Compositions and methods for detecting urological cancer

Abstract

The present disclosure relates to the detection of one or more types of urological 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 urological cancer (e.g., urothelial carcinoma and / or renal cell carcinoma) in a biological sample from a subject having or suspected of having urological cancer.

Description

[Technical Field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This application claims priority to and the benefit of U.S. Provisional Patent Application No. 63 / 426,290, filed November 17, 2022, and U.S. Provisional Patent Application No. 63 / 535,663, filed August 31, 2023, both of which are incorporated herein by reference in their entirety for all purposes.

[0002] Incorporation by Reference of Electronically Submitted Materials The computer-readable nucleotide / amino acid sequence listing, filed concurrently herewith and identified as follows: a single file of 364,958 bytes entitled "41075-601_SEQUENCE_LISTING", created on November 17, 2023, is hereby incorporated by reference in its entirety.

[0003] The present disclosure relates to the detection of one or more types of urological 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 urological cancer (e.g., urothelial carcinoma and / or renal cell carcinoma) in a biological sample from a subject having or suspected of having urological cancer. [Background technology]

[0004] Renal tumors are the third most common urological malignancy and can arise from the renal parenchyma or the urinary collecting system. Renal cell carcinoma (RCC), originating from the renal parenchyma, is the most common malignant renal tumor, associated with an annual incidence of 64,000 cases and approximately 14,000 deaths in the United States. Of the urinary collecting system origins, urothelial cell carcinoma is the most common malignant tumor, accounting for approximately 10–15% of all renal tumors. The overall incidence of malignant renal tumors is increasing, and they are now the third most common form of genitourinary cancer. Both malignant and benign renal tumors are increasingly diagnosed incidentally using advanced cross-sectional imaging techniques. Accurate diagnosis of benign or malignant tumor type is lacking, which can lead to overtreatment of patients. Furthermore, currently, no diagnostic tests exist that accurately characterize renal tumors or identify patients at risk for renal tumors from needle biopsies, urine, or blood samples. The diagnostic and therapeutic approach for renal tumors is complicated by the existence of multiple types of benign renal tumors and the fact that many small malignant renal parenchymal tumors can be observed without curative treatment. Currently, there are no accurate, easy-to-use, and widely available screening tools at the tissue, blood, or urine level for ideal clinical management of renal tumors. Summary of the Invention

[0005] Embodiments of the present disclosure provide methods, compositions, and systems for screening for multiple types of urological cancer from a biological sample. According to these embodiments, the present disclosure includes, but is not limited to, methods and compositions for detecting the presence of multiple types or subtypes of urological cancer from a biological sample. In some embodiments, the biological sample is a tissue sample, a blood sample, a plasma sample, a serum sample, a whole blood sample, a buffy coat sample, a secretion sample, an organ secretion sample, a cerebrospinal fluid (CSF) sample, a saliva sample, a urine sample, and / or a stool sample. In some embodiments, the tissue sample is a urinary system or urothelial tissue sample including one or more of kidney cells or tissue, bladder cells or tissue, renal pelvis cells or tissue, urethral cells or tissue, and ureter cells or tissue. In some embodiments, the tissue sample is a urinary system or urothelial tissue sample including one or more of penile cells or tissue, testicular cells or tissue, and prostate cells or tissue. In some embodiments, the secretion sample is a urinary secretion sample. In some embodiments, the subject is a human.

[0006] As further described herein, embodiments of the present disclosure include novel differentially methylated regions (DMRs) that can individually distinguish certain types of urological cancers (e.g., renal cell carcinoma (RCC), including papillary RCC, clear cell RCC, and chromophobe RCC, and urothelial cell carcinoma (UCC), including upper tract urothelial carcinoma (UTUC), and renal tumors (ROs)) from control or benign tissue. According to these embodiments, the novel DMR(s) include ACCN1, ADCYAP1, ADRA1A, AGAP1, ALX3, ANKRD35, ARRDC2, ASCL4, BARHL2, BCL11B, TMEM240, C1orf94, C1QL3, ECRG4, CRACDL, NICOL1, IRX2-DT, CACNA1B, CACNA1I, CACNG3, CASR, CBLN4, CCDC140, CDHR5, CDO1, CLDN11, CLEC 14A, CMTM1, CNGA3, CNPY1, CNTNAP5, COL23A1, CRMP1, YBX3P1, CTNNA2, CYP4F2, DBX1, DCHS2, DGCR14, DLX6, DMRT1, DMRTA2, DN MT3A, DSCR6, EBF3, EMX1, EMX2OS, EVX1, EVX2, FBRSL1, FGF14, FLJ31485, FLJ32063, FMN2, FOXA2, FOXB1, FOXD3, FOXD4, FOXE1 , FOXF1, FOXG1, FZD8, GAD1, GALR1, GATA4, GATA6, GBX2, GCM2, GHSR, GRASP, GRIK1, HAS1, HMX2, HOXA11, HOXA7, HOXA9, IGF2BP 1, IRF4, IRX1, IRX4, ISL2, JPH4, KCNC2, KCNC4, KCNIP4, KCNQ2, KLF16, LBX2, LHFPL4, LHX1, LHX2, LHX4, LHX5, LIMD2, LOC1001 31366, LOC154860, LOC285548, LOC400550, LRRC4, MADCAM1, MAL, MAML3, MAX.chr1.6151, MAX.chr1.4676, MAX.chr1.9437, T TC34, MAX.chr1.1120, MAX.chr1.5982, MAX.chr1.5203, TLX1NB, MAX.chr10.0288, MAX.chr10.2081, MAX.chr10.7570, MAX.chr10.1197、NKX6-2、MAX.chr10.9377、MAX.chr10.5150、MAX.chr10.0872、FAM111A-DT、MAX.chr12.7397、MAX.chr12.3032、LINC00943、MAX.chr12.9110、KRT86、MAX.chr12.7375、MAX.chr13.1022、MAX.chr13.1687、LINC00554、SOX1-OT、MAX.chr13.2109、OBI1-AS1、LINC00391、MAX.chr14.3769、RAP2CP1、NKX2-8、MAX.chr14.1054、MAX.chr14.6663、MAX.chr14.2697、MAX.chr14.4566、RP11-262A16、MAX.chr17.2359、MAX.chr17.0937、MAX.chr17.8512、MAX.chr17.3547、DLGAP1、SKOR2、MAX.chr18.9881、RP11-714M23.2、RP11-154H12.2、CYP4F23P、CTD-2562J15.6、MAN1A2P1、MAX.chr19.1656、MAX.chr19.4113、MAX.chr19.0870、PANTR1、MAX.chr2.2307、MAX.chr2.6334、RHOQP3、RHOQP2、SLC4A10、SP9、MAX.chr2.6585、LINC01833、MAX.chr2.8149、MAX.chr2.6033、LINC01798、LINC01143、LINC00237、MAX.chr20.8579、MAX.chr20.3480、MAX.chr21.5638、MAX.chr21.7663、ZIC1、MAX.chr3.3606、PTPRG-AS1、NKX1-1、MAX.chr4.1655、SCRG1、LINC00682、MAX.chr4.4040、MAX.chr4.5903、MAX.chr5.2699、MAX.chr5.1156、LOC100996385、MAX.chr5.3053、MAX.chr5.5180、LINC02106、MAX.chr5.5268、MAX.chr5.4245、MAX.chr5.3918、OSTM1、MAX.chr6.0016、RP4-668J24.2、MAX.chr6.8227、MAX.chr6.3523、MAX.chr7.6951、MAX.chr7.0916、MAX.chr7.8965、MAX.chr7.5395、MAX.chr7.6952、MAX.chr7.6206、MAX.chr7.7860、PDE1C、RP11-53M11.5、ERICH1、MAX.chr8.6940、RP11-1102P16.1、MAX.chr8.6725、LINC01388、PRRT1B、MAX.chr9.5748、MAX.chr9.9611、MAX.chr9.9692、MEIS2、MMP23A、MNX1、MYO16、NCRNA00253、NEFM、NEURL、NKX2-3、NKX2-4、NKX2-6、NKX3-2、NKX6-1、NOTCH3、NPR3、NPTX2、NPY、NR2E1、NR2F1、NR2F6、NR5A1、NRN1、NRXN1、OLIG2、OLIG3、ONECUT2、OTP、OTUD7A、OTX1、OTX2、OTX2OS1、PACSIN3、PAX1、PAX6、PAX7、PAX9、PCDH17、PCDH8、PCDHGA1、PDX1、PENK、PHYHIPL、PITX1、PITX2、PNPLA1、POU3F3、POU4F2、PPP1R3G、PRDM13、PRDM14、PRRX1、PTF1A、PTPN5、PTPRN2、PTPRU、RARG、RARRES2、RNF220、RXFP3、RYR2、SALL3、SATB2、SCAND3、SDCCAG8、SEMA6A、SEPTIN9、SFTA3、SH3PXD2A、SHE、SHOX2、SIM2、SIX6、SKOR1、SLC2A14、SLC7A14、SOX1、SOX11、SOX14、SOX17、SP8、SPAG6、SSTR1、ST8SIA3、STAP2、SYCP2L、TBXT、TACC2、TAL1、TBX15、TBX4、TBX5、TFAP2A、TFAP2E、TJP2、TLX3、TMEM132D、TMEM200C、TP73、TRIM58、TWIST1、UNCX、VAX1、VSTM2A、VSX1、VSX2、VWA5B1、ZAR1、ZIC2、ZIC5、ZMIZ1、ZNF521、ADRBK1、AGRN、ALOX5、ARHGAP25、ARHGAP27、ARHGAP30、BCL2L11、CD93、CDC42EP1、EPS15L1、FER1L4、FOSL1、FOXP4、GPR132、GRK6、ITGB4、MAX.chr21.9298、LINC01991、PRIC285、PRKAR1B、PTPN6、PTPRF、RAPGEFL1、RBM38、RHOF、SHH、SKI、TBC1D10C、WNT6、ACSL5、ADAM32、ADAMTS19、ADCY2、AEBP2、AKAP7、ANKRD27、ANKRD43、ANKS1B、ARPM1、BCAN、BMP7、BTBD19、C20orf134、C20orf197、CACNA2D3、CAPN2、CBLN1、CDH22、CTNND2、CYYR1、DGKE、EPOR、EPS8L1、ESPN、FAM38A、FAM83G、FBLIM1、FBN2、FIBP、FOXL1、FXYD5、GP5、GRM6、HOXC4、HS3ST3B1、ICAM4、IL2RA、IRS1、ITPKA、ITPKB、KBTBD11、KCNH3、KCNS1、KCP、KCTD1、LHFPL2、LOC100289410、LOC100499227、LOC402778、LOC645277、LRFN4、LTBP4、LYL1、MACROD1、MAFB、MAST4、LINC01342、MAX.chr1.7620、MAX.chr1.5214、LINC01398、MAX.chr10.0718、GRAMD1B、MAX.chr11.9738、MAX.chr13.8267、MAX.chr15.0918、MAX.chr16.8889、SOX9-AS1、MAX.chr19.3071、MAX.chr19.2699、MAX.chr19.0650、MAX.chr2.2345、MAX.chr20.3366、MAX.chr5.3868、MAX.chr6.1793、MAX.chr7.5822、CTD-2168K21.1, FAM163B, MEST, MFNG, MYO15B, N4BP3, NAGS, NCKAP5, NCRNA00245, NETO1, NR2F2, NRG2, OPLAH, PARVG, PAX2, PDE4D, PEAR1, PLEKHG5, PPFIA4, PPP2R5C, PRDM2, PROX1, PRR14, RGS14, RIMS4, SCAR F2, SEZ6L2, SFT2D3, SLC22A20, SNTG1, SOBP, SRCIN1, SYNGR3, TBCD, TMEM154, TNFRSF1B, TRANK1 , TTBK1, UCN, USP2, VAC14, VWA1, VWC2, ZIC4, ZNF783, ZSCAN30, ABHD8, ADHFE1, AGAP3, AKNA, ALDO C, derived from a gene selected from ATP6V1B1, B3GALT4, BIN1, VPS9D1, FAM218A, CLDN10, CMTM3, DUSP7, EPS8L2, FAIM2, FSCN1, GMDS, GRK7, HVCN1, IRAK3, KATNAL2, LOC100128239, LOC284454, TPBGL, LRRC8D, LRRFIP1, ST3GAL4, MAX.chr11.8952, RIMBP2, SHISA8, SMPD5, MGA, OXR1, PLEKHA2, RAI1, RASSF1, RCN3, SBNO2, SLC26A5, SPARC, TIGD3, TSPAN33, TSPAN9, WDR90, and ZBED3 (Table 1), including any combination thereof. In some embodiments, the novel DMR(s) are derived from any gene selected from Table 1 (including any combination thereof). While each novel DMR alone can distinguish between urological cancer and control samples, combining two or more of the novel DMRs may improve sensitivity. Thus, combinations of two or more novel DMRs selected from Table 1 are provided.

[0007] Embodiments of the present disclosure also include novel differentially methylated regions (DMRs), each of which can independently distinguish urothelial cancer (e.g., upper tract urothelial carcinoma (UTUC)) from a control tissue sample (e.g., control urothelial tissue). According to these embodiments, the novel DMR(s) include ACCN1, ADCYAP1, ADRA1A, AGAP1, ALX3, ANKRD35, ARRDC2, ASCL4, BARHL2, BCL11B, TMEM240, C1orf94, C1QL3, ECRG4, CRACDL, NICOL1, IRX2-DT, CACNA1B, CACNA1I, CACNG3, CASR, CBLN4, CCDC140, CDHR5, CDO1, CLDN11, CLEC14A, CMTM1, CNGA 3, CNPY1, CNTNAP5, COL23A1, CRMP1, YBX3P1, CTNNA2, CYP4F2, DBX1, DCHS2, DGCR14, DLX6, DMRT1, DMRTA2, DNMT3A, DSCR6, EBF3, EMX1, EMX2OS, EVX1, EVX2, FBRSL1, FGF14, FLJ31485, FLJ32063, FMN2, FOXA2, FOXB1, FOXD3, FOXD4, FOXE1, FOXF1, FOXG1, FZD8, GAD1, GALR1, GATA4, GATA6, GBX2, GCM2, GHSR, GRASP, GRIK1, HAS1, HMX2, HOXA11, HOXA7, HOXA9, IGF2BP1, IRF4, IRX1, IRX4, ISL2, JPH4, KCNC2, KCN C4, KCNIP4, KCNQ2, KLF16, LBX2, LHFPL4, LHX1, LHX2, LHX4, LHX5, LIMD2, LOC100131366, LOC154860, LOC285548, LOC400550, LRRC4, M ADCAM1, MAL, MAML3, MAX.chr1.6151, MAX.chr1.4676, MAX.chr1.9437, TTC34, MAX.chr1.1120, MAX.chr1.5982, MAX.chr1.5203, TLX 1NB, MAX.chr10.0288, MAX.chr10.2081, MAX.chr10.7570, MAX.chr10.1197, NKX6-2, MAX.chr10.9377, MAX.chr10.5150, MAX.chr10.0872、FAM111A-DT、MAX.chr12.7397、MAX.chr12.3032、LINC00943、MAX.chr12.9110、KRT86、MAX.chr12.7375、MAX.chr13.1022、MAX.chr13.1687、LINC00554、SOX1-OT、MAX.chr13.2109、OBI1-AS1、LINC00391、MAX.chr14.3769、RAP2CP1、NKX2-8、MAX.chr14.1054、MAX.chr14.6663、MAX.chr14.2697、MAX.chr14.4566、RP11-262A16、MAX.chr17.2359、MAX.chr17.0937、MAX.chr17.8512、MAX.chr17.3547、DLGAP1、SKOR2、MAX.chr18.9881、RP11-714M23.2、RP11-154H12.2、CYP4F23P、CTD-2562J15.6、MAN1A2P1、MAX.chr19.1656、MAX.chr19.4113、MAX.chr19.0870、PANTR1、MAX.chr2.2307、MAX.chr2.6334、RHOQP3、RHOQP2、SLC4A10、SP9、MAX.chr2.6585、LINC01833、MAX.chr2.8149、MAX.chr2.6033、LINC01798、LINC01143、LINC00237、MAX.chr20.8579、MAX.chr20.3480、MAX.chr21.5638、MAX.chr21.7663、ZIC1、MAX.chr3.3606、PTPRG-AS1、NKX1-1、MAX.chr4.1655、SCRG1、LINC00682、MAX.chr4.4040、MAX.chr4.5903、MAX.chr5.2699、MAX.chr5.1156、LOC100996385、MAX.chr5.3053、MAX.chr5.5180、LINC02106、MAX.chr5.5268、MAX.chr5.4245、MAX.chr5.3918、OSTM1、MAX.chr6.0016、RP4-668J24.2、MAX.chr6.8227、MAX.chr6.3523、MAX.chr7.6951、MAX.chr7.0916、MAX.chr7.8965、MAX.chr7.5395、MAX.chr7.6952、MAX.chr7.6206、MAX.chr7.7860、PDE1C、RP11-53M11.5、ERICH1、MAX.chr8.6940、RP11-1102P16.1、MAX.chr8.6725、LINC01388、PRRT1B、MAX.chr9.5748、MAX.chr9.9611、MAX.chr9.9692, MEIS2, MMP23A, MNX1, MYO16, NCRNA00253, NEFM, NEURL, NKX2-3, NKX2-4, NKX2-6, NKX3-2, NKX6-1, NOTCH 3, NPR3, NPTX2, NPY, NR2E1, NR2F1, NR2F6, NR5A1, NRN1, NRXN1, OLIG2, OLIG3, ONECUT2, OTP, OTUD7A, OTX1, OTX2 , OTX2OS1, PACSIN3, PAX1, PAX6, PAX7, PAX9, PCDH17, PCDH8, PCDHGA1, PDX1, PENK, PHYHIPL, PITX1, PITX2, PNP LA1, POU3F3, POU4F2, PPP1R3G, PRDM13, PRDM14, PRRX1, PTF1A, PTPN5, PTPRN2, PTPRU, RARG, RARRES2, RNF220, R XFP3, RYR2, SALL3, SATB2, SCAND3, SDCCAG8, SEMA6A, SEPTIN9, SFTA3, SH3PXD2A, SHE, SHOX2, SIM2, SIX6, SKOR 1, SLC2A14, SLC7A14, SOX1, SOX11, SOX14, SOX17, SP8, SPAG6, SSTR1, ST8SIA3, STAP2, SYCP2L, TBXT, TACC2, TAL 1, TBX15, TBX4, TBX5, TFAP2A, TFAP2E, TJP2, TLX3, TMEM132D, TMEM200C, TP73, TRIM58, TWIST1, UNCX, VAX1, VSTM2A, VSX1, VSX2, VWA5B1, ZAR1, ZIC2, ZIC4, ZIC5, ZMIZ1, and ZNF521 (Table 2), including any combination thereof. In some embodiments, the novel DMR(s) are derived from any gene selected from Table 2, including any combination thereof. While each novel DMR alone can distinguish between urological cancer and control samples, combining two or more of the novel DMRs may improve sensitivity. Accordingly, combinations of two or more novel DMRs selected from Table 2 are provided.

[0008]

[0010] Embodiments of the present disclosure also include novel differentially methylated regions (DMRs), each of which can independently distinguish urothelial cancer (e.g., upper tract urothelial carcinoma (UTUC)) from a control sample (e.g., a control buffy coat sample). According to these embodiments, the novel DMR(s) are derived from a gene selected from ADRBK1, AGRN, ALOX5, ARHGAP25, ARHGAP27, ARHGAP30, BCL2L11, CD93, CDC42EP1, EPS15L1, FER1L4, FOSL1, FOXP4, GPR132, GRK6, ITGB4, MAX.chr21.9298, LINC01991, PRIC285, PRKAR1B, PTPN6, PTPRF, RAPGEFL1, RBM38, RHOF, SHH, SKI, TBC1D10C, and WNT6 (Table 3), and any combination thereof. In some embodiments, at least one DMR is from a gene selected from CRACDL, ANKRD35, DLX6, MAX.chr8.6725, SP9, SOX1-OT, Septin9, LBX2, SIM2, and RAP2CP1 (Table 15), and any combination thereof. In some embodiments, the novel DMR(s) are from any gene selected from Table 3 or 15, including any combination thereof. While each novel DMR alone can distinguish between urological cancer and control samples, combining two or more of the novel DMRs in Table 3 and / or Table 15 may improve sensitivity. Accordingly, combinations of two or more novel DMRs selected from Table 3 and / or Table 15 are provided.

[0009] In some embodiments, 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 was used to validate the novel DMR(s) that can distinguish urothelial carcinoma from control samples based on at least one of the area under the receiver operating characteristic curve (AUC), methylation fold change, methylation rate, and / or hypermethylation ratio between test and control samples. According to these embodiments, the novel DMR(s) are from a gene selected from ALOX5, ANKRD35, ARRDC2, CRACDL, YBX3P1, DLX6, FOXD4, FOXP4, GRASP, HOXA7, LBX2, LHX4, MAX.chr10.5150, FAM111A-DT, MAX.chr12.7397, RAP2CP1, MAX.chr8.6725, PACSIN3, PDX1, RAPGEFL1, RARG, RBM38, SDCCAG8, SEMA6A, SEPTIN, SH3PXD2A, SIM2, SP9, TAL1, TJP2 (Tables 6 and 7). In some embodiments, the novel DMR(s) are from a gene selected from ALOX5, CRACDL, FOXP4, RBM38, SEPTIN9, SIM2, SP9, and TJP2 (Tables 6 and 7), and any combination thereof. In some embodiments, the novel DMR(s) are from any gene selected from Table 6 or 7, including any combination thereof. While each novel DMR alone can distinguish between urological cancer and control samples, combining two or more of the novel DMRs in Table 6 and / or Table 7 may improve sensitivity. Accordingly, combinations of two or more novel DMRs selected from Table 6 and / or Table 7 are provided.

[0010] In accordance with the above, control samples include samples from subjects without cancer (e.g., benign samples), samples from subjects without urological cancer, samples from subjects with a type of cancer other than urological cancer, samples from subjects without urothelial carcinoma, or samples from subjects with urological cancer other than urothelial carcinoma. In some embodiments, control samples include samples from subjects with RCC, but in which at least 50% of the organs from which the samples were taken are tumor-free (e.g., at least 50% of the kidneys taken from subjects with RCC are tumor-free).

[0011] In some embodiments, the novel DMR(s) capable of distinguishing urothelial carcinoma from control samples are associated with an area under the ROC curve (AUC) of 0.5 or greater, where the ROC curve distinguishes between subjects having or suspected of having UTUC and control DNA samples. In some embodiments, the novel DMR(s) capable of distinguishing urothelial carcinoma from control samples are associated with an area under the ROC curve (AUC) of 0.6 or greater, where the ROC curve distinguishes between subjects having or suspected of having UTUC and control DNA samples. In some embodiments, the novel DMR(s) capable of distinguishing urothelial carcinoma from control samples are associated with an area under the ROC curve (AUC) of 0.7 or greater, where the ROC curve distinguishes between subjects having or suspected of having UTUC and control DNA samples. In some embodiments, the novel DMR(s) capable of distinguishing urothelial carcinoma from control samples are associated with an area under the ROC curve (AUC) of 0.8 or greater, where the ROC curve distinguishes between subjects having or suspected of having UTUC and control DNA samples. In some embodiments, the novel DMR(s) capable of distinguishing urothelial carcinoma from control samples are associated with an area under the ROC curve (AUC) of 0.9 or greater, where the ROC curve distinguishes between subjects having or suspected of having UTUC and control DNA samples.

[0012] In some embodiments, the novel DMR(s) that can distinguish urothelial carcinoma from control samples have a high methylation rate compared to the control DNA sample. In some embodiments, the novel DMR(s) that can distinguish urothelial carcinoma from control samples have a high hypermethylation rate compared to the control DNA sample.

[0013] Embodiments of the present disclosure also include novel differentially methylated regions (DMRs), each of which can individually distinguish renal cell carcinoma (e.g., papillary RCC, clear cell RCC, and chromophobe RCC) from control samples (e.g., control kidney tissue samples and / or control buffy coat samples). According to these embodiments, the novel DMR(s) include ACSL5, ADAM32, ADAMTS19, ADCY2, AEBP2, AGRN, AKAP7, ANKRD27, ANKRD43, ANKS1B, ARPM1, BCAN, BMP7, BTBD19, C1QL3, C20orf134, C20orf197, CACNA2D3, CAPN2, CBLN1, CDH22, COL23A1, CTN ND2, CYYR1, DGKE, EPOR, EPS8L1, ESPN, FAM38A, FAM83G, FBLIM1, FBN2, FIBP, FOSL1, FOXL1, FXYD5, GP5, GRM6, HOXC4, HS3ST3B1, ICAM4, IL2RA, IRS1, ITPKA, ITPKB, KBTBD11, KCNH3, KCNS1, KCP, KCTD1, LHFPL2, LOC1002894 10, LOC100499227, LOC402778, LOC645277, LRFN4, LTBP4, LYL1, MACROD1, MAFB, MAST4, LINC01342, MAX.chr1 .7620, MAX.chr1.5214, LINC01398, MAX.chr10.0718, GRAMD1B, MAX.chr11.9738, KRT86, MAX.chr13.8267, R AP2CP1, MAX.chr15.0918, MAX.chr16.8889, SOX9-AS1, DLGAP1, MAX.chr19.3071, MAX.chr19.2699, MAX.chr 19.0650, MAX.chr2.2345, MAX.chr20.3366, MAX.chr5.3868, MAX.chr6.1793, MAX.chr7.5822, CTD-2168K21.1, FAM163B, MEST, MFNG, MYO15B, N4BP3, NAGS, NCKAP5, NCRNA00245, NETO1, NR2F2, NRG2, ONECUT2, OPLAH, PARVG, PAX2, PDE4D, PEAR1, PENK, PLEKHG5, PPFIA4, PPP2R5C, PRDM2, PROX1, PRR14, PTPRF, RBM38, RGS14, R IMS4, SCARF2, SEZ6L2, SFT2D3, SHH, SLC22A20, SNTG1, SOBP, SRCIN1, SYNGR3, TACC2, TBCD, TMEM154, TNFRS F1B, TRANK1, TRIM58, TTBK1, UCN, USP2, VAC14, VWA1, VWC2, ZIC4, ZNF783, ZSCAN30, ABHD8, ADHFE1, AGAP3, AKNA, ALDOC, ATP6V1B1, B3GALT4, BIN1, VPS9D1, FAM218A, CLDN10, CMTM3, DUSP7, EMX1, EPS8L2, FAIM2, FS CN1, GMDS, GRK7, HVCN1, IRAK3, KATNAL2, LHX1, LOC100128239, LOC284454, TPBGL, LRRC8D, LRRFIP1, ST3GA L4, MAX.chr11.8952, RIMBP2, SHISA8, SMPD5, MGA, OXR1, PLEKHA2, RAI1, RASSF1, RCN3, SBNO2, SKI, SLC26A5, SPARC, TIGD3, TSPAN33, TSPAN9, WDR90, ZBED3, and ZMIZ1 (Tables 4 and 5), and any combination thereof. In some embodiments, the novel DMR(s) are derived from any gene selected from Table 4 or 5, including any combination thereof. While each novel DMR alone can distinguish between urological cancer and control samples, combining two or more of the novel DMRs in Table 4 and / or Table 5 may improve sensitivity. Accordingly, combinations of two or more novel DMRs selected from Table 4 and / or Table 5 are provided.

[0014] Embodiments of the present disclosure also include novel differentially methylated regions (DMRs), each of which can individually distinguish renal cell carcinoma (e.g., papillary RCC, clear cell RCC, and chromophobe RCC) from control samples (e.g., control kidney tissue samples and / or control buffy coat samples). According to these embodiments, the novel DMR(s) include ACSL5, ADAM32, ADAMTS19, ADCY2, AEBP2, AGRN, AKAP7, ANKRD27, ANKRD43, ANKS1B, ARPM1, BCAN, BMP7, BTBD19, C1QL3, C20orf134, C20orf197, CACNA2D3, CAPN2, CBLN1, CDH22, COL23A1, CTN ND2, CYYR1, DGKE, EPOR, EPS8L1, ESPN, FAM38A, FAM83G, FBLIM1, FBN2, FIBP, FOSL1, FOXL1, FXYD5, GP5, GRM6, HOXC4, HS3ST3B1, ICAM4, IL2RA, IRS1, ITPKA, ITPKB, KBTBD11, KCNH3, KCNS1, KCP, KCTD1, LHFPL2, LOC1002894 10, LOC100499227, LOC402778, LOC645277, LRFN4, LTBP4, LYL1, MACROD1, MAFB, MAST4, LINC01342, MAX.chr1 .7620, MAX.chr1.5214, LINC01398, MAX.chr10.0718, GRAMD1B, MAX.chr11.9738, KRT86, MAX.chr13.8267, R AP2CP1, MAX.chr15.0918, MAX.chr16.8889, SOX9-AS1, DLGAP1, MAX.chr19.3071, MAX.chr19.2699, MAX.chr 19.0650, MAX.chr2.2345, MAX.chr20.3366, MAX.chr5.3868, MAX.chr6.1793, MAX.chr7.5822, CTD-2168K21.1, FAM163B, MEST, MFNG, MYO15B, N4BP3, NAGS, NCKAP5, NCRNA00245, NETO1, NR2F2, NRG2, ONECUT2, OPLAH, PARVG , PAX2, PDE4D, PEAR1, PENK, PLEKHG5, PPFIA4, PPP2R5C, PRDM2, PROX1, PRR14, PTPRF, RBM38, RGS14, RIMS4, SCARF 2, SEZ6L2, SFT2D3, SHH, SLC22A20, SNTG1, SOBP, SRCIN1, SYNGR3, TACC2, TBCD, TMEM154, TNFRSF1B, TRANK1, TRIM58, TTBK1, UCN, USP2, VAC14, VWA1, VWC2, ZIC4, ZNF783, and ZSCAN30 (Table 4), and any combination thereof. In some embodiments, the novel DMR(s) are derived from any gene selected from Table 4 (including any combination thereof). Each novel DMR alone can distinguish between urological cancer and control samples, and combining two or more of the novel DMRs may improve sensitivity. Thus, combinations of two or more novel DMRs selected from Table 4 are provided.

[0015] Embodiments of the present disclosure also include novel differentially methylated regions (DMRs), each of which can individually distinguish renal cell carcinoma (e.g., papillary RCC, clear cell RCC, and chromophobe RCC) from control samples (e.g., control urothelial tissue). According to these embodiments, the novel DMR(s) include ABHD8, ADHFE1, AGAP3, AKNA, ALDOC, ATP6V1B1, B3GALT4, BIN1, VPS9D1, FAM218A, CLDN10, CMTM3, DUSP7, EMX1, EPS8L2, FAIM2, FSCN1, GMDS, GRK7, HVCN1, IRAK3, KATNAL2, LHX1, LOC100128239, LOC284454, TPB

[0013] In some embodiments, the novel DMR(s) are derived from a gene selected from GL, LRRC8D, LRRFIP1, ST3GAL4, MAX.chr11.8952, RIMBP2, ShiSA8, SMPD5, MGA, OXR1, PLEKHA2, RAI1, RASSF1, RCN3, SBNO2, SKI, SLC26A5, SPARC, TIGD3, TSPAN33, TSPAN9, WDR90, ZBED3, and ZMIZ1 (Table 5), and any combination thereof. In some embodiments, the novel DMR(s) are derived from any gene selected from Table 5, including any combination thereof. While each novel DMR alone can distinguish between urological cancer and control samples, combining two or more of the novel DMRs may improve sensitivity. Accordingly, combinations of two or more novel DMRs selected from Table 5 are provided.

[0016] In some embodiments, 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 was used to validate the novel DMR(s) that can distinguish renal cell carcinoma from control samples based on at least one of the area under the receiver operating characteristic curve (AUC), methylation fold change, methylation rate, and / or hypermethylation ratio between test and control samples. According to these embodiments, the novel DMR(s) are selected from the group consisting of ACSL5, ADAMTS19, AEFP2, ANKRD27, ANNKS1B.r1, ARPM1, BCAN, C1QL3, CBLN1, CTNND2, ESPN, FOSL1, GP5, HOXC4, HS3ST3B1, IRS1, ITPKA, ITPKB, LOC100289410, LRFN4, LTBP4, LYL1, MAST4, MAX.chr1.5214, GRAMD1B, RAP2CP1, MAX.chr15.0918, MAX.chr16 .8889, MAX.chr19.3071, MAX.chr2.2345, MAX.chr20.3366, MFNG, Myo15B, NAGS, NCRNA00245, NRG2, OPLAH, PAX2, PDE4D, PLEKHG5, PPFIIA4, PPP2R5C, PRDM2, RGS14, SFT2D3, SHH, SLC22A20, TMEM154, TRANK1, TRIM58, USP2, VWC2, and ZNF783 (Table 8), and any combination thereof.In some embodiments, the novel DMR(s) are derived from a gene selected from ACSL5, BCAN, C1QL3, CBLN1, CTNND2, ESPN, FOSL1, GP5, HS3ST3B1, IRS1, ITPKA, ITPKB, LOC100289410, LTBP4, LYL1, MAST4, GRAMD1B, MAX.chr15.0918, MAX.chr16.8889, MFNG, Myo15B, NAGS, NCRNA00245, OPLAH, PAX2, PDE4D, PPFIA4, PPP2R5C, PRDM2, PRDM2, SFT2D3, SFT2D3, TMEM154, TRIM58, USP2, and VWC2 (Table 13), and any combination thereof. In some embodiments, the novel DMR(s) are from a gene selected from C1QL3, OXR1, ANKS1B, CMTM3, LINC01398, FBLIM1, VPS9D1, LRRC8D, HVCN1, SFT2D3, FAM83G, LOC100128239, LHX1, GRAMD1B, TSPAN33, PDE4D, LOC100289410, TTBK1, PRDM2, CLDN10, MAST4, MACROD1, and KCNH3. In some embodiments, the novel DMR(s) are from a gene selected from MAST4, KCNH3, GRAMD1B, and LOC100289410. In some embodiments, the novel DMR(s) are from a gene selected from at least one DMR from a gene selected from MAST4, KCNH3, GRAMD1B, and PDE4D. In some embodiments, the novel DMR(s) are from any gene selected from Table 8 or 13, including any combination thereof. While each novel DMR alone can distinguish between urological cancer and control samples, combining two or more of the novel DMRs in Table 8 and / or Table 13 may improve sensitivity. Thus, combinations of two or more novel DMRs selected from Table 8 and / or Table 13 are provided.

[0017] In some embodiments, the novel DMR(s) can distinguish papillary RCC from control samples (e.g., control kidney tissue samples and / or control buffy coat samples). According to these embodiments, the novel DMR(s) are derived from a gene selected from ACSL5, ADAMTS19, ANNKS1B, BCAN, C1QL3, CBLN1, CTNND2, ESPN, GP5, HOXC4, HS3ST3B1, IRS1, ITPKB, LOC100289410, LRFN4, LTBP4, LYL1, MAST4, MAX.chr1.5214, GRAMD1B, MAX.chr15.0918, MAX.chr2.2345, Myo15B, NCRNA00245, PAX2, PDE4D, PLEKHG5, PPFIA4, PPP2R5C, PRDM2, RGS14, SHH, SLC22A20, TMEM154, TRIM58, and VWC2 (Table 11), and any combination thereof. In some embodiments, the novel DMR(s) are derived from a gene selected from ACSL5, C1QL3, ESPN, IRS1, ITPKB, LOC100289410, LYL1, MAST4, GRAMD1B, MAX.chr2.2345, PAX2, PDE4D, and TMEM154 (Table 11), and any combination thereof. In some embodiments, the novel DMR(s) are derived from any gene selected from Table 11, including any combination thereof. While each novel DMR alone can distinguish between urological cancer and control samples, combining two or more of the novel DMRs may improve sensitivity. Accordingly, combinations of two or more novel DMRs selected from Table 11 are provided.

[0018] In some embodiments, the novel DMR(s) can distinguish clear cell RCC from control samples (e.g., control kidney tissue samples and / or control buffy coat samples). According to these embodiments, the novel DMR(s) are derived from a gene selected from ACSL5, ADAMTS19, ANNKS1B, BCAN, C1QL3, CBLN1, CTNND2, ESPN, GP5, HOXC4, HS3ST3B1, IRS1, ITPKB, LOC100289410, LRFN4, LTBP4, LYL1, MAST4, MAX.chr1.5214, GRAMD1B, MAX.chr15.0918, MAX.chr2.2345, Myo15B, NCRNA00245, PAX2, PDE4D, PLEKHG5, PPFIA4, PPP2R5C, PRDM2, RGS14, SHH, SLC22A20, TMEM154, TRIM58, and VWC2 (Table 12), and any combination thereof. In some embodiments, the novel DMR(s) are derived from a gene selected from ACSL5, CTNND2, ESPN, HS3ST3B1, ITPKB, LOC100289410, LTBP4, LYL1, MAST4, GRAMD1B, MAX.chr2.2345, Myo15B, PAX2, PDE4D, PLEKHG5, PPFIA4, PPP2R5C, PRDM2, TMEM154, and VWC2 (Table 12), and any combination thereof. In some embodiments, the novel DMR(s) are derived from any gene selected from Table 12, including any combination thereof. Each novel DMR alone can distinguish between urological cancer and control samples, and combining two or more of the novel DMRs may improve sensitivity. Accordingly, combinations of two or more novel DMRs selected from Table 12 are provided.

[0019] In some embodiments, the novel DMR(s) can distinguish chromophobe RCC from a control sample (e.g., a control kidney tissue sample and / or a control buffy coat sample). According to these embodiments, the novel DMR(s) are derived from a gene selected from AESBP2, ANKRD27, ARPM1, FOSL1, ITPKA, RAP2CP1, MAX.chr16.8889, MAX.chr19.3071, MAX.chr20.3366, MFNG, NAGS, NRG2, OPLAH, PAX2, PRDM2, SFT2D3, TRANK1, USP2, and ZNF783 (Table 10), and any combination thereof. In some embodiments, the novel DMR(s) are derived from a gene selected from ACSL5, C1QL3, ESPN, GPS, LRFN4, LTBP4, LYL1, MAST4, GRAMD1B, MAX.chr2.2345, PAX2, PDE4D, PRDM2, RGS14, TMEM154, VWC2, FOSL1, ITPKA, MAX.chr16.8889, MFNG, NAGS, and OPLAH (Table 10), and any combination thereof. In some embodiments, the novel DMR(s) are derived from any gene selected from Table 10, including any combination thereof. While each novel DMR alone can distinguish between urological cancer and control samples, combining two or more of the novel DMRs may improve sensitivity. Accordingly, combinations of two or more novel DMRs selected from Table 10 are provided.

[0020] According to the above, the control sample includes a sample from a subject without cancer (e.g., a benign sample), a sample from a subject without urological cancer, a sample from a subject with a type of cancer other than urological cancer, a sample from a subject without renal cell carcinoma, or a sample from a subject with a urological cancer other than renal cell carcinoma. In some embodiments, the control sample includes a sample from a subject with RCC, but at least 50% of the organs from which the sample is taken are tumor-free (e.g., at least 50% of the kidneys taken from a subject with RCC are tumor-free).

[0021] In some embodiments, the novel DMR(s) capable of distinguishing renal cell carcinoma from control samples are associated with an area under the ROC curve (AUC) of 0.5 or greater, where the ROC curve distinguishes between subjects having or suspected of having renal cell carcinoma and control DNA samples. In some embodiments, the novel DMR(s) capable of distinguishing renal cell carcinoma from control samples are associated with an area under the ROC curve (AUC) of 0.6 or greater, where the ROC curve distinguishes between subjects having or suspected of having renal cell carcinoma and control DNA samples. In some embodiments, the novel DMR(s) capable of distinguishing renal cell carcinoma from control samples are associated with an area under the ROC curve (AUC) of 0.7 or greater, where the ROC curve distinguishes between subjects having or suspected of having renal cell carcinoma and control DNA samples. In some embodiments, the novel DMR(s) capable of distinguishing renal cell carcinoma from control samples are associated with an area under the ROC curve (AUC) of 0.8 or greater, where the ROC curve distinguishes between subjects having or suspected of having renal cell carcinoma and control DNA samples. In some embodiments, the novel DMR(s) that can distinguish renal cell carcinoma from control samples are associated with an area under the ROC curve (AUC) of 0.9 or greater, where the ROC curve distinguishes between subjects having or suspected of having renal cell carcinoma and control DNA samples.

[0022] In some embodiments, the novel DMR(s) that can distinguish renal cell carcinoma from control samples have a high methylation rate compared to the control DNA sample. In some embodiments, the novel DMR(s) that can distinguish renal cell carcinoma from control samples have a high hypermethylation rate compared to the control DNA sample.

[0023] Embodiments of the present disclosure provide methods, compositions, and systems for screening for oncocytoma from a biological sample. According to these embodiments, the present disclosure includes, but is not limited to, methods and compositions for detecting the presence of oncocytoma from a biological sample. In some embodiments, the biological sample is a tissue sample, a blood sample, a plasma sample, a serum sample, a whole blood sample, a buffy coat sample, a secretion sample, an organ secretion sample, a cerebrospinal fluid (CSF) sample, a saliva sample, a urine sample, and / or a stool sample. In some embodiments, the tissue sample is a urinary system or urothelial tissue sample including one or more of kidney cells or tissue, bladder cells or tissue, renal pelvis cells or tissue, urethral cells or tissue, and ureteral cells or tissue. In some embodiments, the tissue sample is a urinary system or urothelial tissue sample including one or more of penile cells or tissue, testicular cells or tissue, and prostate cells or tissue. In some embodiments, the secretion sample is a urinary secretion sample. In some embodiments, the subject is a human.

[0024] As further described herein, embodiments of the present disclosure include novel differentially methylated regions (DMRs), each of which can individually distinguish oncocytoma from control or benign tissue. According to these embodiments, the novel DMR(s) include ACSL5, ADAMTS19, ANNKS1B, BCAN, C1QL3, CBLN1, CTNND2, ESPN, GP5, HOXC4, HS3ST3B1, IRS1, ITPKB, LOC100289410, LRFN4, LTBP4, LYL1, MAST4, MAX.chr1.5214, GRAMD1B, MAX.chr15.0918, MAX.chr2.2345, Myo15B, NCRNA00245, PAX2, PDE4D, PLEKHG5, and PPFIA. 4, PPP2R5C, PRDM2, RGS14, SHH, SLC22A20, TMEM154, TRIM58, VWC2, AEBP2, ANKRD27, ARPM1, FOSL1, ITPKA, RAP2CP1, MAX.chr16.8889, MAX.chr19.3071, MAX.chr20.3366, MFNG, NAGS, NRG2, OPLAH, PAX2, PRDM2, SFT2D3, TRANK1, USP2, and ZNF783 (Table 9), and any combination thereof. In some embodiments, the novel DMR(s) are derived from a gene selected from AESBP2, ANKRD27, ARPM1, FOSL1, ITPKA, MAX.chr16.8889, MAX.chr19.3071, MAX.chr20.3366, MFNG, NAGS, NRG2, OPLAH, PAX2, PRDM2, SFT2D3, TRANK1, USP2, and ZNF783 (Table 9), and any combination thereof. In some embodiments, the novel DMR(s) are derived from a gene selected from ACSL5, LTBP4, MAX.chr2.2345, PAX2, RGS14, TMEM154, FOSL1, MAX.chr16.8889, MFNG, NAGS, OPLAH, and PRDM2 (Tables 9 and 13), and any combination thereof. In some embodiments, the novel DMR(s) are from any gene selected from Tables 9 or 13 (including any combination thereof).While each novel DMR alone can distinguish between urological cancer and control samples, combining two or more of the novel DMRs in Table 9 and / or Table 13 may improve sensitivity. Thus, combinations of two or more novel DMRs selected from Table 9 and / or Table 13 are provided.

