Minor histocompatibility antigen markers associated with graft versus leukemia effect and uses thereof

Abstract

Minor histocompatibility antigens (mHAgs) associated with graft versus leukemia (GvL) clinical outcomes identified by single nucleotide polymorphisms (SNPS) and uses thereof are described.

Description

[0001] MINOR HISTOCOMPATIBILITY ANTIGEN MARKERS ASSOCIATED

[0002] WITH GRAFT VERSUS LEUKEMIA EFFECT AND USES THEREOF

[0003] CONTINUING APPLICATION DATA

[0004] This application claims the benefit of U.S. Provisional Application Serial No. 63 / 554,503, filed February 16, 2024, which is incorporated by reference herein.

[0005] GOVERNMENT FUNDING

[0006] This invention was made with government support under Grant Nos. 1R01HL157174 and P01 CA229092, awarded by the National Institutes of Health. The Government has certain rights in the invention.

[0007] BACKGROUND

[0008] T cell alloreactivity against minor histocompatibility antigens (mHAgs), polymorphic peptides resulting from donor-recipient (D-R) disparity at sites of genetic polymorphisms (SNPs, indels, frameshifts), is at the core of the therapeutic effect of allogeneic hematopoietic stem cell transplantation (allo-HSCT). Despite the crucial role of mHAgs in graft-versus-leukemia (GvL) and graft-versus-host (GvH) reactions, it has not been possible thus far to consistently link patient-specific mHAg repertoires to clinical outcomes.

[0009] SUMMARY

[0010] There are provided methods for selecting an HLA-matched transplant donor, the method including: determining the presence or absence of one or more SNPs from a panel of SNPs in the donor; determining the presence or absence of one or more SNPs from the panel of SNPs in the recipient; and identifying one or more mismatches between the recipient and the donor, wherein a mismatch includes the presence in the recipient and the absence in the donor of a given SNP from the panel of SNPs; and selecting as the transplant donor the donor including one or more mismatches between the recipient and the donor; wherein GvHD-free and relapse-free survival (GRFS) is improved in the recipient after receipt of donor tissue from the donor; and wherein the panel of SNPs includes the TICRR p.R287C SNR; the CNTLN p.T695I SNP; the ZNF792 p.Rl 10Q SNP; the LY9 p.M240V SNP; the CTLA4 p.T17A SNP; the WDR49 p.L476P SNP; the HELB p.L191P SNP; the PRDM15 p.R88fs SNP; the PRTN3 p.V78I SNP; the C15orf40 p.C25R SNP; the MCPH1 p.A761V SNP; the MEFV p.D424E SNP; the CR1 p.T1408M SNP; the LILRB1 p.L68P SNP; the ARL11 p.C148R SNP; the ATXN3 p.V33M SNP; the EX01 p.E589K SNP; the LILRB4 p.Q361R SNP; the MCPH1 p.R256I SNP; the MTERF p.A274T SNP; the P2RY13 p.T179M SNP; the PLD4 p.E27Q SNP; the PSTK p.G206R SNP; the RNASE3 p.T124R SNP; the SERPINB10 p.I41M SNP; the WDFY4 p.S1528P SNP; the CD300E p.G158R SNP; the DNAH14 p.L3088P SNP; the MMP8 p.T32I SNP; the PAD 14 p.G55S SNP; the RAD18 p.R302Q SNP; the SPNS3 p.A203S SNP; the APOBEC3F p.A108S SNP; the Cl lorf82 p.R159S SNP; the C19orf59 p.I124V SNP; the CCDC171 p.K1069R SNP; the EMR2 p.A53V SNP; the EPX p.Q122H SNP; the GP1BA p.T161M SNP; the IL5RA p.I129V SNP; the PSMG4 p.T44P SNP; the WDFY4 p.T2525P SNP; the ZBED6 p.F560L SNP; the CNR2 p.Q63R SNP; the CD101 p.N225S SNP; the CEACAM4 p.H29D SNP; the TLR3 p.L135F SNP; the CLEC4C p.P35S SNP; the CLECL1 p.S52fs SNP; the TVP23C p.S199T SNP; the AK7 p.N389K SNP; the CD3G p.V131F SNP; the CD86 p.A97T SNP; the IL12RB1 p.Q214R SNP; the NLRP7 p.V3191 SNP; the RHCE p.C16W SNP; the RHCE p.A210P SNP; the SLAMF1 p.FUL SNP; the SLFN12L p.Y383C SNP; the SLFN12L p.Y518S SNP; the TIGD6 p.Q327R SNP; the BATF3 p.Vl II SNP; the CASC1 p.R33S SNP; the CD200R1 p.T99P SNP; the DCLRE1C p.H123R SNP; the N4BP2 p.SlOH SNP; the NLRP12 p.G39V SNP; the SIGLEC9 p.KlOOE SNP; the SPEF2 p.N71H SNP; the TLR7 p.Ql IL SNP; the TRPM6 p.T2I SNP; the CASP5 p.L192V SNP; the CASP5 p.T48A SNP; the CD1E p.Q104R SNP; the CD200R1L p.R92L SNP; the CSF2RA p.A17G SNP; the GTPBP10 p.L85F SNP; the

[0011] KIAA1549 p.P436A SNP; the LILRA4 p.P27L SNP; the NAALADL2 p.G68S SNP; the RGPD2 p.S177L SNP; the RTP4 p.T131M SNP; the S100Z p.E23A SNP; the SIGLEC6 p.P246S SNP; the THEMIS p.I551V SNP; the TTC30A p.P279H SNP; and / or the ZNF286B p.P466S SNP.

[0012] Also provided are methods for inducing a graft versus leukemia (GvL) reaction in a HLA-matched transplant recipient receiving donor tissue from a donor, the method including: determining the presence or absence of one or more SNPs from the panel of SNPs for the donor; determining the presence or absence of SNPs from the panel of SNPs for the recipient; identifying one or more mismatches between the recipient and the donor, wherein a mismatch includes the presence in the recipient and the absence in the donor of a given SNP from the panel of SNPs; and transplanting the recipient with donor tissue from the donor when there is one or more mismatches between the recipient and the donor; wherein the panel of SNPs includes the TICRR p.R287C SNP; the CNTLN p.T695I SNP; the ZNF792 p.Rl 10Q SNP; the LY9 p.M240V SNP; the CTLA4 p.T17A SNP; the WDR49 p.L476P SNP; the HELB p.L191P SNP; the PRDM15 p.R88fs SNP; the PRTN3 p.V78I SNP; the C15orf40 p.C25R SNP; the MCPH1 p.A761V SNP; the MEFV p.D424E SNP; the CR1 p.T1408M SNP; the LILRB1 p.L68P SNP; the ARL11 p.C148R SNP; the ATXN3 p.V33M SNP; the EX01 p.E589K SNP; the LILRB4 p.Q361R SNP; the MCPH1 p.R256I SNP; the MTERF p.A274T SNP; the P2RY13 p.T179M SNP; the PLD4 p.E27Q SNP; the PSTK p.G206R SNP; the RNASE3 p.T124R SNP; the SERPENBIO p.I41M SNP; the WDFY4 p.S1528P SNP; the CD300E p.G158R SNP; the DNAH14 p.L3088P SNP; the MMP8 p.T32I SNP; the PADI4 p.G55S SNP; the RAD18 p.R302Q SNP; the SPNS3 p.A203S SNP; the APOBEC3F p.A108S SNP; the Cl lorf82 p.R159S SNP; the C19orf59 p.I124V SNP; the CCDC171 p.K1069R SNP; the EMR2 p.A53V SNP; the EPX p.Q122H SNP; the GP1BA p.T161M SNP; the IL5RA p.I129V SNP; the PSMG4 p.T44P SNP; the WDFY4 p.T2525P SNP; the ZBED6 p.F560L SNP; the CNR2 p.Q63R SNP; the CD101 p.N225S SNP; the CEACAM4 p.H29D SNP; the TLR3 p.L135F SNP; the CLEC4C p.P35S SNP; the CLECL1 p.S52fs SNP; the TVP23C p.S199T SNP; the AK7 p.N389K SNP; the CD3G p.V13 IF SNP; the CD86 p.A97T SNP; the IL12RB1 p.Q214R SNP; the NLRP7 p.V319I SNP; the RHCE p.C16W SNP; the RHCE p.A210P SNP; the SLAMF1 p.FUL SNP; the SLFN12L p.Y383C SNP; the SLFN12L p.Y518S SNP; the TIGD6 p.Q327R SNP; the BATF3 p.VHI SNP; the CASC1 p.R33S SNP; the CD200R1 p.T99P SNP; the DCLRE1C p.H123R SNP; the N4BP2 p.SlOH SNP; the NLRP12 p.G39V SNP; the SIGLEC9 p.KlOOE SNP; the SPEF2 p.N71H SNP; the TLR7 p.Ql IL SNP; the TRPM6 p.T2I SNP; the CASP5 p.L192V SNP; the CASP5 p.T48A SNP; the CD1E p.Q104R SNP; the CD200R1L p.R92L SNP; the CSF2RA p.A17G SNP; the GTPBP10 p.L85F SNP; the KIAA1549 p.P436A SNP; the LILRA4 p.P27L SNP; the NAALADL2 p.G68S SNP; the RGPD2 p.S177L SNP; the RTP4 p.T131M SNP; the S100Z p.E23A SNP; the SIGLEC6 p.P246S SNP; the THEMIS p.I551V SNP; the TTC30A p.P279H SNP; and / or the ZNF286B p.P466S SNP. In some aspects of the methods provided herein, identifying one or more mismatches between the recipient and the donor includes identifying ten or more mismatches.

[0013] In some aspects of the methods provided herein, the one or more of the SNPs from the panel of SNPs includes the APOBEC3F p.A108S SNP and / or the MCPH1 p.R256I SNP.

[0014] In some aspects of the methods provided herein, the HLA-matched donor and recipient include HLA A0101, HLA A0201, HL A A0208, HLA A0301, HLA A0302, HLA Al 101, HLA A2301, HLA A2402, HLA A2403, HLA A2601, HLA A2902, HLA A3001, HLA A3101, HLA A3201, HLA A3301, HLA A6601, HLA A6801, HLA A6802, HLA A7401, HLA A8001, HLA B0702, HLA B0801, HLA Bl 302, HLA Bl 401, HLA Bl 402, HLA Bl 501, HLA Bl 503, HLA B1801, HLA B2705, HLA B3501, HLA B3502, HLA B3508, HLA B3701, HLA B3801, HLA B3901, HLA B4001, HLA B4006, HLA B4101, HLA B4102, HLA B4402, HLA B4403, HLA B4501, HLA B4901, HLA B5101, HLA B5201, HLA B5301, HLA B5701, HLA B5802, HLA C0102, HLA C0202, HLA C0303, HLA C0304, HLA C0401, HLA C0501, HLA C0602, HLA C0701, HLA C0702, HLA C0704, HLA C0802, HLA Cl 202, HLA Cl 203, HLA Cl 402, HLA C1502, HLA C1505, HLA C1601, HLA C1602, and / or HLA C1701.

[0015] In some aspects of the methods provided herein, the SNP information for the donor and / or the recipient is obtained by targeted next generation sequencing (NGS), whole exome sequencing (WES), whole genomic sequencing (WGS), and / or SNP array-based genotyping.

[0016] In some aspects of the methods provided herein, the donor and / or the recipient are human.

[0017] In some aspects of the methods provided herein, the transplantation of donor tissue is for the treatment of a cancer. In some aspects, the cancer includes acute myeloid leukemia (AML) or myelodysplastic syndrome (MDS).

[0018] In some aspects of the methods provided herein, the donor tissue includes hematopoietic cells.

[0019] In some aspects of the methods provided herein, the donor tissue includes HLA-matched allogeneic hematopoietic stem cells.

[0020] Also provided herein are compositions including one or more graft versus leukemia minor histocompatibility antigen (GvL mHAg)-specific antigenic epitopes and a pharmaceutical composition, wherein a GvL mHAg-specific antigenic epitope consists of a peptide of about 8-11 amino acids encoded by a single nucleotide polymorphism (SNP) selected from the group consisting of the TICRR p.R287C SNP; the CNTLN p.T695I SNP; the ZNF792 p.Rl 10Q SNP; the LY9 p.M240V SNP; the CTLA4 p.T17A SNP; the WDR49 p.L476P SNP; the HELB p.L191P SNP; the PRDM15 p.R88fs SNP; the PRTN3 p.V78I SNP; the C15orf40 p.C25R SNP; the MCPH1 p.A761V SNP; the MEFV p.D424E SNP; the CR1 p.T1408M SNP; the LILRB1 p.L68P SNP; the ARL11 p.C148R SNP; the ATXN3 p.V33M SNP; the EX01 p.E589K SNP; the LILRB4 p.Q361R SNP; the MCPH1 p.R256I SNP; the MTERF p.A274T SNP; the P2RY13 p.T179M SNP; the PLD4 p.E27Q SNP; the PSTK p.G206R SNP; the RNASE3 p.T124R SNP; the SERPINB10 p.I41M SNP; the WDFY4 p.S1528P SNP; the CD300E p.G158R SNP; the DNAH14 p.L3088P SNP; the MMP8 p.T32I SNP; the PADI4 p.G55S SNP; the RAD18 p.R302Q SNP; the SPNS3 p.A203S SNP; the APOBEC3F p.A108S SNP; the Cl lorf82 p.R159S SNP; the C19orf59 p.I124V SNP; the CCDC171 p.K1069R SNP; the EMR2 p.A53V SNP; the EPX p.Q122H SNP; the GP1BA p.T161M SNP; the IL5RA p.I129V SNP; the PSMG4 p.T44P SNP; the WDFY4 p.T2525P SNP; the ZBED6 p.F560L SNP; the CNR2 p.Q63R SNP; the CD101 p.N225S SNP; the CEACAM4 p.H29D SNP; the TLR3 p.L135F SNP; the CLEC4C p.P35S SNP; the CLECL1 p.S52fs SNP; the TVP23C p.S199T SNP; the AK7 p.N389K SNP; the CD3G p.V131F SNP; the CD86 p.A97T SNP; the IL12RB1 p.Q214R SNP; the NLRP7 P.V319I SNP; the RHCE p.C16W SNP; the RHCE p.A210P SNP; the SLAMF1 p.FUL SNP; the SLFN12L p.Y383C SNP; the SLFN12L p.Y518S SNP; the TIGD6 p.Q327R SNP; the BATF3 p.VHI SNP; the CASC1 p.R33S SNP; the CD200R1 p.T99P SNP; the DCLRE1C p.H123R SNP; the N4BP2 p.SlOH SNP; the NLRP12 p.G39V SNP; the SIGLEC9 p.KlOOE SNP; the SPEF2 p.N71H SNP; the TLR7 p.Ql IL SNP; the TRPM6 p.T2I SNP; the CASP5 p.L192V SNP; the CASP5 p.T48A SNP; the CD1E p.Q104R SNP; the CD200R1L p.R92L SNP; the CSF2RA p.A17G SNP; the GTPBP10 p.L85F SNP; the KIAA1549 p.P436A SNP; the LILRA4 p.P27L SNP; the NAALADL2 p.G68S SNP; the RGPD2 p.S177L SNP; the RTP4 p.T131M SNP; the S1OOZ p.E23A SNP; the SIGLEC6 p.P246S SNP; the THEMIS p.I551V SNP; the TTC30A p.P279H SNP; and the ZNF286B p.P466S SNP. In some aspects, the composition is for use as a GvL mHAg-targeting vaccine.

[0021] Also provided herein are kits for including a plurality of probes capable of binding to and / or identifying one or more of the TICRR p.R287C SNP; the CNTLN p.T695I SNP; the ZNF792 p.Rl 10Q SNP; the LY9 p.M240V SNP; the CTLA4 p.T17A SNP; the WDR49 p.L476P SNP; the HELB p.L191P SNP; the PRDM15 p.R88fs SNP; the PRTN3 p.V78I SNP; the C15orf40 p.C25R SNP; the MCPH1 p.A761 V SNP; the MEFV p.D424E SNP; the CR1 p.T1408M SNP; the LILRBl p.L68P SNP; the ARL11 p.C148R SNP; the ATXN3 p.V33M SNP; the EX01 p.E589K SNP; the LILRB4 p.Q361R SNP; the MCPH1 p.R256I SNP; the MTERF p.A274T SNP; the P2RY13 p.T179M SNP; the PLD4 p.E27Q SNP; the PSTK p.G206R SNP; the RNASE3 p.T124R SNP; the SERPINB10 p.I41M SNP; the WDFY4 p.S1528P SNP; the CD300E p.G158R SNP; the DNAH14 p.L3088P SNP; the MMP8 p.T32I SNP; the PADI4 p.G55S SNP; the RAD18 p.R302Q SNP; the SPNS3 p.A203S SNP; the APOBEC3F p.A108S SNP; the Cl lorf 2 p.R159S SNP; the C19orf59 p.I124V SNP; the CCDC171 p.K1069R SNP; the EMR2 p.A53V SNP; the EPX p.Q122H SNP; the GP1BA p.T161M SNP; the IL5RA p.I129V SNP; the PSMG4 p.T44P SNP; the WDFY4 p.T2525P SNP; the ZBED6 p.F56OL SNP; the CNR2 p.Q63R SNP; the CD101 p.N225S SNP; the CEACAM4 p.H29D SNP; the TLR3 p.L135F SNP; the CLEC4C p.P35S SNP; the CLECL1 p.S52fs SNP; the TVP23C p.S199T SNP; the AK7 p.N389K SNP; the CD3G p.V131F SNP; the CD86 p.A97T SNP; the IL12RB1 p.Q214R SNP; the NLRP7 p.V3191 SNP; the RHCE p.C16W SNP; the RHCE p.A210P SNP; the SLAMF1 p.FUL SNP; the SLFN12L p.Y383C SNP; the SLFN12L p.Y518S SNP; the TIGD6 p.Q327R SNP; the BATF3 p.VHI SNP; the CASC1 p.R33S SNP; the CD200R1 p.T99P SNP; the DCLRE1C p.H123R SNP; the N4BP2 p.SlOH SNP; the NLRP12 p.G39V SNP; the SIGLEC9 p.KlOOE SNP; the SPEF2 p.N71H SNP; the TLR7 p.Ql IL SNP; the TRPM6 p.T2I SNP; the CASP5 p.L192V SNP; the CASP5 p.T48A SNP; the CD1E p.Q104R SNP; the CD200R1L p.R92L SNP; the CSF2RA p.A17G SNP; the GTPBP10 p.L85F SNP; the

[0022] KIAA1549 p.P436A SNP; the LILRA4 p.P27L SNP; the NAALADL2 p.G68S SNP; the RGPD2 p.S177L SNP; the RTP4 p.T131M SNP; the S1OOZ p.E23A SNP; the SIGLEC6 p.P246S SNP; the THEMIS p.I551V SNP; the TTC30A p.P279H SNP; and / or the ZNF286B p.P466S SNP in a sample from the transplant donor and / or the transplant recipient.

