indicate the presence of a vegetation. Examples of biological materials include, but are not limited to, nucleic acids, polypeptides, carbohydrates, fatty acids, cell components (e.g., cell membranes and mitochondria) and whole cells. In some cases, a marker is a specific nucleic acid region (e.g., a gene, an intragenic region, a specific locus, etc.). A nucleic acid region as a marker can be referred to as, for example, a "marker gene," "marker region," "marker sequence," "marker locus," etc.

[0128] As used herein, the term "adenoma" refers to a benign tumor of glandular origin. Although these growths are benign, they may develop into malignant tumors over time.

[0129] The terms "precancerous" or "preneoplastic" and equivalents refer to any cell proliferative disorder that is undergoing malignant transformation.

[0130] The "site" of a neoplasm, adenoma, cancer, etc. is the tissue, organ, cell type, anatomical region, body part, etc., within a subject where the neoplasm, adenoma, cancer, etc. is located.

[0131] As used herein, "diagnostic" test applications include detecting or identifying a disease state or condition in a subject, determining the likelihood that a subject is infected with a given disease or condition, determining the likelihood that a subject with a disease or condition will respond to therapy, determining the prognosis of a subject with a disease or condition (or its likely progression or regression), and determining the effect of a treatment on a subject with a disease or condition. For example, diagnostics can be used to detect the presence or likelihood of a subject being infected with a neoplasm, or the likelihood that such a subject will respond favorably to a compound (e.g., a drug, e.g., pharmaceutical) or other treatment.

[0132] When the term "isolated" is applied to a nucleic acid (e.g., an "isolated oligonucleotide"), it refers to a nucleic acid sequence that has been identified and separated from at least one contaminating nucleic acid with which it is normally associated in its natural source. An isolated nucleic acid is present in a form or setting different from that in which it is found in nature. In contrast, unisolated nucleic acids, such as DNA and RNA, are found in the state in which they exist in nature. Examples of unisolated nucleic acids include a given DNA sequence (e.g., a gene) found adjacent to a gene on a host cell chromosome; an RNA sequence, such as a specific mRNA sequence encoding a specific protein, is found in a cell as a mixture with many other mRNAs encoding a variety of proteins. However, an isolated nucleic acid encoding a specific protein includes, for example, such a nucleic acid in a cell that normally expresses the protein, where the nucleic acid is in a chromosomal location different from that of the natural cell, or is otherwise flanked by nucleic acids different from those found in nature. An isolated nucleic acid or oligonucleotide can exist in single-stranded or double-stranded form. When an isolated nucleic acid or oligonucleotide is used to express a protein, the oligonucleotide will contain at least the sense strand or coding strand (i.e., the oligonucleotide can be single-stranded), but may contain both the sense strand and the antisense strand (i.e., the oligonucleotide can be double-stranded). An isolated nucleic acid can be combined with other nucleic acids or molecules after being separated from its natural or typical environment. For example, an isolated nucleic acid can be present in a host cell into which it is placed, for example, for heterologous expression.

[0133] The term "purified" refers to a molecule, whether a nucleic acid or an amino acid sequence, that is removed, separated or isolated from its natural environment. Thus, an "isolated nucleic acid sequence" can be a purified nucleic acid sequence. A "substantially purified" molecule is at least 60% free, preferably at least 75% free, and more preferably at least 90% free from other components with which it is naturally associated. As used herein, the term "purified" or "to purify" also refers to the removal of contaminants from a sample. Removal of contaminating proteins increases the percentage of the polypeptide or nucleic acid of interest in the sample. In another example, a recombinant polypeptide is expressed in a plant, bacterial, yeast or mammalian host cell, and the polypeptide is purified by removing host cell proteins; thereby increasing the percentage of the recombinant polypeptide in the sample.

[0134] The term "composition comprising" a given polynucleotide sequence or polypeptide broadly refers to any composition containing the given polynucleotide sequence or polypeptide. The composition may comprise an aqueous solution containing a salt (e.g., NaCl), a detergent (e.g., SDS), and other ingredients (e.g., Denhardt's solution, powdered milk, salmon sperm DNA, etc.).

[0135] The term "sample" is used in its broadest sense. In one sense, it can refer to animal cells or tissues. In another sense, it refers to specimens or cultures obtained from any source, as well as biological samples and environmental samples. Biological samples can be obtained from plants or animals (including humans) and encompass fluids, solids, tissues, and gases. Environmental samples include environmental materials such as surface materials, soil, water, and industrial samples. These examples should not be construed as limiting the sample types applicable to the various embodiments of the present disclosure.

[0136] As used herein, "remote sample" as used in some instances relates to a sample that is collected indirectly from a site that is not the source of the cells, tissues, or organs of the sample. For example, when a sample material originating from the pancreas is assessed in a stool sample, the sample is a remote sample.

[0137] As used herein, the term "patient" or "subject" refers to an organism to be subjected to the various tests described herein. The term "subject" includes animals, preferably mammals, including humans. In a preferred embodiment, the subject is a primate. In an even more preferred embodiment, the subject is a human. Further with respect to the diagnostic methods, the preferred subject is a vertebrate subject. The preferred vertebrate is warm-blooded; the preferred warm-blooded vertebrate is a mammal. The preferred mammal is most preferably a human. As used herein, the term "subject" includes both human and animal subjects. Thus, veterinary therapeutic uses are provided herein. Thus, the present disclosure provides diagnostics for mammals, such as humans, as well as those mammals that are important because they are endangered, such as Siberian tigers; mammals of economic importance, such as animals raised on farms for human consumption; and / or animals of social importance to humans, such as animals kept as pets or in zoos. Examples of such animals include, but are not limited to, carnivorous plants, such as cats and dogs; swine, including pigs, hogs, and wild boars; ruminants and / or ungulates, such as cattle, bulls, sheep, giraffes, deer, goats, bison, and camels; pinnipeds; and horses. Thus, diagnosis and treatment of livestock are also provided, including, but not limited to, domestic pigs, ruminants, ungulates, horses (including racehorses), and the like. Embodiments of the present disclosure also include systems for diagnosing one or more types or subclasses of gynecological cancer in a subject. The system may be provided, for example, as a commercial kit that can be used to screen a subject for the risk of one or more types or subclasses of gynecological cancer, or to diagnose one or more types or subclasses of gynecological cancer, from a subject from whom a biological sample has been collected. Exemplary systems provided according to various embodiments of the present disclosure include assessing the methylation status or profile of a marker, as described herein.

[0138] As used herein, the term "kit" refers to any delivery system for delivering materials. In the case of a reaction assay, such a delivery system includes a system that allows storage of reaction reagents (e.g., oligonucleotides, enzymes, etc. in appropriate containers) and / or support materials (e.g., buffers, written instructions for determining the assay, etc.), transporting them from one location or delivering them to another. For example, a kit includes one or more housings (e.g., boxes) containing relevant reaction reagents and / or support materials. As used herein, the term "dispersed kit" refers to a delivery system comprising two or more separate containers, each containing a sub-portion of all kit components. These containers can be delivered to a predetermined recipient together or individually. For example, a first container may contain an enzyme for determination, while a second container contains oligonucleotides. The term "dispersed kit" is intended to encompass kits containing analyte-specific reagents (ASRs) regulated by Section 520 (e) of the Federal Food, Drug, and Cosmetic Act, but is not limited thereto. In fact, any delivery system comprising two or more separate containers each containing a sub-portion of all kit components is included in the term "dispersed kit." In contrast, a "combination kit" refers to a delivery system that contains all components of a reaction assay in a single container (eg, a single box containing each required component). The term "kit" includes both discrete kits and combination kits.

[0139] As used herein, the term "information" refers to a collection of any facts or data. When referring to information stored or processed using a computer system (including but not limited to the Internet), the term refers to any data stored in any format (such as analog, digital, optical, etc.). The term "information related to a subject" as used herein refers to facts or data belonging to a subject (such as humans, plants, or animals). The term "genomic information" refers to information related to a genome, including but not limited to nucleic acid sequences, genes, methylation percentages, allele frequencies, RNA expression levels, protein expression, phenotypes related to genotypes, etc. "Allele frequency information" refers to facts or data related to allele frequencies, including but not limited to statistical correlations between allele identity, the presence of alleles and a characteristic of a subject (such as a human subject), the presence or absence of alleles in an individual or population, the probability percentage of the presence of alleles in an individual with one or more specific characteristics, etc.

[0140] 2. Methylated DNA Markers and Biomarker Panels

[0141] The embodiments of the present disclosure provide methods, compositions and systems for screening various types of gynecological cancers from biological samples. According to these embodiments, the present disclosure includes but is not limited to methods and compositions for detecting the presence of various types or subclasses of gynecological cancers from biological samples. In some embodiments, the biological sample is a tissue sample, a blood sample, a plasma sample, a serum sample, a whole blood sample, a secretion sample, an organ secretion sample, a cerebrospinal fluid (CSF) sample, a saliva sample, a urine sample and / or a fecal sample. In some embodiments, the tissue sample is a gynecological tissue sample, which includes one or more of the following: vaginal tissue, vaginal cells, cervical tissue, cervical cells, endometrial tissue, endometrial cells, ovarian tissue and ovarian cells. In some embodiments, the tissue sample is an ovarian tissue sample, an endometrial tissue sample or a cervical tissue sample. In some embodiments, the secretion sample is secretion or discharge from any gynecological organ or tissue, including but not limited to vaginal tissue, cervical tissue, uterine tissue, endometrial tissue and ovarian tissue. In some embodiments, the subject is a human being.

[0142] As further described herein, embodiments of the present disclosure include novel differentially methylated regions (DMRs), each of which is capable of individually distinguishing a specific type of gynecological cancer, namely endometrial cancer (EC) or ovarian cancer (OC) or cervical cancer (CC), from benign gynecological tissue samples. According to these embodiments, these novel DMRs comprise one or more CpG sites of: ADAM8, ADHFE1, AES, AGBL2, AIM1, AK5, ALKBH3, ARAP1, ARHGAP20, ASCL2, BCAT1, BEGAIN, BEND4_3696, BMP6, C12orf68, C13orf18, C14orf169_7694, C14orf169_8382, C18orf18, C1orf61, C20orf195, C4orf31, C5orf52, C6orf 147, C7orf51, CD14, CELF2, CHCHD5, CHMP2A, CHST10, CLIC6, CLIP4, COL13A1, COL19A1, COL6A2, COPZ2, CREB3L1, CXCL2, CXXC5, CYTH 2. DAB2IP, DGKZ, DLGAP3, DNASE2, DSCAML1, EBF1, EDARADD, EGR2, EIF5A2, ELMO1, ELMOD1, ELOVL4, EME2, EML6, EPSTI1, FADS2, FAM10 9B, FAM126A, FAM174B, FGF18, FKBP11, FLI1, FLOT1, FOXD3, FYN, GAL3ST2, GALR3, GAS7, GATA2_5878, GLT25D2, GNB2, HDAC7, HIC1, HL A-F, HNRNPF, HPDL, HS3ST4, HSPA1A, IDUA, IGSF9B, IL12RB2, IRAK3, IRF7, IRF8, ITPKA, KCNA2, KCNC3_6487, KCNC3_7105, KCNC4, KCN H8, KDM2B, LBX2, LCMT2, LOC100129726, LOC100287216, LOC255130, LOC339290, LOC729678, LPPR3, LRRC41, LRRC8D_8856, LTBP2, LY PLAL1, MAST4, MAX.chr1.2152, HIVEP3, GRAMD1B, MAX.chr11.0394, MAX.chr11.3750, FAT3, SLC16A7, MTUS2, LINC02323, MAX.chr14.7696、MCTP2、LOC107984974、TRIM80P、MAX.chr19.5552、ZNF433-AS1、ZNF254、MAX.chr19.0548、B3GALT1、MAX.chr2.8918、MAX.chr2.4778、MAX.chr20.3853、MAX.chr20.2903、MAX.chr21.5011、DSCR9、MAX.chr22.5665、MAX.chr3.6408、LINC02028、LINC02084、MAX.chr5.3588、CTD-2532K18.1、HS3ST5、ARHGAP18、GRM4、LINC01004、MAX.chr8.5938、MAX.chr9.4007、MAX.chr9.2025, TRPM3, MED12L, MIAT, MLH1_4513, MLH1_5193, MMP16, MRPS21, MSI1, MT1E, MX1, MYC, MYH10, MYO15B, N4BP2L1, NBR1 , NDRG2, NEGR1, NEU1, NOL3, NR3C1_2223, NR3C1_4614, NRP2, NTN1, NTNG1, PAPL, PAQR9, PDE10A, PDE3B, PDE4A, PDXK, PER 1. PISD, PLEC, PLIN2, PLXND1, PPM1E, PPP1R9A, PPP2R5C, PRDM5, PTP4A3, PYCARD, RAB3C, RAI1, RARG, RASA3, RPRM, RREB1 , S100A6, SAMD5, SBNO2, SDC2, SDK2, SELM, SERP2, SFMBT2_2029, SHF, SHH, SLC16A11, SLC16A5, SLC25A22, SLCO3A1, SMTN , SPDYA, SPINK2, SPOCK2, SPON1, SQSTM1_4156, ST8SIA1, TAF4B, TAF7, TEAD3, TERC, TIAM1, TLE4, TMEM101, TMEM106A, TR IM9, TRPC3, TSC22D4, TSPAN2, TSPAN5, TTC14, UBB_4001, UBB_4646, UST, VAMP5, VIM, VSTM2B, ZBTB7B, ZEB2, ZFP3, ZFP36 L2, ZIC2, ZMIZ1, ZNF14, ZNF211, ZNF280B, ZNF302, ZNF382, ZNF480, ZNF483, ZNF491, ZNF569, ZNF610, ZNF702P, ZNF709, ZNF773, ZNF845, ZNF91, CDH4, LRRC34, MAX.chr10.4460, NBPF24, OBSCN, SEPT9, ZNF323, ZNF506, and / or ZNF90 (Table 1), including any combination thereof. In some embodiments, the novel DMR is from any gene or region selected from Table 1, including any combination thereof. Each novel DMR alone is capable of distinguishing one or more gynecological cancers from a control sample, and combining two or more novel DMRs can provide increased sensitivity. Thus, combinations of two or more novel DMRs selected from Table 1 are provided.

[0143] Embodiments of the present disclosure also include novel differentially methylated regions (DMRs), each of which is capable of individually distinguishing gynecological cancers from benign gynecological tissue samples; these DMRs are prevalent in all three types of gynecological cancer (i.e., endometrial cancer (EC), ovarian cancer (OC), and cervical cancer (CC)). According to these embodiments, these novel DMRs comprise one or more CpG sites among the following: ACSF2, AJAP1, ARL10, ARL5C, ASCL4, ATP6V1B1, BARHL1, BEND4_2963, C17orf64, C1QL3, C2orf55, C4orf48, CA3, CDO1, CELF2, CLEC14A, CSDAP1, CYTH2_4197, DLGAP1, DSCR6, EPS8L1_2819, EPS8L1_8496, FAIM2, FGF12, GATA2, H IST1H2BE, IRF4, IRX4, ITGA5, KCNA1, LECT1, LHX1, LOC440925, LPHN1, LINC02767, MAX.chr1.2533, SOX1-OT, MAX.chr13.3357, MAX. chr14.2093, MAX.chr17.2455, MAX.chr18.4390, MAX.chr19.2732, MAX.chr19.4467, PANTR1, MAX.chr2.0490, MAX.chr2.8148, MAX. chr2.3137, RIPOR3, SCRG1, MAX.chr4.4210, HMX1, CTC-359M8.1, MAX.chr5.0931, MAX.chr5.9924, LIN28B, MAX.chr6.9522, TTLL2, RNA5SP243, DLGAP2, MEX3B, MNX1, NEFL, NETO1, PAX2, PDX1, psiTPTE22, RASGEF1A, SALL3_9136, SALL3_0615, SEZ6L2, SHANK2, SHANK 3, SKI, SLC35D3, SORCS3_0305, SORCS3_1038, SOX1, SQSTM1, TBXT, TCERG1L, TERT, TNFSF11, TUBB6, ULBP1, VAC14, VWC2, WDR69, ZBTB16, ZNF132, ZSCAN12, ZSCAN23, KRT86, CYP26C1, GYPC, DIDO1, EEF1A2, EMX2OS, GDF7, JSRP1, SMPD5, MDFI, MPZ, and / or VILL (Table 2), including any combination thereof.In some embodiments, the novel DMR is from any gene or region selected from Table 2, including any combination thereof. Each novel DMR alone is capable of distinguishing one or more gynecological cancers from control samples, and combining two or more novel DMRs can provide increased sensitivity. Thus, a combination of two or more novel DMRs selected from Table 2 is provided.

[0144] Embodiments of the present disclosure also include novel differentially methylated regions (DMRs), each of which is capable of individually distinguishing a specific subclass of gynecological cancer (i.e., serous ovarian cancer, clear cell ovarian cancer, endometrioid ovarian cancer, mucinous ovarian cancer, adenocarcinoma cervical cancer, squamous cervical cancer, or endometrioid endometrial cancer) from benign gynecological tissue samples. According to these embodiments, the novel DMRs comprise one or more CpG sites selected from the group consisting of AIM1, AK5, c18orf18, CDO1, DLGAP1, ELMOD1, FKBP11, FLOT1, GAL3ST2, LRRC41, LYPLAL1, MAX.chr11.3750, MLH1_4513, NR3C1_2223, PISD.RABC3, RAI1, TERC, TRPC3, ZIC2, ZMIZ1, ZNF480, ZNF491, ZNF610, and / or ZNF91 (Table 3), including any combination thereof. In some embodiments, the novel DMRs are from any gene or region selected from Table 3, including any combination thereof. Each novel DMR alone is capable of distinguishing one or more gynecological cancers from a control sample, and combining two or more novel DMRs can provide increased sensitivity. Thus, combinations of two or more novel DMRs selected from Table 3 are provided.

[0145] Embodiments of the present disclosure also include novel differentially methylated regions (DMRs), each of which is capable of individually distinguishing a specific subclass of gynecological cancer (i.e., serous ovarian cancer, clear cell ovarian cancer, endometrioid ovarian cancer, mucinous ovarian cancer, adenocarcinoma cervical cancer, squamous cervical cancer, or endometrioid endometrial cancer) from benign gynecological tissue samples. According to these embodiments, these novel DMRs comprise one or more CpG sites of: LBX2, SPDYA, TERC, ZSCAN12, CYP26C1, and / or GYPC (Table 4), including any combination thereof. In some embodiments, the novel DMRs are from any gene or region selected from Table 4, including any combination thereof. Each novel DMR alone is capable of distinguishing one or more gynecological cancers from a control sample, and combining two or more novel DMRs can provide increased sensitivity. Thus, a combination of two or more novel DMRs selected from Table 4 is provided.

[0146] Embodiments of the present disclosure also include novel differentially methylated regions (DMRs), each of which is capable of individually distinguishing a specific subclass of gynecological cancer (i.e., serous ovarian cancer, clear cell ovarian cancer, endometrioid ovarian cancer, mucinous ovarian cancer, adenocarcinoma cervical cancer, squamous cervical cancer, or endometrioid endometrial cancer) from benign gynecological tissue samples. According to these embodiments, the novel DMRs comprise one or more CpG sites in: KRT86, CDH4, c17orf64, EMX2OS, NBPF24, SFMBT2_0970, JSRP1, DIDO1, MAX.chr10.4460, MPZ, ZNF506, GATA2_6370, VILL, LINC02323, CYTH2_4043, LRRC8D_8831, LYPLAL1, SMPD5, SQSTM1_3864, ZNF323, OBSCN, ZNF90, LRRC34, GDF7, MDFI, EEF1A2, LRRC41 and / or SEPT9 (Table 8), including any combination thereof. In some embodiments, the novel DMRs are from any gene or region selected from Table 8, including any combination thereof. Each novel DMR alone is capable of distinguishing one or more gynecological cancers from control samples, and combining two or more novel DMRs may provide increased sensitivity. Thus, a combination of two or more novel DMRs selected from Table 8 is provided.

[0147] As described in the preceding examples, experiments were conducted to identify DMRs (also referred to herein as methylated DNA markers (MDMs)) that can distinguish types and subclasses of gynecological cancers from controls (e.g., healthy or benign samples). These experiments involved validation studies of the utility and performance of a panel of methylated DNA markers and proteins to detect one or more types or subclasses of gynecological cancers by testing an independent set of case / control samples using a refined set of markers. Such experiments led to the identification of MDMs that can be used to simultaneously detect the presence of multiple types of gynecological cancers (i.e., endometrial cancer (EC), ovarian cancer (OC), or cervical cancer (CC)) from benign gynecological tissue samples (e.g., stool samples, tissue samples, organ samples, secretion samples (e.g., vaginal secretion samples), CSF samples, saliva samples, blood samples, plasma samples, or urine samples).

[0148] In some embodiments, the present disclosure provides compositions and methods for identifying, determining and / or classifying various types or subclasses of gynecological cancer from biological samples (e.g., stool samples, tissue samples, organ samples, secretion samples, CSF samples, saliva samples, blood samples, plasma samples, or urine samples). The method generally comprises determining the methylation profile of at least one methylation marker in a biological sample isolated from a subject. In some embodiments, a change in the methylation state or profile of the marker indicates the presence, category, or location of a particular type of gynecological cancer. In general, such methods include, but are not limited to, detecting the presence or absence of a particular type or subclass of gynecological cancer. In some embodiments, the types and subclasses of cancer include, but are not limited to, endometrial cancer, ovarian cancer, cervical cancer, serous ovarian cancer, clear cell ovarian cancer, endometrioid ovarian cancer, mucinous ovarian cancer, adenocarcinoma cervical cancer, squamous cervical cancer, and endometrioid endometrial cancer.

[0149] In some embodiments, provided methods include contacting nucleic acid (e.g., genomic DNA) in a biological sample obtained from a subject with at least one reagent or a series of reagents that distinguishes between methylated and unmethylated nucleotides (e.g., CpG dinucleotides) within at least one methylation marker; and detecting the presence or absence of one or more types or subclasses of gynecological cancer (e.g., with a sensitivity greater than or equal to 80% and a specificity greater than or equal to 80%).

[0150] In some embodiments, provided methods include: measuring one or both of the methylation levels of one or more genes or methylated DNA markers in a biological sample from a human individual by treating genomic DNA in the biological sample with an agent that modifies DNA in a methylation-specific manner; amplifying the treated genomic DNA using a set of primers for the selected one or more genes or methylation markers; and determining the methylation levels of the one or more genes or methylation markers.

[0151] In some embodiments, provided methods include: measuring the amount of one or more methylated DNA markers or genes in DNA from a biological sample; measuring the amount of at least one reference marker in the DNA; and calculating a percentage value of the amount of the at least one methylated marker gene measured in the DNA relative to the amount of the reference marker gene measured in the DNA, wherein the value represents the amount of the at least one methylated marker DNA measured in the biological sample.

[0152] In some embodiments, the provided methods include: measuring the methylation level of CpG sites of one or more genes in a biological sample of a human individual by treating genomic DNA in the biological sample with a bisulfite reagent that can modify DNA in a methylation-specific manner; amplifying the modified genomic DNA using a set of primers for the selected one or more genes; and determining the methylation level of the CpG sites of the selected one or more genes.

[0153] In some embodiments, the present disclosure provides a method for characterizing a biological sample, the method comprising: measuring one or both of the methylation levels of CpG sites of one or more genes in a biological sample of a human individual by treating genomic DNA in the biological sample with bisulfite; amplifying the bisulfite-treated genomic DNA using a set of primers for the selected one or more genes; and determining the methylation levels of the CpG sites. In some embodiments, the method comprises comparing one or both of the methylation levels of the methylation markers with the methylation levels of a set of corresponding genes in a control sample that does not have a specific type of cancer; and / or determining that the subject has one or more types or subtypes of gynecological cancer when one or both of the methylation levels measured in the one or more genes are higher than the methylation levels measured in the corresponding control samples.

[0154] In some embodiments, the present disclosure provides methods comprising: measuring one or both of the methylation levels of one or more genes or markers in a biological sample by treating genomic DNA in the biological sample with bisulfite; amplifying the bisulfite-treated genomic DNA using a set of primers for the selected gene or genes; and determining the methylation levels of the one or more genes or markers.

[0155] In some embodiments, the present disclosure provides methods for screening for one or more types or subtypes of gynecological cancer in a sample obtained from a subject. According to these embodiments, the method comprises one or both of: determining the methylation state or profile of one or more methylated DNA markers; and identifying the subject as having the one or more types or subtypes of gynecological cancer when the methylation state or profile of the markers is different from the methylation state or profile of the markers determined in a subject who does not have the one or more types of cancer.

[0156] In some embodiments, the present disclosure provides methods comprising: measuring the methylation level of one or more genes or markers in a biological sample of a human individual by treating genomic DNA in the biological sample with a reagent that modifies DNA in a methylation-specific manner; amplifying the treated genomic DNA using a set of primers for the selected one or more genes or markers; and determining the methylation level of the one or more genes or markers.

[0157] In some embodiments, the present disclosure provides a method for characterizing a biological sample, the method comprising: measuring the amount of at least one methylated DNA marker in DNA extracted from the biological sample; treating the genomic DNA in the biological sample with bisulfite; and amplifying the bisulfite-treated genomic DNA using primers specific for the CpG sites of each marker. In some embodiments, the primers specific for each marker are capable of binding to an amplicon bound by a primer sequence of a marker listed in Table 1 or Table 2, wherein the amplicon bound by the primer sequence of the marker is at least a portion of a gene region of a methylation marker listed in Table 1 or Table 2; and determining the methylation level of the CpG sites of one or more genes.