[0025] According to the above, the control sample includes a sample from a subject without cancer (e.g., a benign sample), a sample from a subject without urological cancer, a sample from a subject with a type of cancer other than urological cancer, a sample from a subject without renal cell carcinoma, a sample from a subject with a urological cancer other than renal cell carcinoma, or a sample from a subject without oncocytoma. In some embodiments, the control sample includes a sample from a subject with RCC, but at least 50% of the organs from which the sample is taken are tumor-free (e.g., at least 50% of the kidneys taken from a subject with RCC are tumor-free).

[0026] In some embodiments, the novel DMR(s) capable of distinguishing oncocytoma from control samples are associated with an area under the ROC curve (AUC) of 0.5 or greater, where the ROC curve distinguishes between subjects having or suspected of having oncocytoma and control DNA samples. In some embodiments, the novel DMR(s) capable of distinguishing oncocytoma from control samples are associated with an area under the ROC curve (AUC) of 0.6 or greater, where the ROC curve distinguishes between subjects having or suspected of having oncocytoma and control DNA samples. In some embodiments, the novel DMR(s) capable of distinguishing oncocytoma from control samples are associated with an area under the ROC curve (AUC) of 0.7 or greater, where the ROC curve distinguishes between subjects having or suspected of having oncocytoma and control DNA samples. In some embodiments, the novel DMR(s) capable of distinguishing oncocytoma from control samples are associated with an area under the ROC curve (AUC) of 0.8 or greater, where the ROC curve distinguishes between subjects having or suspected of having oncocytoma and control DNA samples. In some embodiments, the novel DMR(s) capable of distinguishing oncocytoma from control samples are associated with an area under the ROC curve (AUC) of 0.9 or greater, where the ROC curve distinguishes between subjects having or suspected of having oncocytoma and control DNA samples.

[0027] In some embodiments, the novel DMR(s) that can distinguish oncocytoma from control samples have a high methylation rate compared to the control DNA sample. In some embodiments, the novel DMR(s) that can distinguish oncocytoma from control samples have a high hypermethylation rate compared to the control DNA sample.

[0028] In some embodiments, a biological sample is obtained from a subject and the method further comprises extracting a DNA sample from the biological sample.

[0029] 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. In some embodiments, the borane reducing agent is pyridine borane (or a derivative or variant thereof), which is used to perform TET-assisted pyridine borane sequencing (TAPS), a bisulfite-free DNA methylation sequencing method.

[0030] 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 (e.g., Tables 6, 8, and 14). 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, flap endonuclease assay, PCR flap assay, and bisulfite genomic sequencing PCR. In some embodiments, determining the methylation profile of at least one DMR comprises determining the presence or absence of methylation at CpG sites. In some embodiments, the one or more CpG sites are present in a coding region, a non-coding region, and / or a regulatory region of a gene (e.g., any one of the genes disclosed herein).

[0031] Embodiments of the present disclosure also include methods for identifying urological cancer. According to these embodiments, the method includes 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 urological cancer by treating the sample with a reagent that modifies DNA in a methylation-specific manner. In some embodiments, the methylation profile indicates that the subject has urological cancer (e.g., RCC, UTUC). In some embodiments, the method further includes treating the subject with an anti-cancer therapy. [Brief explanation of the drawings]

[0032] [Figure 1A] Representative receiver operating characteristic (ROC) curve for the four gene combination using a 50-strand cutoff. (GRAMD1B is referred to in the figure as Max.chr11.1233). [Figure 1B] Representative receiver operating characteristic (ROC) curve for the four gene combination using a 1-strand cutoff. (GRAMD1B is referred to in the figure as Max.chr11.12331). [Figure 1C] Representative results of the four-marker panel in Figure 1B are shown for positive or negative calls for blood drawn from subjects with kidney cancer ("cancer" samples) and subjects without cancer ("normal" samples). The staging and detection calls for the cancer samples are also shown. DETAILED DESCRIPTION OF THE INVENTION

[0033]

[0003] Embodiments of the present disclosure relate to the identification of novel methylated DNA markers for malignant renal and urothelial tumors. As further described herein, experiments were conducted to develop a novel approach based on marker detection in tissues, multiple blood compartments, and urine, targeting novel and highly discriminatory methylated DNA markers capable of predicting primary tumor characteristics using a highly sensitive analytical platform. Various experiments described herein were conducted to discover novel methylated DNA markers in malignant renal and urothelial tumor tissues by unbiased whole-methylome sequencing (e.g., reduced representation bisulfite sequencing), validate top candidates in independent tissues, evaluate the detection accuracy of renal and urothelial cancers by analyzing the top methylated DNA markers in plasma, determine the detection accuracy of renal and urothelial cancers by analyzing the top methylated DNA markers in voided urine, and identify potential site-specific methylated DNA markers for the kidney or urothelium by in silico comparing the discovered candidates with whole-methylome databases created for tumors from multiple organs.

[0034] Studies have shown that aberrant DNA hypermethylation is involved in the pathogenesis of clear cell RCC. Furthermore, promoter hypermethylation and subsequent transcriptional silencing of tumor suppressor genes have been shown to play an important role in the pathogenesis of clear cell RCC. Furthermore, previous studies have shown that in patients with clear cell RCC, the von Hippel-Lindau (VHL) tumor suppressor gene is inactivated by promoter hypermethylation in 15% of cases. The hypermethylation process is achieved by methyltransferases. While hypermethylation can be detected by many testing techniques, the use of next-generation sequencing in all tumor subtypes is less understood. High-grade clear cell RCC and other malignant renal tumors may also be associated with tumor necrosis. For example, necrosis is a strong predictor of outcome in clear cell RCC, most pronounced in grade 3 and grade 4 tumors. Hypoxia, which causes necrosis, has been shown to increase DNA methylation in many tumor types, and necrosis increases the release of circulating tumor products, including DNA.

[0035] The historical lack of clinical sensitivity of blood tests for detecting early-stage cancer may be due to both technical and biological factors. Technically, the analytical sensitivity of the assay methods used is insufficient to detect low-abundance markers in the circulation. Biologically, candidate markers often prove to be either insensitive (i.e., absent from all target tumors) or nonspecific (i.e., present in normal or non-tumor tissues). Furthermore, tumor invasion into the vascular space may be minimal in the earliest stages of progression, in which case marker entry into the blood (or urine) via this traditionally understood mechanism would be minimal. In light of other distant media associated with the kidney, analysis of tests using excreted urine holds certain appeal, particularly in the case of urothelial cell carcinomas arising from the urothelium. Tumors arising from the renal parenchyma may also release MDM into the urine, given that this parenchyma is a source of urine.

[0036] As further described herein, various embodiments of the present disclosure provide solutions to these technical and biological barriers. Analytical sensitivity is improved by orders of magnitude over conventional methods, well within the range required for detecting low-abundance markers in early-stage disease. Thus, the plasma compartment alone may provide sufficient information for such assays. Furthermore, data provided herein demonstrate that assaying markers in alternative blood compartments (e.g., circulating macrophages) offers complementary value to plasma testing alone for detecting the earliest stage of disease, as alternative compartments may address other mechanisms of marker entry into the blood.

[0037] The section headings used in this section and throughout this disclosure are for organizational purposes only and are not intended to be limiting.

[0038] 1. Definition Throughout the specification and claims, the following terms have the meanings expressly associated therewith, unless the context clearly dictates otherwise. As used herein, the phrase "in one embodiment" may refer to the same embodiment, but does not necessarily refer to the same embodiment. Furthermore, as used herein, the phrase "in another embodiment" may refer to a different embodiment, but does not necessarily refer to a different embodiment. Thus, as described below, various embodiments of the invention can be readily combined without departing from the scope or spirit of the invention.

[0039] Additionally, as used herein, the term "or" is an inclusive "or" operator and is synonymous with the term "and / or" unless the context clearly dictates otherwise. The term "based on" is not exclusive and acknowledges that a relationship may be based on additional unlisted factors unless the context clearly dictates otherwise. Additionally, throughout this specification, the meanings of "a," "an," and "the" include plural referents. The meaning of "in" includes "in" and "on."

[0040] The transitional phrase "consisting essentially of," when used in the claims of this application, limits the scope of the claim to certain substances or steps "and which do not materially affect the basic and novel characteristic(s)" of the claimed invention, as stated in In re Herz, 537 F.2d 549,551-52,190 USPQ 461,463 (CCPA 1976). For example, a composition "consisting essentially of" the recited elements may contain an unrecited contaminant at a level such that, although the contaminant is present, the contaminant does not alter the function of the recited composition compared to the pure composition (i.e., a composition "consisting of" the recited components).

[0041] As used herein, the term "one or more" refers to a number greater than 1. For example, the term "one or more" includes any of the following: 2 or more, 3 or more, 4 or more, 5 or more, 6 or more, 7 or more, 8 or more, 9 or more, 10 or more, 12 or more, 13 or more, 14 or more, 15 or more, 20 or more, 50 or more, 100 or more, or even more.

[0042] The terms "one or more, but less than a larger number," "two or more, but less than a larger number," "three or more, but less than a larger number," "four or more, but less than a larger number," "five or more, but less than a larger number," "six or more, but less than a larger number," "seven or more, but less than a larger number," "eight or more, but less than a larger number," "nine or more, but less than a larger number," "ten or more, but less than a larger number," "eleven or more, but less than a larger number," "twelve or more, but less than a larger number," "thirteen or more, but less than a larger number," "fourteen or more, but less than a larger number," or "fifteen or more, but less than a larger number" are not limited to the larger number. For example, the larger number can be 10,000, 1,000, 100, 50, etc. For example, the larger 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).

[0043] The terms "one or more methylation markers" or "one or more DMRs" or "one or more genes" or "one or more markers" or "multiple methylation markers" or "multiple markers" or "multiple genes" or "multiple DMRs" are likewise not limited to a specific numerical combination. Indeed, any numerical combination of methylation markers is contemplated (e.g., 1-2 methylation markers, 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) (e.g., 2-3, 2-4, 2-5, 2-6, 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, 3-17, 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, 9-11, 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, 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, 1 0-23, 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, 1 1-16, 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, 12-33, 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, 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, 3 5 to 38) (e.g., 36 to 37, 36 to 38) (e.g., 37 to 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).

[0044] 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 specific numerical combinations. The DNA methylation markers of the present disclosure can be used to distinguish any number of combinations of urological cancer types or subtypes, including, but not limited to, renal cell carcinoma (RCC), including papillary RCC, clear cell RCC, and chromophobe RCC, and urothelial cell carcinoma (UCC), including upper tract urothelial carcinoma (UTUC). The DNA methylation markers of the present disclosure can also be used to identify (and distinguish from) renal oncocytoma (RO).

[0045] As used herein, "nucleic acid" or "nucleic acid molecule" generally refers to any ribonucleic acid or deoxyribonucleic acid, which may 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. Thus, DNA with backbone modifications for stability or other reasons is a "nucleic acid." As used herein, the term "nucleic acid" encompasses chemically, enzymatically, or metabolically modified forms of nucleic acid, as well as chemical forms of DNA characteristic of viruses and cells, including, for example, simple and complex cells.

[0046] The terms "oligonucleotide" or "polynucleotide" or "nucleotide" or "nucleic acid" refer to a molecule containing two or more deoxyribonucleotides or ribonucleotides, preferably more than three, and usually more than ten. The exact size will depend on many factors and is dependent 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. Typical deoxyribonucleotides of DNA are thymine, adenine, cytosine, and guanine. Typical ribonucleotides of RNA are uracil, adenine, cytosine, and guanine.

[0047] As used herein, the term "locus" or "region" of a nucleic acid refers to a small region of nucleic acid, e.g., a gene on a chromosome, a single nucleotide, a CpG island, and the like.

[0048] The terms "complementary" and "complementarity" refer to nucleotides (e.g., a single nucleotide) or polynucleotides (e.g., a sequence of nucleotides) 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 a portion 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 strands determines the efficiency and strength of hybridization between nucleic acid strands. This is particularly important in amplification reactions and detection methods that rely on binding between nucleic acids.

[0049] The term "gene" refers to a nucleic acid (e.g., DNA or RNA) sequence that comprises coding sequences necessary for the production of an RNA or polypeptide or its precursor. A functional polypeptide can be encoded by a full-length coding sequence or by any portion of the coding sequence, so long as the desired activity or functional property of the polypeptide (e.g., enzymatic activity, ligand binding, signal transduction, etc.) is retained. When used in reference to a gene, the term "portion" refers to fragments of that gene. These fragments can range in size from a few nucleotides to the entire gene sequence minus one nucleotide. Thus, "nucleotides comprising at least a portion of a gene" can include fragments of a gene or the entire gene.

[0050] The term "gene" includes the coding region of a structural gene as well as sequences located adjacent to the coding region at both the 5' and 3' ends, where the gene corresponds to the length of the full-length mRNA (e.g., including coding, regulatory, structural, and other sequences). Sequences located 5' of the coding region and present on the mRNA are referred to as 5' untranslated or non-translated sequences. Sequences located 3' or downstream of the coding region and present on the mRNA are referred to as 3' untranslated or 3' non-translated sequences. The term "gene" encompasses both cDNA and genomic forms of a gene. In some organisms (e.g., eukaryotes), genomic forms or clones of a gene contain coding regions interrupted by non-coding sequences termed "introns" or "intervening regions" or "intervening sequences." Introns are segments of a gene that are transcribed into nuclear RNA (hnRNA) and may contain regulatory elements such as enhancers. Introns are removed or "spliced ​​out" from the nuclear or primary transcript; therefore, introns are absent in the messenger RNA (mRNA) transcript. mRNA functions during translation to specify the sequence or order of amino acids in a nascent polypeptide. As will be understood by those skilled in the art based on the present disclosure, one or more CpG sites in a DMR may be located in a coding region not known to be associated with a particular gene, such as a coding region of a gene, a non-coding regulatory region of a gene, or a region containing long non-coding RNA (lncRNA). In some embodiments, sequences corresponding to these regions may be obtained using corresponding accession numbers (see, e.g., Table 1) in genome databases (e.g., GenBank, NCBI, UniProt, etc.). In some embodiments, one or more CpG sites in a DMR may be located within an unannotated genomic region. As further provided herein, an unannotated genomic region containing one or more CpG sites in a DMR may be described using a SEQ ID NO: (see, e.g., Table 1; SEQ ID NOs: 243-324).

[0051] As will be understood by one of skill in the art based on the present disclosure, the location of one or more CpG sites within a gene or region (e.g., a CpG island) and its relevance to a disease or condition can be determined using a variety of techniques, including, but not limited to, those described in Chen et al., "Methods for identifying differentially methylated regions for sequence- and array-based data," Briefings in Functional Genomics, Volume 15, Issue 6, November 2016, pp. 485-490 (incorporated herein by reference in its entirety for all purposes).

[0052] The term "wild-type," when used in reference to a gene, refers to a gene having the characteristics of a gene isolated from a naturally occurring source. The term "wild-type," when used in reference to a gene product, refers to a gene product having the characteristics of a gene product isolated from a naturally occurring source. The term "wild-type," when used in reference to a protein, refers to a protein having the characteristics of a naturally occurring protein. The term "naturally occurring," when 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 human hands in the laboratory is naturally occurring. A wild-type gene is often that gene or allele that is most frequently observed in a population and is therefore arbitrarily referred to as the "normal" or "wild-type" form of the gene. In contrast, when referring to a gene or gene product, the terms "modified" or "mutant" refer to a gene or gene product, respectively, that exhibits modifications in sequence and / or functional properties (i.e., altered characteristics) when compared to the wild-type gene or gene product. Note that naturally occurring variants can be isolated. These are identified by the fact that they have altered properties when compared to the wild-type gene or gene product.

[0053] The term "allele" refers to a genetic variation, including, without limitation, variants and mutations, polymorphic loci and single nucleotide polymorphic loci, frameshifts, and splice variants. Alleles may occur naturally within a population or may arise during the lifetime of any particular individual in a population.

[0054] Thus, when used in reference to a nucleotide sequence, the terms "variant" and "mutant" refer to a nucleic acid sequence that differs by one or more nucleotides from another, usually related, nucleotide sequence. A "mutation" is a difference between two different nucleotide sequences, typically one sequence being a reference sequence.

[0055] The term "primer" refers to an oligonucleotide, whether naturally occurring as a nucleic acid fragment from a purified restriction digest or synthesized, that can act as a point of initiation of synthesis when placed under conditions that induce synthesis of a primer extension product complementary to a template strand of nucleic acid (e.g., in the presence of nucleotides and an inducing agent such as DNA polymerase, at a suitable temperature and pH). Primers are preferably single-stranded to maximize amplification efficiency, but may alternatively be double-stranded. If double-stranded, the primer is first treated to separate its strands before being used to prepare extension products. Preferably, the primer is an oligodeoxyribonucleotide. The primer must be sufficiently long to prime the synthesis of an extension product in the presence of the inducing agent. The exact length of the primer will depend on many factors, including temperature, primer source, and the use of the method. In some embodiments, the primer pair is specific for a particular differentially methylated region (e.g., a DMR in Tables 1, 2, and 3) and specifically binds to at least a portion of the genetic region containing the DMR.

[0056] The term "probe" refers to an oligonucleotide (e.g., a series of nucleotides) capable of hybridizing to another oligonucleotide of interest, whether naturally occurring, as in a purified restriction digest, or produced synthetically, recombinantly, or by PCR amplification. Probes can be single-stranded or double-stranded. Probes are useful for the detection, identification, and isolation of specific gene sequences (e.g., "capture probes"). It is contemplated that any probe used in embodiments of the present disclosure can, in some embodiments, be labeled with any "reporter molecule" and thus be detectable in any detection system, including, but not limited to, enzymatic (e.g., ELISA and enzyme-based histochemical assays), fluorescent, radioactive, and luminescent systems. It is not intended that the various embodiments of the present disclosure be limited to any particular detection system or label.

[0057] As used herein, the term "target" refers to a nucleic acid to be sorted out from other nucleic acids, e.g., by probe binding, amplification, separation, capture, etc. For example, when used in reference to the polymerase chain reaction, "target" refers to the region of nucleic acid bounded by the primers used in the polymerase chain reaction, whereas when used in assays that do not amplify the target DNA, e.g., in some embodiments of an invasion-cleavage assay, the target includes the site where a probe and an invading oligonucleotide (e.g., an INVADER oligonucleotide) bind to form an invasion-cleavage structure, thereby allowing the presence of the target nucleic acid to be detected. A "segment" is defined as a region of nucleic acid within the target sequence.

[0058] Thus, as used herein, "non-target," when used to describe a nucleic acid such as, for example, DNA, refers to a nucleic acid that may be present in a reaction but is not the subject of detection or characterization by the reaction. In some embodiments, non-target nucleic acid can refer to a nucleic acid present in a sample that does not contain, for example, a target sequence, although in some embodiments, non-target can also refer to an exogenous nucleic acid, i.e., a nucleic acid that is not derived from a sample that contains or is suspected of containing a target nucleic acid, and that is added to a reaction, for example, to reduce variability in the performance of an enzyme (e.g., a polymerase) in the reaction, to normalize the activity of the enzyme.

[0059] As used herein, "methylation" refers to cytosine methylation at the C5 or N4 position of cytosine, the N6 position of adenine, or other types of nucleic acid methylation. In vitro amplified DNA is typically unmethylated, since typical in vitro DNA amplification methods do not preserve the methylation pattern of the amplified template. However, "unmethylated DNA" or "methylated DNA" can also refer to amplified DNA in which the original template was unmethylated or methylated, respectively.

[0060] As used herein, the term "amplification reagents" refers to the reagents needed for amplification (deoxyribonucleoside triphosphates, buffers, etc.) excluding primers, nucleic acid template, and amplification enzymes. Typically, amplification reagents are placed and contained within a reaction vessel along with other reaction components.

[0061] As used herein, the term "control," when used in reference to nucleic acid detection or analysis, refers to a nucleic acid with known characteristics (e.g., known sequence, known copy number per cell) used for comparison with an experimental target (e.g., a nucleic acid of unknown concentration, etc.). A control may be an endogenous, preferably invariant, gene to which a test or target nucleic acid in an assay can be normalized. Such normalization controls for sample-to-sample variations that may arise, for example, from sample processing, assay efficiency, etc., allowing for accurate data comparison between samples. Genes used to normalize nucleic acid detection assays in human samples include, for example, β-actin, ZDHHC1, and B3GALT6 (see, e.g., U.S. Patent Application Nos. 14 / 966,617 and 62 / 364,082, each of which is incorporated herein by reference). As used herein, "ZDHHC1" refers to a gene located on chromosome 16 (16q22.1) of human DNA that encodes a protein belonging to the DHHC palmitoyltransferase family, characterized as zinc finger DHHC-type containing 1.

[0062] Controls can also be external. For example, in quantitative assays such as qPCR and QuARTS, a "calibrator" or "calibration control" is a nucleic acid of known sequence, e.g., a nucleic acid with the same sequence as a portion of an experimental target nucleic acid and a known concentration or series of concentrations (e.g., a serially diluted control target for generating a standard curve for quantitative PCR). Typically, calibration controls are analyzed using the same reagents and reaction conditions as those used for the experimental DNA. In certain embodiments, the measurement of the calibrator is performed simultaneously with the experimental assay, e.g., in the same thermal cycler. In preferred embodiments, multiple calibrators can be included in a single plasmid so that different calibrator sequences can be easily provided in equimolar amounts. In particularly preferred embodiments, the plasmid calibrator is digested, e.g., with one or more restriction enzymes, to release the calibrator portion from the plasmid vector. See, e.g., WO2015 / 066695, incorporated herein by reference.

[0063] As used herein, "methylated nucleotide" or "methylated nucleotide base" refers to the presence of a methyl moiety on a nucleotide base, which 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 the 5th position of its pyrimidine ring.Therefore, cytosine is not a methylated nucleotide, but 5-methylcytosine is a methylated nucleotide.In another example, thymine contains a methyl moiety at the 5th position of its pyrimidine ring, but because thymine is a typical nucleotide base of DNA, for the purposes of this specification, thymine is not considered a methylated nucleotide when present in DNA.

[0064] As used herein, a "methylated nucleic acid molecule" refers to a nucleic acid molecule that contains one or more methylated nucleotides.

[0065] As used herein, the "methylation state," "methylation profile," and "methylation status" of a nucleic acid molecule refer to the presence or absence of one or more methylated nucleotide bases in a nucleic acid molecule. For example, a nucleic acid molecule that contains a methylated cytosine is considered to be 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 to be unmethylated.

[0066] As used herein, the term "methylation level" applied to a methylation marker refers to the amount of methylation in a particular methylation marker. Methylation level may also refer to the amount of methylation in a particular methylation marker compared to an established standard or control. Methylation level may also refer to whether one or more cytosine residues present in a CpG context have a methylation group. Methylation level may also refer to the proportion of cells in a sample that have or do not have a methylation group at such cytosine. Methylation level may also represent whether a single CpG dinucleotide is methylated.

[0067] The methylation state of a particular nucleic acid sequence (e.g., a genetic marker, or a DNA region, as described herein) can indicate the methylation state of all bases in the sequence, or it can indicate the methylation state of a subset of these bases (e.g., one or more cytosines) within the sequence, or it can indicate information about the methylation density of a region within the sequence, with or without providing precise information about the position within the sequence where methylation occurs.

[0068] The methylation state of a nucleotide locus in a nucleic acid molecule refers to the presence or absence of a methylated nucleotide at a particular locus in the nucleic acid molecule. For example, the methylation state of the cytosine at the seventh nucleotide in a nucleic acid molecule is methylated if the nucleotide present at the seventh nucleotide in the nucleic acid molecule is 5-methylcytosine. Similarly, the methylation state of the cytosine at the seventh nucleotide in a nucleic acid molecule is unmethylated if the nucleotide present at the seventh nucleotide in the nucleic acid molecule is cytosine (and not 5-methylcytosine).

[0069] Methylation status can optionally be expressed or indicated by a "methylation value" (e.g., representing a methylation frequency, fraction, proportion, percent, etc.). Methylation values ​​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 bisulfite reaction, or by comparing sequences of bisulfite-treated nucleic acid with sequences of untreated nucleic acid, or by comparing TET-treated nucleic acid with untreated nucleic acid. Thus, a value, e.g., a methylation value, represents methylation status and can thereby be used as a quantitative indicator of methylation status across multiple copies of a locus. This is of particular use when it is desirable to compare the methylation status of sequences in a sample to a threshold or reference value.

[0070] 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.

[0071] As used herein, the term "methylation score" refers to a score indicating the number of methylation events detected in a marker or panel of markers compared to the median number of methylation events for that marker or panel of markers from a randomized population of mammals (e.g., a randomized population of 10, 20, 30, 40, 50, 100, or 500 mammals) that do not have a particular tumor of interest. A high methylation score for a marker or panel of markers can be any score, as long as the score is greater than the corresponding reference score. For example, a high methylation score for a marker or panel of markers can be 0.5, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more times greater than the reference methylation score.

[0072] Thus, a methylation state refers to the methylation state of a nucleic acid (e.g., a genomic sequence). Furthermore, a methylation state refers to characteristics of a nucleic acid segment at a particular genomic locus related to methylation. Such characteristics include, but are not limited to, whether any cytosine (C) residues within this DNA sequence are methylated, the location of the methylated C residue(s), the frequency or percentage of methylated Cs throughout any particular region of the nucleic acid, and allelic differences in methylation due, for example, to differences in allelic origin. Additionally, the terms "methylation state," "methylation profile," and "methylation status" refer to the relative concentration, absolute concentration, or pattern of methylated or unmethylated Cs throughout any particular region of a nucleic acid in a biological sample. For example, if a cytosine (C) residue(s) within a nucleic acid sequence are methylated, they can be said to have "hypermethylated" or "high methylation," whereas if a cytosine (C) residue(s) within the DNA are unmethylated, they can be said to have "hypomethylated" or "low methylation." Similarly, if a cytosine (C) residue(s) in a nucleic acid sequence are methylated compared to another nucleic acid sequence (e.g., from a different region or from a different individual), the sequence is considered to be hypermethylated, or have high methylation, compared to the other nucleic acid sequence. Alternatively, if a cytosine (C) residue(s) in a DNA sequence are unmethylated compared to another nucleic acid sequence (e.g., from a different region or from a different individual), the sequence is considered to be hypomethylated, or have low methylation, compared to the other nucleic acid sequence. Additionally, as used herein, the term "methylation pattern" refers to the collection of methylated and unmethylated nucleotides across a nucleic acid region. Two nucleic acids can have the same or similar methylation frequency or methylation pattern, but have different methylation patterns when the numbers of methylated and unmethylated nucleotides are the same or similar throughout the region but the positions of the methylated and unmethylated nucleotides are different.Sequences are referred to as having "variable methylation," "differences in methylation," or "differential methylation states" when they differ in the degree (e.g., one has increased or decreased methylation compared to the other), frequency, or pattern of methylation. 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. The term can also refer to the difference in the level or pattern between patients who experience cancer recurrence after surgery and those who do not. Variable methylation and specific levels or patterns of DNA methylation can be prognostic and predictive biomarkers, for example, if precise cutoffs or predictive characteristics are defined. In some embodiments, one or more CpG sites in a DMR can be located within a non-coding region, such as a region corresponding to a long non-coding RNA (lncRNA).

[0073] Methylation state frequencies can be used to describe samples from a population of individuals or a single individual. For example, a nucleotide locus with a methylation state frequency of 50% means that 50% of the instances are methylated and 50% of the instances are unmethylated. Such frequencies can be used, for example, to describe the degree to which a nucleotide locus or nucleic acid region is methylated in a population of individuals or a collection of nucleic acids. Thus, if 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 frequencies can also be used, for example, to describe the degree to which a nucleotide locus or nucleic acid region is methylated in a single individual. For example, such frequencies can be used to describe the degree to which a group of cells from a tissue sample is methylated or unmethylated at a nucleotide locus or nucleic acid region.

[0074] Typically, methylation of human DNA occurs at dinucleotide sequences containing adjacent guanines and cytosines, where the cytosine is located 5' of the guanine (also called CpG dinucleotide sequences). In the human genome, most cytosines within CpG dinucleotides are methylated, although some remain unmethylated in certain CpG dinucleotide-rich genomic regions known as CpG islands (see, e.g., Antequera, et al. (1990) Cell 62:503-514).

[0075] As used herein, "CpG island" or "cytosine-phosphate-guanine-island" refers to a G:C-rich region of genomic DNA that contains more CpG dinucleotides than the total genomic DNA. A CpG island can be at least 100, 200 base pairs long, or longer, where the G:C content of the region is at least 50% and the ratio of observed CpG frequency to expected frequency is 0.6; in some cases, a CpG island can be at least 500 base pairs long, where the G:C content of the region is at least 55% and the ratio of observed CpG frequency to expected frequency is 0.65. The observed CpG frequency to 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 observed CpG frequency relative to the expected frequency can be calculated according to the formula R = (A x B) / (C x 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 usually determined in CpG islands, for example, in promoter regions. However, it will be appreciated that other sequences in the human genome, such as CpA and CpT, are also subject to DNA methylation (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).

[0076] As used herein, a "methylation-specific reagent" refers to a reagent that modifies the nucleotides of a nucleic acid molecule as a function of the methylation state of the nucleic acid molecule, or a methylation-specific reagent refers to a compound or composition, or other agent, that is capable of altering the nucleotide sequence of a nucleic acid molecule in a manner that reflects the methylation state of the nucleic acid molecule. Methods of treating nucleic acid molecules with such reagents can include contacting the nucleic acid molecule with the reagent, optionally in combination with additional steps, to achieve a desired change in nucleotide sequence. Such methods can be applied in a manner that results in the modification of unmethylated nucleotides (e.g., each unmethylated cytosine) to a different nucleotide. For example, in some embodiments, such reagents can deaminate unmethylated cytosine nucleotides to generate 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.

[0077] Alteration of a nucleic acid nucleotide sequence with a methylation-specific reagent can also result in a nucleic acid molecule in which each methylated nucleotide is modified to a different nucleotide.

[0078] The term "methylation assay" refers to any assay for determining the methylation status of one or more CpG dinucleotide sequences within a nucleic acid sequence.

[0079] The term "MS AP-PCR" (methylation-sensitive arbitrarily primed polymerase chain reaction) refers to an art-recognized technique that uses CG-rich primers to scan the entire genome and focus on regions most likely to contain CpG dinucleotides, and is described by Gonzalgo et al. (1997) Cancer Research 57:594-599.

[0080] The term "MethyLight™" refers to the art-recognized fluorescence-based real-time PCR technology described by Eads et al. (1999) Cancer Res. 59:2302-2306.

[0081] The term "HeavyMethyl™" refers to an assay in which methylation-specific inhibitory probes (also referred to herein as inhibitors) that cover the CpG positions between or covered by the amplification primers enable methylation-specific selective amplification of a nucleic acid sample.

[0082] The term "HeavyMethyl™ MethyLight™" assay refers to the HeavyMethyl™ MethyLight™ assay, which is a variation of the MethyLight™ assay in which the MethyLight™ assay is combined with a methylation-specific blocking probe that covers the CpG positions between the amplification primers.

[0083] The term "Ms-SNuPE" (methylation-sensitive single-nucleotide primer extension) refers to the art-recognized assay described in Gonzalgo & Jones (1997) Nucleic Acids Res. 25: 2529-2531.

[0084] 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 in US Pat. No. 5,786,146.

[0085] The term "COBRA" (Combined Bisulfite Restriction Analysis) refers to an art-recognized methylation assay described in Xiong & Laird (1997) Nucleic Acids Res. 25:2532-2534.

[0086] The term "MCA" (methylated CpG island amplification) refers to the methylation assay described in Toyota et al. (1999) Cancer Res. 59: 2307-12 and WO00 / 26401A1.

[0087] As used herein, a "selected nucleotide" refers to one of the four nucleotides typically occurring in a nucleic acid molecule (C, G, T, and A for DNA and C, G, U, and A for RNA), and can include methylated derivatives of a typically occurring nucleotide (e.g., when C is a selected nucleotide, both methylated and unmethylated C are included in the meaning of the selected nucleotide), but 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.

[0088] The term "methylation-specific restriction enzyme" refers to a restriction enzyme that selectively digests nucleic acids depending on the methylation state of its recognition site. For restriction enzymes that specifically cleave when their recognition site is unmethylated or hemimethylated (methylation-sensitive enzymes), cleavage does not occur (or occurs at a much lower efficiency) when the recognition site is methylated on one or both strands. For restriction enzymes that specifically cleave only when their recognition site is methylated (methylation-dependent enzymes), cleavage does not occur (or occurs at a much lower efficiency) when the recognition site is unmethylated. Methylation-specific restriction enzymes are preferred, and their recognition sequences contain a CG dinucleotide (e.g., a recognition sequence such as CGCG or CCCGGG). Even more preferred in some embodiments are restriction enzymes that do not cleave when the cytosine in this dinucleotide is methylated at the C5 carbon atom.

[0089] As used herein, the "sensitivity" of a particular marker (or set of markers used in combination) refers to the percentage of samples reporting DNA methylation values ​​above a threshold that distinguishes between tumor and non-tumor samples. In some embodiments, a positive result is defined as a histologically confirmed tumor reporting a DNA methylation value above a threshold (e.g., a range associated with disease), and a false negative result is defined as a histologically confirmed tumor reporting a DNA methylation value below a threshold (e.g., a range associated with non-disease). Thus, a sensitivity value reflects the probability that a DNA methylation measurement value for a given marker from a known diseased sample will fall within the range of disease-associated measurements. As defined herein, the clinical significance of a calculated sensitivity value represents an estimate of the probability that a given marker will detect the presence of a clinical condition when applied to subjects with that condition.

[0090] As used herein, the "specificity" of a given marker (or a set of markers used together) refers to the proportion of non-neoplastic samples reporting DNA methylation values ​​below a threshold that distinguishes between neoplastic and non-neoplastic samples. In some embodiments, a negative is defined as a histologically confirmed non-neoplastic sample reporting a DNA methylation value below the threshold (e.g., a range not associated with any disease), and a false positive is defined as a histologically confirmed non-neoplastic sample reporting a DNA methylation value above the threshold (e.g., a range associated with a disease). Thus, the specificity value reflects the probability that a DNA methylation measurement value for a given marker from a known non-neoplastic sample will fall within the range of non-disease-associated measurements. As defined herein, the clinical relevance of a calculated specificity value represents an estimate of the probability that a given marker will detect the absence of a clinical condition when applied to patients without that condition.

[0091] The term "AUC" used herein is an abbreviation for "area under the curve." In particular, AUC refers to the area under the receiver operating characteristic (ROC) curve. An ROC curve is a plot of the true positive rate against the false positive rate for different possible cut points of a diagnostic test. The ROC curve shows the trade-off between sensitivity and specificity depending on the cut point selected (any increase in sensitivity will be accompanied by a decrease in specificity). The area under the ROC curve (AUC) is a measure of the accuracy of a diagnostic test (the larger the area, the better, with 1 being optimal, and a randomized test has a ROC curve located on the diagonal, with an area of ​​0.5. See: J.P. Egan. (1975) Signal Detection Theory and ROC Analysis, Academic Press, New York).

[0092] As used herein, the term "tumor" refers to any new, abnormal growth of tissue. Thus, a tumor can be a pre-malignant tumor or a malignant tumor.

[0093] The term "tumor-specific marker," as used herein, refers to any biological material or element that can be used to indicate the presence of a tumor. Examples of biological materials include, but are not limited to, nucleic acids, polypeptides, carbohydrates, fatty acids, cellular 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, a region within a gene, a specific locus, etc.). A region of a nucleic acid that is a marker may be referred to, for example, as a "marker gene," a "marker region," a "marker sequence," a "marker locus," etc.

[0094] As used herein, the term "adenoma" refers to a benign tumor of glandular origin. These growths are benign, although over time they can progress to become malignant.

[0095] The terms "precancerous" or "preneoplastic" and their equivalents refer to any cell proliferative disorder undergoing malignant transformation.

[0096] The "site" of a tumor, adenoma, cancer, etc. is the tissue, organ, cell type, anatomical region, body part, etc. in a subject in which the tumor, adenoma, cancer, etc. is located.

[0097] As used herein, the application of a "diagnostic" test includes the detection or identification of a disease state or condition in a subject, determining the likelihood that a subject will suffer from a given disease or condition, determining the likelihood that a subject with a disease or condition will respond to treatment, determining the prognosis (or likelihood of progression or regression) of a subject with a disease or condition, and determining the effectiveness of a treatment for a subject with a disease or condition. For example, a diagnostic test can be used to detect the presence or likelihood of a subject suffering from a tumor, or the likelihood that such a subject will respond successfully to a compound (e.g., a pharmaceutical, e.g., a drug) or other treatment.

[0098] The term "isolated," when used with reference to a nucleic acid, such as an "isolated oligonucleotide," refers to a nucleic acid sequence that is identified and separated from at least one contaminant nucleic acid normally associated with its natural source. An isolated nucleic acid exists in a form or setting that is different from that in which it is found in nature. In contrast, non-isolated nucleic acids, such as DNA and RNA, are found in the state in which they exist in nature. Examples of non-isolated nucleic acids include a given DNA sequence (e.g., a gene) found adjacent to adjacent genes on a host cell chromosome; an RNA sequence, such as a particular mRNA sequence encoding a particular protein, that is found in a cell as a mixture with many other mRNAs encoding many proteins. However, an isolated nucleic acid encoding a particular protein includes, for example, a nucleic acid in a cell that normally expresses that protein, where the nucleic acid is in a location different from that in the chromosome of the natural cell or is otherwise flanked by different nucleic acid sequences than that in which it is 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 minimally contain a sense or coding strand (i.e., the oligonucleotide may be single-stranded), but may also contain both a sense and an antisense strand (i.e., the oligonucleotide may be double-stranded). An isolated nucleic acid may be combined with other nucleic acids or molecules after isolation from its natural or typical environment. For example, an isolated nucleic acid may be present in a host cell, for example, for heterologous expression.

[0099] The term "purified" refers to a molecule, either a nucleic acid or an amino acid sequence, that has been removed, isolated, or separated from its natural environment. Thus, an "isolated nucleic acid sequence" can be a purified nucleic acid sequence. "Substantially purified" molecules are at least 60% free, preferably at least 75% free, and more preferably at least 90% free from other components with which they are naturally associated. As used herein, the terms "purified" or "to purify" also refer to the removal of contaminants from a sample. Removal of contaminating proteins results in an increase in the percentage of the polypeptide or nucleic acid of interest in a sample. In another example, recombinant polypeptides are expressed in plant, bacterial, yeast, or mammalian host cells, and these polypeptides are purified by removal of host cell proteins, thereby increasing the percentage of recombinant polypeptides in a sample.

[0100] The term "composition comprising" a given polynucleotide sequence or polypeptide refers broadly to any composition that includes the given polynucleotide sequence or polypeptide. Compositions can include aqueous solutions containing salts (e.g., NaCl), detergents (e.g., SDS), and other components (e.g., Denhardt's solution, milk powder, salmon sperm DNA, etc.).

[0101] 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 and environmental samples. Biological samples can be obtained from plants or animals (including humans) and can include fluids, solids, tissues, and gases. Environmental samples include environmental materials such as surface material, soil, water, and industrial samples. These examples are not to be construed as limiting the types of samples applicable to this disclosure.

[0102] As used herein, a "remote sample," as used in some contexts, refers to a sample that is indirectly collected from a site that is not the source of the cell, tissue, or organ sample. For example, if sample material derived from the pancreas is evaluated in a stool sample, the sample is a remote sample.

[0103] As used herein, the term "patient" or "subject" refers to an organism that is the subject of the various tests described herein. The term "subject" includes animals, preferably mammals, including humans. In preferred embodiments, the subject is a primate. In even more preferred embodiments, the subject is human. Furthermore, with respect to diagnostic methods, preferred subjects are vertebrate subjects. Preferred vertebrates are warm-blooded, and preferred warm-blooded vertebrates are mammals. Preferred mammals are most preferably humans. As used herein, the term "subject" includes both human and animal subjects. Accordingly, veterinary uses are provided herein. Accordingly, the present disclosure provides for the diagnosis of mammals, such as humans, as well as mammals of endangered importance, such as the Amur tiger, 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, carnivores such as cats and dogs; swine such as pigs, hogs, and wild boars; ruminants and / or ungulates such as cows, bulls, sheep, giraffes, deer, goats, bison, and camels; pinnipeds; and horses. Accordingly, diagnostics and treatments for livestock, including but not limited to domestic pigs, ruminants, ungulates, horses (including racehorses), and the like, are also provided. Embodiments of the present disclosure further include a system for diagnosing one or more types or subtypes of urological cancer in a subject. This system may be provided, for example, as a commercially available kit that can be used to screen for risk of one or more types or subtypes of urological cancer in a subject from whom a biological sample has been obtained, or to diagnose one or more types or subtypes of urological cancer. Exemplary systems provided according to various embodiments of the present disclosure include assessing the methylation status or profile of the markers described herein.

[0104] As used herein, the term "kit" refers to any delivery system for delivering materials. In the context of a reaction assay, such delivery systems include systems that allow for the storage, transport, or delivery of reaction reagents (e.g., oligonucleotides, enzymes, etc. in appropriate containers) and / or supporting materials (e.g., buffers, written instructions for conducting the assay, etc.) from one location to another. For example, a kit may include one or more enclosed members (e.g., boxes) that contain the relevant reaction reagents and / or supporting materials. As used herein, the term "fragmentation kit" refers to a delivery system that includes two or more separate containers, each containing a subportion of the overall kit components. The containers can be delivered to the intended recipient together or separately. For example, a first container may contain an enzyme for use in an assay, while a second container contains an oligonucleotide. The term "fragmentation kit" is intended to encompass, but is not limited to, a kit containing an analyte-specific reagent (ASR) as defined by Section 520(e) of the Federal Food, Drug, and Cosmetic Act. Indeed, any delivery system comprising two or more separate containers, each housing a portion of the overall kit's components, is encompassed by the term "fragmented kit." In contrast, a "combined kit" refers to a delivery system that contains all components of a reaction assay in a single container (e.g., in a single box housing each of the desired components). The term "kit" encompasses both fragmented and combined kits.

[0105] As used herein, the term "information" refers to any collection of facts or data. With respect to information stored or processed using computer system(s), including but not limited to the Internet, the term refers to any data stored in any format (e.g., analog, digital, optical, etc.). As used herein, the term "information about a subject" refers to facts or data about a subject (e.g., a human, plant, or animal). The term "genomic information" refers to information about a genome, including, but not limited to, nucleic acid sequences, genes, methylation percentages, allele frequencies, RNA expression levels, protein expression, phenotypes correlated with genotypes, etc. "Allele frequency information" refers to facts or data about allele frequencies, including, but not limited to, the identity of an allele, statistical correlations between the presence of an allele and characteristics of a subject (e.g., a human subject), the presence or absence of an allele in an individual or population, the percentage likelihood of an allele being present in an individual with one or more particular characteristics, etc.