[0023] In some aspects, the kit consists of each of the TICRR p.R287C SNP; the CNTLN p.T695I SNP; the ZNF792 p.Rl 10Q SNP; the LY9 p.M240V SNP; the CTLA4 p.T17A SNP; the WDR49 p.L476P SNP; the HELB p.L191P SNP; the PRDM15 p.R88fs SNP; the PRTN3 p.V78I SNP; the C15orf40 p.C25R SNP; the MCPH1 p.A761V SNP; the MEFV p.D424E SNP; the CR1 p.T1408M SNP; the LILRB1 p.L68P SNP; the ARL11 p.C148R SNP; the ATXN3 p.V33M SNP; the EXO1 p.E589K SNP; the LILRB4 p.Q361R SNP; the MCPH1 p.R256I SNP; the MTERF p.A274T SNP; the P2RY13 p.T179M SNP; the PLD4 p.E27Q SNP; the PSTK p.G206R SNP; the RNASE3 p.T124R SNP; the SERPINB10 p.I41M SNP; the WDFY4 p.S1528P SNP; the CD3OOE p.G158R SNP; the DNAH14 p.L3088P SNP; the MMP8 p.T32I SNP; the PADI4 p.G55S SNP; the RAD18 p.R302Q SNP; the SPNS3 p.A203S SNP; the APOBEC3F p.A108S SNP; the Cl lorf82 p.R159S SNP; the C19orf59 p.I124V SNP; the CCDC171 p.K1069R SNP; the EMR2 p.A53V SNP; the EPX p.Q122H SNP; the GP1BA p.T161M SNP; the IL5RA p.I129V SNP; the PSMG4 p.T44P SNP; the WDFY4 p.T2525P SNP; the ZBED6 p.F56OL SNP; the CNR2 p.Q63R SNP; the CD1O1 p.N225S SNP; the CEACAM4 p.H29D SNP; the TLR3 p.L135F SNP; the CLEC4C p.P35S SNP; the CLECL1 p.S52fs SNP; the TVP23C p.S199T SNP; the AK7 p.N389K SNP; the CD3G p.V131F SNP; the CD86 p.A97T SNP; the IL12RB1 p.Q214R SNP; the NLRP7 p.V3191 SNP; the RHCE p.C16W SNP; the RHCE p.A210P SNP; the SLAMF1 p.Fl lL SNP; the SLFN12L p.Y383C SNP; the SLFN12L p.Y518S SNP; the TIGD6 p.Q327R SNP; the BATF3 p.Vl II SNP; the CASC1 p.R33S SNP; the CD200R1 p.T99P SNP; the DCLRE1C p.H123R SNP; the N4BP2 p.SlOH SNP; the NLRP12 p.G39V SNP; the SIGLEC9 p.KlOOE SNP; the SPEF2 p.N71H SNP; the TLR7 p.Ql IL SNP; the TRPM6 p.T2I SNP; the CASP5 p.L192V SNP; the CASP5 p.T48A SNP; the CD1E p.Q104R SNP; the CD200R1L p.R92L SNP; the CSF2RA p.A17G SNP; the GTPBP10 p.L85F SNP; the KIAA1549 p.P436A SNP; the LILRA4 p.P27L SNP; the NAALADL2 p.G68S SNP; the RGPD2 p.S177L SNP; the RTP4 p.T131M SNP; the S1OOZ p.E23A SNP; the SIGLEC6 p.P246S SNP; the THEMIS p.I551V SNP; the TTC30A p.P279H SNP; and the ZNF286B p.P466S SNP in a sample from the transplant donor and / or the transplant recipient.

[0024] Also provided herein are kits for including a plurality of primers for selectively amplifying one or more of the TICRR p.R287C SNP; the CNTLN p.T695I SNP; the ZNF792 p.Rl 10Q SNP; the LY9 p.M240V SNP; the CTLA4 p.T17A SNP; the WDR49 p.L476P SNP; the HELB p.L191P SNP; the PRDM15 p.R88fs SNP; the PRTN3 p.V78I SNP; the C15orf40 p.C25R SNP; the MCPH1 p.A761V SNP; the MEFV p.D424E SNP; the CR1 p.T1408M SNP; the LILRB1 p.L68P SNP; the ARL11 p.C148R SNP; the ATXN3 p.V33M SNP; the EXO1 p.E589K SNP; the LILRB4 p.Q361R SNP; the MCPH1 p.R256I SNP; the MTERF p.A274T SNP; the P2RY13 p.T179M SNP; the PLD4 p.E27Q SNP; the PSTK p.G206R SNP; the RNASE3 p.T124R SNP; the SERPINB10 p.I41M SNP; the WDFY4 p.S1528P SNP; the CD300E p.G158R SNP; the DNAH14 p.L3088P SNP; the MMP8 p.T32I SNP; the PAD 14 p.G55S SNP; the RAD18 p.R302Q SNP; the SPNS3 p.A203S SNP; the APOBEC3F p.A108S SNP; the Cl lorf82 p.R159S SNP; the C19orf59 p.I124V SNP; the CCDC171 p.K1069R SNP; the EMR2 p.A53V SNP; the EPX p.Q122H SNP; the GP1BA p.T161M SNP; the IL5RA p.I129V SNP; the PSMG4 p.T44P SNP; the WDFY4 p.T2525P SNP; the ZBED6 p.F560L SNP; the CNR2 p.Q63R SNP; the CD101 p.N225S SNP; the CEACAM4 p.H29D SNP; the TLR3 p.L135F SNP; the CLEC4C pP35S SNP; the CLECL1 p.S52fs SNP; the TVP23C p.S199T SNP; the AK7 p.N389K SNP; the CD3G p.V131F SNP; the CD86 p.A97T SNP; the IL12RB1 p.Q214R SNP; the NLRP7 p.V3191 SNP; the RHCE p.C16W SNP; the RHCE p.A210P SNP; the SLAMF1 p.FUL SNP; the SLFN12L p.Y383C SNP; the SLFN12L p.Y518S SNP; the TIGD6 p.Q327R SNP; the BATF3 p.Vl II SNP; the CASC1 p.R33S SNP; the CD200R1 p.T99P SNP; the DCLRE1C p.H123R SNP; the N4BP2 p.SlOH SNP; the NLRP12 p.G39V SNP; the SIGLEC9 p.KlOOE SNP; the SPEF2 p.N71H SNP; the TLR7 p.Ql IL SNP; the TRPM6 p.T2I SNP; the CASP5 p.L192V SNP; the CASP5 p.T48A SNP; the CD1E p.Q104R SNP; the CD200R1L p.R92L SNP; the CSF2RA p.A17G SNP; the GTPBP10 p.L85F SNP; the KIAA1549 p.P436A SNP; the LILRA4 p.P27L SNP; the NAALADL2 p.G68S SNP; the RGPD2 p.S177L SNP; the RTP4 p.T131M SNP; the S1OOZ p.E23A SNP; the SIGLEC6 pP246S SNP; the THEMIS p.I551V SNP; the TTC30A pP279H SNP; and / or the ZNF286B pP466S SNP in a sample from the transplant donor and / or the transplant recipient.

[0025] In some aspects, the kit consists of each of the TICRR p.R287C SNP; the CNTLN p.T695I SNP; the ZNF792 p.Rl 10Q SNP; the LY9 p.M240V SNP; the CTLA4 p.T17A SNP; the WDR49 p.L476P SNP; the HELB p.L191P SNP; the PRDM15 p.R88fs SNP; the PRTN3 p.V78I SNP; the C15orf40 p.C25R SNP; the MCPH1 p.A761V SNP; the MEFV p.D424E SNP; the CR1 p.T1408M SNP; the LILRB1 p.L68P SNP; the ARL11 p.C148R SNP; the ATXN3 p.V33M SNP; the EXO1 p.E589K SNP; the LILRB4 p.Q361R SNP; the MCPH1 p.R256I SNP; the MTERF p.A274T SNP; the P2RY13 p.T179M SNP; the PLD4 p.E27Q SNP; the PSTK p.G206R SNP; the RNASE3 p.T124R SNP; the SERPINB10 p.I41M SNP; the WDFY4 p.S1528P SNP; the CD300E p.G158R SNP; the DNAH14 p.L3088P SNP; the MMP8 p.T32I SNP; the PADI4 p.G55S SNP; the RAD18 p.R302Q SNP; the SPNS3 p.A203S SNP; the APOBEC3F p.A108S SNP; the Cl lorf82 p.R159S SNP; the C19orf59 p.I124V SNP; the CCDC171 p.K1069R SNP; the EMR2 p.A53V SNP; the EPX p.Q122H SNP; the GP1BA p.T161M SNP; the IL5RA p.I129V SNP; the PSMG4 p.T44P SNP; the WDFY4 p.T2525P SNP; the ZBED6 p.F560L SNP; the CNR2 p Q63R SNP; the CD101 p.N225S SNP; the CEACAM4 p.H29D SNP; the TLR3 p.L135F SNP; the CLEC4C p.P35S SNP; the CLECL1 p.S52fs SNP; the TVP23C p.S199T SNP; the AK7 p.N389K SNP; the CD3G p.V131F SNP; the CD86 p.A97T SNP; the IL12RB1 p.Q214R SNP; the NLRP7 p.V3191 SNP; the RHCE p.C16W SNP; the RHCE p.A210P SNP; the SLAMF1 p.FUL SNP; the SLFN12L p.Y383C SNP; the SLFN12L p.Y518S SNP; the TIGD6 p.Q327R SNP; the BATF3 p.VHI SNP; the CASC1 p.R33S SNP; the CD200R1 p.T99P SNP; the DCLRE1C p.H123R SNP; the N4BP2 p.SlOH SNP; the NLRP12 p.G39V SNP; the SIGLEC9 p.KlOOE SNP; the SPEF2 p.N71H SNP; the TLR7 p.Ql IL SNP; the TRPM6 p.T2I SNP; the CASP5 p.L192V SNP; the CASP5 p.T48A SNP; the CD1E p.Q104R SNP; the CD200R1L p.R92L SNP; the CSF2RA p.A17G SNP; the GTPBP10 p.L85F SNP; the KIAA1549 p.P436A SNP; the LILRA4 p.P27L SNP; the NAALADL2 p.G68S SNP; the RGPD2 p.S177L SNP; the RTP4 p.T131M SNP; the S1OOZ p.E23A SNP; the SIGLEC6 p.P246S SNP; the THEMIS p.I551V SNP; the TTC30A p.P279H SNP; and the ZNF286B p.P466S SNP.

[0026] As used herein, “isolated” refers to material removed from its original environment (e.g., the natural environment if it is naturally occurring), and thus is altered “by the hand of man” from its natural state.

[0027] The term “and / or” means one or all of the listed elements or a combination of any two or more of the listed elements.

[0028] The words “preferred” and “preferably” refer to embodiments that may afford certain benefits, under certain circumstances. However, other embodiments may also be preferred, under the same or other circumstances. Furthermore, the recitation of one or more preferred embodiments does not imply that other embodiments are not useful and is not intended to exclude other embodiments.

[0029] The terms “comprises” and variations thereof do not have a limiting meaning where these terms appear in the description and claims.

[0030] Unless otherwise specified, “a,” “an,” “the,” and “at least one” are used interchangeably and mean one or more than one.

[0031] Also herein, the recitations of numerical ranges by endpoints include all numbers subsumed within that range (e.g., 1 to 5 includes 1, 1.5, 2, 2.75, 3, 3.80, 4, 5, etc.).

[0032] For any method disclosed herein that includes discrete steps, the steps may be conducted in any feasible order. And, as appropriate, any combination of two or more steps may be conducted simultaneously. Unless otherwise indicated, all numbers expressing quantities of components, molecular weights, and so forth used in the specification and claims are to be understood as being modified in all instances by the term "about." Accordingly, unless otherwise indicated to the contrary, the numerical parameters set forth in the specification and claims are approximations that may vary depending upon the desired properties sought to be obtained by the present invention. At the very least, and not as an attempt to limit the doctrine of equivalents to the scope of the claims, each numerical parameter should at least be construed in light of the number of reported significant digits and by applying ordinary rounding techniques.

[0033] Notwithstanding that the numerical ranges and parameters setting forth the broad scope of the invention are approximations, the numerical values set forth in the specific examples are reported as precisely as possible. All numerical values, however, inherently contain a range necessarily resulting from the standard deviation found in their respective testing measurements.

[0034] In several places throughout the application, guidance is provided through lists of examples, which examples can be used in various combinations. In each instance, the recited list serves only as a representative group and should not be interpreted as an exclusive list. It is to be understood that the particular examples, materials, amounts, and procedures are to be interpreted broadly in accordance with the scope and spirit of the invention as set forth herein.

[0035] All headings throughout are for the convenience of the reader and should not be used to limit the meaning of the text that follows the heading, unless so specified.

[0036] BRIEF DESCRIPTION OF THE FIGURES

[0037] FIGS. lA and lB. Building a pipeline for systematic mHAg discovery. FIG. lA is an overview of the analysis workflow for prediction of minor histocompatibility antigens (mHAgs). Starting from whole exome sequencing (WES) obtained from germline DNA of donor and recipient pairs, single-nucleotide polymorphisms (SNPs) altering the protein sequence and present only in the patient are identified. Through the application of tissue-specificity filters (see FIG. IB), the polymorphisms present in genes expressed in the tissues of interest are selected and all possible k-mers encompassing the SNPs are computed and then subjected to HLA class I binding prediction. Resulting candidate mHAgs can be used for downstream applications. FIG. IB presents the GvL filter to identify genes with preferential expression in acute myeloid leukemia (AML): a single-cell based molecular classifier (van Galen et al., Cell 176, 1265-1281 el 224 (2019) was applied to the Beat AML dataset (Tyner et al., Nature 562, 526-531 (2018)) to define distinct AML expression clusters (ECs). AML genes with evidence of expression at the RNA or protein level in the GTEx repository of human adult healthy tissues were excluded, to define a list of 259 candidate genes with preferential expression in AML (heatmap).

[0038] FIGS. 2A-2L. Predicted GvL mHAgs as targets for leukemia immunotherapy. FIG. 2A is a heatmap showing the 86 recurrent polymorphisms in the subgroup of GRFS patients (i.e., patients with long-term survival in the absence of both relapse and acute / chronic GvHD requiring systemic treatment). Right histograms - number of patients sharing the same polymorphism (color-coded based on the GvL filter of origin). Bottom histograms - number of recurrent GvL SNPs per patient. FIG. 2B shows the number of recurrent GvL SNPs for GRFS patients (GRFSyes, pink) versus all the other patients (GRFSno, grey); p < 0.0001, Mann Whitney test. FIG. 2C is the cumulative incidence (CI) of relapse stratifying the overall DFCL MRD cohort based on the median number of recurrent GvL mHAgs in the GRFS subgroup (‘GRFS mHAgs’); p = 0.009, Gray’s test. FIG. 2D is Hazard Ratios (HR) from multivariate Cox proportional hazards regression modeling of variables influencing post-transplant outcomes. Statistically significant p values are in bold. FIG. 2E is a Kaplan-Meier curve for the overall DFCLMRD cohort stratified based on the GRFS mHAg load below (grey) or above (pink) the median; p = 0.03 at 2 years. FIG. 2F shows the number of ‘GRFS mHAgs’ identified in the DFCLMRD cohort present in the HP-MRD cohort stratified based on the GRFS outcome (GRFSyes, purple) vs. all the other patients (GRFSno, grey); p = 0.009, Mann Whitney test. FIG. 2G is the cumulative incidence (CI) of relapse stratifying the overall HP-MRD cohort based on the median number of recurrent GRFS mHAgs. FIG. 2H shows an HLA class I immunopeptidome analysis for 5 commercial AML cell lines. For each cell line, from left to right, dots show: i the number of total predicted epitopes across the genes of the GvL filters; ii. the number of predicted epitopes with evidence of RNA expression with TPM >10; and iii. number of predicted epitopes with evidence of HLA class I presentation. FIG. 21 is the mass spectrum of a detected HLA-B4403 -presented GRFS mHAg derived from APOBEC3F in the SET2 cell line. Red, blue, and green peaks represent y-, b-, and internal ions, respectively, confirming the peptide sequence. Internal ions are labeled with their respective amino acid sequences. FIG. 2J is a schematic of the 1000 Genomes allo-HCT simulation: the 1000 Genomes repository was mined to identify individuals identical at HLA class I alleles (with tolerance for 1 mismatch) across different ethnicities (EUR: pink; EAS: yellow; SAS: green; AFR: teal; AMR: purple) to model population coverage for immunotherapeutic strategies exploiting GRFS mHAgs. DRP: donor-recipient pair. FIG. 2K, for each GRES SNP, the allelic frequency in each population is reported in the top graph, with the black bar indicating the allelic frequency in the overall simulation cohort. The blue shade represents the AF range with the highest probability of D-R mismatch. Stacked histograms on the bottom depict the number of informative DRPs, i.e., the D-R pairs where only the individual serving as ‘recipient’ has the indicated SNP together with an HLA restriction able to present the SNP-encompassing epitope. Histogram segments are color-coded based on the population of origin of the individual serving as ‘recipient.’ FIG. 2L is a simulation of population coverage for a GRFS-based cancer vaccine using a 5-, 10- or 15-SNP design from the pool of 86 GRFS SNPs.

[0039] FIG. 3. GRFS mHAgs. In FIG. 3, for each recurrent GvL SNP, the histogram bars denote the number of HLA alleles predicted to present an epitope encompassing the SNP.

[0040] FIG. 4. Characteristics of the DFCI-MR (n = 220) and HP-MRD (n = 58) cohorts. No statistically significant difference in the distribution of patient, donor or transplant characteristics was observed across the DFCI-MRD and the HP-MRD cohorts. CR: complete remission; PBSC: peripheral blood stem cells; BM: bone marrow. PTCy: posttransplant cyclophosphamide; n.a.: not available.

[0041] DETAILED DESCRIPTION

[0042] Minor histocompatibility antigens (mHAgs) composed of immunogenic peptides presented by HLA molecules can cause immune responses involved in graft-versus-host disease (GvHD) and graft-versus-leukemia (GvL) effects after allogeneic hematopoietic cell transplantation (alloHCT). The pathogenesis of GvHD, the most detrimental immune-related complication after allogeneic hematopoietic cell transplantation, is attributed to a donor-derived immune response directed against mHAgs either broadly expressed across tissues or expressed specifically in GvHD-affected tissues. With allogeneic hematopoietic cell transplantation between HLA-matched donors-recipient pairs, mHAgs present in recipient tissues are sensed as foreign by donor T cells and are expected to be highly immunogenic due to the lack of central tolerance against them. The role of minor histocompatibility antigens in mediating GvHD and GvL following allogeneic hematopoietic cell transplantation is recognized but not well- characterized. Despite the crucial role of mHAgs in GvL and GvHD reactions, it has not been possible thus far to consistently link patient-specific mHAg repertoires to clinical outcomes.

