Granted Patent B2

US 12,584,162 · App. 17/740,212 · Granted Mar 24, 2026

Inventors: Chin-Jen Ku (San Francisco, CA); Francois Collin (San Francisco, CA); Patrick Arensdorf (Palo Alto, CA); Samuel Levy (San Diego, CA)

Assignee: ClearNote Health, Inc.

C12Q1/6827C12Q1/6809G16B20/20G16B40/10G16H50/30C12Q2537/164C12Q2600/154C12Q2600/166C12Q2600/172

Abstract

Claims (475)

1 . A method for probabilistically assigning a tissue of origin to cell-free DNA (cfDNA) in a fluid sample obtained from a human subject, comprising:

(a) analyzing the cfDNA in the fluid sample by assessing hydroxymethylation levels within the cfDNA at each of a plurality of hydroxymethylation biomarker loci to generate a sample hydroxymethylation profile, wherein each biomarker locus is contained within a differentially hydroxymethylated genomic region associated with a tissue-specific gene that is both differentially represented and differentially expressed with respect to tissue of origin, and further wherein the biomarker loci analyzed represent at least 5 tissue types and at least 5 genes per tissue;

(b) comparing each assessed hydroxymethylation level in the sample hydroxymethylation profile with a corresponding reference hydroxymethylation level at each biomarker locus analyzed, the reference hydroxymethylation levels being contained within a plurality of different tissue-specific reference hydroxymethylation profiles in a reference data set, thereby generating a hydroxymethylation difference data set comprising differences identified between the generated sample hydroxymethylation profile and the reference hydroxymethylation profiles at each biomarker locus;

(c) using a computer system, carrying out a correlation analysis using one or more algorithms that determine a statistical correlation between the assessed hydroxymethylation levels and the reference hydroxymethylation levels at each biomarker locus; and

(d) using the statistical correlation, providing a probabilistic assignment of at least one tissue of origin to the cfDNA.

2 . The method of claim 1 , wherein at least one of the hydroxymethylation biomarker loci is contained within a gene body or a component thereof.

3 . The method of claim 2 , wherein at least one hydroxymethylation biomarker locus is contained within an intron or exon.

4 . The method of claim 1 , wherein at least one of the hydroxymethylation biomarker loci is contained within a genomic annotation feature outside of the gene body.

5 . The method of claim 4 , wherein at least one hydroxymethylation biomarker locus is contained within a promoter, an enhancer, a transcription initiation site, a transcription stop site, a DNA binding site, or a combination thereof.

6 . The method of claim 5 , wherein at least one hydroxymethylation biomarker locus is contained within a DNA binding site comprising a silenced region or a transcription repressor binding site.

7 . The method of claim 1 , wherein the cfDNA comprises a plurality of cfDNA fragments, and the method further includes determining at least one of cfDNA length and cfDNA fragment distribution.

8 . The method of claim 1 , wherein the plurality of reference hydroxymethylation profiles in the reference data set comprise a hydroxymethylation profile of reference loci associated with at least five genes originating from each of five human tissue types comprising: adipose; adrenal gland; bladder; bone marrow; brain; breast; colon; cerebral cortex; cervical; uterine; digestive; endometrial; epididymal; esophageal; Fallopian tube; gall bladder; gastrointestinal; heart muscle; hypothalamus; kidney; liver; lung; lymph nodes; ovary; pancreas; parathyroid gland; placenta; prostate; salivary; seminal vesicle; skeletal muscle; smooth muscle; skin; spleen; stomach; testis; thyroid gland; or tonsil.

9 . The method of claim 8 , wherein the plurality of reference hydroxymethylation profiles in the reference data set comprise a hydroxymethylation profile of reference loci associated with at least five genes originating from each of five human tissue types comprising: bladder; bone marrow; brain; breast; colon; gastrointestinal; heart muscle; hypothalamus; kidney; liver; lung; lymph nodes; ovary; pancreas; placenta; prostate; skin; smooth muscle; or testis.