[0106] 2. Methylation DNA markers and biomarker panels Embodiments of the present disclosure provide methods, compositions, and systems for screening for multiple types of urological cancer from a biological sample. According to these embodiments, the present disclosure includes, but is not limited to, methods and compositions for detecting the presence of multiple types or subtypes of urological cancer from a biological sample. In some embodiments, the biological sample is a tissue sample, a blood sample, a plasma sample, a serum sample, a whole blood sample, a buffy coat sample, a secretion sample, an organ secretion sample, a cerebrospinal fluid (CSF) sample, a saliva sample, a urine sample, and / or a stool sample. In some embodiments, the tissue sample is a urinary system or urothelial tissue sample including one or more of kidney cells or tissue, bladder cells or tissue, renal pelvis cells or tissue, urethral cells or tissue, and ureter cells or tissue. In some embodiments, the tissue sample is a urinary system or urothelial tissue sample including one or more of penile cells or tissue, testicular cells or tissue, and prostate cells or tissue. In some embodiments, the secretion sample is a urinary secretion sample. In some embodiments, the subject is a human.

[0107] As further described herein, embodiments of the present disclosure include novel differentially methylated regions (DMRs) that can individually distinguish certain types of urological cancers (e.g., renal cell carcinoma (RCC), including papillary RCC, clear cell RCC, and chromophobe RCC, and urothelial cell carcinoma (UCC), including upper tract urothelial carcinoma (UTUC), and renal tumors (ROs)) from control or benign tissue. According to these embodiments, the novel DMR(s) include ACCN1, ADCYAP1, ADRA1A, AGAP1, ALX3, ANKRD35, ARRDC2, ASCL4, BARHL2, BCL11B, TMEM240, C1orf94, C1QL3, ECRG4, CRACDL, NICOL1, IRX2-DT, CACNA1B, CACNA1I, CACNG3, CASR, CBLN4, CCDC140, CDHR5, CDO1, CLDN11, CLEC 14A, CMTM1, CNGA3, CNPY1, CNTNAP5, COL23A1, CRMP1, YBX3P1, CTNNA2, CYP4F2, DBX1, DCHS2, DGCR14, DLX6, DMRT1, DMRTA2, DN MT3A, DSCR6, EBF3, EMX1, EMX2OS, EVX1, EVX2, FBRSL1, FGF14, FLJ31485, FLJ32063, FMN2, FOXA2, FOXB1, FOXD3, FOXD4, FOXE1 , FOXF1, FOXG1, FZD8, GAD1, GALR1, GATA4, GATA6, GBX2, GCM2, GHSR, GRASP, GRIK1, HAS1, HMX2, HOXA11, HOXA7, HOXA9, IGF2BP 1, IRF4, IRX1, IRX4, ISL2, JPH4, KCNC2, KCNC4, KCNIP4, KCNQ2, KLF16, LBX2, LHFPL4, LHX1, LHX2, LHX4, LHX5, LIMD2, LOC1001 31366, LOC154860, LOC285548, LOC400550, LRRC4, MADCAM1, MAL, MAML3, MAX.chr1.6151, MAX.chr1.4676, MAX.chr1.9437, T TC34, MAX.chr1.1120, MAX.chr1.5982, MAX.chr1.5203, TLX1NB, MAX.chr10.0288, MAX.chr10.2081, MAX.chr10.7570, MAX.chr10.1197、NKX6-2_8165、MAX.chr10.9377、MAX.chr10.5150、MAX.chr10.0872、FAM111A-DT、MAX.chr12.7397、MAX.chr12.3032、LINC00943、MAX.chr12.9110、KRT86_2397、MAX.chr12.7375、MAX.chr13.1022、MAX.chr13.1687、LINC00554、SOX1-OT_8239、SOX1-OT_0340、MAX.chr13.2109、OBI1-AS1、LINC00391、MAX.chr14.3769、RAP2CP1_5515、NKX2-8_9022、MAX.chr14.1054、MAX.chr14.6663、MAX.chr14.2697、MAX.chr14.4566、RP11-262A16、MAX.chr17.2359、MAX.chr17.0937、MAX.chr17.8512、MAX.chr17.3547、DLGAP1_4290、SKOR2_3174、SKOR2_7736、MAX.chr18.9881、RP11-714M23.2、RP11-154H12.2、CYP4F23P、CTD-2562J15.6、MAN1A2P1、MAX.chr19.1656、MAX.chr19.4113、MAX.chr19.0870、PANTR1、MAX.chr2.2307、MAX.chr2.6334、RHOQP3、RHOQP2、SLC4A10、SP9_2220、MAX.chr2.6585、LINC01833、MAX.chr2.8149、MAX.chr2.6033、LINC01798、LINC01143、LINC00237、MAX.chr20.8579、MAX.chr20.3480、MAX.chr21.5638、MAX.chr21.7663、ZIC1_9052、MAX.chr3.3606、PTPRG-AS1、NKX1-1_7332、NKX1-1_8822、MAX.chr4.1655、SCRG1_0602、SCRG1_7917、LINC00682、MAX.chr4.4040、MAX.chr4.5903、MAX.chr5.2699、MAX.chr5.1156、LOC100996385、MAX.chr5.3053、MAX.chr5.5180、LINC02106、MAX.chr5.5268、MAX.chr5.4245、MAX.chr5.3918、OSTM1、MAX.chr6.0016、RP4-668J24.2、MAX.chr6.8227、MAX.chr6.3523、MAX.chr7.6951、MAX.chr7.0916、MAX.chr7.8965、MAX.chr7.5395、MAX.chr7.6952、MAX.chr7.6206、MAX.chr7.7860、PDE1C、GATA4_7541、RP11-53M11.5、ERICH1、MAX.chr8.6940、RP11-1102P16.1、MAX.chr8.6725、LINC01388、PRRT1B、MAX.chr9.5748、MAX.chr9.9611、MAX.chr9.9692、MEIS2、MMP23A、MNX1_1549、MYO16、NCRNA00253、NEFM、NEURL、NKX2-3、NKX2-4、NKX2-6、NKX2-8_3188、NKX3-2、NKX6-1、NKX6-2_8699、NOTCH3、NPR3、NPTX2、NPY、NR2E1、NR2F1、NR2F6、NR5A1、NRN1、NRXN1、OLIG2、OLIG3、ONECUT2、OTP、OTUD7A、OTX1、OTX2、OTX2OS1、PACSIN3、PAX1、PAX6、PAX7、PAX9、PCDH17、PCDH8、PCDHGA1、PDX1、PENK、PHYHIPL、PITX1、PITX2、PNPLA1、POU3F3、POU4F2、PPP1R3G、PRDM13、PRDM14、PRRX1、PTF1A、PTPN5、PTPRN2、PTPRU、RARG、RARRES2、RNF220、RXFP3、RYR2、SALL3、SATB2、SCAND3、SDCCAG8、SEMA6A、SEPTIN9、SFTA3、SH3PXD2A、SHE、SHOX2、SIM2、SIX6、SKOR1、SLC2A14、SLC7A14、SOX1、SOX11、SOX14、SOX17、SP8、SP9、SPAG6、SSTR1、ST8SIA3、STAP2、SYCP2L、TBXT、TACC2、TAL1、TBX15、TBX4、TBX5、TFAP2A、TFAP2E、TJP2、TLX3、TMEM132D、TMEM200C、TP73、TRIM58、TWIST1_7883、UNCX、VAX1、VSTM2A、VSX1、VSX2、VWA5B1、ZAR1、ZIC1_7566、ZIC2、ZIC5、ZMIZ1、ZNF521、ADRBK1、AGRN、ALOX5、ARHGAP25、ARHGAP27、ARHGAP30、BCL2L11、CD93、CDC42EP1、EPS15L1、FER1L4、FOSL1、FOXP4、GPR132、GRK6、ITGB4、MAX.chr21.9298、LINC01991、PRIC285、PRKAR1B、PTPN6、PTPRF、RAPGEFL1、RBM38、RHOF、SHH、SKI、TBC1D10C、WNT6、ACSL5、ADAM32、ADAMTS19、ADCY2、AEBP2、AKAP7、ANKRD27、ANKRD43、ANKS1B、ARPM1、BCAN、BMP7、BTBD19、C20orf134、C20orf197、CACNA2D3、CAPN2、CBLN1、CDH22、CTNND2、CYYR1、DGKE、EPOR、EPS8L1、ESPN、FAM38A、FAM83G、FBLIM1、FBN2、FIBP、FOXL1、FXYD5、GP5、GRM6、HOXC4、HS3ST3B1、ICAM4、IL2RA、IRS1、ITPKA、ITPKB、KBTBD11、KCNH3、KCNS1、KCP、KCTD1、LHFPL2、LOC100289410、LOC100499227、LOC402778、LOC645277、LRFN4、LTBP4、LYL1、MACROD1、MAFB、MAST4、LINC01342、MAX.chr1.7620、MAX.chr1.5214、LINC01398、MAX.chr10.0718、GRAMD1B、MAX.chr11.9738、KRT86_2534、MAX.chr13.8267、RAP2CP1_5784、MAX.chr15.0918、MAX.chr16.8889、SOX9-AS1、DLGAP1_4962、MAX.chr19.3071、MAX.chr19.2699、MAX.chr19.0650、MAX.chr2.2345、MAX.chr20.3366、MAX.chr5.3868、MAX.chr6.1793、MAX.chr7.5822、CTD-2168K21.1, FAM163B, MEST, MFNG, MYO15B, N4BP3, NAGS, NCKAP5, NCRNA00245, NETO1, NR2F2, NRG2, OPLAH, PA RVG, PAX2, PDE4D, PEAR1, PLEKHG5, PPFIA4, PPP2R5C, PRDM2, PROX1, PRR14, RGS14, RIMS4, SCARF2, S EZ6L2, SFT2D3, SLC22A20, SNTG1, SOBP, SRCIN1, SYNGR3, TBCD, TMEM154, TNFRSF1B, TRANK1, TTBK1 , UCN, USP2, VAC14, VWA1, VWC2, ZIC4, ZNF783, ZSCAN30, ABHD8, ADHFE1, AGAP3, AKNA, ALDOC, ATP6V1 The gene is derived from a gene selected from B1, B3GALT4, BIN1, VPS9D1, FAM218A, CLDN10, CMTM3, DUSP7, EPS8L2, FAIM2, FSCN1, GMDS, GRK7, HVCN1, IRAK3, KATNAL2, LOC100128239, LOC284454, TPBGL, LRRC8D, LRRFIP1, ST3GAL4, MAX.chr11.8952, RIMBP2, SHISA8, SMPD5_3864, SMPD5_5418, MGA, OXR1, PLEKHA2, RAI1, RASSF1, RCN3, SBNO2, SLC26A5, SPARC, TIGD3, TSPAN33, TSPAN9, WDR90, and ZBED3 (including any combination thereof) (Table 1). In some embodiments, the novel DMR(s) are derived from any gene selected from Table 1 (including any combination thereof). While each novel DMR alone can distinguish between urological cancer and control samples, combining two or more of the novel DMRs may improve sensitivity. Thus, combinations of two or more novel DMRs selected from Table 1 are provided.

[0108] Embodiments of the present disclosure also include novel differentially methylated regions (DMRs), each of which can independently distinguish urothelial cancer (e.g., upper tract urothelial carcinoma (UTUC)) from a control tissue sample (e.g., control urothelial tissue). According to these embodiments, the novel DMR(s) include ACCN1, ADCYAP1, ADRA1A, AGAP1, ALX3, ANKRD35, ARRDC2, ASCL4, BARHL2, BCL11B, TMEM240, C1orf94, C1QL3, ECRG4, CRACDL, NICOL1, IRX2-DT, CACNA1B, CACNA1I, CACNG3, CASR, CBLN4, CCDC140, CDHR5, CDO1, CLDN11, CLEC14A, CMTM1, CNGA3 , CNPY1, CNTNAP5, COL23A1, CRMP1, YBX3P1, CTNNA2, CYP4F2, DBX1, DCHS2, DGCR14, DLX6, DMRT1, DMRTA2, DNMT3A, DSCR6, EBF3, EMX1, EM X2OS, EVX1, EVX2, FBRSL1, FGF14, FLJ31485, FLJ32063, FMN2, FOXA2, FOXB1, FOXD3, FOXD4, FOXE1, FOXF1, FOXG1, FZD8, GAD1, GALR1, GA TA4, GATA6, GBX2, GCM2, GHSR, GRASP, GRIK1, HAS1, HMX2, HOXA11, HOXA7, HOXA9, IGF2BP1, IRF4, IRX1, IRX4, ISL2, JPH4, KCNC2, KCNC4, KCNIP4, KCNQ2, KLF16, LBX2, LHFPL4, LHX1, LHX2, LHX4, LHX5, LIMD2, LOC100131366, LOC154860, LOC285548, LOC400550, LRRC4, MADCA M1, MAL, MAML3, MAX.chr1.6151, MAX.chr1.4676, MAX.chr1.9437, TTC34, MAX.chr1.1120, MAX.chr1.5982, MAX.chr1.5203, TLX1NB, M AX.chr10.0288, MAX.chr10.2081, MAX.chr10.7570, MAX.chr10.1197, NKX6-2_8165, MAX.chr10.9377, MAX.chr10.5150, MAX.chr10.0872、FAM111A-DT、MAX.chr12.7397、MAX.chr12.3032、LINC00943、MAX.chr12.9110、KRT86_2397、MAX.chr12.7375、MAX.chr13.1022、MAX.chr13.1687、LINC00554、SOX1-OT_8239、SOX1-OT_0340、MAX.chr13.2109、OBI1-AS1、LINC00391、MAX.chr14.3769、RAP2CP1_5515、NKX2-8_9022、MAX.chr14.1054、MAX.chr14.6663、MAX.chr14.2697、MAX.chr14.4566、RP11-262A16、MAX.chr17.2359、MAX.chr17.0937、MAX.chr17.8512、MAX.chr17.3547、DLGAP1_4290、SKOR2_3174、SKOR2_7736、MAX.chr18.9881、RP11-714M23.2、RP11-154H12.2、CYP4F23P、CTD-2562J15.6、MAN1A2P1、MAX.chr19.1656、MAX.chr19.4113、MAX.chr19.0870、PANTR1、MAX.chr2.2307、MAX.chr2.119616334-119616553、RHOQP3、RHOQP2、SLC4A10、SP9_2220、MAX.chr2.6585、LINC01833、MAX.chr2.8149、MAX.chr2.6033、LINC01798、LINC01143、LINC00237、MAX.chr20.8579、MAX.chr20.3480、MAX.chr21.5638、MAX.chr21.7663、ZIC1_9052、MAX.chr3.3606、PTPRG-AS1、NKX1-1_7332、NKX1-1_8822、MAX.chr4.1655、SCRG1_0602、SCRG1_7917、LINC00682、MAX.chr4.4040、MAX.chr4.5903、MAX.chr5.2699、MAX.chr5.1156、LOC100996385、MAX.chr5.3053、MAX.chr5.5180、LINC02106、MAX.chr5.5268、MAX.chr5.4245、MAX.chr5.3918、OSTM1、MAX.chr6.0016、RP4-668J24.2、MAX.chr6.8227、MAX.chr6.3523、MAX.chr7.6951、MAX.chr7.0916、MAX.chr7.8965、MAX.chr7.5395、MAX.chr7.6952、MAX.chr7.6206、MAX.chr7.7860、PDE1C、GATA4_7541、RP11-53M11.5、ERICH1、MAX.chr8.6940、RP11-1102P16.1、MAX.chr8.6725、LINC01388、PRRT1B、MAX.chr9.5748、MAX.chr9.9611、MAX.chr9.9692, MEIS2, MMP23A, MNX1_1549, MYO16, NCRNA00253, NEFM, NEURL, NKX2-3, NKX2-4, NKX2-6, NKX2-8_3188, NKX3-2, N KX6-1, NKX6-2_8699, NOTCH3, NPR3, NPTX2, NPY, NR2E1, NR2F1, NR2F6, NR5A1, NRN1, NRXN1, OLIG2, OLIG3, ONECUT2, OTP , OTUD7A, OTX1, OTX2, OTX2OS1, PACSIN3, PAX1, PAX6, PAX7, PAX9, PCDH17, PCDH8, PCDHGA1, PDX1, PENK, PHYHIPL, PITX 1, PITX2, PNPLA1, POU3F3, POU4F2, PPP1R3G, PRDM13, PRDM14, PRRX1, PTF1A, PTPN5, PTPRN2, PTPRU, RARG, RARRES2, RNF 220, RXFP3, RYR2, SALL3, SATB2, SCAND3, SDCCAG8, SEMA6A, SEPTIN9, SFTA3, SH3PXD2A, SHE, SHOX2, SIM2, SIX6, SKOR1 , SLC2A14, SLC7A14, SOX1, SOX11, SOX14, SOX17, SP8, SP9, SPAG6, SSTR1, ST8SIA3, STAP2, SYCP2L, TBXT, TACC2, TAL1, T BX15, TBX4, TBX5, TFAP2A, TFAP2E, TJP2, TLX3, TMEM132D, TMEM200C, TP73, TRIM58, TWIST1_7883, UNCX, VAX1, VSTM2A, VSX1, VSX2, VWA5B1, ZAR1, ZIC1_7566, ZIC2, ZIC4, ZIC5, ZMIZ1, and ZNF521 (Table 2), including any combination thereof. In some embodiments, the novel DMR(s) are derived from any gene selected from Table 2, including any combination thereof. While each novel DMR alone can distinguish between urological cancer and control samples, combining two or more of the novel DMRs may improve sensitivity. Accordingly, combinations of two or more novel DMRs selected from Table 2 are provided.

[0109] Embodiments of the present disclosure also include novel differentially methylated regions (DMRs), each of which can individually distinguish renal cell carcinoma (e.g., papillary RCC, clear cell RCC, and chromophobe RCC) from control samples (e.g., control kidney tissue samples and / or control buffy coat samples). According to these embodiments, the novel DMR(s) include ACSL5, ADAM32, ADAMTS19, ADCY2, AEBP2, AGRN, AKAP7, ANKRD27, ANKRD43, ANKS1B, ARPM1, BCAN, BMP7, BTBD19, C1QL3, C20orf134, C20orf197, CACNA2D3, CAPN2, CBLN1, CDH22, COL23A1, CTNND2, CYYR1, DGKE, EPOR, EPS8L1, ESPN, FAM38A, FAM83G, FBLIM1, FBN2, FIBP, FOSL1, FOXL1, FXYD5, GP5, GRM6, HOXC4, HS3ST3B1, ICAM4, IL2RA, IRS1, ITPKA, ITPKB, KBTBD11, KCNH3, KCNS1, KCP, KCTD1, LHFPL2, LOC100289410, LOC1 00499227, LOC402778, LOC645277, LRFN4, LTBP4, LYL1, MACROD1, MAFB, MAST4, LINC01342, MAX.chr1.7620, MAX .chr1.5214, LINC01398, MAX.chr10.0718, GRAMD1B, MAX.chr11.9738, KRT86_2534, MAX.chr13.8267, RAP2CP1 _5784, MAX.chr15.0918, MAX.chr16.8889, SOX9-AS1, DLGAP1_4962, MAX.chr19.3071, MAX.chr19.2699, MAX.c hr19.0650, MAX.chr2.2345, MAX.chr20.3366, MAX.chr5.3868, MAX.chr6.1793, MAX.chr7.5822, CTD-2168K21.1, FAM163B, MEST, MFNG, MYO15B, N4BP3, NAGS, NCKAP5, NCRNA00245, NETO1, NR2F2, NRG2, ONECUT2, OPLAH, PA RVG, PAX2, PDE4D, PEAR1, PENK, PLEKHG5, PPFIA4, PPP2R5C, PRDM2, PROX1, PRR14, PTPRF, RBM38, RGS14, RIMS4 , SCARF2, SEZ6L2, SFT2D3, SHH, SLC22A20, SNTG1, SOBP, SRCIN1, SYNGR3, TACC2, TBCD, TMEM154, TNFRSF1B, TR ANK1, TRIM58, TTBK1, UCN, USP2, VAC14, VWA1, VWC2, ZIC4, ZNF783, ZSCAN30, ABHD8, ADHFE1, AGAP3, AKNA, ALD OC, ATP6V1B1, B3GALT4, BIN1, VPS9D1, FAM218A, CLDN10, CMTM3, DUSP7, EMX1, EPS8L2, FAIM2, FSCN1, GMDS, G RK7, HVCN1, IRAK3, KATNAL2, LHX1, LOC100128239, LOC284454, TPBGL, LRRC8D, LRRFIP1, ST3GAL4, MAX.chr11 .8952, RIMBP2, SHISA8, SMPD5_3864, SMPD5_5418, MGA, OXR1, PLEKHA2, RAI1, RASSF1, RCN3, SBNO2, SKI, SLC26A5, SPARC, TIGD3, TSPAN33, TSPAN9, WDR90, ZBED3, and ZMIZ1 (Tables 4 and 5), and any combination thereof. In some embodiments, the novel DMR(s) are derived from any gene selected from Table 4 or 5, including any combination thereof. While each novel DMR alone can distinguish between urological cancer and control samples, combining two or more of the novel DMRs in Table 4 and / or Table 5 may improve sensitivity. Accordingly, combinations of two or more novel DMRs selected from Table 4 and / or Table 5 are provided.

[0110] As described in the preceding examples, experiments were conducted to identify DMRs (also referred to herein as methylated DNA markers (MDMs)) that can distinguish between types and subtypes of urological cancer and controls (e.g., healthy or benign samples). These experiments involved validation studies of the utility and performance of a panel of methylated DNA markers for detecting one or more types or subtypes of urological cancer by testing an independent set of case / control samples with the refined marker panel. As a result of such experiments, MDMs were identified that are useful for simultaneously detecting the presence of multiple types of urological cancer (e.g., renal cell carcinoma (RCC), including papillary RCC, clear cell RCC, and chromophobe RCC, and urothelial cell carcinoma (UCC), including upper tract urothelial carcinoma (UTUC)) from control samples.

[0111] In some embodiments, the control sample includes a sample from a subject without cancer (e.g., a benign sample), a sample from a subject without urological cancer, a sample from a subject with a type of cancer that is not urological cancer, a sample from a subject without urothelial carcinoma, a sample from a subject without renal cell carcinoma, a sample from a subject with a urological cancer that is not urothelial carcinoma, or a sample from a subject with a urological cancer that is not renal cell carcinoma. In some embodiments, the control sample includes a sample from a subject with RCC, but in which at least 50% of the organs from which the sample was taken are tumor-free (e.g., at least 50% of the kidneys from a subject with RCC are tumor-free). In some embodiments, the control sample is derived from a tissue sample, blood sample, plasma sample, serum sample, whole blood sample, buffy coat sample, secretion sample, organ secretion sample, cerebrospinal fluid (CSF) sample, saliva sample, urine sample, or stool sample. In some embodiments, the control sample is derived from urinary system or urothelial tissue, including one or more of kidney cells or tissue, bladder cells or tissue, renal pelvis cells or tissue, urethral cells or tissue, and ureteral cells or tissue.

[0112] In some embodiments, the present disclosure provides compositions and methods for identifying, determining, and / or classifying multiple types or subtypes of urological cancer from a biological sample. The methods generally involve determining a methylation profile of at least one methylation marker from a biological sample isolated from a subject. In some embodiments, changes in the methylation status or profile of the markers indicate the presence, class, or location of a particular type of urological cancer. Generally, such methods are useful for detecting the presence or absence of a particular type or subtype of urological cancer. In some embodiments, types and subtypes of urological cancer include, but are not limited to, renal cell carcinoma (RCC), including papillary RCC, clear cell RCC, and chromophobe RCC, and urothelial cell carcinoma (UCC), including urothelial carcinoma (UTUC). In some embodiments, the methods are useful for detecting the presence or absence of oncocytoma.

[0113] In some embodiments, a method is provided that includes contacting nucleic acid (e.g., genomic DNA) in a biological sample obtained from a subject with at least one reagent or set of reagents that distinguish between methylated and unmethylated nucleotides (e.g., CpG dinucleotides) in at least one methylation marker, to detect the presence or absence of one or more types or subtypes of urological cancer (e.g., provided with a sensitivity of 80% or greater and a specificity of 80% or greater).

[0114] In some embodiments, methods are provided that 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 a reagent that modifies the DNA in a methylation-specific manner, thereby determining the methylation levels of the one or more genes or methylation markers.

[0115] In some embodiments, methods are provided that include measuring the amount of one or more methylated DNA markers or genes in DNA of a biological sample, measuring the amount of at least one reference marker in the DNA, and calculating a value for the amount of the at least one methylation marker gene measured in the DNA as a percentage of the amount of the reference marker gene measured in the DNA, wherein the value represents the amount of the at least one methylation marker DNA measured in the biological sample.

[0116] In some embodiments, methods are provided that include measuring the methylation level of CpG sites of one or more genes in a biological sample from a human individual by treating genomic DNA in the biological sample with bisulfite, a reagent that can modify DNA in a methylation-specific manner, amplifying the modified genomic DNA using a set of primers for one or more selected genes, and determining the methylation level of CpG sites of the selected one or more genes.

[0117] In some embodiments, the present disclosure provides a method for characterizing a biological sample from a human individual, comprising measuring one or both methylation levels of CpG sites of one or more genes in the biological sample by treating genomic DNA in the biological sample with bisulfite, amplifying the bisulfite-treated genomic DNA using a set of primers for one or more selected genes, and determining the methylation levels of the CpG sites. In some embodiments, the method comprises comparing the methylation levels of one or both of the methylation markers with the methylation levels of the corresponding set of genes in a control sample that does not have the particular type of cancer, and / or determining that the subject has one or more types or subtypes of urological cancer if one or both of the methylation levels measured for the one or more genes are higher than the methylation levels measured in the respective control sample.

[0118] In some embodiments, the present disclosure provides methods that include one or all of measuring the methylation level 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 one or more selected genes, and determining the methylation level of the one or more genes or markers.

[0119] In some embodiments, the present disclosure provides methods of screening for one or more types or subtypes of urological cancer in a sample obtained from a subject. According to these embodiments, the methods include one or both of assaying the methylation status or profile of one or more methylated DNA markers and identifying the subject as having one or more types or subtypes of urological cancer if the methylation status or profile of the markers differs from the methylation status or profile of the markers assayed in a subject who does not have one or more types of cancer.

[0120] In some embodiments, the disclosure provides methods for measuring the methylation level of one or more genes or markers in a biological sample from a human individual by treating genomic DNA in the biological sample with a reagent that modifies the DNA in a methylation-specific manner, amplifying the treated genomic DNA using a set of primers for selected one or more genes or markers, and determining the methylation level of the one or more genes or markers.

[0121] In some embodiments, the present disclosure provides methods for characterizing a biological sample, comprising: a) measuring the amount of at least one methylated DNA marker in DNA extracted from the biological sample; treating genomic DNA in the biological sample with bisulfite; and amplifying the bisulfite-treated genomic DNA with primers specific for CpG sites of each marker, wherein the primers specific for each marker are capable of binding to amplicons bounded by the primer sequences of marker genes listed in Tables 6, 8, and 14, and the amplicons bounded by the primer sequences of marker genes listed in Tables 6, 8, and 14 are at least a portion of a gene region of a methylated marker gene listed in Tables 1, 2, or 3; and determining the methylation level of the CpG sites for one or more genes.

[0122] 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 urological 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 with primers specific for 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 of a chromosomal region of a marker listed in Table 1, 2, or 3, and measuring the methylation level of the one or more methylation markers.

[0123] 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 urological 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 with primers specific for 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 of a chromosomal region of a marker listed in Table 1, and measuring the methylation level of the one or more methylation markers.

[0124] 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 urological 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 with primers specific for 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 of a chromosomal region of a marker listed in Table 2, and measuring the methylation level of the one or more methylation markers.

[0125] 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 urological 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 with primers specific for 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 of a chromosomal region of a marker listed in Table 3, and measuring the methylation level of the one or more methylation markers.

[0126] 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 one or more CpG sites of methylated DNA markers, and measuring the methylation level of each CpG site of the one or more markers.

[0127] In some embodiments, the present disclosure provides methods for preparing a DNA fraction from a biological sample of a human individual, useful for analyzing one or more genetic loci involved in one or more chromosomal abnormalities. According to these embodiments, the method includes extracting genomic DNA from the biological sample of the human individual, treating the extracted genomic DNA with a reagent that modifies DNA in a methylation-specific manner to generate a fraction of extracted genomic DNA, amplifying the bisulfite-treated genomic DNA using separate primers specific for one or more methylated DNA markers, and analyzing one or more genetic loci in the generated fraction of extracted genomic DNA by measuring the methylation level of CpG sites for each of the one or more markers.

[0128] In some embodiments, the present disclosure provides methods for preparing a DNA fraction from a biological sample of a human individual, the DNA fraction being useful for analyzing one or more DNA fragments involved in one or more chromosomal abnormalities. According to these embodiments, the method includes extracting genomic DNA from the biological sample of the human individual, treating the extracted genomic DNA with a reagent that modifies DNA in a methylation-specific manner to generate a fraction of extracted genomic DNA, amplifying the bisulfite-treated genomic DNA using separate primers specific for one or more methylated DNA markers, and analyzing one or more DNA fragments in the generated fraction of extracted genomic DNA by measuring the methylation level of each CpG site of the one or more markers.

[0129] As will be understood by those of skill in the art based on the present disclosure, the various methods described herein are not limited to the use of any one particular methylated DNA marker, methylation marker gene, methylation gene, and / or DMR. That is, one or more of the methylated DNA markers, methylation marker genes, methylation genes, and / or DMRs disclosed herein can be used to distinguish and / or identify one or more types or subtypes of urological cancer (including any combination thereof). Furthermore, the methylated DNA markers, methylation marker genes, methylation genes, and / or DMRs disclosed herein can include regions or subregions (e.g., genes on chromosomes, single nucleotides, CpG islands, etc.) of any of the markers listed in Tables 1, 2, and 3.

[0130] In some embodiments, the DMR is derived from a gene selected from ADRBK1, AGRN, ALOX5, ARHGAP25, ARHGAP27, ARHGAP30, BCL2L11, CD93, CDC42EP1, EPS15L1, FER1L4, FOSL1, FOXP4, GPR132, GRK6, ITGB4, MAX.chr21.9298, LINC01991, PRIC285, PRKAR1B, PTPN6, PTPRF, RAPGEFL1, RBM38, RHOF, SHH, SKI, TBC1D10C, and WNT6 (Table 3), and the subject has or is suspected of having urothelial carcinoma (e.g., upper tract urothelial carcinoma (UTUC)). In some embodiments, determining the methylation profile of the DMR comprises comparing the methylation profile to a corresponding region of a control DNA sample (e.g., control urothelial tissue or a control buffy coat sample). In some embodiments, the novel DMR(s) are derived from any gene selected from Table 3, including any combination thereof. While each novel DMR alone can distinguish between urological cancer and control samples, combining two or more of the novel DMRs may improve sensitivity. Thus, combinations of two or more novel DMRs selected from Table 3 are provided.

[0131] In some embodiments, the DMR is derived from a gene selected from CRACDL, ANKRD35, DLX6, MAX.chr8.6725, SP9, SOX1-OT_8239, Septin9, LBX2, SIM2, and RAP2CP1_5515 (Table 15), and the subject has or is suspected of having urothelial cancer (e.g., upper tract urothelial carcinoma (UTUC)). In some embodiments, determining the methylation profile of the DMR comprises comparing the methylation profile to a corresponding region of a control DNA sample (e.g., control urothelial tissue or a control buffy coat sample). In some embodiments, the novel DMR(s) is derived from any gene selected from Table 15 (including any combination thereof). Each novel DMR alone can distinguish between urological cancer and control samples, and combining two or more of the novel DMRs may improve sensitivity. Accordingly, combinations of two or more novel DMRs selected from Table 15 are provided.

[0132] In some embodiments, the DMR is from a gene selected from ALOX5, ANKRD35, ARRDC2, CRACDL, YBX3P1, DLX6, FOXD4, FOXP4, GRASP, HOXA7, LBX2, LHX4, MAX.chr10.5150, FAM111A-DT, MAX.chr12.7397, RAP2CP1_5784, MAX.chr8.6725, PACSIN3, PDX1, RAPGEFL1, RARG, RBM38, SDCCAG8, SEMA6A, SEPTIN, SH3PXD2A, SIM2, SP9, TAL1, TJP2 (Tables 6 and 7), and the subject has or is suspected of having urothelial cancer (e.g., upper tract urothelial carcinoma (UTUC)). In some embodiments, determining the methylation profile of the DMR comprises comparing the methylation profile to a corresponding region of a control DNA sample (e.g., a control urothelial tissue or a control buffy coat sample). In some embodiments, the novel DMR(s) are derived from any gene selected from Table 6 or 7 (including any combination thereof). While each novel DMR alone can distinguish between urological cancer and control samples, combining two or more of the novel DMRs in Table 6 and / or Table 7 may improve sensitivity. Accordingly, combinations of two or more novel DMRs selected from Table 6 and / or Table 7 are provided.

[0133] In some embodiments, the DMR is from a gene selected from ALOX5, CRACDL, FOXP4, RBM38, SEPTIN9, SIM2, SP9, and TJP2 (Tables 6 and 7), and the subject has or is suspected of having urothelial cancer (e.g., upper tract urothelial carcinoma (UTUC)). In some embodiments, determining the methylation profile of the DMR comprises comparing the methylation profile to a corresponding region of a control DNA sample (e.g., control urothelial tissue or a control buffy coat sample). In some embodiments, the novel DMR(s) is from any gene selected from Table 6 or 7 (including any combination thereof). While each novel DMR alone can distinguish between urological cancer and control samples, combining two or more of the novel DMRs in Table 6 and / or Table 7 may improve sensitivity. Accordingly, combinations of two or more novel DMRs selected from Table 6 and / or Table 7 are provided.

[0134] In some embodiments, the DMR(s) capable of distinguishing urothelial carcinoma from control samples are associated with an area under the ROC curve (AUC) of 0.5 or greater, where the ROC curve distinguishes between subjects having or suspected of having UTUC and control DNA samples. In some embodiments, the DMR(s) capable of distinguishing urothelial carcinoma from control samples are associated with an area under the ROC curve (AUC) of 0.6 or greater, where the ROC curve distinguishes between subjects having or suspected of having UTUC and control DNA samples. In some embodiments, the DMR(s) capable of distinguishing urothelial carcinoma from control samples are associated with an area under the ROC curve (AUC) of 0.7 or greater, where the ROC curve distinguishes between subjects having or suspected of having UTUC and control DNA samples. In some embodiments, the DMR(s) capable of distinguishing urothelial carcinoma from control samples are associated with an area under the ROC curve (AUC) of 0.8 or greater, where the ROC curve distinguishes between subjects having or suspected of having UTUC and control DNA samples. In some embodiments, a DMR(s) that can distinguish urothelial carcinoma from control samples is associated with an area under the ROC curve (AUC) of 0.9 or greater, where the ROC curve distinguishes between subjects having or suspected of having UTUC and control DNA samples.

[0135] In some embodiments, the DMR(s) that can distinguish urothelial carcinoma from a control sample have a high methylation rate compared to a control DNA sample. In some embodiments, the DMR(s) that can distinguish urothelial carcinoma from a control sample have a high hypermethylation rate compared to a control DNA sample.

[0136] In some embodiments, the DMRs are ACSL5, ADAMTS19, AEFP2, ANKRD27, ANNKS1B.r1, ARPM1, BCAN, C1QL3, CBLN1, CTNND2, ESPN, FOSL1, GP5, HOXC4, HS3ST3B1, IRS1, ITPKA, ITPKB, LOC100289410, LRFN4, LTBP4, LYL1, MAST4, MAX.chr1.5214, GRAMD1B, RAP2CP1_5784, MAX.chr15.0918, MA Derived from a gene selected from X.chr16.8889, MAX.chr19.3071, MAX.chr2.2345, MAX.chr20.3366, MFNG, Myo15B, NAGS, NCRNA00245, NRG2, OPLAH, PAX2, PDE4D, PLEKHG5, PPFIIA4, PPP2R5C, PRDM2, RGS14, SFT2D3, SHH, SLC22A20, TMEM154, TRANK1, TRIM58, USP2, VWC2, and ZNF783 (Table 8). In some embodiments, the novel DMR(s) are from a gene selected from ACSL5, BCAN, C1QL3, CBLN1, CTNND2, ESPN, FOSL1, GP5, HS3ST3B1, IRS1, ITPKA, ITPKB, LOC100289410, LTBP4, LYL1, MAST4, GRAMD1B, MAX.chr15.0918, MAX.chr16.8889, MFNG, Myo15B, NAGS, NCRNA00245, OPLAH, PAX2, PDE4D, PPFIA4, PPP2R5C, PRDM2, PRDM2, SFT2D3, SFT2D3, TMEM154, TRIM58, USP2, and VWC2 (Table 13), and the subject has or is suspected of having renal cell carcinoma. In some embodiments, determining the methylation profile of the DMR comprises comparing the methylation profile to a corresponding region of a control DNA sample (e.g., a control kidney tissue sample and / or a control buffy coat sample).In some embodiments, the novel DMR(s) are from a gene selected from C1QL3, OXR1, ANKS1B, CMTM3, LINC01398, FBLIM1, VPS9D1, LRRC8D_9548, HVCN1, SFT2D3, FAM83G, LOC100128239, LHX1, GRAMD1B, TSPAN33, PDE4D, LOC100289410, TTBK1, PRDM2, CLDN10, MAST4, MACROD1, and KCNH3. In some embodiments, the novel DMR(s) are from a gene selected from MAST4, KCNH3, GRAMD1B, and LOC100289410. In some embodiments, the novel DMR(s) are from a gene selected from at least one DMR from a gene selected from MAST4, KCNH3, GRAMD1B, and PDE4D. In some embodiments, the novel DMR(s) are from any gene selected from Table 8 or 13, including any combination thereof. While each novel DMR alone can distinguish between urological cancer and control samples, combining two or more of the novel DMRs in Table 8 and / or Table 13 may improve sensitivity. Thus, combinations of two or more novel DMRs selected from Table 8 and / or Table 13 are provided.

[0137] In some embodiments, the DMR is from a gene selected from ACSL5, ADAMTS19, ANNKS1B, BCAN, C1QL3, CBLN1, CTNND2, ESPN, GP5, HOXC4, HS3ST3B1, IRS1, ITPKB, LOC100289410, LRFN4, LTBP4, LYL1, MAST4, MAX.chr1.5214, GRAMD1B, MAX.chr15.0918, MAX.chr2.2345, MYO15B, NCRNA00245, PAX2, PDE4D, PLEKHG5, PPFIA4, PPP2R5C, PRDM2, RGS14, SHH, SLC22A20, TMEM154, TRIM58, and VWC2 (Table 11). In some embodiments, the novel DMR(s) are derived from a gene selected from ACSL5, C1QL3, ESPN, IRS1, ITPKB, LOC100289410, LYL1, MAST4, GRAMD1B, MAX.chr2.2345, PAX2, PDE4D, and TMEM154 (Table 11), and the subject has or is suspected of having papillary renal cell carcinoma (pRCC). In some embodiments, determining the methylation profile of the DMR comprises comparing the methylation profile to a corresponding region of a control DNA sample (e.g., a control kidney tissue sample and / or a control buffy coat sample). In some embodiments, the novel DMR(s) are derived from any gene selected from Table 11 (including any combination thereof). Each novel DMR alone can distinguish between urological cancer and control samples, and combining two or more of the novel DMRs may improve sensitivity. Accordingly, combinations of two or more novel DMRs selected from Table 11 are provided.

[0138] In some embodiments, the DMR is from a gene selected from ACSL5, ADAMTS19, ANNKS1B, BCAN, C1QL3, CBLN1, CTNND2, ESPN, GP5, HOXC4, HS3ST3B1, IRS1, ITPKB, LOC100289410, LRFN4, LTBP4, LYL1, MAST4, MAX.chr1.5214, GRAMD1B, MAX.chr15.0918, MAX.chr2.2345, MYO15B, NCRNA00245, PAX2, PDE4D, PLEKHG5, PPFIA4, PPP2R5C, PRDM2, RGS14, SHH, SLC22A20, TMEM154, TRIM58, and VWC2 (Table 12). In some embodiments, the novel DMR(s) are derived from a gene selected from ACSL5, CTNND2, ESPN, HS3ST3B1, ITPKB, LOC100289410, LTBP4, LYL1, MAST4, GRAMD1B, MAX.chr2.2345, MYO15B, PAX2, PDE4D, PLEKHG5, PPFIA4, PPP2R5C, PRDM2, TMEM154, and VWC2 (Table 12), and the subject has or is suspected of having clear cell renal cell carcinoma (ccRCC). In some embodiments, determining the methylation profile of the DMR comprises comparing the methylation profile to a corresponding region of a control DNA sample (e.g., a control kidney tissue sample and / or a control buffy coat sample). In some embodiments, the novel DMR(s) are derived from any gene selected from Table 12 (including any combination thereof). While each novel DMR alone can distinguish urological cancer from control samples, combining two or more of the novel DMRs may improve sensitivity. Thus, combinations of two or more novel DMRs selected from Table 12 are provided.

[0139] In some embodiments, the DMR is from a gene selected from AESBP2, ANKRD27, ARPM1, FOSL1, ITPKA, RAP2CP1_5784, MAX.chr16.8889, MAX.chr19.3071, MAX.chr20.3366, MFNG, NAGS, NRG2, OPLAH, PAX2, PRDM2, SFT2D3, TRANK1, USP2, and ZNF783 (Table 10). In some embodiments, the novel DMR(s) are derived from a gene selected from ACSL5, C1QL3, ESPN, GPS, LRFN4, LTBP4, LYL1, MAST4, GRAMD1B, MAX.chr2.2345, PAX2, PDE4D, PRDM2, RGS14, TMEM154, VWC2, FOSL1, ITPKA, MAX.chr16.8889, MFNG, NAGS, and OPLAH (Table 10), and the subject has or is suspected of having chromophobe renal cell carcinoma (chRCC). In some embodiments, determining the methylation profile of the DMR comprises comparing the methylation profile to a corresponding region of a control DNA sample (e.g., a control kidney tissue sample and / or a control buffy coat sample). In some embodiments, the novel DMR(s) are derived from any gene selected from Table 10 (including any combination thereof). While each novel DMR alone can distinguish urological cancer from control samples, combining two or more of the novel DMRs may improve sensitivity. Thus, combinations of two or more novel DMRs selected from Table 10 are provided.

[0140] In some embodiments, DMR(s) capable of distinguishing renal cell carcinoma from control samples are associated with an area under the ROC curve (AUC) of 0.5 or greater, where the ROC curve distinguishes between subjects having or suspected of having renal cell carcinoma and control DNA samples. In some embodiments, DMR(s) capable of distinguishing renal cell carcinoma from control samples are associated with an area under the ROC curve (AUC) of 0.6 or greater, where the ROC curve distinguishes between subjects having or suspected of having renal cell carcinoma and control DNA samples. In some embodiments, DMR(s) capable of distinguishing renal cell carcinoma from control samples are associated with an area under the ROC curve (AUC) of 0.7 or greater, where the ROC curve distinguishes between subjects having or suspected of having renal cell carcinoma and control DNA samples. In some embodiments, DMR(s) capable of distinguishing renal cell carcinoma from control samples are associated with an area under the ROC curve (AUC) of 0.8 or greater, where the ROC curve distinguishes between subjects having or suspected of having renal cell carcinoma and control DNA samples. In some embodiments, a DMR(s) that can distinguish renal cell carcinoma from control samples is associated with an area under the ROC curve (AUC) of 0.9 or greater, where the ROC curve distinguishes between subjects having or suspected of having renal cell carcinoma and control DNA samples.

[0141] In some embodiments, the DMR(s) that can distinguish renal cell carcinoma from a control sample have a high methylation rate compared to a control DNA sample. In some embodiments, the DMR(s) that can distinguish renal cell carcinoma from a control sample have a high hypermethylation rate compared to a control DNA sample.