[0158] In some embodiments, the present disclosure provides a method comprising: extracting genomic DNA from a biological sample of a human individual suspected of having or having one or more types or subtypes of gynecological cancer, measuring the methylation level of one or more methylated DNA markers in the DNA extracted from the biological sample; treating the extracted genomic DNA with bisulfite; and amplifying the bisulfite-treated genomic DNA with primers specific for one or more markers. In some embodiments, the primers specific for one or more markers are capable of binding to at least a portion of the bisulfite-treated genomic DNA for a chromosomal region of the marker (e.g., one or more markers listed in Table 1 or Table 2), and measuring the methylation level of one or more methylated markers.

[0159] In some embodiments, the present disclosure provides methods comprising: extracting genomic DNA from a biological sample of a human individual suspected of having or having one or more types or subtypes of gynecological cancer, measuring the methylation level of one or more methylated DNA markers in the DNA extracted from the biological sample; treating the extracted genomic DNA with bisulfite, amplifying the bisulfite-treated genomic DNA using primers specific for the one or more markers, wherein the primers specific for the one or more markers are capable of binding to at least a portion of the bisulfite-treated genomic DNA for a chromosomal region of a marker listed in Table 2; and measuring the methylation level of the one or more methylated markers.

[0160] In some embodiments, the present disclosure provides methods comprising: extracting genomic DNA from a biological sample of a human individual suspected of having or having one or more types or subtypes of gynecological cancer, measuring the methylation level of one or more methylated DNA markers in the DNA extracted from the biological sample; treating the extracted genomic DNA with bisulfite, amplifying the bisulfite-treated genomic DNA using primers specific for the one or more markers, wherein the primers specific for the one or more markers are capable of binding to at least a portion of the bisulfite-treated genomic DNA for a chromosomal region of a marker listed in Table 3; and measuring the methylation level of the one or more methylated markers.

[0161] In some embodiments, the present disclosure provides methods comprising: extracting genomic DNA from a biological sample of a human individual suspected of having or having one or more types or subtypes of gynecological cancer, measuring the methylation level of one or more methylated DNA markers in the DNA extracted from the biological sample; treating the extracted genomic DNA with bisulfite, amplifying the bisulfite-treated genomic DNA using primers specific for the one or more markers, wherein the primers specific for the one or more markers are capable of binding to at least a portion of the bisulfite-treated genomic DNA for a chromosomal region of a marker listed in Table 4; and measuring the methylation level of the one or more methylated markers.

[0162] In some embodiments, the present disclosure provides methods comprising: extracting genomic DNA from a biological sample of a human individual suspected of having or having one or more types or subtypes of gynecological cancer, measuring the methylation level of one or more methylated DNA markers in the DNA extracted from the biological sample; treating the extracted genomic DNA with bisulfite, amplifying the bisulfite-treated genomic DNA using primers specific for the one or more markers, wherein the primers specific for the one or more markers are capable of binding to at least a portion of the bisulfite-treated genomic DNA for a chromosomal region of a marker listed in Table 8; and measuring the methylation level of the one or more methylated markers.

[0163] In some embodiments, the present disclosure provides methods comprising extracting genomic DNA from a biological sample of a human individual suspected of having or having cancer, treating the extracted genomic DNA with bisulfite, amplifying the bisulfite-treated genomic DNA using separate primers specific for CpG sites of one or more methylated DNA markers, and measuring the methylation level of the CpG sites for each of the one or more markers.

[0164] In some embodiments, the present disclosure provides a method for preparing a DNA portion from a biological sample of a human individual that can be used to analyze one or more genetic loci involved in one or more chromosomal aberrations. According to these embodiments, the method includes extracting genomic DNA from a biological sample of a human individual; generating a portion of the extracted genomic DNA by treating the extracted genomic DNA with an agent that modifies DNA in a methylation-specific manner; amplifying the sulfite-treated genomic DNA using separate primers specific for one or more methylated DNA markers; and analyzing the one or more genetic loci in the generated portion of the extracted genomic DNA by measuring the methylation level of the one or more marked CpG sites.

[0165] In some embodiments, the present disclosure provides a method for preparing a DNA portion from a biological sample of a human individual that can be used to analyze one or more DNA fragments involved in one or more chromosomal aberrations. According to these embodiments, the method includes extracting genomic DNA from a biological sample of a human individual; generating a portion of the extracted genomic DNA by treating the extracted genomic DNA with an agent that modifies DNA in a methylation-specific manner; amplifying the sulfite-treated genomic DNA using separate primers specific for one or more methylated DNA markers; and analyzing one or more DNA fragments in the generated portion of the extracted genomic DNA by measuring the methylation level of one or more marked CpG sites.

[0166] Based on the present disclosure, it will be understood by those skilled in the art that the various methods described herein are not limited to the use of any one specific methylated DNA marker, methylated marker gene, methylated gene and / or DMR. That is, one or more of the methylated DNA marker, methylated marker gene, methylated gene and / or DMR disclosed herein can be used to distinguish and / or identify one or more types or subclasses of gynecological cancer, including any combination thereof. In addition, the methylated DNA marker, methylated marker gene, methylated gene and / or DMR disclosed herein may include regions or subregions of any marker described herein (e.g., genes on chromosomes, single nucleotides, CpG islands, etc.).

[0167] In some embodiments, at least one DMR comprises one or more CpG sites among AIM1, FLOT1, GAL3ST2, LRRC41, LYPLAL1, MAX.chr11.3750, PISD, RAI1, ZIC2, ZMIZ1, CDH4, ZNF506, ZNF323, OBSCN, ZNF90, and / or SEPT9; and the subject has or is suspected of having ovarian cancer (OC). In some embodiments, at least one DMR comprises one or more CpG sites among AIM1, FLOT1, GAL3ST2, LYPLAL1, and / or OBSCN; and the subject has or is suspected of having serous OC. In some embodiments, at least one DMR comprises one or more CpG sites among LRRC41, PISD, ZIC2, OBSCN, and / or SEPT9; and the subject has or is suspected of having clear cell OC. In some embodiments, at least one DMR comprises one or more CpG sites in MAX.chr11.3750; and the subject has or is suspected of having endometrioid OC. In some embodiments, at least one DMR comprises one or more CpG sites in RAI1 and / or ZMIZ1; and the subject has or is suspected of having mucinous OC. In some embodiments, determining the methylation profile of one or more CpG sites in AIM1, FLOT1, GAL3ST2, LRRC41, LYPLAL1, MAX.chr11.3750, PISD, RAI1, ZIC2, ZMIZ1, CDH4, ZNF506, ZNF323, OBSCN, ZNF90, and / or SEPT9 comprises comparing the methylation profile to corresponding regions in a control DNA sample obtained from a subject who does not have OC.

[0168] In some embodiments, at least one DMR comprises one or more CpG sites selected from the group consisting of AK5, ELMOD1, RABC3, TRPC3, ZNF480, ZNF491, ZNF610, ZNF91, and / or NBPF24, and the subject has or is suspected of having cervical cancer (CC). In some embodiments, at least one DMR comprises one or more CpG sites selected from the group consisting of AK5, ELMOD1, TRPC3, and / or ZNF480, and the subject has or is suspected of having adenocarcinoma (CC). In some embodiments, at least one DMR comprises one or more CpG sites selected from the group consisting of ZNF491, ZNF610, ZNF91, and / or NBPF24, and the subject has or is suspected of having squamous cell (CC) cancer. In some embodiments, determining the methylation profile of one or more CpG sites in AK5, ELMOD1, RABC3, TRPC3, ZNF480, ZNF491, ZNF610, and / or ZNF91 comprises comparing the methylation profile to corresponding regions in a control DNA sample obtained from a subject not having CC.

[0169] In some embodiments, at least one DMR comprises one or more CpG sites in c18orf18, FKBP11, MLH1, NR3C1, and / or TERC; and the subject has or is suspected of having endometrial cancer (EC). In some embodiments, at least one DMR comprises one or more CpG sites in MLH1 and / or SEPT9; and the subject has or is suspected of having clear cell EC. In some embodiments, at least one DMR comprises one or more CpG sites in NR3C1; and the subject has or is suspected of having endometrioid EC. In some embodiments, determining the methylation profile of one or more CpG sites in c18orf18, FKBP11, MLH1, NR3C1, and / or TERC comprises comparing the methylation profile to corresponding regions in a control DNA sample obtained from a subject who does not have EC.

[0170] In some embodiments, at least one DMR comprises one or more CpG sites in CDO1 and / or DLGAP1; and wherein the subject has or is suspected of having CC, OC, or EC. In some embodiments, determining the methylation profile of the one or more CpG sites in CDO1 and / or DLGAP1 comprises comparing the methylation profile to corresponding regions in a control DNA sample obtained from a subject who does not have CC, OC, or EC.

[0171] In some embodiments, the methods of the present disclosure comprise determining the methylation profile of one or more CpG sites in AIM1, FLOT1, GAL3ST2, LRRC41, LYPLAL1, MAX.chr11.3750, PISD, RAI1, ZIC2, and / or ZMIZ1. In some embodiments, the methods comprise determining the methylation profile of one or more CpG sites in AK5, ELMOD1, RABC3, TRPC3, ZNF480, ZNF491, ZNF610, and / or ZNF91. In some embodiments, the methods comprise determining the methylation profile of one or more CpG sites in c18orf18, FKBP11, MLH1, NR3C1, and / or TERC.

[0172] In some embodiments, the at least one DMR comprises NBPF24, and wherein the subject has or is suspected of having CC. In some embodiments, determining the methylation profile of NBPF24 comprises comparing the methylation profile to a corresponding region of a control DNA sample obtained from a subject not having CC.

[0173] In some embodiments, the at least one DMR comprises one or more CpG sites in CDH4, NBPF24, MAX.chr10.4460, ZNF506, ZNF323, OBSCN, ZNF90, LRRC34, SFMBT2, LINC02323, CYTH2, LRRC8D, LYPLAL1, LRRC41, and / or SEPT9, and wherein the subject has or is suspected of having EC. In some embodiments, determining the methylation profile of one or more CpG sites in CDH4, NBPF24, MAX.chr10.4460, ZNF506, ZNF323, OBSCN, ZNF90, LRRC34, SFMBT2, LINC02323, CYTH2, LRRC8D, LYPLAL1, LRRC41, and / or SEPT9 comprises comparing the methylation profile to corresponding regions in a control DNA sample obtained from a subject not having EC.

[0174] In some embodiments, the at least one DMR comprises one or more CpG sites in CDH4, ZNF506, ZNF323, OBSCN, ZNF90, SFMBT2, LINC02323, CYTH2, LRRC8D, LYPLAL1, LRRC41, and / or SEPT9, and wherein the subject has or is suspected of having OC. In some embodiments, determining the methylation profile of one or more CpG sites in CDH4, ZNF506, ZNF323, OBSCN, ZNF90, SFMBT2, LINC02323, CYTH2, LRRC8D, LYPLAL1, LRRC41, and / or SEPT9 comprises comparing the methylation profile to corresponding regions in a control DNA sample obtained from a subject who does not have OC.

[0175] In some embodiments, the at least one DMR comprises one or more CpG sites among KRT86, EMX2OS, JSRP1, DIDO1, MPZ, VILL, SMPD5, GDF7, MDFI, c17orf64, GATA2, SQSTM1, and / or EEF1A2, and wherein the subject has or is suspected of having CC, OC, or EC. In some embodiments, determining the methylation profile of one or more CpG sites among KRT86, EMX2OS, JSRP1, DIDO1, MPZ, VILL, SMPD5, GDF7, MDFI, c17orf64, GATA2, SQSTM1, and / or EEF1A2 comprises comparing the methylation profile to corresponding regions of a control DNA sample obtained from a subject not having CC, OC, or EC.

[0176] One of ordinary skill in the art will appreciate based on this disclosure that various marker combinations can be used to predict one or more types or subtypes of gynecological cancer (e.g., as determined by statistical techniques related to the specificity and sensitivity of the predictions). Embodiments of the present disclosure provide methods for identifying predictive combinations and validated predictive combinations for one or more types or subtypes of gynecological cancer.

[0177] Such methods are not limited to the type of subject. In some embodiments, the subject is a mammal. In some embodiments, the subject is a human. Such methods are not limited to a particular manner or technique for measuring protein expression and / or activity. Techniques for measuring protein expression and / or activity levels are known in the art. Indeed, any known technique for measuring protein expression and / or activity levels is contemplated and incorporated herein.

[0178] Such methods are not limited to a particular manner or technique for determining, characterizing, measuring or assaying the methylation of one or more methylation markers, methylation marker genes, genes, DMRs and / or DNA methylation markers. In some embodiments, such techniques are based on analysis of the methylation status (e.g., CpG methylation status) of at least one marker comprising a DMR, a marked region, or a marked base.

[0179] In some embodiments, measuring the methylation state or profile of a methylated DNA marker in a sample comprises determining the methylation state of one nucleotide base. In some embodiments, measuring the methylation state of a methylated DNA marker in a sample comprises determining the degree of methylation at a plurality of nucleotide bases. Additionally, in some embodiments, the methylation state or profile of a methylated DNA marker comprises an increase in methylation of the marker relative to a normal methylation state or profile of the marker. In some embodiments, the methylation state or profile of the marker comprises a decrease in methylation of the marker relative to a normal methylation state of the marker. In some embodiments, the methylation state or profile of the marker comprises a different pattern of methylation of the marker relative to a normal methylation state or profile of the marker.

[0180] In addition, in some embodiments, the marker is a region of 100 or less nucleotide bases. In some embodiments, the marker is a region of 500 or less nucleotide bases. In some embodiments, the marker is a region of 1000 or less nucleotide bases. In some embodiments, the marker is a region of 5000 or less nucleotide bases. In some embodiments, the marker is a single nucleotide base. In some embodiments, the marker is in a high CpG density promoter region.

[0181] In certain embodiments, methods for analyzing the presence of 5-methylcytosine in nucleic acids involve treating the DNA with a reagent that modifies the DNA in a methylation-specific manner. Examples of such reagents include, but are not limited to, methylation-sensitive restriction enzymes, methylation-dependent restriction enzymes, bisulfite reagents, TET enzymes, and borane reducing agents.

[0182] A common method for analyzing the presence of 5-methylcytosine in nucleic acids is based on the bisulfite method described by Frommer et al. (Frommer et al. (1992) Proc. Natl. Acad. Sci. USA 89: 1827–31, incorporated herein by reference in its entirety for all purposes) or variants thereof. The bisulfite method for mapping 5-methylcytosine is based on the observation that cytosine (rather than 5-methylcytosine) reacts with bisulfite ions (also known as bisulfite). The reaction is generally carried out according to the following steps: first, cytosine reacts with bisulfite to form sulfonated cytosine. Next, spontaneous deamination of the sulfonation reaction intermediate produces sulfonated uracil. Finally, the sulfonated uracil is desulfonated under alkaline conditions to form uracil. Detection is possible because uracil pairs with adenine bases (thus behaving like thymine), while 5-methylcytosine pairs with guanine bases (thus behaving like cytosine). This makes it possible to distinguish methylated from unmethylated cytosines by, for example, bisulfite genomic sequencing (Grigg G and Clark S, Bioessays (1994) 16:431–36; Grigg G, DNA Seq. (1996) 6:189–98), methylation-specific PCR (MSP) (as disclosed in U.S. Pat. No. 5,786,146), or using assays involving sequence-specific probe cleavage, such as the QuARTS flap endonuclease assay (see, e.g., Zou et al. (2010) “Sensitive quantification of methylated markers with a novel methylation specific technology” Clin Chem 56:A199; and U.S. Pat. Nos. 8,361,720; 8,715,937; 8,916,344; and 9,212,392).

[0183] In some embodiments, conventional techniques include methods that include encapsulating the DNA to be analyzed in an agarose matrix to prevent DNA diffusion and renaturation (bisulfite reacts only with single-stranded DNA) and replacing precipitation and purification steps with rapid dialysis (Olek A et al., (1996) "A modified and improved method for bisulfite-based cytosine methylation analysis" Nucleic Acids Res. 24:5064-6). This makes it possible to analyze the methylation status of individual cells, demonstrating the practicality and sensitivity of the method. Rein, T. et al., (1998) Nucleic Acids Res. 26:2255 provide an overview of conventional methods for detecting 5-methylcytosine.

[0184] Bisulfite techniques typically involve amplifying short, specific fragments of known nucleic acids after bisulfite treatment, followed by sequencing (Olek and Walter (1997) Nat. Genet. 17: 275–6) or assaying the products using primer extension reactions (Gonzalgo and Jones (1997) Nucleic Acids Res. 25: 2529–31; WO 95 / 00669; U.S. Patent No. 6,251,594) to analyze individual cytosine positions. Some methods use enzymatic digestion (Xiong and Laird (1997) Nucleic Acids Res. 25: 2532–4). Detection by hybridization has also been described in the art (Olek et al., WO 99 / 28498). In addition, the use of bisulfite technology to detect methylation of individual genes has been described (Grigg and Clark (1994) Bioessays 16:431-6; Zeschnigk et al. (1997) Hum Mol Genet. 6:387-95; Feil et al. (1994) Nucleic Acids Res. 22:695; Martin et al. (1995) Gene 157:261-4; WO9746705; WO 9515373).

[0185] According to embodiments of the present disclosure, various methylation assays can be used in conjunction with sulfite treatment. These assays allow determination of the methylation status of one or more CpG dinucleotides (e.g., CpG islands) in a nucleic acid sequence. Such assays involve sequencing of sulfite-treated nucleic acids, PCR (for sequence-specific amplification), Southern blot analysis, and the use of methylation-specific restriction enzymes (e.g., methylation-sensitive or methylation-dependent enzymes).

[0186] For example, genomic sequencing has been simplified by the use of bisulfite treatment to analyze methylation patterns and 5-methylcytosine distribution (Frommer et al. (1992) Proc. Natl. Acad. Sci. USA 89: 1827–1831). Additionally, restriction enzyme digestion of PCR products amplified from bisulfite-converted DNA can be used to assess methylation status, for example, as described in Sadri and Hornsby (1997) Nucl. Acids Res. 24: 5058–5059, or as embodied in a method known as COBRA (Combined Bisulfite Restriction Analysis) (Xiong and Laird (1997) Nucleic Acids Res. 25: 2532–2534).

[0187] COBRA TM Analysis is a quantitative methylation assay that can be used to determine the DNA methylation level at a specific locus in a small amount of genomic DNA (Xiong and Laird, Nucleic Acids Res. 25: 2532-2534, 1997). In short, restriction enzyme digestion is used to reveal the methylation-dependent sequence differences in the PCR products of sodium bisulfite-treated DNA. First, according to the procedure described by Frommer et al. (Proc. Natl. Acad. Sci. USA 89: 1827-1831, 1992), methylation-dependent sequence differences are introduced into genomic DNA by standard sulfite treatment. The sulfite-converted DNA is then PCR amplified using primers specific for the CpG island of interest, followed by restriction enzyme digestion, gel electrophoresis, and detection using specific, labeled hybridization probes. The methylation level in the original DNA sample is represented by the relative amounts of digested and undigested PCR products in a linear quantitative manner over a wide range of DNA methylation levels. In addition, this technique can be reliably applied to DNA obtained from microdissected paraffin-embedded tissue samples.

[0188] For COBRA TM Typical reagents for the assay (e.g., those found in typical COBRA-based TM The kits (found in the kits) may include, but are not limited to: PCR primers for specific loci (e.g., specific genes, markers, DMRs, gene regions, marker regions, sulfite-treated DNA sequences, CpG islands, etc.); restriction enzymes and appropriate buffers; gene hybridization oligonucleotides; control hybridization oligonucleotides; kinase labeling kits for oligonucleotide probes; and labeled nucleotides. In addition, bisulfite conversion reagents may include DNA denaturation buffers; sulfonation buffers; DNA recovery reagents or kits (e.g., precipitation, ultrafiltration, affinity columns); desulfonation buffers; and DNA recovery components.

[0189] Such as "MethyLight TM "(Real-time PCR technology based on fluorescence) (Eads et al., Cancer Res. 59: 2302-2306, 1999), Ms-SNuPE TM Assays such as the (methylation-sensitive single nucleotide primer extension) reaction (Gonzalgo and Jones, Nucleic Acids Res. 25:2529-2531, 1997), methylation-specific PCR ("MSP"; Herman et al., Proc. Natl. Acad. Sci. USA 93:9821-9826, 1996; U.S. Pat. No. 5,786,146), and methylated CpG island amplification ("MCA"; Toyota et al., Cancer Res. 59:2307-12, 1999) can be used alone or in combination with one or more of these methods.

[0190] “Heavy Methyl TM The assay technology is a quantitative method for assessing methylation differences based on methylation-specific amplification of bisulfite-treated DNA. Methylation-specific blocking probes ("blockers") that cover CpG positions between, or are covered by, amplification primers enable methylation-specific selective amplification of nucleic acid samples.

[0191] The term "Heavy Methyl TM MethyLight TM "Assay refers to a HeavyMethyl TM MethyLight TM Determination, it is MethyLight TM A variant of the assay in which MethyLight TM The assay is combined with a methylation-specific blocking probe covering the CpG position between the amplification primers. TM The assay can also be used in combination with methylation-specific amplification primers.

[0192] Uses for HeavyMethyl TM Typical reagents for the assay (e.g., those found in typical MethyLight-based TM The kit may include, but is not limited to: PCR primers for a specific locus (e.g., a specific gene, marker, gene region, marker region, sulfite-treated DNA sequence, CpG island or sulfite-treated DNA sequence or CpG island, etc.); blocking oligonucleotides; optimized PCR buffer and deoxynucleotides; and Taq polymerase.

[0193] MSP (methylation-specific PCR) can assess the methylation status of almost any group of CpG sites within a CpG island without relying on the use of methylation-sensitive restriction enzymes (Herman et al. Proc. Natl. Acad. Sci. USA 93:9821-9826, 1996; U.S. Patent No. 5,786,146). Briefly, DNA is modified with sodium bisulfite to convert unmethylated cytosine (but not methylated cytosine) to uracil, and the product is then amplified using primers that are specific for methylated DNA compared to unmethylated DNA. MSP requires only a small amount of DNA, is sensitive to 0.1% methylated alleles at a given CpG island locus, and can be performed on DNA extracted from paraffin-embedded samples. Typical reagents for MSP analysis (such as those found in typical MSP-based kits) may include, but are not limited to, methylated and unmethylated PCR primers for specific loci (e.g., specific genes, markers, gene regions, marker regions, sulfite-treated DNA sequences, CpG islands, etc.); optimized PCR buffers and deoxynucleotides, and specific probes.

[0194] MethyLight TM The assay is a high-throughput quantitative methylation assay that utilizes fluorescence-based real-time PCR (e.g. ), no further manipulation is required after the PCR step (Eads et al., Cancer Res. 59:2302-2306, 1999). In short, MethyLight TM The process begins with a mixed sample of genomic DNA, which is converted into a pool of methylation-dependent sequence differences in a sodium bisulfite reaction according to standard procedures (the bisulfite process converts unmethylated cytosine residues to uracil). This is followed by fluorescence-based PCR using a "biased" reaction, for example, using PCR primers that overlap with known CpG dinucleotides. Sequence discrimination occurs at the level of the amplification process and the fluorescence detection process.

[0195] MethyLight TM The assay is used to quantitatively test methylation patterns in nucleic acids (e.g., genomic DNA samples), where sequence discrimination occurs at the probe hybridization level. In the quantitative version, the PCR reaction provides methylation-specific amplification in the presence of a fluorescent probe that overlaps a specific putative methylation site. An unbiased control of the amount of input DNA is provided by reactions where neither the primers nor the probe cover any CpG dinucleotides. Alternatively, the amount of input DNA can be determined by using a control oligonucleotide that does not cover a known methylation site (e.g., a fluorescence-based HeavyMethyl TMQualitative testing of genomic methylation can be achieved by using oligonucleotides (e.g., PCR-MS / MSP) or by probing biased PCR pools covering potential methylation sites.

[0196] MethyLight TM The process can be used with any suitable probe (e.g. Probe, For example, in some applications, double-stranded genomic DNA is treated with sodium bisulfite and used One of two sets of PCR reactions is performed using the probe, for example, using MSP primers and / or HeavyMethyl blocking oligonucleotides and probe. The probe is dual-labeled with a fluorescent "reporter molecule" and a "quencher" molecule and is specifically designed for regions with relatively high GC content, so that its melting temperature during PCR cycles is approximately 10°C higher than that of the forward or reverse primer. The probe remains fully hybridized during the melt / extension step of PCR. As the Taq polymerase enzymatically synthesizes new strands during PCR, it eventually reaches the melted The Taq polymerase 5' to 3' endonuclease activity will then digest the The probe is replaced by a fluorescent reporter molecule to release the fluorescent reporter molecule for quantitative detection of its now unquenched signal using a real-time fluorescence detection system.

[0197] Used for MethyLight TM Typical reagents for the assay (e.g., those found in typical MethyLight-based TM The primers (found in the kit) may include, but are not limited to: PCR primers for specific loci (e.g., specific genes, markers, gene regions, marker regions, sulfite-treated DNA sequences, CpG islands, etc.); or probe; optimized PCR buffer and deoxynucleotides; and Taq polymerase.

[0198] QM TM The (Quantitative Methylation) assay is an alternative quantitative test for methylation patterns in genomic DNA samples, in which sequence discrimination occurs at the probe hybridization level. In this quantitative version, the PCR reaction provides unbiased amplification in the presence of a fluorescent probe that overlaps with a specific putative methylation site. An unbiased control of the amount of input DNA is provided by a reaction in which neither the primers nor the probe cover any CpG dinucleotides. Alternatively, the methylation site is detected by using a control oligonucleotide that does not cover a known methylation site (fluorescence-based HeavyMethyl TM Qualitative testing of genomic methylation can be achieved by using oligonucleotides (e.g., PCR-MS / MSP) or by probing biased PCR pools covering potential methylation sites.