10 . The method of claim 1 , wherein each hydroxymethylation biomarker locus is contained within a differentially represented, differentially expressed gene comprising AARD, ADARB1, AKR1B10, CRYM-AS1, EPHA3, GTSF1, KCNMB1, MAP1B, NT5DC3, P2RX1, PCP4, PGM5, PLCD4, PTGFR, RBFOX3, SCARA3, SLIT3, SNX29P1, ST8SIA1, TBX4, TXNRD1, VCL, WFDC3, ABCA13, AZU1, CA1, CEACAM8, CLEC6A, DAZL, DRGX, DYTN, ELANE, FCAR, GFI1, GYPA, HK3, IL18RAP, LINC00333, LINC00550, LINC00558, LIPN, LOC100129620, LOC442028, LPO, MEFV, MMP8, MMP9, MPO, MS4A3, MYB, MYO1F, NCOR1P1, NME8, OR8U8, OSCAR, PARPBP, PAX3, PDCL2, PRDM13, PROK2, RGS18, RGS21, RRM2, RXFP2, SERPINB10, SLC22A16, SPATA16, SPI1, SPTA1, TARM1, TMPRSS15, TRIM58, VSTM1, XKR3, ASPHD1, BRSK1, CCDC177, CNTN2, HAPLN2, KCNJ10, KIF1A, LGI3, NCAN, NR2E1, RHBDL3, TMEM151A, TMEM235, TMEM59L, ZNF488, FGL2, SCNN1B, ADPRHL1, ASB18, ATP1A3, CDH13, CORO6, FSD2, GALNT16, GJA3, MYOM2, PCDHGA1, PCDHGA10, PCDHGA11, PCDHGA12, PCDHGA2, PCDHGA3, PCDHGA4, PCDHGA5, PCDHGA6, PCDHGA7, PCDHGA8, PCDHGA9, PCDHGB1, PCDHGB2, PCDHGB3, PCDHGB5, PCDHGB6, PCDHGB7, PXDNL, RPL3L, SGCG, TNNT1, ASTN1, DGK1, BBOX1, BCRP3, CA12, COL4A3, CXCL14, CYS1, EVC, FIGNL2, GALNT14, GLIS2, HAVCR1, LOC100130238, PAQR5, PAX2, PAX8, PLA2G15, SLC22A2, SLC9A3, SULT1C2, TSPAN33, ABCC2, ABCG5, ABCG8, AHSG, AKR1C4, AMDHD1, APOH, ASGR1, ASGR2, C3P1, C8A, C8B, C9, CASA, CFHR4, CPN2, CREB3L3, CYP2B6, CYP2C9, CYP2E1, CYP3A4, DHODH, F12, F2, F7, GC, HAL, HPD, HPX, INHBC, ITIH1, ITIH2, ITIH3, KNG1, LBP, PGLYRP2, PLG, PROC, PRODH2, SERPINA6, SERPINC1, SLC13A5, SLC22A1, SLC25A47, SLC27A5, SULT2A1, TFR2, TMPRSS6, UROC1, ANXA3, BMP5, CYP4Z2P, DRAM1, FMO2, GNA15, IDO1, KCNS3, LIMCH1, MBIP, PAPSS2, PCDH17, RSPH4A, RTKN2, TRPC6, ACAP1, AKNA, ARHGAP9, BCL11B, BIRC3, CARD11, CD180, CD37, CD3E, CD3G, CD40, CETP, CITA, CLEC2D, CNR2, CXCR5, DOCK10, ETS1, GPR132, GPR18, ICAM2, ICOS, ITGB7, ITK, KIAA1551, KLHL6, LCK, LINC00426, LY86, MDS2, MEOX2, MX2, NAPSB, PATL2, PCED1B-AS1, PIK3CD, PLVAP, POU2F2, SCIMP, SCML4, SLFN12L, SMAP2, SP110, SPIB, TLR10, TMC8, TMEM156, TNFAIP8, TNFRSF9, TNFSF11, TRAF1, TRIM22, UCP2, ZC3H12D, ABCA10, ACSS3, ADAMTS5, AQP11, C7, CDH3, CDON, CLDN11, COL14A1, COLEC11, ESR2, FAM198B, FZD3, GALNT10, GLI2, GSTM5, HS3ST1, LEMD1-AS1, LHX9, LRRC17, MCHR1, MRC2, NTF3, OMD, PDGFRA, PGR, PKNOX2, PTCH2, RWDD4, SCD5, SERPINE2, SIMC1, SLC25A17, SNCAIP, SULF2, TENM4, TSPAN5, TTC8, UBXN8, ALDH1L2, ANKEF1, ASNS, B3GALNT2, BCAT1, CASP9, CCDC110, CELA2B, CELABB, CFTR, CHMP4C, CLDN1, CNIH3, COCH, CUZD1, DEFB1, EGF, EIF4EBP1, ERP27, FAM24B-CUZD1, FBXW12, GUCA1C, KCTD16, KIAA1324, LINC00339, LNX2, MKNK1, NAA16, NPHS1, PAIP2B, PM20D1, PRSS3, SCGN, SEL1L, SERPINI2, SH3YL1, SLC33A1, SLC4A4, TC2N, TDH, TMEM51-AS1, TRHDE, UMOD, ADAM12, ATG9B, ATP6V1C2, BCAR4, BMP1, BPGM, CSF3R, CYP11A1, CYP19A1, DACT2, DEPDC1B, DLX5, EBI3, GCM1, GPR78, GSTA3, IGF2BP3, IGSF5, ISM2, KISS1, KRT23, LIN28B, MMP11, PGF, PSG11, PSG2, PSG3, PSG6, PSG7, PSG8, SPTLC3, TPRXL, ZFAT, ZNF554, ABCC4, ACPP, ALOX15B, ANO7, AP1B1P1, ARG2, BEND4, C6orf132, C6orf52, CANT1, CASZ1, CBFA2T2, CHRM1, CHRNA2, COL26A1, EVX1, EYA2, FAM135A, HMGN2P46, KLK2, KLKP1, MME, MPPED2, MUC12, NANS, NCAPD3, NEFH, NIPAL3, OACYLP, OR51E2, PAK1IP1, PDE9A, PI15, PMEPA1, POTEF, RDH11, SCNN1G, SIM2, SLC14A1, SLC22A3, SLC2A12, SLC30A4, SLC35F2, SLC37A1, SLC39A6, SPDEF, STEAP2, THSD4, TMEM79, TPM3P9, TXNDC16, URB1, VIPR1, ZNF350, ZNF532, ZNF613, ZNF649, ZNF761, ZNF827, GADL1, GIPC3, PTGES3L, WSCD2, CCDC27, DMRT1, DNAJC5G, FBXO24, IGLL1, MOV10L1, SEPT14, THEG, or TTC16.