[0142] Embodiments of the present disclosure provide methods, compositions, and systems for screening for oncocytoma from a biological sample. In some embodiments, the DMRs include ACSL5, ADAMTS19, ANNKS1B, BCAN, C1QL3, CBLN1, CTNND2, ESPN, GP5, HOXC4, HS3ST3B1, IRS1, ITPKB, LOC100289410, LRFN4, LTBP4, LYL1, MAST4, MAX.chr1.5214, GRAMD1B, MAX.chr15.0918, MAX.chr2.2345, MYO15B, NCRNA00245, PAX2, PDE4D, PLEKHG5, PPF Derived from a gene selected from IA4, PPP2R5C, PRDM2, RGS14, SHH, SLC22A20, TMEM154, TRIM58, VWC2, AEBP2, ANKRD27, ARPM1, FOSL1, ITPKA, RAP2CP1_5784, MAX.chr16.8889, MAX.chr19.3071, MAX.chr20.3366, MFNG, NAGS, NRG2, OPLAH, PAX2, PRDM2, SFT2D3, TRANK1, USP2, and ZNF783 (Table 9). In some embodiments, the novel DMR(s) are derived from a gene selected from AESBP2, ANKRD27, ARPM1, FOSL1, ITPKA, RAP2CP1_5784, MAX.chr16.8889, MAX.chr19.3071, MAX.chr20.3366, MFNG, NAGS, NRG2, OPLAH, PAX2, PRDM2, SFT2D3, TRANK1, USP2, and ZNF783 (Table 9), and the subject has or is suspected of having renal oncocytoma (e.g., RO). In some embodiments, determining the methylation profile of the DMR comprises comparing the methylation profile to a corresponding region of a control DNA sample (e.g., a control urinary tissue or a control buffy coat sample). In some embodiments, the novel DMR(s) are derived from any gene selected from Table 9 (including any combination thereof). Each novel DMR alone can distinguish urological cancer from control samples, and combining two or more of the novel DMRs may improve sensitivity.Thus, combinations of two or more novel DMRs selected from Table 9 are provided.

[0143] In some embodiments, the DMR(s) that can distinguish oncocytoma from control samples are associated with an area under the ROC curve (AUC) of 0.5 or greater, where the ROC curve distinguishes between subjects having or suspected of having oncocytoma and control DNA samples. In some embodiments, the DMR(s) that can distinguish oncocytoma from control samples are associated with an area under the ROC curve (AUC) of 0.6 or greater, where the ROC curve distinguishes between subjects having or suspected of having oncocytoma and control DNA samples. In some embodiments, the DMR(s) that can distinguish oncocytoma from control samples are associated with an area under the ROC curve (AUC) of 0.7 or greater, where the ROC curve distinguishes between subjects having or suspected of having oncocytoma and control DNA samples. In some embodiments, the DMR(s) that can distinguish oncocytoma from control samples are associated with an area under the ROC curve (AUC) of 0.8 or greater, where the ROC curve distinguishes between subjects having or suspected of having oncocytoma and control DNA samples. In some embodiments, the DMR(s) that can distinguish oncocytoma from control samples are associated with an area under the ROC curve (AUC) of 0.9 or greater, where the ROC curve distinguishes between subjects having or suspected of having oncocytoma and control DNA samples.

[0144] In some embodiments, the DMR(s) that can distinguish oncocytoma from a control sample have a high methylation rate compared to a control DNA sample. In some embodiments, the DMR(s) that can distinguish oncocytoma from a control sample have a high hypermethylation rate compared to a control DNA sample.

[0145] 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 (e.g., Tables 6, 8, and 14). 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, flap endonuclease assay, PCR flap assay, and bisulfite genomic sequencing PCR. In some embodiments, determining the methylation profile of at least one DMR comprises determining the presence or absence of methylation at CpG sites. In some embodiments, the one or more CpG sites are present in a coding region, a non-coding region, and / or a regulatory region of a gene (e.g., any one of the genes disclosed herein). In some embodiments, the DMR(s) that can distinguish urological cancer from control samples can be validated using 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. In some embodiments, the DMR(s) that can distinguish urological cancer from control samples can be assessed based on at least one of the area under the receiver operating characteristic curve (AUC) between the test sample and the control sample, the fold change in methylation, the methylation ratio, and / or the hypermethylation ratio.

[0146] As will be appreciated by those skilled in the art based on the present disclosure, one or more types or subtypes of urological cancer can be predicted by various combinations of markers (e.g., identified by statistical methods related to the specificity and sensitivity of the prediction). Embodiments of the present disclosure provide methods for identifying predictive combinations and validated predictive combinations for one or more types or subtypes of urological cancer.

[0147] Such methods are not limited to a particular modality or technique for determining the methylation characterization, measurement, or assay for 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 of at least one marker, marker region, or marker base (e.g., CpG methylation status) that comprises a DMR.

[0148] In some embodiments, measuring the methylation state or profile of a methylated DNA marker in a sample comprises determining the methylation state of a single nucleotide base. In some embodiments, measuring the methylation state of a methylated DNA marker in a sample comprises determining the degree of methylation at multiple nucleotide bases. Further, in some embodiments, the methylation state or profile of a methylated DNA marker comprises an increase in methylation of the marker relative to the marker's normal methylation state or profile. In some embodiments, the methylation state or profile of a marker comprises a decrease in methylation of the marker relative to the marker's normal methylation state. In some embodiments, the methylation state or profile of a marker comprises a different pattern of methylation of the marker compared to the marker's normal methylation state or profile.

[0149] Further, in some embodiments, the marker is a region of 100 or fewer nucleotide bases. In some embodiments, the marker is a region of 500 or fewer nucleotide bases. In some embodiments, the marker is a region of 1000 or fewer nucleotide bases. In some embodiments, the marker is a region of 5000 or fewer nucleotide bases. In some embodiments, the marker is one nucleotide base. In some embodiments, the marker is within a high CpG density promoter region.

[0150] In certain embodiments, methods for analyzing nucleic acids for the presence of 5-methylcytosine include treating DNA with reagents that modify 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.

[0151] A frequently used method for analyzing nucleic acids for the presence of 5-methylcytosine is based on the bisulfite method described by Frommer et al. for detecting 5-methylcytosine or its mutations in DNA (Frommer et al. (1992) Proc. Natl. Acad. Sci. USA 89:1827-31, expressly incorporated herein by reference in its entirety for all purposes). The bisulfite method for mapping 5-methylcytosine is based on the finding that cytosine, but not 5-methylcytosine, reacts with hydrogen sulfite ions (also known as bisulfite). The reaction is typically carried out according to the following steps: first, cytosine reacts with bisulfite to form sulfonated cytosine; second, spontaneous deamination of the sulfonated reaction intermediate results in sulfonated uracil; and finally, the sulfonated uracil is desulfonated under alkaline conditions to form uracil. Detectability is possible because uracil base pairs with adenine (and thus behaves like thymine), whereas 5-methylcytosine base pairs with guanine (and therefore behaves like cytosine). This allows methylated cytosines to be distinguished from unmethylated cytosines, for example, by bisulfite genomic sequencing (Grigg G, & 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 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).

[0152] In some embodiments, conventional techniques involve 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 the precipitation and purification steps with high-speed dialysis (Olek A, et al. (1996) "A modified and improved method for bisulfite-based cytosine methylation analysis" Nucleic Acids Res. 24:5064-6). Thus, it is possible to analyze individual cells for methylation status, demonstrating the utility and sensitivity of the method. An overview of conventional methods for detecting 5-methylcytosine is provided by Rein, T., et al. (1998) Nucleic Acids Res. 26:2255.

[0153] Bisulfite methods generally involve bisulfite treatment followed by amplification of short, specific fragments of known nucleic acids, followed by assay of the products by sequencing (Olek & Walter (1997) Nat Genet. 17:275-6) or primer extension reactions (Gonzalgo & 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 & Laird (1997) Nucleic Acids Res. 25:2532-4). Hybridization detection has also been described in the art (Olek et al., WO 99 / 28498). Additionally, the use of bisulfite techniques for methylation detection of individual genes has been described (Grigg & 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; WO9515373).

[0154] Various methylation assay techniques can be used in conjunction with bisulfite treatment according to the techniques of the present invention. These assays allow for the determination of the methylation status of one or more CpG dinucleotides (e.g., CpG islands) within a nucleic acid sequence. Such assays involve, among other techniques, sequencing of bisulfite-treated nucleic acids, PCR (for sequence-specific amplification), Southern blot analysis, and the use of methylation-specific enzymes, e.g., methylation-sensitive or methylation-dependent enzymes.

[0155] For example, genome sequencing has been simplified for the analysis of methylation patterns and 5-methylcytosine distribution by using bisulfite treatment (Frommer et al. (1992) Proc. Natl. Acad. Sci. USA 89:1827-1831). Furthermore, restriction enzyme digestion of PCR products amplified from bisulfite-converted DNA can be used to assess methylation status, as described, for example, in Sadri & Hornsby (1997) Nucl. Acids Res. 24:5058-5059, or as implemented in a method known as COBRA (Combined Bisulfite Restriction Analysis) (Xiong & Laird (1997) Nucleic Acids Res. 25:2532-2534).

[0156] The COBRA™ analysis is a quantitative methylation assay useful for determining DNA methylation levels at specific loci in small amounts of genomic DNA (Xiong & Laird, Nucleic Acids Res. 25:2532-2534, 1997). Briefly, restriction enzyme digestion is used to reveal methylation-dependent sequence differences in PCR products of sodium bisulfite-treated DNA. Methylation-dependent sequence differences are first introduced into genomic DNA by standard bisulfite treatment according to the procedure described by Frommer et al. (Proc. Natl. Acad. Sci. USA 89:1827-1831, 1992). PCR amplification of the bisulfite-converted DNA is then performed using primers specific for the CpG island of interest, followed by restriction endonuclease digestion, gel electrophoresis, and a specifically labeled hybridization probe. Methylation levels in the original DNA sample are represented by the relative amounts of digested and undigested PCR products, providing a linear method for quantitating a wide range of DNA methylation levels. In addition, this method can be reliably applied to DNA obtained from microdissected paraffin-embedded tissue samples.

[0157] Typical reagents for COBRA™ analysis (e.g., as might be found in a typical COBRA™-based kit) can include, but are not limited to: PCR primers for specific loci (e.g., specific genes, markers, DMRs, regions of genes, regions of markers, bisulfite-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. Additionally, bisulfite conversion reagents can include DNA denaturing buffers; sulfonation buffers; DNA recovery reagents or kits (e.g., precipitation, ultrafiltration, affinity columns); desulfonation buffers; and DNA recovery components.

[0158] Assays such as "MethyLight™" (fluorescence-based real-time PCR technology) (Eads et al., Cancer Res. 59:2302-2306, 1999), Ms-SNuPE™ (methylation-sensitive single nucleotide primer extension) reactions (Gonzalgo & 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. Patent No. 5,786,146), and methylated CpG island amplification ("MCA"; Toyota et al., Cancer Res. 59:2307-12, 1999) are used alone or in combination with one or more of these methods.

[0159] The "HeavyMethyl™" assay technique is a quantitative method for assessing methylation differences based on methylation-specific amplification of bisulfite-treated DNA. Methylation-specific inhibitor probes ("inhibitors") covering CpG positions between or covered by the amplification primers allow for methylation-specific selective amplification of the sample.

[0160] The term "HeavyMethyl™ MethyLight™" assay refers to the HeavyMethyl™ MethyLight™ assay, which is a variation of the MethyLight™ assay in which the MethyLight™ assay is combined with a methylation-specific blocking probe that covers the CpG positions between the amplification primers. The HeavyMethyl™ assay can also be used in combination with methylation-specific amplification primers.

[0161] Typical reagents for HeavyMethyl analysis (e.g., as found in a typical MethyLight™-based kit) include, but are not limited to, PCR primers for specific loci (e.g., specific genes, markers, gene regions, marker regions, bisulfite-treated DNA sequences, CpG islands, or bisulfite-treated DNA sequences or CpG islands, etc.); blocking oligonucleotides; optimized PCR buffers and deoxynucleotides; and Taq polymerase.

[0162] MSP (methylation-specific PCR) allows for the assessment of the methylation status of virtually all CpG sites within a CpG island, regardless of 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, which converts unmethylated cytosines, but not methylated cytosines, to uracil, and these products are then amplified with primers specific for methylated versus unmethylated DNA. MSP requires only small amounts of DNA, is sensitive to 0.1% methylated alleles of a given CpG island locus, and can be performed on DNA extracted from paraffin-embedded samples. Typical reagents for MSP analysis (e.g., as found in a typical MSP-based kit) include, but are not limited to, methylated and unmethylated PCR primers for specific loci (e.g., specific genes, markers, gene regions, marker regions, bisulfite-treated DNA sequences, CpG islands, etc.); optimized PCR buffers and deoxynucleotides, and specific probes.

[0163] The MethyLight™ assay is a high-throughput quantitative methylation assay that utilizes fluorescence-based real-time PCR (e.g., TaqMan®) and requires no further manipulation after the PCR step (Eads et al., Cancer Res. 59:2302-2306, 1999). Briefly, the MethyLight™ process begins with a mixed sample of genomic DNA that is converted into a mixed pool of methylation-dependent sequence differences in a sodium bisulfite reaction according to standard procedures (the bisulfite process converts unmethylated cytosine residues to uracil). Fluorescence-based PCR is then performed in a "biased" reaction, e.g., with PCR primers that overlap known CpG dinucleotides. Sequence discrimination occurs both at the level of the amplification process and at the level of the fluorescence detection process.

[0164] The MethyLight™ assay is used as a quantitative test for methylation patterns in nucleic acids, e.g., genomic DNA samples, in which sequence discrimination occurs at the level of probe hybridization. In the quantitative version, PCR reactions result in methylation-specific amplification in the presence of fluorescent probes that overlap specific putative methylation sites. An unbiased control for input DNA amount is provided by reactions in which neither the primers nor the probe overlap any CpG dinucleotides. Alternatively, quantitative tests for genomic methylation are achieved by probing biased PCR pools with either control oligonucleotides that do not cover known methylation sites (e.g., fluorescent-based versions of the HeavyMethyl™ and MSP techniques) or oligonucleotides that cover potential methylation sites.

[0165] The MethyLight™ process can be used with any suitable probe (e.g., TaqMan® probe, Lightcycler® probe). For example, in some applications, double-stranded genomic DNA is treated with sodium bisulfite and subjected to one of two sets of PCR reactions, using, for example, a TaqMan® probe with MSP primers and / or a HeavyMethyl inhibitor oligonucleotide and a TaqMan® probe. The TaqMan® probe is dual-labeled with fluorescent "reporter" and "quencher" molecules and is designed to be specific for relatively GC-rich regions, so that it melts during PCR cycles at a temperature approximately 10°C higher than the forward or reverse primers. This allows the TaqMan® probe to remain fully hybridized during the PCR annealing / extension step. Taq polymerase enzymatically synthesizes new strands during PCR, ultimately reaching the annealed TaqMan® probe. Taq polymerase 5' to 3' endonuclease activity then displaces the TaqMan® probe by digesting it, releasing a fluorescent reporter molecule for quantitative detection of its unquenched signal using a real-time fluorescence detection system.

[0166] Typical reagents for MethyLight™ analysis (e.g., as found in a typical MethyLight™-based kit) include, but are not limited to, PCR primers for specific loci (e.g., specific genes, markers, gene regions, marker regions, bisulfite-treated DNA sequences, CpG islands, etc.); TaqMan® or Lightcycler® probes; optimized PCR buffers and deoxynucleotides, and Taq polymerase.

[0167] The QM™ (Quantitative Methylation) Assay is an alternative quantitative test for methylation patterns in genomic DNA samples, in which sequence discrimination occurs at the level of probe hybridization. In this quantitative version, PCR reactions result in unbiased amplification in the presence of fluorescent probes that overlap specific putative methylation sites. An unbiased control for input DNA amount is provided by reactions in which neither the primers nor the probe overlap any CpG dinucleotides. Alternatively, quantitative testing for genomic methylation is achieved by probing biased PCR pools with either control oligonucleotides that do not cover known methylation sites (fluorescence-based versions of HeavyMethyl™ and MSP techniques) or oligonucleotides that cover potential methylation sites.

[0168] The QM™ process can be used with any suitable probe, such as a TaqMan® probe, a Lightcycler® probe, or the like, in the amplification process. For example, double-stranded genomic DNA is treated with sodium bisulfite and subjected to unbiased primers and a TaqMan® probe. The TaqMan® probe is dual-labeled with fluorescent reporter and quencher molecules and is designed to be specific for relatively GC-rich regions, so it melts during PCR cycles at a temperature approximately 10°C higher than the forward or reverse primers. This allows the TaqMan® probe to remain fully hybridized during the PCR annealing / extension step. Taq polymerase enzymatically synthesizes new strands during PCR, eventually reaching the annealed TaqMan® probe. The 5' to 3' endonuclease activity of Taq polymerase then displaces the TaqMan® probe by digesting it, releasing a fluorescent reporter molecule for quantitative detection of its unquenched signal using a real-time fluorescence detection system. Typical reagents for QM™ analysis (e.g., as found in a typical QM™-based kit) include, but are not limited to, PCR primers for specific loci (e.g., specific genes, markers, gene regions, marker regions, bisulfite-treated DNA sequences, CpG islands, etc.); TaqMan® or Lightcycler® probes; optimized PCR buffers and deoxynucleotides; and Taq polymerase.

[0169] The SNuPE™ technique is a quantitative method that involves single-base primer extension, based on bisulfite treatment of DNA to assess differences in methylation at specific CpG sites (Gonzalgo & Jones, Nucleic Acids Res 25:2529-2531, 1997). Briefly, genomic DNA is reacted with sodium bisulfite to convert unmethylated cytosine to uracil, while leaving 5-methylcytosine unchanged. Next, PCR primers specific to the bisulfite-converted DNA are used to amplify the desired target sequence, and the resulting product is isolated and used as a template for methylation analysis at the CpG sites of interest. This allows for the analysis of small amounts of DNA (e.g., microdissected pathology slices), avoiding the use of restriction enzymes to determine the methylation status at CpG sites.

[0170] Typical reagents for Ms-SNuPE™ analysis (e.g., as found in a typical Ms-SNuPE™-based kit) include, but are not limited to, PCR primers for specific loci (e.g., specific genes, markers, gene regions, marker regions, bisulfite-treated DNA sequences, CpG islands, etc.); optimized PCR buffers and deoxynucleotides; gel extraction kits; positive control primers; Ms-SNuPE™ primers for specific loci; reaction buffers (for the Ms-SNuPE reaction); and labeled nucleotides. Additionally, bisulfite conversion reagents can include DNA denaturing buffers; sulfonation buffers; DNA recovery reagents or kits (e.g., precipitation, ultrafiltration, affinity columns); desulfonation buffers; and DNA recovery components.

[0171] Reduced representation bisulfite sequencing (RRBS) begins with bisulfite treatment of nucleic acids to convert all unmethylated cytosines to uracils, followed by restriction enzyme digestion (e.g., with an enzyme that recognizes sites containing CG sequences, such as Mspl) and coupling to an adaptor ligand, completing the sequencing of the fragments. The choice of restriction enzyme enriches for fragments in CpG-dense regions, reducing the number of redundant sequences that may map to multiple gene locations during analysis. As such, RRBS reduces the complexity of the nucleic acid sample by selecting a subset of restriction fragments for sequencing (e.g., by size selection using preparative gel electrophoresis). In contrast to whole-genome bisulfite sequencing, all fragments generated by restriction enzyme digestion contain DNA methylation information for at least one CpG dinucleotide. As such, RRBS enriches samples for promoters, CpG islands, and other genomic features, frequently restriction enzyme cleavage sites in these regions, providing an assay to assess the methylation status of one or more genomic loci.

[0172] A typical protocol for RRBS includes the steps of digesting a nucleic acid sample with a restriction enzyme such as MspI, filling in overhangs and A-tailing, adapter ligation, bisulfite conversion, and PCR (see, e.g., 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).

[0173] In some embodiments, quantitative allele-specific real-time target and signal amplification (QuARTS) assays are used to assess methylation status. Each QuARTS assay involves three sequential reactions: a primary reaction involving amplification (reaction 1) and target probe cleavage (reaction 2), and a secondary reaction involving FRET cleavage and fluorescent signal generation (reaction 3). When a 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, such as FEN-1 endonuclease, to cleave the gap between the detection probe and the flap sequence, thereby releasing the flap sequence. The flap sequence is complementary to the non-hairpin portion of the corresponding FRET cassette. Thus, the flap sequence functions as an invasive oligonucleotide on the FRET cassette, resulting in cleavage between the FRET cassette fluorophore and quencher, generating a fluorescent signal. The cleavage reaction can cleave multiple probes per target, thereby releasing multiple fluorophores per flap, resulting in exponential signal amplification. QuARTS can detect multiple targets in a single reaction well by using FRET cassettes 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 by reference herein for all purposes.

[0174] The term "bisulfite reagent" refers to a reagent containing bisulfite, disulfite, hydrogen sulfite, or a combination thereof, useful for distinguishing between methylated and unmethylated CpG dinucleotide sequences, as disclosed herein. Methods for such 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 bisulfite treatment is carried out in the presence of a denaturing solvent, such as, but not limited to, n-alkylene 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 of 1% to 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, e.g., 6-hydroxy-2,5,7,8-tetramethylchroman-2-carboxylic acid or trihydroxybenzoic acid, and derivatives thereof, e.g., gallic acid (see PCT / EP2004 / 011715, incorporated herein by reference in its entirety). In certain preferred embodiments, the bisulfite reaction involves treatment with ammonium bisulfite, e.g., as described in WO2013 / 116375.

[0175] In some embodiments, fragments of the treated DNA are amplified using a set of primer oligonucleotides (see, e.g., Tables 6, 8, and 14) and an amplification enzyme according to the methods and compositions described herein. Amplification of several DNA segments can be performed simultaneously in one reaction vessel, and in the same reaction vessel. Typically, amplification is performed using the polymerase chain reaction (PCR). Amplicons are typically 100-2000 base pairs in length.

[0176] In some embodiments of the method, the methylation status or profile of CpG positions within or near differentially methylated regions (e.g., Tables 1, 2, and 3) may be detected using methylation-specific primer oligonucleotides. This technique (MSP) is described in U.S. Patent No. 6,265,171 to Herman. The use of methylation-status-specific primers for amplification of bisulfite-treated DNA allows differentiation between methylated and unmethylated nucleic acids. An MSP primer pair contains at least one primer that hybridizes to a bisulfite-treated CpG dinucleotide. Thus, the primer sequence contains at least one CpG dinucleotide. MSP primers specific for unmethylated DNA contain a "T" at the C position in the CpG.

[0177] Such methods are not limited to a particular type or kind of primer or primer pair associated with one or more methylation markers, methylation marker genes, genes, DMRs, and / or methylated DNA markers. In some embodiments, the primers or primer pairs are listed in Tables 6, 8, and 14 (SEQ ID NOs: 1-242). In some embodiments, a primer or primer pair specific to each methylation marker gene can bind to an amplicon bounded by the primer sequences of the marker genes listed in Tables 6, 8, and 14, and the amplicon bounded by the primer sequences of the marker genes listed in Tables 6, 8, and 14 is at least a portion of a gene region of a methylation marker gene listed in Tables 1, 2, or 3. In some embodiments, the primer or primer pair for a methylation marker is a primer set that specifically binds to at least a portion of a gene region containing a particular methylation marker.

[0178] In another embodiment, the present disclosure provides a method for converting oxidized 5-methylcytosine residues in cell-free DNA to dihydrouracil residues (see Liu et al., 2019, Nat Biotechnol. 37, pp. 424-429; U.S. Patent Application Publication No. 202000370114). The method comprises reacting an oxidized 5mC residue selected from 5-formylcytosine (5fC), 5-carboxymethylcytosine (5caC), and combinations thereof with a borane reducing agent. The oxidized 5mC residue may be naturally occurring or, more typically, may result from prior oxidation of a 5mC or 5hmC residue, e.g., oxidation of 5mC or 5hmC by a TET family enzyme (e.g., TET1, TET2, or TET3), or chemical oxidation of 5mC or 5hmC (see, e.g., Okamato et al. (2011) Chem. Commun. 47:11231-33), e.g., using an inorganic peroxo compound or composition such as potassium perruthenate (KRuO) or peroxotungstate and a combination of copper(II) perchlorate / 2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO) (see, e.g., Matsushita et al. (2017) Chem. Commun. 53:5756-59).

[0179] The borane reducing agent can be characterized as a complex of borane and a nitrogen-containing compound selected from a nitrogen heterocycle and a tertiary amine. The nitrogen heterocycle can be monocyclic, bicyclic, or polycyclic, but is typically a monocyclic ring in the form of a five- or six-membered ring containing a nitrogen heteroatom and, optionally, one or more additional heteroatoms selected from N, O, and S. The nitrogen heterocycle can 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, t-butyl and the like. Exemplary compounds include, but are not limited to, borane, pyridine borane, 2-methylpyridine borane (also known as 2-picoline borane or pic-BH), 5-ethyl-2-pyridine, sodium borohydride, sodium cyanoborohydride, sodium triacetoxyborohydride, diborane, decaborane, borane-tetrahydrofuran, borane-dimethylsulfide, borane-N,N-diisopropylethylamine, borane-2-chloropyridine, borane-aniline, N,N-dimethylamine borane, tert-butylamine borane, sodium triacetoxyborohydride, borane hydride, hydrazine or dibutylamine borane, morpholine borane, borane-ammonia complex (BHNH), dicyclohexylamine borane, morpholine borane, 4-methylmorpholine borane, alkali and tetramethylamine borane (e.g., NaBH) and other -BH-containing complexes and / or derivatives. In some embodiments, the reducing agent is pyridine borane and / or pic-BH3.

[0180] The reaction of oxidized 5mC residues in cell-free DNA with borane reducing agents is advantageous insofar as it utilizes nontoxic reagents and mild reaction conditions, eliminating the need for hydrogen sulfate or other reagents that may degrade DNA. Furthermore, the conversion of oxidized 5mC residues to dihydrolauracils with borane reducing agents can be carried out in a "one-pot" or "one-tube" reaction without the need for isolation of intermediates. This is crucial because this conversion involves multiple steps: (1) reduction of the alkene bond connecting C-4 and C-5 of oxidized 5mC, (2) deamination, and (3) either decarboxylation if the oxidized 5mC is 5caC or deformylation if the oxidized 5mC is 5fC.

[0181] In addition to a method for converting oxidized 5-methylcytosine residues in cell-free DNA to dihydrouracil residues, the present disclosure also provides a reaction mixture related to the aforementioned method. The reaction mixture includes a sample of cell-free DNA containing at least one oxidized 5-methylcytosine residue selected from 5caC, 5fC, and combinations thereof, and a borane reducing agent effective in reducing, deaminating, and decarboxylating or deformylating the at least one oxidized 5-methylcytosine residue. As explained above, the borane reducing agent is a complex of borane and a nitrogen-containing compound selected from nitrogen heterocycles and tertiary amines. In a preferred embodiment, the reaction mixture is substantially bisulfite-free, meaning that it is substantially free of bisulfite ions and bisulfite salts. Ideally, the reaction mixture is free of bisulfite salts.

[0182] In a related aspect of the present disclosure, a kit for converting 5mC residues in cell-free DNA to dihydrouracil residues is provided, the kit including a reagent for blocking 5mC 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 practice the method.

[0183] In another embodiment, a method utilizing the above-described oxidation reaction is provided, which can detect the presence and location of 5-methylcytosine residues in cell-free DNA, and includes the following steps: (a) modifying 5hmC residues in fragmented, adaptor-ligated cell-free DNA to provide affinity tags thereon (the affinity tags enable removal of the modified 5hmC-containing DNA from the cell-free DNA), (b) removing the modified 5hmC-containing DNA from the cell-free DNA to leave DNA containing unmodified 5mC residues, and (c) oxidizing the unmodified 5mC residues to form 5caC, (d) contacting the DNA containing the oxidized 5mC residues with a borane reducing agent effective to reduce, deaminate, and 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 from the sequencing results of (e).

[0184] 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 containing the target nucleic acid; modifying the target nucleic acid by converting 5mC and 5hmC in the nucleic acid sample to 5-carboxylcytosine (5caC) and / or 5-formylcytosine (5fC) to generate one or more 5caC or 5fC residues by contacting the nucleic acid sample with a TET enzyme; treating the target nucleic acid with a borane reducing agent to convert the 5caC and / or 5fC to dihydrouracil (DHU) to provide a modified nucleic acid sample containing the modified target nucleic acid; and detecting the sequence of the modified target nucleic acid, wherein a cytosine (C) to thymine (T) transition or a cytosine (C) to DHU transition in the sequence of the modified target nucleic acid indicates the location of either a 5mC or a 5hmC in the target nucleic acid, relative to the target nucleic acid. In some embodiments, the borane reducing agent is 2-picoline borane.

[0185] In some embodiments, detecting the sequence of the modified target nucleic acid comprises 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 blocking one or more modified cytosines. In some embodiments, the blocking comprises adding a sugar to 5hmC. In some embodiments, the method further comprises amplifying the copy number of one or more nucleic acid sequences. In some embodiments, the oxidizing agent is potassium perruthenate or Cu(II) / TEMPO (2,2,6,6-tetramethylpiperidine-1-oxyl).

[0186] Cell-free DNA is typically extracted from a subject's biological sample, which may be whole blood, buffy coat, plasma, urine, saliva, mucosal discharge, organ secretions, sputum, stool, or tears. In some embodiments, the cell-free DNA is derived from a tumor (e.g., a urological tumor). In other embodiments, the cell-free DNA is derived from a patient with a disease or other pathological condition. The cell-free DNA may or may not be derived from a tumor. In some embodiments, the cell-free DNA modified at 5hmC residues is purified, fragmented, and adapter-ligated. DNA purification in this regard can be performed using any suitable method known to those skilled in the art and / or described in the relevant literature. The cell-free DNA itself may be highly fragmented, although further fragmentation may be desirable in some cases, as described, for example, in U.S. Patent Publication No. 2017 / 0253924. Cell-free DNA fragments generally range in size from about 20 nucleotides to about 500 nucleotides, more typically from about 20 nucleotides to about 250 nucleotides. The purified cell-free DNA fragments modified in step (a) are end-repaired using conventional means (e.g., restriction enzymes) to ensure that the fragments have blunt ends at each 3' and 5' end. In a preferred method, as described in WO 2017 / 176630, the blunted fragments are also provided with 3' overhangs containing a single adenine residue using a polymerase such as Taq polymerase. This facilitates subsequent ligation of a selected universal adapter, i.e., a Y adapter or hairpin adapter, which ligates to both ends of the cell-free DNA fragments and contains at least one molecular barcode. The use of adapters also allows for selective PCR enrichment of adapter-ligated DNA fragments.

[0187] In some embodiments, "purified fragmented cell-free DNA" includes adaptor-ligated DNA fragments. The 5hmC residues of these cell-free DNA fragments are modified with an affinity tag to enable subsequent removal of the modified 5hmC-containing DNA 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, or biocytin. The use of a biotin moiety as an affinity tag facilitates removal with streptavidin (e.g., streptavidin beads, magnetic streptavidin beads, etc.).

[0188] Tagging of 5hmC residues with biotin moieties or other affinity tags is achieved by covalently attaching a chemoselective group to the 5hmC residues in the DNA fragment, which can react with a functionalized affinity tag to attach the affinity tag to the 5hmC residue. In one embodiment, the chemoselective group is UDP-glucose-6-azide, which undergoes spontaneous 1,3-cycloaddition 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, addition of the alkyne-functionalized biotin moiety results in the covalent attachment of the biotin moiety to each 5hmC residue.

[0189] The affinity-tagged DNA fragments can then be removed, in one embodiment, using streptavidin, in the form of streptavidin beads, magnetic streptavidin beads, etc., and saved for later analysis if desired. The supernatant remaining after removal of the affinity-tagged fragments contains DNA with unmodified 5mC residues but no 5hmC residues.

[0190] In some embodiments, unmodified 5mC residues are oxidized to yield 5caC and / or 5fC residues using any suitable means. The oxidizing agent is selected to oxidize the 5mC residue beyond hydroxymethylation, i.e., to yield 5caC and / or 5fC residues. Oxidation may be performed enzymatically using a catalytically active TET family enzyme. The terms "TET family enzyme" or "TET enzyme" as used herein refer to a catalytically active "TET family protein" or "TET catalytically active fragment," as defined in U.S. Pat. No. 9,115,386, the disclosure of which is incorporated herein by reference. A preferred TET enzyme in this regard is TET2 (see Ito et al. (2011) Science 333(6047):1300-1303). Oxidation may also be performed chemically using a chemical oxidizing agent, 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 (KRuO), tetraalkylammonium perruthenates such as tetrapropylammonium perruthenate (TPAP) and tetrabutylammonium perruthenate (TBAP), and polymer-supported perruthenate (PSP); and inorganic peroxo compounds and compositions such as peroxotungstate or a combination of copper(II) perchlorate / TEMPO. Separation of 5fC-containing fragments from 5caC-containing fragments is not necessary at this point, as long as both 5fC and 5caC residues are converted to dihydrouracil (DHU) in the next step of the process. In some embodiments, 5-hydroxymethylcytosine residues are blocked with β-glucosyltransferase (β3GT), while 5-methylcytosine residues are oxidized with a TET enzyme, which is effective in providing a mixture of 5-formylcytosine and 5-carboxymethylcytosine. A mixture containing both of these oxidized species can be reacted with 2-picoline borane or another borane reducing agent to give dihydrouracil.

[0191] In a variation of this embodiment, 5hmC-containing fragments are not removed. Instead, "TET-assisted picoline borane sequencing (TAPS)" enzymatically oxidizes 5mC-containing and 5hmC-containing fragments together to yield 5fC-containing and 5caC-containing fragments. Reaction with 2-picoline borane generates DHU residues where the 5mC and 5hmC residues originally resided. In "chemically assisted picoline borane sequencing (CAPS)," 5hmC-containing fragments are selectively oxidized with potassium perruthenate, leaving the 5mC residues unchanged. As disclosed in International PCT Application PCT / US2019 / 012627 (incorporated herein by reference in its entirety), TAPS involves the use of mild enzymatic and chemical reactions to directly detect 5mC and 5hmC quantitatively at base resolution without affecting unmodified cytosines. In a related embodiment, the method further comprises identifying hydroxymethylation patterns in the 5hmC-containing DNA removed from the cell-free DNA. This can be done using the techniques described in detail in WO 2017 / 176630. This process can be performed in a one-tube manner without intermediate removal or isolation. For example, cell-free DNA fragments, preferably adapter-ligated DNA fragments, are first functionalized with βGT-catalyzed uridine diphosphoglucose 6-azide and then biotinylated with a chemoselective azide group. This procedure covalently attaches biotin to each 5hmC site. In the next step, the biotinylated strands and strands containing unmodified (native) 5mC are simultaneously removed for further processing. The native 5mC-containing strands are removed using an anti-5mC antibody or a methyl-CpG binding domain (MBD) protein, as is well known to those skilled in the art. With the 5hmC residues blocked, unmodified 5mC residues are then selectively oxidized using any suitable technique for converting 5mC to 5fC and / or 5caC, as described elsewhere herein.

[0192] These fragments obtained by amplification can have directly or indirectly detectable labels.In some embodiments, these labels are fluorescent labels, radionuclides, or detachable molecular fragments, which have a typical mass that can be detected in mass spectrometer.When these labels are mass labels, some embodiments provide that the labeled amplicons have a single positive or negative effective charge, which allows for better detectability in mass spectrometer.For example, this detection can be performed and visualized by matrix-assisted laser desorption / ionization mass spectrometry (MALDI) or by electron spray mass spectrometry (ESI).

[0193] Methods for isolating DNA suitable for these assay techniques are well known in the art. In particular, some embodiments involve isolating nucleic acids as described in U.S. Patent Application No. 13 / 470,251 ("Isolation of Nucleic Acids"), which is incorporated herein by reference in its entirety.

[0194] In some embodiments, the markers described herein are used in a QUARTS assay performed on a stool sample. In some embodiments, methods are provided for generating DNA samples, particularly DNA samples containing highly purified, low-abundance nucleic acids in small volumes (e.g., less than 100 microliters, less than 60 microliters) that are substantially and / or effectively free of substances that inhibit assays used to test the DNA sample (e.g., PCR, INVADER, QuARTS assays, etc.). Such DNA samples are utilized in diagnostic tests that qualitatively detect the presence or quantitatively measure the activity, expression, or amount of genes, genetic variants (e.g., alleles), or genetic modifications (e.g., methylation) present in a sample collected from a patient. For example, some cancers are correlated with the presence of specific mutant alleles or specific methylation states, and therefore, detection and / or quantification of such mutant alleles or methylation states has predictive value in cancer diagnosis and treatment.

[0195] Many useful genetic markers are present in very small amounts in samples, and many of the events that produce such markers are rare. Therefore, even highly sensitive detection methods such as PCR require a large amount of DNA to provide targets with low abundances sufficient to meet or exceed the detection threshold of the assay. Furthermore, the presence of even a small amount of inhibitors can impair the accuracy and precision of these assays aimed at detecting such low-abundance targets. Therefore, the present specification provides a method for producing such DNA samples, providing the necessary volume and concentration control.

[0196] Such samples can be obtained by any number of means known in the art, as will be apparent to those skilled in the art. Cell-free or substantially cell-free samples can be obtained by subjecting the sample to a variety of techniques known to those skilled in the art, including, but not limited to, centrifugation and filtration. While obtaining samples without the use of invasive techniques is generally preferred, it may still be preferable to obtain samples such as tissue homogenates, tissue sections, and biopsy specimens. The present technology is not limited by the method used to prepare the sample and provide nucleic acids for testing. For example, in some embodiments, DNA is isolated from a sample (e.g., a tissue sample, a blood sample, a plasma sample, a serum sample, a whole blood sample, a buffy coat sample, a secretion sample, an organ secretion sample, a cerebrospinal fluid (CSF) sample, a saliva sample, a urine sample, and / or a stool sample) as detailed in U.S. Pat. Nos. 8,808,990 and 9,169,511 and WO 2012 / 155072, or by related methods.

[0197] Marker analysis can be performed separately or simultaneously with additional markers within a single test sample. For example, it is possible to combine several markers in one test to efficiently process multiple samples and potentially provide higher diagnostic and / or prognostic accuracy. Furthermore, those skilled in the art will recognize the value of testing multiple samples from the same subject (e.g., at successive time points). Testing such serial samples allows for the identification of changes in the methylation status of markers over time. Changes in methylation status, and the absence of changes in methylation status, can provide useful information about disease states, including, but not limited to, identifying the subject's outcome, including the approximate time since the occurrence of this event, the presence and amount of recoverable tissue, the suitability of drug therapy, the effectiveness of various therapies, and the risk of future events.

[0198] Biomarker analysis can be performed in a variety of physical formats. For example, microtiter plates or automated applications can be used to facilitate the processing of large numbers of test samples. Alternatively, single sample formats can be developed to facilitate immediate treatment and diagnosis in a timely manner, for example, in an outpatient or emergency room setting.

[0199] Genomic DNA can be isolated by any means, including the use of commercially available kits. Briefly, if the DNA of interest is encapsulated in a cell membrane, the biological sample must be disrupted 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 done by a variety of methods, such as salting out, organic extraction, or binding of DNA to a solid support. The choice of method is influenced by several factors, including time, cost, and the amount of DNA required. All clinical sample types containing neoplastic or pre-neoplastic material are suitable for use in this method, including cell lines, histological slides, biopsies, paraffin-embedded tissues, body fluids, feces, tissues, colonic effluent, urine, plasma, serum, whole blood, buffy coat, isolated blood cells, cells isolated from blood, and combinations thereof.

[0200] The present technology is not limited to the method used to prepare the sample and provide the nucleic acid for testing.For example, in some embodiments, DNA is isolated from a fecal sample, or from a blood sample, or from a plasma sample, using a direct gene capture method, such as that described in U.S. Patent Application No. 61 / 485386, or by related methods.

[0201] The genomic DNA sample is then treated with at least one reagent, or a series of reagents, that distinguishes between methylated and unmethylated CpG dinucleotides within at least one marker that comprises a DMR (e.g., a DMR (Table 1, 2, or 3)).

[0202] In some embodiments, the reagent converts unmethylated cytosine bases at the 5' position to uracil, thymine, or another base that differs from cytosine in terms of hybridization behavior, although in some embodiments the reagent may be a methylation-sensitive restriction enzyme.

[0203] In some embodiments, genomic DNA samples are treated in such a way that cytosine bases that are not methylated at the 5' position are converted to uracil, thymine, or another base that differs from cytosine in terms of hybridization behavior. In some embodiments, this treatment is carried out with bisulfite (hydrogen sulfite), followed by alkaline hydrolysis.

[0204] The processed 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 at least one DMR, e.g., a DMR selected from the DMRs in Tables 1, 2, or 3). The analytical method can be selected from those known in the art, including those listed herein, e.g., QuARTS and MSP as described herein.

[0205] Such samples can be obtained by any number of means known in the art, as 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, for example, by using a needle and syringe. Cell-free, or substantially cell-free, samples can be obtained by subjecting the sample to a variety of techniques, including, but not limited to, centrifugation and filtration. While it is generally preferred to obtain samples without the use of invasive techniques, it may still be preferable to obtain samples such as tissue homogenates, tissue sections, and biopsy specimens.

[0206] Embodiments of the present disclosure further provide compositions. In some embodiments, the present disclosure provides compositions comprising a DMR-containing nucleic acid and a bisulfite reagent. In some embodiments, compositions are provided comprising a DMR-containing nucleic acid and one or more oligonucleotides set forth in SEQ ID NOS: 1-242. In certain embodiments, compositions are provided comprising a DMR-containing nucleic acid and a methylation-sensitive restriction enzyme. In certain embodiments, compositions are provided comprising a DMR-containing nucleic acid and a polymerase.

[0207] 3. Treatment Method In some embodiments, the present disclosure provides methods for treating a subject (e.g., a patient having or suspected of having one or more types or subtypes of urological cancer). According to these embodiments, the methods include determining the methylation status or profile of one or more methylated DNA markers provided herein and administering a treatment to the patient based on the methylation status determination. The treatment can be administering a pharmaceutical compound, administering a vaccine, performing surgery, imaging the patient, or performing another test. In some embodiments, treating a subject includes methods of clinical screening, prognostic evaluation, monitoring treatment outcome, identifying patients most likely to respond to a particular therapeutic treatment, imaging patients or subjects, and methods for drug screening and development.

[0208] 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 a method by which a skilled artisan can estimate, and even determine, whether a subject suffers from a given disease or condition, or whether a subject is likely to develop a given disease or condition in the future. Those skilled in the art often make a diagnosis based on one or more diagnostic indicators, such as one or more biomarkers (e.g., one or more methylation markers, methylation marker genes, genes, DMRs, and / or DNA methylation markers, such as those disclosed herein), where the methylation status of the biomarkers indicates the presence, severity, or absence of the condition.

[0209] In addition to diagnosis, clinical cancer prognosis involves determining the aggressiveness of cancer and the likelihood of tumor recurrence, and planning 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, and in some cases, a less harsh therapy for the patient, can be selected. Assessment of cancer biomarkers (e.g., determining methylation status) is useful for separating subjects with a good prognosis and / or a low risk of developing cancer, who do not require treatment or only limited treatment, from subjects who are more likely to develop cancer or suffer from cancer recurrence, who may benefit from more intensive treatment.