[0043] Provided herein is an analytic framework to systematically identify autosomal encoded mHAgs associated with GvL clinical outcomes. This analytic framework, shown schematically in FIGS. 1 A and IB and described in more detail in the examples section included herewith, is based on the integration of polymorphism detection by whole exome sequencing of germline DNA from donor-recipient (D-R) pairs together with organ-specific transcriptional- and proteome-level expression. Application of this analytic framework to a cohort of 220 HLA- matched allo-HSCT D-R pairs identified GvL targets for the prevention or treatment of posttransplant disease recurrence. Specifically, the analytic framework described herein identifies single nucleotide polymorphisms (SNPs) that produce amino acid coding differences between recipients and donors and are associated with GvL outcomes.

[0044] Graft-versus- leukemia (GvL) effect appears after allogeneic hematopoietic stem cell transplantation (HSCT). The graft contains donor T cells (T lymphocytes) that can be beneficial for the recipient by eliminating residual malignant cells. GvL might develop after recognizing tumor-specific or recipient-specific alloantigens. It can lead to remission or immune control of hematologic malignancies.

[0045] A single-nucleotide polymorphism (SNP) is a germline substitution of a single nucleotide at a specific position in the genome, with a frequency of more than 1% in the population. For example, a G nucleotide present at a specific location in a reference genome may be replaced by an A in a minority of individuals. The two possible nucleotide variations of this SNP - G or A - are called alleles. Around 90% of genome variations are limited to SNPs. SNPs have proven to be of great value for medical diagnostics. Several SNP databases are maintained, including, but not limited to, dbSNP a SNP database maintained by the National Center for Biotechnology Information (NCBI) (available on the worldwide web at ncbi.nlm.nih.gov / snp / ). As of June 8, 2015, dbSNP listed 149,735,377 SNPs for the human genome.

[0046] Graft-versus-host disease-free, relapse-free survival (GRFS) is a composite endpoint that measures survival free of relapse or significant morbidity after allogeneic hematopoietic stem cell transplantation (HSCT). Methods are provided for selecting an HLA-matched transplant donor wherein GvHD-free and relapse-free survival (GRFS) is improved in the recipient after receipt of donor tissue from the donor. Such methods include: determining the presence or absence of one or more SNPs from a panel of SNPs in the donor; determining the presence or absence of one or more SNPs from the panel of SNPs in the recipient; and identifying one or more mismatches between the recipient and the donor, wherein a mismatch comprises the presence in the recipient and the absence in the donor of a given SNP from the panel of SNPs; and selecting as the transplant donor the donor comprising one or more mismatches between the recipient and the donor; wherein GvHD-free and relapse-free survival (GRFS) is improved in the recipient after receipt of donor tissue from the donor; and wherein the panel of SNPs includes the TICRR p.R287C SNP; the CNTLN p.T695I SNP; the ZNF792 p.Rl 10Q SNP; the LY9 P.M240V SNP; the CTLA4 p.T17A SNP; the WDR49 p.L476P SNP; the HELB p.L191P SNP; the PRDM15 p.R88fs SNP; the PRTN3 p.V78I SNP; the C15orf40 p.C25R SNP; the MCPH1 p.A761V SNP; the MEFV p.D424E SNP; the CR1 p.T1408M SNP; the LILRB1 p.L68P SNP; the ARL11 p.C148R SNP; the ATXN3 p.V33M SNP; the EX01 p.E589K SNP; the LILRB4 p.Q361R SNP; the MCPHl p.R256I SNP; the MTERF p.A274T SNP; the P2RY13 p.T179M SNP; the PLD4 p.E27Q SNP; the PSTK p.G206R SNP; the RNASE3 p.T124R SNP; the SERPINB10 p.I41M SNP; the WDFY4 p.S1528P SNP; the CD300E p.G158R SNP; the DNAH14 p.L3088P SNP; the MMP8 p.T32I SNP; the PADI4 p.G55S SNP; the RAD18 P.R302Q SNP; the SPNS3 p.A203S SNP; the APOBEC3F p.A108S SNP; the Cl lorf82 p.R159S SNP; the C19orf59 p.I124V SNP; the CCDC171 p.K1069R SNP; the EMR2 p.A53V SNP; the EPX p.Q122H SNP; the GP1BA p.T161M SNP; the IL5RA p.I129V SNP; the PSMG4 p.T44P SNP; the WDFY4 p.T2525P SNP; the ZBED6 p.F560L SNP; the CNR2 p.Q63R SNP; the CD101 p.N225S SNP; the CEACAM4 p.H29D SNP; the TLR3 p.L135F SNP; the CLEC4C p.P35S SNP; the CLECL1 p.S52fs SNP; the TVP23C p.S199T SNP; the AK7 p.N389K SNP; the CD3G p.V131F SNP; the CD86 p.A97T SNP; the IL12RB1 p.Q214R SNP; the NLRP7 p.V319I SNP; the RHCE p.C16W SNP; the RHCE p.A210P SNP; the SLAMF1 p.Fl lL SNP; the SLFN12L p.Y383C SNP; the SLFN12L p.Y518S SNP; the TIGD6 p.Q327R SNP; the BATF3 p.VHI SNP; the CASC1 p.R33S SNP; the CD200R1 p.T99P SNP; the DCLRE1C p.H123R SNP; the N4BP2 p.SlOH SNP; the NLRP12 p.G39V SNP; the SIGLEC9 p.KlOOE SNP; the SPEF2 p.N71H SNP; the TLR7 p.Ql IL SNP; the TRPM6 p.T2I SNP; the CASP5 p.L192V SNP; the CASP5 p.T48A SNP; the CD1E p.Q104R SNP; the CD200R1L p.R92L SNP; the CSF2RA p.A17G SNP; the GTPBP10 p.L85F SNP; the KIAA1549 p.P436A SNP; the LILRA4 p.P27L SNP; the NAALADL2 p.G68S SNP; the RGPD2 p.S177L SNP; the RTP4 p.T131M SNP; the S100Z p.E23A SNP; the SIGLEC6 p.P246S SNP; the THEMIS p.I551V SNP; the TTC30A p.P279H SNP; and / or the ZNF286B p.P466S SNP.

[0047] In some aspects, the panel of SNPs includes, but is not limited to, any one, any two, any three, any four, any five, any six, any seven, any eight, any nine, any ten, about any fifteen, about any twenty, about any twenty-five, about any thirty, about any thirty-five, about any forty, about any forty-five, about any fifty, about any fifty-five, about any sixty, about any sixty -five, about any seventy, about and seventy -five, about any eighty, about any eight-five, or all eighty-seven of these SNPs, or any range thereof.

[0048] In some aspects of a method for selecting an HLA-matched transplant donor wherein GvHD-free and relapse-free survival (GRES) is improved in the recipient after receipt of donor tissue from the donor, identifying one or more mismatches between the recipient and the donor includes identifying about ten mismatches, about fifteen mismatches, about twenty mismatches, about twenty-five mismatches, about thirty mismatches, about thirty-five mismatches, about forty mismatches, about forty-five mismatches, about fifty mismatches, about fifty-five mismatches, about sixty mismatches, about sixty-five mismatches, about seventy mismatches, about seventy-five mismatches, about eighty mismatched, about eighty-five mismatches from the panel of SNPs, or any range thereof.

[0049] In some aspects of a method for selecting an HLA-matched transplant donor wherein GvHD-free and relapse-free survival (GRFS) is improved in the recipient after receipt of donor tissue from the donor, determining the presence or absence of one or more SNPs from a panel of SNPs in the donor and / or determining the presence or absence of one or more SNPs from the panel of SNPs in the recipient includes determining the presence or absence the APOBEC3F p.A108S SNP and / or the MCPH1 p.R256I SNP.

[0050] Methods are provided for inducing a GvL reaction in a HLA-matched transplant recipient receiving donor tissue from a donor. Such methods include: determining the presence or absence of one or more SNPs from the panel of SNPs for the donor; determining the presence or absence of SNPs from the panel of SNPs for the recipient; identifying one or more mismatches between the recipient and the donor, wherein a mismatch comprises the presence in the recipient and the absence in the donor of a given SNP from the panel of SNPs; and transplanting the recipient with donor tissue from the donor when there is one or more mismatches between the recipient and the donor; wherein the panel of SNPs comprises the TICRR p.R287C SNP; the CNTLN p.T695I SNP; the ZNF792 p.Rl 10Q SNP; the LY9 p.M240V SNP; the CTLA4 p.T17A SNP; the WDR49 p.L476P SNP; the HELB p.L191P SNP; the PRDM15 p.R88fs SNP; the PRTN3 p.V78I SNP; the C15orf40 p.C25R SNP; the MCPH1 p.A761V SNP; the MEFV p.D424E SNP; the CR1 p.T1408M SNP; the LILRBl p.L68P SNP; the ARL11 p.C148R SNP; the ATXN3 p.V33M SNP; the EXO1 p.E589K SNP; the LILRB4 p.Q361R SNP; the MCPH1 p.R256I SNP; the MTERF p.A274T SNP; the P2RY13 p.T179M SNP; the PLD4 p.E27Q SNP; the PSTK p.G206R SNP; the RNASE3 p.T124R SNP; the SERPINB10 p.I41M SNP; the WDFY4 p.S1528P SNP; the CD300E p.G158R SNP; the DNAH14 p.L3088P SNP; the MMP8 p.T32I SNP; the PADI4 p.G55S SNP; the RAD18 p.R302Q SNP; the SPNS3 p.A203S SNP; the APOBEC3F p.A108S SNP; the Cl lorf82 p.R159S SNP; the C19orf59 p.I124V SNP; the CCDC171 p.K1069R SNP; the EMR2 p.A53V SNP; the EPX p.Q122H SNP; the GP1BA p.T161M SNP; the IL5RA p.I129V SNP; the PSMG4 p.T44P SNP; the WDFY4 p.T2525P SNP; the ZBED6 p.F56OL SNP; the CNR2 p.Q63R SNP; the CD101 p.N225S SNP; the CEACAM4 p.H29D SNP; the TLR3 p.L135F SNP; the CLEC4C p.P35S SNP; the CLECL1 p.S52fs SNP; the TVP23C p.S199T SNP; the AK7 p.N389K SNP; the CD3G p.V131F SNP; the CD86 p.A97T SNP; the IL12RB1 p.Q214R SNP; the NLRP7 p.V3191 SNP; the RHCE p.C16W SNP; the RHCE p.A210P SNP; the SLAMF1 p.FUL SNP; the SLFN12L p.Y383C SNP; the SLFN12L p.Y518S SNP; the TIGD6 p.Q327R SNP; the BATF3 p.VHI SNP; the CASC1 p.R33S SNP; the CD200R1 p.T99P SNP; the DCLRE1C p.H123R SNP; the N4BP2 p.SlOH SNP; the NLRP12 p.G39V SNP; the SIGLEC9 p.KlOOE SNP; the SPEF2 p.N71H SNP; the TLR7 p.Ql IL SNP; the TRPM6 p.T2I SNP; the CASP5 p.L192V SNP; the CASP5 p.T48A SNP; the CD1E p.Q104R SNP; the CD200R1L p.R92L SNP; the CSF2RA p.A17G SNP; the GTPBP10 p.L85F SNP; the KIAA1549 p.P436A SNP; the LILRA4 p.P27L SNP; the NAALADL2 p.G68S SNP; the RGPD2 p.S177L SNP; the RTP4 p.T131M SNP; the S1OOZ p.E23A SNP; the SIGLEC6 p.P246S SNP; the THEMIS p.I551V SNP; the TTC30A p.P279H SNP; and / or the ZNF286B p.P466S SNP.

[0051] In some aspects, the panel of SNPs includes, but is not limited to, any one, any two, any three, any four, any five, any six, any seven, any eight, any nine, any ten, about any fifteen, about any twenty, about any twenty-five, about any thirty, about any thirty-five, about any forty, about any forty-five, about any fifty, about any fifty-five, about any sixty, about any sixty-five, about any seventy, about and seventy -five, about any eighty, about any eight-five, or all eighty-seven of these SNPs, or any range thereof. In some aspects of a method for inducing a GvL reaction in a HLA-matched transplant recipient receiving donor tissue from a donor, identifying one or more mismatches between the recipient and the donor includes identifying about ten mismatches, about fifteen mismatches, about twenty mismatches, about twenty-five mismatches, about thirty mismatches, about thirty- five mismatches, about forty mismatches, about forty-five mismatches, about fifty mismatches, about fifty -five mismatches, about sixty mismatches, about sixty-five mismatches, about seventy mismatches, about seventy-five mismatches, about eighty mismatched, about eighty-five mismatches from the panel of SNPs, or any range thereof.

[0052] In some aspects of a method for inducing a GvL reaction in a HLA-matched transplant recipient receiving donor tissue from a donor, determining the presence or absence of one or more SNPs from a panel of SNPs in the donor and / or determining the presence or absence of one or more SNPs from the panel of SNPs in the recipient includes determining the presence or absence the APOBEC3F p.A108S SNP and / or the MCPH1 p.R256I SNP.

[0053] In some aspects of the methods described herein, the donor and the recipient may be HLA-matched, wherein HLA stands for human leukocyte antigens. In some aspects of the methods, the HLA type of HLA-matched donor and recipient includes the HLA type HLA A0101, HLA A0201, HLA A0208, HLA A0301, HLA A0302, HLA Al 101, HLA A2301, HLA A2402, HLA A2403, HLA A2601, HLA A2902, HLA A3001, HLA A3101, HLA A3201, HLA A3301, HLA A6601, HLA A6801, HLA A6802, HLA A7401, HLA A8001, HLA B0702, HLA B0801, HLA B1302, HLA B1401, HLA B1402, HLA B1501, HLA B1503, HLA B1801, HLA B2705, HLA B3501, HLA B3502, HLA B3508, HLA B3701, HLA B3801, HLA B3901, HLA B4001, HLA B4006, HLA B4101, HLA B4102, HLA B4402, HLA B4403, HLA B4501, HLA B4901, HLA B5101, HLA B5201, HLA B5301, HLA B5701, HLA B5802, HLA C0102, HLA C0202, HLA C0303, HLA C0304, HLA C0401, HLA C0501, HLA C0602, HLA C0701, HLA C0702, HLA C0704, HLA C0802, HLA Cl 202, HLA Cl 203, HLA Cl 402, HLA Cl 502, HLA Cl 505, HLA Cl 601, HLA Cl 602, and / or HLA Cl 701.

[0054] For the methods provided herein, SNP information for a panel of SNPs may be obtained for a donor and / or a recipient by any of a variety of methods. As SNPs are allelic germline variations, SNPs information for a donor and / or a recipient may be determined from a genomic DNA sample. A panel of SNPs includes, but is not limited to, one or more of the one or more of the TOPBP 1 Interacting Checkpoint And Replication (TICRR) p.R287C SNP, the Centlein (CNTLN) p.T695I SNP, the zinc finger protein 292 (ZNF792) p.Rl 10Q SNP, the Lymphocyte Antigen 9 (LY9) SNP p.M240V, the cytotoxic T-lymphocyte associated protein 4 (CTLA4) p.T17A SNP, the WD Repeat Domain 49 (WDR49) p.L476P SNP, the DNA Helicase B (HELB) p.L191P SNP, the PR / SET Domain 15 (PRDM15) p.R88fs SNP, the proteinase 3 (PRTN3) p.V78I SNP, the Chromosome 15 Open Reading Frame 40 (C15orf40) p.C25R SNP, the microcephalin 1 (MCPH1) p.A761V SNP, the Mediterranean fever (MEFV) p.D424E SNP, the Complement C3b / C4b Receptor 1 (CR1) p.T1408M SNP, the Leukocyte Immunoglobulin Like Receptor Bl (LILRB1) pE68P SNP, the ADP Ribosylation Factor Like GTPase 11 (ARL11) P.C148R SNP, the Ataxin 3 (ATXN3) p.V33M SNP, the Exonuclease 1 (EXO1) p.E589K SNP, the Leukocyte Immunoglobulin Like Receptor B4 (LILRB4) p.Q361R SNP, the Microcephalin 1 (MCPH1 p.R256I SNP, the mitochondrial transcription termination factor (MTERF) p.A274T SNP, the Purinergic Receptor (P2Y13) SNP, the P2RY13 p.T179M SNP, the Phospholipase D Family Member 4 (PLD4) p.E27Q SNP, the Phosphoseryl-tRNA Kinase (PSTK) p.G206R) SNP, the Ribonuclease A Family Member 3 (RNASE3) p.T124R SNP, the Serpin Family B Member 10 (SERPINB10) p.I41M SNP, the WDFY Family Member 4 (WDFY4) p.S1528P SNP, the CD300e Molecule (CD300E) p.G158R SNP, the Dynein Axonemal Heavy Chain 14 (DNAH14) p.L3088P SNP, the Matrix Metallopeptidase 8 (MMP8) p.T32I SNP, the Peptidyl Arginine Deiminase 4 (PADI4) p.G55S SNP, the RAD18 E3 Ubiquitin Protein Ligase (RAD18) p.R302Q SNP, the SPNS Lysolipid Transporter 3, Sphingosine- 1 -Phosphate (SPNS3) p.A203S SNP, the apolipoprotein B mRNA editing enzyme catalytic subunit 3F (APOBEC3F) p.A108S SNP, the chromosome 11 open reading frame 82 (Cl lorf82) p.R159S SNP, the chromosome 19 open reading frame 59 (C19orf59) p.H24V SNP, the Coiled-Coil Domain Containing 171 (CCDC171) p.K1069R SNP, the EGF-like module-containing mucin-like hormone receptor-like 2 (EMR2) p.A53V SNP, the Eosinophil Peroxidase (EPX) p.Q122H SNP, the Glycoprotein lb Platelet Subunit Alpha (GP1BA) p.T161M SNP, the Interleukin 5 Receptor Subunit Alpha (IL5RA) p.I129V SNP, the Proteasome Assembly Chaperone 4 (PSMG4) p.T44P SNP, the WDFY Family Member 4 (WDFY4) p.T2525P SNP, the Zinc Finger BED-Type Containing 6 (ZBED6) P.F560L SNP, the Cannabinoid Receptor 2 (CNR2) p.Q63R SNP, the CD101 Molecule (CD101) p.N225S SNP, the CEA Cell Adhesion Molecule 4 (CEACAM4) p.H29D SNP, the Toll Like Receptor 3 (TLR3) p.L135F SNP, the C-Type Lectin Domain Family 4 Member C (CLEC4C) p.P35S SNP, the C-Type Lectin Like 1 (CLECL1) p.S52fs SNP, the Trans-Golgi Network Vesicle Protein 23 Homolog C (TVP23C) p.S199T SNP, the Adenylate Kinase 7 (AK7) p.N389K SNP, the CD3 Gamma Subunit Of T-Cell Receptor Complex (CD3G) p.V131F SNP, the CD86 Molecule (CD86) p.A97T SNP, the Interleukin 12 Receptor Subunit Beta 1 (IL12RB1) p.Q214R SNP, the NLR Family Pyrin Domain Containing 7 (NLRP7) p.V3191 SNP, the Rh Blood Group CcEe Antigens (RHCE) p.C16W SNP, the Rh Blood Group CcEe Antigens (RHCE) p.A210P SNP, the Signaling Lymphocytic Activation Molecule Family Member 1 (SLAMF1) p.Fl IL SNP, the Schlafen Family Member 12 Like (SLFN12L) p.Y383C SNP, the Schlafen Family Member 12 Like (SLFN12L) p.Y518S SNP, the Tigger Transposable Element Derived 6 (TIGD6) p.Q327R SNP, the Basic Leucine Zipper ATF-Like Transcription Factor 3 (BATF3) p.VHI SNP, the Cancer Susceptibility Candidate 1 (CASC1) p.R33S SNP, the CD200 Receptor 1 (CD200R1) p.T99P SNP, the DNA Cross-Link Repair 1C (DCLRE1C) p.H123R SNP, the NEDD4 Binding Protein 2 (N4BP2) p.SlOH SNP, the NLR Family Pyrin Domain Containing 12 (NLRP12) p.G39V SNP, the Sialic Acid Binding Ig Like Lectin 9 (SIGLEC9) p.KlOOE SNP, the Sperm Flagellar 2 (SPEF2) p.N71H SNP, the Toll Like Receptor 7 (TLR7) p.Ql IL SNP, the Transient Receptor Potential Cation Channel Subfamily M Member 6 (TRPM6) p.T2I SNP, the Caspase 5 (CASP5) p.L192V SNP, the Caspase 5 (CASP5) p.T48A SNP, the CDle Molecule (CD1E) p.Q104R SNP, the CD200 Receptor 1 Like (CD200R1L) p.R92L SNP, the Colony Stimulating Factor 2 Receptor Subunit Alpha (CSF2RA) p.A17G SNP, the GTP Binding Protein 10 (GTPBP10) p.L85F SNP, the KIAA1549 (KIAA1549) p.P436A SNP, the Leukocyte Immunoglobulin Like Receptor A4 (LILRA4) p.P27L SNP, the N- Acetylated Alpha-Linked Acidic Dipeptidase Like 2 (NAALADL2) p.G68S SNP, the RANBP2 Like And GRIP Domain Containing 2 (RGPD2) p.S177L SNP, the Receptor Transporter Protein 4 (RTP4) p.T131M SNP, the S100 Calcium Binding Protein Z (S100Z) p.E23A SNP, the Sialic Acid Binding Ig Like Lectin 6 (SIGLEC6) p.P246S SNP, the Thymocyte Selection Associated (THEMIS) p.I55 IV SNP, the Tetratricopeptide repeat domain 30A (TTC30A) p.P279H SNP, and / or the Zinc Finger Protein 286B (ZNF286B) p.P466S SNP.