11 . The method of claim 1 , wherein the reference hydroxymethylation profile comprises at least one of:

hydroxymethylation density within each hydroxymethylation biomarker locus;

total 5-hydroxymethylcytosine residues within each hydroxymethylation biomarker locus;

location of the 5-hydroxymethylcytosine residues within each hydroxymethylation biomarker locus;

identification of a hydroxymethylation biomarker locus as hemi-hydroxymethylated or fully hydroxymethylated; and

relative positions of 5-hydroxymethylcytosine residues within each hydroxymethylation biomarker locus.

12 . The method of claim 1 , wherein the one or more algorithms comprises a tree-based method.

13 . The method of claim 12 , wherein the tree-based method comprises a regression model.

14 . The method of claim 1 , wherein the tissue-specific gene is a tissue-enriched gene.

15 . The method of claim 1 , wherein the reference data set comprises five or more data sets selected from the following:

Set 3A:

ChromosomeName_GeneName

chr16_SNX29P1_

chr10_CUTC_

chr12_NT5DC3_

chr17_RBFOX3_

chr05_IL17B_

chr12_GTSF1_

chr01_FMO1_

chr10_NEBL_

chr07_CLEC2L_

chr17_TBX4_

chr10_TACR2_

chr09_TMOD1_

chr20_C20orf166_

chr16_LOC732275_

chr07_TPST1_

chr17_P2RX1_

chr01_HIST2H2BF_

chr02_C2orf40_

Set 3B:

ChromosomeName_GeneName

chr10_KCNK18_

chr12_LRP6_

chr19_TARM1_

chr12_NUAK1_

chr15_TJP1_

chr05_HK3_

chr01_NDUFS5_

chr19_CEACAM8_

chr12_BCL2L14_

chr02_AGAP1_

chr06_SLC22A16_

chr04_FAT1_

chr05_PPAP2A_

chr17_CRK_

chr19_LYPD4_

chr10_BMPR1A_

chr14_APOPT1_

chr01_S100A9_

chr19_VSTM1_

chr02_FAM168B_

chr16_MEFV_

chr10_VDAC2_

chr13_FARP1_

chr19_CEACAM4_

chr06_SASH1_

chr03_FLNB_

chr16_ADCY9_

chr03_WWTR1_

chr02_LOC339803_

chr12_SP1_

chr12_LRIG3_

chr13_RNF113B_

chr17_LPO_

chr15_CYFIP1_

Set 3C:

ChromosomeName_GeneName

chr10_ZNF503.AS2_

chr05_LRRTM2_

chr02_CCDC140_

chr05_FLJ35946_

chr01_DMRTA2_

chr12_TUBA1A_

chr01_HAPLN2_

chr22_LOC150381_

chr03_ZIC1_

chr01_CAMK2N1_

chr03_EIF4A2_

chr10_VAX1_

chr08_HEY1_

chr11_HSPA8_

chr03_EGOT_

chr17_DDX5_

chr17_TOB1_

chr13_AMER2_

Set 3D:

ChromosomeName_GeneName

chr12_KCNA1_

chr02_NPPC_

chr11_ALX4_

chr11_GAL_

chr19_SBK2_

chr18_RBBP8_

chr21_LINC00323_

chr20_TSHZ2_

chr09_LHX6_

chr02_WNT6_

chr01_LRRC71_

chr11_LOC650368_

chr17_PIK3R6_

chr18_GRP_

chr17_RNASEK_

chr05_FOXI1_

chr02_TBR1_

chr01_LOC339505_

chr08_LZTS1.AS1_

Set 3E:

ChromosomeName_GeneName

chr14_CBLN3_

chr03_NRADDP_

chr01_SERTAD4.AS1_

chr01_ATPAF1_

chr11_CALCB_

chr16_ZNF764_

chr20_SNRPB2_

chr01_AMIGO1_

chr07_MUC12_

chr16_PDIA2_

chr19_JOSD2_

chr02_IGFBP2_

chr19_HMG20B_

chr22_CHADL_

chr01_DUSP23_

chr22_TUBA3FP_

chr11_KLHL35_

chr06_TOMM6_

chr11_TRPT1_

chr07_NSUN5P1_

chr02_LOC375196_

chr06_LOC729603_

chr19_ANGPTL4_

chr07_NSUN5_

chr13_RBM26.AS1_

chr08_GRINA_

chr01_TSSK3_

chr20_RBBP9_

chr16_PRSS53_

Set 3F:

ChromosomeName_GeneName

chr09_DPM2_

chr01_AURKAIP1_

chr01_DCDC2B_

chr01_TAGLN2_

chr02_FAHD2B_

chr11_CDKN1C_

chr22_TNFRSF13C_

chr02_C2orf27B_

chr08_SLURP1_

chr11_TAGLN_

chr17_B4GALNT2_

chr07_RASA4CP_

chr06_SPACA1_

chr19_PAFAH1B3_

chr11_LOC100652768_

chr07_CYCS_

chr17_TLCD1_

chr17_XYLT2_

chr20_PCK1_

chr02_FABP1_

chr17_ACADVL_

chr17_NPTX1_

chr05_TRIM7_

chr16_RPS2_

chr13_NEK3_

chr01_LEFTY1_

chr01_S100A4_

chr03_C3orf45_

chr16_TBC1D10B_

Chr17_GP1BA_

Set 3G:

ChromosomeName_GeneName

chr03_CLDN18_

chr02_GKN1_

chr01_CAPN8_

chr21_TFF1_

chr01_FAM177B_

chr02_GKN2_

chr04_ANXA10_

chr02_SULT1C2_

chr08_FER1L6_

chr03_NAALADL2.AS3_

Set 3H:

ChromosomeName_GeneName

chr02_TTN.AS1_

chr05_PCDHGA5_

chr05_PCDHGB3_

chr05_PCDHGA6_

chr05_PCDHGA7_

chr05_MIR548AO_

chr05_PCDHGB4_

chr03_SCN5A_

chr19_TNNT1_

chr02_ASB18_

chr05_PCDHGA8_

chr19_ZNF256_

chr03_FGF12_

chr03_FBXO40_

chr05_PCDHGB5_

Set 3I:

ChromosomeName_GeneName

chr12_BHLHE41_

chr11_COX8A_

chr02_GBX2_

chr11_FAM181B_

chr10_LINC00200_

chr11_ZNHIT2_

chr01_FAM43B_

chr15_APBA2_

chr21_KCNJ15_

chr10_C10orf114_

chr05_NPR3_

chr07_DPP6_

chr08_ADRB3_

chr18_CDH20_

chr07_ZNF479_

chr09_SSNA1_

chr12_GAPDH_

chr06_QKI_

chr11_NTM_

chr10_ADARB2_

chr04_HMX1_

chr03_LINC00606_

chr11_KIRREL3.AS2_

chr05_C5orf64_

chr08_NKX2.6_

chr11_ASCL2_

chr19_ETV2_

chr18_SALL3_

chr03_ZDHHC23_

Set 3J:

ChromosomeName_GeneName

chr10_PAX2_

chr02_GALNT14_

chr12_CCDC64_

chr02_LOC654433_

chr15_PAQR5_

chr01_DNAJC11_

chr12_LOC100130238_

chr02_EMX1_

chr13_C13orf35_

chr16_CDH16_

chr19_FUT3_

chr22_BCRP3_

chr02_PAX8_

chr01_SEMA4A_

chr15_IL16_

chr10_OGDHL_

chr17_LOC284100_

Set 3K:

ChromosomeName_GeneName

chr02_APOB_

chr10_CYP2E1_

chr03_ITIH1_

chr05_F12_

chr10_ITIH2_

chr02_ABCG8_

chr11_F2_

chr03_ITIH4_

chr03_NR112_

chr17_ASGR2_

chr10_GPAM_

chr15_AQP9_

chr06_PLG_

chr17_SLC13A5_

chr12_AMDHD1_

chr20_LBP_

Set 3L:

ChromosomeName_GeneName

chr03_CCR5_

chr06_GPR116_

chr01_TDRD10_

chr01_SHE_

chr10_MYOZ1_

chr15_FAM108C1_

chr19_ICAM5_

chr06_MLLT4.AS1_

chr05_GDNF_

chr04_KDR_

chr12_ALDH2_

chr19_KANK3_

chr12_RILPL2_

chr01_TACSTD2_

chr20_GGTLC1_

chr19_ICAM1_

Set 3M:

ChromosomeName_GeneName

chr19_SPIB_

chr12_HVCN1_

chr01_PIK3CD_

chr08_BLK_

chr11_GSTP1_

chr19_FCER2_

chr17_SCIMP_

chr15_LOC388152_

chr19_BST2_

chr07_CARD11_

chr19_CD37_

chr19_NOSIP_

chr07_ATP6V0E2.AS1_

chr09_TRAF1_

chr01_IL10_

chr01_ARHGAP30_

chr16_IL21R.AS1_

chr02_DAPL1_

chr17_ICAM2_

chr05_ITK_

chr08_TNFRSF10A_

chr01_RHD_

chr01_SMAP2_

chr06_TAP1_

chr16_CD19_

chr20_MYBL2_

Set 3N:

ChromosomeName_GeneName

chr01_KLHDC8A_

chr02_TCF23_

chr11_WT1_

chr11_AQP11_

chr01_LHX9_

chr07_TSGA13_

chr12_BTBD11_

chr16_CDH3_

chr02_GREB1_

chr17_ATP1B2_

chr01_LEMD1.AS1_

chr05_LOC643201_

chr19_NXNL1_

Set 3O:

ChromosomeName_GeneName

chr08_EIF4EBP1_

chr10_SFRP5_

chr01_TMEM51.AS1_

chr19_NPHS1_

chr16_UMOD_

chr01_NR5A2_

chr01_KIAA1324_

chr01_ERO1LB_

chr13_DZIP1_

chr15_HOMER2_

chr04_TMED11P_

chr13_CLDN10_

chr06_LINC00222_

chr20_RBPJL_

chr06_SLC16A10_

chr08_TDH_

Set 3P:

ChromosomeName_GeneName

chr19_DPRX_

chr08_CYP7B1_

chr01_HSD3B1_

chr02_ZFP36L2_

chr07_IGF2BP3_

chr18_MBP_

chr13_METTL21C_

chr01_AIM1L_

chr13_WASF3_

chr02_RGPD1_

chr15_CYP19A1_

chr02_RGPD2_

chr01_ADCY10_

chr15_SLCO3A1_

chr07_SLC13A4_

chr16_C16orf45_

chr06_LIN28B_

chr17_RNF222_

chr04_TENM3_

chr15_SH2D7_

chr19_LGALS14_

chr19_CLEC4GP1_

chr16_SPIRE2_

chr08_C8orf42_

chr05_LOC728613_

Set 3Q:

ChromosomeName_GeneName

chr22_NEFH_

chr19_KLKP1_

chr06_SPDEF_

chr03_ACPP_

chr18_SLC14A1_

chr19_ZNF350_

chr07_HOXA13_

chr15_SLC30A4_

chr17_KRT14_

chr15_USP50_

chr06_C6orf52_

chr18_OACYLP_

chr19_KLK2_

chr20_EYA2_

chr10_LOC283038_

chr15_LMANIL_

chr02_HOXD10_

chr02_PPP1R7_

Set 3R:

ChromosomeName_GeneName

chr14_C14orf177_

chr19_SBSN_

chr06_C6orf132_

chr08_LOC340357_

chr18_CD226_

chr05_AHRR_

chr07_HOXA11.AS_

chr14_BCL11B_

chr06_RAB44_

chr10_FAM25A_

chr05_IRX1_

chr02_SLC35F6_

chr18_RAX_

chr07_MIR548T_

chr12_KRT1_

chr16_HS3ST6_

chr02_PTPN4_

chr07_GPNMB_

Chr17_FAM57A_

and

Set 3S:

ChromosomeName_GeneName

chr05_FAM153C_

chr20_DEFB123_

chr16_LITAF_

chr18_ZADH2_

chr09_DMRT1_

chr01_EPS8L3_

chr01_CCDC27_

chr04_SMAD1_

chr11_C11orf91_

chr07_C1GALT1_

chr03_NFKBIZ_

chr20_RIMS4_

chr07_PRSS1_

chr09_OBP2B_

chr12_KRT6A_

chr12_CDK17_

chr21_TEKT4P2_

chr05_ANKRD33B_

chr14_RNASE1_

chr12_PTMS_

chr03_LRRC2_

chr02_SLC30A3_

chr14_IFI27L1_

chr07_C7orf33_.

16 . A method for probabilistically assigning a tissue of origin to cell-free DNA (cfDNA) in a fluid sample obtained from a human subject, comprising:

(a) analyzing the cfDNA in the fluid sample by assessing hydroxymethylation levels within the cfDNA at each of a plurality of hydroxymethylation biomarker loci to generate a sample hydroxymethylation profile, wherein each biomarker locus is contained within a differentially hydroxymethylated genomic region associated with a tissue-specific gene that is both differentially represented and differentially expressed with respect to tissue of origin, and further wherein the biomarker loci analyzed comprise

three or more genes selected from the group consisting of AARD, ADARB1, AKR1B10, CRYM-AS1, EPHA3, GTSF1, KCNMB1, MAP1B, NT5DC3, P2RX1, PCP4, PGM5, PLCD4, PTGFR, RBFOX3, SCARA3, SLIT3, SNX29P1, ST8SIA1, TBX4, TXNRD1, VCL, and WFDC3;

three or more genes selected from the group consisting of ABCA13, AZU1, CA1, CEACAM8, CLEC6A, DAZL, DRGX, DYTN, ELANE, FCAR, GFI1, GYPA, HK3, IL18RAP, LINC00333, LINC00550, LINC00558, LIPN, LOC100129620, LOC442028, LPO, MEFV, MMP8, MMP9, MPO, MS4A3, MYB, MYO1F, NCOR1P1, NME8, OR8U8, OSCAR, PARPBP, PAX3, PDCL2, PRDM13, PROK2, RGS18, RGS21, RRM2, RXFP2, SERPINB10, SLC22A16, SPATA16, SPI1, SPTA1, TARM1, TMPRSS15, TRIM58, VSTM1, and XKR;

three or more genes selected from the group consisting of ASPHD1, BRSK1, CCDC177, CNTN2, HAPLN2, KCNJ10, KIF1A, LGI3, NCAN, NR2E1, RHBDL3, TMEM151A, TMEM235, TMEM59L, and ZNF488;

three or more genes selected from the group consisting of ADPRHL1, ASB18, ATP1A3, CDH13, CORO6, FSD2, GALNT16, GJA3, MYOM2, PCDHGA1, PCDHGA10, PCDHGA11, PCDHGA12, PCDHGA2, PCDHGA3, PCDHGA4, PCDHGA5, PCDHGA6, PCDHGA7, PCDHGA8, PCDHGA9, PCDHGB1, PCDHGB2, PCDHGB3, PCDHGB5, PCDHGB6, PCDHGB7, PXDNL, RPL3L, SGCG, and TNNT1;

three or more genes selected from the group consisting of BBOX1, BCRP3, CA12, COL4A3, CXCL14, CYS1, EVC, FIGNL2, GALNT14, GLIS2, HAVCR1, LOC100130238, PAQR5, PAX2, PAX8, PLA2G15, SLC22A2, SLC9A3, SULT1C2, and TSPAN33;

three or more genes selected from the group consisting of ABCC2, ABCG5, ABCG8, AHSG, AKR1C4, AMDHD1, APOH, ASGR1, ASGR2, C3P1, C8A, C8B, C9, CA5A, CFHR4, CPN2, CREB3L3, CYP2B6, CYP2C9, CYP2E1, CYP3A4, DHODH, F12, F2, F7, GC, HAL, HPD, HPX, INHBC, ITIH1, ITIH2, ITIH3, KNG1, LBP, PGLYRP2, PLG, PROC, PRODH2, SERPINA6, SERPINC1, SLC13A5, SLC22A1, SLC25A47, SLC27A5, SULT2A1, TFR2, TMPRSS6, and UROC1;

three or more genes selected from the group consisting of ANXA3, BMP5, CYP4Z2P, DRAM1, FMO2, GNA15, IDO1, KCNS3, LIMCH1, MBIP, PAPSS2, PCDH17, RSPH4A, RTKN2, and TRPC6;

three or more genes selected from the group consisting of ACAP1, AKNA, ARHGAP9, BCL11B, BIRC3, CARD11, CD180, CD37, CD3E, CD3G, CD40, CETP, CIITA, CLEC2D, CNR2, CXCR5, DOCK10, ETS1, GPR132, GPR18, ICAM2, ICOS, ITGB7, ITK, KIAA1551, KLHL6, LCK, LINC00426, LY86, MDS2, MEOX2, MX2, NAPSB, PATL2, PCED1B-AS1, PIK3CD, PLVAP, POU2F2, SCIMP, SCML4, SLFN12L, SMAP2, SP110, SPIB, TLR10, TMC8, TMEM156, TNFAIP8, TNFRSF9, TNFSF11, TRAF1, TRIM22, UCP2, and ZC3H12D;