[0210] Thus, "making a diagnosis" or "diagnosing," as used herein, further includes determining the risk of developing cancer or determining a prognosis, which can be provided to predict a clinical outcome (with or without medical treatment), select an appropriate treatment (or whether a treatment is effective), or monitor a current treatment to potentially modify the treatment, based on measurements of the diagnostic biomarkers (e.g., DMRs) disclosed herein. Furthermore, in some embodiments of the presently disclosed subject matter, multiple determinations of biomarkers over time can be made to facilitate diagnosis and / or prognosis. Changes in biomarkers over time can be used to predict clinical outcomes, monitor the progression of cancer or cancer subtypes, and / or monitor the effectiveness of appropriate cancer-directed treatments. In such embodiments, for example, one can expect to see changes in the methylation status of one or more biomarkers (e.g., DMRs) disclosed herein (and potentially one or more additional biomarker(s), if monitored).

[0211] The presently disclosed subject matter further provides, in some embodiments, a method for determining whether to initiate or continue cancer prevention or treatment in a subject. In some embodiments, such a method includes 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 of the biological samples; and comparing measurable changes in the methylation status of the one or more biomarkers in each of the biological samples. 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, or determine whether a current treatment is effectively treating the cancer. For example, a first time point can be selected before treatment begins, and a second time point can be selected sometime after treatment begins. The methylation status can be measured in each of the samples collected at different time points, and qualitative and / or quantitative differences can be noted. Changes in the methylation status of biomarker levels from different samples can be correlated with a particular cancer risk, prognosis, treatment efficacy assessment, and / or cancer progression in the subject. In some embodiments, the disclosed methods and compositions are for the treatment or diagnosis of disease at an early stage, e.g., before disease symptoms appear, hi some embodiments, the disclosed methods and compositions are for the treatment or diagnosis of disease at a clinical stage.

[0212] In some embodiments, multiple determinations of one or more diagnostic or prognostic biomarkers can be performed, and changes in the markers over time can be used to determine a diagnosis or prognosis. For example, a diagnostic marker can be determined a first time and then again a second time. In such embodiments, an increase in a marker from the first time to the second time can be diagnostic of a particular type or severity of cancer, or a given prognosis. Similarly, a decrease in a marker from the first time to the second time can indicate a particular type or severity of cancer, or a given prognosis. Furthermore, the degree of change in one or more markers can be related to the severity of cancer and future adverse events. Those skilled in the art will understand that, in certain embodiments, comparative measurements of the same biomarker can be performed at multiple time points, but a given biomarker can also be measured at one time point and a second biomarker at a second time point, and the comparison of these markers can provide diagnostic information.

[0213] As used herein, the phrase "determining a prognosis" refers to a method by which a person skilled in the art can predict the course or outcome of a condition in a subject. The term "prognosis" does not refer to the ability to predict the course or outcome of a condition with 100% accuracy, or even the ability to predict that a given course or outcome is more or less likely to occur based on the methylation status of a biomarker (e.g., DMR). Instead, a person skilled in the art will understand that the term "prognosis" refers to a high probability of a particular course or outcome occurring, i.e., a high probability of a certain course or outcome occurring in a subject exhibiting a given condition, compared to an individual not exhibiting the condition. For example, an individual not exhibiting a condition (e.g., having a normal methylation status of one or more DMRs) may have a very low probability of a given outcome (e.g., suffering from a particular type of cancer).

[0214] In some embodiments, statistical analysis correlates the prognostic indicator with a predisposition to an adverse outcome. For example, in some embodiments, a methylation status that differs from the methylation status in a normal control sample obtained from a patient without cancer, as determined by a statistical significance level, may indicate that the subject is more likely to suffer from cancer than a subject with a methylation level more similar to that in the control sample. Furthermore, a change in methylation status from baseline (e.g., "normal") levels may reflect the subject's prognosis, and the degree of methylation change may be related to the severity of an adverse event. Statistical significance is often determined by comparing two or more populations to determine a confidence interval and / or p-value. See, e.g., Dowdy and Wearden, Statistics for Research, John Wiley & Sons, New York, 1983, 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%, and exemplary p-values ​​are 0.1, 0.05, 0.025, 0.02, 0.01, 0.005, 0.001, and 0.0001.

[0215] In other embodiments, a threshold degree of change in the methylation status of a prognostic or diagnostic biomarker (e.g., DMR) disclosed herein can be established, and the degree of change in the methylation status of the biomarker in a biological sample is simply compared to the threshold degree of change in methylation status. Preferred threshold changes in the methylation status 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 yet another embodiment, a "nomogram" can be established, whereby the methylation status of a prognostic or diagnostic indicator (biomarker or combination of biomarkers) is directly correlated with the associated predisposition for a given outcome. Those skilled in the art are familiar with the use of such nomograms to relate two values, with the understanding that because measurements are referenced to individual samples rather than population averages, the uncertainty in the measurements is the same as the uncertainty in the marker concentration.

[0216] In some embodiments, a control sample is analyzed simultaneously with the biological sample to allow results obtained from the biological sample to be compared to those obtained from the control sample. It is further contemplated that a calibration curve may be provided to which assay results for the biological sample can be compared. Such a standard curve displays the methylation status of the biomarkers according to assay units, e.g., fluorescent signal intensity if a fluorescent label is used. Samples collected from multiple donors can be used to provide a standard curve of control methylation status of one or more biomarkers in normal tissues, as well as "at risk" levels of one or more biomarkers in plasma collected from donors with a particular type of cancer. In certain embodiments of the method, a subject is identified as having cancer upon identification of an aberrant methylation status of one or more DMRs provided herein in a biological sample obtained from the subject. In other embodiments of the method, detection of an aberrant methylation status of one or more of such biomarkers in a biological sample obtained from the subject identifies the subject as having cancer.

[0217] Marker analysis can be performed separately or simultaneously with additional markers within a single test sample. For example, it is possible to combine several markers in one test to efficiently process multiple samples and potentially provide higher diagnostic and / or prognostic accuracy. Furthermore, those skilled in the art will recognize the value of testing multiple samples from the same subject (e.g., at successive time points). Testing such serial samples allows for the identification of changes in the methylation status of markers over time. Changes in methylation status, and the absence of changes in methylation status, can provide useful information about disease states, including, but not limited to, identifying the subject's outcome, including the approximate time since the occurrence of this event, the presence and amount of recoverable tissue, the suitability of drug therapy, the effectiveness of various therapies, and the risk of future events.

[0218] Biomarker analysis can be performed in a variety of physical formats. For example, microtiter plates or automated applications can be used to facilitate the processing of large numbers of test samples. Alternatively, single sample formats can be developed to facilitate immediate treatment and diagnosis in a timely manner, for example, in an outpatient or emergency room setting.

[0219] In some embodiments, a subject is diagnosed with a particular type of cancer if there is a measurable difference in the methylation status of at least one biomarker in the sample compared to a control methylation status. Conversely, if no change in methylation status is identified in the biological sample, the subject is identified as not having, not at risk for, or at low risk for a particular type of cancer. In this regard, subjects with or at risk for cancer can be distinguished from subjects with or at low risk for cancer as those who are substantially free of cancer. Subjects at risk for developing a particular type of cancer can be placed on a more intensive and / or regular screening schedule. Meanwhile, subjects at low risk to substantially no risk may avoid further testing for cancer risk (e.g., invasive procedures) until future screening, e.g., screening performed according to various embodiments of the present disclosure, indicates that the subject is at risk for cancer.

[0220] As described above, depending on the embodiment of the disclosed methods, detecting a change in the methylation state of one or more biomarkers can be a qualitative or quantitative determination. Thus, diagnosing a subject as having or at risk of developing a particular type of cancer indicates that a certain threshold measurement is made, e.g., that the methylation state of one or more biomarkers in a biological sample differs from a predetermined control methylation state. In some embodiments of the methods, the control methylation state is any detectable methylation state of a biomarker. In other embodiments of the methods, in which a control sample is tested simultaneously with the biological sample, the predetermined methylation state is the methylation state of the control sample. In other embodiments of the methods, the predetermined methylation state is based on and / or identified by a standard curve. In other embodiments of the methods, the predetermined methylation state is a specific state or range of states. Thus, the predetermined methylation state can be selected, within acceptable limits as will be apparent to one skilled in the art, based in part on the embodiment of the method being performed and the desired specificity, etc.

[0221] Further, with respect to diagnostic methods, preferred subjects are vertebrate subjects. Preferred vertebrates are warm-blooded, and preferred warm-blooded vertebrates are mammals. Preferred mammals are most preferably humans. As used herein, the term "subject" includes both human and animal subjects. Accordingly, veterinary uses are provided herein. Accordingly, embodiments of the present disclosure provide for the diagnosis of mammals, such as humans, as well as mammals of endangered importance, such as the Amur tiger, 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, carnivores, such as cats and dogs; swine, including pigs, hogs, and wild boars; ruminants and / or ungulates, such as cows, oxen, sheep, giraffes, deer, goats, bison, and camels; and horses. Thus, diagnostics and treatments for livestock, including but not limited to domestic pigs, ruminants, ungulates, horses (including racehorses), and the like, are also provided.

[0222] 4. Samples, Kits, and Controls Embodiments of the present disclosure provide techniques for screening for multiple types of urological cancer from a biological sample. According to these embodiments, the present disclosure includes, but is not limited to, methods and compositions for detecting the presence of multiple types and / or subtypes of urological cancer from a biological sample. In some embodiments, the biological sample is a tissue sample, a blood sample, a plasma sample, a serum sample, a whole blood sample, a buffy coat sample, a secretion sample, an organ secretion sample, a cerebrospinal fluid (CSF) sample, a saliva sample, a urine sample, and / or a stool sample. In some embodiments, the tissue sample is a urinary system or urothelial tissue sample including one or more of kidney cells or tissue, bladder cells or tissue, renal pelvis cells or tissue, urethral cells or tissue, and ureter cells or tissue. In some embodiments, the tissue sample is a urinary system or urothelial tissue sample including one or more of penile cells or tissue, testicular cells or tissue, and prostate cells or tissue. In some embodiments, the secretion sample is a urinary secretion sample. In some embodiments, the subject is a human.

[0223] In other embodiments, "sample," "test sample," and "biological sample" refer to a fluid sample containing or suspected of containing a methylated DNA marker of the present disclosure. A sample may be derived from any suitable source. In some cases, a sample may include a liquid, a fluid particulate solid, or a solid particle suspension. In some cases, a sample may be processed prior to analysis as described herein. For example, a sample may be separated or purified from its source prior to analysis. In certain examples, the source is a mammalian (e.g., human) bodily substance (e.g., bodily fluid, blood such as whole blood, buffy coat, 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, urinary system or urothelial tissue, including kidney cells or tissue, bladder cells or tissue, renal pelvis cells or tissue, urethral cells or tissue, ureteral cells or tissue, penile cells or tissue, testicular cells or tissue, and prostate cells or tissue. The sample may be a liquid sample or a liquid extract of a solid sample. In some embodiments, the sample source may be an organ or tissue, such as a biopsy sample and / or a secretory sample (e.g., urinary secretions), which may be solubilized by tissue disruption / cell lysis.

[0224] A wide range of fluid sample volumes 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 fluid sample volume is about 0.01 μL to about 10 mL, about 0.01 μL to about 1 mL, about 0.01 μL to about 100 μL, or about 0.1 μL to about 10 μL.

[0225] In some cases, the fluid sample may be diluted before use in the assay. For example, in embodiments where the source containing the methylated DNA marker is a human body fluid (e.g., blood, serum, secretions), the body fluid may be diluted with an appropriate solvent (e.g., a buffer such as PBS buffer). The fluid sample may be diluted about 1-fold, about 2-fold, about 3-fold, about 4-fold, about 5-fold, about 6-fold, about 10-fold, about 100-fold, or more before use. In other cases, the fluid sample is not diluted before use in the assay.

[0226] In some cases, the sample may undergo pre-analysis treatment. Pre-analysis treatment may provide additional functions, such as removal of non-specific proteins and / or effective yet inexpensively implemented mixing functions. Common methods of pre-analysis treatment may include the use of electrokinetic trapping, AC electrokinetics, surface acoustic waves, isotachophoresis, dielectrophoresis, electrophoresis, or other pre-concentration techniques known in the art. In some cases, the fluid sample may be concentrated before use in the assay. For example, in embodiments where the source containing the methylated DNA marker is a human bodily fluid (e.g., blood, serum, secretions), the bodily fluid may be concentrated by precipitation, evaporation, filtration, centrifugation, or a combination thereof. The fluid sample may be concentrated about 1-fold, about 2-fold, about 3-fold, about 4-fold, about 5-fold, about 6-fold, about 10-fold, about 100-fold, or more, prior to use.

[0227] It may be desirable to include a control. The control may be analyzed simultaneously with the sample from the subject, as described above. Results obtained from the subject sample may be compared to results obtained from the control sample. A standard curve may be provided to which the assay results of the sample may be compared. Such a standard curve shows the level of one or more methylated DNA markers as a function of assay units. Samples from multiple donors may be used to provide standard curves for reference levels of methylated DNA markers in normal healthy tissue and "at risk" levels of methylated DNA markers in tissue from donors, who may have one or more characteristics of urological cancer.

[0228] Embodiments of the present disclosure also include kits for carrying out the methods described herein. The kits include embodiments of the compositions, devices, apparatus, etc. described herein, as well as instructions for using the kit. Such instructions describe appropriate methods for preparing an analyte from a sample, e.g., methods for collecting a sample and preparing nucleic acid from the sample. Individual components of the kit are packaged in suitable containers and packaging (e.g., vials, boxes, blister packs, ampoules, jars, bottles, tubes, etc.), and the components are packaged together in suitable containers (e.g., box(es)) for convenient storage, shipping, and / or use by the user of the kit. It is understood that liquid components (e.g., buffers) may be provided in lyophilized form to be reconstituted by the user. The kit may also include controls or references for assessing, validating, and / or ensuring the performance of the kit. For example, a kit for assaying the amount of nucleic acid present in a sample may include a control containing a known concentration of the same or another nucleic acid for comparison, and in some embodiments, a detection reagent (e.g., primers) specific for the control nucleic acid. The kit is suitable for use in a clinical setting and, in some embodiments, for use in the user's home. The components of the kit, in some embodiments, provide the functionality of a system for preparing a nucleic acid solution from a sample. In some embodiments, certain components of the system are provided by the user.

[0229] In some embodiments, the disclosure provides compositions (e.g., reaction mixtures). In some embodiments, the disclosure provides compositions comprising a nucleic acid containing a DMR and a reagent capable of modifying DNA in a methylation-specific manner (e.g., a methylation-sensitive restriction enzyme, a methylation-dependent restriction enzyme, and a bisulfite reagent) (e.g., a methylation-sensitive restriction enzyme, a methylation-dependent restriction enzyme, a ten-eleven translocation (TET) enzyme (e.g., human TET1, human TET2, human TET3, mouse TET1, mouse TET2, mouse TET3, Naegleria TET (NgTET), Coprinopsis cinerea (CcTET)), or a variant thereof), a borane reducing agent). Some embodiments provide compositions comprising a nucleic acid containing a DMR and an oligonucleotide described herein. Some embodiments provide compositions comprising a nucleic acid containing a DMR and a methylation-sensitive restriction enzyme. Some embodiments provide compositions comprising a nucleic acid containing a DMR and a polymerase.

[0230] In some embodiments, the technology described herein is associated with a programmable machine designed to perform an array of arithmetic or logical operations, such as those provided by the methods described herein. For example, some embodiments of the technology are associated with (e.g., implemented in) computer software and / or computer hardware. In one aspect, the technology relates to a computer that includes a form of memory, elements for performing arithmetic and logical operations, and a processing element (e.g., a microprocessor) for executing a set of instructions for reading, manipulating, and storing data (e.g., the methods provided herein). In some embodiments, the microprocessor is part of a system that determines methylation status (e.g., one or more DMRs in Tables 1, 2, or 3), compares methylation status, creates standard curves, measures Ct values, calculates methylation fractions, frequencies, or percentages, identifies CpG islands, determines assay or marker specificity and / or sensitivity, calculates ROC curves and associated AUCs, and performs sequence analysis, all of which are described herein or known in the art. In some embodiments, the microprocessor is part of a system that determines methylation status (e.g., one or more DMRs in Tables 1, 2, or 3), compares methylation status, generates standard curves, measures Ct values, calculates methylation rates, frequencies, or percentages, identifies CpG islands, determines assay or marker specificity and / or sensitivity, calculates ROC curves and associated AUCs, and performs sequence analysis, all of which are described herein or known in the art.

[0231] In some embodiments, a software or hardware component receives the results of multiple assays, determines a single-value result, and reports it to a user indicating cancer risk based on the results of the multiple assays (e.g., determining the methylation status of one or more DMRs in Table 1, 2, or 3). Related embodiments calculate a risk factor based, for example, on a mathematical combination (e.g., weighted combination, linear combination) of the results of the multiple assays (e.g., determining the methylation status of one or more DMRs in Table 1, 2, or 3). In some embodiments, the methylation status of the DMRs defines a dimension and can have values ​​in a multidimensional space, and the coordinate defined by the methylation status of the multiple DMRs is a result (e.g., for reporting to a user or related to cancer risk).

[0232] Various embodiments of the present disclosure involve multiple programmable devices operating in cooperation to perform the methods as described herein. For example, in some embodiments, multiple computers (e.g., connected by a network) can operate in parallel to collect and process data, for example, in an implementation of cluster computing or grid computing or some other distributed computing architecture that relies on complete computers (on-board CPU, storage, power, network interfaces, etc.) being connected to a network (private, public, or the Internet) by traditional network interfaces such as Ethernet, fiber optics, etc., or by wireless networking technology.

[0233] 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. Processors such as these may include microprocessors, ASICs, state machines, or other processors, and may be any of a number of computer processors, such as processors from Intel Corporation of Santa Clara, California, or Motorola Corporation of Schaumburg, Illinois. Processors such as these may include or be in communication with a medium, such as a computer-readable medium, that stores instructions that, when executed by the processor, cause the processor to perform the steps described herein.

[0234] In some embodiments, the computer is connected to a network. The computer may also include multiple external or internal devices, such as a mouse, CD-ROM, DVD, keyboard, display, or other input or output devices. Examples of computers include personal computers, digital assistants, personal digital assistants, cellular phones, mobile phones, smartphones, pagers, digital tablets, laptop computers, Internet appliances, and other processor-based devices. Generally, these computers related to aspects of the technology provided herein can be any type of processor-based platform, running any operating system, such as Microsoft Windows, Linux, UNIX, or Mac OS X, and capable of supporting one or more programs, including the technology provided herein. Some embodiments include personal computers running other application programs (e.g., applications). Applications can be stored in memory and can include, for example, word processing applications, spreadsheet applications, email applications, instant messenger applications, presentation applications, Internet browser applications, calendar / organizer applications, and any other application executable by a client device. All such components, computers, and systems described herein as related to the technology may be logical or virtual.

[0235] In some embodiments, the present disclosure provides a system for screening for one or more types or subtypes of urological cancer in a sample obtained from a subject. Exemplary embodiments of the system include, for example, a system for screening for multiple types or subtypes of urological cancer in a sample obtained from a subject (e.g., a tissue sample, a blood sample, a plasma sample, a serum sample, a whole blood sample, a buffy coat sample, a secretion sample, an organ secretion sample, a cerebrospinal fluid (CSF) sample, a saliva sample, a urine sample, and / or a stool sample). In some embodiments, the system includes an analytical component configured to determine the methylation status of one or more methylation markers in the sample, a software component configured to compare the methylation status of the one or more methylation markers in the sample with a control or reference sample recorded in a database, and an alert component configured to alert a user of a cancer-related condition.

[0236] In some embodiments, the alert is determined by a software component that receives results from multiple assays (e.g., determining the methylation status of one or more methylation markers) and calculates a reported value or result based on the multiple results.

[0237] Some embodiments provide a database of weighting parameters associated with each methylation marker provided herein for use in calculating a value or result and / or reporting an alert to a user (e.g., a doctor, 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 based on a combined result of one or more results from multiple assays that is indicative of a subject's risk of cancer. Such methods are not limited to particular methylation markers. In such methods and systems, the one or more methylation markers comprise bases in a DMR selected from the DMRs of Tables 1, 2, and 3.

[0238] In this detailed description of various embodiments, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the disclosed embodiments. However, those skilled in the art will understand that these various embodiments may be practiced with or without these specific details. In other instances, structures and mechanisms are shown in block diagram form. Furthermore, those skilled in the art will readily appreciate that the specific order in which the methods are presented and performed is illustrative, and that the order can be changed and still be within the spirit and scope of the various embodiments disclosed herein.

[0239] The various components of the kit may be provided in suitable containers as needed. The kit may further include a container for holding or storing the sample (e.g., a container or cartridge for urine, whole blood, buffy coat, plasma, serum sample, tissue, or endocrine sample). If needed, the kit may also optionally contain reaction vessels, mixing vessels, and reagents or other components to facilitate preparation of the test sample. The kit may also include one or more instruments to assist in obtaining the test sample, such as a syringe, pipette, forceps, measuring spoon, etc. In some embodiments, the instrument is a collection device. In some embodiments, a biological sample is obtained from a subject, and the method further includes extracting a DNA sample from the biological sample. In some embodiments, the biological sample is collected with 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. [Example]

[0240] It will be readily apparent to those skilled in the art that other suitable modifications and adaptations of the methods of the present disclosure described herein are readily applicable and discernible, and may be made using suitable equivalents without departing from the scope of the present disclosure or the aspects and embodiments disclosed herein. Having described the present disclosure in detail, the same will be more clearly understood by reference to the following examples, which are intended merely to illustrate certain aspects and embodiments of the disclosure and should not be construed as limiting the scope of the disclosure. The disclosures of all journal articles, U.S. patents, and publications mentioned herein are incorporated herein by reference in their entirety.

[0241] The present disclosure has multiple aspects, illustrated by the following non-limiting examples.

[0242] Example 1 Experiments were conducted to evaluate the feasibility of a panel of methylated DNA markers (MDMs) for detecting urological cancers, site-specific urological cancers (e.g., renal cell carcinoma and urothelial cell carcinoma), and renal oncocytoma. These markers are listed in Table 1 below.

[0243] [Table 1-1] [Table 1-2] [Table 1-3] [Table 1-4] [Table 1-5] [Table 1-6] [Table 1-7] [Table 1-8] [Table 1-9] [Table 1-10] [Table 1-11] [Table 1-12] [Table 1-13] [Table 1-14] [Table 1-15] [Table 1-16] [Table 1-17] [Table 1-18]

[0244] Example 2 Using a proprietary methodology for sample preparation, sequencing, analytical pipeline, and filters, we identified differentially methylated regions (DMRs) and narrowed them down to DMRs that accurately represent urological cancers and excel in a clinical trial setting. Tissue-specific analysis identified 358 hypermethylated UTCC DMRs (Table 2). These included regions specific to UTUC (or at least regions previously unrecognized or unidentified in 14 epithelial cancer types sequenced over the past decade) as well as regions frequently methylated in several epithelial cancer types (i.e., previously recognized regions). Analysis of UTUC tissues from buffy coats yielded 29 hypermethylated UTUC tissue DMRs with an area under 0.95 and less than 1% noise in leukocytes (Table 3).

[0245] [Table 2-1] [Table 2-2] [Table 2-3] [Table 2-4] [Table 2-5] [Table 2-6] [Table 2-7] [Table 2-8] [Table 2-9] [Table 2-10] [Table 2-11] [Table 2-12]

[0246] [Table 3]

[0247] Example 3 For RCC samples analyzed by subtype, combining the comparative DMRs from tissue and buffy coat yielded 140 regions (Table 4). Because previous studies have shown that normal renal parenchyma is somewhat more methylated than expected from normal epithelium at other sites, these were weighted more heavily toward the buffy DMRs. This was particularly true for oncocytoma and chromophobe samples, where many regions were more highly methylated than controls. Clear cell carcinoma and papillary carcinoma exhibited epigenetic signatures distinct from the other two subtypes. Therefore, a second RCC comparison was performed using urothelial tissue controls instead of parenchyma. This yielded an additional 51 DMRs with highly robust AUCs (>0.95) and elevated methylation, whereas urothelial tissue control levels were low, mostly below 2% (Table 5).

[0248] [Table 4-1] [Table 4-2] [Table 4-3] [Table 4-4] [Table 4-5]

[0249] [Table 5-1] [Table 5-2]

[0250] Example 4 For UTUC validation, 38 candidates were selected and are listed in Table 6 below with their corresponding primer sequences. These were the top-ranked MDMs in terms of AUC, fold change, delta methylation, and p-value. A methylation-specific PCR assay was developed to test the discovery tissue samples, FF and FFPE. Short amplicon primers (less than 150 bp) were designed to target the most discriminatory CpGs within the DMR, and the assay was checked with controls to ensure stable and linear amplification of fully methylated fragments and no amplification of unmethylated and / or unconverted fragments.

[0251] [Table 6-1] [Table 6-2] [Table 6-3]

[0252] Results were analyzed logistically to determine AUC and fold change. Analyses of tissue and buffy coat controls were performed separately. Results are highlighted in Table 7. The degree of red shading indicates the discriminatory strength of the marker assay. One MDM, CRACDL, accurately distinguished UTUC from benign tissue 100%, and nine MDMs completely distinguished UTUC from buffy coat samples, an important characteristic for liquid biopsy applications. Ultimately, 32 of the 38 assays were utilized for further validation testing of this cancer type.

[0253] [Table 7]

[0254] Example 5 For the RCC region, 65 were selected using the criteria outlined in the methodology, and are listed in Table 8 below with their corresponding primer sequences. Of these, 42 were obtained from the papillary cell and clear cell analyses, and 23 were obtained from the chromophobe and oncocytoma analyses. Interestingly, 42 MDMs overlapped somewhat with all subtypes (the first 42 markers described for oncocytoma (Table 8) and chromophobe RCC (Table 9)), while 23 MDMs were exclusive to the chromophobe and oncocytoma subtypes (the last 23 markers described for oncocytoma (Table 8) and chromophobe RCC (Table 9)). Because independent samples were already available, two rounds of marker validation were performed: one on the discovery samples and a second on a new, expanded set of FFPE samples. The results by subtype for the discovery samples are summarized in Tables 9, 10, 11, and 12. When buffy coat samples were used as controls, MDM performance was excellent across all RCCs, with many showing complete discrimination, as well as >20% hypermethylation and >20-fold changes. For kidney tissue controls, performance was more muted and subtype-specific. Papillary and clear cell RCCs were similar, with AUCs >0.85 and FCs >5 for 8–10 hypermethylated MDMs. Chromophobe and oncocytoma had similar AUCs, but the degree of methylation (%) and FC values ​​within the tumors were almost universally worse. In some cases, tumors were hypomethylated compared to controls. In chromophobe RCC, the markers CBLN1, CTNND2, PRDM2, NAGS, SFT2D3, and USP2 were some of the markers that showed positive metrics, while in oncocytoma, NAGS was the marker that showed positive metrics.

[0255] [Table 8-1] [Table 8-2] [Table 8-3] [Table 8-4] [Table 8-5]

[0256] [Table 9-1] [Table 9-2]

[0257] [Table 10-1] [Table 10-2]

[0258] [Table 11]

[0259] [Table 12]

[0260] Example 6 For the second validation round of RCC, 38 MDMs were selected from the original 65 (Table 13). The criteria were markers with an AUC of 0.95 or higher and an FC of 20 or higher in the first round in the buffy coat comparison. For the normal tissue comparison, in addition to the MDMs listed above for the RCC subtypes in question, we also included MDMs for papillary and clear cell results with an AUC of 0.85 or higher and an FC of 5 or higher. The results of these 38 MDMs are shown in Table 13. As in the previous validation, many MDMs performed well in the tissue-to-buffy coat setting, and many perfectly distinguished all RCC subtypes. In the tissue-to-tissue comparison, as previously mentioned, many MDMs were ineffective at distinguishing cancers. Because these were all independent samples, these results confirm the unique biology of renal tissue, i.e., unlike many other epithelial cancers, methylation differences between cancer and normal tissues do not strictly follow the traditional cancer-hypermethylation; normal-hypomethylation paradigm. The top inter-tissue MDMs by subtype are as follows: papillary: C1QL3, ITPKB, MAX.chr15.0918; clear cell: PPFIA4, PRDM2, TRIM58, VWC2; chromophobe: SFT2D3; and oncocytoma: NAGS, SFT2D3.

[0261] [Table 13]

[0262] Based on these data, it was decided to return to the sequencing results and perform a de novo comparison between RCC samples and urothelial tissue controls, substituting normal kidney tissue. As previously described, 51 DMRs were selected that generally had significantly better metrics than those from normal kidney tissue. Of these, 18 were selected and converted to the qMSP assay (Table 14).

[0263] [Table 14-1] [Table 14-2]

[0264] Taken together, the disclosed DMRs developed for the detection of urological cancers demonstrated excellent performance throughout validation for both normal tissues and normal WBCs. The disclosed DMRs for UTUC and RCC, and the corresponding assays developed to assess their presence or absence in subject-derived samples, are particularly suitable for detecting these cancers in a non-invasive clinical setting.

[0265] Example 7 Upper tract urothelial carcinoma (UTUC) can be difficult to characterize in some cases, and noninvasive monitoring tools are lacking. UTUC is often treated with nephroureterectomy (NU). To address these gaps, we conducted experiments to discover and validate methylated DNA markers (MDMs; also known as DMRs) for the detection of UTUC.

[0266] Archival formalin-fixed, paraffin-embedded (FFPE) tissue samples from NU were pathologically examined and perforated prior to DNA extraction. Reduced representation bisulfite sequencing (RRBS) was used to identify candidate DMRs that distinguished UTUC from age-balanced control urothelial tissue (ureter / renal pelvis uninvolved by renal cell carcinoma in radical nephrectomy). The highest-ranking (fold change and p-value) candidate DMRs were biologically validated by quantitative methylation-specific PCR in a second, independent set of UTUC and age-balanced controls. DNA from urine and buffy coat samples from healthy donors was used to assess DMR background signal. Discrimination between UTUC and controls was assessed by the area under the receiver operating characteristic curve (AUC) and corresponding 95% confidence interval.

[0267] The RRBS evaluated 33 UTUC cases and 26 ureteral / renal pelvic controls. 6CpGs were mapped to the reference genome at a read depth of at least 10x. From 358 candidates, 20 DMRs were selected for biological validation in independent patient samples, including 20 renal pelvis and 16 ureteral UTUC cases and 17 renal pelvis and 15 ureteral control specimens. Among UTUC patients and control patients, 36% and 65%, respectively, were male. The median AUC for comparing UTUC and control tissues was 0.87 (IQR 0.81-0.88). The AUCs for the 10 most accurate DMRs across all control types are shown with their corresponding 95% CIs (Table 15). These data demonstrate the identification and validation of sensitive and specific DMRs, with the potential for accurate noninvasive screening supported by low background in urine and blood. AUCs (95% CI) of selected methylated DNA markers in UTUC versus control tissues.

[0268] [Table 15]

[0269] Example 8 This example describes the design and use of various LQAS assays to detect a set of DMRs in renal cancer and control samples using the TELQAS workflow. Plasma was extracted from 140 control samples, including 20 stage I samples, 7 stage II samples, 23 stage III samples, 10 stage IV samples, and 9 undetermined samples, and 70 renal cancer samples. The methylation profiles of the following DMRs were determined in these samples: C1QL3, OXR1, ANKS1B, CMTM3, LINC01398, FBLIM1, VPS9D1, LRRC8D_9548, HVCN1, SFT2D3, FAM83G, LOC100128239, LHX1, GRAMD1B, TSPAN33, PDE4D, LOC100289410, TTBK1, PRDM2, CLDN10, MAST4, MACROD1, and KCNH3. The LQAS assay was performed as described below. Data analysis was performed using differential Cp normalized to the mean Cp value of B3GALT6 reference RNA. ZF_RASSF1 was used as a processing control.

[0270] Representative receiver operating characteristic (ROC) curves for the four-gene combination using a 50-strand cutoff (Figure 1A) and a 1-strand cutoff (Figure 1B). Figure 1C shows representative results for the four-marker panel in Figure 1B in determining whether a gene is positive or negative for blood drawn from subjects with kidney cancer ("cancer" samples) and blood drawn from subjects without cancer ("normal" samples). The staging and detection calls for the cancer samples are also shown.

[0271] For combined analysis of the RT-LQAS data using stepwise logistic regression model fitting performed on the discovery sample set using JMP software, four markers were selected: MAST4, KCNH3, GRAMD1B, and LOC100289410 (Figure 1A; GRAMD1B is designated Max.chr11.1233) or PDE4D (Figure 1B; GRAMD1B is designated Max.chr11.12331 in Figure 1B). Data from these markers were combined into a four-marker ROC curve fit. The four-marker ROC curve fit is shown in Figures 1A-1B, and Figure 1C shows a table showing the results (sensitivity for cancer and stage-specific sensitivity for the four-marker log-strand fit (1-strand cutoff) at 98.5% specificity) for cancers classified as stage I (low stage) to stage IV. These data demonstrate the detection of cancer at all four stages and show that combining data from multiple markers into one AUC calculation can increase the AUC value and therefore the sensitivity for a given specificity (%).

[0272] The QuARTS and LQAS flap assay technologies combine a polymerase-based target DNA amplification process with an invading cleavage-based signal amplification process. QuARTS technology is described, for example, in U.S. Patent Nos. 8,361,720, 8,715,937, 8,916,344, and 9,212,392, and a flap assay using a probe oligonucleotide with a long target-specific region (Long probe Quantitative Amplified Signal, "LQAS") is described in U.S. Patent No. 10,648,025, each of which is incorporated herein by reference in its entirety for all purposes. An assay combining preamplification and LQAS is called a "TELQAS" (for "Target Enrichment Long probe Quantitative Amplified Signal") assay. In some embodiments, DNA from the sample may optionally be treated with a methylation-specific reagent, such as a bisulfite reagent, or treated using the TAPS method, which combines oxidation with a TET enzyme and reduction with a borane derivative, as described above. The converted DNA is then used in a detection assay, such as a pre-amplification and / or flap endonuclease assay. For further embodiments of bisulfite treatment of nucleic acids, see U.S. Patent No. 10,704,081 and U.S. Patent Application No. 63 / 058,179, filed July 29, 2020, each of which is incorporated herein by reference in its entirety for all purposes and may be applied in the techniques described herein. For further embodiments of isolation of plasma-derived DNA and bisulfite treatment of nucleic acids, see also U.S. Patent No. 10,822,638, U.S. Patent No. 10,704,081, and WO2022 / 039904, filed July 29, 2021 (each of which is incorporated by reference in its entirety for all purposes and may be applied in the techniques described herein).

[0273] 6. Materials and Methods The following materials and methods were used to identify various DNA methylation markers capable of distinguishing one or more types of urological cancer in biological samples from subjects having or suspected of having urological cancer.

[0274] Samples. Fresh-frozen tissue was obtained from 44 renal cell carcinoma cases (16 clear cell, 13 papillary, and 15 chromophobe) with a balanced low-stage vs. high-stage, 15 benign oncocytoma cases, 18 urothelial cell carcinoma cases with a balanced invasive vs. noninvasive stage, 8 cases of normal renal parenchymal tissue, and 18 cases of normal urothelial tissue. Frozen tissue samples of parenchymal tumors were obtained from the Mayo Clinic Biomarker Discovery Program at the Center for Personalized Medicine. Fresh tissue was harvested for 18 cases of urothelial cell carcinoma, 8 cases of normal renal parenchyma, and 18 cases of normal urothelium. For urothelial cell carcinoma tissue, fresh fresh-frozen specimens were obtained from patients with index tumors in the renal pelvis, ureter, and / or bladder. Normal fresh-frozen renal parenchymal tissue was obtained from patients undergoing nephroureterectomy for urothelial cell carcinoma involving the upper urinary tract (from renal parenchyma not involved by urothelial cell carcinoma). Normal renal parenchyma was selectively obtained from patients with ipsilateral renal tumors undergoing radical nephrectomy. Cases were selected after the investigator completed radiographic examinations to confirm that more than 50% of the kidney was tumor-free. Because it is known that electric field effects are absent in urothelial cell carcinoma and non-invasive renal parenchyma, normal renal parenchyma samples could also be collected from cases included in the urothelial cell carcinoma group. For similar reasons, normal fresh-frozen urothelial tissue could be obtained from patients undergoing radical nephrectomy and partial ureterectomy for renal cell carcinoma (derived from non-invasive urothelium of the renal pelvis and / or ureter). In addition, 18 urothelial cell carcinoma cases and 18 urothelial control FFPE tissues were obtained from clinical residual tissues in the Mayo Clinic Tissue Registry. To date, RRBS has been technically successful using only DNA extracted from frozen specimens. Recently, sequencing library preparation kits that can be used with paraffin-embedded tissues have become available, so we compared the sequencing results of frozen and paraffin-embedded sources. If the results are comparable, sequencing of paraffin-embedded tissue samples may become more rapid and cost-effective in the future. Eighteen normal buffy coat samples were obtained from the NOMAD study.

[0275] Genomic DNA was purified using the QIAamp DNA Tissue Mini Kit (fresh frozen), QIAamp FFPE Mini Kit (FFPE), and QIAamp DNA Blood Mini Kit (buffy coat) (Qiagen, Valencia, CA). DNA was repurified with AMPure XP beads (Beckman-Coulter, Brea, CA) and quantified with PicoGreen (Thermo-Fisher, Waltham, MA). DNA integrity was assessed using qPCR.

[0276] Sequencing. Reduced representation bisulfite sequencing (RRBS) sequencing libraries were prepared using a modified Ovation RRBS Methyl-Seq Library Prep Kit (Tecan Genomics, Redwood City, CA). Briefly, samples were digested with Msp1, ligated to index flow cell adapters, bisulfite converted (twice), amplified, ligated in a 4-plex format, and sequenced on an Illumina HiSeq2500 instrument (Illumina, San Diego, CA) at the Mayo Genomics Facility. Reads were processed through Illumina pipeline modules for image analysis and base calling. Secondary analysis was performed using SAAP-RRBS, a bioinformatics suite developed by Mayo. Briefly, reads were cleaned using Trim-Galore and aligned to the GRCh37 / hg19 reference genome constructed with BSMAP. For CpGs with ≥10x coverage and a base quality score of ≥20, methylation rates were determined by calculating C / (C+T) or, conversely, G / (G+A) in the case of reads mapping to the opposite strand.

[0277] Biomarker selection. Significant differentially methylated (DMR) regions were derived using a proprietary identification pipeline and regression package. Differences in mean methylation rates were compared between cases, tissue controls, and buffy coat controls. Tiled reading frames within 100 base pairs of each mapped CpG were used to identify DMRs with <5% methylation in controls; this cutoff value was varied depending on the required stringency. DMRs were only analyzed if the total depth of coverage was an average of 10 reads per subject and the variance between subgroups was >0.

[0278] After regression, DMRs were ranked by p-value, area under the receiver operating characteristic curve (AUC), and fold-change difference between cases and controls. No adjustment for false positives was performed at this stage, as independent validation was planned in advance.

[0279] Specifically, individual CpGs within DMRs were ranked by their hypermethylation rate, i.e., the number of methylated cytosines relative to the total number of cytosines at that location in a given locus. For cases, the ratio had to be ≥0.20 (20%); for tissue controls, ≤0.05 (5%); and for buffy coat controls, ≤0.01 (1%). DMRs ranged from 60 to 200 bp and included a minimum cutoff of 5 CpGs per region. To avoid GC-related amplification issues during the validation phase, DMRs with excessively high CpG density (>30%) were excluded. For each candidate region, a 2D methylation intensity heat map was created, which plotted individual CpGs within the region against case-control samples. Methylated CpG patterns were analyzed in RCC and UTUC compared with their respective benign controls and / or non-cancerous buffy coats, as well as across subtypes. Final selection required, at the sample-by-sample level, coordinated and consecutive (in cases) hypermethylation of individual CpGs across the DMR sequence. Conversely, control samples had to be at least 10 times less methylated than cases, and the CpG patterns had to be empirically discordant.

[0280] Biomarker validation. A subset of DMRs was selected for further development. Criteria were primarily logistic-derived area under the receiver operating characteristic curve (ROC) measures, which provide a performance assessment of the region's discriminatory potential. AUC 0.85 was selected as the cutoff value for tissue-to-tissue comparisons, and AUC 0.95 for tissue-to-buffy coat comparisons. Additionally, methylation fold change (mean cancer hypermethylation rate / mean control hypermethylation rate) was calculated, with a lower limit of 10 for tissue-to-tissue comparisons and 20 for tissue-to-buffy coat comparisons. P values ​​were required to be less than 0.01. DMRs were required to be concordantly methylated in cancer and discordant (or unmethylated) in controls.

[0281] Case-Control Comparisons. In the various experiments described herein, the following case-control comparisons were used: UTUC vs. urothelial tissue control; UTUC vs. normal buffy coat; papillary RCC vs. normal renal parenchyma; clear cell RCC vs. normal renal parenchyma; chromophobe RCC vs. normal renal parenchyma; oncocytoma vs. normal renal parenchyma; papillary RCC vs. normal buffy coat; clear cell RCC vs. normal buffy coat; chromophobe RCC vs. normal buffy coat; oncocytoma vs. normal buffy coat; papillary RCC vs. urothelial tissue control; clear cell RCC vs. urothelial tissue control; chromophobe RCC vs. urothelial tissue control; and oncocytoma vs. urothelial tissue control.

[0282] Quantitative methylation-specific PCR (qMSP) primers were designed for the genomic hg19 candidate region using MethPrimer (Li LC and Dahiya R. MethPrimer: designing primers for methylation PCRs. Bioinformatics 2002 Nov;18(11):1427-31 PMID:12424112), and 20 ng (6250 equivalents) of positive and negative genomic methylation controls were QC-tested. Multiple annealing temperatures were evaluated for optimal discrimination. Validation was performed with qMSP in two stages. The first stage consisted of retesting sequenced DNA samples. This was done to verify that the DMRs were indeed highly discriminatory and not the result of overfitting in an extremely large next-generation dataset. The second stage utilized a larger set of independent samples (see Table 16).

[0283] [Table 16]

[0284] Patients and corresponding FFPE tissue biopsies were identified as previously described by expert clinical and pathological examination. DNA purification was performed as previously described. The bisulfite conversion step used the EZ-96 DNA Methylation Kit (Zymo Research, Irvine, CA). 10 ng of converted DNA (per marker) was amplified using SYBR Green detection on a Roche 480 LightCycler (Roche, Basel, Switzerland). Serially diluted universally methylated genomic DNA (Zymo Research) was used as a quantification standard. A CpG-independent ACTB (β-actin) assay was used as the input reference and normalization control. Results were expressed as methylated copies (specific marker) / ACTB copies.

[0285] These tissues were identified as previously described by expert clinical examination and pathological review. DNA purification was performed as previously described. The bisulfite conversion step used the EZ-96 DNA Methylation Kit (Zymo Research, Irvine, CA). 10 ng of converted DNA (per marker) was amplified using SYBR Green detection on a Roche 480 LightCycler (Roche, Basel, Switzerland). Serially diluted universally methylated genomic DNA (Zymo Research) was used as a quantification standard. A CpG-independent ACTB (β-actin) assay was used as the input reference and normalization control. Results were expressed as methylated copies (specific marker) / ACTB copies.

[0286] Statistics. Results were analyzed logistically for the performance of individual MDMs (methylated DNA markers). Two techniques were used for marker combinations: first, rPart technology was applied to the entire MDM set, restricted to combinations of three MDMs, and then rPart-predicted cancer probabilities were calculated. The second approach used random forest regression (rForest) to generate 500 individual rPart models fitted to bootstrap samples of the original data (approximately 2 / 3 of the data for training) and used to estimate the cross-validation error for the entire MDM panel (1 / 3 of the data for testing), which was repeated 500 times to avoid spurious splits that would under- or overestimate the true cross-validation measure. Results were then averaged over the 500 iterations.