[0055] In some aspects, the panel of SNPs includes, but is not limited to, any one, about any two, about any three, about any four, about any five, about any ten, about any fifteen, about any twenty, about any twenty-five, about any thirty, about any thirty-five, about any forty, about any forty-five, about any fifty, about any fifty-five, about any sixty, about any sixty-five, about any seventy, about and seventy-five, about any eighty, about any eight-five, or all eighty-seven of these SNPs, or any range thereof.

[0056] SNP information may be obtained, for example, by utilizing any of a variety of DNA sequencing approaches, including for example, targeted next generation sequencing (NGS), whole exome sequencing (WES), and whole genomic sequencing (WGS). The term “Next Generation Sequencing (NGS)” herein refers to sequencing methods that allow for massively parallel sequencing of clonally amplified molecules and of single nucleic acid molecules. Nonlimiting examples of NGS include sequencing-by-synthesis using reversible dye terminators, and sequencing-by-ligation. In some applications, SNP information may be obtained utilizing microarray-based SNP genotyping assays. In some applications, SNP information may be obtained by capillary electrophoresis, mass spectrometry, single-strand conformation polymorphism (SSCP), single base extension, electrochemical analysis, denaturating HPLC and gel electrophoresis, restriction fragment length polymorphism (RFLP), chip detection, various novel PCR or qPCR-based technologies, such as amplification refractory mutation system PCR (ARMS-PCR), and kompetitive allele-specific PCR (KASP), or hybridization analysis.

[0057] SNP information for a panel of SNPs for the donor and / or SNP information for a panel of SNPs for the recipient may have been previously determined and may be provided as a computer-readable medium having stored thereon computer-readable SNP information for the panel of SNPs.

[0058] As used herein, donor and / or recipient refers to a human donor and / or recipient as well as a non-human mammalian subject. Although the examples herein concern humans and the language is primarily directed to human concerns, the concept is applicable to any mammal, and is useful in the fields of veterinary medicine, animal sciences, research laboratories and such.

[0059] The methods provided herein may be used in association with transplantation of donor tissue for the treatment of a malignant or a nonmalignant hematologic disease with indication to allogeneic hematopoietic cell transplantation. Such disorders may include, but are not limited to, cancers such as, for example, acute myeloid leukemia (AML), myelodysplastic syndrome (MDS).

[0060] For the methods provided herein, any of a variety of donor tissues may be transplanted, including but not limited to, allogeneic hematopoietic stem cells. Such stem cells may be obtained from the bone marrow or the bloodstream. In some aspects, the donor tissue includes HLA-matched allogeneic hematopoietic stem cells.

[0061] Provided are compositions including one or more graft versus leukemia minor histocompatibility antigen (GvL mHAg)-specific antigenic epitopes, wherein a GvL mHAg- specific antigenic epitope consists of a peptide of about 8-11 amino acids in length encoded by a single nucleotide polymorphism (SNP) selected from the TICRR p.R287C SNP; the CNTLN p.T695I SNP; the ZNF792 p.Rl 10Q SNP; the LY9 p.M240V SNP; the CTLA4 p.T17A SNP; the WDR49 p.L476P SNP; the HELB p.L191P SNP; the PRDM15 p.R88fs SNP; the PRTN3 p.V78I SNP; the C15orf40 p.C25R SNP; the MCPH1 p.A761V SNP; the MEFV p.D424E SNP; the CR1 p.T1408M SNP; the LILRB1 p.L68P SNP; the ARL11 p.C148R SNP; the ATXN3 p.V33M SNP; the EX01 p.E589K SNP; the LILRB4 p.Q361R SNP; the MCPH1 p.R256I SNP; the MTERF p.A274T SNP; the P2RY13 p.T179M SNP; the PLD4 p.E27Q SNP; the PSTK p.G206R SNP; the RNASE3 p.T124R SNP; the SERPINB10 p.I41M SNP; the WDFY4 p.S1528P SNP; the CD300E p.G158R SNP; the DNAH14 p.L3088P SNP; the MMP8 p.T32I SNP; the PADI4 p.G55S SNP; the RAD18 p.R302Q SNP; the SPNS3 p.A203S SNP; the APOBEC3F p.A108S SNP; the Cl lorf 2 p.R159S SNP; the C19orf59 p.I124V SNP; the CCDC171 p.K1069R SNP; the EMR2 p.A53V SNP; the EPX p.Q122H SNP; the GP1BA p.T161M SNP; the IL5RA p.I129V SNP; the PSMG4 p.T44P SNP; the WDFY4 p.T2525P SNP; the ZBED6 p.F560L SNP; the CNR2 p.Q63R SNP; the CD101 p.N225S SNP; the CEACAM4 p.H29D SNP; the TLR3 p.L135F SNP; the CLEC4C p.P35S SNP; the CLECL1 p.S52fs SNP; the TVP23C p.S199T SNP; the AK7 p.N389K SNP; the CD3G p.V131F SNP; the CD86 p.A97T SNP; the IL12RB1 p.Q214R SNP; the NLRP7 p.V3191 SNP; the RHCE p.C16W SNP; the RHCE p.A210P SNP; the SLAMF1 p.Fl IL SNP; the SLFN12L p.Y383C SNP; the SLFN12L p.Y518S SNP; the TIGD6 p.Q327R SNP; the BATF3 p.VHI SNP; the CASC1 p.R33S SNP; the CD200R1 p.T99P SNP; the DCLRE1C p.H123R SNP; the N4BP2 p.SlOH SNP; the NLRP12 p.G39V SNP; the SIGLEC9 p.KlOOE SNP; the SPEF2 p.N71H SNP; the TLR7 p.Ql IL SNP; the TRPM6 p.T2I SNP; the CASP5 p.L192V SNP; the CASP5 p.T48A SNP; the CD1E p.Q104R SNP; the CD200R1L p.R92L SNP; the CSF2RA p.A17G SNP; the GTPBP10 p.L85F SNP; the KIAA1549 p.P436A SNP; the LILRA4 p.P27L SNP; the NAALADL2 p.G68S SNP; the RGPD2 p.S177L SNP; the RTP4 p.T131M SNP; the S100Z p.E23A SNP; the SIGLEC6 p.P246S SNP; the THEMIS p.I551 V SNP; the TTC30A p.P279H SNP; and / or the ZNF286B p.P466S SNP. In some aspects, the composition may include one, two, three, four, five, about ten, about fifteen, about twenty, about twenty-five, about thirty, about thirty-five, about forty, about forty- five, about fifty, about fifty-five, about sixty, about sixty-five, about seventy, about seventy-five, about eighty, or about eight-five of these GvL mHAg-specific antigenic epitopes, or any range thereof.

[0062] A composition may further include a pharmaceutically acceptable carrier. As used, a pharmaceutically acceptable carrier refers to one or more compatible solid or liquid fillers, diluents or encapsulating substances which are suitable for administration to a human or other vertebrate animal. Such a carrier may be pyrogen free. Such a composition may be used as an immunotherapeutic vaccine. Such a vaccine may further include an adjuvant.

[0063] Kits for use in selecting an HLA-matched transplant donor wherein GvHD-free and relapse-free survival (GRFS) is improved in the recipient after receipt of donor tissue from the donor are provided. A kit is any manufacture (for example, a package or container) including at least one reagent for specifically detecting one or more of the SNPs described herein. The kit may be promoted, distributed, or sold as a unit for performing the methods provided herein.

[0064] A kit may include a plurality of probes capable of binding to and / or identifying one or more of the TICRR p.R287C SNP; the CNTLN p.T695I SNP; the ZNF792 p.Rl 10Q SNP; the LY9 p.M240V SNP; the CTLA4 p.T17A SNP; the WDR49 p.L476P SNP; the HELB p.L191P SNP; the PRDM15 p.R88fs SNP; the PRTN3 p.V78I SNP; the C15orf40 p.C25R SNP; the MCPH1 p.A761V SNP; the MEFV p.D424E SNP; the CR1 p.T1408M SNP; the LILRB1 p.L68P SNP; the ARL11 p.C148R SNP; the ATXN3 p.V33M SNP; the EX01 p.E589K SNP; the LILRB4 p.Q361R SNP; the MCPH1 p.R256I SNP; the MTERF p.A274T SNP; the P2RY13 p.T179M SNP; the PLD4 p.E27Q SNP; the PSTK p.G206R SNP; the RNASE3 p.T124R SNP; the SERPINB10 p.I41M SNP; the WDFY4 p.S1528P SNP; the CD300E p.G158R SNP; the DNAH14 p.L3088P SNP; the MMP8 p.T32I SNP; the PADI4 p.G55S SNP; the RAD18 p.R302Q SNP; the SPNS3 p.A203S SNP; the APOBEC3F p.A108S SNP; the Cl lorf82 p.R159S SNP; the C19orf59 p.I124V SNP; the CCDC171 p.K1069R SNP; the EMR2 p.A53V SNP; the EPX p.Q122H SNP; the GP1BA p.T161M SNP; the IL5RA p.I129V SNP; the PSMG4 p.T44P SNP; the WDFY4 p.T2525P SNP; the ZBED6 p.F560L SNP; the CNR2 p.Q63R SNP; the CD101 p.N225S SNP; the CEACAM4 p.H29D SNP; the TLR3 p.L135F SNP; the CLEC4C p.P35S SNP; the CLECL1 p.S52fs SNP; the TVP23C p.S199T SNP; the AK7 p.N389K SNP; the CD3G p.V131F SNP; the CD86 p.A97T SNP; the IL12RB1 p.Q214R SNP; the NLRP7 p.V319I SNP; the RHCE p.C16W SNP; the RHCE p.A210P SNP; the SLAMF1 p.Fl lL SNP; the SLFN12L p.Y383C SNP; the SLFN12L p.Y518S SNP; the TIGD6 p.Q327R SNP; the BATF3 p.VHI SNP; the CASC1 p.R33S SNP; the CD200R1 p.T99P SNP; the DCLRE1C p.H123R SNP; the N4BP2 p.SlOH SNP; the NLRP12 p.G39V SNP; the SIGLEC9 p.KlOOE SNP; the SPEF2 p.N71H SNP; the TLR7 p.Ql IL SNP; the TRPM6 p.T2I SNP; the CASP5 p.L192V SNP; the CASP5 p.T48A SNP; the CD1E p.Q104R SNP; the CD200R1L p.R92L SNP; the CSF2RA p.A17G SNP; the GTPBP10 p.L85F SNP; the KIAA1549 p.P436A SNP; the LILRA4 p.P27L SNP; the NAALADL2 p.G68S SNP; the RGPD2 p.S177L SNP; the RTP4 p.T131M SNP; the S1OOZ p.E23A SNP; the SIGLEC6 p.P246S SNP; the THEMIS p.I551V SNP; the TTC30A p.P279H SNP; and / or the ZNF286B p.P466S SNP in a sample from the transplant donor and / or the transplant recipient. In some aspects, the kit may include probes capable of binding to and / or identifying any one, about any two, about any three, about any four, about any five, about any ten, about any fifteen, about any twenty, about any twenty-five, about any thirty, about any thirty-five, about any forty, about any forty-five, about any fifty, about any fifty-five, about any sixty, about any sixty-five, about any seventy, about and seventy-five, about any eighty, about any eight-five, or all eighty-seven of these SNPs, or any range thereof, in a sample from the transplant donor and / or the transplant recipient.

[0065] A kit may include a plurality of primers for selectively amplifying one or more of the TICRR p.R287C SNP; the CNTLN p.T695I SNP; the ZNF792 p.Rl 10Q SNP; the LY9 p.M240V SNP; the CTLA4 p.T17A SNP; the WDR49 p.L476P SNP; the HELB p.L191P SNP; the PRDM15 p.R88fs SNP; the PRTN3 p.V78I SNP; the C15orf40 p.C25R SNP; the MCPH1 p.A761 V SNP; the MEFV p.D424E SNP; the CR1 p.T1408M SNP; the LILRB1 p.L68P SNP; the ARL11 p.C148R SNP; the ATXN3 p.V33M SNP; the EX01 p.E589K SNP; the LILRB4 p.Q361R SNP; the MCPHl p.R256I SNP; the MTERF p.A274T SNP; the P2RY13 p.T179M SNP; the PLD4 p.E27Q SNP; the PSTK p.G206R SNP; the RNASE3 p.T124R SNP; the SERPINB10 p.I41M SNP; the WDFY4 p.S1528P SNP; the CD300E p.G158R SNP; the DNAH14 p.L3088P SNP; the MMP8 p.T32I SNP; the PADI4 p.G55S SNP; the RAD18 p.R302Q SNP; the SPNS3 p.A203S SNP; the APOBEC3F p.A108S SNP; the Cl lorf82 p.R159S SNP; the C19orf59 p.I124V SNP; the CCDC171 p.K1069R SNP; the EMR2 p.A53V SNP; the EPX p.Q122H SNP; the GP1BA p.T161M SNP; the IL5RA p.I129V SNP; the PSMG4 p.T44P SNP; the WDFY4 p.T2525P SNP; the ZBED6 p.F560L SNP; the CNR2 p.Q63R SNP; the CD101 p.N225S SNP; the CEACAM4 p.H29D SNP; the TLR3 p.L135F SNP; the CLEC4C p.P35S SNP; the CLECL1 p.S52fs SNP; the TVP23C p.S199T SNP; the AK7 p.N389K SNP; the CD3G p.V131F SNP; the CD86 p.A97T SNP; the IL12RB1 p.Q214R SNP; the NLRP7 p.V319I SNP; the RHCE p.C16W SNP; the RHCE p.A210P SNP; the SLAMF1 p.Fl lL SNP; the SLFN12L p.Y383C SNP; the SLFN12L p.Y518S SNP; the TIGD6 p.Q327R SNP; the BATF3 p.VHI SNP; the CASC1 p.R33S SNP; the CD200R1 p.T99P SNP; the DCLRE1C p.H123R SNP; the N4BP2 p.SlOH SNP; the NLRP12 p.G39V SNP; the SIGLEC9 p.KlOOE SNP; the SPEF2 p.N71H SNP; the TLR7 p.Ql IL SNP; the TRPM6 p.T2I SNP; the CASP5 p.L192V SNP; the CASP5 p.T48A SNP; the CD1E p.Q104R SNP; the CD200R1L p.R92L SNP; the CSF2RA p.A17G SNP; the GTPBP10 p.L85F SNP; the KIAA1549 p.P436A SNP; the LILRA4 p.P27L SNP; the NAALADL2 p.G68S SNP; the RGPD2 p.S177L SNP; the RTP4 p.T131M SNP; the S1OOZ p.E23A SNP; the SIGLEC6 p.P246S SNP; the THEMIS p.I551V SNP; the TTC30A p.P279H SNP; and / or the ZNF286B p.P466S SNP in a sample from the transplant donor and / or the transplant recipient. In some aspects, the kit may include a plurality of primers for selectively amplifying any one, about any two, about any three, about any four, about any five, about any ten, about any fifteen, about any twenty, about any twenty-five, about any thirty, about any thirty-five, about any forty, about any forty-five, about any fifty, about any fifty-five, about any sixty, about any sixty-five, about any seventy, about and seventy-five, about any eighty, about any eight-five, or all eighty-seven of these SNPs, or any range thereof, in a sample from the transplant donor and / or the transplant recipient.

[0066] The present invention is illustrated by the following examples. It is to be understood that the particular examples, materials, amounts, and procedures are to be interpreted broadly in accordance with the scope and spirit of the invention as set forth herein.