[0199] During the amplification process, QM TM The process can be used with any suitable probe, e.g. Probe, For example, double-stranded genomic DNA is treated with sodium bisulfite and subjected to unbiased primers and Probe processing. The probe is dual-labeled with a fluorescent "reporter molecule" and a "quencher" molecule and is specifically designed for regions with relatively high GC content, so that its melting temperature during PCR cycles is approximately 10°C higher than that of the forward or reverse primer. The probe remains fully hybridized during the melt / extension step of PCR. As the Taq polymerase enzymatically synthesizes new strands during PCR, it eventually reaches the melted The Taq polymerase 5' to 3' endonuclease activity will then digest the The probe is replaced by a fluorescent reporter to release the fluorescent reporter molecule for quantitative detection of its currently unquenched signal using a real-time fluorescence detection system. TM Typical reagents for the analysis (e.g., those found in typical QM-based TM The primers (found in the kit) may include, but are not limited to: PCR primers for specific loci (e.g., specific genes, markers, gene regions, marker regions, sulfite-treated DNA sequences, CpG islands, etc.); or probe; optimized PCR buffer and deoxynucleotides; and Taq polymerase.

[0200] Ms-SNuPE TM The technique is a quantitative method for assessing methylation differences at specific CpG sites, based on sulfite treatment of DNA followed by single nucleotide primer extension (Gonzalgo and Jones, Nucleic Acids Res. 25: 2529-2531, 1997). In short, genomic DNA is reacted with sodium bisulfite to convert unmethylated cytosine into uracil while keeping 5-methylcytosine unchanged. PCR primers specific for sulfite-converted DNA are then used to amplify the desired target sequence, and the resulting product is separated and used as a template for methylation analysis at the CpG site of interest. Small amounts of DNA (e.g., microdissected pathology sections) can be analyzed, and the use of restriction enzymes to determine the methylation status of CpG sites is avoided.

[0201] For Ms-SNuPE TM Typical reagents for the analysis (e.g., those found in typical Ms-SNuPE-based TMThe kits (found in the kit) may include but are not limited to: PCR primers for specific loci (e.g., specific genes, markers, gene regions, marker regions, sulfite-treated DNA sequences, CpG islands, etc.); optimized PCR buffers and deoxynucleotides; gel extraction kits; positive control primers; Ms-SNuPE for specific loci; TM Primers; reaction buffer (for Ms-SNuPE reaction); and labeled nucleotides. In addition, bisulfite conversion reagents may include DNA denaturation buffer; sulfonation buffer; DNA recovery reagents or kits (such as precipitation, ultrafiltration, affinity column); desulfonation buffer; and DNA recovery components.

[0202] Reduced representational sulfite sequencing (RRBS) starts with sulfite treatment of the nucleic acid, converts all unmethylated cytosines into uracil, and then performs restriction enzyme digestion (e.g., by an enzyme that recognizes sites including CG sequences, such as MspI), and completes sequencing of the fragments after coupling with an adapter ligand. The choice of restriction enzymes enriches fragments in CpG-dense regions, reducing the number of redundant sequences that may be mapped to multiple gene positions during the analysis process. Therefore, RRBS reduces the complexity of the nucleic acid sample by selecting a subset of restriction fragments (e.g., by size selection using preparative gel electrophoresis) for sequencing. In contrast to whole-genome sulfite sequencing, each fragment produced by restriction enzyme digestion contains DNA methylation information for at least one CpG dinucleotide. Therefore, RRBS enriches the promoters, CpG islands, and other genomic features of the sample through high-frequency restriction enzyme sites in these regions, and therefore provides a determination for evaluating the methylation status of one or more genomic loci.

[0203] A typical protocol for RRBS includes digesting the nucleic acid sample with a restriction enzyme (such as Mspl), filling in overhangs and A-tails, ligating adapters, bisulfite conversion, and PCR. See, for example, Meissner et al. (2005) "Genome-scale DNA methylation mapping of clinical samples at single-nucleotide resolution" Nat Methods 7:133–6; Meissner et al. (2005) "Reduced representation bisulfite sequencing for comparative high-resolution DNA methylation analysis" Nucleic Acids Res. 33:5868–77.

[0204] In some embodiments, a quantitative allele-specific real-time target and signal amplification (QuARTS) assay is used to assess methylation status. In each QuARTS assay, three reactions occur sequentially, including amplification (reaction 1) and target probe cleavage (reaction 2) in the primary reaction; and FRET cleavage and fluorescence signal generation (reaction 3) in the secondary reaction. When the target nucleic acid is amplified with specific primers, a specific detection probe with a flap sequence loosely binds to the amplicon. The presence of a specific invasive oligonucleotide at the target binding site allows a 5' nuclease (e.g., FEN-1 endonuclease) to release the flap sequence by cutting between the detection probe and the flap sequence. The flap sequence is complementary to the non-hairpin portion of the corresponding FRET box. Therefore, the flap sequence acts as an invasive oligonucleotide on the FRET box and cleaves the FRET box fluorophore and quencher, thereby generating a fluorescent signal. The cleavage reaction can cut multiple probes for each target, and therefore each flap releases multiple fluorophores, providing exponential signal amplification. QuARTS can detect multiple targets in a single reaction well by using FRET boxes with different dyes. See, e.g., Zou et al. (2010) “Sensitive quantification of methylated markers with a novel methylation specific technology” Clin Chem 56:A199) and U.S. Patent Nos. 8,361,720, 8,715,937, 8,916,344, and 9,212,392, each of which is incorporated herein by reference for all purposes.

[0205] The term "bisulfite reagent" refers to a reagent comprising bisulfite, disulfite, hydrogen sulfite, or a combination thereof, as disclosed herein, which can be used to distinguish methylated from unmethylated CpG dinucleotide sequences. The methods of treatment are known in the art (e.g., PCT / EP2004 / 011715 and WO2013 / 116375, each of which is incorporated by reference in its entirety). In some embodiments, the sulfite treatment is carried out in the presence of a denaturing solvent (e.g., but not limited to, n-alkyl glycol or diethylene glycol dimethyl ether (DME)), or in the presence of dioxane or a dioxane derivative. In some embodiments, the denaturing solvent is used at a concentration between 1% and 35% (v / v). In some embodiments, the bisulfite reaction is carried out in the presence of a scavenger, such as, but not limited to, a chroman derivative, for example, 6-hydroxy-2,5,7,8,-tetramethylchroman 2-carboxylic acid or trihydroxybenzoic acid and its derivatives, for example, gallic acid (see: PCT / EP2004 / 011715, which is incorporated by reference in its entirety). In certain preferred embodiments, the bisulfite reaction comprises treatment with ammonium bisulfite, for example, as described in WO2013 / 116375.

[0206] In some embodiments, according to the methods and compositions described herein, primer oligonucleotide sets and amplification enzymes are used to amplify the fragments of the DNA processed. The amplification of several DNA segments can be carried out simultaneously in the same reaction vessel. Typically, polymerase chain reaction (PCR) is used to amplify. The length of the amplicon is typically 100 to 2000 base pairs.

[0207] In some embodiments of the method, the methylation status or profile of CpG positions within or near differentially methylated regions (e.g., Tables 1 and 2) can be detected by using methylation-specific primer oligonucleotides. This technology (MSP) has been described in U.S. Pat. No. 6,265,171 to Herman. Amplification of sulfite-treated DNA using methylation-specific primers can distinguish between methylated and unmethylated nucleic acids. An MSP primer pair contains at least one primer that hybridizes to a sulfite-treated CpG dinucleotide. Thus, the sequence of the primer contains at least one CpG dinucleotide. An MSP primer that is specific for unmethylated DNA contains a "T" at the C position of the CpG.

[0208] Such methods are not limited to specific types or classes of primers or primer pairs associated with one or more methylation markers, methylation marker genes, genes, DMRs, and / or methylated DNA markers. In some embodiments, a primer or primer pair specific for each methylation marker gene is capable of binding to an amplicon bound by a primer sequence for a marker gene listed in Table 1 or Table 2, wherein the amplicon bound by the primer sequence for the marker gene is at least a portion of a gene region for a methylation marker gene listed in Table 1 or Table 2.

[0209] In another embodiment, the present disclosure provides a method for converting oxidized 5-methylcytosine residues in cell-free DNA into dihydrouracil residues (see Liu et al., 2019, Nat Biotechnol. 37, pp. 424-429; U.S. Patent Application Publication No. 202000370114). The method involves reacting an oxidized 5mC residue selected from 5-formylcytosine (5fC), 5-carboxymethylcytosine (5caC), and a combination thereof with a borane reducing agent. The oxidized 5mC residue can be naturally occurring, or more typically is the result of prior oxidation of the 5mC or 5hmC residue, for example, oxidation of 5mC or 5hmC by a TET family enzyme (e.g., TET1, TET2, or TET3), or chemical oxidation of 5mC or 5hmC, for example, by potassium perruthenate (KRuO4) or inorganic peroxide compounds or compositions such as peroxytungstate (see, e.g., Okamoto et al. (2011) Chem. Commun. 47: 11231-33) and copper (II) perchlorate / 2,2,6,6-tetramethylpiperidin-1-oxyl (TEMPO) combination (see, Matsushita et al. (2017) Chem. Commun. 53: 5756-59).

[0210] Borane reducing agents may be characterized by a complex of borane with a nitrogen-containing compound selected from nitrogen heterocycles and tertiary amines. The nitrogen heterocycle may be monocyclic, bicyclic or polycyclic, but is typically monocyclic in the form of a 5-membered or 6-membered ring containing a nitrogen heteroatom and optionally one or more additional heteroatoms selected from N, O and S. The nitrogen heterocycle may be aromatic or alicyclic. Preferred nitrogen heterocycles herein include 2-pyrroline, 2H-pyrrole, 1H-pyrrole, pyrazolidine, imidazolidine, 2-pyrazoline, 2-imidazoline, pyrazole, imidazole, 1,2,4-triazole, 1,2,4-triazole, pyridazine, pyrimidine, pyrazine, 1,2,4-triazine and 1,3,5-triazine, any of which may be unsubstituted or substituted with one or more non-hydrogen substituents. Typical non-hydrogen substituents are alkyl groups, particularly lower alkyl groups, such as methyl, ethyl, n-propyl, isopropyl, n-butyl, isobutyl, tert-butyl, etc. Exemplary compounds include, but are not limited to, borane, pyridine borane, 2-methylpyridine borane (also known as 2-methylpyridine borane or pic-BH3), 5-ethyl-2-pyridine, sodium borohydride, sodium cyanoborohydride, sodium triacetoxyborohydride, diborane, decaborane, borane tetrahydrofuran, borane-dimethyl sulfide, borane-N,N-diisopropylethylamine, borane-2-chloropyridine, borane-aniline, N,N-dimethylamine borane, tert-butylamine borane sodium triacetoxyborohydride, borohydride, hydrazine or dibutylamine borane, morpholine borane, borane-ammonia complex (BH3NH3), dicyclohexylamine borane, morpholine borane, 4-methylmorpholine borane, base and tetramethylamine borane (e.g., NaBH4), and other complexes and / or derivatives containing -BH3. In some embodiments, the reducing agent is pyridine borane and / or pic-BH3.

[0211] The reaction of oxidized 5mC residues in cell-free DNA with borane reducing agents is advantageous because nontoxic reagents and mild reaction conditions can be employed; no bisulfate is required, nor are any other potentially DNA-degrading agents. Furthermore, the conversion of oxidized 5mC residues to dihydrouracil using borane reducing agents can be performed in a "one-pot" or "one-tube" reaction without the need to isolate any intermediates. This is significant because the conversion involves multiple steps, namely (1) reduction of the olefin bond connecting C-4 and C-5 in oxidized 5mC, (2) deamination, and (3) decarboxylation if the oxidized 5mC is 5caC, or deformylation if the oxidized 5mC is 5fC.

[0212] In addition to providing a method for converting oxidized 5-methylcytosine residues in cell-free DNA into dihydrouracil residues, the present disclosure also provides a reaction mixture related to the aforementioned method. The reaction mixture comprises a cell-free DNA sample containing at least one oxidized 5-methylcytosine residue selected from 5caC, 5fC, and a combination thereof, and a borane reducing agent that can effectively reduce, deaminize, decarboxylate, or deformylate the at least one oxidized 5-methylcytosine residue. The borane reducing agent is a complex of borane and a nitrogen-containing compound selected from nitrogen heterocycles and tertiary amines, as described above. In a preferred embodiment, the reaction mixture is substantially free of bisulfite, meaning substantially free of bisulfite ions and bisulfite. Ideally, the reaction mixture is free of bisulfite.

[0213] In a related aspect of the present disclosure, a kit for converting 5mC residues in cell-free DNA to dihydrouracil residues is provided, wherein the kit includes a reagent for blocking 5hmC residues, a reagent for oxidizing 5mC residues beyond hydroxymethylation to provide oxidized 5mC residues, and a borane reducing agent effective for reducing, deaminating, and decarboxylating or deformylating the oxidized 5mC residues. The kit may also include instructions for using the components to perform the above method.

[0214] In another embodiment, a method utilizing the above-described oxidation reaction is provided. The method is capable of detecting the presence and location of 5-methylcytosine residues in cell-free DNA and comprises the following steps: (a) modifying 5hmC residues in fragmented, adaptor-ligated cell-free DNA to provide an affinity tag thereon, wherein the affinity tag is capable of removing DNA containing modified 5hmC from the cell-free DNA; (b) removing DNA containing modified 5hmC from the cell-free DNA, leaving DNA containing unmodified 5mC residues; (c) oxidizing the unmodified 5mC residues to provide DNA containing oxidized 5mC residues selected from 5caC, 5fC, and combinations thereof; (d) contacting the DNA containing the oxidized 5mC residues with a borane reducing agent that is effective to reduce, deaminize, decarboxylate, or deformylate the oxidized 5mC residues, thereby providing DNA containing dihydrouracil residues in place of the oxidized 5mC residues; (e) amplifying and sequencing the DNA containing the dihydrouracil residues; and (f) determining the 5-methylation pattern based on the sequencing results in (e).

[0215] In some embodiments, the present disclosure provides a method for identifying 5-methylcytosine (5mC) or 5-hydroxymethylcytosine (5hmC) in a target nucleic acid. In some embodiments, the method includes providing a biological sample comprising a target nucleic acid, modifying the target nucleic acid by converting 5mC and 5hmC in the nucleic acid sample into 5-carboxylcytosine (5caC) and / or 5-formylcytosine (5fC) by contacting the nucleic acid sample with a TET enzyme, thereby generating one or more 5caC or 5fC residues, and converting 5caC and / or 5fC into dihydrouracil (DHU) by treating the target nucleic acid with a borane reducing agent to provide a modified nucleic acid sample comprising a modified target nucleic acid, and detecting the sequence of the modified target nucleic acid; wherein the conversion of cytosine (C) to thymine (T) or the conversion of cytosine (C) to DHU in the modified target nucleic acid sequence compared to the target nucleic acid provides the position of 5mC or 5hmC in the target nucleic acid. In some embodiments, the borane reducing agent is 2-methylpyridine borane.

[0216] In some embodiments, detecting the sequence of the modified target nucleic acid includes one or more of chain termination sequencing, microarray, high-throughput sequencing, and restriction enzyme analysis. In some embodiments, the TET enzyme is selected from the group consisting of: human TET1, TET2, and TET3; mouse Tet1, Tet2, and Tet3; Naegleria TET (NgTET); and Coprinopsis cinerea (CcTET). In some embodiments, the method further comprises a step of blocking one or more modified cytosines. In some embodiments, the blocking step comprises adding a sugar to 5hmC. In some embodiments, the method further comprises a step of amplifying the number of copies of one or more nucleic acid sequences. In some embodiments, the oxidant is potassium perruthenate or Cu(II) / TEMPO (2,2,6,6-tetramethylpiperidine-1-oxyl).

[0217] Cell-free DNA is typically extracted from a biological sample of a subject, wherein the sample can be whole blood, plasma, urine, saliva, mucosal secretions, organ secretions, sputum, feces or tears. In some embodiments, cell-free DNA is derived from a tumor (e.g., a gynecological tumor). In other embodiments, cell-free DNA is from a patient suffering from a disease or other pathogenic condition. Cell-free DNA may or may not be derived from a tumor. In some embodiments, the cell-free DNA to be modified with 5hmC residues is in a purified, fragmented form and is adapter-connected. DNA purification in this context can be performed using any suitable method known to those of ordinary skill in the art and / or described in the relevant literature, and although cell-free DNA itself can be highly fragmented, further fragmentation may sometimes be required, such as described in U.S. Patent Publication No. 2017 / 0253924. The size of the cell-free DNA fragments is generally in the range of about 20 nucleotides to about 500 nucleotides, more typically in the range of about 20 nucleotides to about 250 nucleotides. The purified cell-free DNA fragments modified in step (a) have been end-repaired using conventional methods (e.g., restriction enzymes) so that the fragments have blunt ends at each 3' and 5' end. In a preferred method, as described in WO 2017 / 176630, a polymerase (such as Taq polymerase) is also used to provide the blunted fragments with 3' overhangs containing a single adenine residue. This facilitates the subsequent connection of selected universal adapters, i.e., adapters that are connected to both ends of the cell-free DNA fragments and contain at least one molecular barcode, such as Y-type adapters or hairpin adapters. The use of adapters can also achieve selective PCR enrichment of adapter-connected DNA fragments.

[0218] In some embodiments, "purified, fragmented cell-free DNA" includes adaptor-ligated DNA fragments. 5hmC residues in these cell-free DNA fragments are modified with an affinity tag so that the DNA containing modified 5hmC can be subsequently removed from the cell-free DNA. In one embodiment, the affinity tag comprises a biotin moiety, such as biotin, desthiobiotin, oxybiotin, 2-iminobiotin, diaminobiotin, biotin sulfoxide, biocytin, etc. The use of a biotin moiety as an affinity tag allows for easy removal using streptavidin (e.g., streptavidin beads, magnetic streptavidin beads, etc.).

[0219] Labeling 5hmC residues with a biotin moiety or other affinity tag is accomplished by covalently attaching a chemoselective group to the 5hmC residues in the DNA fragment, wherein the chemoselective group is capable of reacting with the functionalized affinity tag, thereby attaching the affinity tag to the 5hmC residue. In one embodiment, the chemoselective group is UDP glucose-6-azide, which undergoes a spontaneous 1,3-cycloaddition reaction with an alkyne-functionalized biotin moiety, as described in Robertson et al. (2011) Biochem. Biophys. Res. Comm. 411(1):40-3, U.S. Patent No. 8,741,567, and WO 2017 / 176630. Thus, the addition of the alkyne-functionalized biotin moiety results in the covalent attachment of the biotin moiety to each 5hmC residue.

[0220] In one embodiment, the affinity-tagged DNA fragments can then be pulled down using streptavidin in the form of streptavidin beads, magnetic streptavidin beads, etc., and, if desired, retained for later analysis. The supernatant remaining after removal of the affinity-tagged fragments contains DNA with unmodified 5mC residues and no 5hmC residues.

[0221] In some embodiments, the unmodified 5mC residue is oxidized using any suitable method to provide a 5caC residue and / or a 5fC residue. An oxidizing agent is selected to oxidize the 5mC residue beyond hydroxymethylation, i.e., to provide a 5caC and / or 5fC residue. Oxidation can be performed enzymatically using a catalytically active TET family enzyme. The term "TET family enzyme" or "TET enzyme" as used herein refers to the catalytically active "TET family protein" or "TET catalytically active fragment" defined in U.S. Patent No. 9,115,386, the disclosure of which is incorporated herein by reference. In this case, the preferred TET enzyme is TET2; see Ito et al. (2011) Science 333(6047):1300-1303. Oxidation can also be performed chemically using a chemical oxidant, as described in the previous section. Examples of suitable oxidizing agents include, but are not limited to, perruthenate anions in the form of inorganic or organic perruthenates, including metal perruthenates such as potassium perruthenate (KRuO4), tetraalkylammonium perruthenates such as tetrapropylammonium perruthenate (TPAP) and tetrabutylammonium perruthenate (TBAP), and polymer-supported perruthenates (PSP); and inorganic peroxy compounds and compositions such as peroxytungstate or copper (II) perchlorate / TEMPO combinations. There is no need to separate the 5fC-containing fragment from the 5caC-containing fragment at this point, as both the 5fC residue and the 5caC residue are converted to dihydrouracil (DHU) in the next step of the process.

[0222] In some embodiments, 5-hydroxymethylcytosine residues are blocked with β-glucosyltransferase (β3GT), while 5-methylcytosine residues are oxidized with a TET enzyme that effectively provides a mixture of 5-formylcytosine and 5-carboxymethylcytosine. The mixture containing these two oxidizing species can be reacted with 2-pyridine borane or another borane reducing agent to obtain dihydrouracil. In a variant of this embodiment, fragments containing 5hmC are not removed. Instead, "TET-assisted methylpyridine borane sequencing (TAPS)" enzymatically oxidizes fragments containing 5mC and fragments containing 5hmC together to provide fragments containing 5fC and 5caC. The reaction with 2-methylpyridine borane produces DHU residues where the 5mC and 5hmC residues were originally present. "Chemically assisted methylpyridine borane sequencing (CAPS)" involves selectively oxidizing fragments containing 5hmC with potassium perruthenate, leaving the 5mC residues unchanged.

[0223] As disclosed in International PCT Application PCT / US2019 / 012627, which is incorporated herein by reference in its entirety, TAPS includes the use of mild enzymatic and chemical reactions to directly and quantitatively detect 5mC and 5hmC at base resolution without affecting unmodified cytosine. In a related embodiment, the above method also includes identifying the hydroxymethylation pattern in DNA containing 5hmC removed from cell-free DNA. This can be performed using the technology described in detail in WO 2017 / 176630. The process can be performed in a single tube method without removing or separating intermediates. For example, first, cell-free DNA fragments (preferably adapter-connected DNA fragments) are functionalized with βGT-catalyzed uridine diphosphate glucose 6-azide and then biotinylated by chemically selective azide groups. This procedure produces covalently linked biotin at each 5hmC site. In the next step, the biotinylated chain and the chain containing unmodified (natural) 5mC are pulled down simultaneously for further processing. As is known in the art, the native 5mC-containing chain is pulled down using an anti-5mC antibody or a methyl-CpG binding domain (MBD) protein. Then, in the presence of blocking 5hmC residues, unmodified 5mC residues are selectively oxidized using any suitable technique to convert 5mC to 5fC and / or 5caC, as described elsewhere herein.

[0224] The fragment obtained by amplification can be with direct or indirect detectable label.In some embodiments, label is fluorescent label, radionuclide or has the separable molecular fragment of the typical mass that can be detected in mass spectrometer.When described label is mass label, the amplicon of some embodiments regulation mark has single positive or negative net charge, thereby allows to have better detectability in mass spectrometer.Can detect and visualize by for example matrix-assisted laser desorption / ionization mass spectrometry (MALDI) or use electrospray mass spectrometry (ESI).

[0225] Methods for isolating DNA suitable for these assay techniques are known in the art. Specifically, some embodiments include nucleic acid isolation as described in U.S. patent application Ser. No. 13 / 470,251 ("nucleic acid isolation"), which is incorporated herein by reference in its entirety.

[0226] In some embodiments, mark as described herein can be used for the QUARTS determination that stool sample is carried out.In some embodiments, provide for the method for producing DNA sample, particularly for the method for producing the DNA sample of the highly purified low abundance nucleic acid comprising small volume (for example less than 100 microlitres, less than 60 microlitres) and substantially and / or effectively do not contain the material of the mensuration (for example PCR, INVADER, QuARTS determination etc.) that suppresses for testing DNA sample.Such DNA sample can be used for diagnostic determination, and its qualitative detection is taken from the gene, gene variant (for example allele) or genetic modification (for example methylation) present in the sample of patient, or quantitatively measures its activity, expression or amount.For example, some cancers are relevant to the existence of specific mutant allele or specific methylation state, and therefore detection and / or quantification of such mutant allele or methylation state has predictive value in the diagnosis and treatment of cancer.

[0227] Many valuable genetic markers are present at very low levels in samples, and many events that produce such markers are rare. Therefore, even sensitive detection methods such as PCR require large amounts of DNA to provide enough low-abundance targets to meet or replace the detection threshold of the assay. In addition, even the presence of small amounts of inhibitory substances can compromise the accuracy and precision of these assays for detecting such low-amount targets. Therefore, this article provides methods for providing the necessary management of volume and concentration to produce such DNA samples.

[0228] In some embodiments, the sample includes feces, tissue samples, organ secretions, CSF, saliva, blood or urine. In some embodiments, the subject is a human. Such samples can be obtained by various methods known in the art, such as methods apparent to those skilled in the art. Cell-free or substantially cell-free samples can be obtained by subjecting the sample to various techniques known to those skilled in the art, including but not limited to centrifugation and filtration. Although it is generally preferred not to use invasive techniques to obtain samples, it may still be preferred to obtain samples such as tissue homogenates, tissue sections and biopsy specimens. The technology is not limited by the method for preparing samples and providing nucleic acids for testing. For example, in some embodiments, direct gene capture is used, for example, as described in detail in U.S. Patent numbers 8,808,990 and 9,169,511, and WO 2012 / 155072, or DNA is isolated from a sample (for example, fecal sample, tissue sample, organ secretion sample, CSF sample, saliva sample, blood sample, plasma sample or urine sample) by a related method.