[0287] In some embodiments, RNA and DNA are isolated from different blood samples from a subject. For example, blood may be collected into a first collection tube configured for optimal preservation and / or isolation of RNA and a second collection tube configured for optimal preservation and isolation of DNA, and RNA and DNA may be extracted from portions of the blood collected in this manner. In other embodiments, RNA and DNA are both extracted from a single collected blood sample, for example, using a collection tube configured for optimal preservation and isolation of both DNA and RNA (e.g., cf-DNA / cf-RNA Preservative Tubes (Cat. No. 63950) from NORGEN Biotek Corp., for preservation and isolation of both cell-free DNA and cell-free RNA).

[0288] In some embodiments, RNA and DNA are assayed together, e.g., in an RT-LQAS / RT-TELQAS reaction. In some embodiments, RNA and DNA are isolated separately and / or treated separately, e.g., with bisulfite, as described above, while in some embodiments, RNA and DNA are present together, e.g., during bisulfite treatment and subsequent purification, and then added together to the assay reaction.

[0289] Sequences. The various nucleotide sequences referred to in this disclosure are provided below.

[0290] MAX.chr1.6151 (DMR 112):

[0291] CGCGAAGTCTCTCTGTCCTCATTCGCACCTCCTCTACTTCTCTCCGGCCTCTCCGTATTTCTGCTTTTCACCCTTCCTCTCTCCCGCCGGACCGACCGAAGCAGAGGTGAGCGAGGGTAGCGCAAGCAGCGTAGCGAGTCAGGTGAAGGCGGAGCCAAGAACTGCGAGAGCTGTCACTAGAGCCCACCGGGCGTTCTGCTTGCTTCCCTTCGGACCCACGCGATTCAGGCTCAGGGAGTCGCGGACCCGGGCGTTTCCAGGATGCTGGGTCTGATGCCTGCGAGGGGCAGGACGAGGCGAAGGCCATTCCGCTGCCCTTCCAGCTTCAGAATCACCCAATGCACGGGTTTCAACCGTAGCCGGCAAGCTGCCCCTCTCCGGTTTTCCGAGGCTTTGGAGCCTGCACAATTGTTCTACAAAAGGCGGTGGCTCCGCCTAACGTTAGATGGACGCTTGCTCTGCGTGGTGATACCAGAGCGAGAGTCGACTGTTCCTGTGTCGCAGTCGGGTGGTGTGCTTGCTTCCAAGTCTGGAGGCGGGTGGTTCGAGCTCGTTCTATGGAACG (SEQ ID NO: 243).

[0292] MAX.chr1.4676 (DMR 113):

[0293] AACACTACGTGCTTGCCACTTTGCTTAGCGGTTTGTTGAGTCCAACAACTGCGTGGGTCCCGGGTTAGTCTCCTGAATGTCTTTTGCTGCTACTTTGGTCAGCGTTGTTGTCAGTTTACCTTGTGGTGGCCAAGCCCTTAAATGCACTATTAGGTTATGCAGTGTAATTCTGCAGGGCAGAAGGGTAAAGAGCCATAGTGAAGAGCAAAAGAACCTCTTGCCTTGACCGGGAATTGAACCCGGGTGTCCCGCGTGTGAGGCGAGAATTCTACCACTGAACCACCAGTGCCTCTCCCCAGCAACCCTTGGAGAATTATCGGAAAGAGTATCCAGAAAGACTTAGAAACTTCCAAGCGGCCTTTTCAAGTGTCGACTCAAAGCTAACAAAGACATCCAAACCAAATGTTTTTATAGGAAACTTTTACTAAACAAAGTTATAAATATCAAAATAGCTCATTTGTCGGATCAAACTCTTAACTCTGAAAAAGGTCTTTCTACCTGCATTACATACCCCTATAATAAAACGTCACAAATTCATTCATGTTT (SEQ ID NO: 244).

[0294] MAX.chr1.9437 (DMR 114): TCATGAGAGAAAGACCTGCGTCGAGTTTTTGGCCTGAACGTGTGGAGGGTGGAGTTGCCATTAACTAACGTGGGAAAAGGCAGGTGTAGTACGTTTTAGAGAAAATATCCGGAATTCCGTTCAGGGCCCTGGGGTCTTCCTTGAAAGAGTTTTCCATCCAGGCCGTCTCGGTTTCCGCATCCGTCTGAGTCGTTTATGATGTCGGGAATGCAGGAATCTGAGTCCTTTATGATGTTGAGGGTGCCACGGTCTCACCCCGGGCGCCTCCCCGCTCCAGCCTCCTCCCGGAAGCCTGGTGCGCTCTGGCCCCGCCGACCAGCGACAGTCTCTCCACGCGCTGCCGCCTAGCAAAGGCGCATCTTTAGGTCGGTAGTGAGGTGCGGCCGGGACGCTGCAACTCGCTCCGGGACTTGTAAACCTGGCAGGTGTTCGAAGAGGGCCACTGGCTGGAAGGAAAGGAGAGAGCTCTGCACGTCGCGTGTGGGCTCGCAACTTGGAGAAAGCAGGGAGAGGACAGCCTTTTGGGACTATTCCTTGGATGGGCGGGTGGCACCAGGAAGGGTAGATGGAGCTTTCTAGAGGTCAATGTCAGCGTAATTTCTGCTGAAACAATTGAAGGAGGAAAAAAAAAAAAGTATGTGCTTTGTGGTTC (SEQ ID NO: 245).

[0295] MAX.chr1.1120 (DMR 116):

[0296] CGGAGCTACCCGCGGCGGCCCGGGTTCGCATCCTCCCACTGCTCAGACCGAGTCGGCTCCAGCTTGCTTTGGGAAGCATTCAGGAATAAACGTGGACAGTAGCGGTCAGGAAGGAGATTCCCGTTTCCCCTTCTCCCAGGAGGAAAAGAGGTAACGCTGCCGCCACTGCCCTCTCTTTCCAGGGTGGGAACGCCGCCCGAGACCGGGGTACCCCACACTCCTCCCTAGCGCTGATCCCAGCGGAGCTCAGGCCGCAGTCCCCTCCTGCCGGCTGCGGAAGCTCCCAGAAGCGGAGACTCAATCGCCCCCCTGCCCCTGCTACCAGGCCAGAGTCTGGAGTACAGATACTGGCTCCCTGGGGCCTGGGTGTGCGACCCCAGGCCGGTCATTGCAGGTCTCTGCGCCTCCCTGTTCCTGACTGTGCAATGGGCAGCGGGTCAGGGGCGCACCGTGGGCGCAGTACGTTCCCAGGCGCCAAGGGCTGTGACTGACCGACCTGGGCTTCCACCGCGGGGCCTGGGCCATGGAGACGCTCCGGGCCCAGGAACGGGGGACCTCGGGTGCCCCACTACCTCACTCCTAGAACGCCCACCGCTCACG (SEQ ID NO: 246).

[0297] MAX.chr1.5982 (DMR 117):

[0298] CGCGCCGGGCCGGTGGAACTCAGCTCCGGGAAGGCTGTGGACCTGGACCCTGGGGCTCCCCGCTGCCTGGGCGCCTCTAGCCCGGCGATGAGTGGTTCTGCGGGGACCGACGGCCCCATTTCCTTCTTGCCTCGTGATGTGGGAGGGAAGAAAGAAGGCGGCAACTGCAGGCCCGAAGCTCCCCTCGCCCAGCGGCCCAACCACAGTGCTGTCGTGTCGGGGATCGGTCCCCAAGGGAGCCCCCAACCCCCTGCCCACGCCGAGATCACCCCCGTGCCAACCTCGAGGGCTCGGCCTGCGGGACTCCAGCTGCCCCTGCCTGGAGGGAGGGAAGGGAGAAGAGAATACGAATTAATTACGAAGGAAACCCAGGTGTGAAAGGCACCCGCCGCGGAGCTGGGCGTGCAGCGGGGCGCGCGGTGGGACCTCTGCTCCCGTCCCCGTCCCGCGGCTACTCAGTTGCCCGCTCATGGGAGGCTCGCGACGGAAAATAAATCCCCTCAGAGTGAACCTGGGAGGCCGAGAGGACCCAGCCTGGGATCTCTGGGGGAAATAGGGGCAAGTTTACCACGGTTTAATTAAGCCACAGCCCTAGCACGAGGACCCCGGCGACCCATCCGGGCTGGGGGATGGACTGGAGTGCCCCCCACCCCAGGCCGCGAACCGGCAGCGAGAAGCACACTCTCCGCCATCCCCGGCCCCGCCGCTTCCGCCTCTGCGGACTCCGCGTTTGCCATGCTCCTTCCCGGGGTCCAGGGACCGGAGCTGCGGTGCACG (SEQ ID NO: 247).

[0299] MAX.chr1.5203 (DMR 118):

[0300] GGTAGTCAGAAACAAACAACCAAAGCAAGAGAGGATGAAGATTTAAATAAAATAATTATGTGCATCATTAAAATAATCATATATGTTTGTACAGACACGTATACACCAAGGAACGTAATGGGGGCTCCTCGCACAGTCCCAGGAGATGCAGGAGCCCAATTGGTGCCCAGGAGCTGCAGGCTCGGGTCCCCAGCCAGGCGGGGGACTGCGGGCCGCCCGCGCTGCAGGGCCGCGGGTCACCGCAGGGGGCGCCGGGGCGCTACGGGTCCTCGGGCCTGGTCTTTTCCGGTCCCTGCCCGAGCCCGCGCCTTTCCCGCCTTTCGGGGGAGAAACCTGCCTGGACACTGGAACTGGGAGAAAGCAGCAGCCTAATTGCTCTTCCGATCGTCGCTTGGGAAAGGGGGGCTTCACATTTAGAAACTTCTCGCACCTTTCTCTCTCGGTCTCTGCCTTTTGGTGCCTGAAAAACCTTCAAAGATTTGCTTATTTTGATTCCTCGGGCGTTGGAGCTGTATTAGGCAGCACTCGTAGATAATATTG (SEQ ID NO: 248).

[0301] MAX.chr10.0288 (DMR 120):

[0302] AGTTAAGATTAGACATTCCGTGCACGTGTGGGGACTATAGGGCACTATGGAAATTTTTTCTTTTTTTTCTCCTCTTCTCTAAAGCAGAATTCATTCTCCGTCTCTTTCTCCTTTCCCCCATCTCTGCCTGTCTTCCACCTCCCCTCTTTCCCCCCATTTCTGTCCCTCTGTAGAAACCTGGCTGCTCATAGTGCATTTTCACAGACTCTTCTTGGAAGGTGTGTGTGCCGTGAGGGGATACACCGCCGCCGGGAGTTGCCGGGGGAGGAGGGAGACGGGGTGGCCTCAGGAGACCCGGGCTTGCGTCTCACAGGGACAGGTGCGCCTCGGGGTATCCTGGAAACCCTCGTGGGGCTTCCAGGCGCTTTGACAGCACGACCCTCAGTGACCACCAGCTGTCTCAAGCGCTTTGCAGTCAGTGCTCCCGGAAAGCATCCCTTTCTCTTCAACAAGTACAAATTACCTTTTCCTTCCACTCACCTTCCAAAACCCGGAATACCTCAAACACCGAGCTCATTCTTAAACATTCTTAAAATTCAGATGGTCTGTCCAGAAAAAAAAAAAAATTCCGTCTTAACAGAAGGTTTACTTCTGCCGAAATTATATAC (SEQ ID NO: 249).

[0303] MAX.chr10.2081 (DMR 121):

[0304] CGGGCGCTCATTCTGAGCCGCGACGCCCCCTCAACAGGCTCCCGGCACCGCAGAGCCAGAGGCCACGCGGTGAGAACCCCAGTGCGTGCGCTCTTCTTGTGTGAGAGGCCGGAGGTAGAGTTGGGAGAAAGAGGAGCCGGCGAAAAGGTTAGTGGGATCTGCTTTCCCTTCTGCGGCCTTCTGGGCCAGCTAGGGCCTGGGAGATGGGGACCAGGGTCGGAGGCTTGGGGGCGGGAGGGCGGTGCTGCCGGCTGCTTCCTGCAAGCGGTTTGAAGAGGCATCGCGTTGTCCGGCCGCCTGCGCAAGGGCCACGCGCTGCTGCTTTCACCCCCTTGCGCCCGCGGGGCACCTGGACTCCCCTTAAGAGTCCCCGTGGGGCCTGAGCTTCTGCTGGGCGCTACGCTGCCCTCCACGATTCCATTTTGCCCCATTTACTCGGGTCGTCCACTTCCCGCGGCTCAGTGACCCAGCCAGGGGGCGTCTTCCGCTAGCGGTCCAAATGTAGACTCCGCAAAGAGGCTAAGAAGACCTGTCTACCCGGGTGCGCGCGATGGGGTCAGGGTGTAAGAACCAGGAGCCTCATAGAAACCTCTGCTTGGGGTCCAAAGCCCAGCCGGGCACTCCCAGAGGACAACATCCGCCCCCGCATGTACACGTGGCCCCGCAGGACCCAGCCGCAGGGCTCCCACGCTCGGCTCCCCGCCCTCTCG (SEQ ID NO: 250).

[0305] MAX.chr10.7570 (DMR 122):

[0306] CGTGAGCAAGGGTCGGACCAAGCCCGGCACTGGGCAGAAGGCCTAGGTACCAAGCGCCATGCGAACGTCCTTGCTGGAGAGAAACCTGCGCTCTAAGTGCCCGGCCCCGCAGCGGGGCGACGGACCTGACCTGGAACTCGCTCAACCTTCTCCCTGGAAAACCATGGGCGCTCCAAGCGGGGCGAAAACGCCGGGGTGTGCCTCGGCTCCTGCAGCGTGCTAAATTATAAGGGAAACAGTTAATTATTGTTTCCTTTTCCTAACTTTTCTCGGATTCCTTCGGTCACTTTGGCCGACCCCACGAGTCAGCTCTGGGGGCTCTTCTACTTGAGCGAAACCCCCAAATCAAACACTGGCGAACTTGGGCTTCTCCCAACGCACCCGGCAACCCGAAAGGTTGCCTGTCTGTAAAGATACTCCGGAGGAGCAGCCGAGCTGGAAAAGACAGCTGGTGCGTGGCGACGTCCCTCGGACCCTAAAAGGCCCATCGGTTTAGCAACGAGCTGGGATTTCTCGAGCTGCGTTCGGCGGCGCCCGGAAAATCAGTCCTGCTGGATGCGCCCGAGCGGGCGCGGGAGACGCCG (SEQ ID NO: 251).

[0307] MAX.chr10.1197 (DMR 123):

[0308] GCGCAGCTCATGGTCAGGGGCTCCTGCCTCCACAGTCCCACCCCGCGCCTCCGCCGCAGCCCCGCCCGCGCTCCCGTAGGCGAGAGGAGCGCACCCGGCTCCGGGGCCCCGGCAACCCGGCCCCCAGCGTTCAGTGTCCGGCCCGCCACGCGCGAAGTTCAACTTTGCTGGCGCCGCGGCCGCCTGGGGGCCGCGGGCTGGGGCGGGGAGCCCCCGACGGGATCGAGAGCGCGCTTACCTGTGCCGCTCACTCGACGGACATCGCGGGCGCCCCGGCCGCGAGGTGTCGGCGGCGCCGGCTGCGGGCCGGGAGGTGGGCGGCCCCGCGCCTTCCCACGTTCCCACCTCCCGCCCTCCCGGGAGAGCCCACGGGCCCGGCCGCGAGCACGCCAGTGCGCACGCGCCACACTGCCTTCCACCGCGGGCGGCGGGCTAGGGCCGAGCGGGGGCGCGTGGAGGTGCCCGTAGGCGGCCCAGCGGCCCGCCTGCCACCGTGCCCCGGGGCCGCAGCTGCGCCCAGCGCTAGCCACCTGGAGGAGAGGCCTCCTGGGCCACGCGCGGGGCTCCTCCGCGGGGAGGCCCCCTTGCAAGGACCTGAGCCCCTCTCTTTCGTCGGGGGCCCGAGGGTATTCGTGCGCCTCCTTGGCCAAAAGA (SEQ ID NO: 252).

[0309] MAX.chr10.9377 (DMR 125):

[0310]

[0311] MAX.chr10.5150 (DMR 126):

[0312]

[0313] MAX.chr10.0872 (DMR 127):

[0314] TCAGTTGAATGTGCCGCACACCGAGGTTTGGAAACCACCCGTGAACTTCTATCCCAATCCACCCGGACATAAGGGAGCTGATGGCCCAGGCCCGCGCCTTCCAGCGGGGCAGGCCCAGCGGGGACCAGTTCGGCAGGCGCCTCCCCCAGGGTCTAGGATACCTGCTGGAAAGCTCGCAGCAGGGCCCGCTCCCGGTCCTGGGCAGGCCCAGGCGCGTCAAGACGCCGCGGCTACCTCTGCGGAGCGCGGCCGCTCGGCCACCAGCCCCTTCCCGCCCCCCGAGCTCCGCGGCACTGGAGTCCCCGGGCGGTGCCATGCGTCCCTGGAGCGCACGACACTTTCGGGCCCTGGGGACCCCGGGAGGCCGGGATCTGGCCTGGGGTGGAGGGCGAGGCCAGTCGGCCCCCACCTGCTCACCGGGCAGACTGTACCCGGGCAACGGCTCCCCGCAGCTCCGGCTTTTTGCCTGAAGCCCCCTGCAGGCAAATTCCGCGTCGCGCGGGCCCGCGGGCGCGCTGCAGTCTCCGAGCCCCAGGAAGCAGAGACCC (SEQ ID NO: 255).

[0315] MAX.chr12.7379 (DMR 129):

[0316] CTTTAGCTCTTGGCTAGGCGTATAAAGGCACTTTCGATTAAGTCTAATTAGCGAGCCCGAGCTAAAAGGCCGCCACAGCGGCGGGGCCCAGGGAGAAAAAGCAGCGTTCCCAATTCCCATGCTTCCAGCTCCAGGTTGTCGGTCTTTTGTCAGCCTCCGAAGCCAGGGTGCTCAACCTGGCCCCCTTTCTTTCCTGCTGGTGAGGCCACCCGCTTTGGGACAGAACTCTGGGCCTGCGCCTCAGCTCTCCCTCTTAGCGCCCCGGCGCCCCGGCTTCCCAAGCCTGGGGACTGAGCCCGCAGACGCCCATGGCGCATTGGCGAGCGCCCGGCTGGGAGTCAGCTTGGAAACCCACAACTCGCCTTTCTTGAGCGGCCAGACTTAGGATTCTTTACGATACTAACCTGTAATTTACACATTACATTATATTATATATTTTATATATAATTATATTATTATATATTATACTGGAATTTACACATTTTGATTCCGCCTGTAATTTGCCCTTGGAGCTCCGATGCCATAAAATCCATGGGATCTGGCAGAGGAACCCCCACCTCACCCCCTAAGGCCCCAGCTCTCCCTGAACTTCCCTAAGCT (SEQ ID NO: 256).

[0317] MAX.chr12.3032 (DMR 130):

[0318] CGGATCCTGCGCGCTGGCTTCTGTTACCTCCCGGCTTCGACTTCGGCTGCTGCACACTCGTCAAAGTAATGAATGGAGAGAGAAAAGAAGAGGGGGGGAGGGAGGGGGCATTGTGAAGGGGGTGGAATATTTTGGAAATAATACCCTGAGAGAAGGAAATATGGACAACAGTTTATCAGCACCCCCGCCCCCATTGTCCGCATGTTTAAAACCCCTAAGTAATTTTAGATTGTGTCTTCAGTTAATATATCTCTCTCTCTTTCCCGCGGGCTGACAGAGAAGCGCGGTTGCTGCAAGATGTCTGCAGAAATGGGTCTTTAAAAGTTTCCACATTGTTTAGCTACACAAACGTGTTTGCGGTTCCCGAGGCCCTCCCCCTCCCCCACCCGCCTCCGAATCTCATTTCACTTTACGACTCCAATTGTTTGAGGATCCCCGCGCCACATAAATCCTGCTTCGAGATTAATCTCCCTGCTCGCTCGCGCTGGGCGCAGTGATTTTTTTTTTCTTTCTTTCTTTCTTTTTTTTTTTTTTTTTTTTTGAGTTCTTTAAAAGAGGGCGCCGGGCGGAGATTTATTAACAAGGAAAAATAGTTTATTTTTATAGCCGATCTCAGAAAGGTGGGGGTGGAAGTGGGCCGGGAAGGAGAGCGCTTCATATGGATAAACAGTGAGGCTGAGAAGGCCGGGGGGGGGGTGTTAAAGACCACTTCAGCTGGCGACTTGAACTTTTCTCACTGCCCTCAGCTCGGCTGTGGATGCTTAGCCAGGGGTTTGCCG (SEQ ID NO: 257).

[0319] MAX.chr12.9110 (DMR 132):

[0320]

[0321] MAX.chr12.7375 (DMR 134):

[0322] CAACATGTGAAACAAAAAGGGCACTGTCCTTACCAAGGGACGGCTAGATGATCCATCTGCCAACATCAATATTTGGAGGGAAAGCTTAAAATATGCTGTTTTTCCAAGGGTTAAACTTTAAAGGGGTGAAAACACAACTGATGAAATGTTAGCATCAAATCGGTTAACCACTAACTCCTTTCCATATTCGTCGTCGAGGCTCTTTTAAGTTTCCATGAGAAGCGAAACTTCATTCTCTTTGCTCAGAATAGAGACTCCTCCACCTATGCGCGTTTAACCACAGAGTTGTTCTTGATTGTAAGGGACTTCGCCCACTTGGTTGAAGTGGAGAGCCGGTCCTCATTCCAGACGTCCCGCACGGCAGTCGCTCATGGCTCCCTCCAGGCCGGGAGCCAGGAAGGTGGTCCTTCACCGAGGTGCGCACCAAGCGGCGGTCCACCCAGGCAATGGGGTGCACCAATTTGCCTCCAAAAATTTGCTGCGCACACAACCTGTTCACAGTTCCTGATCAGAAAGGGCTAACGAGATGTCTGTCTACAGCTGTCTCTGGGCGAGGGCGCAGGCTTTGGGAAGTGGTTCAGCGCGATCGGGGACACCGCTTGCAGCCCTTGGTCCTGCACCCCTAGGAGGGGTGTCCCACAAGCTCGGCTTCCCTTTTGCGAGCCACAGAGAGCTTTTTGTTCCGAAACTCTCATTACGACAGATAGTATTTAAAACTCATCAAAATTCGCTTCAGAAATCTG (SEQ ID NO: 259).

[0323] MAX.chr13.1022 (DMR 135):

[0324]

[0325] MAX.chr13.1687 (DMR 136):

[0326] CGCGCTGCGCTGCGGGTAGCTGCCCGCAGGGAGGCCCAACCTGCCGCGGCTGGAGCACGGTTTCTGCTAGCCGCCGCCGTCAACTTGAACTTCAGTGAGCCTAGGCCGGCTTCCTTCGCGCTCACCTCCATCCACCACCTAAGAAGTCCCCTCAGCGCGAGCGTCGCTTTATCCGGAGGCAGCTGGAGCCCCCTCGGGAGGCCCGTCATTATTATTATTAATTATCGTGATCCTTACTGCATTATTAATGCCCAGGATGATAACCGGCATCGGTATCAGCTTTCCCTGGTTCAGTGATATCCCACGAAGTTCGGGGCGGGGAGGAAGTCACTCCAGGATCAGAGGCCGCGTCGGTTCTGCTTGGGGCATGGGCAGAGGGAGGCTGCTGGGGCCAAGCCCCGGCTGGACGCGAGGGAAGAAACTCGTCCCAGGACCCGCACGCCCATACCTGGCTGTCCCAGAGCTCTTCCCTAGGCCGGCACCTTCGCTCTTCCTCTTCCCCACCCCCTAGCCCTTTTGTCTCTTTTTCAGACGGATGTTTTCAGTCTCAAGTGGTTTTATTTTCCGCACAAAACCCTGAGATCAAGGGCAGATCACAGACTGTACCGGAGGCTCGGGTTTCCCTGGACTCTGTGCTGTTCTGCGTCCCAGGGTTGGCTAGGAAGGAAGGCCTGGGCCGGCGAGGTGACGGGTCTCCCGCCCAGGTCGGCAGGACGGGGGGAGGTGTGTCCCGGTAGGTCCCTGGTGAGCTCACCCGTGGCATCGGGGACCCGCGGGAACCCACCGGGCGCCCACTAGAGACTCGGGTCCTACCCTCCCCCACACTACTCCACCGAAATGATCGGAAGGGCGCG (SEQ ID NO: 261).

[0327] MAX.chr13.2109 (DMR 140):

[0328] CGCCGACCAGTTAGTTGGTGGAGGCGCAGAAACTTGTCCTCGGACCCCACGCAGAAGCCGCCCGCCCTCTCCAAGGCTCCGGCCCCGACTTCGCTCTGCGAATTGGGCCAGCCGCTGCTTTTCGCGAGACCCGAGGGTTCGCCAAGGAGAGGAGAAGGGCACAGGCTGCCTGAGACTGGTCTTCGGGCAGCCGAGGGCGGCGGGATGACTCGGGCAGGCGT GTGGCCTCCGACTGACCAGGGTTGGGCCCGGGATCAGAGCTTTGCTTGGAAGTTCTCTGGGTGGCAGAGACTCGGGCAACCGGAGCCTGAGCCTCCCCGGGGAAGAGCTCGGACTCCGGAGGTCGCGCCGCCTTGGGCTTGAATTCAGTCCTTCCTTACTACTCGTGGCTTTGCTTACATCATTTAACTCTCCATTTCCTTGTCTATACAGTGGGCTCAT AAGGAGGCGGTAAGGAGATGATGATGTCTTTGAAGAGTTTTAGGACAGGACCTGGTGTCTCCCGTACGCTTGGTGGGTGGGCGGAGGTGATGCGTTGTTTAACAGGAAAACCGACCTTCCAGGGAGGCAGCGGAGAGCGAAGTCCTGCTCGGCGAGAGACCTCGAGGAGAGAGTATGGGGAAAAGGAATGAATGCTGCGGAGCCCCCTCTGGGTCCACCCAAGCCTCGGAGGCGGGACGGTGGGCTCCGTCCGACCCCTTAGGCAGCTGACCGATACCTCTGGATCAGACCCCACAGGAAGACTCGCGTGGGGCCGATATGTGTACTTCAAACTCTGAGCGGCCACCCTCAGCCAACTGGCCAGTGGATGCGAATCGTGGCCCTGAGGGGCGAGGGCGCTCGGAACTGCATGCCTGTGCACGGTGCCG (sequence number 262).

[0329] MAX.chr14.3769 (DMR 143):

[0330]

[0331] MAX.chr14.1054 (DMR 146):

[0332]

[0333] MAX.chr14.6663 (DMR 147):

[0334] TCCCCTTCCCCCACCCCCTCCCCCTGGCAAGGACCGCGTATAGTTACAGTTTAATCTTGGAAATGCCAGACAGCTGTTCCCCGTTGCTAAGAGACTGGCCCACATTATGCAGATGTCAGGGGCCTCAAATGTCTGCCGGAAATTACAGATCATGTTGGAAGAGCAGAGGGGCCTTCTCTTGACTGGGGAAGCGCAGTGGGAGACTCCTTGGGTGGATGGCAGAAATAAGGGGCCCACCCTTTCCGGGTCTCTTCCGAGGCTCTGAGGCTCCAGCCTGTCCCTCCTCCCAGCTCCCCGATGCCTTGGCTCCCACCCCAGGTTCCGGCCTCCATCCTTTGGCAACTGTGCCAATGGCCATGTCCACCCCCCACCTCCAGTGCTCCTTCTGGGACATCTTTCTTCAGTCCAGTGTCCCTGTCTGTCTTCCAGTCTTCCCAGCTGCTGCGATGCCACTGAGCTGGCTGGGTCCCAGCTGGGAGGAGGAGCAGACCCCACTCGAGGAGGGTAGGATTCCACTCCATAAGCTCTCCTCACCTGGAG (SEQ ID NO: 265).

[0335] MAX.chr14.2697 (DMRs 148):

[0336] CTGTCTCTGCTCCCTCTCTCTCCCCCTTCCCTCTCTCCTGCTCTCTGACGTTAAATGCTTGGTTACTCAAGGCCGCAGTTACAGGATGTTAGGTAAACAGCCCTCCGTCCCTGCCCCCGCCCTTTTACTTTCAATACCGAGAAAATGGAACAGAACGTTAGGGAAGGAGGCTTCGCGGGCTGTGCCGGCGCCTGGCTCAGCCCCTCCCGGCGGCCACGGTCGGCTGCCCGGCTGCTCTGACCGCGAGCGGCTGGGTGTCGGTGCCCTGCTCTCCTCTGGGCGCCAGGATGTTCCTGCCCAGTGCGTGTCCAGAATAGCCGCTCAGACACCGGCTCCAGGTTCAGCCAGGCGGGGCGCGTCCCTGCCTCCCTCCCCTTTGCCTGCCACTGCCCTCCTTCTAACGAGGGCTCAGCTCCGACTACCCCAGGCCTCCGGGGACCCTCTCCGGATGCGCTCCCCGCTTTGCGCTTTGCGCTTTTTGCCTGTTCCCTGGGGTCGCGGAAGTCCCGCTTGCCCGGCCAGCGGGTACCACTCCCCTAGTCAGCCTAGGGAAGCTACACACACACACACACACACACACACACACACACACACACACACACACACACGTACACACTCTGTTCGCGTTC (SEQ ID NO: 266).

[0337] MAX.chr14.4566 (DMR 149):

[0338] CGTCCGGGTTGGCCCCGCAGGGACGAGGGACGGCCCTGCTTCTAACCCGAGTGTCAGCAGCCACACCCCGCGTCTTGAGAGATTCTGATGCCCGCCATCTGGAGGGAGAACGCCGGACCCGGGGCGGCAGGCCAAGAAAAGCGTGGTCGCCGGAGCCTCCCGGGAGCCAAGCGGCACCATGTGTGCGACGCTATCATTTACACTGAGGAGCCGGGTATTTAGAAAACAGGGCTGGTACCAAGCGCGCCATCTGTGGCCAAGCGTTCCCGGCCCACCGCACCATATTGTGCAAGGCGCGGGCTGAAGGAAACAGCGTCCCGTGTCGCGCAGTGTTTGTTTGGTTTGGGGCTTTTGTTGTTTTTTGTTTTTTGTTTTTAACAAATTCAAATGTGGCTTCCTCACTTCGCGAAGCAGGCTCAATGGCCCCACAGAGTCGCTGGAGGGAAAGAAGGATTGCCGCGTTGTGGGATTTGCACGCTGGCCCTGGGAGAGGGAAAGATTGTCCCCCGCTGCGCGCACTGAGGGCGCATTCTCGGTCAGGCACTTGGCTAAGCGCGGTAGCTATAGATACAGATAGAGACATAGATCGCGCTCGCGCGCGCGCG (SEQ ID NO: 267).

[0339] MAX.chr17.2359 (DMR 151):

[0340] CGTTAACAATGTCGCGTACACGCCCGAACCGGAGGAACCCCATTCCACGCTCCTTCTGGAACCGAATTCACCTCTGAGGCTTTGGGGCTTCAGAGCCGGAGCCGCTTGGGCAAAACCAGCAGAACAGCGAGAGGGAACGGGCTGGTCTAGCCCTGCCCTGAGCATTTCTACTGAGACCCCCGGTCCTGCTTCTTCCAGCCTCTGCTGGATTTCTCTCCGACCCCTCTGGAGCGAAGCCCTTTGGCCCTGCGTTGCATGCGGCACGGTGCGGGTTCGGGCTCTGCGCTGGAGCCGGGATGCCCTCCGGCGGAGGGTGCGCGTAGGCGGCGCCTGGGCGTGAGCCCCGCCTGCAAGGCTCAGCGTCGGGGAAGCACTTTTCTCGTCGACCCGGGGTCTTTTTCCGCCAAGGAGCTCGGGGCTCAAGAACTCGGGACTGGGCTGTGGGCGGGGCATGGTTTTCCTCTCTGGGCGTCCTAATCTCCAATTTCAGGCAAATTCGCTAGGAAGAACCTTCCCGAGCGCG (SEQ ID NO: 268).

[0341] MAX.chr17.0937 (DMR 152):

[0342] CGGGGACGATTCTGGCGATCACATGAGGAAGGGAGCAGCCTCAGCAGCGCAGGTGGACACAGTCGTCAACCACTCGCTGGCCGCCTGCGACGTGAAGCACCTGCGCTGGGCGCGGCGGGTAAGCGCCGACACTAGCGGGCGCCTGAACAGTCCAGCGGCGTCAGCGCTGCGGAGCAGGAAAGGGTCCCAAACGCAGGGCGGCCATGCAGCGTGGCGCCCACCTGTCCCTCTCCTCGAAGCGCTGAGCCAGCACGATGCACATAAGGGAAGGAGGAAGGTGGCTTGAGGGCAGTGACCGAGCGGACAGCGGAAGCCCATTTCAGGAGCCCCGGTACCCGAGCTCGGGCCCCTTTCCAATCCCCCAGGCGTCCTTCCCATGTCCTTGTCTCCTAGTCCTGGGAATCCACGGCCACTCCACTCTCCTGCAGTACCGCGGACAAGAACACCATGTACTCTTCACAGGCAGGTGTCTTCTGGTGGACCCAACTCTGTTGGTACTTGTCGTCTCCAAAAAGTCCCCAAATGCGCTAGAGGCCAGCCAGCCCGGTATCCGAGAGGTAAGAGCCCCGGCGGCGCAGGCGGAAGCGTGTCTGTCGCGAGGCCTCTCTAGGACTCCGGGAGGACCCCTCGTTAGCGCAGGACCTCGGCAGCCGGGGGTTGGGCTCGAGGGCTGAGGGCGGCGCGCCATGCGCGGATTAGCTGCCATCCGGCGGGTCTTTCTGCCGGGGACCAGTGGGGTCGGACGCTGAGGGCCGAGGAACCCCGCCCCCCCACCGCACCGGGCGGGCTCTGGGGCGTCCGCGGAGGCTCCCGCGTGCGTGTGCGGGGTGGGGTCG (SEQ ID NO: 269).

[0343] MAX.chr17.851 (DMR 153):

[0344] CGGCTCCGATGCCAGAACCCAGGATTACGACACCGGATCAGCCAGAGACGCGCTGGAGGGGCCCAGGAGGGGCTGCAGCGCGCCGCAAATCCCCCGGGGCTTACGGGAGCCGCTCTTTAGGAGACAGCGCTGGACGAACCGGGCGGGGTGGGGATGGATAATCTTCAGGCGCCAACGCAAAACGGCCGCAAGACGTGGCCAGGCCAGGAGGCTCCTGGGTCCCGGGCCCGCGATGTGGCCCTTGCGCGGGGACAAAGACGAGGCCATCGCCCTCACGTGTTCCCAAAGACGCCCAACCTCATCAGGAGGCCGCCCCATCCGCCACCTGGGAGCGTCCCACACGCCCGGGCCCTTGAGGATGTCCCCTCGGCGATGTGCCTGACCGGGCGCTCCCCGCCCGCCAACCTCCAACCTCCAACCTCCGCCCTCCACCCTCCACCCTCCTTGCTCTGTCCGCGTGGACGCAGCCCCCGGTTCAGACACTAGCGGGTGCGCGGGGCCGCCCAGGACGGCGGGAGAGGACGGGGCCCTCCCTCCCCTCTGGTCCCCCAAAGCTCCCCGGACGCCGCGGCCGCGCCCCCTGCCGGCTCCCTCCGGCCGGCTCCCGCGTCCCACTGGGGCTCCTCTCCCGCTGCAAGGTCAGCGCTTCCCCGCCCCACGCCCTCCACAACTCCCCGCCCTTCCGTTCCTGCTGCCGCCGCCCTCTCCACCCAGGCTCCTGTCACCCACCACGGGAGTTCACACGCTCCAGTCCATCGGCCTCCCCCGGCCCGACCG (SEQ ID NO: 270).

[0345] MAX.chr***17***.3547 (DMR 154):

[0346] Note: In the translation of , the "chr17" in the original text seems to be a chromosome number, which is translated as "chr***17***" here to maintain the original format. If there is more context indicating its specific meaning, a more accurate translation can be provided.

[0347] MAX.chr18.9881 (DMR 158):

[0348] CGCGCCCCCTTAGTCGCTCTGGGGAATCTTCTTTCGCTGGGAGGATGAATGGGGCGCTCGCCGCGGCTCATGGCGCCCCCTAGGAGCGGCAGGAAACTTCTCCTGCAGGGCAGCGCGGGCCGGGCTCGCCCTCCGGAAGGCGGGCGGGGAGGGTAGTTGCTGGGGGTCCCTAGGCCGGGCCCCAGGACATCTAGGACATGCCGGGGGCTTTTGCTACGGCTTCATCCC GGAGCTCCTGCTCGGGGTTGCCGGCTGCCTCTGCTGGCGTCCCTCTTCCCTTCCTTTGCGTAAGCGGCAACTCCTCCAGGAAGCCAGGGGAAGGACGGGATTTCCTCTCCACGTAGGGTAGTAGATCGCATAGCCCAGCCGGATCGCCCAGCAGGAGTGCAGGGCGCGCTGGGGTCTCCGGCTTGTGGGTGTGCGGTTCGAAACCTTAGCTGGGGTGGGGAAGGGATGT CTTTAACCTTCTGTCTACCGTCCCCCTTCTCTCAGCCTAGAGGCAGGGGATGCTGCGGAATCAGACTGGGTGCACCAAGGCGGAGGCCCATGCCGGGCTTCGCCTTCCTGGGTTCCCGGAGTCGTTCGGGAGAAACCCTGGCATTGCCCAGAACTGGGTCCCGCACTCACTCCTCCATAATTCGCGGCGGGATCAGCGGGAGGGCGGAGGCGGGCGGGCGAGGCTCTCTGGCGGTGTGGCCAAAGTGTGCGGGTGTGGCCAAAGTGCGGCGGACCCGGTCCTGGGACCGAAGGGCCTCTCTCTGGAGCCG (SEQ ID NO: 272).

[0349] MAX.chr19.1656 (DMR 164):

[0350] CGAACCTCTCGCCTCGCCTCGCCTGACGCCGTTTCCTGCCCTTTATCTCTCCCTTCAGAATTAAAAAAAAAAAAAAAAAAAAAGACAGTCGGAAGCAGCAGCGCATGAGCCCCAATCACCACTCTGAAACAGGTGCGCGCGGTGGCCTGCGGGCTCGCGGGAGCTCACGCGAACTCACGCGCGAGCTCACAAGCTGCGGCGGCCGGCTAGGCGACTAGTGACGTCACCGAGGCTTGTCCCTGCCTTATTGGCTGCCTTCGACCAGCGCGCGTTTGCTGGAGTAGTCGGCCACGCCTTGCCAATCGCCAGGGGGCGCTCAGCGCTAGAGCTCCGCGACCCTGGGAGCCCTATAGAGAGACTCGTGTCATCATGGCAACCCTGCCCTACCTAATTGGATACCTGCTCCAGTTGGTTGGATCCATTACTCTGATTGGATGCCTGGCGAGTCAAGGCTTGTATATAATTGGATGCCGGAAATTTGGATCTTTTCTACGTTTCGCATTTCTGTCTCTTAGCCG (SEQ ID NO: 273).

[0351] MAX.chr19.4113 (DMR 165):

[0352]

[0353] MAX.chr19.0870 (DMR 166):

[0354] ATACATAATAAATACATAAAACGCCCATGGCAGGGACACACACGCTGGTTTGGGTTGGAGCCAGCCCGTAAACCCAAATTTGGGGGCCCGGGCTCTCGGCTGCTGCAGCACTGACTACCGTTAAGGTACAATAAAACTGACACATGGGCAGTGAGGGGAATTTGCTCTCCTGCCTCCCTCCCTAAGTTCATCTGCTGAGAAAAATGCTTTGAGATAAACCTGGAGCCACAGCTCTCTGCACAGTCAGATCGCAGGAACGCGGCCTAGCTGCTTCAGCCACGTTCTCGCGGCGCCACCTGGTGGCCATGGACCGCCATCGCCGCTGGACGTCAGGGCCGCCAGGCCCAGCGAGATGTCACCTCCTCTGAGGAGCCTTCCAGGATCGCACCCGGCACGCGCTCCACGCCTCGTTGTCTGTTCTTCGGAGCACCGACCATGATCACAAATCAGCTCGCTCGCTGTGTTTCCTGCCGGGTCGCTACCGCCATGATCCGCACGTAGTGGTCAAGGCTGAGGTTGTATGAATGTGGACGTTATAACCCTGGCTCCCTCTCCCTCCCTATGCTGGGCTCCCCTCGATCCCCAGGCGGTGGGGTGCCCCTGGTTTTTCCTTTTTAAAATTATAAGTCTGGCCGGACGCGGTGGCTCAGGACCGTAATCCCAGCACTTTGGGAAGTCGAGGGAGGGTGTATCACTTGAGGCCAGGAGTTCAAGACCAGCCTGGCCAACATGGTGAAACACCATCTC (SEQ ID NO: 275). <\

[0355] MAX.chr2.2307 (DMR 168):

[0356] <\ CGGGGCCTCGCAACGGCTCGGGTTTAGTGTGATCTGGGGAGGCTGCAGCCCAGTTCCGGCTACCGTGGGCGCCTGAGCAGAGCCGGGGCGAGTTGTAAACCTCAGAGAAAGGCACTTGTCCCCAGCAAAACGCTTGGAGAGGACCGTGCACGCTGTGCTGCCCCCGCCCCGAGACGCGCCGGGCCGCCGGGTCACCGGTTTTCCGAAAGGGACCCGGCAGAGACAAAGTGCCTTCGCCGCTGCGATAGGTTGGTTTTACTTTGCAATAAACAGCCCCTAATGGGACCGGGCGCCGGGCGGAGAGCTCGGCCCGGGGCGCGGCCTTTGCCGCCTGGCTCTGCGGGCCGCCCCGCCGGGCGCCAGGTTTTGGGGGGTGGCCCGGCCCCGCGTCCGCCACTGCAGGCCGCTCTCCTCCTTCCCGCGCACACAGCGGAGAAAAAAGGACGCAAACAGCATTTTACACTTTTCCCACTTTAGCGGGAATCGGAGGAGCCGGGCGAGAAAGCCCGAAAAGGGAGGCGGTTATTTACGACCGGCGGGTTGGAGTCTGGCACCAGATGGTGGGGGTCTGTCAGGCCCGGCCGCCCCGCCCAGCGCCCCGCAAACAGCGCCCGGTTGGCAGCGTCGCCTGAGCAGCCCCCATCTTCGCTTCCAGCCCCTCCCGTATATTTTCTCCCGTCCAAGTCGATCAAAGACG (SEQ ID NO: 276).