[0067] EXAMPLES

[0068] Example 1

[0069] Systematic identification of minor histocompatibility antigens informs outcomes after allogeneic stem cell transplantation

[0070] This example describes an analytic framework to systematically identify autosomal and Y-encoded mHAgs, including their detection on HLA class I ligandomes and functionally verifying their immunogenicity, based on the integration of polymorphism detection by whole exome sequencing of germline DNA from D-R pairs together with organ-specific transcriptional- and proteome-level expression. Application of this pipeline to a cohort of 220 HLA-matched allo-HCT D-R pairs of the DFCLMRD cohort (FIG. 4) uncovered novel associations with GvHD outcomes and defined promising GvL targets, confirmed in the HP-MRD validation cohort of 58 D-R pairs (FIG. 4), for the prevention or treatment of post-transplant disease recurrence.

[0071] Genomic analyses to quantify neoantigens arising from somatic tumor mutations have been tremendously impactful towards advancing cancer immunology and immunotherapy and implementing personalized immune-based treatments in clinical practice. A widely used individualized form of immunotherapy that is potentially curative for many blood disorders is allogeneic hematopoietic stem cell transplantation (allo-HCT), wherein a suitable stem cell donor is selected for each patient based on HLA matching. In this scenario, the driving principle underlying response is alloreactivity, primarily originating from immune responses against minor histocompatibility antigens (mHAgs), HLA-binding peptides derived from polymorphic protein sequences differing between donor and recipient (D-R) pairs. Like tumor neoantigens, mHAgs are sensed as foreign by donor T cells and are expected to be highly immunogenic due to the lack of central tolerance against them. However, mHAgs are inherited as germline traits encoded by polymorphic genes rather than presenting as somatic events, hence they are not tumor-specific antigens per se. The pathogenesis of graft-versus-host disease (GvHD), the most detrimental immune-related complication after allo-HCT, can be thus attributed to a donor-derived immune response directed against mHAgs either broadly expressed across tissues or expressed specifically in GvHD-affected tissues. Conversely, the curative graft-versus-leukemia (GvL) effect can be conceptualized as the result of productive donor immune responses against mHAgs expressed on hematopoietic cells, including, but not limited to epitopes with hematopoietic tissue restriction. While more than 50,000 allogeneic transplants are performed annually worldwide - with numbers still rising - the beneficial effect of allo-HCT is too often hampered by disease relapse or complicated by GvHD, which together account for >50% of post-transplant mortality. Hence, identification of molecular determinants to aid in predicting transplant outcomes is urgently needed.

[0072] Currently, only D-R HLA matching and the activity of GvHD prophylaxis strategies are available to help clinicians in this challenge. Post-transplant outcomes are likely impacted by genome-wide mHAg load, delineated in an organ- and malignancy-specific fashion. While >100 individual mHAgs have been identified thus far worldwide, only few have been linked to increased risk of GvHD, and such associations have been only inconsistently validated. More recently, the use of high-throughput sequencing technologies to catalogue the mHAg repertoire has been reported, but only one study linked mHAg burden to 1-year GvHD mortality in a large yet non-contemporary transplant cohort. Certainly, large-scale sequencing capabilities, coupled with the availability of robust HLA class I epitope prediction models, now offer an unprecedented opportunity to delineate the mHAg repertoire of allo-transplanted patients in a personalized fashion which can then be linked to clinical outcomes.

[0073] Results

[0074] Building a pipeline for systematic mHAg discovery

[0075] To identify single nucleotide germline variants (both autosomal and Y chromosome- encoded) present exclusively in the recipient and resulting in nonsynonymous alterations in protein-coding regions, whole-exome sequencing (WES) data from paired D-R DNA was analyzed. An analytic pipeline was devised that further incorporated: (i) filtering for variants in genes of interest, either expressed in GvHD-targeted tissues (skin, liver, GI, lung, oral mucosa and lacrimal gland); or in GvL genes, i.e. genes preferentially expressed in malignant (and non- malignant) hematopoietic cells, but not in non-hematopoietic tissues, and (ii) predicting variantcontaining peptide 8-1 Imers (k-mers) binding to patient-specific HLA class I alleles using the tool HLAthena (FIG. 1A).

[0076] A critical component of the pipeline was building a reliable expression atlas for acute or chronic GvHD-targeted tissues (‘GvHD filter’). To capture less frequent albeit biologically relevant cell types consistently underestimated in bulk RNA expression profiles, multiple external single-cell datasets of healthy human skin (Reynolds et al., 2021, Science,' 371:6527), liver (Aizarani et al., 2019, Nature; 572,199-204; and MacParland et al., 2018, Nat Cormnun; 9:4383), lung (Vieira Braga et al., 2019, Nat Med, 25: 1153-1163; and Laughney et al., 2020, Nat Med, 26:259-269), GI (Parikh et al., 2019, Nature,' 567:49-55; and Wang et al., 2020, J Exp Med, 217(2):e20191130), oral mucosa (Williams et al., 2021, Cell, 184:4090-4104.e4015), and lacrimal gland (Bannier-Helaouet et al., 2021, Cell Stem Cell,' 28: 1221-1232. el227) was evaluated. For each tissue, the corresponding single-cell data sets were merged and then clustered and annotated tissue-resident cell types, for which specific expressed genes were then identified. Using a cut-off of 5 counts per million for positive expression (based on the expression levels of lineage-defining markers, such as MLANA, SFTB and ALB), 13,512 genes expressed in >1 GvHD target tissue were identified.

[0077] Conversely, to predict candidate mHAgs with an acceptable safety profile if targeted therapeutically, a set of genes with exclusive or near-exclusive expression within the hematopoietic compartment (‘GvL filter’) was identified. The focus was on acute myeloid leukemia (AML) and myelodysplastic syndromes (MDS), as they represent the most common indications for allo-HSCT in (FIG. IB). To capture the transcriptional heterogeneity of malignant myeloid cells, a single-cell based classifier was applied to define genes expressed by leukemic cells in the Beat AML cohort (Tyner et al., 2018, Nature,' 562:526-531), and then removed those expressed in non-hemopoietic tissues, per the GTEx database (both RNA (Consortium, The Genotype-Tissue Expression (GTEx) project, 2013, Nat Genet, 45:580-585) and / or protein (Jiang et al., 2020, Cell; 183:269-283 e219)), applying a gender-specific tolerance for reproductive organs based on the inputted patient gender. Similarly, a broader ‘Hematopoietic filter’ was built by incorporating gene expression profiles from 18 mature hematopoietic lineages and hematopoietic stem and precursor cells.

[0078] Through this stringent process, 259 genes with preferential expression in AML (and 615 broadly expressed in the hematopoietic compartment) were identified. Notably, these genes were distributed: (i) across all chromosomes, thereby providing targetable options even in the presence of chromosomal aberrations, that frequently occur in myeloid malignancies; and (ii) across distinct biological pathways and cellular compartments. The pipeline was further tuned to incorporate RNA-Seq data from leukemic blasts, if available, to confirm patient-specific expression.

[0079] In the -25% of allo-HCT cases consisting of male recipients paired with female donors (F— >M), chromosome Y-encoded genes represent an additional source of potentially immunogenic epitopes, since the female immune system lacks central tolerance to these. To systematically evaluate Y-encoded mHAgs, genes from the 78 harbored in the male-specific region (MSY) of the Y chromosome with expression >1 TPM in >1 adult GvHD target tissue per GTEx were selected, generated corresponding hi silica proteomes, and filtered out all homologous peptides (100% BLAST identity) arising from other chromosomal locations (primarily gene paralogues). HLA class I binding prediction of the remaining set of unique k- mers resulted in a median of 62 (range: 24 - 107) predicted epitopes per allele. The number of predicted epitopes per MSY gene varied greatly across the different HLA alleles, when grouped based on their peptide binding motifs.

[0080] The ability of the pipeline to predict a set of known mHAgs (12 autosomal (Griffioen, et al., 2016, Front Immunol, 7: 1002) and 9 Y-encoded (Feng et al., 2008, Trends Immunol,' 29:624-632)) was confirmed in a training dataset of 19 D-R pairs with available WES data (Bachireddy et al., 2021, Cell Rep; 37: 109992; and Bachireddy et al., 2020, Sci Trans! Med; 12: 12(561):eabb7661). The pipeline verified that: (i) genes harboring the causative SNPs were included in the GvHD and Y filters, respectively; (ii) the SNPs were detected in various combinations among the D-R pairs in accordance with their reported allelic frequencies (Sherry et al., 2001, Nucleic Acids Res; 29:308-311); (iii) in D-R pairs with correct SNP configuration (i.e. Dneg, Rpos), peptides corresponding to the mHAg epitopes were part of in silico generated -mers and iv) mHAg-corresponding peptides were predicted as HLA binders. Overall, the pipeline predicted 18 of 21 known mHAgs. Detection failures were due to the epitope originating from an alternative open reading frame (not captured by our pipeline, which focuses on mHAgs deriving from SNPs, indels and frameshifts) or to HLA prediction rank above the threshold of positivity.

[0081] Antigenicity and immunogenicity of predicted mHAgs

[0082] To ascertain whether predictions were supported by evidence of HLA presentation, a previously generated HLA class I ligandome dataset of 60 single-HLA class I expressing B721 .221 cell lines that encompassed all peptide-binding motifs identified by Sarkizova et al. (Sarkizova et al., 2020, Nat Biotechnol 38: 199-209) was evaluated. From whole-genome sequencing of parental B721.221 cells, exonic non-synonymous SNPs present in the B721.221 cells (surrogate ‘HSCT recipient’) that were absent in the reference genome (surrogate ‘donor’) were identified. Epitopes predicted from these sites were searched against the immunopeptidomes from these monoallelic cell lines, and 517 were confirmed to be presented across all 60 HLA alleles (median of 8 [range: 1-20] MS-supported peptides per allele). To evaluate Y mHAg antigenicity, male immunopeptidomes were generated and interrogated from 11 male cell lines and from the IEDB database for epitopes predicted from the 9 MSY genes (since B721.221 cells are of female origin. Indeed, 81 predicted Y mHAgs were presented across 37 HLA alleles.

[0083] To estimate the fraction of predicted binders that were immunogenic, Y-encoded mHAgs in the setting of F— >M transplants were analyzed, since SNP genotyping was not required for functional validation, and this facilitated ready and unbiased testing of all predicted epitopes for any given HLA allele. Peripheral blood mononuclear cells (PBMCs) were isolated from 3 healthy female donors carrying 6 common class I HLA alleles (HLA-A0201, -A0101, -B0702, - Bl 801, -C0501, and -C0702), and challenged purified T cells with pools of synthetic peptides encompassing all 410 predicted binders (HLAthena rank <0.5, n=53 for HLA-A0201; n=97 for HLA-A0101; n=47 for HLA-B0702; n=68 for HLA-B 1801; n=94 for HLA-C0501; and n=51 for HLA-C0702). Peptides were pulsed on CD3-depleted PBMCs, and cocultured with autologous female-derived T cells. Cells were similarly restimulated after 7 days; on day 14, they were screened for antigen specificity by dextramer staining.

[0084] Of 410 peptides tested, 110 (14, 21 and 75 HLA-A, -B and -C restricted, respectively) elicited antigen-specific T cell responses, with a preponderance of HLA-C-restricted epitopes. For 9 such Y mHAgs, antigen-specific recognition by CD 137 upregulation and IFNv production in response to the cognate epitope presented on autologous immortalized B cell lines was confirmed. To investigate the unexpectedly high number of immunogenic HLA-C-restricted epitopes, epitope hydrophobicity, a property associated with immunogenicity, was evaluated. Observed inter-allele differences were mainly driven by the richness of hydrophobic residues in the allele-specific binding motifs, with HLA-A0201 having the highest frequency of hydrophobic predicted binders (Kyte-Doolittle hydrophobicity score. Comparison between peptides with or without experimental evidence of immunogenicity across HLA alleles revealed immunogenicity to correlate with higher hydrophobicity scores only for HLA-A0101 and HLA- C0501. Thus, hydrophobicity potentially contributed but was not the sole driver of HLA-C epitope immunogenicity. Additional contributing factors were considered, including: (i) the in vitro stimulation conditions potentially favoring HLA-C restricted responses, as antigen- presenting cells express higher cell surface levels of HLA-C than other cell types; and (ii) a less stringent central tolerance for HLA-C epitopes, since cortical and medullary thymic epithelial cells tend to express less HLA-C than HLA-A and -B. Nevertheless, by longitudinally tracking Y-encoded mHAg-specific T cells ex vivo in a patient undergoing a F^M transplant and experiencing severe chronic GvHD, a sizeable population was detected (accounting for up to 3% of the circulating CD8+ cell pool) of T cells specific for HLA-C0501 -restricted epitopes with in vitro evidence of immunogenicity, thereby supporting the in vivo impact of HLA-C-restricted mHAgs.

[0085] Predicted GvL mHAgs as targets for anti-leukemia immunotherapy

[0086] To discover mHAgs with optimal GvL potential for therapeutic targeting, the subgroup of 45 patients in the cohort with long-term survival in the absence of both relapse and GvHD requiring systemic treatment (i.e. GvHD-free and relapse-free survival (GRFS) was analyzed. For these patients experiencing purely GvL, the individual repertoire of predicted GvL mHAgs was analyzed, and 87 SNPs recurring in >5 GRFS were found patients (FIG. 2A), that gave rise to predicted epitopes across multiple HLA restrictions (FIG. 3). Notably, these GvL SNPs were enriched in the subgroup of GRFS patients versus those without GRFS (p<0.0001, FIG. 2B), suggesting that their overrepresentation was not merely dictated by high allelic frequency in the overall cohort. Using the median number of recurring GvL mHAgs in the GRFS subgroup (GRFS mHAgs) as a cutoff to stratify the entire study cohort, we found that a higher GRFS mHAg load was associated with a protective effect against relapse in both univariate and multivariable analysis (FIGS. 2C and 2D) and conferred a benefit in 2-year overall survival (p = 0.03, FIG. 2E).

[0087] Analysis of an external cohort of 58 MRD allo-HCT D-R pairs (‘HP-MRD cohort’, FIG. 4) confirmed that GRFS mHAgs co-occurred at a higher frequency in patients not experiencing relapse nor GvHD (FIG. 2F) and were protective against relapse (FIG. 2G). As further validation, HLA class I immunopeptidome analysis of 5 AML cell lines revealed evidence of presentation for 10 epitopes predicted from genes included in the overall GvL filter (FIG. 2H), two of which were also part of the GRFS mHAg set, i.e., APOBEC3F p.A108S and MCPH1 p.R256I (FIG. 21).

[0088] Given the limited size and ethnic diversity of the discovery cohort (composed mainly of patients with European ancestry, genomic data from the 1000 Genomes project was used (The 1000 Genomes Project Consortium, 2015, “A global reference for human genetic variation. Nature, 526:68-74) to estimate the feasibility of targeting the GRFS mHAg set in a broader population via in silico modeling of allo-HSCT. From 2,504 individuals, those with identical HLA class I alleles (with tolerance for 1 mismatch), mirroring a typical unrelated donor search in the National Marrow Donor Program (NMDP) registry, were identified. 844 individuals were found who could be matched to generate 2270 D-R pairs across 5 populations of disparate ancestry (Africa [AFR], East Asia [EAS], Europe [EUR], South Asia [SAS], and Americas [AMR]; FIG. 2J). All 87 GvL SNPs were detected in the 844 individuals, albeit with differences in their relative representation across the distinct ancestry backgrounds. The only exceptions were GTPBP10 p.L85F absent in AFR and TLR7 p.Ql IL absent in EAS (FIG. 2K (top)O. By evaluating the number of informative D-R pairs per SNP, defined as those where only the individual serving as ‘recipient’ was positive for the SNP (FIG. 2K (bottom)), the vast majority of GRFS SNPs were represented across the different ancestry backgrounds.

[0089] To gauge the feasibility of generating personalized mHAg-specific immunotherapy (i.e. cancer vaccines, adoptive cellular therapy) based on the GRFS mHAg set, it was estimated that a 10-SNP design (i.e., the number of GRFS SNPs used for the outcome correlative analyses in our discovery cohort, FIGS. 2C and 2D) would be possible for -90% of the 1000 Genomes simulated cohort (EUR: 99%, EAS: 72%, SAS: 91%, AFR: 69%, and AMR: 74%, FIG. 21). Through a similar process, population coverage simulating a T cell-based approach targeting >1 epitope from the GRFS mHAg set was calculated. To this end, 18 HLA alleles we identified that could ensure -99% coverage across diverse ethnic backgrounds. For each HLA allele, the 3 most frequently predicted (and with highest agretopicity) epitopes from the GRFS SNP set were selected defining a pool of 54 epitopes. Thus, >1 epitope could be potentially targeted for 81% of the simulated D-R pairs (EUR: 91%, EAS: 78%, SAS: 71%, AFR: 62%, and AMR:85%). HLA alleles capable of binding the peptides originating originating from the 87 GRFS SNPs in the MRD cohort include HLA A0101, HLA A0201, HLA A0208, HLA A0301, HLA A0302, HLA Al 101, HLA A2301, HLA A2402, HLA A2403, HLA A2601, HLA A2902, HLA A3001, HLA A3101, HLA A3201, HLA A3301, HLA A6601, HLA A6801, HLA A6802, HLA A7401, HLA A8001, HLA B0702, HLA B0801, HLA Bl 302, HLA Bl 401, HLA Bl 402, HLA B1501, HLA B 1503, HLA B1801, HLA B2705, HLA B3501, HLA B3502, HLA B3508, HLA B3701, HLA B3801, HLA B3901, HLA B4001, HLA B4006, HLA B4101, HLA B4102, HLA B4402, HLA B4403, HLA B4501, HLA B4901, HLA B5101, HLA B5201, HLA B5301, HLA B5701, HLA B5802, HLA C0102, HLA C0202, HLA C0303, HLA C0304, HLA C0401, HLA C0501, HLA C0602, HLA C0701, HLA C0702, HLA C0704, HLA C0802, HLA C1202, HLA C1203, HLA C1402, HLA C1502, HLA C1505, HLA C1601, HLA C1602, and HLA C1701.