[0229] The analysis of mark can be carried out separately, or be carried out simultaneously with the extra mark in a test sample.For example, several marks can be combined into a kind of test, to effectively process multiple samples, and may provide higher diagnosis and / or prognosis accuracy.In addition, those skilled in the art will recognize the value of testing multiple samples (for example, at continuous time points) from the same experimenter.Serial samples are carried out this type of test and can identify the change of mark methylation state over time.The change of methylation state and the no change of methylation state can provide useful information about disease state, include but not limited to the approximate time that identification event begins, the existence and quantity of salvageable tissue, the suitability of drug therapy, the effectiveness of various therapies, and the result of identification experimenter, including the risk of future events.

[0230] Analysis of biomarkers can be performed in a variety of physical formats. For example, the use of microtiter plates or automation can be used to facilitate the processing of large numbers of test samples. Alternatively, a single sample format can be developed to facilitate immediate treatment and diagnosis in a timely manner, such as in ambulatory transport or emergency room settings.

[0231] Genomic DNA can be separated by any means, including the use of commercially available test kits. In short, when the DNA of interest is wrapped by the cell membrane, the biological sample must be destroyed and dissolved by enzymatic, chemical or mechanical means. Proteins and other contaminants can then be removed from the DNA solution, for example, by digestion with Proteinase K. The genomic DNA is then recovered from the solution. This can be achieved by a variety of methods, including salting out, organic extraction or combining the DNA with a solid support. The selection of the method will be affected by several factors, including time, cost and the required amount of DNA. All clinical sample types containing neoplastic material or pre-neoplastic material are suitable for the method of the present invention, such as cell lines, tissue sections, biopsies, paraffin-embedded tissues, body fluids, feces, tissues, colon effluent, urine, plasma, serum, whole blood, separated blood cells, cells separated from blood, and combinations thereof.

[0232] The technology is not limited by the method used to prepare the sample and provide the nucleic acid for testing. For example, in some embodiments, DNA is isolated from a stool sample or from a blood sample or from a plasma sample using direct gene capture, e.g., as described in detail in U.S. patent application Ser. No. 61 / 485,386, or by related methods.

[0233] The genomic DNA sample is then treated with at least one reagent or series of reagents that distinguish between methylated and unmethylated CpG dinucleotides within at least one marker comprising a DMR (eg, a DMR in Table 1 or Table 2).

[0234] In some embodiments, the reagent converts an unmethylated cytosine base at the 5'-position to uracil, thymine, or another base that differs from cytosine in hybridization behavior. However, in some embodiments, the reagent may be a methylation-sensitive restriction enzyme.

[0235] In some embodiments, the genomic DNA sample is treated in a manner such that unmethylated cytosine bases at the 5'-position are converted to uracil, thymine, or another base that differs from cytosine in hybridization behavior. In some embodiments, this treatment is performed with bisulfite (hydrogensulfite, disulfite) followed by alkaline hydrolysis.

[0236] The treated nucleic acid is then analyzed to determine the methylation status of the target gene sequence (at least one gene, genomic sequence, or nucleotide from a marker comprising a DMR (e.g., at least one DMR selected from the DMRs in Table 1 or Table 2). The analysis method can be selected from those known in the art, including those listed herein (e.g., QuARTS and MSP as described herein).

[0237] Such samples can be obtained by various methods known in the art, such as methods that will be apparent to those skilled in the art. For example, urine and fecal samples are readily available, while blood, ascites, serum, or pancreatic juice samples can be obtained parenterally using, for example, a needle and syringe. Cell-free or substantially cell-free samples can be obtained by subjecting the sample to various techniques known to those skilled in the art, including, but not limited to, centrifugation and filtration. Although it is generally preferred not to use invasive techniques to obtain samples, it may still be preferred to obtain samples such as tissue homogenates, tissue sections, and biopsy specimens.

[0238] Embodiments of the present disclosure also provide compositions. In some embodiments, the present disclosure provides compositions comprising a nucleic acid comprising a DMR and a bisulfite reagent. In some embodiments, compositions are provided, comprising a nucleic acid comprising a DMR and one or more primers (e.g., a primer capable of binding to at least a portion of the DMR region listed in Table 1 or Table 2, or a primer capable of binding to an amplicon bound by a primer capable of binding to at least a portion of the DMR region listed in Table 1 or Table 2). In certain embodiments, compositions are provided, comprising a nucleic acid comprising a DMR and a methylation-sensitive restriction enzyme. In certain embodiments, compositions comprising a nucleic acid comprising a DMR and a polymerase are provided.

[0239] 3. Treatment Methods

[0240] In some embodiments, the present disclosure provides a method for treating a subject (e.g., a patient suffering from or suspected of suffering from one or more types or subclasses of gynecological cancer). According to these embodiments, the method includes determining the methylation state or overview of one or more methylated DNA markers provided herein, and / or measuring the expression and / or activity level of one or more protein markers, and administering treatment to the patient based on the result of determining the methylation state and / or protein marker expression and / or activity level. Treatment can be the administration of a pharmaceutical compound, a vaccine, surgery, imaging the patient, or performing another test. In some embodiments, treatment of a subject includes a method for clinical screening, a method for prognostic assessment, a method for monitoring therapy results, a method for identifying the patient most likely to respond to a specific therapeutic treatment, a method for imaging the patient or subject, and a method for drug screening and development.

[0241] In some embodiments, a method for diagnosing a particular type of cancer in a subject is provided. As used herein, the terms "diagnosing" and "diagnosis" refer to methods by which one skilled in the art can estimate and even determine whether a subject is suffering from a given disease or illness or is likely to develop a given disease or illness in the future. One skilled in the art typically diagnoses based on one or more diagnostic indices, such as, for example, one or more biomarkers (e.g., one or more methylation markers, methylation marker genes, genes, DMRs, and / or DNA methylation markers as disclosed herein), the methylation state of which indicates the presence, severity, or absence of an illness and / or the expression and / or activity level of one or more protein markers.

[0242] Along with diagnosis, clinical cancer prognosis involves determining the aggressiveness of cancer and the likelihood of tumor recurrence in order to plan the most effective therapy. If a more accurate prognosis can be made, or even the potential risk of developing cancer can be assessed, appropriate therapy can be selected for the patient, and in some cases less severe therapy can be selected. Assessment of cancer markers (e.g., determining methylation status) can be used to distinguish subjects with a good prognosis and / or a low risk of developing cancer who will not require treatment or will require limited treatment from those subjects who are more likely to develop cancer or suffer a recurrence of cancer who may benefit from more intensive treatment.

[0243] Thus, as used herein, "making a diagnosis" or "diagnosis" also includes determining the risk of developing a cancer or determining a prognosis based on measurements of the diagnostic markers (e.g., DMRs) disclosed herein, which can provide a prediction of clinical outcome (with or without medical treatment), selection of an appropriate treatment (or whether a treatment is effective), or monitoring a current treatment and potentially changing treatment. In addition, in some embodiments of the presently disclosed subject matter, multiple measurements of biomarkers can be made over time to facilitate diagnosis and / or prognosis. Temporal changes in biomarkers can be used to predict clinical outcome, monitor the progression of a cancer or a subtype of cancer, and / or monitor the efficacy of appropriate therapies for the cancer. For example, in such embodiments, it may be desirable to observe changes in the methylation state and / or expression and / or activity levels of one or more biomarkers (e.g., DMRs) disclosed herein (and potentially one or more additional biomarkers, if monitored) in a biological sample during the course of effective therapy.

[0244] In some embodiments, the presently disclosed subject matter also provides a method for determining whether to initiate or continue cancer prevention or treatment in a subject. In some embodiments, the method comprises providing a series of biological samples from a subject over a period of time; analyzing the series of biological samples to determine the methylation status or profile of at least one marker disclosed herein in each biological sample; and comparing any measurable changes in the methylation status of one or more biomarkers in each biological sample. Any changes over a period of time can be used to predict the risk of developing cancer, predict clinical outcome, determine whether to initiate or continue cancer prevention or treatment, and whether current therapies are effectively treating cancer. For example, a first time point can be selected before the start of treatment, and a second time point can be selected at some time after the start of treatment. Methylation status and protein marker expression / activity levels can be measured in each sample taken at different time points, and qualitative and / or quantitative differences can be noted. Changes in the methylation status and / or protein marker expression / activity levels of biomarker levels from different samples can be correlated with a particular cancer risk, prognosis, determining treatment efficacy, and / or cancer progression in the subject. In some embodiments, the methods and compositions of the present disclosure are used to treat or diagnose a disease at an early stage, such as before symptoms of the disease appear. In some embodiments, the methods and compositions of the present disclosure are used to treat or diagnose a disease at the clinical stage.

[0245] In some embodiments, multiple measurements of one or more diagnostic or prognostic biomarkers may be performed, and changes in the markers over time may be used to determine a diagnosis or prognosis. For example, a diagnostic marker may be determined at an initial time and again at a second time. In such embodiments, an increase in the marker from the initial time to the second time may be diagnostic of a particular type or severity of cancer, or a given prognosis. Similarly, a decrease in the marker from the initial time to the second time may be indicative of a particular type or severity of cancer, or a given prognosis. Furthermore, the degree of change in one or more markers may correlate with the severity of the cancer and future adverse events. Those skilled in the art will appreciate that while in certain embodiments, comparative measurements of the same biomarker may be performed at multiple time points, it is also possible to measure a given biomarker at one time point and a second biomarker at a second time point, and to compare these markers to provide diagnostic information.

[0246] As used herein, the phrase "determining a prognosis" refers to a method by which one skilled in the art can predict the course or outcome of a condition in a subject. The term "prognosis" does not mean that the course or outcome of a condition can be predicted with 100% accuracy, or even that the methylation status of a biomarker (e.g., a DMR) can predict whether a given course or outcome is more or less likely to occur. Instead, one skilled in the art will understand that the term "prognosis" refers to an increased likelihood that a certain process or outcome will occur; that is, the process or outcome is more likely to occur in a subject who exhibits the condition when compared to those individuals who do not exhibit the given condition. For example, in an individual who does not exhibit the condition (e.g., has a normal methylation status of one or more DMRs and / or protein marker expression and / or activity levels), the chance of a given outcome (e.g., developing a particular type of cancer) may be very low.

[0247] In some embodiments, statistical analysis associates prognostic indicators with a tendency toward adverse outcomes. For example, in some embodiments, the difference between the methylation state and / or protein marker expression and / or activity level and the methylation state and / or protein marker expression and / or activity level in the normal control sample obtained from a patient who does not suffer from cancer can indicate that the subject is more likely to suffer from cancer than the subject whose level is more similar to the methylation state in the control sample, as determined by statistical significance level. In addition, the change in methylation state and / or protein marker expression / activity level relative to baseline (for example, "normal") level can reflect the prognosis of the subject, and the degree of change in methylation state and / or protein marker expression / activity level can be related to the severity of the adverse event. Statistical significance is generally determined by comparing two or more colonies and determining confidence intervals and / or p values. See, for example, Dowdy and Wearden, Statistics for Research, John Wiley & Sons, New York, 1983, which is incorporated herein by reference in its entirety. Exemplary confidence intervals for the present subject matter are 90%, 95%, 97.5%, 98%, 99%, 99.5%, 99.9%, and 99.99%, while exemplary p-values ​​are 0.1, 0.05, 0.025, 0.02, 0.01, 0.005, 0.001, and 0.0001.

[0248] In other embodiments, a threshold degree of change in the methylation state and / or protein marker expression / activity level of a prognostic or diagnostic biomarker (e.g., a DMR; a protein marker) disclosed herein can be established, and the degree of change in the methylation state and / or protein marker expression / activity level of the biomarker in a biological sample can be simply compared to the threshold degree of change in the methylation state and / or protein marker expression / activity level. Preferred threshold changes in the methylation state and / or protein marker expression / activity level of the biomarkers provided herein are about 5%, about 10%, about 15%, about 20%, about 25%, about 30%, about 50%, about 75%, about 100%, and about 150%. In other embodiments, a "nomogram" can be created by which the methylation state and / or protein marker expression / activity level of a prognostic or diagnostic indicator (biomarker or combination of biomarkers) is directly correlated with a tendency toward a given outcome. Those skilled in the art are familiar with the use of such nomograms to correlate two values ​​and understand that the uncertainty in this measurement is the same as the uncertainty in the marker concentration, since reference is made to a single sample measurement, not a population average.

[0249] In some embodiments, a control sample is analyzed simultaneously with the biological sample so that the results obtained from the biological sample can be compared with the results obtained from the control sample. In addition, it is contemplated that a standard curve can be provided, which can be compared with the results of the measurement of the biological sample. If a fluorescent label is used, such a standard curve is presented as the relationship between the methylation state of the biomarker and / or the expression / activity level of the protein marker and the measurement unit (e.g., the intensity of the fluorescent signal). Using samples taken from multiple donors, a standard curve of the control methylation state of one or more biomarkers in normal tissue and a standard curve of the "risk" level of one or more biomarkers in the plasma of donors with a specific type of cancer can be provided. In certain embodiments of the method, after identifying the abnormal methylation state and / or protein marker expression / activity level of one or more DMRs provided herein in a biological sample obtained from the subject, the subject is identified as having cancer. In other embodiments of the method, the detection of abnormal methylation state and / or protein marker expression / activity level of one or more such biomarkers in a biological sample obtained from the subject results in the subject being identified as having cancer.

[0250] The analysis of mark can be carried out separately, or carry out simultaneously with the extra mark in a test sample.For example, several marks can be combined into a kind of test, to effectively process multiple samples, and may provide higher diagnosis and / or prognosis accuracy.In addition, those skilled in the art will recognize the value of testing multiple samples (for example, at continuous time points) from the same experimenter.Serial samples are carried out this test and can allow identification mark methylation state and / or protein marker expression / activity level to change over time.The change of methylation state and / or protein marker expression / activity level and methylation state do not change can provide useful information about disease state, include but not limited to the approximate time that identification event starts, the existence and quantity of salvageable tissue, the suitability of drug therapy, the effectiveness of various therapies, and the result of identification experimenter, including the risk of future events.

[0251] Analysis of biomarkers can be performed in a variety of physical formats. For example, the use of microtiter plates or automation can be used to facilitate the processing of large numbers of test samples. Alternatively, a single sample format can be developed to facilitate prompt treatment and diagnosis, such as in ambulatory transport or emergency room settings.

[0252] In some embodiments, if there is a measurable difference in the methylation state and / or protein marker expression / activity level of at least one biomarker in the sample when compared to a control methylation state and / or protein marker expression / activity level, the subject is diagnosed as having a particular type of cancer. Conversely, when no change in methylation state and / or protein marker expression / activity level is identified in the biological sample, the subject can be identified as not having a particular type of cancer, not at risk of having cancer, or having a low risk of having cancer. In this regard, subjects with cancer or its risk can be distinguished from subjects with low to substantially no cancer or its risk. Those subjects at risk of having a particular type of cancer can be placed on a more intensive and / or regular screening program. In another aspect, those subjects with low to substantially no risk can avoid undergoing additional cancer risk testing (e.g., invasive procedures) until, such as future screening, for example, screening performed according to various embodiments of the present disclosure indicates the emergence of cancer risk in those subjects.

[0253] As described above, according to embodiments of the methods disclosed herein, detecting a change in the methylation state of one or more biomarkers and / or protein marker expression / activity level can be a qualitative measurement, or it can be a quantitative measurement. Thus, diagnosing a subject as having or being at risk for a particular type of cancer indicates that certain threshold measurements have been made, e.g., the methylation state of one or more biomarkers and / or protein marker expression / activity level in a biological sample is different from a predetermined control methylation state and / or control protein marker expression / activity level. In some embodiments of the methods, the control methylation state is any detectable methylation state of a biomarker. In some embodiments, the control protein marker expression / activity level is any measurable protein marker and / or protein marker expression / activity level. In other embodiments of the methods in which a control sample is tested simultaneously with a biological sample, the predetermined methylation state is the methylation state in the control sample, and the predetermined protein marker expression / activity level control state is the protein marker expression / activity level in the control sample. In other embodiments of the methods, the predetermined methylation state and / or predetermined protein marker expression / activity level is based on and / or identified by a standard curve. In other embodiments of the methods, the predetermined methylation state and / or predetermined protein marker expression / activity level is a specific state or range of states. Thus, the predetermined methylation state and / or predetermined protein marker expression / activity level can be selected within acceptable limits that will be apparent to one skilled in the art based, in part, on the embodiment of the method being practiced and the desired specificity, among other factors.

[0254] Further with respect to the diagnostic methods, the preferred subject is a vertebrate subject. The preferred vertebrate is warm-blooded; the preferred warm-blooded vertebrate is a mammal. The preferred mammal is most preferably a human. As used herein, the term "subject" includes both human and animal subjects. Thus, veterinary therapeutic uses are provided herein. Thus, embodiments of the present disclosure provide for the diagnosis of mammals, such as humans, as well as those mammals that are important due to endangerment, such as Siberian tigers; mammals of economic importance, such as animals raised on farms for human consumption; and / or animals of social importance to humans, such as animals kept as pets or in zoos. Examples of such animals include, but are not limited to: carnivorous plants, such as cats and dogs; swine, including pigs, hogs, and wild boars; ruminants and / or ungulates, such as cattle, bulls, sheep, giraffes, deer, goats, bison, and camels; and horses. Thus, diagnosis and treatment of livestock are also provided, including, but not limited to, domestic pigs, ruminants, ungulates, horses (including racehorses), and the like.

[0255] 4. Samples, Kits, and Controls

[0256] Embodiments of the present disclosure provide the technology for screening various types of gynecological cancer from biological samples. According to these embodiments, the present disclosure includes but is not limited to the method and composition for detecting the presence of various types and / or subclasses of gynecological cancer from biological samples. In some embodiments, the biological sample is a tissue sample, a blood sample, a plasma sample, a serum sample, a whole blood sample, a secretion sample, an organ secretion sample, a cerebrospinal fluid (CSF) sample, a saliva sample, a urine sample and / or a fecal sample. In some embodiments, the tissue sample is a gynecological tissue sample, which includes one or more of the following: vaginal tissue, vaginal cells, cervical tissue, cervical cells, endometrial tissue, endometrial cells, ovarian tissue and ovarian cells. In some embodiments, the tissue sample is an ovarian tissue sample, an endometrial tissue sample or a cervical tissue sample. In some embodiments, the subject is a human being.

[0257] In other embodiments, "sample", "test sample" and "biological sample" refer to a fluid sample containing or suspected of containing the methylated DNA markers of the present disclosure. The sample may be derived from any suitable source. In some cases, the sample may comprise a liquid, a flowing particulate solid or a fluid suspension of solid particles. In some cases, the sample may be processed before the analysis described herein. For example, the sample may be separated or purified from its source before analysis. In a specific example, the source is a mammalian (e.g., human) body material (e.g., body fluids, blood such as whole blood, serum, plasma, urine, saliva, sweat, sputum, semen, mucus, tears, lymph, amniotic fluid, interstitial fluid, cerebrospinal fluid, feces, tissue, organ, one or more dried blood spots, etc.). Tissues may include, but are not limited to, gynecological tissue, oropharyngeal tissue, nasopharyngeal tissue, skeletal muscle tissue, liver tissue, lung tissue, kidney tissue, myocardial tissue, brain tissue, bone marrow, cervical tissue, skin, etc. The sample may be a liquid sample or a liquid extract of a solid sample. In some embodiments, the source of the sample can be an organ or tissue, such as a biopsy sample and / or a secretion sample (e.g., gynecological secretions), which can be dissolved by tissue disintegration / cell lysis. Alternatively, the sample can be a nasopharyngeal or oropharyngeal sample obtained using one or more swabs, which, once obtained, are placed in a sterile tube containing viral transport medium (VTM) or universal transport medium (UTM) for testing.

[0258] Various volumes of fluid samples can be analyzed. In some exemplary embodiments, the sample volume can be about 0.5 nL, about 1 nL, about 3 nL, about 0.01 μL, about 0.1 μL, about 1 μL, about 5 μL, about 10 μL, about 100 μL, about 1 mL, about 5 mL, about 10 mL, etc. In some cases, the volume of the fluid sample is between about 0.01 μL and about 10 mL, between about 0.01 μL and about 1 mL, between about 0.01 μL and about 100 μL, or between about 0.1 μL and about 10 μL.

[0259] In some cases, fluid sample can be diluted before being used to measure.For example, in the embodiment that the source containing methylated DNA mark is body fluid (for example blood, serum, secretion), available suitable solvent (for example buffer, such as PBS buffer) dilution body fluid.Fluid sample can be diluted about 1 times, about 2 times, about 3 times, about 4 times, about 5 times, about 6 times, about 10 times, about 100 times or more times before use.In other cases, fluid sample is not diluted before being used to measure.

[0260] In some cases, sample may be processed before analysis. Processing before analysis can provide additional functions, such as non-specific protein removal and / or the mixing function of effective but cheap realization. The general method of processing before analysis can comprise and use electric capture, AC electric, surface acoustic wave, isotachophoresis, dielectrophoresis, electrophoresis or other pre-concentration technology known in the art. In some cases, fluid sample can be concentrated before being used to measure. For example, in the embodiment that the source that contains methylated DNA mark is human body fluid (for example blood, serum, secretion), can concentrate fluid by precipitation, evaporation, filtration, centrifugation or its combination. Fluid sample can be concentrated about 1 times, about 2 times, about 3 times, about 4 times, about 5 times, about 6 times, about 10 times, about 100 times or more times before use.

[0261] It may be necessary to include a control. The control can be analyzed simultaneously with the sample from the subject, as described above. The results obtained from the subject sample can be compared with the results obtained from the control sample. A standard curve can be provided, which can be compared with the assay results of the sample. Such a standard curve shows the relationship between the assay unit and the level of one or more methylated DNA markers. Using samples taken from multiple donors, a standard curve can be provided for reference levels of methylated DNA markers in normal healthy tissue, as well as a standard curve for "risk" levels of methylated DNA markers in tissue taken from donors who may have one or more characteristics of gynecological cancer.

[0262] The embodiments of the present disclosure also include test kits for performing the methods described herein. Test kits include embodiments of compositions, devices, equipment, etc. as described herein, and instructions for use of test kits. Such instructions describe appropriate methods for preparing analytes from samples, such as collecting samples and preparing nucleic acids from samples. The individual components of the test kit are packaged in appropriate containers and packaging (e.g., vials, boxes, blister packs, ampoules, cans, bottles, tubes, etc.), and the components are packaged together in appropriate containers (e.g., one or more boxes) to facilitate storage, transportation, and / or user use of the test kit. It should be understood that liquid components (e.g., buffer) can be provided in lyophilized form for user recovery. The test kit may include controls or references for evaluating, verifying, and / or ensuring test kit performance. For example, a test kit for determining the amount of nucleic acid present in a sample may include controls comprising the same or another nucleic acid of known concentration for comparison, and in some embodiments, further includes a detection reagent (e.g., primer) having specificity for the control nucleic acid. The test kit is suitable for use in clinical settings, and in some embodiments, is suitable for use at home. In some embodiments, the components of the test kit provide the function of a system for preparing nucleic acid solutions from a sample. In some embodiments, certain components of the system are provided by the user.

[0263] In some embodiments, the present disclosure provides compositions (e.g., reaction mixtures). In some embodiments, the present disclosure provides compositions comprising nucleic acids comprising DMRs and reagents capable of modifying DNA in a methylation-specific manner (e.g., methylation-sensitive restriction enzymes, methylation-dependent restriction enzymes, and bisulfite reagents) (e.g., methylation-sensitive restriction enzymes, methylation-dependent restriction enzymes, 10-11 translocation (TET) enzymes (e.g., human TET1, human TET2, human TET3, murine TET1, murine TET2, murine TET3, Nasella TET (NgTET), Coprinus cinereus (CcTET)) or variants thereof), borane reducing agents). Some embodiments provide compositions comprising nucleic acids comprising DMRs and oligonucleotides, as described herein. Some embodiments provide compositions comprising nucleic acids comprising DMRs and methylation-sensitive restriction enzymes. Some embodiments provide compositions comprising nucleic acids comprising DMRs and polymerases.

[0264] In some embodiments, the technology described herein is associated with a programmable machine that is designed to perform a series of arithmetic or logical operations provided by the methods described herein. For example, some embodiments of this technology are associated with computer software and / or computer hardware (e.g., executed therein). In one aspect, the technology relates to a computer comprising a form of memory, an element for performing arithmetic and logical operations, and a processing element (e.g., a microprocessor) for executing a series of instructions (e.g., methods as provided herein) to read, operate, and store data. In some embodiments, the microprocessor is part of a system for: determining methylation status (e.g., the methylation status of one or more DMRs in Table 1 or Table 2); comparing methylation status; generating a standard curve; determining Ct values; calculating scores, frequencies, or percentages of methylation; identifying CpG islands; determining the specificity and / or sensitivity of an assay or marker; calculating ROC curves and associated AUCs; sequence analysis; all as described herein or known in the art. In some embodiments, the microprocessor is part of a system for determining the level of protein expression and / or activity (e.g., one or more protein markers described herein); comparing the level of protein marker expression or activity to a standard non-cancerous level; all as described herein or known in the art. In some embodiments, the microprocessor is part of a system for determining methylation status (e.g., the methylation status of one or more DMRs in Table 1 or Table 2); comparing methylation status; generating a standard curve; determining a Ct value; calculating the score, frequency, or percentage of methylation; identifying CpG islands; determining the specificity and / or sensitivity of an assay or marker; calculating an ROC curve and associated AUC; sequence analysis; all as described herein or known in the art; and / or determining the level of protein expression and / or activity (e.g., one or more protein markers described herein); comparing the level of protein marker expression or activity to a standard non-cancerous level; all as described herein or known in the art.