[0357] MAX.chr2.6334 (DMR 169):

[0358] CGCGAGGTCTCAGCGCTCCCAGGCGCTCCAGTGGGGCCGCGTTCCCCGCCAGGGTGGGTCAGGGGAATACTCTGCCTGCGCCCTCTCCGAGGGTCCGCGCAGAGCGAGCGCCTCTTTAGGTGGGGCCTCTGGCTCCGACCCCTGCTCCCAACAGGGATCTTCGTTTGCATCACCCAGAGGAGCTGGCCAGAGAGCCGCGCCGGAGGCCGCATCTCCCCTTGTTGGTATTGTTGTCGGCTTGCTTTCTTCTGGCTTCCCAGCTCAGTGACCCCGGAAAGGGTCGAGCATCCGACTCCGGCATGCTGGTTGGCTGCCCCCGGAGGCGGAGGTAGGGGGCCAGAAATGCTGACCTGGGCAGGCCCCCAGCCCTGAGCTCCTGGGGTGGACATCTCAGGGTCCCGGGCCTCCAAGCTCATGGCCGGTCTCCGCGGCGGCGGGGTGACCCACCAAGGGCAAGACTTTTTCAGACTTGCCTATGGTCACCAGGCAATGACTCCGACTGGTACGTGAGGGAGCTCGGGTCCCACCTTGAGGACAAGGCCCAGCCTTCCCCGGAGCCGCACCTCAACTGTCAGGGTGCAAGTGGTGGTGATCCGGGAGCAGTCGAGGCCCGTGACAAAACCAGGATGACCCAGCGTTTTCTAACCGCGCTGAGGCAGTCGCCTCTCCGGGTCGCTCCACTCCCGGACTCCG (SEQ ID NO: 277).

[0359] MAX.chr2.6585 (DMR 174):

[0360]

[0361] MAX.chr2.8149 (DMR176):

[0362] CGCCGGGGCGCAAGGCCGAGTCATCCCAGGCGTCCGTGGGCCGTGATTCCCACTCACGCCGGGGGCCCAGGCAGGCAGAGAAGAGTTAATGAGCGCGCAAGTGCAGGCGGTCACTCCTGGGCCTGAAACTCCCGCGCTGTGCATTCAGGGCCCTCGTGGCTCTCAGAGGCGCGTCCCAGGGGCGCACACTGCACCTTGGGCTGGGCAGCTCCGCCGGGTTGTGGCGAGCGGATGAGGGAAGGACGCAGAAACCAGGGCGGAGGAGCCGCGAGGGGCAGGACGAGGCTGCATGGGCCAGCGAGGGGGTCGACACCGAGCCAGAGTGAGCGCGGGGCCTGGGGCGCAGAGCCCGCCCAGGGAGCCGGGAGACGCCGCGCAAGCTCCCCGGACAAACGCAATGACCGAGGACGCGCGGGCGAGGCCGTCCAGGGAGCCCTGGTCCCTCAGCTGCACCGGACTGAGCCGCGACCGCTCAGCACGCGCTGCTTATAAATCAGGGGTGCGCTTCCCAAGCCCCGGGTGAGGTCCCCTACGTCGGCACAGCCTTAGGAGCTGCAAAGCAGCGCGCGCCTCCGGGGCTCCTGCGCGCCCCTTGAACCCCGCCTCCCGCATCCTCCTGCAACAGCCTGGAGCTCCCTGTGCAGGACGCAGCGGGGGGCGGGGGGCGGTCTTAGGAGGCTGCGGGGCGCACTCCCACCTCCTGCCTCCCCGAGACCCCCAGCGCCTTCTCCAGGGTTTAGAGCGGAGGTGAAGGGGCCTCGTCCTGCACCGCCACTGGGCGCCTGGGCTGTTCATCATCGGTTACCGCCG (SEQ ID NO: 279).

[0363] MAX.chr2.6033 (DMR 177):

[0364]

[0365] MAX.chr20.8579 (DMR 181):

[0366]

[0367] MAX.chr20.3480 (DMR 182):

[0368]

[0369] MAX.chr21.5638 (DMR 183):

[0370]

[0371] MAX.chr21.7663 (DMR 184):

[0372] CAAAGACAGTTATGGATAGAGCTGGGAGCCCGAAACACATGCGGCAGTCTCTCAGTTTCCAGGTACCGGTTCTCACATCATCCATGCATGTGTTTGAGGAAAAACAAAAAAAAATTGATGGTTGCCAAAAACAAAAATGCTTCCATATCAAAGTTTATCAGTGTCAATGTCAAGAGACTTCTGGTTCGTAGACTCATTTTGGCTTGAGGCCACCAGAAGTGAACTCTGGTTTCTAAATGCAGAAGCAGAGGCACTGGCCGATCATGGAAGATGCAGGGAACTGTTCAAGAGGCCCAAGCCTGGTGCTCAGAAACTTGGCAGGATCAAGCATCTCGCCCAGGAATTCATCCCCTGCTTGTCTAAGCCGGCTGGCTCTCGTGACTGACTCGGAACAACAGAGCAGATGTTTGCGTGGGAGGCAAGCCTCACCCAACATCTGTCCTGCGGCGGGAAGGCCTGGGTGTTCACAGATAGAGCTGGAGTTCCCCGGTGGGTGGCACAGACAATTAGCTGGGGCTGCCTCACATGTAATCTAATTACAGGGGAAACAGGCTCAAACACCGGGTGATAAGCAGCGCAACTGTTTCGGGTGACTCTGTAATTTTTCCTCCATTAATTTTCTCCATAACGCACATGATTGTCATAAGGGTTAATTAAAAAGAGCGTGAGTGGCCTCATGTCACATGTAGCTGGACCAGAAAGTGTTGAGTACCTGCTCATGCGTGCAAGAGGAGGAGGGAGGAGCACATCACTGAACTTCACATGAAATTGGATACCCGGGATTAGAGACAGTAGAGGGTTTTGGTGAAA (SEQ ID NO: 284).

[0373] MAX.chr3.3606 (DMR 186):

[0374] CGCGCCCGAGCGCTCCCGGCTTGGGATTGATTTTTGGCCCCCGCTGCAGCAAGTTGGGGGCTGGTGAGGAGTGTAGCGGTGACTGGGGGCGGAGTGCGGACTCGCATCCGCTGTACCAGGAGCCCACTGCCACCTCGGGATTTTTTTTTTAACTTGGAATTTCCATATGACAAAAAAGAAAGAGGTTTCTCCTCAATCTAACGGAGCCATTAACATCTATTAATAACGCCGACAGGGTAAGTAACGGAGCCGCGCTCCTCGGGGTGGTCACCGGGCTGCGTGGTCCTCGGCCGGCCTCCTGCATCCGCTGCCCCTGTGCGCTCCGGGCCGGATGCGCAAGGGCGGCGCGGGGACCAAGCCTGGCTGCCGGCCGCCTACTCCTCCCCTTCCCTAAGGTAAGGGGTCGTTTTCACACTCACCAGAGCTCCTGCGGGCTGAGCTCGCCCCCTCCCCCGACTTCTTTGCGGGGCATTTTCTCTTGCTGGTGTATTACGTGTCATTTCTCACGGGGCATTGCCGGCCG (SEQ ID NO: 285).

[0375] MAX.chr4.1655 (DMR 190):

[0376] TGAGTCTTTATTTGGGTACGTTTTATCTACAGCGGCGGTGTTTGCAGGACAGGGCCCTGCGGCCCGCGGCCCTCGGCCCTCGAGGATTGGGCCTGGCGTCCGGAGTCCCAGTGCGGGATCGTGGTAGCTCCCCGGCGGGTCGCTCCTCTCCCTCCTCCTCCTGCCCACGCAGCGAGCAGCCAGACGCAGGTGGACCCTGGTGGGCGCCGGCAGTGCGAGCGCGCGCGCTTCTTCAGGGTGTGAGCGCGCGGGCGCGTGCACCGGCGGGTGTGCGCGCCGCCTTACACTGCGGTCCCCGGAGCCTGTTCCGCGCGCAGGGCGGTCCTTTGCAATTACCGCGGGCAATGATCCTTTGGAAGCAGAAATTAAAAGTTGGGAGAAATAATGGTGGACCGATCGGCTGTAATTTGGGCCAAGCTCGGACACGCTGAGCCCCAGGGAGCCTGGAACTGGTTGGGCGGGGCGGGGGGGGGGCGCAGGGCTTCCCGTCCCTCTTCCCCTCCCCTTCCCCTCCCCTTCCCCTCCCCCGCCCTCCCCGCT (SEQ ID NO: 286).

[0377] MAX.chr4.4040 (DMR 194):

[0378] CGAAAACTACCCCGCGGAAACTAGCACAGTGTGCCTGGATGTCTGTGTCCCGGGACCTCGGGGAAGAGGGCCCGCACCGGTCTGCGAATTGCAAGGCCCGGCCTTCCCCAGCGACGCTCTGGTATCCGCTGTCCCCTCCCTGTACCTCCGCGACCCAGGGGACGCCCAGTGCACCAGGCCCTTCCCCGGGGTCAGCGGAGGCGCAGGGCGTTAGCCACATCAGAGGTGCAAATTTACCCCGGGCCCAGGGGAAAATGGCGACAGCGTTCGCGGCTCCACCCGGGGCGCGTGTCAGCGTTGGAGAGCCTGCCCGGCCTGCAGAGGGCGTAACAGGCACCGCTGGGGAGAGCCAAGCACCCCTGCGTCCAGGATCCGTAGCGCCGAGCTGCAGGCCCGACCTGCAGGGGGCGTGCCCGGCATGGGAAGCTCAGGCTACGTCTCCGAAGCTTGCGCTGAAAACACCAGAGGTAGGGAAAACGGGGAGAGCGTACTGTGCTGGGCTCTACCCTGGACACCCCAGTTTCATTCTCTGCGAAGCCACGCGCTGGCAGGGCTCTCGGGACGGCGATACCCAGGGATGATGGTACCCCTGGTCTCGGCGGGACCTCCCGGGAACTTGTCCTGGGGGAGGGAGCCCAACTGGCCACGTACTGGTAGCAGCAGTGGGTGGAGCGCACAAACTCCGAGGCCCGCG (SEQ ID NO: 287).

[0379] MAX.chr4.5903 (DMR 195):

[0380] CGCGGTGCGGAGCGTCTGGAGCGGAGCACGCGCTGTCAGCTGGTGAGCGCACTCTCCTTTCAGGCAGCTCCCCGGGGAGCTGTGCGGCCACATTTAACACCATCATCACCCCTCCCCGGCCTCCTCAACCTCGGCCTCCTCCTCGTCGACAGCCTTCCTTGGCCCCCCACCAGCAGAGCTCACAGTAGCGAGCGTCTCTCGCCGTCTCCCGCACTCGGCCGGGGCCCCTCTCCTCCCCCAGCTGCGCAGCGGGAGCCGCCACTGCCCACTGCACCTCCCAGCAACCAGCCCAGCACGCAAAGAAGCTGCGCAAAGTTAAAGCCAAGCAATGCCAAGGGGAGGGGAAGCTGGAGGCGGCAGAGGCGGCGGCGGGAGAGCTGTGGGGTTGTTCAGGAAAAGTTGGGCTGGGGGCTGAGGCACCTGAAGCAGTGAACCAGGACTAGGTAGGAAGCAAGAGCATCCTCCTGCGCAAGCGGAGACGCAAACGCGCTCCTGAACCCATGCAACCGCCCGGCCCAGCGCCG (SEQ ID NO: 288).

[0381] MAX.chr5.2699 (DMR 196):

[0382]

[0383] MAX.chr5.1156 (DMR 197):

[0384] CGGATTCCGAGGATCCGAGGGAGTCGCTTTCAGACTTCCGGTGTCCTTTCGCGTTAATTTCGTCCTCTTTTCTTCTCTGGGCTGGGGCTGGTGGCTGCCACATCCCACCCCTTCTGCCCCGACGGCTGCAAACCGCTTCAGCCAAAACGGGCGGAGAGGCGGAGAGAATCGAGACGCTGGAATCAGTTCCTCGGAGTCCCGTCGCTGGAGGTCACAGCTGGGAAAATCAGGTGACATTCGAGTCAGATGGACAACGACTCAGATACAGTGAAGAGGAAAATGGTTGTCCTGGGGCTGGTTCGCGCCTGCCCGGCGGGTGTGAAGCCCGGGGAACCGCGACTTTGGAAGAACCTTCGGCTTGGCGGTTCAGGTTTGGGAAAAGAGAGCTGGCGAACTGCCGCCTGTTTTTGTGCCCGCGCGGGGGACCAGCCGGGCCGACGGCAGCGCTGCGGGTGGGTTGGGTCGTCGGCCGCCGCTCCCCGGAGAGGTGAAGAGTCGCACCTACCACCGGGCAGCCTCCGCGGCTCTGGCCGAAACCCCGGCTGGCCGCAGCTCCGGGAGCCCCCAGCCCTGTGCTGCTGCGGCCGGCTCAGTGCTGAATTGATGCTGGAAACGGCTGGCCAGCGGGCCTAGGGTCGCCGCCTTTCCCTCCTCGCCTCTTCCTTCCTTCCGGGTCGTGCCCTCCAACCTGCTGTGCGTTACCGCAGCCAAGTTTCCACCGCCCGGCGGAGCGCATTGTGAACAGCAGCTGACAAATTGTTGTGTTGCACACACACACCAAAAAAACCCATTCAGTCTCGTATAATTCGGCGCAAGCGGTGTCTGTGGAGAGCCTCCCGGGGGCATGGCACGGGGGACCCGGAGGCCAACAAGCTGCGCGATACCGGAGCAAAGTCGGGATCAGCAGCCGCCTTTCGCGGAGGGCGTTCTGCGCTCCAAGCAAATTGGCGAAATGCGGGGATTCAGACACGAAACGAGCGCGCTAGAAAGGGTCG(Array number 290).

[0385] MAX.chr5.3053 (DMR 199):

[0386] CGAAGTCAGAGCCGAGTCCCGAGGTCAGAGCGGCCGTCCTCCGCTCGCACCCCCAGCCTGTGACCCGCCCTTCCCGGCTTGCTCGAGACCCACTGGCGCCAGTGCTGCGCGTGGGGACTCCGTGCATGGCCGAAGCGAGGGGGAAAGTCGGGGCGCTGGTGTCTTTTCAGAGGTTCCAGGAAAGAGGGAGGCTCGCGTTAGGACTAGGAGGTGCCAGTCCACGGCTCCTACCCGCTCCCGACGCCCGCATCCTTCTACAGCCCTCCACCCCGTTCCTGGTCCCTGTAGAGGGGAAGGTCCTCTCCCTGCCCCGAGGCGGGAGGAAAAGCGGCGAAGAGGAGGCTCGAAGGGCGCCGCGTAGGGCAAGTGGGCCGAGGACACCGGGGGCGCGTCGGGGAGCGGGGAGTGGGCGGGGTGGGATGAGGCAGGGAGGAGCCGGGCCGGAGCGGAGTGGAGTGGACCGCGGGCGGACGGACTCGGGCCGGGCCCCGGGGAGCAGCTCCGCAGTCGGAATGGACGTGCTCCAGGCGCCCTCTATGGTCCGAAAGCGGAATGCGGCCTTGAGCAGCGCCCATCTCGCTCCTGGGGTGTGGGGGCAACTCTGGGGGCGCTGGGCCTTGGGGCTCCGTGGGCACGAGCCTGCATTTGTAGTGATGGGAACCAATTTGTGTTCCAAGGCTGCACCCACTGGTTCTTTTTGTGTGTTTTGGGGGAGTGCCGGGCCTGCAGGTTAGGCTACTGGCATTTGGAGGGAGTGGGCACTGGGCTCTACGT (Array number 291).

[0387] MAX.chr5.5180 (DMR 200):

[0388] TATTTTTAAATGCTCTTTTTGTGTCTTTTGCTCTGAGAACAATGCTACCGGTAGTTTCCAGTGTGTTTGCTTTGCCTTTTTATTTGAATTTTAGAATTTATTATTTTAAAATTTTATCTTATTTAAATGTTATTCATTTTTCTTCTACTAATTTTGAGTATCACAGCTTCGTACTCCTTGACTTGCATTCTCTCAGGAGCTGGGGAGCCAAGCTCGGTCTCCGCTTCGGTGGTTTCAGGTCCCGGGTTCTGTCTGGCGGCTCTGCTTCTAATGCGGAGCTGGCGGTTTTGCAGCAACGCTTTTGCCAGTAGCGCCCACTGAGCGGTTTTTCAGTTGCTGCACCGTTCTTAGCGCCCAACGGAACGTTTCCCGTACGCGGAGTCCATAAGTTGTCTGTGTCGTCACTTTCTCGGTTCTGGCACCGCTAGTATCTCCTAGGAACTTCCTAAACCCGTTTTACGGTGCAGAACGGTAATTGCACCGAGCCTCTGTGCCAACTAGTACTTCCGTAATACCGTTAGCCGGCTCTTTTCCTGTCACAACACATTAAAACGTGTTAAAACACATTAAACGGATTAAACACATTAAACGGATTAAAACACATTAAAACGTCACAACACATTTAAACAGAGTCGGTCCATTCCTCCAGACAGTATGTTTCGGGATGGAAGCACCCCTCCTAAGAATCCGCAGTTTCTTTCTAGCAGCACCGTTATGGCGCCTAAACGGATATTTGTTTGGCAATACCAGCGCTATCCGCTAGGTGCCGGCGCTTGCTGAGTCTCAGCGCCGCCAGATTCTTGCTAGCGAGGTCCAGAGCAGTGCAGAGACCTAGCGGACAGTTTTCCGGTGGCAGCAATGCTCATTTCCCGGACACAG (SEQ ID NO: 292).

[0389] MAX.chr5.5268 (DMR 202):

[0390] CAGGGACAATCGACGTGGTCCGAGAGAGGAAAATAAGGGTATTTCTGGGCCCTTCTCTTTCAGGAGTTGATCAGGTTGGCAGATCTGGAGGGCTAATCCAAACAAGGCGCTTGACTTGTGAGGTCGCGAGTCTAGACAGAGCTGGTGGCTCGGCGGCTCCTTATCTTTCCCTGGAATCAGCCGAAGAGGCGCTCCCCGGCCCACTCCGCTCGGCTCGCCCGGGTCCGGAGCCACCGCTCGACGCAGACGGCACAACAAACAGCACCTGAGGCTTTATAGCTCGCTTTATTGTTTAATGGAGAATGCGGCATAACATTCATTTGTCTTCTTGGTTCCGCGACCTGGCCGCTTTGCAGCCACAGACGCTGGGTACGGGCGTGCGCCAGCGCCCGGCCGTTATGGTCCCCATGTTGAGCAGCGCCGGGCGTTCCGCTTCGGCATCGCGCGTGTAAGCGCGCACGGCTCTGTCCGTGCGCCCTCAGGCCCCTGGAGAGGTACCCAGCTGCAGCCCCTTTCTTGCTTCCAAAGCCCGGAGGCGGAAGGGTGGAGGGACAGTGAAAGAAAGCTTAGGCGAGGTGTCTTTGACTAATCCAGTATCTCCTCTTGCTGCTTGGAAATGACAGTTTTGCGCCAAAGCC (SEQ ID NO: 293).

[0391] MAX.chr5.4245 (DMR 203):

[0392]

[0393] MAX.chr5.3918 (DMR 204):

[0394] CGTCCCGGACACGCCTCTTCTGGAGAAGCGCGTTTGTCCCTTACTTGGGAGGTCCCGGGTATCTGAAGCGGATCCCGGGTCTGGGGACATGAAGGGGCGCCGTGGCCTTAGGGAAGGCCCCAAAGAGGCCTAGGCCCCGGAGGAGGCAAGAGCCGCGGCCTAGCTTCCACCGCGTACCTGGGGCCAGACACGGCTGGGGCGGCGCCGGAGAGCAGAACTCCAGGCTCTGAAGGCCGAGGGTGCGAATTGTGGTCCCCTCCCACCCACGGCCTCCCCATCACGCGCACGCAGCCCGCGAGGGGCGCCCTCCGCGCCACTGCCCCAGGGACACCGTTCATCTGAGGAACTCTCGCGCCCTGCGTTTCGTGCCGACAGCGACGCTCGGAGTCCCACCTGGGAAACCTGGGTTGGCCCGGAAACCTCGGGAGGCTCAGAGCTTGCGTGAGGCGCTCGCGGCGCCCCAGCATGCCGCCCCGTCGCGGAGACCTCACCTTGCAGCCCAGAAACCGAACCCAAGCCCACTGCAGGGCGAAGGGCCCACGCGTTCCAACTGGCGCGAATATAACCATTCCCAAGACCGGCCCCTCCCCTCCCCCCACGAGACCCCTCCCGCCG (SEQ ID NO: 295).

[0395] MAX.chr6.0016 (DMR 206):

[0396] CGAGGCGAGTTAAATTCCTTTTGCCGGTGCCTGGCTGCGAGGACAAACGTCCGTACTTTCGTTCGGGAGCCACGGGCAGTCCAGGGGCTTGGGTTAGAAGCAACGGCTCTCTTCCAGGGGCTGTGATCCGGGTCGGCCAGGGAGAGCGAGGCCCCGGGGTCCTCTGTGAGGTCCCCAGCGAAGAGACGCAGCTGGGGAAGGCGCCGCCCCCGGGCCCCCTGCGCCACCCTAACCGGGCCTCTCCTTAGCAAAGTTGACAAATTCTTGAGAGTGTCAGCCCAGGGCTGCGCGTGAGGGCGCTGGGACCGGGGAGGAAAGAGCACCTGCCGCGCTCAGCCCGACTTTGAATTTGTTTGTTGTTACCGTTTTTGTTTTTCCTCCCAGTTTCCATAAACGCTTAGTATTTCGAGGCACTTTGCAGGTGTTGGCGCAGGTGATGATGGGCCTCGTTGGACTCTGCCTCCCACGCATCCTTTTGTTTTCTGCGCGCCAGCCTGTCTGACTGTGTCCTGCGGGGACCCCGAGACAGTCCGGGGTCAGGGCGTAGAGACTCATGCTTGCCACTTGACCCATCCGCAACCCGGGGACCCCCTAGCCCGTCGCGGAGCTGGAGTTTGGGCTTCCGGCTCCCAGCTCTCCGCCCTGGATACAGGAAGAGGGCGGGAGAGGTCGCGCACCCGCGCCGCTCGGCGGGGATCGCTCACAGGGGCTCCGGGGCCACCGCGAGCGCGGACTGCGGCTGCTGGCGGGCTCCTTCGTCGTCCAACGCACCCCATCCTCTCCCGCCCCGCAGTGTCCCAGGGAAGGCTTCACTGAAAACAGACGCTCGACGGAAAACTGACTCTGCAGGCCCGAGCTTTCG (SEQ ID NO: 296).

[0397] MAX.chr6.8227 (DMR 208):

[0398] CCAGCCTGGCCAACATGGTGAAACCCCGTCTCTACTAAAAAATACAAAAATTAGCTGGGCGTGGTGGCGGGCGCCTGTAATCCCAGCTACTCGGGAGTCTGAGACAGGAGAATTGCTTGAACCCAGGAGGCGGAGGTTCAGTGAGCGAGGTCGCGCCATTGCACTCCAGCCTGGGCGACAAGAGCAAAATTCCGTCTCAATAAATAAATAAATACAAAAAACAAAAACAAAAATAAAACCCATCTGCCCAGGACCATTTAGGGTCGCGGTGACCGGAGAACCACCCCGAGTCCAGGCGGCGAGAGGCTGCAAATTCCCTGGTTCCGAGGCCTCAGGGAAGAGCCCACCTGCCGGGCGAGCGTCTCCAAGAGTGAAAAGGAATCCGCACCCCGCGCGAGGGAGCCGGGTCCTGTGAACTCTGCGGTGGCTTCGTGGTTGCTTCCCTGATCCATTCGCTGCAGTCTCAGAGTTGGAGCAGCTTGGCGTTTACTCCCGGGCCTTTCCCGGATGGGAGAAGGAACCTGCGCGGGAACTTGAATTTTTTCGAGTCAGAATCAGCAAGTTGTTGTTGTTTGAGACCAAGTGAGCCACCGCACCCAGCCAAGAATCGGCTGTTTAAGAAAGACTAGGTTTCCACGTAAGAAGCAGGGTTCTCTGGGCCAAATGTTGACCTTTTCTCTTTTCTTTTTTCTATCTTCTTGATGAAGAGAATGCAATAGGAAGAATGTGAAGATTTTTAAAAATTGTTTTTGGTTGTTTCACGTTTGGGGATTTTTTTTCCCTGCAAGGAAA (SEQ ID NO: 297).

[0399] MAX.chr6.3523 (DMR 209):

[0400] GGAGGAGAGAGTGAGAGACTAGTCTTAATGGAGAGGCCGGCCTGCCAGAAACCAGGGCTCTATCCTCCAGCGTCCTGGAGTATGGATAGAGTCAAAGAGAGGGACACCGTCGTCAGGGCTGCCTCCCTCTCACCAAACCAGAACCAAAAGGCGCCTAACAGAAAAACCAGGGCTCTGTCCTCCAGCGCCCTGGAAAAGCGGGCAGTGTCAAAGACAGGGATGCCCTCGTCAGGGCTGCCTCCCTCTCACCAAACAGAAGTCAAATCTAACTTACCTGACCCCGGGGTCAGAAGCTGAGGACTCAGAGGTTGAATTTTGTGGGCACACACACACGGTAGTCGATCCGCTGTCCTCCGGAAGACGGTCGCCTTTCGGGGACCTGGAAAATTTTTTTTCAGGTGGCTCCTCGCCTATAAGCCGGCCGTCCCTCCGGGGGAGCCCGGAGCTAGCCCGGCTCTCGCCCAGTGGCGAATATATCTCGCTGGGGCTTCCAAATGTTGTACCCGAGCGAGTTAGAGAAACGCCACACTTCGAGACGAATTTAAGAGTCCTTCATTAGCCGGCGACCGACAGACGACTAACGCTCGAAATTCTCTCGGCCCCGAGGAAGGGGCTTGATTTTCCTTTATACTTTGGTTTAGAAAGGGGAGGGGGAGCTTAGTTGCAGCAATTCTACAGAAGTAAAAGCATGCAAAAAAATTAAAAAGACAAATGGTTACAAGGAAACAAACAGTTCCAGGTGCAGGGGCTCTAAATCTATCATAAGGCGTTAGGTATGGGGGCTCTCCCGGACACAAACTCAAAGCTTTATGGTGTTATCTCTTGAGCGAAATCCTGGTAACT (SEQ ID NO: 298).

[0401] MAX.chr7.6951 (DMR 210):

[0402] CGAGGGCGTCGCTGCTCTCAACCCCTCTCCGCTACTGCCCGGCCGCCCAGGCCTGTGGACGCGACTCCATCTGTAGCAAAGTTCGGGGGCCAAATGGGTCGCGGCTCTTCCTCGAAGGTTACTGCGAGCGGGACTTGAAGGGAAAAGGAGGCGCATTAGCGACTTCGTTTTCTTGCATAGTACTGGTACAGAGTACCGGTGATGGTCGTAGGGGAACTCTATGTAAAGACTGGATGACCACCGGCCTCCCGGAAACCCCACACGCCAGGCCTCCAACTTCTTCACAAAAGTGGGGTGGGTGGCGGAGGGCTGTGGCGGGGGCTTGGAGCTGCTGAGAGCCGAGAGGCGCAGAGCGCAAGCTGGCAGGCTGGGCTGCTATCCCGGCGCGCAGATGCCCCGCCGCCAGTCGAGCGCGAACATCTCTCCGGAACATCGATCTATCACCTCCCTTTAAGGACCCGGACCGGGAAATTTCCATTTTCTGTTTTGGGAATAAGAAATAAAAGCGACCAAGCTCTTGCCCTAATTTCCCCCCGCGGGCCCTTCCACGCGGGCTGGCGGGATCAGAAGGACGGGTCCGAGCTCGGGGGCGCGGGGTTCCTGTGAACTCCGGGCTTGCTCGGTCCGGTCCCCGCGCCTGCTGTCCCCAGGCCCTCTCGGGAGGCAGACCGCGGCAGCGCAAAGGGGCTTCGAGGATCTCTGAGCAACGACGGCTGAGTGACCTCTTTCCCTCTCAAGCACACCTTCAAGGAGCCGGTGGACCCTCTCACCGCCGGTAGCTGCAGGCTGAGGGCGGCG (SEQ ID NO: 299).

[0403] MAX.chr7.9016 (DMR 211):

[0404] GCGCAAGGAGTGAAAACGGCGAGTTTGGGATGAGAGCCAGGGCCAGGAGGGGAGCCTCGCCCTCGCTACTCCTTCCCTTTCTTCTAAAGCCAGGGAGCTCCCCGCCCAGCATTGCCCGTTCCTTCCTCCCCGCCAGGGCCCAGAGAAATCCGGGCTCCAGCACCGGGCCTCAGTTTCCCGGAAGCGGACTTGGGCCCCGATCCCGGGCCCTCTCCGCCCTTCCCAGGTCTCAGGCGTCGCTGCGTGGAGGAGGCGCGCGTGGCTCCCGGCGCCGATGTCCCGGCCCGGAACCCTGCCCGCCGCTGCGACTCCGGGGCGGGGGTGGGTCAGCCTCGGGGGCGGCCGGGGTGGGCGTGGAGGTGGACGCGGGGCCGCATATTGGGCGCTTGGTTCTGTTTATCTCACTTAGCGGTGGAGGGACTGGAGGGAAGGGGCGGCCCGAAGGGAGGCCTTGGTGGGGCCCAGCGGCTCCCTGGCGCACCCCGGACACGGTGGCCACGAGGAGCCGGGGCTGTGGCCG (SEQ ID NO: 300).

[0405] ​​​​

[0407] MAX.chr7.7860 (DMR 216):

[0408] CGCCGCAGCAGCCTCCGGTGGCACGGGCAGAAAGATCAAGCGCGGCACCCCGTGACAGGATGGGACAGATTCCCCGGGCTCCGAGGCCCTAGGATGGCGCAGGGCAGCGGGCTGGTGCGGGAAAACTACAGAGCAAGCGAGGGAGGGAAGCGAAGGCAGGGGAATCCCTCACCCCGTCCGGCCCGAGTGTCTTTTGAGAGCCCACAGGCGAGCGGGGCGGGGGGAGGCTCCCCGCGCATTCCCACCGTGGGTTTGCCCAAGGTCAGAGGCCCGGGACTGGCGGGGCGGGTCTGGCCGGCATTGCCCGCGCTGAGCGCGCTGCAGAACGGGAGCAGGGCACAGGGTGGCGCTCGCTGTCCGTGCAGCGGGCGGAGGCGGCCGCGGTGCCTTTGTGTGCGGTGGGCGCGGCGATGGGCTGCTCCGGCCCGCAGCCCGAGGGGAGCGGCGGGCCCGGGCCGGGGCCAGGGCTCGCGGGGAGACCCCAGACCACCACCTCACTCTTCGCTGCTACGTGCAAGCGGACCGTGCGGATCGCCAGTTCGGAACCCTCCCCGGGAGGGCCCCGGGGTCTTTCTCAATGTACTGGGCACTTCGAGGAGCTGGGAAGAGGAAAGCGGAGGGTAGCGTTTAGAAAGGGAGGGAAATCCTCCCAGGCTCAAAACCTCTCGCAGAATTCATTCGAAAAGAGAACGAAGGGAACTTTGGGCAGGCCGGACCTCGGCTCAGCGCCCTGCGAGAGAAGCAGAGGTCGCTGCCAGCGTTTCCTCCCGCG (SEQ ID NO: 302).

[0409] MAX.chr8.6940 (DMR 221):

[0410] TTTGTAAGGCTAGGAGAAAAACGTTATTTTAAATATACGGAATTTGCTCCTCTCCAAATCCACTCTCCCTTTCGCCTCCCTAGAGGTTGTCAGGTTCAAGAAGCGGCCCGGAGTTGCAGGAAGGGCGCCGGCGTCACTGGCCCCAAGAGCTCGGAACGCGCGCGCCGCAGGAGTGCCGGCTGCGGGGTCGGGTTGAGACTGGCGGGACCCTCGGCCTCTGCCGGGGTGCGGAAGGTGGATGCTACGGGCAAAGGGGCGGGGCTTGCGGTTCCCAGATCCAGAGGCGGGTTGGGGACGTGAGCCGGCGTCCATGTGTTCTGCACCCCTTCTCGCCCGGTGCCTCTCTCAAGGCACGTTTTCCAAAGTGTGTTGAATTCGGGAATCGATCGAAAATTTCAAGGCCAATTAAATGCCCTCTGATGTAGAGCTCCGATTAGGCCCGAAAGGCTTCAAACAGCCCCTCTAGACCCTCGAGGGTCTTCGCCGCGGTAACCTTAGGCGTCCCCTCCCCGAGAAGTCTCCCTGAGGCTTTCACAGAGGGCGGGAGGGGCTGCGCTGGGGCCTCCGTTCCCAGTGCCCCTGACTGGTGGGGAGGGATGGCCTTAGTGTCTGAG (SEQ ID NO: 303).

[0411] MAX.chr8.6725 (DMR 223):

[0412]

[0413] MAX.chr9.5748 (DMR 226):

[0414]

[0415] MAX.chr9.9611 (DMR 227):

[0416]

[0417] MAX.chr9.9692 (DMR 228):

[0418] CGTGAGATGATAAATTTAAATAGTGGCACCTATTCACCCAAGGGTTGGTCACAAAGTCAGTGCGATCCCCGTGAACACACCCGTGAAGCTTTGCTTCCCAGCAACTTTCCTGGGGGCCGCGGGCGAAGGAACACCCCCAGATGCCGCTGCGCAGGGACAGGGGACGCGCCCAGACGTAGAGGCCCTGACCTCTGAATCTTGGCGGGGCACCCAGGAGCCCGGCTTCGGGGTGCTTAGCGGGGCGAAGCCGCCCCCGGACCCGCGTGGCTCCAGCCTCCTGGGGGTACCTGGCAGAGGGGGCTGCAGCGAGCGCCCTGCCGCGCCGCTTCCTCCGCGCGTCTCCCGCCTGGCTCCGCCAAGACTGGGGGCTTCCCCATAGGCCCGCGTCCGAGCGCGTCCTCAGGCTTCGCTCCGCGAGATCTGGGGGCCCCGTGGGCTGGGGTTCGGGCGGGGTCCGTTCCTTGCGGTCCGCGGTCTTGAAGCAATTTCCCGGCAAAGTCCCGGGACAGCGGGAAAGAAACTGGTCTCCCTGCCTGGGGTCGTTCCCGGTGGATGTGCCTCTTCATCAGACGGAATTTTCCGTCTGTGCAAAAATGAAGCTTACTCGGTATCATGTGTGCTTTTTGGGGGGAAGGACAAAAAAATATATTTTCTATAAACAACTTAATTGGCTTATTAATACTCAAATACCCTGCTTC (SEQ ID NO: 307).

[0419] MAX.chr21.9298 (DMR​​​CGGCGACGTGGTGCAGGCCTCGCGAGTGACGTGAGGGTTCATGACCCAGGTGTGGGCAGCCAGCCCTTCACGGGAGGCCACCCACCTGGCCACAGTGCCTGGGAATTTAGGTCGGGCACTGCCGATATGTCGCCTTCCACAAGGCGGGCCCGGGCCTCTGCTGACCGTGCACCGGTCCTGGGGCTGGGTAATTCTGCAGCAGCAGCGCAGCCCATGCCGGGGAATTTGCGGGCAGAGGAGACAGTGAGGCCCGCGTTCTGTGCGGGAACTCCCGAGCTCACAGAGCCCAAGACCACACGGCTGCATCTGCTTGGCTGACTGGGCCAGGCCCACGCGTAGTAACCCGGACGTCTCTCTCTCACAGTCCCCTTGCGTCTGGCCAGGGAGCTGCCAGGCTGCACCCCGCGGTGGGGATCGGGAGAGGGGCAGTGTCGCCCATCCCCGGAAGGCTGAGCCTGGTGCAGCCAGGGAGTGAGGGGGCGGGAAGCCGGGGTGCTGCCCTGAGGGTGCCCCGACACGCTCTCCTGGGGCCCTGAGCGGCTGCCACGTGCG (SEQ ID NO: 308).

[0421] MAX.chr1.7620 (DMR 453(66)):

[0422] TTACAACAAGATTGGCCAGCTTGGAGCCTGACTTTCCACTGGAGGTCCCGCTCCTGAGGGAACCCTGAGGCTGCACAGCCACCGGATCAAGGTCACATATGGGGGGACAGAGGCTCCCACTCCTATGGTGCCCTTACCCCTTACCCTCACAAAGGGCCCCACCGCCGGAAGCCGCCCGCGCTCCCACACCTTGTGCAGGTCTCCCCTGAAATGAATTTTAATTTCCGCTGAGGGCAGGCGGCGTCGTGAGTCCTGAGCCCGTGGCGGCGGCGGCGGCGCGGGTGTGGGGCCGCGCGGCCGGGAGCGGGCGGAAGAGAGCGCGAATTTGAATTTCAAAGGCATCTGGAACCCAAGTGCTTCTGCGTTGCCCGATTGTGTGTGTGGCGCTTTTGTGTGTCCGCGAATGCGCGCGTGCGTGTGTGGCGTGTGTCTGGGTGTTTTATGACTGTCCTCCGTGAGGCCGTGTGTGAGCCCTTGCGTGGGCCGTGAGTGCGGCAGGGAGCGCGGTGTCCGGGGGCCGCCTGT (SEQ ID NO: 309).

[0423] MAX.chr1.5214 (DMR 454 (67)):

[0424] GCAGGCACTACTAGGGCCTCTGCTTTACAGGGAGGGGAACTGAGACTGAGACAGGAGTTAGCCAGGAAGCTGCGGGGCTGAGAGTTTTGGACACCGGCAGTGTGATCCCAGAGTCCAGGCACTTAACCATCAGGGCTCCTTCTGCTACGTGCATTTTGCAGAGGAGGAAACTGAGTCTCAGAGTGGTGCAGGGGAAGTCACTGGCCAAGGTCACGGAGCGCTTTTTGGCAGATCAGGAAGGTCAAGTCCGGTACGATTCTTCCGCTTGCAGCTTCGTGTTGCTCGGTGCGCAGGGCAACGTCAGAGCACCTCTGACTCCAGGGAGGTGGAAGCGGCTTCCGGGGTGAATGCGGTTGGATCGTGCGAGGCCGCCACCACTGCCAAGAAAAGAAACACACCACCGCACACCTTGCCATCCCTGGGTCACCACTTCCTTCTTCGTGTATGAAGAGCAGCAGACGGAACTCAGCAATGTTTTTCTAACACAAGAAGGATGACTTTCCGAAATCGTTTGAAGTGGGAAGACTGGGGCGAGCGGGCGGGGCGGGGCGGGGGGCGAGCGGGAGGGGCGGGGCGGGGGCACGGGCTTCTTGT (SEQ ID NO: 310).

[0425] MAX.chr10.0718 (DMR 456(69)):

[0426] TCAGTTGAATGTGCCGCACACCGAGGTTTGGAAACCACCCGTGAACTTCTATCCCAATCCACCCGGACATAAGGGAGCTGATGGCCCAGGCCCGCGCCTTCCAGCGGGGCAGGCCCAGCGGGGACCAGTTCGGCAGGCGCCTCCCCCAGGGTCTAGGATACCTGCTGGAAAGCTCGCAGCAGGGCCCGCTCCCGGTCCTGGGCAGGCCCAGGCGCGTCAAGACGCCGCGGCTACCTCTGCGGAGCGCGGCCGCTCGGCCACCAGCCCCTTCCCGCCCCCCGAGCTCCGCGGCACTGGAGTCCCCGGGCGGTGCCATGCGTCCCTGGAGCGCACGACACTTTCGGGCCCTGGGGACCCCGGGAGGCCGGGATCTGGCCTGGGGTGGAGGGCGAGGCCAGTCGGCCCCCACCTGCTCACCGGGCAGACTGTACCCGGGCAACGGCTCCCCGCAGCTCCGGCTTTTTGCCTGAAGCCCCCTGCAGGCAAATTCCGCGTCGCGCGGGCCCGCGGGCGCGCTGCAGTCTCCGAGCCCCAGGAAGCAGAGACCC (SEQ ID NO: 311).

[0427] MAX.chr11.9738 (DMR 458(71)):

[0428] GGACTTCACATAAGTGGGAAAATCGTTCTTTGAGAAGAAGGTATATGATTTGATATTGTTTTGCCTAGAGAAGAAAAAGAAACAAACCCATTAGAGTGTTGCAGAACCTGAATGGTTTTTCAAGAATTATGTTGATCAACTTTCTGTGTAGAGTAGCAAATAACAAGTGTCACCGATTTGAACAATAGTGTATTTGGGAAATAGAGAAAGGGCTGCTTCCTGTCCTTTGAGATCTTCACAGCAACCACAAACCCTATCTTGTCATCTGTGTTCCGGCATGCCCAGGCACATTTGACCAATTCTAAACGCTAAACGTTACTCCAGCACCCAAGTGTAACCCGTCACGAGGTGAGTCACAATGAATCCTAACCAGGACCCCAGTGGGAAATGTGCCTCCCCTTTAGATTTCTGATTTCACTTCAGTTTCCCGGTAGCACTTATGGTGTCATTGATCACCCCTCCCCACCCCCCATCTCTTTCACAATTTTGTCTTCCGTGGGTCACGTATGTTTTGGAGATGTCTGACTTTCCCAAGAGCTGGTGTTGAATTTCCACCCAGTGTTTCCAGGACGGCAGCCTGTGTGAAGTGCTAGGGAAAGCCTTTTCATGCCTTGAAAAATACACACAAGTATTTCTCTTCCTGAGCTTCAAGGAGACTCTGCATTCAAAAGACCACTCCCGGGCACTGCCTTCTACCAACTT (SEQ ID NO: 312).

[0429] MAX.chr13.8267 (DMR 460 (73)):

[0430]

[0431] MAX.chr15.0918 (DMR 462 (75)):

[0432] GAGCTCGTGGGGGACTCAGGCCCTTTCAGAGTCACCCGTGTGGCTCGGCCACTGCGCCAGGTCTTGGAACATCTAAGGCAGAAACAGGACCAACACCCGCAAGCCTCCAACAGCCCCTGGGGCTCCGTCCAGCCGTTGGGGTGGAGGGGTTGGGGGGAGGTGCAGGGGCGGGCACTGTGGGGGGTGGGGCGGGGCCGGTGGCCGCGACTCCACCCCGCGCCCCTAGTCGAGTAAACAAGCCACGGGCGGCGCCTGGGGGCCGCTCCTGCAAGCCGGGGCGCTGGGTTACATCACGGTTCCCTGGAGACTCCCGCCCCAGCGGCCGGGTCCCTGAGGCCCGCGCCCGCCCGCCGCCTGTGTCCGAGAAGCAGAGAGCTGGCAAGGGCCCGCCAGGGCGGGAAGGCTCCCACGTTTTCTCCGGAGGCCCCTGGGACTTTGTTGCAATTGGGTTCAGCCCGGGCATGGGCTGAACGTGGACGCGCGGGAACCGCGCCTCGGTTTCCCCATCTGTGAAACCTGGAGGCTGTATTAGGATTCTGTGCCTCCTATTAGGATTCAGCTGGGGGAAGGAGAGCGGCAGCCAGGGCCAGGGCCAGGGCCAGTCCCAGGCAGGCTGTGACTGGAGCCGGGCTTTCTACGTTAGGGTTTTGGTGGGTACCCGCTCAGCCACGTGCCAGA (SEQ ID NO: 314).