[0090] Discussion

[0091] The analytic pipeline described herein overcomes the limitations of previous efforts to delineate the patient-specific mHAg repertoires due to the incorporation of multiple novel features. First, the pipeline provides genome-wide assessment of the entire mHAg landscape, as it uses WES as data input for mHAg prediction (rather than SNP genotyping, utilized in most prior studies). Second, mHAgs are more stringently filtered to be incorporated within the GvHD or GvL set than any prior study (Lansford et al., 2018, Blood Adv, 2:2052-2062; and Olsen et al., 2023, Blood Adv, 7: 1635-1649) on the basis of expression on GvHD targeted tissues or on malignant myeloid cells. This was achieved through: (i) intensive incorporation of information from high resolution single-cell RNA-seq data (analyzing 354,606 individual cells across 9 datasets covering 6 GvHD-targeted organs) to curate an expression atlas of all resident cell types present in organs frequently targeted by acute and chronic GvHD; and (ii) usage of RNA and protein GTEx data from >15,000 samples across 49 non-hematopoietic organs to selected genes with preferential expression in malignant and non-malignant hematopoietic cells and limited - if not absent - representation in healthy tissues. Third, the pipeline was designed to predict not only autosomal but also Y-encoded mHAgs. Fourth, it substantially reduces false positive predictions by eliminating all possible redundant k-mers. These are peptide sequences that, in addition to arising from the discordant SNP, are also generated from other sites in donor or patient exomes. This was accomplished through extensive pruning via sequential BLAST searches against the patient- and donor-specific proteomes reconstructed in silico from WES; indeed, it was found that -40% of SNP-encompassing k-mers were redundant. As a result of this pruning step, the unbiased screening of Y-encoded mHAgs predicted a higher percentage of epitopes with detectable immunogenicity than similar screenings performed for cancer neoantigens.

[0092] The robust pipeline described in this example provided numerous novel insights with several clear translational implications through its application to a cohort of 220 patients transplanted from HLA-matched related donors and identifying promising prime candidate targets for post-transplant immunotherapy by defining GvL mHAgs that were significantly recurrent and had a protective effect against relapse in a subgroup of patients who had clinical evidence of a pure GvL effect. In silico modelling via analysis of the 1000 Genomes project revealed the feasibility of broad coverage across diverse ancestries with a limited set of 87 SNPs, paving the way for generating ‘off the shelf GvL mHAg-targeting vaccine or adoptive T cell therapeutics. While the analysis focused on AML / MDS, the scalable design of the GvL filter enables incorporating expression profiles from other hematological malignancies with indication to allo-HCT but only a paucity of immunotherapy targets (such as T-ALL or PTCLs). Systematic identification of GvL mHAgs may lead to their effective use to prevent or treat posttransplant relapse in an analogous fashion as has been tested for tumor neoantigens.

[0093] The robustness and modular design of the pipeline facilitates the high throughput analysis of additional large-scale patient datasets, from which we can anticipate gaining greater sensitivity to further refine the algorithm for prognostication and prediction of response to HCT in future studies. Such datasets could include the analysis of ethnically diverse allo-HSCT study populations to expand the list of actionable GvL mHAgs to improve population coverage - especially for individuals of Asian or African ancestry. Extension studies could also evaluate other transplant modalities, such as different donor types (i.e., unrelated donors, versus our current study of related donors) and GvHD prophylaxis regimens, such as post-transplant cyclophosphamide, that is expected to substantially impact the mHAg-specific T cell repertoire by in vivo purging of alloreactive T cells. Additional studies on larger cohorts would furthermore aid in providing increased power to potentially pinpoint other organ-specific driver mHAgs in settings beyond lung and liver GvHD. In summary, this example demonstrates the potential applications of personalized mHAg prediction in allo-HCT. HCT represents a model setting of precision medicine: one individual donor is selected for one individual recipient based on genetic findings, and optimal donor matching to modulate the GvHD / GvL effects has been an inherent point of debate since its inception.

[0094] Methods

[0095] Patient samples

[0096] Peripheral blood mononuclear cells (PBMCs) were collected from allo-HCT patients and donors following written informed consent through sample collection protocols approved by the Dana-Farber and Hospital de la Princesa Institutional Review Board in accordance with the principles of the Declaration of Helsinki. All samples were processed by Ficoll-Paque PLUS (Fisher Scientific) density gradient centrifugation and then cryopreserved with FBS / 10% DMSO and stored in liquid nitrogen until time of analysis.

[0097] For the DFCI-AML-MRD cohort, matched donor and recipient DNA was analyzed, as well as PBMCs in some cases, collected from all adult patients who underwent first T-replete allo-HSCT from a matched related donor (MRD) between January 1st, 2013 and December 31st, 2020. For the HP -MRD cohort, we analyzed matched donor and recipient DNA collected from 58 adult patients who underwent first T-replete MRD allo-HCT for myeloid disease (AML / MDS) between January 1, 2011, and April 30, 2021, at Hospital de la Princesa, Madrid. Patients were considered in complete remission if disease activity could not be documented by BM evaluation. All other patients not falling within this definition were categorized as having active disease. Minimal residual disease was not considered for the definition of disease status at transplant, as the information was not available for all the study patients. Additionally, patients were stratified by disease-specific prognostic risk scores: ELN 2017 (Dohner et al., 2017, Blood, 129:424-447) and R-IPSS (Greenberg et al., 2012, Blood, 120:2454-2465) for AML and MDS, respectively. For multivariate analysis, the ELN and R-IPSS scores were consolidated in a single variable, termed ‘overall risk score’ and comprising 3 categories: i) favorable, including ELN favorable and R-IPSS very low / low; ii) intermediate, encompassing ELN intermediate and R- IPSS intermediate; and iii) adverse, including ELN adverse and R-IPSS high / very high. Clinical diagnosis and grading of acute GvHD were annotated according to consensus criteria (Przepiorka et al., 1995, Bone Marrow Transplant, 15:825-828; and Glucksberg et al., 1974, Transplantation, 18:295-304). Chronic GvHD diagnosis and grading were based on the National Institutes of Health consensus criteria (Pavletic et al., 2010, Biol Blood Marrow Transplant, 16:871-890).

[0098] Exome sequencing, processing, and analysis

[0099] Library preparation and sequencing. A total of 556 DNA samples originating from 278 D-R pairs were processed and sequenced by whole-exome sequencing (>85% target base coverage at >20x depth; Genomics Platform, Broad Institute). For all D-R pairs, genomic DNA (250 ng) was provided by the HLA typing Lab at the Brigham and Women Hospital (Boston, MA). Library construction from double-stranded DNA was performed using the KAPA Library Prep kit (KAPA Hyper Prep with Library Amplification Primer Mix, product KK8504), with palindromic forked adapters from Integrated DNA Technologies. Libraries were then amplified by 10 cycles of PCRs, and enzymatic clean-ups were performed using AMPure XP beads (Beckman Coulter). Following the library construction, library quantification was performed using a standardized PicoGreen dsDNA Quantitation Reagent (Invitrogen) assay. All library construction, hybridization and capture steps were automated on the Agilent Bravo liquid handling system. Hybridization and capture were then performed using the XGen hybridization and wash kit (IDT) following the manufacturer’s recommendations on the Hamilton Starlet. After post-capture enrichment, library pools were quantified using a qPCR kit from KAPA Biosystem (automated assay on the Agilent Bravo). Based on qPCR quantification, pools were normalized using a Hamilton Starlet and sequenced on NovaSeq S4 platform using the NovaSeq 6000 Xp workflow with a paired-end reads of 2x15 Ibp. Quality control identification check was performed using fingerprint genotyping of 95 common SNPs by Fluidigm Genotyping.

[0100] Alignment and quality control. All DNA sequence data were processed through Broad Institute pipelines. Outputs from Illumina software were processed by the Picard data- processing pipeline to yield BAM / CRAM files. Raw sequence data were aligned to the human genome hgl9 genome assembly (v.b37, using BWA-MEM [v.0.7.15-rl 140]) provided by the Picard and Genome Analysis Toolkit (GATK) developed at the Broad Institute (Andreatta et al., 2019, Proteomics,' 19 :e 1800357), a process that involves marking duplicate reads, recalibrating base qualities, and realigning around indels. Single-cell analysis

[0101] For all publicly available datasets of skin (Reynolds et al., 2021, Science-, 371 :6527), liver (Aizarani et al., 2019, Nature; 572,199-204; and MacParland et al., 2018, Nat Commun; 9:4383), GI (Parikh et al., 2019, Nature; 567:49-55; and Wang et al., 2020, J Exp Med; 217(2):e20191130), lung (Vieira Braga et al., 2019, Nat Med; 25: 1153-1163; and Laughney et al., 2020, Nat Med; 26:259-269), lacrimal gland (Bannier-Helaouet et al., 2021, Cell Stem Cell; 28: 1221-1232. el227) and oral mucosa (Williams et al., 2021, Cell ;184:4090-4104.e4015), files were downloaded from the appropriate repository (GEO or EGAS). For each dataset, only data generated from healthy subjects were extracted and imported into Seurat-compatible objects. All quality control, normalization, and downstream analyses were performed using the R package Seurat (Hao et al., 2021, Cell; 184:3573-3587 e352 ;ver. 4.3.0, available on the worldwide web at github.com / satijalab / seurat). Low quality cells were excluded from downstream analyses based on percentage of mitochondrial reads (<20), features per cell (>200 and <4,000), and number of reads per cell (<20,000). For GI, liver, and lung, 2 independent datasets were merged, and data integration and batch correction were performed using Harmony. For all datasets, Louvain clustering was then performed on all cells with the ‘FindClusters’ function using the first 50 PCs and a resolution of 1. Through manual annotation, clusters of hematopoietic origin were identified using standard lineage markers (PTPRC, CD3E, MS4A1, CD79B, KLRB KLRG1, LYZ, CD68, CD14, KIT) and excluded from further analysis (with the only exceptions of Langerhans cells in skin and Kupffer cells in liver). Clustering was repeated after the removal of immune cells, and non-immune cell types were manually annotated using the same set of lineage-defining genes used in the original publications. For each cluster, gene expression profiles were compiled, upon exclusion of non-coding genes as well as HLA genes. Genes with a sum count >5 counts per million (CPM) were retained to create the final list of genes to be used for the GvHD filter. For the thymic single-cell dataset from Park et al. (Park et al., 2020, Science; 367(6480):eaay3224), files were downloaded from https: / / developmentcellatlas.ncl.ac.uk and loaded into a Seurat object as described above. EPCAM+ thymic epithelial cells were clustered using a resolution of 0.03 to define 3 macroclusters (corresponding to cortical, medullary, and myo / neuroendocrine thymic epithelial cells). Pseudo-bulk expression of AIRE, HLA-A, HLA-B and HLA-C within the 3 clusters was calculated using the ‘ AggregateExpressiori function in Seurat and the resulting expression levels were normalized on the number of cells present in each cluster.

[0102] Minor Histocompatibility Antigen pipeline

[0103] Input fdes for the pipeline were donor and recipient exomes in the form of BAM / CRAM files aligned to the hg!9 reference genome, that were processed using Deep Variant (Poplin et al., 2018, Nat Biotechnol', 36:983-987) version 1.1.0 and Funcotator (part of the GATK package, v4.2.6.1) to define germline variants (including SNPs, indels and frameshifts) and proceed to their annotation, respectively. By comparing resulting VCF files from each D-R pair, only germline variants present exclusively in the recipient and producing nonsynonymous alteration in protein-coding regions were retained. Subsequent steps included filtering for variants present in genes of interest through the use of ‘GvHD,’ ‘GvL,’ and / or ‘Y mHAg’ filters. The ‘GvHD filter’ has been already described in the previous section. The GvL filter features 2 main components: the ‘AML filter’ (to define genes expressed by malignant myeloid cells) and the ‘Hematopoietic filter’ (to define genes expressed across the different hematopoietic lineages). With respect to the ‘AML filter’ design, to address the challenge posed by AML heterogeneity, a molecular classifier based on AML single-cell expression profiles (van Galen et al., 2019, Cell,' 176: 1265-1281 el224) is used to define 7 expression clusters in the Beat AML cohort (Tyner et al., 2018, Nature,' 562:526-531). Genes expressed with TPM >2 in each cluster are retained. Next, to select genes with preferential expression in AML, all genes with median expression >5 TPM and / or max expression >8 TPM in any of the normal tissues present in the Genotype-Tissue Expression (GTEx) Project RNA repository were filtered out. More specifically, based on the patient gender (a required input information when running the pipeline), the list of GTEx tissues varies to include either female reproductive organs (for male patients) or male reproductive organs (for female patients); for both female and male patients, whole blood, spleen, and lung are excluded given the inherent large proportion of hematopoietic cells present. The resulting list of genes is then subjected to a second filtering round using the GTEx proteomics dataset (Jiang et al., 2020, Cell,' 183:269-283 e219), with all genes with a tissue specificity score (TS) >2 in any GTEx tissue being removed; in instances when protein data was missing, we applied a second RNA-Seq filtering step, using a cutoff of log2(TPM)>5 in any GTEx tissue, a threshold shown to reliably correspond to protein expression (Jiang et al., 2020, Cell,' 183:269-283 e219). The same filtering steps are applied for the generation of the ‘Hematopoietic filter,’ using as starting point publicly available RNA-Seq expression profiles of 18 purified mature hemopoietic cell types (Uhlen et al., 2019, Science,' 366:6472) and of hematopoietic stem and precursor cells (Drissen et al., 2019, Sci Immunol,' 4(35):eaau7148; and Cesana et al., 2018, Cell Stem Cell, 22:575-588 e577). Overall, the resulting gene sets are composed by 259 genes for the ‘AML filter’, and 615 for the ‘Hematopoietic filter’ (with 224 overlapping genes). The list of variant-encompassing k- mers are then blasted against custom in silico proteomes inferred from the exomes from both donor and recipient, sequentially. All k-mers found elsewhere in the proteomes (100% homology) are discarded, and remaining unique k-mers are subjected to binding prediction to the patient-specific class I HLA alleles through HLAthena (Sarkizova et al., 2020, Nat Biotechnol, 38: 199-209) using a threshold of 0.5% prediction rank to define binders. Whenever available, pre-transplant AML RNA-Seq expression can be provided as an optional input file, in order to filter prediction results based on actual expression in the specific patient analyzed. The pipeline is entirely docked on Terra, one of the NCI Cloud Pilots systems, to ensure fully reproducible analyses.

[0104] Immunopeptidome analysis

[0105] B721.221 monoallelic cell line immunopeptidome analysis. WGS from parental B721.221 was processed using BWA-MEM [v.0.7.15-rl 140], subsetted to coding regions, and annotated with DeepVariant. A modified version of the mHAg pipeline was used in order to predict all k-mers deriving from non-synonymous polymorphisms present in the B721.221 (serving as surrogate ‘recipient’) and not in the reference hgl9 genome (serving as surrogate ‘donor’). Genes were filtered based on RNA-Seq expression in B721.221 (TPM>10). Raw mass spectra from 60 HLA-monoallelic B721.221 cell lines were interpreted with the Spectrum Mill (SM) software package, version 8.01 (Broad Institute; proteomics.broadinstitute.org). MS / MS spectra were excluded from searching if they did not have a precursor sequence MH+ in the range of 700-2000 and a precursor charge of + 1 to +3. Similar spectra with the same precursor m / z acquired in the same chromatographic peak were merged. MS / MS spectra with a sequence tag length >1 (i.e. minimum of three masses separated by the in-chain masses of two amino acids) were searched with no-enzyme specificity. MS / MS spectra were searched against the B721.221 -specific SNPs appended to a base reference proteome composed by 98,298 entries, including all University of California Santa Cruz Genome Browser genes with hg!9 annotation of the genome and its protein-coding transcripts (63,691 entries), 602 common laboratory contaminants, 2043 curated smORFs (IncRNA and uORFs), 237,427 nuORF DB vl.037, and the JPT iRT peptides (JPT Peptide Technologies, Berlin, Germany, RTK-1-10 pmol) for a total of 303,803 entries (Ouspenskaia et al., 2022, Nat Biotechnol; 40:209-217). Target-decoy FDR estimation was enabled by Spectrum Mill with on-the-fly generation of decoy sequences during searches. For each candidate sequence passing the precursor mass tolerance filter, the internal sequence was reversed, while holding fixed the second position and the peptide C terminus, to maintain not only equal size target and decoy search spaces, but also comparable HLA class I binding motifs among the sequence candidate population. Peptide spectrum matches (PSMs) within <1% false discovery rate (% FDR) were confidently assigned for individual spectra via the target decoy estimation of the SM Autovalidation module. PSMs were filtered for precursor charges of + 1 to +5, sequence lengths ranging between 9 to 40 amino acids, and a minimum backbone cleavage score of 5. PSMs were consolidated to the peptide level to generate lists of confidently observed peptides for each allele using the Spectrum Mill protein / peptide summary module’s peptide-distinct mode with filtering distinct peptides set to case sensitive.

[0106] IEDB search for Y-encoded mHAgs. A curated set of previously identified HLA class I ligands was downloaded from IEDB available on the worldwide web at iedb.org / downloader.php?file_name=doc / mhc_ligand_full.zip (accessed on September 19, 2022). Records were filtered to Organism = homo sapiens, Epitope Object Type = Linear peptide, Parent Protein and Antigen Name = MSY genes of interest and Allele Name consistent with human HLA class I nomenclature.

[0107] AML cell lines. The following AML cell lines were purchased from DSMZ: Mono- MAC6, MUTZ-3, OCI-AML3 and SET2; MOLM-13 were kindly gifted by the Genovese Lab (DFCI). All cell lines are part of the LL-100 panel (Quentmeier et al., 2019, Sci Rep 9:8218), i.e., profiled at the genomic and transcriptomic level with publicly available results. For each cell line, paired WES and RNA-Seq data were downloaded from ENA (accession numbers: PRJEB30297 and PRJEB30312, respectively). WES was run through a modified version of the mHAg pipeline, using hgl9 as the surrogate ‘donor’ to define the GvL mHAg landscape of each AML cell line. RNA-Seq data was used to evaluate the expression levels of the genes harboring the GvL SNPs and to infer HLA class I typing with OptiType (Szolek et al., 2014, Bioinformatics, 30:3310-3316). Up to 50 million or 0.2 g of each AML cell line were immunoprecipitated, as previously described (Sarkizova et al., 2020, Nat Biotechnol, 38: 199- 209). Peptides of three immunoprecipitations were combined, acid eluted, and analyzed using LC / MS-MS on Orbitrap Exploris 480 equipped with a FAIMSpro interface (Thermo Fisher Scientific) (Klaeger et al., 2021, Mol Cell Proteomics, 20: 100133). MS spectra were interpreted with Spectrum Mill as detailed in the ‘B721.221 monoallelic cell line immunopeptidome analysis’ section, with the only difference being the proteome customization with the GvL SNP entries.

[0108] Immunogenicity assays

[0109] Peptides. All synthetic 8-1 Imers peptides used throughout the study were purchased as microscale libraries with purity >70% (median purity: 93.8%, range: 70.1% - 99.8%) from GenScript, and dissolved in ultrapure DMSO (Sigma Aldrich) to a stock concentration of 10 mM.