[0265] In some embodiments, a software or hardware component receives the results of multiple assays and determines a single value result based on the results of the multiple assays to report to a user, wherein the single value result indicates a cancer risk (e.g., determining the methylation state of one or more DMRs in Table 1 or Table 2, and determining protein marker expression and / or activity levels). A related embodiment calculates a risk factor based on a mathematical combination (e.g., a weighted combination, a linear combination) of the results from multiple assays (e.g., determining the methylation state of one or more DMRs in Table 1 or Table 2, and determining protein marker expression and / or activity levels). In some embodiments, the methylation state of the DMR defines a dimension and can have values ​​in a multidimensional space, and the coordinates defined by the methylation states of the multiple DMRs are, for example, results reported to the user that are associated with cancer risk.

[0266] In some embodiments, various embodiments of the present disclosure are associated with a plurality of programmable devices that operate in concert to perform the methods described herein. For example, in some embodiments, a plurality of computers (e.g., connected via a network) can work in parallel to collect and process data, e.g., in the implementation of cluster computing or grid computing or some other distributed computer architecture that relies on a complete computer (with onboard CPU, storage, power supply, network interface, etc.) connected to a network (private, public, or the Internet) via conventional network interfaces (e.g., Ethernet, fiber optic) or wireless networking technology.

[0267] For example, some embodiments provide a computer including a computer-readable medium. The embodiment includes a random access memory (RAM) coupled to a processor. The processor executes computer-executable program instructions stored in the memory. Such processors may include a microprocessor, an ASIC, a state machine, or other processors, and may be any of a variety of computer processors, such as processors from Intel Corporation (Intel Corporation) in Santa Clara, California and Motorola Corporation (Motorola Corporation) in Schaumburg, Illinois. Such processors include or may communicate with a medium (e.g., a computer-readable medium) storing instructions that, when executed by the processor, cause the processor to perform the steps described herein.

[0268] In some embodiments, the computer is connected to a network. The computer may also include many external or internal devices, such as a mouse, CD-ROM, DVD, keyboard, display or other input or output device. Examples of computers are personal computers, digital assistants, personal digital assistants, cellular phones, mobile phones, smart phones, pagers, digital tablets, notebook computers, internet appliances and other processor-based devices. Generally speaking, the computer related to the aspects of the technology provided herein can be any type of processor-based platform, which operates on any operating system that can support one or more programs including the technology provided herein, such as Microsoft Windows, Linux, UNIX, Mac OS X, etc. Some embodiments include a personal computer that executes other application programs (such as application programs). Application programs may be included in a memory and may include, for example, word processing applications, electronic spreadsheet applications, email applications, instant messaging applications, presentation applications, internet browser applications, calendar / organizer applications and any other applications that can be executed by a client device. All such components, computers and systems associated with the technology described herein may be logical or virtual.

[0269] In some embodiments, the present disclosure provides a system for screening one or more types or subclasses of gynecological cancer in a sample obtained from a subject. Exemplary embodiments of the system include, for example, a system for screening multiple types or subclasses of gynecological cancer in a sample obtained from a subject (e.g., a stool sample, a tissue sample, an organ secretion sample, a CSF sample, a saliva sample, a blood sample, a plasma sample, or a urine sample). In some embodiments, the system includes: an analysis component configured to perform one or both of determining the methylation state of one or more methylation markers in the sample and determining the expression and / or activity level of one or more protein markers in the sample; a software component configured to compare the methylation state of one or more methylation markers in the sample and / or the expression and / or activity level of one or more protein markers in the sample with a control sample or a reference sample recorded in a database; and an alarm component configured to warn the user of a cancer-related state.

[0270] In some embodiments, an alert is determined by a software component that receives results from multiple assays (e.g., determining the methylation status of one or more methylation marks) (e.g., determining the expression and / or activity level of one or more protein markers) and calculates a value or result to be reported based on the multiple results.

[0271] Some embodiments provide a database of weighted parameters associated with each methylation marker and / or protein marker expression and / or activity level provided herein for calculating a value or result and / or an alert to be reported to a user (e.g., a physician, nurse, clinician, etc.) In some embodiments, all results from multiple assays are reported. In some embodiments, one or more results are used to provide a score, value, or result that is based on a combination of one or more results from multiple assays that indicates a cancer risk for the subject. Such methods are not limited to specific methylation markers. In such methods and systems, one or more methylation markers include bases in a DMR selected from the DMRs in Table 1 or Table 2.

[0272] In this detailed description of the various embodiments, for purposes of explanation, numerous specific details are set forth to provide a thorough understanding of the disclosed embodiments. However, those skilled in the art will appreciate that the various embodiments may be practiced with or without these specific details. In other cases, structures and devices are shown in block diagram form. Furthermore, those skilled in the art will readily appreciate that the particular order in which the methods are presented and performed is exemplary, and it is contemplated that these orders may be varied and still remain within the spirit and scope of the various embodiments disclosed herein.

[0273] The various components of the test kit can be placed in suitable containers as needed. The test kit may also include a container for holding or storing samples (e.g., a container or box for urine, whole blood, plasma, serum samples, tissue or body secretion samples). Where appropriate, the test kit may also optionally contain a reaction vessel, a mixing container and other components that help prepare reagents or test samples. The test kit may also include one or more instruments for assisting in obtaining test samples, such as a syringe, a pipette, tweezers, a measuring spoon, etc. In some embodiments, the instrument is a collection device, including but not limited to a tampon, a douche that releases liquid into the vagina and recollects fluid, a cervical brush, a Fournier cervical self-sampling device and a swab. In some embodiments, the biological sample is obtained from a subject, and the method also includes extracting a DNA sample from the biological sample. In some embodiments, a collection device with an absorbent member that can collect the biological sample upon contact is used to collect the biological sample. In some embodiments, the absorbent member is a sponge configured to be inserted into the orifice.

[0274] 5. Examples

[0275] It will be apparent to those skilled in the art that other suitable modifications and adaptations of the disclosed methods described herein are readily applicable and understandable, and can be made using suitable equivalents without departing from the scope of the disclosure or the aspects and embodiments disclosed herein. Having now described the disclosure in detail, it will be more clearly understood by reference to the following examples, which are intended only to illustrate some aspects and embodiments of the disclosure and should not be construed as limiting the scope of the disclosure. The disclosures of all journal references, U.S. patents, and publications cited herein are hereby incorporated by reference in their entirety.

[0276] The present disclosure has several aspects, illustrated by the following non-limiting examples.

[0277] Example 1

[0278] Experiments were performed to evaluate the feasibility of a panel of methylated DNA markers (MDMs) for detecting nonspecific gynecological cancers, site-specific gynecological cancers (e.g., cervical cancer, ovarian cancer, endometrial cancer), and specific gynecological cancer subtypes.

[0279] A proprietary approach utilizing sample preparation, sequencing, an analyses pipeline, and filters was used to identify differentially methylated regions (DMRs) and narrow them to those that pinpoint specific gynecological cancer types and perform well in clinical testing settings. A cross-cancer analysis of RRBS data identified 249 hypermethylated gynecological cancer-specific (endometrial cancer (EC), ovarian cancer (OC), or cervical cancer (CC)) DMRs (Table 1). These included regions specifically hypermethylated for one or two (most) gynecological cancers, as well as subclass-specific regions. These experiments also identified 89 regions that were commonly hypermethylated across all three gynecological cancers (Table 2). Characteristics of the markers include very low background noise (≤0.01) in leukocytes, which mitigates inflammatory signatures and may allow for plasma-based testing. The marker signal was also low (≤0.05) in BCV tissue, the primary cell type in tampon tissue. All MDMs achieved an AUC exceeding 0.90 for distinguishing cancer from leukocytes and ≥0.85 for distinguishing one cancer from another.

[0280] Table 1: Methylated regions that distinguish specific types of gynecological cancer (endometrial cancer (EC), ovarian cancer (OC) or cervical cancer (CC)) from benign tissue (genomic coordinates available using the human February 2009 (GRCh37 / hg19) assembly).

[0281]

[0282]

[0283]

[0284]

[0285]

[0286]

[0287]

[0288]

[0289]

[0290] Example 2

[0291] Based on the experiments described in Example 1, a set of novel differentially methylated regions (DMRs) were identified that distinguished various types of gynecological cancers from non-neoplastic control DNA, as shown in Table 2.

[0292] Table 2: Commonly methylated regions present in all three gynecological cancers (e.g., endometrial cancer (EC), ovarian cancer (OC), and cervical cancer (CC)) assayed from benign gynecological tissues (genomic coordinates available using the human February 2009 (GRCh37 / hg19) assembly).

[0293]

[0294]

[0295]

[0296]

[0297] Example 3

[0298] From the two sets of markers in Example 1 and Example 2, 25 candidate markers were selected for validation studies with independent cases and controls (Table 3). Methylation-specific PCR assays were developed based on DMR sequences and tested on tissue samples. Short amplicon primers (<150 bp) were designed to target the most discriminatory CpGs in DMRs, and assay controls were tested to ensure that fully methylated fragments were robustly amplified in a linear fashion; whereas unmethylated and / or unconverted fragments were not amplified. Tissue samples from 82 EC (16 serous, 18 carcinosarcoma, 7 clear cell, 17 grade 1 / 2 endometrioid, 24 grade 3 endometrioid), 82 OC (36 serous, 21 clear cell, 4 mucinous, 21 endometrioid), and 64 CC (36 squamous cell, 28 adenocarcinoma) were compared with benign epithelial controls (29 cervicovaginal, 29 fallopian tube, 14 benign endometrial tissue). As shown in Table 3, although CDO1 and DLGAP1 differentiated any cancer type from benign control tissue, most MDMs showed gynecological cancer specificity.

[0299] Table 3: Candidate markers selected for validation (OC: ovarian cancer; Ser OC: serous ovarian cancer; clear cell OC: clear cell ovarian cancer; endo OC: endometrioid ovarian cancer; muc OC: mucinous ovarian cancer; CC: cervical cancer; Ad CC: adenocarcinoma cervical cancer; sqCC: squamous cervical cancer; EC: endometrial cancer; endo EC: endometrioid endometrial cancer; pangyne: nonspecific gynecological cancer (e.g., OC, EC, and CC)).

[0300]

[0301]

[0302] Additionally, representative data for calibration plots, adjusted box plots, and subclass-adjusted box plots are provided for each of the 25 candidate MDMs identified, as shown in Figures 2-26. Taken together, global methylome sequencing, stringent filtering criteria, and biological validation for gynecological cancers yielded candidate MDMs for both site-specific and universal detection of gynecological cancers.

[0303] Example 4

[0304] DNA methylation is an early event in the development of endometrial cancer (EC) and may have utility in EC testing. One of the most promising sample types for clinical testing is vaginal fluid from tampons or similar collection devices. A comprehensive methylome NGS study, followed by validation on independent tissues, was previously performed to identify discriminatory EC-associated methylated DNA marker (MDM) candidates, which were subsequently tested in self-collected tampon samples from women with and without EC. In this example, an additional round of testing was performed on a subset of tampon samples using several new MDMs and a new set of epithelial reference assays, which provide a measure of total epithelial shedding.

[0305] In brief, an earlier reduced representation bisulfite sequencing (RRBS) study (including DNA from frozen EC, benign endometrial (BE), benign cervicovaginal (BCV) tissue, and benign buffy coat samples) was reanalyzed to identify epithelial reference genes and several new EC MDMs. Candidate reference markers were selected based on receiver operating characteristic (ROC) discrimination, fold change in methylation levels, methylation differences, and p-values ​​for all three epithelial tissue types compared with buffy coat (leukocyte) samples. EC MDMs were selected using the same criteria, but comparing EC tissue to the other three sample types. Several additional previously identified ECMDMs were also selected for testing in vaginal fluid. A quantitative methylation-specific PCR (qMSP) assay was developed and tested in 50 women aged ≥45 years with abnormal uterine bleeding (AUB) or postmenopausal bleeding (PMB), or women of any age who self-collected vaginal fluid using tampons before clinically indicated endometrial sampling or hysterectomy and had biopsy-proven EC. Cases included 25 women with biopsy-proven EC and 25 controls with benign biopsies.

[0306] Four candidate epithelial reference markers were selected from early tissue RRBS data: FNBP1, NCOR2, and two regions associated with S1PR4. Methylation was consistent, concordant (all CpGs), and robust (>50%) across EC, EB, and BCV tissues. In contrast, leukocyte methylation was <1%. Two novel EC MDMs, GYPC and CYP26C1, met cancer-specific criteria from the RRBS data (AUC > 0.85; absolute mean CpG methylation >20% in EC; methylation fold-change ratio (case / control) >10; p-value <0.001). These markers, along with LBX2, SPDYA, ZSCAN12, and TERC (positive and negative strands) from Examples 1 and 2, were tested in a pilot 50-sample tampon sample. The four reference gene markers were strongly positive in all 25 cases and 25 controls, with the positive strand S1PR4 assay demonstrating the most robust and consistent methylation between cases and controls. For EC-specific MDM, TERC (positive chain) performed the best (AUC = 0.88) and SPDYA performed the worst (AUC = 0.60).

[0307] Reanalysis of the endometrial / cervical RRBS discovery data with reference epithelial markers generated MDM candidates for vaginal fluid samples, and most of the tested EC-associated MDMs showed promising high performance in tampon-collected vaginal fluid (Table 4).

[0308] Table 4. Methylated regions that distinguish benign tissue from endometrial cancer (EC) (genomic coordinates available using the human February 2009 (GRCh37 / hg19) assembly).

[0309]

[0310]

[0311] Example 5

[0312] Early detection and treatment of endometrial cancer (EC) portends a favorable prognosis, often curable with surgery alone, especially in the setting of stage IA disease. However, presentation with advanced-stage EC often requires multimodal therapy, and oncologic outcomes are less than optimal. Therefore, a study was conducted using methylome sequencing discovery and independent sample validation experiments to broaden the current range of candidate methylated DNA markers (MDMs) for EC to include both the more common endometrioid histology and the less common, more aggressive EC histology. The performance of these novel ECMDMs was tested in vaginal fluid obtained via patient-collected tampons from women presenting with a new diagnosis of perimenopausal AUB, PMB, or biopsy-proven EC.

[0313] The study was conducted in three phases. First, tissue-based methylated DNA marker (MDM) discovery was performed using reduced representation bisulfite sequencing (RRBS) on DNA extracted from frozen EC and benign tissues. Second, biological validation of EC-specific MDM was performed using quantitative methylation-specific PCR (qMSP) on DNA extracted from an independent set of formalin-fixed paraffin-embedded (FFPE) EC and benign endometrium (BE). The third phase involved clinical translation of MDM detection via qMSP on DNA extracted from vaginal fluid samples obtained from women with EC, atypical endometrial hyperplasia (AEH), endometrial hyperplasia without atypia, or benign endometrium (BE) via patient-collected intravaginal tampons.

[0314] Primary fresh-frozen EC tissue was identified from a prospectively maintained EC biobank containing >1,500 frozen specimens from consenting patients at the time of hysterectomy for EC or AEH. EC included in the discovery phase represented the five most common EC histologies (grade 1 / 2 endometrioid carcinoma, grade 3 endometrioid carcinoma, serous and clear cell carcinomas, and uterine carcinosarcoma). Frozen tissue blocks were required to have at least 70% tumor purity for inclusion. Benign endometrial (BE) tissue was collected from consenting patients by Pipelle or EndoSampler immediately after a clinically indicated outpatient endometrial biopsy in women aged ≥45 years who presented for AUB or PMB as an additional sample for study. EC histology and BE menstrual or atrophic endometrium were confirmed by a gynecologic pathologist. Benign cervicovaginal (BCV) squamous tissue was collected from premenopausal and postmenopausal women undergoing hysterectomy for benign indications. Both BE and BCV tissues were fresh-frozen until DNA extraction. Buffy coats were collected from healthy, cancer-free female donors who were currently undergoing cervical cancer screening and mammography. Women who had been diagnosed with other cancers, had received chemotherapy within the previous 5 years, had received prior pelvic radiation, had a concurrent cancer diagnosis at the time of cervical cancer, or had undergone prior solid organ or bone marrow transplantation were excluded. Clinical variables were extracted from the electronic medical records of all enrolled participants.

[0315] The biological validation cohort identified an independent cohort of women with newly diagnosed EC who underwent hysterectomy as initial treatment. Formalin-fixed, paraffin-embedded (FFPE) EC tissue representing the same histology as the discovery cohort was included. Additionally, FFPE BE tissue was obtained from women who underwent hysterectomy for benign indications (frequency-matched by age), as well as FFPE endometrial hyperplasia and AEH tissue without atypia from women who underwent hysterectomy. All histologies were confirmed by a gynecologic pathologist (MES), who also selected the tissue block sites for macroscopic dissection. Eligibility criteria were the same as for the discovery cohort.

[0316] Vaginal fluid was collected from two cohorts of women using self-inserted tampons (tampon pilot). One cohort included women aged 45 years or older who presented to the Mayo Clinic Department of Obstetrics and Gynecology for AUB or PMB or were postmenopausal without bleeding and were referred for pelvic ultrasound to assess for thickened endometrial streaks (ES). Women were excluded if they did not undergo clinical endometrial sampling or if they had undergone endometrial sampling within the previous 3 months. Final clinical pathology diagnosis was used. EC cases were included if the endometrial sampling or hysterectomy pathology had EC. All final clinical diagnoses of AEH or endometrial hyperplasia without atypia were included in the exploratory analysis, and any sample with benign endometrial sampling was eligible as a BE control. The other cohort consisted of women aged 18 years or older with biopsy-proven EC or AEH who presented to the Mayo Clinic Department of Gynecologic Oncology for clinically indicated hysterectomy. Eligibility criteria were the same as for the discovery and biovalidation cohorts.

[0317] After verification of diagnosis and selection of tissue blocks by a research gynecologic pathologist (JKS, SEK), frozen EC and BCV tissues embedded in optimal cutting temperature (OCT) compound were microtomed to provide ten 10-micron volumes. Completely frozen tissue samples of BE collected using an office biopsy Pipelle or EndoSampler were used, either once or twice. Genomic DNA was purified from tissue and buffy coat specimens using the DNeasy blood and tissue protocol and the QIAamp DNA blood protocol (Qiagen, Valencia, CA), respectively. DNA was repurified using AMPure XP beads (Beckman-Coulter, Brea CA) and quantified using PicoGreen (Thermo-Fisher, Waltham MA). DNA quality was assessed using real-time quantitative PCR. RRBS libraries were prepared. In brief, 300ng of DNA 1) is digested with MspI, 2) is connected to methylation sequencing adapter, 3) is treated with sodium bisulfite (Epitect sodium bisulfite scheme, Qiagen), 4) is amplified and enriched with adapter-specific primers, and 5) size selection (160bp-280bp) is carried out to remove primer dimers and larger CpG sparse regions using AMPure beads. The library is sequenced using the Illumina HiSeq 2500 instrument (Illumina, San Diego CA) of the Mayo Clinic Medical Genomics Center. Candidate genome differentially methylated regions (DMRs) are selected as described below.

[0318] A quantitative methylation-specific PCR assay was developed based on the CpG methylation signatures of selected DMRs. Primers were designed using MethPrimer to target bisulfite-modified sequences for each gene identified, as well as a CpG-free reference region within the β-actin gene. Quality control checks were performed on primers on 20 ng (approximately 6250 genome equivalents) of positive and negative methylation controls. DNA was bisulfite-converted using the EZ-96 DNA Methylation Kit (Zymo Research, Irvine CA) and amplified using SYBR Green detection on Roche 480 LightCyclers (Roche, Basel Switzerland). Serially diluted, universally methylated DNA samples were used as positive control standards, and negative controls included bisulfite-converted and unconverted leukocyte-derived genomic DNA and converted whole-genome amplified (unmethylated) DNA. MDM results were normalized to β-actin. Assay performance was validated using discovery cohort samples. Markers that performed suboptimally compared to RRBS results and cutoff values ​​(described below) were not considered further.

[0319] DNA extracted from independent FFPE EC and BE tissues was then tested for MDM using qMS. These MDMs were also tested in AEH and endometrial hyperplasia without atypia. Tissue blocks were grossly dissected using a 1 mm or 2 mm core needle after histological verification by a research gynecologic pathologist (MES) and selection of the gross anatomical site that best represented the diagnosis. DNA was purified using the Qiagen QIAmp FFPE DNA Tissue Kit (Part No. 56404) and bisulfite converted as described above. Samples were blinded, randomized, and assayed by qMSP as described above.

[0320] In the tampon pilot, two groups of consenting women placed regular-sized, unscented tampons on their own. Patients in the group undergoing examination for AUB, PMB, or thickened ES had tampons inserted in the clinic before their gynecological consultation and removed before the clinician-assigned pelvic examination and endometrial sampling. Patients in the group with biopsy-proven EC or AEH had tampons placed in the preoperative area on the day of their hysterectomy and removed in the operating room. The duration of tampon retention in the vagina was recorded in both groups.

[0321] After removal, each tampon was placed in a 50 mL conical tube containing sterile PBS buffer, centrifuged through a mesh filter, and separated into a precipitate and a supernatant fraction, which was stored at -80°C until DNA extraction. Approximately halfway through the expected recruitment of the tampon pilot, 50 mM EDTA was added to the PBS buffer to enhance DNA recovery and reduce nuclease degradation. Tampon precipitate DNA was extracted using the High Pure Viral Nucleic Acid Kit (Roche, Basel, Switzerland) and quantified using a Qubit fluorometer (Invitrogen, Walther MA). DNA was bisulfite converted and the selected MDMs were assayed by qMSP as described above using β-actin as a reference gene.

[0322] For discovery, previously published methods were used. Briefly, the Simplified Analysis and Annotation Pipeline (SAAP-RRBS) of the Mayo Clinic in-house analysis software package RRBS was used for quality scoring, sequence alignment, annotation to the UC Santa Cruz reference genome, and differential analysis of DMRs. Candidate CpGs were excluded if data coverage within each sample group was <50%. CpG islands are typically defined biochemically by an observed CpG to expected CpG ratio >0.6. However, for this model, DMRs were created based on the distance between CpG site locations on each chromosome, excluding regions containing five or fewer CpGs. DMRs with background methylation rates <2% in benign controls (BE, BCV, and buffy coat) were then selected and ranked according to the AUC of EC histology relative to benign controls. Statistical significance was determined by performing overdispersion-corrected logistic regression on the methylation percentage for each candidate DMR based on read counts. To account for the varying read depths within individual subjects, an overdispersion-corrected logistic regression model was used, with the dispersion parameter estimated using the Pearson chi-square statistic of the fitted model residuals. Candidate genomic DMRs were ranked and selected for further testing based on their significance level, AUC, and fold change difference between EC and benign controls (BE, BCV, and buffy coat). Sample size estimates for discovery were based on previously described methods.

[0323] Secondary DMR analysis was performed to identify endometrium-specific MDMs that were methylated in both EC and BE and unmethylated in BCV and buffy coat.

[0324] For independent tissue validation, the sample size was selected to improve the precision of sensitivity and specificity (minimize the width of the 95% confidence interval (95% CI)). Assuming a specificity of 95%, a control group of 29 subjects would provide a 95% CI of no more than ±10%. To achieve a 95% CI of no more than ±7% (target sensitivity of 90%), a minimum of 84 samples was required. The distribution of individual markers was examined using box plots and marker intensity plots. AUC values ​​were generated for each marker to assess accuracy. A random forest (rForest) model was used to generate predicted probabilities for samples representing EC cases. Random forest was cross-validated on a random marker set using 500 random unique training and test sets from bootstrap selection (approximately 2 / 3 for the training set and 1 / 3 for the test set) to generate 500 models. The accuracy error based on out-of-bag samples was then averaged across the 500 models. Marker selection was performed using the VSURF package in R using random forests in three steps: 1) eliminating the least important predictors, 2) selecting all predictors that were correlated with the response variable, and 3) reducing redundancy in the final marker selection.

[0325] For the tampon pilot, the sample size estimate was limited to detect an AUC of 0.70 (AUC = 0.50 represents chance). Using 100 EC and 92 BE, the power to detect this difference using a one-sided test at a 5% significance level exceeded 90%. EC frequency was matched to control BE by menopausal status of the subjects and date of tampon collection.

[0326] All women in the clinical group who underwent ES evaluation for AUB, PMB, or thickening and were diagnosed with AEH or endometrial hyperplasia without atypia after tampon collection were included in the exploratory analysis. In addition, the following tampon pilot subanalyses were performed: 1) sensitivity and specificity of MDM for EC when restricted to vaginal fluid samples collected before endometrial sampling (assuming spontaneous shedding of endometrial DNA), and 2) performance of MDM specifically in PBS / EDTA-buffered vaginal fluid samples.

[0327] RRBS was performed on 69 EC (16 grade 1 / 2 endometrioid, 16 grade 3 endometrioid, 11 serous, 11 clear cell carcinoma, and 15 carcinosarcoma), 44 BE (14 hyperplastic, 18 dysplastic, and 12 atrophic), 18 BCV, and 18 buffy coat samples from healthy female donors. The clinicopathological characteristics of the discovery-stage EC cases and BE controls are detailed in Table 5.

[0328] Table 5: Clinicopathological characteristics of EC cases and BE controls in the discovery cohort.

[0329]

[0330]

[0331] Sequencing coverage depth for all samples was approximately 40-50X. On average, filtered Cs with at least 10X coverage in the CpG context (our minimum inclusion requirement) averaged approximately 1.7 million per sample. The DMR calling algorithm, applied to multiple comparisons (all EC vs. all controls, histological EC subclass vs. BE, histological EC subclass vs. BCV, etc.), yielded a total of 323 statistically significant DMRs. Imposing performance cutoffs (AUC > 0.85; absolute mean CpG methylation in EC > 20%; methylation fold-change ratio (case / control) > 10; p-value < 0.001) reduced the number of DMRs to 54. Targeted qMSP assays were constructed and tested for the 54 selected DMRs. Subsequently, 21 targeted qMSP assays were discarded due to QC failure or poor performance relative to the corresponding sequencing data and / or the cutoffs noted above.