[0433] <00)) MAX.chr16.8889 (DMR 463 (76)):

[0434] GGGTACTCCCTCAGCCCTGCCTTTACACAGAATTTGTGGGGGATGAGGGGAGGGGGAAAGGGGGGAGGAAGGCAGTGAGTGCATCTGAATTTTTTTTTTTTTTTTACAAAAAGTGGCTTATTGCATTTTTCTGATTACTCTATCAGCACGTGCAGACCTTTTCCTATTCAGAGAAAGCCTGAAGATATAAAGAGGAAAGTGAAGAAAAACCACCGGAAATCCCATCCCCGCCCCAGCATCTGGCACTGTGTGGGCGATCACGAAATGAGCGCTTGTTTTTGAAGGCGTAGTATCTCCGTGAACATCCGGTTGAACAACCTTTCTGACTTTATTTTTCCCACGAAAGTTATTAATTAAAAAACAAAAAGCAAAACACCGAAAAAACAAAAAACCCAGCAAGTGTTTGAGCTCCCACCACGAGGGAGGCCTGACGTCACTGGATCCTCCCGGCAGCCGATGAGGCTGCATGGGACTTGCCCACGATGTGCTGTTACCGAGTGGCATAGCCAG (SEQ ID NO: 315).

[0435] MAX.chr19.3071 (DMR 466 (79)):

[0436]

[0437] MAX.chr19.2699 (DMR 467 (80)):

[0438] CTGTTTCAAAACTGTGCCATCTGGATGTTGCAGTATACCCATTTTGTCCTTCCCATACCTGTGCCCGGCCACCTGATGCAAGATGGGCACACAGCCACTGAGGAAGCGGAGTCTGCCGCCTGCCGGCTGCAGGGTGCCCTTAGGGGTGGCCTCGATCGCCGGTGGGGTCCGCATTTCTGGGGGACCCGGCGCCTCGACCCGGAGCGGGGATGGTGGCTCTCTTGCCATAACGGAGAACAGAAGCGGTAGGGTCAGCAAGAGCAGGAAAAGAAAAATAGGGGGAGGGAGGGGGCGCCGGAGAACCCAGGGGTCGCTCAGGCTCGGGCGCGAGGAGGCCCGGGGGTTCCCGCGGCTGGTGCCCGCTGAGGTGAGGGGAGGGGGCCCATGACGCCGCGGCGGCGCGGGCACTCCCTCTGCCCAACTCTCGGCTGAGCGCGGCTCCCGGCTCAGGCCCCTCTGCCGCCGCAGCCGCGGGCCCAGTAGACACAACCCAGCCGAGGAGCAGCAGCAGCAGCAGCGGCGCCCCGCGCTCCCTGGGGCCCTCCAGAAAGTTTTTTTATGGATATCAGCAATCTAATTCTACAATTTATATGGAGAGACAAAAGACTCAGAATAACCAACACAATATTGAAGGA (SEQ ID NO: 317).

[0439] MAX.chr19.0650 (DMR 468 (8)):

[0440]

[0441] MAX.chr2.2345 (DMR 469 (82)):

[0442] TGAAGTCATAAACATATTTAAAAACAGTGTGAGTCTGTGACATTTACAATCACAAAATTCATGTCAGAGAATAAATCCAGCATTACCTCCAATCACTGAATATGGAATACCCATTCATCTCCACCCACGTGTTGGGGGACACACACTTCAGAACGATGATATTCAGAAAATGCCAGGAGGAGTGCATGTCAGAGGTAACCACCCTCAGCAACCCAGCCTGTCAACAGTTGCAAATGCACGAAAAATGAGGGGAACCGGAAGACAGCAGCAGGAAGGAGATAATAGAGCAACTGAGAGCAGCCAGCCTTGACGTTTGTCAACCTCTGCCCGAAACAGCACATGTGGCTTTGCTGAGAGGCACAGGTGTGTGGGCTGAGCTCAGCAGATGAATGTCACATCCGGGAGGAGGCATGTGCATTTCTCAGCTTGAAATGCTTCCCCAACAAAACCAAATAAGGTTCCTGCAGATGACGTCAGGAGGCTTAGCTGCTACTGCCACAAAGGGACAATTTATTGAAGAGCTAAAAATGGTCGCCTCCGCAAGGCTGACAGGCAAATATTTGAGGGAACGCTCCCCTTGTTTTGAAGAGACATCTGCCAGCTCCCTGACTGGCACCTTCCTGCATTAGTCATCCTGCTGGGCCTTGCTAAAAACTC (SEQ ID NO: 319).

[0443] MAX.chr20.3366 (DMR 470 (83)):

[0444]

[0445] MAX.chr5.3868 (DMR 471 (84)):

[0446] GAGAAAGGGACACAAAAACCCATGGAAGCAATAGGGCGGGACTCAAAGCCCACGAGGAGGGCCGGCCCAGTTGTTCTCTGTCTCGTTTTCTAAGCGCTGCGGCAGGGCTGGTGGTGAATTCAGATAAACAGGCACAAAGGGCCAGTGGGGTCGCTAGCAAGATCTGGGACACGCTGAAAGTTAATAGGAATTGGCTGCCCTTTGCCGGCGCAACCCAACGTACAAAGATGATCTTTTCTGAGGCTCCACCGCCGCAGAGCCCTTCGCGCGGCCCACGGCACCAGCCGCCGCTGATTGGCCCGTGGCAGCCACCTGACCGAACGGACCAATAGGAGGCGTTCTCCCAGGAATGCGGCCCGCGTGTGGCCGGGAGCGGAAGCCCGACCTGAGTGCGGCAGGGCCCAGAGGCTGTGCTGGCCACGTGCACCCGGCTGGATTCCGCGGGCGCCGAACTGGGAGTGTGGAGCCGGGTCTCCCACTACCCTGTTCCGCCGGCCGAGGGAGTTGGGGAGGCCGCCTGTCCCAGACGCCCGGACCCTGTGTCCTTCTGATAAATTCCCCCTTTTTCTCTCGCTGGCTTCTGGGGCCATGTCCTTTTTACCCCCTCTGGTCCAAAGTAGTGTTTTAGGAGATTTGGAAGCAAGCAGAACCAAGTTGAAATTACTTGCTCCGCTGGGCGCGGTGGCTCACACCTGCAATCTCAGCACTTTGGGAGGTCTAGGCGGGCGGATTGCTTTA (SEQ ID NO: 321).

[0447] MAX.chr6.1793 (DMR 472 (85)):

[0448] [[ID=AAACATTTCTATTTGGCAAAATGGTAATGTTTAAGCTGTGCTAGGGGAGTACACTGCAAGAGGAAGGGGCCTCTGGACCCCATGATTTTTCTGCTTGTTCCTGCTGAAACCAAGATGTTAATCTGAGCGGGTATGCCAAACTTAGCCTGCCCTGCTTGCTTTTGGCCGCTGTCTTTTTGTGATTTTTTCCCCCTGTGAAGCTGAGGGCTGCTCCGCTGAACATTAGAACTTAACCCTCACCGGCGACCTTGTAGATAACGTCTATAAGTCACCATGGTAACGGTCGCTTCAGTTGTTTTTCAGGAACCTGGGGCAACTCCTGTCCAGTTTAAACCGGTTGAGACTACCGACCTTTCAACTGGACCCACGCAAGTGCCCAAGAGGTGGCCAAAAACTCCACCCTCAAATCATACTAACGGCGCCATTTTCTGTACATTATGTCCAATGCAATACCATGAACTTTTGCGCAGAACGAACCTGTTACTTCATTTTCCCTAACTGCCAATCACTTTTCCCCACACCTTAGACCACCCCACTTCCCTAACTCGTAATTATCCCTAAGACTTCTCTTCCGGG (SEQ ID NO: 322).

[0449] MAX.chr7.5822 (DMR 473 (86)):

[0450] GGCCACTCCTCAGGCCTTCAACCTGTCATCTGAGAGCCGCCAGCAGATGGCAGCAAAGGCCCAGCTCTGGCAGGTCTCTGAGGCCTCCCGGCTGGGCCGGGCCCTGGTACCTGGAGGAAGATTGCACGCTCTGGGACTGCGAGTTGCAAAGGTACCATGAGGAGCCCCGGGAGGTGAAAACACTTCCCGGGCTAACGTGGCGCCGAGAGGGACTGCGGACCCACTCTTGGCTTCCTCTTTAGAGGAGAGATGGAGCGGGGTCCGAAGCGCACAGGCTTCGAAGGAACTAGTGAGCCAGCCGAGGGCAGCGGGAGCCGCAGAAATCAGCTCGGAGAGAGTCGCGTGCAGGCTGCAGGTGTAGGGAGAGCCGGGGTCAGGCTCCGGTGCGCCGCGGGGGATGGCGGACCCTCCGGGGGCCGTGCTCCCCGCATTCCCACCACGGCGCAGGCATCGGGTGCCCTGCTCATCGCCCCTCCAGCCGGGGCCGGGCCTGCCTCTGGAAGCCCCACGGGTTCTCTGGGGCCTTTGGTTCCAGCGGGACCCAGGAGAGCAGCAGCTTTTGTCCGTGTGGGCCACGGTGACCTTCCCAGACACAAAATCAATGCCTAGGAATTGCGGAGTGACCCATCAGCACACGTAGAAAGGGTGGCATTTGTGACTTTTGTGCAGCTCGCT (SEQ ID NO: 323).

[0451] MAX.chr11.8952 (DMR 55 (SEQ ID NO: 170)):

[0452]

[0453] All publications and patent...

Claims

1. 1. A method for characterizing a biological sample, said method comprising: The characterization 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 urological cancer by treating the sample with a reagent that modifies DNA in a methylation-specific manner.

2. 10. The method of claim 1, wherein the methylation profile in the at least one DMR indicates that the subject has or is suspected of having urothelial carcinoma and / or renal cell carcinoma (RCC).

3. The at least one DMR is ACCN1, ADCYAP1, ADRA1A, AGAP1, ALX3, ANKRD35, ARRDC2, ASCL4, BARHL2, BCL11B, TMEM240, C1orf94, C1QL3, ECRG4, CRACDL, NICOL1, IRX2-DT, CACNA1B, CACNA1I, CACNG3, CASR, CBLN4, CCDC140, CDHR5, CDO1, CLDN11, CLEC14A, CMTM1, CNGA3, CNPY1, CNTNAP5, COL23A1, CRMP1, YBX3P1, CTNNAA, CYP4F2, DBX1, DCHS2, DCRG14, DLX6, DMR1, DMRT2, DNMT3A, DSCR6, EBF3, EMX1, EMX2OS, EVX1, EVX2, FBRSL1, FGF14, FLJ31485, FLJ32063, FMN2, FOXA2, FOXB1, FOXD3, FOXD4, FOXE1, FOXF1, FOXG1, FZD8, GAD1, GALR1, GATA4, GATA6, GBX2, GCM2, GHSR, GRASP, GRIK1, HAS1, HMX2, HOXA11, HOXA7, HOXA9, IGF2BP1, IRF4, IRX1, IRX4, ISL2, JPH4, KCNC2, KCNC4, KCNIP4, KCNQ2, KLF16, LBX2, LHFP14, LHX1, LHX2, LHX4, LHX5, LIMD2, LOC100131366, LOC154860, LOC285548, LOC4005, LRRRC4, MADCAM1, MAL, MAML3, MAX.chr1.6151, MAX.chr1.4676, MAX.chr1.9437, TTC34, MAX.chr1.1120, MAX.chr1.5982, MAX.chr1.5203, TLX1NB, MAX.chr10.0288, MAX.chr10.2081, MAX.chr10.7570, MAX.chr10.1197, NKX6-2, MAX.chr10.9377, MAX.chr10.5150, MAX.chr10.0872, FAM111A-DT, MAX.chr12.7397, MAX.chr12.3032, LINCOSG43, MAX.chr12.9110, KRT86, MAX.chr12.7375, MAX.chr13.1022, MAX.chr13.1687,LINC00554、SOX1-OT、MAX.chr13.2109、OBI1-AS1、LINC00391、MAX.chr14.3769、RAP2CP1、NKX2-8、MAX.chr14.1054、MAX.chr14.6663、MAX.chr14.2697、MAX.chr14.4566、RP11-262A16、MAX.chr17.2359、MAX.chr17.0937、MAX.chr17.8512、MAX.chr17.3547、DLGAP1、SKOR2、MAX.chr18.9881、RP11-714M23.2、RP11-154H12.2、CYP4F23P、CTD-2562J15.6、MAN1A2P1、MAX.chr19.1656、MAX.chr19.4113、MAX.chr19.0870、PANTR1、MAX.chr2.2307、MAX.chr2.6334、RHOQP3、RHOQP2、SLC4A10、SP9、MAX.chr2.6585、LINC01833、MAX.chr2.8149、MAX.chr2.6033、LINC01798、LINC01143、LINC00237、MAX.chr20.8579、MAX.chr20.3480、MAX.chr21.5638、MAX.chr21.7663、ZIC1、MAX.chr3.3606、PTPRG-AS1、NKX1-1、MAX.chr4.1655、SCRG1、LINC00682、MAX.chr4.4040、MAX.chr4.5903、MAX.chr5.2699、MAX.chr5.1156、LOC100996385、MAX.chr5.3053、MAX.chr5.5180、LINC02106、MAX.chr5.5268、MAX.chr5.4245、MAX.chr5.3918、OSTM1、MAX.chr6.0016、RP4-668J24.2、MAX.chr6.8227、MAX.chr6.3523、MAX.chr7.6951、MAX.chr7.0916、MAX.chr7.8965、MAX.chr7.5395、MAX.chr7.6952、MAX.chr7.6206、MAX.chr7.7860、PDE1C、RP11-53M11.5、ERICH1、MAX.chr8.6940、RP11-1102P16.1、MAX.chr8.6725、LINC01388、PRRT1B、MAX.chr9.5748、 MAX.chr9.9611、MAX.chr9.9692、MEI S2, MMP23A, MN1, MYO16, NCRANAA253, NEFM, NEURL, NK2-3, NK2-4, NK2- 6、NKX3-2、NKX6-1、NOTCH3、NPR3、NPT X2、NPY、NR2E1、NR2F1、NR2F6、NR5A1、 NRN1、NRXN1、OLIG2、OLIG3、ONECUT2、 OTP、OTUD7A、OTX1、OTX2、OTX2OS1、PAC SIN3、PAX1、PAX6、PAX7、PAX9、PCDH17 、PCDH8、PCDHGA1、PDX1、PENK、PHYHIP L、PITX1、PITX2、PNPLA1、POU3F3、POU 4F2、PPP1R3G、PRDM13、PRDM14、PRRX1、 PTF1A、PTPN5、PTPRN2、PTPRU、RARG、R ARRES2、RNF220、RXFP3、RYR2、SALL3、 SATB2、SCAND3、SDCCAG8、SEMA6A、SEP TIN9、SFTA3、SH3PXD2A、SHE、SHOX2、SI M2、SIX6、SKOR1、SLC2A14、SLC7A14、SOX11、SOX14、SOX17、SP8、SPAG6 、SSTR1、ST8SIA3、STAP2、SYCP2L、TBX T、TACC2、TAL1、TBX15、TBX4、TBX5、TFA P2A、TFAP2E、TJP2、TLX3、TMEM132D、TMEM200C、TP73、TRIM58、TWIST1、UNCX 、VAX1、VSTM2A、VSX1、VSX2、VWA5B1、Z AR1、ZIC2、ZIC5、ZMIZ1、ZNF521、ADRBK 1、AGRN、ALOX5、ARHGAP25、ARHGAP27、 ARHGAP30、BCL2L11、CD93、CDC42EP1、 EPS15L1、FER1L4、FOSL1、FOXP4、GPR1 32、GRK6、ITGB4、MAX.chr21.9298、LIN C01991、PRIC285、PRKAR1B、PTPN6、PT PRF、RAPGEFL1、RBM38、RHOF、SHH、SKI 、TBC1D10C、WNT6、ACSL5、ADAM32、ADA MTS19、ADCY2、AEBP2、AKAP7、ANKRD27、ANKRD43、ANKS1B、ARPM1、BCAN、BMP7、BTBD19、C20orf134、C20orf197、CACNA2D3、CAPN2、CBLN1、CDH22、CTNND2、CYYR1、DGKE、EPOR、EPS8L1、ESPN、FAM38A、FAM83G、FBLIM1、FBN2、FIBP、FOXL1、FXYD5、GP5、GRM6、HOXC4、HS3ST3B1、ICAM4、IL2RA、IRS1、ITPKA、ITPKB、KBTBD11、KCNH3、KCNS1、KCP、KCTD1、LHFPL2、LOC100289410、LOC100499227、LOC402778、LOC645277、LRFN4、LTBP4、LYL1、MACROD1、MAFB、MAST4、LINC01342、MAX.chr1.7620、MAX.chr1.5214、LINC01398、MAX.chr10.0718、GRAMD1B、MAX.chr11.9738、MAX.chr13.8267、MAX.chr15.0918、MAX.chr16.8889、SOX9-AS1、MAX.chr19.3071、MAX.chr19.2699、MAX.chr19.0650、MAX.chr2.2345、MAX.chr20.3366、MAX.chr5.3868、MAX.chr6.1793、MAX.chr7.5822、CTD-2168K21.1、FAM163B、MEST、MFNG、MYO15B、N4BP3、NAGS、NCKAP5、NCRNA00245、NETO1、NR2F2、NRG2、OPLAH、PARVG、PAX2、PDE4D、PEAR1、PLEKHG5、PPFIA4、PPP2R5C、PRDM2、PROX1、PRR14、RGS14、RIMS4、SCARF2、SEZ6L2、SFT2D3、SLC22A20、SNTG1、SOBP、SRCIN1、SYNGR3、TBCD、TMEM154、TNFRSF1B、TRANK1、TTBK1、UCN、USP2、VAC14、VWA1、VWC2、ZIC4、ZNF783、ZSCAN30、ABHD8、ADHFE1、AGAP3、AKNA、ALDOC、ATP6V1B1、B3GALT4、BIN1、VPS9D1、FAM218A、CLDN10、CMTM3、DUSP7、EPS8L2、FAIM2、FSCN1、3. The method of claim 1 or 2, wherein the gene is derived from a gene selected from GMDS, GRK7, HVCN1, IRAK3, KATNAL2, LOC100128239, LOC284454, TPBGL, LRRC8D, LRRFIP1, ST3GAL4, MAX.chr11.8952, RIMBP2, SHISA8, SMPD5, MGA, OXR1, PLEKHA2, RAI1, RASSF1, RCN3, SBNO2, SLC26A5, SPARC, TIGD3, TSPAN33, TSPAN9, WDR90, and ZBED3.

4. The at least one DMR is ACCN1, ADCYAP1, ADRA1A, AGAP1, ALX3, ANKRD35, ARRDC2, ASCL4, BARHL2, BCL11B, TMEM240, C1orf94, C1QL3, ECRG4, CRACDL, NICOL1, IRX2-DT, CACNA1B, CACNA1I, CACNG3, CASR, CBLN4, CCDC140, CDHR5, CDO1, CLDN11, CLEC14A, CMTM1, CNGA3, CNPY1, CNTNAP5, COL23A1, CRMP1, YBX3P1, CTNNNA2, CYP4F2, DBX1, DCHS2, DCRG14, DLX6, DMR1, DMRT2, DNMT3A, DSCR6, EBF3, EMX1, EMX2OS, EVX1, EVX2, FBRSL1, FGF14, FLJ31485, FLJ32063, FMN2, FOXA2, FOXB1, FOXD3, FOXD4, FOXE1, FOXF1, FOXGI, FZD8, GAD1, GALR1, GATA4, GATA6, GBX2, GCM2, GHSR, GRASP, GRIK1, HAS1, HMX2, HOXA11, HOXA7, HOXA9, IGF2BP1, IRF4, IRX1, IRX4, ISL2, JPH4, KCNC2, KCNC4, KCNIP4, KCNQ2, KLF16, LBX2, LHFP14, LHX1, LHX2, LHX4, LHX5, LIMD2, LOC100131366, LOC154860, LOC285548, LOC400550, LRRRC4, MADCAM1, MAL, MAML3, MAX.chr1.6151, MAX.chr1.4676, MAX.chr1.9437, TTC34, MAX.chr1.1120, MAX.chr1.5982, MAX.chr1.5203, TLX1NB, MAX.chr10.0288, MAX.chr10.2081, MAX.chr10.7570, MAX.chr10.1197, NKX6-2, MAX.chr10.9377, MAX.chr10.5150, MAX.chr10.0872, FAM111A-DT, MAX.chr12.7397, MAX.chr12.3032, LINCO0943, MAX.chr12.9110, KRT86, MAX.chr12.7375, MAX.chr13.1022, MAX.chr13.1687,LINC00554、SOX1-OT、MAX.chr13.2109、OBI1-AS1、LINC00391、MAX.chr14.3769、RAP2CP1、NKX2-8、MAX.chr14.1054、MAX.chr14.6663、MAX.chr14.2697、MAX.chr14.4566、RP11-262A16、MAX.chr17.2359、MAX.chr17.0937、MAX.chr17.8512、MAX.chr17.3547、DLGAP1、SKOR2、MAX.chr18.9881、MAX.chr18.55094898-55095207、RP11-154H12.2、CYP4F23P、CTD-2562J15.6、MAN1A2P1、MAX.chr19.1656、MAX.chr19.4113、MAX.chr19.0870、PANTR1、MAX.chr2.2307、MAX.chr2.6334、RHOQP3、RHOQP2、SLC4A10、SP9、MAX.chr2.6585、LINC01833、MAX.chr2.8149、MAX.chr2.6033、LINC01798、LINC01143、LINC00237、MAX.chr20.8579、MAX.chr20.3480、MAX.chr21.5638、MAX.chr21.7663、ZIC1、MAX.chr3.3606、PTPRG-AS1、NKX1-1、MAX.chr4.1655、SCRG1、LINC00682、MAX.chr4.4040、MAX.chr4.5903、MAX.chr5.2699、MAX.chr5.1156、LOC100996385、MAX.chr5.3053、MAX.chr5.5180、LINC02106、MAX.chr5.5268、MAX.chr5.4245、MAX.chr5.3918、OSTM1、MAX.chr6.0016、RP4-668J24.2、MAX.chr6.8227、MAX.chr6.3523、MAX.chr7.6951、MAX.chr7.0916、MAX.chr7.8965、MAX.chr7.5395、MAX.chr7.6952、MAX.chr7.6206、MAX.chr7.7860、PDE1C、RP11-53M11.5、ERICH1、MAX.chr8.6940、RP11-1102P16.1、MAX. chr8.6725, LINC01388, PRRT1B, MAX. chr9.5748, MAX. chr9.9611, MAX. chr9.9692, MEIS2, MMP23A, MNX1, MYO16, NCRNA00253, NEFM, NEURL, NKX2-3, NKX2-4, NKX2-6, NKX3-2, NKX6-1, NOTCH3, NPR3, NPTX2, NPY, NR2E1, NR2F1, NR2F6, NR5A1, NRN1, NRXN1, OLIG2, OLIG3, ONECUT2, OTP, OTUD7A, OTX1 , OTX2, OTX2OS1, PACSIN3, PAX1, PAX6, PAX7, PAX9, PCDH17, PCDH8, PCDHGA1, PDX1, PENK, PHYHIPL, PITX1, PITX2 , PNPLA1, POU3F3, POU4F2, PPP1R3G, PRDM13, PRDM14, PRRX1, PTF1A, PTPN5, PTPRN2, PTPRU, RARG, RARRES2, RNF2 20, RXFP3, RYR2, SALL3, SATB2, SCAND3, SDCCAG8, SEMA6A, SEPTIN9, SFTA3, SH3PXD2A, SHE, SHOX2, SIM2, SIX6, S KOR1, SLC2A14, SLC7A14, SOX1, SOX11, SOX14, SOX17, SP8, SPAG6, SSTR1, ST8SIA3, STAP2, SYCP2L, TBXT, TACC2, The method of claim 1 or 2, wherein the gene is derived from a gene selected from TAL1, TBX15, TBX4, TBX5, TFAP2A, TFAP2E, TJP2, TLX3, TMEM132D, TMEM200C, TP73, TRIM58, TWIST1, UNCX, VAX1, VSTM2A, VSX1, VSX2, VWA5B1, ZAR1, ZIC2, ZIC4, ZIC5, ZMIZ1, and ZNF521.

5. 3. The method of claim 1 or claim 2, wherein the at least one DMR is derived from a gene selected from ADRBK1, AGRN, ALOX5, ARHGAP25, ARHGAP27, ARHGAP30, BCL2L11, CD93, CDC42EP1, EPS15L1, FER1L4, FOSL1, FOXP4, GPR132, GRK6, ITGB4, MAX.chr21.9298, LINC01991, PRIC285, PRKAR1B, PTPN6, PTPRF, RAPGEFL1, RBM38, RHOF, SHH, SKI, TBC1D10C, and WNT6.

6. 3. The method of claim 1 or claim 2, wherein the at least one DMR is derived from a gene selected from ALOX5, ANKRD35, ARRDC2, CRACDL, YBX3P1, DLX6, FOXD4, FOXP4, GRASP, HOXA7, LBX2, LHX4, MAX.chr10.5150, FAM111A-DT, MAX.chr12.7397, RAP2CP1, MAX.chr8.6725, PACSIN3, PDX1, RAPGEFL1, RARG, RBM38, SDCCAG8, SEMA6A, SEPTIN, SH3PXD2A, SIM2, SP9, TAL1, TJP2.

7. 3. The method of claim 1 or claim 2, wherein the at least one DMR is derived from a gene selected from ALOX5, CRACDL, FOXP4, RBM38, SEPTIN9, SIM2, SP9, and TJP2.

8. The method of any one of claims 3 to 7, wherein the subject has or is suspected of having upper tract urothelial carcinoma (UTUC).

9. 9. The method of any one of claims 1-8, wherein the at least one DMR is associated with an area under the ROC curve (AUC) of 0.5 or greater, and the ROC curve distinguishes between subjects having or suspected of having UTCC and control DNA samples.

10. The method of any one of claims 1 to 8, wherein the at least one DMR has a higher methylation rate compared to a control DNA sample.

11. The method of any one of claims 1 to 8, wherein the at least one DMR has a high rate of hypermethylation compared to a control DNA sample.

12. The method of any one of claims 9 to 11, wherein the control DNA sample is derived from a subject not affected by urothelial carcinoma.

13. 13. The method of claim 12, wherein the control DNA sample is selected from a tissue sample, a blood sample, a plasma sample, a serum sample, a whole blood sample, a buffy coat sample, a secretion sample, an organ secretion sample, a cerebrospinal fluid (CSF) sample, a saliva sample, a urine sample, and a stool sample.

14. The at least one DMR is ACSL5, ADAM32, ADAMTS19, ADCY2, AEBBP2, AGRN, AKAP7, ANKRD27, ANKRD43, ANKS1B, ARPM1, BCAN, BMP7, BTBD19, C1QL3, C20orf134, C20orf197, CACNA2D3, CAPN2, CBLN1, CDH22, COL23A1, CTNND2, CYYR1, DGKE, EPOR, EPS8L1, ESPN, FAM38A, FAM83G, FB LIM1, FBN2, FIBP, FOSL1, FOXL1, FXYD5, GP5, GRM6, HOXC4, HS3ST3B1, ICAM4, IL2RA, IRS1, ITPKA, ITPKB, KBTBD11, KCNH, KCN, KCP, KCTD1, LHFP L2, LOC100289410, LOC100499227, LOC402778, LOC645277, LRFN4, LTBP4, LYL1, MACROD1, MAFB, MAST4, LINCO1342, MAX.chr1.7620, MAX.chr1.5214, LINCO1398, MAX.chr10.0718, GRAMD1B, MAX.chr11.9738, KRT86, MAX.chr13.8267, RAP2CP1, MAX.chr15.0918, MAX.chr16.8889, SOX9-AS1, DL GAP1, MAX.chr19.3071, MAX.chr19.2699, MAX.chr19.065, MAX.chr2.2345, MAX.chr20.3366, MAX.chr5.3868, MAX.chr6.1793, MAX.chr7.5822, CTD- N2168K21.1, FAM163B, MEST, MFNG, MYO15B, N4BP3, NAGS, NCKAP5, ncRNA00245, NETO1, NR2F2, NRG2, ONECUT2, OP LAH, PARVG, PAX2, PDE4D, PEAR1, PENK, PLEKHG5, PPFIA4, PPP2R5C, PRDM2, PROX1, PRR14, PTPRF, RBM38, RGS14, RIMS4, SCARF2, SEZ6L2, SFT2D3, SHH, SLC22A20, SNTG1, SOBP, SRCIN1, SYNGR3, TACC2, TBCD, TMEM154, TNFRSF1B, TRAN K1, TRIM58, TT BK1,UCN, USP2, VAC14, VWA1, VWC2, ZIC4, ZNF783, ZSCAN30, ABHD8, ADHFE1, AGA P3, AKNA, ALDOC, ATP6V1B1, B3GALT4, BIN1, VPS9D1, FAM218A, CLDN10, CMTM 3, DUSP7, EMX1, EPS8L2, FAIM2, FSCN1, GMDS, GRK7, HVCN1, IRAK3, KATNAL2 , LHX1, LOC100128239, LOC284454, TPBGL, LRRC8D, LRRFIP1, ST3GAL4, MAX. The method of claim 1 or 2, wherein the gene is derived from a gene selected from chr11.8952, RIMBP2, SHISA8, SMPD5, MGA, OXR1, PLEKHA2, RAI1, RASSF1, RCN3, SBNO2, SKI, SLC26A5, SPARC, TIGD3, TSPAN33, TSPAN9, WDR90, ZBED3, and ZMIZ1.

15. The at least one DMR is ACSL5, ADAM32, ADAMTS19, ADCY2, AEBP2, AGRN, AKAP7, ANKRD27, ANKRD43, ANKS1B, ARPM1, BCAN, BMP7, BTBD19, C1QL3, C20orf134, C20orf197, CACNA2D3, CAPN2, CBLN1, CDH22, COL23A1, CTNND2, CYYR1, DGKE, EPOR, EPS8L1, ESPN, FAM38A, FAM83G, FB LIM1, FBN2, FIBP, FOSL1, FOXL1, FXYD5, GP5, GRM6, HOXC4, HS3ST3B1, ICAM4, IL2RA, IRS1, ITPKA, ITPKB, KBTBD11, KCNH3, KCN S1, KCP, KCTD1, LHFP L2, LOC100289410, LOC100499227, LOC402778, LOC645277, LR FN4, LTBP4, LYL1, MACROD1, MAFB, MAST4, LIN C01342, MAX.chr1.7620, MAX.chr1.5214, LIN C01398, MAX.chr10.0718, GRAMD1B, MAX.chr11.9738, KRT86, MAX.chr13.8267, RAP2 CP1, MAX.chr15.0918, MAX.chr16.8889, SOX9-AS1, DLGA P1, MAX.chr19.3071, MAX.chr19.2699, MAX.chr19.0650, MAX.chr2.2345, MAX.chr20.3366, MAX.chr5.3868, MAX.chr6.1793, MAX.chr7.5822, CTD-2168K21.1, FAM163B, MEST, MFNG, MYO15B, N4BP3, NAGS, NCKAP5, ncRNA00245, NETO1, NR2F2, NRG2, ONECUT2, OPLAH, PARVG, PAX2, PDE4D, PEAR1, PENK, PLEKHG5, PPFIA4, PPP2R5C, PRDM2, PROX1, PRR14, PTPRF, RBM38, RGS14, RIMS4, SCARF2, SEZ6L2, SFT2D3, SHH, SLCZ2A20, SNTG1, SOBP, SRCIN1, SYNGR3, TACC2, TBCD, TMEM154, TNFRSF1B, TRAN K1, TRIM58, TT BK1,The method of claim 1 or claim 2, wherein the gene is derived from a gene selected from UCN, USP2, VAC14, VWA1, VWC2, ZIC4, ZNF783, and ZSCAN30.

16. The at least one DMR is selected from the group consisting of ABHD8, ADHFE1, AGAP3, AKNA, ALDOC, ATP6V1B1, B3GALT4, BIN1, VPS9D1, FAM218A, CLDN10, CMTM3, DUSP7, EMX1, EPS8L2, FAIM2, FSCN1, GMDS, GRK7, HVCN1, IRAK3, KATNAL2, LHX1, LOC100128239, LOC284454, TPBGL, LRRC8D, LRRFIP1, ST3GAL4, MAX. The method of claim 1 or claim 2, wherein the gene is derived from a gene selected from chr11.8952, RIMBP2, ShiSA8, SMPD5, MGA, OXR1, PLEKHA2, RAI1, RASSF1, RCN3, SBNO2, SKI, SLC26A5, SPARC, TIGD3, TSPAN33, TSPAN9, WDR90, ZBED3, and ZMIZ1.

17. The at least one DMR is selected from the group consisting of ACSL5, ADAMTS19, AEFP2, ANKRD27, ANNKS1B.r1, ARPM1, BCAN, C1QL3, CBLN1, CTNND2, ESPN, FOSL1, GP5, HOXC4, HS3ST3B1, IRS1, ITPKA, ITPKB, LOC100289410, LRFN4, LTBP4, LYL1, MAST4, MAX.chr1.5214, GRAMD1B, RAP2CP1, MAX.chr15.0918, MAX.chr16.8889, MAX.chr19.3071, MAX.chr2.2345, MAX.chr3.2214, MAX.chr4.2214, MAX.chr5.2214, MAX.chr6.2214, MAX.chr7.2214, MAX.chr8.2214, MAX.chr9.2214, MAX.chr10.2214, MAX.chr11.2214, MAX.chr12.2214, MAX.chr13.2214, MAX.chr14.2214, MAX.chr15.0918, MAX.chr16.8889, MAX.chr19.3071, MAX.chr2.2345, MAX.chr16.2214, MAX.chr18.2214, MAX.chr19.3071, MAX.chr2 ...

3. The method of claim 1 or claim 2, wherein the gene is derived from a gene selected from chr20.3366, MFNG, MYO15B, NAGS, NCRNA00245, NRG2, OPLAH, PAX2, PDE4D, PLEKHG5, PPFIIA4, PPP2R5C, PRDM2, RGS14, SFT2D3, SHH, SLC22A20, TMEM154, TRANK1, TRIM58, USP2, VWC2, and ZNF783.

18. The at least one DMR is selected from the group consisting of ACSL5, BCAN, C1QL3, CBLN1, CTNND2, ESPN, FOSL1, GP5, HS3ST3B1, IRS1, ITPKA, ITPKB, LOC100289410, LTBP4, LYL1, MAST4, GRAMD1B, MAX. chr15.0918, MAX.

3. The method of claim 1 or claim 2, wherein the gene is derived from a gene selected from chr16.8889, MFNG, MYO15B, NAGS, NCRNA00245, OPLAH, PAX2, PDE4D, PPFIA4, PPP2R5C, PRDM2, PRDM2, SFT2D3, SFT2D3, TMEM154, TRIM58, USP2, and VWC2.

19. 3. The method of claim 1 or claim 2, wherein the at least one DMR is derived from a gene selected from C1QL3, OXR1, ANKS1B, CMTM3, LINC01398, FBLIM1, VPS9D1, LRRC8D, HVCN1, SFT2D3, FAM83G, LOC100128239, LHX1, GRAMD1B, TSPAN33, PDE4D, LOC100289410, TTBK1, PRDM2, CLDN10, MAST4, MACROD1, and KCNH3.

20. 3. The method of claim 1 or claim 2, wherein the at least one DMR is derived from a gene selected from MAST4, KCNH3, GRAMD1B, and LOC100289410.

21. 3. The method of claim 1 or claim 2, wherein the at least one DMR is derived from a gene selected from MAST4, KCNH3, GRAMD1B, and PDE4D.

22. The method of any one of claims 14 to 21, wherein the subject has or is suspected of having RCC.

23. The at least one DMR is selected from the group consisting of ACSL5, ADAMTS19, ANNKS1B, BCAN, C1QL3, CBLN1, CTNND2, ESPN, GP5, HOXC4, HS3ST3B1, IRS1, ITPKB, LOC100289410, LRFN4, LTBP4, LYL1, MAST4, MAX. chr1.5214, GRAMD1B, MAX. chr15.0918, MAX. derived from a gene selected from chr2.2345, MYO15B, NCRNA00245, PAX2, PDE4D, PLEKHG5, PPFIA4, PPP2R5C, PRDM2, RGS14, SHH, SLC22A20, TMEM154, TRIM58, and VWC2; 23. The method of claim 22, wherein the subject has or is suspected of having papillary renal cell carcinoma (PRCC) or clear cell renal cell carcinoma (ccRCC).

24. the at least one DMR is derived from a gene selected from ACSL5, C1QL3, ESPN, IRS1, ITPKB, LOC100289410, LYL1, MAST4, GRAMD1B, MAX.chr2.2345, PAX2, PDE4D, and TMEM154; 24. The method of claim 23, wherein the subject has or is suspected of having PRCC.

25. the at least one DMR is derived from a gene selected from ACSL5, CTNND2, ESPN, HS3ST3B1, ITPKB, LOC100289410, LTBP4, LYL1, MAST4, GRAMD1B, MAX.chr2.2345, MYO15B, PAX2, PDE4D, PLEKHG5, PPFIA4, PPP2R5C, PRDM2, TMEM154, and VWC2; 24. The method of claim 23, wherein the subject has or is suspected of having ccRCC.

26. the at least one DMR is derived from a gene selected from AESBP2, ANKRD27, ARPM1, FOSL1, ITPKA, RAP2CP1, MAX. chr16.8889, MAX. chr19.3071, MAX. chr20.3366, MFNG, NAGS, NRG2, OPLAH, PAX2, PRDM2, SFT2D3, TRANK1, USP2, and ZNF783; 23. The method of claim 22, wherein the subject has or is suspected of having chromophobe renal cell carcinoma (chRCC).

27. the at least one DMR is derived from a gene selected from ACSL5, C1QL3, ESPN, GPS, LRFN4, LTBP4, LYL1, MAST4, GRAMD1B, MAX.chr2.2345, PAX2, PDE4D, PRDM2, RGS14, TMEM154, VWC2, FOSL1, ITPKA, MAX.chr16.8889, MFNG, NAGS, and OPLAH; 27. The method of claim 26, wherein the subject has or is suspected of having chRCC.

28. 28. The method of any one of claims 14-27, wherein the at least one DMR is associated with an area under the ROC curve (AUC) of 0.5 or greater, and the ROC curve distinguishes between subjects having or suspected of having RCC and control DNA samples.

29. 28. The method of any one of claims 14 to 27, wherein the at least one DMR is highly methylated compared to a control DNA sample.

30. 28. The method of any one of claims 14 to 27, wherein the at least one DMR has a high rate of hypermethylation compared to a control DNA sample.

31. The method of any one of claims 28 to 30, wherein the control DNA sample is derived from a subject not affected with RCC.

32. 32. The method of claim 31 , wherein the control DNA sample is selected from a tissue sample, a blood sample, a plasma sample, a serum sample, a whole blood sample, a buffy coat sample, a secretion sample, an organ secretion sample, a cerebrospinal fluid (CSF) sample, a saliva sample, a urine sample, and a stool sample.

33. 31. The method of any one of claims 28 to 30, wherein the control DNA sample comprises a non-cancerous portion of the kidney of the subject.

34. 1. A method for characterizing a biological sample, said method comprising: The characterization 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 renal oncocytoma by treating the sample with a reagent that modifies DNA in a methylation-specific manner.

35. The at least one DMR is selected from the group consisting of ACSL5, ADAMTS19, ANKS1B, BCAN, C1QL3, CBLN1, CTNND2, ESPN, GP5, HOXC4, HS3ST3B1, IRS1, ITPKB, LOC100289410, LRFN4, LTBP4, LYL1, MAST4, MAX. chr1.5214, GRAMD1B, MAX. chr15.0918, MAX. chr2.2345, MYO15B, NCRNA00245, PAX2, PDE4D, PLEKHG5, PPFIA4, PPP2R5C, PRDM2, RGS14, S HH, SLC22A20, TMEM154, TRIM58, VWC2, AEBP2, ANKRD27, ARPM1, FOSL1, ITPKA, RAP2CP1, MAX. chr16.8889, MAX. chr19.3071, MAX.

35. The method of claim 34, wherein the gene is derived from a gene selected from chr20.3366, MFNG, NAGS, NRG2, OPLAH, PAX2, PRDM2, SFT2D3, TRANK1, USP2, and ZNF783.

36. 36. The method of claim 35, wherein the at least one DMR is from a gene selected from ACSL5, LTBP4, MAX.chr2.2345, PAX2, RGS14, TMEM154, FOSL1, MAX.chr16.8889, MFNG, NAGS, OPLAH, and PRDM2.

37. 37. The method of any one of claims 34-36, wherein the at least one DMR is associated with an area under the ROC curve (AUC) of 0.5 or greater, and the ROC curve distinguishes between subjects having or suspected of having oncocytoma and control DNA samples.

38. 38. The method of any one of claims 34 to 37, wherein the at least one DMR has an increased methylation rate compared to a control DNA sample.

39. 38. The method of any one of claims 34 to 37, wherein the at least one DMR has a high rate of hypermethylation compared to a control DNA sample.

40. The method of any one of claims 37 to 39, wherein the control DNA sample is derived from a subject not affected with oncocytoma.

41. 41. The method of claim 40, wherein the control DNA sample is selected from a tissue sample, a blood sample, a plasma sample, a serum sample, a whole blood sample, a buffy coat sample, a secretion sample, an organ secretion sample, a cerebrospinal fluid (CSF) sample, a saliva sample, a urine sample, and a stool sample.

42. 42. The method of any one of claims 1 to 41, wherein the biological sample is selected from a tissue sample, a blood sample, a plasma sample, a serum sample, a whole blood sample, a buffy coat sample, a secretion sample, an organ secretion sample, a cerebrospinal fluid (CSF) sample, a saliva sample, a urine sample, and a stool sample.

43. 43. The method of claim 42, wherein the tissue sample is a urinary tissue sample or a urothelial tissue sample.

44. 44. The method of claim 43, wherein the urinary or urothelial tissue sample comprises one or more of kidney cells or tissue, bladder cells or tissue, renal pelvis cells or tissue, and urethral cells or tissue.

45. The method of any one of claims 1 to 44, wherein the subject is a human.

46. 46. ​​The method of any one of claims 1 to 45, wherein the biological sample is obtained from the subject, and the method further comprises extracting the DNA sample from the biological sample.

47. The method of any one of claims 1 to 46, wherein the biological sample is collected with a collection device.

48. 48. The method of any one of claims 1 to 47, wherein the reagent that modifies DNA in a methylation-specific manner is a borane reducing agent.

49. 49. The method of any one of claims 1 to 48, wherein 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.

50. 50. The method of any one of claims 1 to 49, wherein determining the methylation profile of at least one DMR comprises amplifying at least a portion of the DMR using a set of primers.

51. 51. The method of any one of claims 1 to 50, 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.

52. 51. The method of any one of claims 1 to 50, wherein determining the methylation profile of at least one DMR comprises determining the presence or absence of methylation at one or more CpG sites.

53. 53. The method of claim 52, wherein the one or more CpG sites are present in a coding region, a non-coding region, and / or a regulatory region of the gene.

54. 54. The method of any one of claims 1 to 53, wherein determining the methylation profile of at least one DMR comprises determining a frequency of methylation.

55. 55. The method of any one of claims 1 to 54, wherein determining the methylation profile of at least one DMR comprises determining a methylation pattern.

56. 3. The method of claim 1 or claim 2, wherein the at least one DMR is derived from a gene selected from CRACDL, ANKRD35, DLX6, MAX.chr8.6725, SP9, SOX1-OT, Septin9, LBX2, SIM2, and RAP2CP1.

57. 57. The method of claim 56, wherein the subject has or is suspected of having upper tract urothelial carcinoma (UTUC).

Images