[0110] Antigen-specific stimulation. PBMCs for immunogenicity testing were isolated by Ficoll- Paque PLUS (Fisher Scientific) density gradient centrifugation from peripheral blood samples of healthy donors. DNA was extracted with the DNA mini kit (Qiagen) following manufacturer’s instructions and used for HLA typing (through the Brigham and Hospital HLA typing lab), and for SRY PCR to select those from female donors with appropriate HLA restrictions. SRY PCR primers were used, following the protocol described by Cui et al. (Cui et al., 1994, Lancet, 343: 79-82). T cells were enriched from PBMCs using the PanT cell selection kit (Miltenyi Biotech) and then stimulated with autologous CD3-depleted PBMCs pulsed with pools of 5 pM synthetic Y-encoded mHAg peptides at 1 : 1 ratio, in RPMI-1640 supplemented with 5% AB-positive heat- inactivated human serum (Gemini Bioproduct), in presence of 30 ng / ml of IL-21 (Peprotech) till day 3, then replaced by 5 ng / ml of IL-7 and IL-15 from day 4 on (both from Peprotech). On day 7 cultures were restimulated with CD3-depleted PBMCs pulsed with 2 pM peptide pools, in the presence of 5 ng / ml of IL-7 and IL-15. Half-medium change and supplementation of cytokines were performed every 3 days.

[0111] Quantification of mHAg-specific T cells. The presence of antigen-specific T cells was determined on day 14 post stimulation, by staining with HLA-A0201, -A0101, -B0702, -Bl 801, -C0501 and -C0702 easYmers (Immunaware) first loaded with the relevant peptides, and then docked on U-Load dextramers (Immudex), following manufacturer’s instructions. mHAg specificity was assessed by analyzing 3 specificities at a time using triplets of FITC-, PE- and APC-conjugated U-Loads. Cells were then stained with anti-CD3 antibody (conjugated with BV510, clone UCHT1, Biolegend), CD8 (BV785, clone RPA-T8, Biolegend), CD4 (PerCP- Cy5.5, clone RPA-T4, Biolegend), and Zombie Violet (vitality dye, Biolegend). Samples were acquired on a high throughput sampler (HTS)-equipped Fortessa cytometer (BD Biosciences) and analyzed using Flowjo vl0.8 software (BD Biosciences).

[0112] Generation of EBV-immortalized B cell lines (EBV-LCLs). CD19+ cells were isolated from PBMCs of the same female healthy subjects used for the immunogenicity studies through magnetic selection (Miltenyi Biotech). 0.2 - 0.5 x 106purified B cells were then incubated with a 1 : 1 mix of RPM1-1640 supplemented with 20% FBS and 1% penicillin / streptomycin, and EBV supernatant (ATCC) in a total volume of 200 pL. Every 3-4 days thereafter, cultures were examined for signs of transformation and fresh medium was added. EBV-immortalized cell lines were established in 3-4 weeks and were then maintained in culture with RPM1-1640 supplemented with 10% FBS at a maximum density of 1-2 x 106cells / mL.

[0113] CD137 and IFNv catch assays. For 9 mHAg specificities selected based on the expansion level of mHAg-specific T cells, functional validation of antigen-specificity was performed used 2 different assays: CD137 upregulation and IFNy production upon coculture with autologous EBV-LCLs pulsed with the relevant (or control) peptides. Peptide pulsing of target cells was performed by incubating EBV-LCLs in serum-free medium at a density of 2 x 106cells per ml for 2 h in the presence of 5 pM peptides. Ovalbumin (OVA) peptide was used as control. For CD137 assay, upon overnight co-incubation of effector and target cells, mHAg specificity was assessed by flow cytometric detection of CD137 upregulation on CD8+ T cells, using the following antibodies: anti-human CD8a (BV785, clone RPA-T8, Biolegend), CD4 (PerCP - Cy5.5, clone RPA-T4, Biolegend), Zombie Violet (vitality dye, Biolegend), CD 19 (APC- Fire750, clone HIB19, Biolegend) and CD14 (APC-Fire750, clone M5E2, Biolegend). Data were acquired on a high throughput sampler (HTS)-equipped Fortessa cytometer (BD Biosciences) and analyzed using Flowjo vl0.8 software (BD Biosciences). To detect the antigen-specific production of IFNy, T cells were co-incubated with autologous EBV-LCL pulsed with the appropriate peptides for 6 hours, and then labeled with the IFNy secretion Assay detection kit in PE (Miltenyi Biotech) following manufacturer’s instructions. Cells were then counterstained with the following antibodies: anti-human CD8a (BV785, clone RPA-T8, Biolegend), CD4 (PerCP-Cy5.5, clone RPA-T4, Biolegend), Zombie Violet (vitality dye, Biolegend), CD19 (APC-Fire750, clone HIB19, Biolegend) and CD14 (APC-Fire750, clone M5E2, Biolegend). Data were acquired on a high throughput sampler (HTS)-equipped Fortessa cytometer (BD Biosciences) and analyzed using Flowjo vl0.8 software (BD Biosciences).

[0114] Peptide hydrophobicity calculation. The GRAVY hydrophobicity index with the Kyte- Doolittle scale was calculated for the 410 tested Y mHAgs using the ‘Peptides’ R package (v 2.4.4).

[0115] 1000 Genomes in silica allo-HCT simulation

[0116] The WGS bam files for the 1000 Genomes Project (1000G), mapped to the GRCH37 reference genome, were obtained from the Google Brain Genomics repository. Suitable D-R pairs were selected based on the HLA typing information available for each individual in the 1000G dataset. The criterion for selection was that >5 alleles in the HLA class I genes (HLA- A, HLA-B, HLA-C) had to be matched between donor and recipient. A total of 844 individuals combined into 2270 unique D-R pairs satisfying this criterion were identified. The study cohort comprised 239 individuals from EUR, 216 from EAS, 160 from SAS, 140 from AFR and 89 from AMR ancestry. WGS bam files from the selected individuals were reduced to include only the coding region of the genes included in the AML and Hematopoietic filter. Variant calling was performed on the reduced bam files using DeepVariant (version 1.1.0) (Poplin et al., 2018, Nat Biotechnol; 36:983-987), generating germline variant call files. Allelic frequency (AF) of each GvL SNP was calculated for the 1000G cohort and compared to the gnomAD allele frequency which was incorporated into the Funcotator task. Population coverage analysis was performed as previously described by Bui et al. (Bui et al., 2006, BMC Bioinformatics., 7: 153).

[0117] Statistical analyses

[0118] All statistical analyses were conducted using Prism v.9.5 (GraphPad Software) or R v.4.2.2 (available on the worldwide web at r-project.org / ). The following statistical tests were used in this study, unless otherwise indicated: paired t test, unpaired t test or Mann Whitney test, based on prior assessment of data normality (using Shapiro-Wilk test or Kolmogorov-Smirnov test, depending on sample size). The minimum threshold for significance was defined as p < 0.05, and all statistical tests were two-sided.

[0119] Clinical outcomes are reported as of June 2022 (lock date: 25 June 2022). Overall survival (OS) was defined as the time from stem cell infusion to death from any cause. Patients who were alive were censored at the time last seen alive. GvHD-free / relapse-free survival (GRFS) was defined as time to first occurrence of grade III-IV acute GvHD, chronic GvHD requiring systemic treatment, relapse, or death, whichever occurred first. Probabilities of OS and GRFS were estimated with the Kaplan-Meier method using the ‘survival’ (version 3.4-0) R package, while cumulative incidences were estimated using the ‘tidycmprsk’ (version 0.2.0) R package. Cumulative incidence of non-relapse mortality (NRM), relapse, acute GvHD, and chronic GvHD were computed to take into account the presence of competing risks. Specifically, in calculating the cumulative incidence rates of NRM, the competing risk was relapse; when calculating relapse, the competing risk was NRM. For acute and chronic GvHD, the competing risks were relapse and death from other causes. All patients were considered evaluable for acute GvHD analysis, and those who had a documented engraftment and a followup >100 days were evaluated for chronic GvHD (n = 210). To link mHAg load with GvHD outcomes (i.e., overall acute and chronic, as well as organ-specific GvHD), initial evaluation of deciles of mHAg load was used to guide subsequent analyses and define stratification criteria (mHAg load median vs. analysis of individual SNPs). The log-rank test and the Gray test were used for group comparison of OS and cumulative incidence of relapse and GvHD, respectively. The risk factor analysis on acute GvHD-specific hazard was firstly assessed by the Cox proportional-hazards model, and hazard ratio (HR) with the associate 95% confidence interval were calculated for each variable. Forest plots were performed by the forest model function in the ‘forestmodel’ (version 0.6.2) R package. Analysis of promoter region for interferonresponsive elements in the genes associated with liver acute GvHD was performed using the open access interferome database (available on the worldwide web at interferome.org) (Samarajiwa et al, 2009, Nucleic Acids Res 37:D852-857), using the following search conditions: all interferon types, homo sapiens species (all systems and sample types).

[0120] This example has published as Cieri, “Systematic identification of minor histocompatibility antigens predicts outcomes of allogeneic hematopoietic cell transplantation,” Nat Biotechnol. 2024 Aug 21 . doi: 10.1038 / s41587-024-02348-3, which is herein incorporated by reference in its entirety.

[0121] The complete disclosure of all patents, patent applications, and publications, and electronically available material (including, for instance, nucleotide sequence submissions in, e.g., GenBank and RefSeq, and amino acid sequence submissions in, e.g., SwissProt, PIR, PRF, PDB, and translations from annotated coding regions in GenBank and RefSeq) cited herein are incorporated by reference. In the event that any inconsistency exists between the disclosure of the present application and the disclosure(s) of any document incorporated herein by reference, the disclosure of the present application shall govern. The foregoing detailed description and examples have been given for clarity of understanding only. No unnecessary limitations are to be understood therefrom. Variations of the exact details shown and described, obvious to one skilled in the art, as included within the scope of the claims.

Claims

What is claimed is:

1. A method for selecting an HLA-matched transplant donor, the method comprising: determining the presence or absence of one or more SNPs from a panel of SNPs in the donor; determining the presence or absence of one or more SNPs from the panel of SNPs in the recipient; and identifying one or more mismatches between the recipient and the donor, wherein a mismatch comprises the presence in the recipient and the absence in the donor of a given SNP from the panel of SNPs; and selecting as the transplant donor the donor comprising one or more mismatches between the recipient and the donor; wherein GvHD-free and relapse-free survival (GRFS) is improved in the recipient after receipt of donor tissue from the donor; and wherein the panel of SNPs comprises the TICRR p.R287C SNP; the CNTLN p.T695I SNP; the ZNF792 p.Rl 10Q SNP; the LY9 p.M240V SNP; the CTLA4 p.T17A SNP; the WDR49 p.L476P SNP; the HELB p.L191P SNP; the PRDM15 p.R88fs SNP; the PRTN3 p.V78I SNP; the C15orf40 p.C25R SNP; the MCPH1 p.A761V SNP; the MEFV p.D424E SNP; the CR1 p.T1408M SNP; the LILRB1 p.L68P SNP; the ARL11 p.C148R SNP; the ATXN3 p.V33M SNP; the EX01 p.E589K SNP; the LILRB4 p.Q361R SNP; the MCPH1 p.R256I SNP; the MTERF p.A274T SNP; the P2RY13 p.T179M SNP; the PLD4 p.E27Q SNP; the PSTK p.G206R SNP; the RNASE3 p.T124R SNP; the SERPINB10 p.I41M SNP; the WDFY4 p.S1528P SNP; the CD300E p.G158R SNP; the DNAH14 p.L3088P SNP; the MMP8 p.T32I SNP; the PADI4 p.G55S SNP; the RAD18 p.R302Q SNP; the SPNS3 p.A203S SNP; the APOBEC3F p.A108S SNP; the Cl lorf82 p.R159S SNP; the C19orf59 p.I124V SNP; the CCDC171 p.K1069R SNP; the EMR2 p.A53V SNP; the EPX p.Q122H SNP; the GP1BA p.T161M SNP; the IL5RA p. Il 29V SNP; the PSMG4 p.T44P SNP; the WDFY4 p.T2525P SNP; the ZBED6 p.F560L SNP; the CNR2 p.Q63R SNP; the CD101 p.N225S SNP; the CEACAM4 p.H29D SNP; the TLR3 p.L135F SNP; the CLEC4C p.P35S SNP; the CLECL1 p.S52fs SNP; the TVP23C p.S199T SNP; the AK7 p.N389K SNP; the CD3G p.V131F SNP; the CD86 p.A97T SNP; the IL12RB1 p.Q214R SNP; the NLRP7 p.V3191 SNP; the RHCE p.C16W SNP; the RHCE p.A210P SNP;the SLAMF1 p.Fl IL SNP; the SLFN12L p.Y383C SNP; the SLFN12L p.Y518S SNP; the TIGD6 p.Q327R SNP; the BATF3 p.VHI SNP; the CASC1 p.R33S SNP; the CD200R1 p.T99P SNP; the DCLRE1C p.H123R SNP; the N4BP2 p.SlOH SNP; the NLRP12 p.G39V SNP; the SIGLEC9 p.KlOOE SNP; the SPEF2 p.N71H SNP; the TLR7 p.Ql IL SNP; the TRPM6 p.T2I SNP; the CASP5 p.L192V SNP; the CASP5 p.T48A SNP; the CD1E p.Q104R SNP; the CD200R1L p.R92L SNP; the CSF2RA p.A17G SNP; the GTPBP10 p.L85F SNP; the KIAA1549 p.P436A SNP; the LILRA4 p.P27L SNP; the NAALADL2 p.G68S SNP; the RGPD2 p.S177L SNP; the RTP4 p.T131M SNP; the S1OOZ p.E23A SNP; the SIGLEC6 p.P246S SNP; the THEMIS p.I551V SNP; the TTC30A p.P279H SNP; and / or the ZNF286B p.P466S SNP.

2. A method for inducing a graft versus leukemia (GvL) reaction in a HLA-matched transplant recipient receiving donor tissue from a donor, the method comprising: determining the presence or absence of one or more SNPs from the panel of SNPs for the donor; determining the presence or absence of SNPs from the panel of SNPs for the recipient; identifying one or more mismatches between the recipient and the donor, wherein a mismatch comprises the presence in the recipient and the absence in the donor of a given SNP from the panel of SNPs; and transplanting the recipient with donor tissue from the donor when there is one or more mismatches between the recipient and the donor; wherein the panel of SNPs comprises the TICRR p.R287C SNP; the CNTLN p.T695I SNP; the ZNF792 p.Rl 10Q SNP; the LY9 p.M240V SNP; the CTLA4 p.T17A SNP; the WDR49 p.L476P SNP; the HELB p.L191P SNP; the PRDM15 p.R88fs SNP; the PRTN3 p.V78I SNP; the C15orf40 p.C25R SNP; the MCPH1 p.A761V SNP; the MEFV p.D424E SNP; the CR1 p.T1408M SNP; the LILRB1 p.L68P SNP; the ARL11 p.C148R SNP; the ATXN3 p.V33M SNP; the EX01 p.E589K SNP; the LILRB4 p.Q361R SNP; the MCPH1 p.R256I SNP; the MTERF p.A274T SNP; the P2RY13 p.T179M SNP; the PLD4 p.E27Q SNP; the PSTK p.G206R SNP; the RNASE3 p.T124R SNP; the SERPINB10 p.I41M SNP; the WDFY4 p.S1528P SNP; the CD300E p.G158R SNP; the DNAH14 p.L3088P SNP; the MMP8 p.T32I SNP; the PADI4 p.G55S SNP; the RAD18 p.R302Q SNP; the SPNS3 p.A203S SNP; the APOBEC3F p.A108S SNP; the Cl lorf82 p.R159S SNP; the C19orf59 p.I124V SNP; the CCDC171 p.K1069R SNP;the EMR2 p.A53V SNP; the EPX p.Q122H SNP; the GP1BA p.T161M SNP; the IL5RA p.I129V SNP; the PSMG4 p.T44P SNP; the WDFY4 p.T2525P SNP; the ZBED6 p.F560L SNP; the CNR2 p.Q63R SNP; the CD101 p.N225S SNP; the CEACAM4 p.H29D SNP; the TLR3 p.L135F SNP; the CLEC4C p.P35S SNP; the CLECL1 p.S52fs SNP; the TVP23C p.S199T SNP; the AK7 p.N389K SNP; the CD3G p.V131F SNP; the CD86 p.A97T SNP; the IL12RB1 p.Q214R SNP; the NLRP7 p.V319I SNP; the RHCE p.C16W SNP; the RHCE p.A210P SNP; the SLAMF1 p.FUL SNP; the SLFN12L p.Y383C SNP; the SLFN12L p.Y518S SNP; the TIGD6 p.Q327R SNP; the BATF3 p.VHI SNP; the CASC1 p.R33S SNP; the CD200R1 p.T99P SNP; the DCLRE1C p.H123R SNP; the N4BP2 p.SlOH SNP; the NLRP12 p.G39V SNP; the SIGLEC9 p.KlOOE SNP; the SPEF2 p.N71H SNP; the TLR7 p.Ql IL SNP; the TRPM6 p.T2I SNP; the CASP5 p.L192V SNP; the CASP5 p.T48A SNP; the CD1E p.Q104R SNP; the CD200R1L p.R92L SNP; the CSF2RA p.A17G SNP; the GTPBP10 p.L85F SNP; the KIAA1549 p.P436A SNP; the LILRA4 p.P27L SNP; the NAALADL2 p.G68S SNP; the RGPD2 p.S177L SNP; the RTP4 p.T131M SNP; the S1OOZ p.E23A SNP; the SIGLEC6 p.P246S SNP; the THEMIS p.I551V SNP; the TTC30A p.P279H SNP; and / or the ZNF286B p.P466S SNP.

3. The method of claim 1 or claim 2, wherein identifying one or more mismatches between the recipient and the donor comprises identifying ten or more mismatches.

4. The method of any one of claims 1 to 3, wherein one or more of the SNPs from the panel of SNPs comprises the APOBEC3F p.A108S SNP and / or the MCPH1 p.R256I SNP.

5. The method of any one of claims 1 to 4, wherein the HLA-matched donor and recipient comprise HLA A0101, HLA A0201, HLA A0208, HLA A0301, HLA A0302, HLA Al 101, HL A A2301, HLA A2402, HLA A2403, HLA A2601, HLA A2902, HLA A3001, HLA A3101, HLA A3201, HLA A3301, HLA A6601, HLA A6801, HLA A6802, HLA A7401, HLA A8001, HLA B0702, HLA B0801, HLA B1302, HLA B1401, HLA B1402, HLA B1501, HLA B15O3, HLA B1801, HLA B2705, HLA B35O1, HLA B3502, HLA B35O8, HLA B3701, HLA B3801, HLA B3901, HLA B4001, HLA B4006, HLA B4101, HLA B4102, HLA B4402, HLA B4403, HLA B4501, HLA B4901, HLA B5101, HLA B5201, HLA B53O1, HLA B5701, HLA B5802, HLA C0102, HLA C0202, HLA CO3O3, HLA C0304, HLA C0401, HLA C0501, HLA C0602,HLA C0701, HL A C0702, HLA C0704, HL A C0802, HLA Cl 202, HL A Cl 203, HLA Cl 402, HLA C1502, HLA C1505, HLA C1601, HLA C1602, and / or HLA C1701.