[0332] The remaining 33 MDMs were independently analyzed. These samples included 141 cases of EC (34 grade 1 / 2 endometrioid, 31 grade 3 endometrioid, 27 serous, 19 clear cell, and 30 carcinosarcoma), 112 cases of BE (35 secretory, 30 hyperplastic, 19 dysplastic, and 28 atrophic), 35 cases of AEH, and 24 cases of endometrial hyperplasia without atypia. Clinicopathological characteristics are shown in Table 6.

[0333] Table 6: Clinicopathological characteristics of EC cases, benign endometrium (BE) controls, atypical endometrial hyperplasia (AEH), and endometrial hyperplasia without atypia in the biological validation cohort.

[0334]

[0335] Several MDMs (EMX2OS, CYTH2_ 4043 , MPZ, NBPF24) demonstrated an AUC > 0.85 when differentiating EC (all histological types combined) from BE, with the majority uniquely differentiating between specific EC histological subclasses and BE. For example, when all EC histological subclasses were compared with BE, EEF1A2 had an AUC of 0.59, while the AUC for differentiating clear cell EC from BE was 0.91 (0.80-1). For the analysis of clear cell EC versus BE, 14 of 33 MDMs had an AUC ≥ 0.85. In contrast, only 5 of 33 MDMs distinguished carcinosarcoma from BE with an AUC ≥ 0.85. When evaluating EC histology combination MDMs and histology-specific MDMs, only 10 MDMs had an AUC below 0.85 across all comparisons. Thus, 23 MDMs had an AUC ≥ 0.85 in either the histology combination analysis or the histology-specific analysis.

[0336] For the tampon pilot experiment, four MDM assays (CDH4, LYPLAL1, c17orf64, and KRT86) were developed for endometrium-specific DMRs (ie, methylated in both EC and BE, but not in BCV tissue). In addition to these 4, 24 MDMs were proposed from biological validation, for a total of 28 MDMs tested in the tampon pilot: CDH4, c17orf64, CYTH2_4043, DIDO1, EEF1A2, EMX2OS, GATA2_3670, GDF7, JSRP1, LRRC8D_8831, LRRC34, LRRC41, LYPLAL1, SMPD5, MAX.chr10.4460, MAX.chr12.52652239-52652424, LINC02323, MDFI, MPZ, NBPF24, OBSCN, SEPT9, SFMBT2_0970, SQSTM1_3864, VILL, ZNF90, ZNF323, and ZNF506.

[0337] The tampon pilot enrolled 100 women with EC, 92 with BE, 11 with AEH, and 25 with endometrial hyperplasia without atypia. EC cases included 31 women undergoing clinical evaluation for AUB or PMB whose EC was diagnosed after tampon collection and 69 women with biopsy-proven EC known before tampon collection. All women with BE, all but three with AEH, and all but one with endometrial hyperplasia without atypia were from the perimenopausal group of women with AUB or PMB, whose tampons were collected before endometrial sampling. EC cases included 49 with grade 1 / 2 endometrioid, 9 with grade 3 endometrioid, 24 with serous, 4 with clear cell, 9 with carcinosarcoma, and 5 with mixed EC histologies. The clinicopathological characteristics of the EC cases, BE controls, and the AEH and endometrial hyperplasia without atypia groups are detailed in Table 7.

[0338] Table 7: Clinicopathological characteristics of EC cases, benign endometrium (BE) controls, endometrial hyperplasia without atypia, and atypical endometrial hyperplasia (AEH) in the Tampon Pilot Cohort.

[0339]

[0340]

[0341] When the combined EC cases from the AUB / PMB group and the biopsy-proven EC group were compared with BE controls, 28 MDMs each had a significant methylation fold change compared with controls. Table 8 lists the AUCs for differentiating EC from BE for each of the 28 MDMs tested in the tampon pilot. The 28-MDM group had a specificity of 96% (95% CI 89-99%) and a sensitivity of 76% (66-84%) for differentiating EC from BE (AUC 0.88 [0.82-0.93]). When the number of MDMs in the post hoc analysis was reduced to a 3-MDM group, the combination of SFMBT2_0970, NBPF24, and MAX.chr10.4460 produced an AUC that was identical to the 28-MDM group. When comparing stratified AUCs considering age ≥64 years versus <64 years (median age of the tampon pilot) and BMI ≥30 versus <30 kg / m2, there were no statistically significant differences in either covariate. When the analysis was restricted to tampon samples collected before endometrial sampling, the 28-MDM panel had a specificity of 96% (95% CI 89-99%) for distinguishing EC (n=31) from BE, with a similar sensitivity of 74% (95% CI 55-88%) (AUC 0.87 [0.77-0.98]).

[0342] Exploration of the performance of 28 MDMs in tampon specimens from women subsequently diagnosed with AEH or endometrial hyperplasia without atypia revealed lower methylation intensity compared with EC and higher intensity compared with BE.

[0343] As previously described, 50 mM EDTA was added to the PBS tampon buffer approximately halfway through the prospective vaginal fluid collection study period to improve DNA stability. Of the total EC cases and BE controls in the tampon pilot, 57 cases of EC and 52 cases of BE were collected with tampons in PBS / EDTA buffer. Table 8 lists the AUCs for discriminating between EC and BE for each of the 28 individual MDMs based on tampons collected in PBS / EDTA buffer. Compared to the complete tampon assay that included both PBS-only and PBS / EDTA-buffered vaginal fluid, the combined 28-MDM panel demonstrated improved sensitivity when tested on tampons collected into PBS / EDTA buffer (96% (95% CI 87-99%) specificity; 82% (70-91%) sensitivity (AUC 0.91 [0.85-0.97]) (Table 8). Additionally, in the PBS / EDTA buffer subanalysis with 95% specificity, the 28-MDM panel correctly identified: 17 of 20 endometrioid EC (85%), 18 of 23 serous EC (78%), all of 9 uterine carcinosarcomas (100%), 2 of 3 clear cell EC (67%), and 1 of 2 mixed EC histologies (50%).

[0344] Table 8: AUCs for the 28 DMRs included in the tampon pilot test set. Analysis was performed on all samples (100 EC, 92 BE), including tampons collected in PBS alone plus tampons collected in PBS / EDTA. The subanalysis of tampons collected in PBS / EDTA included 57 EC and 52 BE. AUCs are listed in descending order based on the analysis of PBS alone plus PBS / EDTA. Cancer specificity is also provided (CC: cervical cancer; OC: ovarian cancer; Ser OC: serous ovarian cancer; clear cell OC: clear cell ovarian cancer; EC: endometrial cancer; clear cell EC: clear cell endometrial cancer; pan gyne: nonspecific gynecological cancer (e.g., OC, EC, and CC)).

[0345]

[0346]

[0347] Through rigorous discovery and validation in tissue, we identified unique EC MDMs detectable in vaginal fluid collected with tampons and demonstrated the efficacy of using self-collected samples to triage patients with perimenopausal AUB or PMB. Translation to tampon-collected vaginal fluid samples demonstrated the high sensitivity and specificity of the 28-MDMEC panel tested in the tampon pilot for distinguishing underlying EC from BE. This high sensitivity and specificity also appeared to be maintained when a smaller 3-marker panel was evaluated. Sensitivity for detecting EC in this setting also remained high in a subanalysis that included only vaginal fluid samples collected from women with perimenopausal AUB or PMB before endometrial sampling to identify underlying endometrial pathology. These data support the conclusion that EC-associated MDMs are spontaneously shed into the vagina.

[0348] 6. Materials and Methods

[0349] The following materials and methods are used to identify various DNA methylation signatures that can distinguish one or more types and / or subtypes of gynecological cancer in a biological sample from a subject having or suspected of having a gynecological cancer.

[0350] Samples. Tissue and blood samples were obtained from the Mayo Clinic Biorepository and were overseen by the institutional IRB. Sample selection adhered strictly to the subject research authorization and inclusion / exclusion criteria. Tissues were macroscopically dissected, and histological review was conducted by a dedicated GI pathologist. Samples were age- and sex-matched, randomized, and blinded. Cervical cancer (CC) subtypes included 1) adenocarcinoma and 2) squamous cell carcinoma. Controls included benign cervicovaginal (BCV) tissue and whole blood-derived leukocytes. Endometrial cancer subtypes included 1) serous EC, 2) clear cell EC, 3) carcinosarcoma EC, and 4) endometrioid EC. Controls included non-neoplastic uterine tissue and whole blood-derived leukocytes. Ovarian cancer (OC) subtypes included 1) serous OC, 2) clear cell OC, 3) mucinous OC, and 4) endometrioid OC. Controls included non-neoplastic fallopian tube tissue and whole blood-derived leukocytes. The QIAamp DNA Tissue Mini kit (frozen tissue), QIAamp DNA FFPE Tissue kit (FFPE tissue), and QIAamp DNA Blood Mini kit (buffy coat samples) were used (Qiagen, Valencia, CA). DNA was purified from 190 frozen tissues (16 grade 1 / 2 endometrioid (G1 / 2E), 16 grade 3 endometrioid (G3E), 11 serous, 11 clear cell EC, 15 uterine carcinosarcoma, 44 benign endometrial (BE) tissues (14 hyperplastic, 12 atrophic, 18 dysplastic, 18 serous OC, 15 clear cell OC, 6 mucinous OC, 18 endometrioid OC, 6 benign fallopian tube, 14 benign fallopian tube brushings), 88 formalin-fixed paraffin-embedded (FFPE) cervical cancers (CC) and controls (36 squamous cell, 34 adenocarcinoma, 18 BCV), and 36 buffy coats from cancer-free women. DNA was purified using AMPure XP beads (Beckman-Coulter, Brea, VA). The DNA was repurified by PicoGreen (Thermo-Fisher, Waltham, MA) and quantified by qPCR.

[0351] Sequencing. Reduced representation bisulfite sequencing (RRBS) was performed on two sample batches: the first batch was endometrial and cervical samples, and the second batch was ovarian samples. To account for variability, randomly selected samples from batch 1 were also included in batch 2. Sequencing libraries were prepared according to the Meissner protocol (Gu et al. Nature Protocols 2011) with modifications. Samples were pooled in 4-plex format and sequenced by the Mayo Genomics Facility on an Illumina HiSeq2500 instrument (Illumina, San Diego CA). Reads were processed by Illumina pipeline modules for image analysis and base calling. Secondary analysis was performed using the Mayo-developed bioinformatics suite SAAP-RRBS. Briefly, reads were cleaned using Trim-Galore and aligned to the GRCh37 / hg19 reference genome constructed using BSMAP. For CpGs with coverage ≥10X and base quality scores ≥20, methylation ratios were determined by calculating C / (C+T) or, conversely, G / (G+A) for reads mapped to the reverse strand.

[0352] Biomarker selection. A proprietary DMR (differentially methylated region) identification pipeline and regression package were used to infer DMRs based on the mean methylation values ​​of CpGs. Differences in mean methylation percentages were compared between cancer and buffy coat controls; tiling reading frames within 100 base pairs of each mapped CpG were used to identify DMRs with <2% methylation in controls; DMRs were analyzed only when the total depth of coverage was an average of 10 reads per subject and the difference between subgroups was >0. Assuming a biologically relevant increase in odds ratios of >3x and a coverage depth of 10 reads, at a 5% significance level in a two-sided test, and assuming a binomial variance inflation factor of 1, ≥18 samples per group were required to achieve 80% power.

[0353] After regression, DMRs were ranked by p-value, area under the receiver operating characteristic curve (AUC), and fold change difference (FCD) between cancer and buffy coat. AUC > 0.90 and FCD > 20 were required. Because independent validation was planned in advance, no adjustment for false discovery was made during this phase.

[0354] As described above, the three cancers were analyzed separately and by subtype, generating separate lists of the best-performing DMRs. The combined sample and CpG level data were then appended to the three DMR lists. Each CpG had to be represented by 80% or more in the compared samples. The DMRs in each list were then ranked by methylation ratio, which is the ratio of the number of methylated cytosines at a given locus to the total cytosine counts at that locus. For cancer, the ratio was required to be ≥0.20 (20%); for BCV tissue controls, ≤0.05 (5%); and for buffy coat controls, ≤0.01 (1%). Regions that did not meet these criteria were discarded. In addition, the CpG methylation patterns within the region were required to be continuous or consistent. Subsequently, the candidate DMRs (for each cancer and each subtype) were compared with the other two cancers separately (using average CpG methylation). For example, serous EC regions that met the filtering criteria were compared with ovarian cancer (overall) and then compared with cervical cancer (overall). To qualify as a site-specific DMR (in this case, a serous EC DMR), the FCR between serous EC cancer samples and OC or CC samples (or both) must be 5-fold or higher. To qualify as a universal DMR, the marker needs to appear in each of the best lists (above).

[0355] Biomarker Validation. A subset of locus-specific and universal cancer DMRs were selected for further development. The criterion was primarily a logistically derived area under the ROC curve metric, which provides a performance estimate of the discriminatory potential of the regions. An AUC of 0.85 was chosen as the cutoff for the comparison of cancer to cancer tissue. Differences in methylation were also an important factor. The feasibility of 20-30 methylated DNA markers (MDMs) was limited. This was primarily due to the limited amount of sample DNA and the workload required to develop a high-performance analytical assay. Quantitative methylation-specific PCR (qMSP) primers were designed for the candidate regions using MethPrimer (Li LC and Dahiya R. MethPrimer: designing primers for methylation PCRs. Bioinformatics 2002 Nov;18(11):1427-31 PMID:12424112) and QC checks were performed on 20 ng (6250 equivalents) of positive and negative genomic methylation controls. Multiple annealing temperatures were tested to obtain optimal discrimination. Validation was performed on independent tissue samples by qMSP.

[0356] These tissues were identified as before by expert clinical and pathological review. DNA purification was performed as previously described. The EZ-96 DNA methylation kit (Zymo Research, Irvine CA) was used for the sulfite conversion step. 10 ng of converted DNA (per marker) was amplified using SYBR Green detection on Roche 480 LightCyclers (Roche, Basel, Switzerland). Serial dilutions of universal methylated genomic DNA (Zymo Research) were used as quantitative standards. The CpG-agnostic ACTB (β-actin) assay was used as an input reference and normalization control. Results are expressed as methylated copies (specific marker) / ACTB copies.

[0357] Statistics. Results of individual MDM performance were analyzed. Calibration plots were tested to confirm the suitability of ACTB normalization. Boxplots (radii and corrections) and heatmaps were created to represent a large number of epigenetic relationships between cancers, subtypes, and controls.

[0358] Sequences. Provided below are various nucleotide sequences cited in this disclosure.

[0359] MAX.chr10.4460:

[0360]

[0361] MAX.chr1.2152:

[0362] CGACTCTTCGAGCGCCCCTCTGCTTCTGTAGAGGGGTCGAGCCATGTCAAGGTAGACCCTGTGTCGGCCCGTCTCCCTCGGATCCTCCGCACCAATCACTGTTGCTGAATCCGACACCCGGCGGATCCAGTGCGGAGTCTCGAACAGCTGCGGAGCTGGGAGCTACGGGACATGAGGAGTGCGGGGGGGAAGAGAAGACGGCGGAGGAAAATCCCCCGGCGGTGCTCAACTGCGGCTTTCTCTCTCGGCTGTGAGCCGGCTCCGCCCTCCGGCTTCCAGAGCAAGTGGCTTCTGCGTTCACCGCCCCCCGCCGTTTGTGGGGCGGGGCCGATTCATAAGAATCGGTTCTCACCAATGGAGGGCTTAGCATGTTTAACCTCAGGATCATAAACAAAAGACACTGCTAGAACGGTCGGGAAAGTCATACGCTTTGCTTATCTTATATATAGATTTCTAAAATTCCAAACCGGGGACGCGTTGGTGGTGTAGTGGTGAGCACAGCTGCCTTTCAAGCAGTTAACGCGGGTTCGATTCCCGGGTAACGAAACGTTTTTGTCTTTCCTTCTACGAAAAACTTTTCTGAGCCG(SEQ ID NO:2)。

[0363] MAX.chr11.0394:

[0364] CCCTTGAGGCCAGGAGTTCGAGACCAGCCTGTGCAACACAGAAGACACTATCTCTACAAAAAATTAAAAAATTAGCTAGGCATAGTGGCACATGCCTGTGGTCCCAGCTACTCCGGAGATTGAAGCAGGAGGATCACTTGAGTGAGGGAGGTGGAGGCTCCAGTGAGTCGTGATCGTGCCACTGCACTCCAGCCTGGACGACAGAGCGAGACCCTGCCCCCTCGCCAAAAAAAAAATACTGGGATGCTATACACAAAATTGCCTTGAAAACTTGAGCACGGAACACCAAACAGCTAAGCGTGCCGGTTTGGGGAGGGCGGGGGAGGAATAAGGAGCTGCAACGGTAAGAGGCCGCCACACGGTGGCGCAGTGAGGCTGGGAAACGGTGCACCCCGCGCAGGAGGGGGCACTCCCCGTCGCGGCCACCCGGGGTGGGCAGGAGGCGGCGCGGGCTGGCTGGTCTCTCCCGAGAAGGTTCTCTCCCGAGAAGGGTGCGTCTCAGGGCTTGTCAGTGGACCCCTGGAACATGGGGAAGACGCACAGACAAGGGTTTCGCTCTTTGCTCTCCTCTCTCCTTGTCAGACCTCTGTGACC(SEQ IDNO:3)。

[0365] MAX.chr11.3750:

[0366]

[0367] MAX.chr14.7696:

[0368] CGGCACGTGGGTGGGCGATGACGCCATTTACTGAGATTTGATCCCCACCACACGGCTCCGGGGTGAGAATTATGACATCTGGCTCAACACGGCTGCCCGGGACCCACACAGCCGAGCGGCCGAGCTCGGGCGGAGTCCCAGGGCGCCCACAGCACCCCGCCAGCGCGCCCCGTCCAGCAGGGCAGCTTTTGGGCGGAGGCGACCCCCACCGCAGGTCCCAGGACCCTGCGTGCTCTTGAGCCAGGGGTGGAGAGGCCCGACCGCGGGGGGCTGCCCCACCCCGCCGCCCTTCACCGCGAGCCGGGGCCCAGACCGCCCAGCCACGCCCAGAGCCCGCGGGCGGAGACGCCAGGGGCGGTGCCAGCGAGGTCCCGTCCCCGGTACCCCGTCCCGCCCCCCCACACGCGGTGACCTGGGGACGCCCCGCGGGAGTCGTTCTGCGGCTCCCCCTGGCGTCGGCTGGGGCCACCGCCCGGGCTCCCACCTCAACCCTGCAATATGGGGTTGGGGCAGAGTGGTCTGCTGCCCGCTGCCCGCAGCCGCTTCCGGTTAGGGAGGGAGCCTGGGCCTCTGGGTGCTCACGCTGCGCTTAACGCTGGTCCCGGCAGCAGTGAGGGTGGAAGCGGCCG(SEQ ID NO:5)。

[0369] MAX.chr19.5552:

[0370] CGGACCGTAGCTCCTTCCACGCATGAACCCCGCACACGAGTCGGGATTCCCCCCATGACCCTCCCGTGGCCCCCGCACAATCTGGAGAGACGCGGGGCTGCGGGCGCGGAGCTGCCCAGAGAGGACTCCTGCCCGGGCCCGCAGTCGCCGCGAAGGGACGGGACAGGACGCCCGGGGTCCCGGCTGCCAGCCCAGCCCCACCCTGCGGCCGAGGGGACCGAGGGCCGAGCTCCGCCAGCGGTACTCCGGTCCACAGAGCCCGGAGTCGCTGGCTGGGAGGCCGGGGACCCGCCACGGCCAGTTCCAACCAGCCCCTCCTCCCGTCTCGGGATCCCTGGCCCCTCACGCTCACCATTTTCCGAATTCCTCCGTGTCCCGGGGGCCTCTCTGCGGCTCCCACGACCAGTGCAGGTCCCTGTGTGACAGAGGCTGCCGCAGACTCTCCAGAGTGCCTCTCAGCGACAGAGACAGGAGCCCAGCGAAGTGGCGTGTAGAAGACGCCGCGGGCTTTTTCAATCTCGCACCCTCTTAGCTGAAGTGCGCCTGATTGACAGTTCCCACGACCCCGCCCCACGGCCCTGATTGGATAGTGCGACAGATCCCGCCCCCTGACGACTGAGTTACAGAAGCGATCTCACG(SEQ ID NO:6)。

[0371] MAX.chr19.0548:

[0372]

[0373] MAX.chr2.8918:

[0374] GAAGTCAGGGCAGTGCTGCAAAACCTCCACAGTGCGGAATTCCGGGAAAATTCTTTACAGAGGTGTGGAGGTGGAGGAAAGCTTCCTGGGCAGGCCTTTGGGGTCGTCCCCACGCAGGCGCTTGCAGCCACCCCAGCTCGCGCGGGGCCGGGCTTTGGGGTGTGAGAGCTGGGACGGGAGTCGGGTGGATGCCTGGCCGGAGCCGCCAGCTCCCCTCGTCCTCTTTGCTTGTCCTTTAGCACAAGGGCGAGCAGCGTAGGACAAAGACTCGGGCGGCAGCTGCCTGGTTCGGCGCGCAGGGGCGGCCTCGGCCACCCGGGGCGCCCGCCGCCTCCACCGCCCCGCGGGGGAGGCCCGATGCCCGTCTTTGTCTGTGCCGCCGCCGTGGGCCGGGTCCGCAGGAAGCGGGCGCCATCGTGCGGCCTGAGCTGGACACTGCGCCCCCGGAGGCGCGGAGGCGCGAACCACCAAGCGTGGCTCCAAGCTCCACGGGGACGCTGGTGTCATCGTGGCCACGACTGCTTGTACTGTTGTGGTGCGTTCTCTTTTGTATACTAAGTGCTGTGTGAACACAGAACCACTTCCAGTAAATGCAACTGAGCCGTCGCCAGCAGAAAAAG(SEQ ID NO:8)。

[0375] MAX.chr2.4778:

[0376] AACAGTGGCGCTCAGAGAAGACAGGACAGCGGGCGAGAGCTTGGGGGGCGATGGGAGGTGGAGAGGCACTCCAGGTCCCCAGGGGGCCAGGCGGAGCTGCGGGACAGGGCGCAGACCCCGAGGCCCAGGGAGCACCGGGTGGCCGGCGGCCTGCAGGCTGGCGAGGGCGTCGGGCGGCGCAGGGCAGGCCAGGGGGCGGGGGCGTCTGGGGCCCTGGCGTGGCGCCCGGAACACCCCGTGCCGGAAGCTCCATGTGACCGTGACTCCGCAGAAGCCGCGAGCGCAGCGAAACAAAGGGCGGCTCTGCGGCCGCCTCGAGCTCAGGCTGGCACCGAGGGCCCGGACCCCCATCCCACTCCGCACCCCCGGGCCTCCCGGCCCTTCTTGCCCTCCGACCCCGGGCTCTGGCAGGGCCGGGAGGCGCAGGAACCCCGCGGGGGATGGGGCCGGCGGACTGGCACTGAAGACACTGGGATGCAAGCGGGAGGCTGGGGGCGGGGGGCTGGGGGCGGGGGGCGGGGCTGCAGGGCGTGGACGGTCTC(SEQID NO:9)。

[0377] MAX.chr20.3853:

[0378] CGGAGCGGATATTCCCGGAGCCCCTCTGCGAGCCACGCGCCCCTCTGGGAAGCCCGCTTCCCCCTGCAGACAGGCGCTGTGACACGCTTGCGCCCCGGTCGAACAGGCGAAGAGGCCGAGGCCCAGAGCGGCGCAGGGCGAGCCTGGAGGCTGCGCCCCAGACCTGGACCAGCCACGGACGCCGCTCCCGCCGCTCCCTCCGCTCCGCTGCGCTCCGCACGCTGGCGCCGGCTCCCCGAGGCCCCGGGCGCCCCGGCCGCACGCCTGGGTAAAAGGTCCCGAGGAGTCCGCAGAAGCGCGCCCACGCCCGAGACGGCCGTTTCCGCCGGCCTGGGAAAGGGGCGGAGAAGGGGGTCGCCCGGGCCGCAGCGTGCCGGTCCCCGCCGGCCGAGCCGTGTTTGGGGCCAGTCCCCGCACCCCGCTTCTTCCCCACCTGGGGAGCGGGGCGCCGCGGTAGGGGCACTGGAGCGCACGATGCACCCCGCCAACGAGTCCTTTCTGCAGACGGGGTTCCTGTTTTCATGCAAATGCCTTTGTTAGCGCACCGGGAACCAGGGGGACGGAACTGCAGCTGACGCGGGCTGCGCGCCGCTTTTCCGCCTTCGCTTGATTCGGCCTCAACGACTTAAACGCGCCGGGAACAAAAACGCCGGCGCCGCGGAAACCCTCAGGAGCGGCACGAGAAGCGCGGCTCCGCTGGGGTCCGCGAGAAGCGGTGCGGGCGGCCG(SEQ ID NO:10)。

[0379] MAX.chr20.2903:

[0380] CGCTCGCCCCCTTCTCCGCGCGGGCCCTCAGCTCAGCTCCCTCTTCGCTCCCCGTGTCCCCGCGAGCGGGAGGGAGGGGATGCTAGGACGCCCTGTCGGCGTCGTCGCCGCTTTCCGCCATTGTTTAGTCGTGATGCTCTCATTTTCTCTGAATCAACAATTTTCTGCTCGGCTCCGCGCCGACCGGCGAACGCGGGGCTTTTCCTCGCCCGCCTGATGACAGCAGAGCGGCGCGGAGCAGCTGGTCCGGAAGGAAGCGCCAGGCGCCTGCCCGGTCCCAGGCGTCCGCTGCCGCCCACCCACACCAGACCCCGCCCCCGCGCGTCAAGCCCCGCCCATCCATACCAAGTCCCGCCCCCACACCCTCACCCACACACCAGGCCGTCCCCACCCCGCCCCCAGAGCCCCGGGGCGCCCCGCCCGCTAGCCGCGCACGCGCAGTGAGCACGGCGACCCCCGGTGGTCGGGTGTCTCCGCAGGCCGAACACGCTGCTCGCCCAGCTGCGGATCATTACCGCCCTTTTGTTCTCCGTCGCGCGCTCGCCCCACGCTAGGAATGCAAACTGTAGGCGCCG(SEQ ID NO:11)。

[0381] MAX.chr21.5011:

[0382] TGTTTTTCCAAAAGATAATAAGCGTCAACAACAACAAAAAAATAAAAAGTCCAACTCCGCCCCAAAGCAGCATCTGGCTGGCCTGCGAGATGCCCACTGGGGAGGCGAGTCCGCAGCTTAGGACTCAAGCCCGGGGTCGGAAGCTATTGCCGAAATCCGAAACGCAGCGCTCGCAGCTGCAGTGACGCGACCTGCTCATAAGTCCCCGTGCTCACAGCATCCCGGCAACTTACGAGCTAGTGCTTCCGGGTCACCCCGGCCCAGGAAGGCGCACGCGCGAAGCATAGCGAGCTTCACTCCGCACTCTTAGGCTGCGTGTGAGGCCTGCGAGTGCTCGGGAGCTGCCGCGGTCACAAGAGAAAGCCTAGCTGTCAATGACAGCCCCAGAGCATCTGGGCGCCTTGCGATACCCGGGTGTCTGTAGGCAGCCAGGAGACACTTCCAAGCTGATCTGGAATCTTTCCTCGCCCAGCTCTGTCCCTCGCAGGGATGGCAAAGGACATTACGACCTACATCCCTTCCCGGATCTGATGGCTTCAGATTGGCAGATTGTGTTAAAGTGGAAGGCTCGTGGTGCCCCTTTGCTGAGTTTTTATGGACTTAGTTTTCCCAAGTAGTTCTAATTATCG(SEQ ID NO:12)。

[0383] MAX.chr22.5665:

[0384] CGGCTGTCTTTGTCTCCCGCGAGGCAACTCTGACTCAGGCTCCAGCTGCCCGTGGGAGGGAGGGGGCGCCCGGGCTCCTGAGGTCGCCAGGGAGCGGCGGGACTGGGAGGCTCCAAAGCCCTCAGTGTACGTGCGAATCCGGAGCGGACACCGAGACCTTAGCGCGGGAACCAAGAGAGGACAGAGCTCCACGGAGGCCACAGCGCGTGCACGGGGACAGGTGCGCCCTCCCCGGCAGCCCCCCTGCTCCTCGGTCACAGTTCTGTGCGGAGGCGTCTTGCGCCCTCCCCCCTGAGCCTCGCCCTTGAGTCGGGGCCGTGGGCCGCATCCAGGCCCCCAGGGCTCGGGATGCGCGTGAGGACCCGGACTCCCGAGGGCGCAGAGGTCGGGAGCCCGAAGCAGGCGCCCTTGGCCTTGGTCCCGCCCCTTATCCGGTCCCAAGCTTTTTCCTCGCCCCTTGGCCTTGACTCCACCCCTTAGGCATGCCGCTGGCCCCGCCCCTTTCCGGCCACCTTGAGGCTTGGGGGTCCCTCAGCCCCGCCTCTCTTCTTGACCCCGCCCCTTGGCAGCACCCCCTACCCCCGCCCCACGTCCAAATCTCCCGGGGCCGGTGGTGGCCGGGGCTGACGGCGGAAGCCGCGCAGAGACTCGCTTGCCCCGAAGTCGCTGGATTCGGGCCTGGATCCCAGATTATCCGCAGCCTAGGGGAGTGGAGAGATGCCCAAGGTTCCTCTGGGTCCCGGGACCCCAGTAGCGTCCCTCCCCCCGTCCCCCACGCCAACCACTGAGCGCCCTTCGGAGTCCCGGGAGGAAAGCGTAGGGGCGGGGAACTCTGGCATCTCTCTCCTCCCGGTTGCTCCCCGACTCTGCCCCGCTATTCCGCTATTTGGGGCAGTCGTTTCTACCG(SEQ ID NO:13)。

[0385] MAX.chr3.6408:

[0386] CGCCGACCCCAGACCCAGTCCTAGTCCGGCCAGAGGAGGCCGTTTACGAGCCCACACCCGTAGGTGGCGCCACAGCCGGAGAATTGGCTTTGGTTCTGTTGGAGCCGCGCCGCCTTTAAATTAGCCCCACGCATGCGCGACTTTTCTAGCCCGAGCCCGCCGTCTGCGCCTGCGATTTCGCCCATACTCCCCGGTGCCCGCCTCGTGACGTGCCGCAGTGTTACGAAGGGACACCAGGGCGCAGGCGCAGCTCGCTCCTCAGGCCTGCGAGAGGCCCGCCGGCCCAGCAGAGGGCGCCCACCAATCTGCACGCGGGCCCAGCGAGTTATCTTGATTTCGGCCAAGCTTTCTGACTGCTCCAAAAAACGAAGAAAAAGATTCAGGGAGAGTAAGAGGATGAAGAGAGCTGGTGAAGCAGCTGACCAAATGGCCCGAGGTGGTATGCAGCCGCGGTAAAGCAGGGCCCCTCCGTGAGGCACAGCCGCCCGGGGGTTCCCTAGGGGAAGCAGGGGCTGCGGCAGACGCCTCTCGGGCAGGTCAGGGTATGCACCCTCCCGCAGGGGCTCCCAAGGCCGGGCGTGCGTGAGGCCAGGTCCACGGGCACACCACTGTGAACACTGATTAAACGTGGCCTCCACGGCTTCCAACCCCCAGGACAGGACCAACCCTCTGCCCCCGGCTCAGGCCAGAGCTCGGCGAGACCGTCG(SEQ ID NO:14)。

[0387] MAX.chr5.3588:

[0388] CGCGTCCGGAGGAAGGCTCACCCGGAGGCCGCCTGCAGGCGGCCAGGTGCCAGCCACTGCGGGCCTCTGGGGCCGAAGCCGGCGGATGGTGAGACGCTGGTTGGTCTGCAACACTGCCCAGACCCCGGGCACTCATGTCTAGAAAAAAGCTGACTCGTGACACCAAAGGAGCTCTTTCAAGCTTCCTGCACGCTCTTAGCGCCAGAGCACCCCAGCCGTCCTGGGAGCCCCCGAAGCCAAGCATATTCGAACTCCGAATCCGCTCGATCGCCGGGGACCTGCCATCTGGGTTCGGTTCCCCAAGGTCGCTGCCGACCTTAGACCGCGGGGGTGTGGGGCGCCGGGGAAGGAGACAGAAGGACAGGCGCCGCCCAGGGCCGCGGGGACACTTGGGGCTGCGTCCTGGGTGGGCGCGATGCTCCCCCAGAACGACTGGAGATGGAGAGTGTCGGGGAGGGAAACGGGACCCACGAATTCAGGGCGCTGAGTCGGCGGAATGCGCCCTGACTCCCCCTGGCCGAGAGCCGGCTCAGAATGAAAGAGCGCGGAGTGGGAGGTCTGGGAAATGGCAGTATTTGTATTAGGGAGAGAAGGAAACAGGAGTGGGAGCCGCACGGCTTGGGGAACGCGGGAGATCGCGGATTGCGGGGATAGCGCAGCGCGGCTGCCCGGGGCTGCTGGGAGGGGCCGGACGAGGCCAGGGCGAGCGGGGTAACTGCGGCCGGCCGGACGGCGGCGGTAACCGGCTGCACCGAGGTGGTTCCACCACCGCGCTGGGCGCTTGCGGTTCGTCTGCTCCAACGAAAGCCGCGTCCCACGCTCCCTGCCGCCGCGTGGTTTTGCCTCCTCAGAGGGGCAGCGGCGACCCAGGGGCTGGCG(SEQ ID NO:15)。

[0389] MAX.chr8.5938:

[0390] CGCAGCACCGGGTGTTCCCTCCTAGCCTGGTCGCTCGGGGGGAGCGTTGGTTGGCGGGGTGCAGGTCTGGTGCTCGCTCAGGTGGGCCAGGCACCCGCGCGCCAGGTGAGGCGGGCGGGGGAACACACGCCCCTGGCCCCTGCGCCGCCGTCACGGCCGCCCACCACCCGAGGGCGGGGGTCCTGGTGGGGTGTCGATTCCGCCTCCCCGCCCACAGGCACTGGGCCCCGGGCGGCCACCGGGGTGCGGGGCTCCCAGCGTCTCGGGCTCCCACTGCTTCAGGCCTGTCCAGGGGCGGGGAGCGTCTCTGTGGCCGCGGCGGGATTGCGGCGCGGTGGCCGGGCGTCCCCTGCAGGAAGCTGTTCTCGCTCGCTGCCTCCCCCACCTGGGAGGGAAGCGCCTGGATTTTGGGTCCCGCCGCCCTCCGCGCCCTGGGCCTCCACCTGTGTTCCCAAAGCCCAGCCACGAGTCTGGGGGTGCCGGGCGTGCCGTGGTGGGCGGAGGCTTCCACAGCCCCTCCCTGCCAGGGACGGCGGGGCGGGACATGGCGGGGCCGCACGCACCGGGTGGACGACAGGGGATGCCGCGGGCTCGCGTCAGCCAGGGCG(SEQ ID NO:16)。

[0391] MAX.chr9.4007:

[0392]

[0393] MAX.chr9.2025:

[0394] TGATGTACGCCCTGGTGGACAAAAGCTGCTAGTGTCAGCTTGATTTGCAAGATCAACATTCATGAGTTTCACCGCTTAGAAAGGGGCATTATCTGCAAACCGGAGACTGAATGGAAGCCATAAACAAGTGATTTCACACTACCAAGCAGGAAGAATATTCTACCTCCTCAATTATTCTGAACAGCATGTTTGGCCCCTTCCAGGTTCCCACCGCTAGCGAGCCCTCCACCCCTGGTGTGTGCAAACGGTGGACCTTTCGGCGCCTAAGAAACCGGGTGCTGAGCCCGGGAGCAGCGCCTGCTTTTCTTCCCAAGATCCACTCCGGGTTTTGCCTAGCGCTGCTCCGGGAACCCATTCCAGACGCAGGTAACGCCAGGCAACGTTTTCCTTCTCACCCGCCCAAGGCCAGCCCCGAGCCGCCGGGGTTCCAGGCCCAACACAGCACAGATGCACGTTTCAAAATGTGCTCGAATATGCAGCCTGCATCAAAGGCGTTGGGAGGCTCTTTCATCCTCTCAGCTGCCTAAGAAGGGACATGCTCCCAGCTACCCTCATTTGTGGCTGGGTTTACTCTGAAATGAAGATGTACCTCTGGATGCAAAAAGAAAGGGTGGAAGGTTTTTTTCCCCCTAC(SEQ ID NO:18)。

[0395] MAX.chr1.2533:

[0396]

[0397] MAX.chr13.3357:

[0398] AGGGTTGACCCCAGTACCTGACTTCTCCGGGAGCTGTCAGCTCTCCTCTGTTCTTCGGGCTTGGCGCGCTCCTTTCATAATGGACAGACACCAGTGGCCTTCAAAAGGTCTGGGGTGGGGGAACGGAGGAAGTGGCCTTGGGTGCAGAGGAAGAGCAGAGCTCCTGCCAAAGCTGAACGCAGTTAGCCCTACCCAAGTGCGCGCTGGCTCGGCATATGCGCTCCAGAGCCGGCAGGACAGCCCGGCCCTGCTCACCCCGAGGAGAAATCCAACAGCGCAGCCTCCTGCACCTCCTTGCCCCAGAGACCGTCCGAGCTGGAGCCACAAGCCCTCCATTCCTCTTGGAATCTTCAACCCCAAGGTAAGGTAAGTTCACCGAGCACCGCCCAGCGATGCGCAGGATCCGGGGGGGATCACGCGCGGCGACCCTACCGAGCGCTCCGTGCGCGCCCCCATCTCTCGGATCGTGTTCCTGGCTCTGTCGAAGCTGCTGAGTCCCGCGATTCGGGAAATCCGGCACTTGTTTCTCACCCTACACCATCACGTGGAAATCATTGAAAATGGGAACCCTGGTGGAGTATCTGGGAGAGCACGCTTGTGCCGAGGGGCCTGAGCTATGGGACTTCCTCCAGGTCCCTCTGTTTCCTGCCGGCGTAGGGGACTCGTAGTGTCGGATCGCATAGTGCCAAAAAATAGTGCATGGGAAACAAACAA(SEQ ID NO:20)。

[0399] MAX.chr14.2093:

[0400] GTAGAGACGGTGTTTCACCATGTTGGCCAGGATGGTCTCGAACTCCTGACCTCGTGATCTGCCCGCCTCGGTCTCCCAAAGTGCTGGGATTACAGGCGTGAGCCACTGCGCCCAGCCCCAAAATTGGGAATTATTTCAAAATAAAAAGCTGGATAAATGCATACACACAAGGCAGTATCGCGTATTTTCCACGAGTGCCTGTGCAGGCAGGTAAGGATTTAGGAAAGGTCTGGAAGGATGTGCAAAATGTTCCGCCTGCGAAGGTTCCGCGGTGGCGGGGACACTGCTCCGGCTCCGCTCCCGCCCGCCCGAGCGCTCGGATGGGGCCGCCTCTGCACTGCGTGGCCACAGGCGCGGCCCGGCTGCCCACGGGCGCCCTTTGCAGCTGCTGCCCCCTGGCGGCCGCGGGCGGCTACTAGCGGGAAAGCGAAACCCGCCCGGTCCATTCAAGCCCCGCTGCCTGGCGCCCTCTAGGGTCGTTCTTGGGAACGGGCGGACCTTTCGTCAACACTTTGCCTGCAAGATCCCCCATTGGGGGAACCGAGGAGGAAGTTAAAGGAAGATGTGTGTTTTTGAGCGCTGCTTTGTGCCAGGCTCATCTTAGGTGTGGGACGTGTACTATCTGAATTAATACCCCACCAGGCCTGTGGGACAGTCACTGTCACCATTCGCAAATTATGGATGAAGAAAGGAGGTACCAAGTGGTGGTATCACCTGTCCATAGTGAGCTGTCCCTCAGGAGGGTGGCCGCCCCAC(SEQ ID NO:21)。

[0401] MAX.chr17.2455:

[0402] CGTTAACAATGTCGCGTACACGCCCGAACCGGAGGAACCCCATTCCACGCTCCTTCTGGAACCGAATTCACCTCTGAGGCTTTGGGGCTTCAGAGCCGGAGCCGCTTGGGCAAAACCAGCAGAACAGCGAGAGGGAACGGGCTGGTCTAGCCCTGCCCTGAGCATTTCTACTGAGACCCCCGGTCCTGCTTCTTCCAGCCTCTGCTGGATTTCTCTCCGACCCCTCTGGAGCGAAGCCCTTTGGCCCTGCGTTGCATGCGGCACGGTGCGGGTTCGGGCTCTGCGCTGGAGCCGGGATGCCCTCCGGCGGAGGGTGCGCGTAGGCGGCGCCTGGGCGTGAGCCCCGCCTGCAAGGCTCAGCGTCGGGGAAGCACTTTTCTCGTCGACCCGGGGTCTTTTTCCGCCAAGGAGCTCGGGGCTCAAGAACTCGGGACTGGGCTGTGGGCGGGGCATGGTTTTCCTCTCTGGGCGTCCTAATCTCCAATTTCAGGCAAATTCGCTAGGAAGAACCTTCCCGAGCGCG(SEQ ID NO:22)。

[0403] MAX.chr18.4390:

[0404]

[0405] MAX.chr19.2732:

[0406] CTGTTTCAAAACTGTGCCATCTGGATGTTGCAGTATACCCATTTTGTCCTTCCCATACCTGTGCCCGGCCACCTGATGCAAGATGGGCACACAGCCACTGAGGAAGCGGAGTCTGCCGCCTGCCGGCTGCAGGGTGCCCTTAGGGGTGGCCTCGATCGCCGGTGGGGTCCGCATTTCTGGGGGACCCGGCGCCTCGACCCGGAGCGGGGATGGTGGCTCTCTTGCCATAACGGAGAACAGAAGCGGTAGGGTCAGCAAGAGCAGGAAAAGAAAAATAGGGGGAGGGAGGGGGCGCCGGAGAACCCAGGGGTCGCTCAGGCTCGGGCGCGAGGAGGCCCGGGGGTTCCCGCGGCTGGTGCCCGCTGAGGTGAGGGGAGGGGGCCCATGACGCCGCGGCGGCGCGGGCACTCCCTCTGCCCAACTCTCGGCTGAGCGCGGCTCCCGGCTCAGGCCCCTCTGCCGCCGCAGCCGCGGGCCCAGTAGACACAACCCAGCCGAGGAGCAGCAGCAGCAGCAGCGGCGCCCCGCGCTCCCTGGGGCCCTCCAGAAAGTTTTTTTATGGATATCAGCAATCTAATTCTACAATTTATATGGAGAGACAAAAGACTCAGAATAACCAACACAATATTGAAGGA(SEQ ID NO:24)。

[0407] MAX.chr19.4467:

[0408] CTGTTCCTCTGTGGTGGAGGAAGGGACACGCGCTTTTTTTTCCGACCTTAGGAAGGAACAAGGGAGCCGGGGTCCCCTCCCAGCCTGGGAGCCCTGGGCACAGTCCCGGCTCATTTGTCAGAGCTATCGGAGCCGTCCTCGGGCTGGTGGGAGTTCAGGGCTCTGAAAGGTTTTCTGTCAAGGCTTGAAAGGGGGCCAGGTTTTTTTCCCCCCGGAGCCGCGCAGTCTCGGGGCTGTTGTTCTCAGCAATCGCAGGGCCTCGTGTTAGCAGGAAGCACAGCCAAGTAGGGTTTCCTGCGTGTTGGAGAGAGGAAGCTCCGTAATGTTCTGGGAGGCGATGGTTAAAAATAACTCCGGTATATAAAGACAGCGGAGGGTCCCCTTGTTCGCTCACTCGGGCGCCGGCCGGCTGGACGCAGGGCCGAGCAGGTGGTTTGGGGCCTCGGGAAGGCCAAACCCCCGCCTCTGGGCCCCTGGCTGGGGAAGACACCAGCCAAGTTCAGAGCCCCAAGTCGGCCTCACTTCCACAACTCAGCGTCAGGGACACCGTGGGCGTTTCTGTTTCAAAACGCTTTTCTCCAGCAAAGAACGTAACCTCAAGCTGCTGTCAGGGTAGAGGAATCCCTGCCCCCCGCC(SEQ IDNO:25)。

[0409] MAX.chr2.0490:

[0410] CGAAGGATGCGGCGCGTGGAAGGAGATGCGCTGACTTGTTCCAACCCATAACCTTTCGCTCGGGTCCCCATGTGCGGGCAGAAGAAGTCAGAGCGGAACAGCCTAGTGCACTGGCAGGGCTCATTGTCTGGGAAGACACCGAGGTCTAGGCAGCTGGGACTGCGGAGTGGAGGCAAGGCCGGAGGCGGCCGGCGGCTTTGTGGAAGTTTCGCGCCGCCAGGCCCTGCGCGCCGCACGGGGCGGTGGAGTTCTTGGGCAGCCCCCGGCGCTTGGCCCACGCCTCCGCTTCCCGCGTGTGGGAAACTCGAGCACCCTACAGGCACCAGGGTAAACTGCCTGTGCCTGGCCCGGTGAGGGTCGCTCCCCCAGGCCCCGTCTCCGCCCGAGGACTGCAGGCCTAGGCCTGCGGGGAGATCCTGAGACCGCGGTGTGCGGGCGCCGGCAGCAGGGCAAGGCAGGGACTGTGCCCAGTCCGCCCGCCAAGGAGATCGCACGCCGGCTTCGCTTCTGAAGCTGCAGACGGAGGCCGTGGTGAGCCTTAGAAAGATCCCGGGACAAAGGCG(SEQ ID NO:26)。

[0411] MAX.chr2.8148:

[0412] CGCCGGGGCGCAAGGCCGAGTCATCCCAGGCGTCCGTGGGCCGTGATTCCCACTCACGCCGGGGGCCCAGGCAGGCAGAGAAGAGTTAATGAGCGCGCAAGTGCAGGCGGTCACTCCTGGGCCTGAAACTCCCGCGCTGTGCATTCAGGGCCCTCGTGGCTCTCAGAGGCGCGTCCCAGGGGCGCACACTGCACCTTGGGCTGGGCAGCTCCGCCGGGTTGTGGCGAGCGGATGAGGGAAGGACGCAGAAACCAGGGCGGAGGAGCCGCGAGGGGCAGGACGAGGCTGCATGGGCCAGCGAGGGGGTCGACACCGAGCCAGAGTGAGCGCGGGGCCTGGGGCGCAGAGCCCGCCCAGGGAGCCGGGAGACGCCGCGCAAGCTCCCCGGACAAACGCAATGACCGAGGACGCGCGGGCGAGGCCGTCCAGGGAGCCCTGGTCCCTCAGCTGCACCGGACTGAGCCGCGACCGCTCAGCACGCGCTGCTTATAAATCAGGGGTGCGCTTCCCAAGCCCCGGGTGAGGTCCCCTACGTCGGCACAGCCTTAGGAGCTGCAAAGCAGCGCGCGCCTCCGGGGCTCCTGCGCGCCCCTTGAACCCCGCCTCCCGCATCCTCCTGCAACAGCCTGGAGCTCCCTGTGCAGGACGCAGCGGGGGGCGGGGGGCGGTCTTAGGAGGCTGCGGGGCGCACTCCCACCTCCTGCCTCCCCGAGACCCCCAGCGCCTTCTCCAGGGTTTAGAGCGGAGGTGAAGGGGCCTCGTCCTGCACCGCCACTGGGCGCCTGGGCTGTTCATCATCGGTTACCGCCG(SEQ ID NO:27)。

[0413] MAX.chr2.3137:

[0414] CGTCCTGAGAACCCGAGAGAGCAGGGCCCGCTGGGACAGGCAGGGGAAGGCCTCGGGAGGGACACGACGGTCCGGCAGCAGAGCCTGCGGGGCTGGAGGAGGCGCCCTCCTCTCAGCTGCTCTTCCTGCCCCTTTCGGTGGCGAAGATGGATGGGGCCCGGGGCTTTCGGCGGGGCCCGAGGGGCCGGCGAGGCTGCGGCCCTGGAGCCCCCTGCCTGGCAGCCATTTGGGCCCCAGGGAAATATCGGCGCTTTGGCTAACCGAATTATTCTTTCGGTTTGAGCCAGCTCCCCTTTTTGAGTCAGATCCGGCGGCAGGGCCAGAAAAGCGCTTTCTGAAACCCCAGCGCGGTCCTCGGTGGGGGTGGAATGGGGTGGGGTGGGGGGCGCGGCCGCGCCGCTGGGCGCCCTCCCCGCCCTCCCCCCTCCCCACCCCCAGTCCTCCCTCCGCTGCCCGCCCCCCAAGCCCGGTGTCGCCCCCTCCGCCCCCTGCCGCATCCCCGGAGCCAGTGCCCACAGGGGCCAGGCAGCCCGCAGGGGTCGCTCACGGCTGGTGTAGGGGCTTGGTCCACCACGCTAGTACTTCGGGCACCAAAATAGAAAAAGAATAACGCTTGGAAAGAATCTGATGTTTCCG(SEQ ID NO:28)。

[0415] MAX.chr4.4210:

[0416] CGAAAACTACCCCGCGGAAACTAGCACAGTGTGCCTGGATGTCTGTGTCCCGGGACCTCGGGGAAGAGGGCCCGCACCGGTCTGCGAATTGCAAGGCCCGGCCTTCCCCAGCGACGCTCTGGTATCCGCTGTCCCCTCCCTGTACCTCCGCGACCCAGGGGACGCCCAGTGCACCAGGCCCTTCCCCGGGGTCAGCGGAGGCGCAGGGCGTTAGCCACATCAGAGGTGCAAATTTACCCCGGGCCCAGGGGAAAATGGCGACAGCGTTCGCGGCTCCACCCGGGGCGCGTGTCAGCGTTGGAGAGCCTGCCCGGCCTGCAGAGGGCGTAACAGGCACCGCTGGGGAGAGCCAAGCACCCCTGCGTCCAGGATCCGTAGCGCCGAGCTGCAGGCCCGACCTGCAGGGGGCGTGCCCGGCATGGGAAGCTCAGGCTACGTCTCCGAAGCTTGCGCTGAAAACACCAGAGGTAGGGAAAACGGGGAGAGCGTACTGTGCTGGGCTCTACCCTGGACACCCCAGTTTCATTCTCTGCGAAGCCACGCGCTGGCAGGGCTCTCGGGACGGCGATACCCAGGGATGATGGTACCCCTGGTCTCGGCGGGACCTCCCGGGAACTTGTCCTGGGGGAGGGAGCCCAACTGGCCACGTACTGGTAGCAGCAGTGGGTGGAGCGCACAAACTCCGAGGCCCGCG(SEQ ID NO:29)。

[0417] MAX.chr5.0931:

[0418] CGCCTCCTGCCTGAGGCGGGCTGGGGGGTCGTTGTCCTCGCAGCGTTAAGGCGAGTCTGGGACAGGACCCCGGCACCCCCTCCGGATCTGTGGCATCCTCCAGGACTCCGGCGCAGGACGCGCTCCAGGAGCCGCTCCTTCAGGGCCTCCGGTGCGCGCAGTCCGGGCGCCGGACGAGCTCCTTTATCAGAAAGGGCAGCCGCAGAGCCCGCGTGTGCGCGATGTGGCTGCGGGTGGGGAGCGGGCGGCGGGCCCGGGACACCGCGGCCACTGTTCTAGCCCCGCCTGGGCCGCCTGACCGCGGCTCCGCTGCGCCGCAGCCCCGCGCCCCTCTGGCTCCTGTTCCCGGGCGCGGGGAGAAGGCGGCGGGGCGCGCCTGGGCCCGCGCGGGTGCGAACGCGAGGTCTTTCCTGGGTGCTCCCAGGTCGGAGGATTCCCAGGGCGGGGGCCATCAGGGTGGCGAGGAACCGGCAGGGACCAGCCTCCGCTAGGACCGCGCTCGTGGAGCG(SEQ ID NO:30)。

[0419] MAX.chr5.9924:

[0420] CTTTGGTTTGAAACACTGGAGGTGGCCCAGGGCCGTTTTCCTCAAAGGACTGAGAATCTTGATTTGCCAAGTGCTTGGGGCCTCCGCCCAAGGTGTTTGGGGGCTGCGTGGTGAGCCGAGGCAAAGCCAGGGTACCCCGATCGTCTTCCGGGCGCATCCACCATGCGGCACCGCCCCAGCCACGGCGGCCGCGCGTGGAGACCCGGGGGCTTAACAAAGGGCTCCGCGGGGGCACGGGGGGGCGCGGCCACGTGACAGGCCCGAGCGCGACGTCGCTGTCCAGCCGCGGGGAGGGGCGGCCAGCCCGGGGGGCCGTGGGGCTTCTTGACATAGAACGTCCGGGCCTCGGGCTGGCCGCGCCGGGCCGCGCTCCGCCGGGATGAGAAGTACTTGTCTGGCTCCGCGCTGGAGAAGCCGCACCTCTCATCTCTCCGGCTCTTACTTGAAAAAGCACTTGGAAGAAACTGTGTGTGCGCTGGGAGGGCCGCGGGGTGGGCCGGGGCCGGCTGCGAGGCTGAGGGGGGCCGGCTGGTGGGTGGATGGGGAGGAGGTTGAAGAAACAGCCCCTTTCTGAGTGACAGGACCCCTTTTCAAAGGGCAAACAGAAAAAAAAAAGAAGAAGAAGAAGAAGA(SEQ ID NO:31)。

[0421] MAX.chr6.9522:

[0422] CGAGGCGAGTTAAATTCCTTTTGCCGGTGCCTGGCTGCGAGGACAAACGTCCGTACTTTCGTTCGGGAGCCACGGGCAGTCCAGGGGCTTGGGTTAGAAGCAACGGCTCTCTTCCAGGGGCTGTGATCCGGGTCGGCCAGGGAGAGCGAGGCCCCGGGGTCCTCTGTGAGGTCCCCAGCGAAGAGACGCAGCTGGGGAAGGCGCCGCCCCCGGGCCCCCTGCGCCACCCTAACCGGGCCTCTCCTTAGCAAAGTTGACAAATTCTTGAGAGTGTCAGCCCAGGGCTGCGCGTGAGGGCGCTGGGACCGGGGAGGAAAGAGCACCTGCCGCGCTCAGCCCGACTTTGAATTTGTTTGTTGTTACCGTTTTTGTTTTTCCTCCCAGTTTCCATAAACGCTTAGTATTTCGAGGCACTTTGCAGGTGTTGGCGCAGGTGATGATGGGCCTCGTTGGACTCTGCCTCCCACGCATCCTTTTGTTTTCTGCGCGCCAGCCTGTCTGACTGTGTCCTGCGGGGACCCCGAGACAGTCCGGGGTCAGGGCGTAGAGACTCATGCTTGCCACTTGACCCATCCGCAACCCGGGGACCCCCTAGCCCGTCGCGGAGCTGGAGTTTGGGCTTCCGGCTCCCAGCTCTCCGCCCTGGATACAGGAAGAGGGCGGGAGAGGTCGCGCACCCGCGCCGCTCGGCGGGGATCGCTCACAGGGGCTCCGGGGCCACCGCGAGCGCGGACTGCGGCTGCTGGCGGGCTCCTTCGTCGTCCAACGCACCCCATCCTCTCCCGCCCCGCAGTGTCCCAGGGAAGGCTTCACTGAAAACAGACGCTCGACGGAAAACTGACTCTGCAGGCCCGAGCTTTCG(SEQ ID NO:32)。

[0423] All publications and patents mentioned in the above description are incorporated herein by reference in their entirety for all purposes. Without departing from the scope and spirit of the described technology, various modifications and variations of the described compositions, methods and technical uses will be apparent to those skilled in the art. Although technology has been described in conjunction with specific exemplary embodiments, it should be understood that the claimed invention should not be unduly limited to such specific embodiments. In fact, various modifications of the described modes for implementing the present invention that are apparent to those skilled in the art of pharmacology, biochemistry, medicine or related fields are intended to fall within the scope of the following claims.

Claims

1. A method for characterizing a biological sample, the method comprising: Determining a methylation profile in at least one differentially methylated region (DMR) of the sample by treating a DNA sample obtained from a subject with or suspected of having a gynecological cancer with a reagent that modifies DNA in a methylation-specific manner.

2. The method according to claim 1, wherein the methylation profile in the at least one DMR indicates that the subject has or is suspected of having at least one of ovarian cancer (OC), cervical cancer (CC), and endometrial cancer (EC).

3. The method according to claim 1 or claim 2, wherein the at least one DMR comprises one or more CpG sites selected from the following: ADAM8, ADHFE1, AES, AGBL2, AIM1, AK5, ALKBH3, ARAP1, ARHGAP20, ASCL2, BCAT1, BEGAIN, BEND4, BMP6, C12orf68, C13orf18, C14orf169, C14orf169, C18orf18, C1orf61, C20orf195, C4orf31, C5orf52, C6orf147, C7orf51, CD14, CELF2, CHCHD5, CHMP2A, CHST10, CLIC6, CLIP4, COL13A1, COL19A1, COL6A2, COPZ2, CREB3L1, CXCL2, CXXC5, CYTH2, DAB2IP, DGKZ, DLGAP3, DNASE2, DSCAML1, EBF1, EDARADD, EGR2, EIF5A2, ELMO1, ELMOD1, ELOVL4, EME2, EML6, EPSTI1, FADS2, FAM109B, FAM126A, FAM174B, FGF18, FKBP11, FLI1, FLOT1, FOXD3, FYN, GAL3ST2, GALR3, GAS7, GATA2, GLT25D2, GNB2, HDAC7, HIC1, HLA-F, HNRNPF, HPDL, HS3ST4, HSPA1A, IDUA, IGSF9B, IL12RB2, IRAK3, IRF7, IRF8, ITPKA, KCNA2, KCNC3, KCNC3, KCNC4, KCNH8, KDM2B, LBX2, LCMT2, LOC100129726, LOC100287216, LOC255130, LOC339290, LOC729678, LPPR3, LRRC41, LRRC8D, LTBP2, LYPLAL1, MAST4, MAX.chr1.2152, HIVEP3, GRAMD1B, MAX.chr11.0394, MAX.chr11.3750, FAT3, SLC16A7, MTUS2, LINC02323, MAX.chr14.7696, MCTP2, LOC107984974, TRIM80P, MAX.chr19.5552, ZNF433-AS1, ZNF254, MAX.chr19.0548, B3GALT1, MAX.chr2.8918, MAX.chr2.4778, MAX.chr20.3853, MAX.chr20.2903, MAX.chr21.5011, DSCR9, MAX.chr22.5665,. MAX.chr3.6408, LINC02028, LINC02084, MAX.chr5.3588, CTD-2532K18.1, HS3ST5, ARHGAP18, GRM4, LINC01004, MAX.chr8.5938, MAX.chr9.4007, MAX.chr9.2025, TRPM3, MED12L, MIAT, MLH1, MLH1, MMP16, MRPS21, MSI1, MT1E, MX1, MYC, MYH10, MYO15B, N4BP2L1, NBR1, NDRG2, NEGR1, NEU1, NOL3, NR3C1, NR3C1, NRP2, NTN1, NTNG1, PAPL, PAQR9, PDE10A, PDE3B, PDE4A, PDXK, PER1, PISD, PLEC, PLIN2, PLXND1, PPM1E, PPP1R9A, PPP2R5C, PRDM5, PTP4A3, PYCARD, RAB3C, RAI1, RARG, RASA3, RPRM, RREB1, S100A6, SAMD5, SBNO2, SDC2, SDK2, SELM, SERP2, SFMBT2, SHF, SHH, SLC16A11, SLC16A5, SLC25A22, SLCO3A1, SMTN, SPDYA, SPINK2, SPOCK2, SPON1, SQSTM1, ST8SIA1, TAF4B, TAF7, TEAD3, TERC, TIAM1, TLE4, TMEM101, TMEM106A, TRIM9, TRPC3, TSC22D4, TSPAN2, TSPAN5, TTC14, UBB, UBB, UST, VAMP5, VIM, VSTM2B, ZBTB7B, ZEB2, ZFP3, ZFP36L2, ZIC2, ZMIZ1, ZNF14, ZNF211, ZNF280B, ZNF302, ZNF382, ZNF480, ZNF483, ZNF491, ZNF569, ZNF610, ZNF702P, ZNF709, ZNF773, ZNF845, ZNF91, CDH4, LRRC34, MAX.chr10.4460, NBPF24, OBSCN, SEPT9, ZNF323, ZNF506, and / or ZNF90.

4. The method according to claim 1 or claim 2, wherein the at least one DMR comprises one or more of the following CpG sites: ACSF2, AJAP1, ARL10, ARL5C, ASCL4, ATP6V1B1, BARHL1, BEND4, C17orf64, C1QL3, C2orf55, C4orf48, CA3, CDO1, CELF2, CLEC14A, CSD AP1, CYTH2, DLGAP1, DSCR6, EPS8L1, EPS8L1, FAIM2, FG F12, GATA2, HIST1H2BE, IRF4, IRX4, ITGA5, KCNA1, LECT 1, LHX1, LOC440925, LPHN1, LINC02767, MAX.chr1.2533, SO X1-OT, MAX.chr13.3357, MAX.chr14.2093, MAX.chr17.2455, MA X.chr18.4390, MAX.chr19.2732, MAX.chr19.4467, PANTR1, MAX.chr2.0490, MAX.chr2.8148, MAX.chr2.3137, RIPOR3, SCRG1, MAX.chr4.4210, HMX1, CTC-359M8.1, MAX.chr5.0931, MAX.chr5.9924, LIN28B, MAX.chr6.9522, TTLL2, RNA5SP243, DLGAP2, MEX3B, MNX1, NEFL, NETO1, PAX2, PDX1, psiTPTE22, RA SGEF1A, SALL3, SALL3, SEZ6L2, SHANK2, SHANK3, SKI, SLC35D3, SORCS3, SORCS3, SOX1, SQSTM1, TBXT, TCERG1L, TERT, TNFSF11, TUBB6, ULBP1, VAC14, VWC2, WDR69, ZBTB16, ZNF132, ZSCAN12, ZSCAN23, KRT86, CYP26C1, GYPC, DIDO1, EEF1A2, EMX2OS, GDF7, JSRP1, SMPD5, MDFI, MPZ and / or VILL.

5. The method according to claim 1 or claim 2, wherein the at least one DMR comprises one or more CpG sites among the following: AIM1, FLOT1, GAL3ST2, LRRC41, LYPLAL1, MAX.chr11.3750, PISD, RAI1, ZIC2, ZMIZ1, CDH4, ZNF506, ZNF323, OBSCN, ZNF90, and / or SEPT9; and wherein the subject has or is suspected of having OC.

6. The method according to claim 5, wherein the at least one DMR comprises one or more CpG sites among the following: AIM1, FLOT1, GAL3ST2, LYPLAL1, and / or OBSCN; and wherein the subject has or is suspected of having serous OC.

7. The method according to claim 5, wherein the at least one DMR comprises one or more CpG sites among the following: LRRC41, PISD, ZIC2, OBSCN, and / or SEPT9; and wherein the subject has or is suspected of having clear cell OC.

8. The method according to claim 5, wherein the at least one DMR comprises one or more CpG sites in MAX.chr11.3750; and wherein the subject has or is suspected of having endometrioid OC.

9. The method according to claim 5, wherein the at least one DMR comprises one or more CpG sites in RAI1 and / or ZMIZ1; and wherein the subject has or is suspected of having mucinous OC.

10. The method according to any one of claims 5 to 9, wherein determining the methylation profile of one or more CpG sites in AIM1, FLOT1, GAL3ST2, LRRC41, LYPLAL1, MAX.chr11.3750, PISD, RAI1, ZIC2, ZMIZ1, CDH4, ZNF506, ZNF323, OBSCN, ZNF90, and / or SEPT9 comprises comparing the methylation profile with the corresponding region of a control DNA sample obtained from a subject who has never had OC.

11. The method according to claim 1 or claim 2, wherein the at least one DMR comprises one or more CpG sites among the following: AK5, ELMOD1, RABC3, TRPC3, ZNF480, ZNF491, ZNF610, ZNF91, and / or NBPF24; and wherein the subject has or is suspected of having CC.

12. The method according to claim 11, wherein the at least one DMR comprises one or more CpG sites among the following: AK5, ELMOD1, TRPC3, and / or ZNF480; and wherein the subject has or is suspected of having adenocarcinoma CC.

13. The method according to claim 11, wherein the at least one DMR comprises one or more CpG sites among the following: ZNF491, ZNF610, and / or ZNF91; and wherein the subject has or is suspected of having squamous cell CC.

14. The method according to any one of claims 11 to 13, wherein determining the methylation profile of one or more CpG sites among AK5, ELMOD1, RABC3, TRPC3, ZNF480, ZNF491, ZNF610, ZNF91, and / or NBPF24 comprises comparing the methylation profile with a corresponding region of a control DNA sample obtained from a subject who has never had CC.

15. The method according to claim 1 or claim 2, wherein the at least one DMR comprises one or more CpG sites among the following: c18orf18, FKBP11, MLH1, NR3C1, and / or TERC; and wherein the subject has or is suspected of having EC.

16. The method according to claim 15, wherein the at least one DMR comprises one or more CpG sites among MLH1 and / or SEPT9; and wherein the subject has or is suspected of having clear cell EC.

17. The method according to claim 15, wherein the at least one DMR comprises one or more CpG sites among NR3C1; and wherein the subject has or is suspected of having endometrioid EC.

18. The method according to any one of claims 15 to 17, wherein determining the methylation profile of one or more CpG sites among c18orf18, FKBP11, MLH1, NR3C1, and / or TERC comprises comparing the methylation profile with a corresponding region of a control DNA sample obtained from a subject who has never had EC.

19. The method according to claim 1 or claim 2, wherein the at least one DMR comprises one or more CpG sites among CDO1 and / or DLGAP1; and wherein the subject has or is suspected of having CC, OC, or EC.

20. The method according to claim 19, wherein determining the methylation profile of at least one CpG site among CDO1 and / or DLGAP1 comprises comparing the methylation profile with a corresponding region of a control DNA sample obtained from a subject who has never had CC, OC, or EC.

21. The method according to claim 20, wherein the method further comprises determining the methylation profile of one or more CpG sites among AIM1, FLOT1, GAL3ST2, LRRC41, LYPLAL1, MAX.chr11.3750, PISD, RAI1, ZIC2, and / or ZMIZ1.

22. The method according to claim 20, wherein the method further comprises determining the methylation profile of one or more CpG sites in AK5, ELMOD1, RABC3, TRPC3, ZNF480, ZNF491, ZNF610, and / or ZNF91.

23. The method according to claim 20, wherein the method further comprises determining the methylation profile of one or more CpG sites in c18orf18, FKBP11, MLH1, NR3C1, and / or TERC.

24. The method according to claim 1 or claim 2, wherein the at least one DMR comprises one or more CpG sites in NBPF24, and wherein the subject has or is suspected of having CC.

25. The method according to claim 24, wherein determining the methylation profile of the one or more CpG sites in NBPF24 comprises comparing the methylation profile with a corresponding region of a control DNA sample obtained from a subject who has never had CC.

26. The method according to claim 1 or claim 2, wherein the at least one DMR comprises one or more CpG sites in the following: CDH4, NBPF24, MAX.chr10.4460, ZNF506, ZNF323, OBSCN, ZNF90, LRRC34, SFMBT2, LINC02323, CYTH2, LRRC8D, LYPLAL1, LRRC41, and / or SEPT9, and wherein the subject has or is suspected of having EC.

27. The method according to claim 26, wherein determining the methylation profile of the one or more CpG sites in CDH4, NBPF24, MAX.chr10.4460, ZNF506, ZNF323, OBSCN, ZNF90, LRRC34, SFMBT2, LINC02323, CYTH2, LRRC8D, LYPLAL1, LRRC41, and / or SEPT9 comprises comparing the methylation profile with a corresponding region of a control DNA sample obtained from a subject who has never had EC.

28. The method according to claim 1 or claim 2, wherein the at least one DMR comprises one or more CpG sites in the following: CDH4, ZNF506, ZNF323, OBSCN, ZNF90, SFMBT2, LINC02323, CYTH2, LRRC8D, LYPLAL1, LRRC41, and / or SEPT9, and wherein the subject has or is suspected of having OC.

29. The method according to claim 28, wherein determining the methylation profile of the one or more CpG sites in CDH4, ZNF506, ZNF323, OBSCN, ZNF90, SFMBT2, LINC02323, CYTH2, LRRC8D, LYPLAL1, LRRC41, and / or SEPT9 comprises comparing the methylation profile with a corresponding region of a control DNA sample obtained from a subject who has never had OC.

30. The method according to claim 1 or claim 2, wherein the at least one DMR comprises one or more CpG sites among the following: KRT86, EMX2OS, JSRP1, DIDO1, MPZ, VILL, SMPD5, GDF7, MDFI, c17orf64, GATA2, SQSTM1, and / or EEF1A2; and wherein the subject has or is suspected of having CC, OC, or EC.

31. The method according to claim 30, wherein determining the methylation profile of the one or more CpG sites in KRT86, EMX2OS, JSRP1, DIDO1, MPZ, VILL, SMPD5, GDF7, MDFI, c17orf64, GATA2, SQSTM1, and / or EEF1A2 comprises comparing the methylation profile with a corresponding region of a control DNA sample obtained from a subject who has never had CC, OC, or EC.

32. The method according to any one of claims 1 to 31, wherein the at least one DMR is associated with an area under the ROC curve (AUC) of greater than or equal to 0.8, and wherein the ROC curve differentiates subjects who have or are suspected of having OC, CC, or EC from control samples.

33. The method according to any one of claims 1 to 32, wherein the biological sample is selected from tissue samples, blood samples, plasma samples, serum samples, whole blood samples, secretion samples, organ secretion samples, cerebrospinal fluid (CSF) samples, saliva samples, urine samples, and fecal samples.

34. The method according to claim 33, wherein the tissue sample is a gynecological tissue sample.

35. The method according to claim 34, wherein the gynecological tissue sample comprises one or more of vaginal tissue, vaginal cells, cervical tissue, cervical cells, endometrial tissue, endometrial cells, ovarian tissue, and ovarian cells.

36. The method according to claim 35, wherein the tissue sample is an ovarian tissue sample, an endometrial tissue sample, or a cervical tissue sample.

37. The method according to claim 35, wherein the secretion sample is a gynecological secretion sample.

38. The method according to any one of claims 1 to 37, wherein the subject is human.

39. The method according to any one of claims 1 to 38, wherein the biological sample is obtained from the subject, and wherein the method further comprises extracting the DNA sample from the biological sample.

40. The method according to any one of claims 1 to 39, wherein the biological sample is collected using a collection device having an absorbent member capable of collecting the biological sample upon contact.

41. The method according to claim 40, wherein the absorbent member is a sponge configured to be inserted into the orifice.

42. The method according to claim 40, wherein the collection device is selected from a tampon, an irrigator that releases a liquid into the vagina and recollects the fluid, a cervical brush, a Fournier cervical self-sampling device, and a swab.

43. The method according to any one of claims 1 to 42, wherein the reagent for modifying DNA in a methylation-specific manner is a borane reducing agent.

44. The method according to any one of claims 1 to 42, wherein the reagent for modifying DNA in a methylation-specific manner comprises one or more of a methylation-sensitive restriction enzyme, a methylation-dependent restriction enzyme, and a bisulfite reagent.

45. The method according to any one of claims 1 to 44, wherein determining the methylation profile of at least one DMR comprises amplifying at least a portion of the DMR using a set of primers.

46. The method according to any one of claims 1 to 45, wherein determining the methylation profile of at least one DMR comprises performing at least one of methylation-specific PCR, quantitative methylation-specific PCR, methylation-specific DNA restriction enzyme analysis, quantitative bisulfite pyrosequencing, flap endonuclease assay, PCR-flap assay, and bisulfite genomic sequencing PCR.

47. The method according to any one of claims 1 to 46, wherein determining the methylation profile of at least one DMR comprises determining the presence or absence of methylation at a CpG site.

48. A method for identifying gynecological cancer, the method comprising: determining the methylation profile in at least one differentially methylated region (DMR) of a DNA sample obtained from a subject having or suspected of having gynecological cancer by treating the DNA sample with a reagent for modifying DNA in a methylation-specific manner; wherein the at least one DMR comprises one or more CpG sites selected from AIM1, FLOT1, GAL3ST2, LRRC41, LYPLAL1, MAX.chr11.3750, PISD, RAI1, ZIC2, and / or ZMIZ1; and wherein the methylation profile indicates that the subject has ovarian cancer.

49. A method for identifying gynecological cancer, the method comprising: determining the methylation profile in at least one differentially methylated region (DMR) of a DNA sample obtained from a subject having or suspected of having gynecological cancer by treating the DNA sample with a reagent for modifying DNA in a methylation-specific manner; wherein the at least one DMR comprises one or more CpG sites selected from AK5, ELMOD1, RABC3, TRPC3, ZNF480, ZNF491, ZNF610, and / or ZNF91; and wherein the methylation profile indicates that the subject has cervical cancer.

50. A method for identifying gynecological cancer, the method comprising: Determining a methylation profile in at least one differentially methylated region (DMR) of a DNA sample obtained from a subject having or suspected of having gynecological cancer by treating the DNA sample with a reagent that modifies DNA in a methylation-specific manner; Wherein the at least one DMR comprises one or more CpG sites among the following: c18orf18, FKBP11, MLH1, NR3C1, and / or TERC; and wherein the methylation profile indicates that the subject has endometrial cancer.

51. A method for identifying gynecological cancer, the method comprising: Determining a methylation profile in at least one differentially methylated region (DMR) of a DNA sample obtained from a subject having or suspected of having gynecological cancer by treating the DNA sample with a reagent that modifies DNA in a methylation-specific manner; Wherein the at least one DMR comprises one or more CpG sites in CDO1 and / or DLGAP1; and wherein the methylation profile indicates that the subject has ovarian cancer, cervical cancer, or endometrial cancer.

52. A method for identifying gynecological cancer, the method comprising: Determining a methylation profile in at least one differentially methylated region (DMR) of a DNA sample obtained from a subject having or suspected of having gynecological cancer by treating the DNA sample with a reagent that modifies DNA in a methylation-specific manner; Wherein the at least one DMR comprises one or more CpG sites in NBPF24, and wherein the methylation profile indicates that the subject has cervical cancer.

53. A method for identifying gynecological cancer, the method comprising: Determining a methylation profile in at least one differentially methylated region (DMR) of a DNA sample obtained from a subject having or suspected of having gynecological cancer by treating the DNA sample with a reagent that modifies DNA in a methylation-specific manner; Wherein the at least one DMR comprises one or more CpG sites among the following: CDH4, NBPF24, MAX.chr10.4460, ZNF506, ZNF323, OBSCN, ZNF90, LRRC34, SFMBT2, LINC02323, CYTH2, LRRC8D, LYPLAL1, LRRC41, and / or SEPT9; and wherein the methylation profile indicates that the subject has endometrial cancer.

54. A method for identifying gynecological cancer, the method comprising: Determining a methylation profile in at least one differentially methylated region (DMR) of a DNA sample obtained from a subject having or suspected of having gynecological cancer by treating the DNA sample with a reagent that modifies DNA in a methylation-specific manner; wherein the at least one DMR comprises one or more CpG sites among the following: CDH4, ZNF506, ZNF323, OBSCN, ZNF90, SFMBT2, LINC02323, CYTH2, LRRC8D, LYPLAL1, LRRC41, and / or SEPT9; and wherein the methylation profile indicates that the subject has ovarian cancer.

55. A method for identifying a gynecological cancer, the method comprising: determining a methylation profile in at least one differentially methylated region (DMR) of a sample by treating a DNA sample obtained from a subject having or suspected of having a gynecological cancer with a reagent that modifies DNA in a methylation-specific manner; wherein the at least one DMR comprises one or more CpG sites among the following: KRT86, EMX2OS, JSRP1, DIDO1, MPZ, VILL, SMPD5, GDF7, MDFI, c17orf64, GATA2, SQSTM1, and / or EEF1A2; and wherein the methylation profile indicates that the subject has ovarian cancer, cervical cancer, or endometrial cancer.

56. The method according to any one of claims 48 to 55, wherein the method further comprises treating the subject with an anticancer therapy.

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