three or more genes selected from the group consisting of ABCA10, ACSS3, ADAMTS5, AQP11, C7, CDH3, CDON, CLDN11, COL14A1, COLEC11, ESR2, FAM198B, FZD3, GALNT10, GLI2, GSTM5, HS3ST1, LEMD1-AS1, LHX9, LRRC17, MCHR1, MRC2, NTF3, OMD, PDGFRA, PGR, PKNOX2, PTCH2, RWDD4, SCD5, SERPINE2, SIMC1, SLC25A17, SNCAIP, SULF2, TENM4, TSPAN5, TTC8, and UBXN8;

three or more genes selected from the group consisting of ALDH1L2, ANKEF1, ASNS, B3GALNT2, BCAT1, CASP9, CCDC110, CELA2B, CELA3B, CFTR, CHMP4C, CLDN1, CNIH3, COCH, CUZD1, DEFB1, EGF, EIF4EBP1, ERP27, FAM24B-CUZD1, FBXW12, GUCA1C, KCTD16, KIAA1324, LINC00339, LNX2, MKNK1, NAA16, NPHS1, PAIP2B, PM20D1, PRSS3, SCGN, SEL1L, SERPINI2, SH3YL1, SLC33A1, SLC4A4, TC2N, TDH, TMEM51-AS1, TRHDE, and UMOD;

three or more genes selected from the group consisting of ADAM12, ATG9B, ATP6V1C2, BCAR4, BMP1, BPGM, CSF3R, CYP11A1, CYP19A1, DACT2, DEPDC1B, DLX5, EBI3, GCM1, GPR78, GSTA3, IGF2BP3, IGSF5, ISM2, KISS1, KRT23, LIN28B, MMP11, PGF, PSG11, PSG2, PSG3, PSG6, PSG7, PSG8, SPTLC3, TPRXL, ZFAT, and ZNF554;

three or more genes selected from the group consisting of ABCC4, ACPP, ALOX15B, ANO7, AP1B1P1, ARG2, BEND4, C6orf132, C6orf52, CANT1, CASZ1, CBFA2T2, CHRM1, CHRNA2, COL26A1, EVX1, EYA2, FAM135A, HMGN2P46, KLK2, KLKP1, MME, MPPED2, MUC12, NANS, NCAPD3, NEFH, NIPAL3, OACYLP, OR51E2, PAK1IP1, PDE9A, PI15, PMEPA1, POTEF, RDH11, SCNN1G, SIM2, SLC14A1, SLC22A3, SLC2A12, SLC30A4, SLC35F2, SLC37A1, SLC39A6, SPDEF, STEAP2, THSD4, TMEM79, TPM3P9, TXNDC16, URB1, VIPR1, ZNF350, ZNF532, ZNF613, ZNF649, ZNF761, and ZNF827;

three or more genes selected from the group consisting of GADL1, GIPC3, PTGES3L, and WSCD2;

three or more genes selected from the group consisting of CCDC27, DMRT1, DNAJC5G, FBXO24, IGLL1, MOV10L1, SEPT14, THEG, and TTC16;

at least one gene selected from FGL2 and SCNN1B; and at least one gene selected from ASTN1 and DGK1;

(b) comparing each assessed hydroxymethylation level in the sample hydroxymethylation profile with a corresponding reference hydroxymethylation level at each biomarker locus analyzed, the reference hydroxymethylation levels being contained within a plurality of different tissue-specific reference hydroxymethylation profiles in a reference data set, thereby generating a hydroxymethylation difference data set comprising differences identified between the generated sample hydroxymethylation profile and the reference hydroxymethylation profiles at each biomarker locus;

(c) using a computer system, carrying out a correlation analysis using one or more algorithms that determine a statistical correlation between the assessed hydroxymethylation levels and the reference hydroxymethylation levels at each biomarker locus; and

(d) using the statistical correlation, providing a probabilistic assignment of at least one tissue of origin to the cfDNA.

Assignments (2)

Continuity (4)

References Cited (34)