6. The method of any one of claims 1 to 5, wherein the SNP information for the donor and / or the recipient is obtained by targeted next generation sequencing (NGS), whole exome sequencing (WES), whole genomic sequencing (WGS), and / or SNP array -based genotyping.

7. The methods of any one of claim 1 to 6, wherein the donor and the recipient are human.

8. The methods of any one of claim 1 to 7, wherein the transplantation of donor tissue is for the treatment of a cancer.

9. The method of claim 8, wherein the cancer comprises acute myeloid leukemia (AML) or myelodysplastic syndrome (MDS).

10. The method of any one of claims 1 to 9, wherein the donor tissue comprises hematopoietic cells.

11. The method of any one of claims 1 to 10, wherein the donor tissue comprises HLA- matched allogeneic hematopoietic stem cells.

12. A composition comprising one or more graft versus leukemia minor histocompatibility antigen (GvL mHAg)-specific antigenic epitopes and a pharmaceutical composition, wherein a GvL mHAg-specific antigenic epitope consists of a peptide of about 8-11 amino acids encoded by a single nucleotide polymorphism (SNP) selected from the group consisting of the TICRR p.R287C SNP; the CNTLN p.T695I SNP; the ZNF792 p.Rl 10Q SNP; the LY9 p.M240V SNP; the CTLA4 p.T17A SNP; the WDR49 p.L476P SNP; the HELB p.L191P SNP; the PRDM15 p.R88fs SNP; the PRTN3 p.V78I SNP; the C15orf40 p.C25R SNP; the MCPH1 p.A761V SNP; the MEFV p.D424E SNP; the CR1 p.T1408M SNP; the LILRB1 p.L68P SNP; the ARL11 p.C148R SNP; the ATXN3 p.V33M SNP; the EXO1 p.E589K SNP; the LILRB4 p.Q361R SNP; the MCPH1 p.R256I SNP; the MTERF p.A274T SNP; the P2RY13 p.T179M SNP; the PLD4p.E27Q SNP; the PSTK p.G206R SNP; the RNASE3 p.T124R SNP; the SERPINB10 p.I41M SNP; the WDFY4 p.S1528P SNP; the CD3OOE p.G158R SNP; the DNAH14 p.L3088P SNP; the MMP8 p.T32I SNP; the PADI4 p.G55S SNP; the RAD18 p.R302Q SNP; the SPNS3 p.A203S SNP; the APOBEC3F p.A108S SNP; the Cl lorf82 p.R159S SNP; the C19orf59 p.I124V SNP; the CCDC171 p.K1069R SNP; the EMR2 p.A53V SNP; the EPX p.Q122H SNP; the GP1BA p.T161M SNP; the IL5RA p.I129V SNP; the PSMG4 p.T44P SNP; the WDFY4 p.T2525P SNP; the ZBED6 p.F560L SNP; the CNR2 p.Q63R SNP; the CD1O1 p.N225S SNP; the CEACAM4 p.H29D SNP; the TLR3 p.L135F SNP; the CLEC4C p.P35S SNP; the CLECL1 p.S52fs SNP; the TVP23C p.S199T SNP; the AK7 p.N389K SNP; the CD3G p.V131F SNP; the CD86 p.A97T SNP; the IL12RB1 p.Q214R SNP; the NLRP7 p.V319I SNP; the RHCE p.C16W SNP; the RHCE p.A210P SNP; the SLAMF1 p.FUL SNP; the SLFN12L p.Y383C SNP; the SLFN12L p.Y518S SNP; the TIGD6 p.Q327R SNP; the BATF3 p.VHI SNP; the CASC1 p.R33S SNP; the CD200R1 p.T99P SNP; the DCLRE1C p.H123R SNP; the N4BP2 p.SlOH SNP; the NLRP12 p.G39V SNP; the SIGLEC9 p.KlOOE SNP; the SPEF2 p.N71H SNP; the TLR7 p.Ql IL SNP; the TRPM6 p.T2I SNP; the CASP5 p.L192V SNP; the CASP5 p.T48A SNP; the CD1E p.Q104R SNP; the CD200R1L p.R92L SNP; the CSF2RA p.A17G SNP; the GTPBP10 p.L85F SNP; the KIAA1549 p.P436A SNP; the LILRA4 p.P27L SNP; the NAALADL2 p.G68S SNP; the RGPD2 p.S177L SNP; the RTP4 p.T131M SNP; the S1OOZ p.E23A SNP; the SIGLEC6 p.P246S SNP; the THEMIS p.I551V SNP; the TTC30A p.P279H SNP; and the ZNF286B p.P466S SNP.

13. A GvL mHAg-targeting vaccine comprising a composition of claim 12.

14. A kit for comprising a plurality of probes capable of binding to and / or identifying one or more of the TICRR p.R287C SNP; the CNTLN p.T695I SNP; the ZNF792 p.Rl 10Q SNP; the LY9 p.M240V SNP; the CTLA4 p.T17A SNP; the WDR49 p.L476P SNP; the HELB p.L191P SNP; the PRDM15 p.R88fs SNP; the PRTN3 p.V78I SNP; the C15orf40 p.C25R SNP; the MCPH1 p.A761V SNP; the MEFV p.D424E SNP; the CR1 p.T1408M SNP; the LILRB1 p.L68P SNP; the ARL11 p.C148R SNP; the ATXN3 p.V33M SNP; the EXOl p.E589K SNP; the LILRB4 p.Q361R SNP; the MCPH1 p.R256I SNP; the MTERF p.A274T SNP; the P2RY13 p.T179M SNP; the PLD4 p.E27Q SNP; the PSTK p.G206R SNP; the RNASE3 p.T124R SNP; the SERPINB10 p.I41M SNP; the WDFY4 p.S1528P SNP; the CD300E p.G158R SNP; theDNAH14 p.L3088P SNP; the MMP8 p.T32I SNP; the PADI4 p.G55S SNP; the RADI 8 p.R302Q SNP; the SPNS3 p.A203S SNP; the APOBEC3F p.A108S SNP; the Cl lorf82 p.R159S SNP; the C19orf59 p.I124V SNP; the CCDC171 p.K1069R SNP; the EMR2 p.A53V SNP; the EPX p.Q122H SNP; the GP1BA p.T161M SNP; the IL5RA p.I129V SNP; the PSMG4 p.T44P SNP; the WDFY4 p.T2525P SNP; the ZBED6 p.F560L SNP; the CNR2 p.Q63R SNP; the CD101 p.N225S SNP; the CEACAM4 p.H29D SNP; the TLR3 p.L135F SNP; the CLEC4C p.P35S SNP; the CLECL1 p.S52fs SNP; the TVP23C p.S199T SNP; the AK7 p.N389K SNP; the CD3G p.V131F SNP; the CD86 p.A97T SNP; the IL12RB1 p.Q214R SNP; the NLRP7 p.V3191 SNP; the RHCE p.C16W SNP; the RHCE p.A210P SNP; the SLAMF1 p.Fl IL SNP; the SLFN12L p.Y383C SNP; the SLFN12L p.Y518S SNP; the TIGD6 p.Q327R SNP; the BATF3 p.VHI SNP; the CASC1 p.R33S SNP; the CD200R1 p.T99P SNP; the DCLRE1C p.H123R SNP; the N4BP2 p.SlOlI SNP; the NLRP12 p.G39V SNP; the SIGLEC9 p.KlOOE SNP; the SPEF2 p.N71H SNP; the TLR7 p.Ql IL SNP; the TRPM6 p.T2I SNP; the CASP5 p.L192V SNP; the CASP5 p.T48A SNP; the CD1E p.Q104R SNP; the CD200R1L p.R92L SNP; the CSF2RA p.A17G SNP; the GTPBP10 p.L85F SNP; the KIAA1549 p.P436A SNP; the LILRA4 p.P27L SNP; the NAALADL2 p.G68S SNP; the RGPD2 p.S177L SNP; the RTP4 P.T131M SNP; the S100Z p.E23A SNP; the SIGLEC6 p.P246S SNP; the THEMIS p.I551V SNP; the TTC30A p.P279H SNP; and / or the ZNF286B p.P466S SNP in a sample from the transplant donor and / or the transplant recipient.

15. The kit of claim 14, the kit consisting of probes capable of binding to and / or identifying each of the TICRR p.R287C SNP; the CNTLN p.T695I SNP; the ZNF792 p.Rl 10Q SNP; the LY9 p.M240V SNP; the CTLA4 p.T17A SNP; the WDR49 p.L476P SNP; the HELB p.L191P SNP; the PRDM15 p.R88fs SNP; the PRTN3 p.V78I SNP; the C15orf40 p.C25R SNP; the MCPH1 p.A761V SNP; the MEFV p.D424E SNP; the CR1 p.T1408M SNP; the LILRB 1 p.L68P SNP; the ARL11 p.C148R SNP; the ATXN3 p.V33M SNP; the EXOl p.E589K SNP; the LILRB4 p.Q361R SNP; the MCPH1 p.R256I SNP; the MTERF p.A274T SNP; the P2RY13 P.T179M SNP; the PLD4 p.E27Q SNP; the PSTK p.G206R SNP; the RNASE3 p.T124R SNP; the SERPINB10 p.I41M SNP; the WDFY4 p.S1528P SNP; the CD300E p.G158R SNP; the DNAH14 p.L3088P SNP; the MMP8 p.T32I SNP; the PADI4 p.G55S SNP; the RAD18 p.R302Q SNP; the SPNS3 p.A203S SNP; the APOBEC3F p.A108S SNP; the Cl lorf82 p.R159SSNP; the C19orf59 p.I124V SNP; the CCDC171 p.K1069R SNP; the EMR2 p.A53V SNP; the EPX p.Q122H SNP; the GP1BA p.T161M SNP; the IL5RA p.I129V SNP; the PSMG4 p.T44P SNP; the WDFY4 p.T2525P SNP; the ZBED6 p.F560L SNP; the CNR2 p.Q63R SNP; the CD101 p.N225S SNP; the CEACAM4 p.H29D SNP; the TLR3 p.L135F SNP; the CLEC4C p.P35S SNP; the CLECL1 p.S52fs SNP; the TVP23C p.S199T SNP; the AK7 p.N389K SNP; the CD3G p.V13 IF SNP; the CD86 p.A97T SNP; the IL12RB1 p.Q214R SNP; the NLRP7 p.V319I SNP; the RHCE p.C16W SNP; the RHCE p.A210P SNP; the SLAMF1 p.Fl lL SNP; the SLFN12L p.Y383C SNP; the SLFN12L p.Y518S SNP; the TIGD6 p.Q327R SNP; the BATF3 p.Vl II SNP; the CASC1 p.R33S SNP; the CD200R1 p.T99P SNP; the DCLRE1C p.H123R SNP; the N4BP2 p.SlOH SNP; the NLRP12 p.G39V SNP; the SIGLEC9 p.KlOOE SNP; the SPEF2 p.N71H SNP; the TLR7 p.Ql IL SNP; the TRPM6 p.T2I SNP; the CASP5 p.L192V SNP; the CASP5 p.T48A SNP; the CD1E p.Q104R SNP; the CD200R1L p.R92L SNP; the CSF2RA p.A17G SNP; the GTPBP10 p.L85F SNP; the KIAA1549 p.P436A SNP; the LILRA4 p.P27L SNP; the NAALADL2 p.G68S SNP; the RGPD2 p.S177L SNP; the RTP4 p.T131M SNP; the S1OOZ p.E23A SNP; the SIGLEC6 p.P246S SNP; the THEMIS p.I551V SNP; the TTC30A p.P279H SNP; and the ZNF286B p.P466S SNP.

16. A kit for comprising a plurality of primers for selectively amplifying one or more of theTICRR p.R287C SNP; the CNTLN p.T695I SNP; the ZNF792 p.Rl 10Q SNP; the LY9 p.M240V SNP; the CTLA4 p.T17A SNP; the WDR49 p.L476P SNP; the HELB p.L191P SNP; the PRDM15 p.R88fs SNP; the PRTN3 p.V78I SNP; the C15orf40 p.C25R SNP; the MCPH1 P.A761V SNP; the MEFV p.D424E SNP; the CR1 p.T1408M SNP; the LILRB1 p.L68P SNP; the ARL11 p.C148R SNP; the ATXN3 p.V33M SNP; the EXO1 p.E589K SNP; the LILRB4 p.Q361R SNP; the MCPHl p.R256I SNP; the MTERF p.A274T SNP; the P2RY13 p.T179M SNP; the PLD4 p.E27Q SNP; the PSTK p.G206R SNP; the RNASE3 p.T124R SNP; the SERPINB10 p.I41M SNP; the WDFY4 p.S1528P SNP; the CD300E p.G158R SNP; the DNAH14 p.L3088P SNP; the MMP8 p.T32I SNP; the PADI4 p.G55S SNP; the RAD18 P.R302Q SNP; the SPNS3 p.A203S SNP; the APOBEC3F p.A108S SNP; the Cl lorf82 p.R159S SNP; the C19orf59 p.I124V SNP; the CCDC171 p.K1069R SNP; the EMR2 p.A53V SNP; the EPX p.Q122H SNP; the GP1BA p.T161M SNP; the IL5RA p.I129V SNP; the PSMG4 p.T44P SNP; the WDFY4 p.T2525P SNP; the ZBED6 p.F560L SNP; the CNR2 p.Q63R SNP; theCD101 p.N225S SNP; the CEACAM4 p.H29D SNP; the TLR3 p.L135F SNP; the CLEC4C p.P35S SNP; the CLECL1 p.S52fs SNP; the TVP23C p.S199T SNP; the AK7 p.N389K SNP; the CD3G p.V13 IF SNP; the CD86 p.A97T SNP; the IL12RB1 p.Q214R SNP; the NLRP7 p.V319I SNP; the RHCE p.C16W SNP; the RHCE p.A210P SNP; the SLAMF1 p.FUL SNP; the SLFN12L p.Y383C SNP; the SLFN12L p.Y518S SNP; the TIGD6 p.Q327R SNP; the BATF3 p.Vl II SNP; the CASC1 p.R33S SNP; the CD200R1 p.T99P SNP; the DCLRE1C p.H123R SNP; the N4BP2 p.SlOH SNP; the NLRP12 p.G39V SNP; the SIGLEC9 p.KlOOE SNP; the SPEF2 p.N71H SNP; the TLR7 p.Ql IL SNP; the TRPM6 p.T2I SNP; the CASP5 P.L192V SNP; the CASP5 p.T48A SNP; the CD1E p.Q104R SNP; the CD200R1L p.R92L SNP; the CSF2RA p.A17G SNP; the GTPBP10 p.L85F SNP; the KIAA1549 p.P436A SNP; the LILRA4 p.P27L SNP; the NAALADL2 p.G68S SNP; the RGPD2 p.S177L SNP; the RTP4 p.T131M SNP; the S1OOZ p.E23A SNP; the SIGLEC6 p.P246S SNP; the THEMIS p.I551V SNP; the TTC30A p.P279H SNP; and / or the ZNF286B p.P466S SNP in a sample from the transplant donor and / or the transplant recipient.

17. The kit of claim 16, the kit consisting of primers for selectively amplifying each of the TICRR p.R287C SNP; the CNTLN p.T695I SNP; the ZNF792 p.Rl 10Q SNP; the LY9 p.M240V SNP; the CTLA4 p.T17A SNP; the WDR49 p.L476P SNP; the HELB p.L191P SNP; the PRDM15 p.R88fs SNP; the PRTN3 p.V78I SNP; the C15orf40 p.C25R SNP; the MCPH1 p.A761 V SNP; the MEFV p.D424E SNP; the CR1 p.T1408M SNP; the LILRB1 p.L68P SNP; the ARL11 p.C148R SNP; the ATXN3 p.V33M SNP; the EX01 p.E589K SNP; the LILRB4 P.Q361R SNP; the MCPHl p.R256I SNP; the MTERF p.A274T SNP; the P2RY13 p.T179M SNP; the PLD4 p.E27Q SNP; the PSTK p.G206R SNP; the RNASE3 p.T124R SNP; the SERPINB10 p.I41M SNP; the WDFY4 p.S1528P SNP; the CD300E p.G158R SNP; the DNAH14 p.L3088P SNP; the MMP8 p.T32I SNP; the PADI4 p.G55S SNP; the RAD18 p.R302Q SNP; the SPNS3 p.A203S SNP; the APOBEC3F p.A108S SNP; the Cl lorf82 p.R159S SNP; the C19orf59 p.I124V SNP; the CCDC171 p.K1069R SNP; the EMR2 p.A53V SNP; the EPX p.Q122H SNP; the GP1BA p.T161M SNP; the IL5RA p.I129V SNP; the PSMG4 p.T44P SNP; the WDFY4 p.T2525P SNP; the ZBED6 p.F560L SNP; the CNR2 p.Q63R SNP; the CD101 p.N225S SNP; the CEACAM4 p.H29D SNP; the TLR3 p.L135F SNP; the CLEC4C p.P35S SNP; the CLECL1 p.S52fs SNP; the TVP23C p.S199T SNP; the AK7 p.N389K SNP;the CD3G p.V131F SNP; the CD86 p.A97T SNP; the IL12RB1 p.Q214R SNP; the NLRP7 p.V319I SNP; the RHCE p.C16W SNP; the RHCE p.A210P SNP; the SLAMF1 p.Fl lL SNP; the SLFN12L p.Y383C SNP; the SLFN12L p.Y518S SNP; the TIGD6 p.Q327R SNP; the BATF3 p.VHI SNP; the CASC1 p.R33S SNP; the CD200R1 p.T99P SNP; the DCLRE1C p.H123R SNP; the N4BP2 p.SlOH SNP; the NLRP12 p.G39V SNP; the SIGLEC9 p.KlOOE SNP; the SPEF2 p.N71H SNP; the TLR7 p.Ql IL SNP; the TRPM6 p.T2I SNP; the CASP5 p.L192V SNP; the CASP5 p.T48A SNP; the CD1E p.Q104R SNP; the CD200R1L p.R92L SNP; the CSF2RA p.A17G SNP; the GTPBP10 p.L85F SNP; the KIAA1549 p.P436A SNP; the LILRA4 p.P27L SNP; the NAALADL2 p.G68S SNP; the RGPD2 p.S177L SNP; the RTP4 p.T131M SNP; the S1OOZ p.E23A SNP; the SIGLEC6 p.P246S SNP; the THEMIS p.I551V SNP; the TTC30A p.P279H SNP; and the ZNF286B p.P466S SNP.

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