Biomarkers for xenograft rejection

Abstract

The present invention relates to methods of detecting a xenograft rejection in a subject, monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said methods comprising determination of expression levels of certain human or porcine genes and comparing expression levels of said genes.

Description

Attorney Docket No: 243735.000437 BIOMARKERS FOR XENOGRAFT REJECTION CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to U.S. Provisional Patent Application No.63 / 649,853, filed May 20, 2024, and U.S. Provisional Patent Application No.63 / 664,311, filed June 26, 2024, the disclosures of which are herein incorporated by reference in their entireties. STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH

[0002] This invention was made with government support under HG009491, OD033430, P30 CA016087, and AI144522 awarded by the National Institutes of Health. The government has certain rights in the invention. SEQUENCE LISTING

[0003] The instant application contains a Sequence Listing which has been submitted electronically in XML format and is hereby incorporated by reference in its entirety. Said XML copy, created on May 19, 2025, is named 243735_000437_SL.xml and is 18,223 bytes in size. FIELD OF THE INVENTION

[0004] The present invention relates to methods of detecting a xenograft rejection in a subject, monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said methods comprising determination of expression levels of certain human or porcine genes and comparing expression levels of said genes. BACKGROUND

[0005] Organ transplantation is a life-saving procedure for end-stage organ failure patients. Severe shortage of donor organs has been a worldwide challenge (Sykes, et al., 2022; Matas, et al., 2023) and remains a major limitation within human allo-transplantation, with waiting lists greatly outpacing the number of donors available. Over 100,000 people are currently on the 1 314164997v1Attorney Docket No: 243735.000437 transplant waiting list in the United States, and due to organ shortages, only ~1 in 4 of those will ever receive an allograft (national U.S. data, OPTN). Exploring alternative sources of organs for transplantation to meet the increasing demand is considered to be a health care imperative. Xenotransplantation (transplantation of organs across species) of genetically engineered organs or tissues from different species has emerged as a promising solution to address this challenge (Wolbrom, et al., 2023). Genetically modified pig organs offer several significant advantages for transplantation into humans and may help alleviate the current shortage of suitable organs (Cooper, et al., 2023; Wolbrom, et al., 2023). The domesticated pig (Sus scrofa domesticus) has been identified as a suitable species due to its size / physiology similarities to human organs, quick maturation to near adult size in 6 months, and positive public perception (Cooper, et al., 2002; Elisseeff, et al., 2021). Organs from 6-10-month-old pigs are the most suitable for xenotransplantation (Hryhorowicz, et al., 2017). SUMMARY OF THE INVENTION

[0006] In one aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes MS4A1, CD19, AIM2, BANK1, CD79A, TNFRSF13C, BLK, IGHM, and IGHD, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0007] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes XBP1, MZB1, TNFRSF17, CD27, TENT5C, POU2AF1, 2 314164997v1Attorney Docket No: 243735.000437 PRDM1, NUGGC, and SDC1, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs); and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0008] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes KLRC1, GZMB, TRDC, KLRF1, and GNLY, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0009] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes LYZ, MRC1, STAB1, SLCO2B1, F13A1, CD163, MSR1, SLC40A1, and CD14, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0010] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes IRF7, TLR7, TLR9, MYD88, and STAT1, wherein the sample is a xenograft tissue biopsy; and 3 314164997v1Attorney Docket No: 243735.000437 b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0011] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes PLD4, CLEC4C, LILRA4, TPM2, MZB1, SCT, IRF4, and SMPD3, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0012] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, and CLEC10A, wherein the sample is a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0013] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, and IFIH1, wherein the sample is a xenograft tissue biopsy; and 4 314164997v1Attorney Docket No: 243735.000437 b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0014] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes CD3G, THEMIS, CD5, and CD6, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0015] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of CD8B and / or CD8A, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the gene(s) determined in step (a) to a corresponding control.

[0016] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes KLRG1, GZMK, CST7, and GZMH, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0017] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft 5 314164997v1Attorney Docket No: 243735.000437 rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes LEF1, TCF7, SELL, CD27, CD55, and CCR7, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0018] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes CD4, CD40LG, CCR2, CCR6, and DPP4, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0019] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes CTLA4, FOXP3, IKZF2, RTKN2, IRF4, IL21, and IL2RA, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0020] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: 6 314164997v1Attorney Docket No: 243735.000437 a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes ITGAE, CD38, TNFRSF9, and MKI67, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0021] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes GZMA, PRF1, and FASLG, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0022] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes TOP2A, TYMS, and MKI67, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0023] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes GBP1, IRF1, TAP1, WARS1, and IDO1, wherein the sample is a xenograft tissue biopsy; and 7 314164997v1Attorney Docket No: 243735.000437 b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0024] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes CLEC10A, CD1C, FCER1A, CD1E, CD1D, and CCR2, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0025] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes CSF3R, FCGR3B, FPR1, ALPL, MGAM, CXCR1, MXD1, and CXCR2, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0026] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes MS4A1, CD19, AIM2, BANK1, CD79A, TNFRSF13C, BLK, IGHM, IGHD, XBP1, MZB1, TNFRSF17, CD27, TENT5C, POU2AF1, PRDM1, NUGGC, SDC1, KLRC1, GZMB, TRDC, KLRF1, GNLY, LYZ, MRC1, STAB1, SLCO2B1, F13A1, CD163, MSR1, SLC40A1, CD14, IRF7, TLR7, TLR9, MYD88, STAT1, PLD4, CLEC4C, 8 314164997v1Attorney Docket No: 243735.000437 LILRA4, TPM2, MZB1, SCT, IRF4, SMPD3, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, CD3G, THEMIS, CD5, CD6, CD8B, CD8A, KLRG1, GZMK, CST7, GZMH, LEF1, TCF7, SELL, CD27, CD55, CCR7, CD4, CD40LG, CCR2, CCR6, DPP4, CTLA4, FOXP3, IKZF2, RTKN2, IRF4, IL21, IL2RA, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, MKI67, GBP1, IRF1, TAP1, WARS1, IDO1, CLEC10A, CD1C, FCER1A, CD1E, CD1D, CCR2, CSF3R, FCGR3B, FPR1, ALPL, MGAM, CXCR1, MXD1, and CXCR2, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0027] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes XBP1, MZB1, TNFRSF17, CD27, TENT5C, POU2AF1, PRDM1, NUGGC, SDC1, KLRC1, GZMB, TRDC, KLRF1, GNLY, LYZ, MRC1, STAB1, SLCO2B1, F13A1, CD163, MSR1, SLC40A1, CD14, IRF7, TLR7, TLR9, MYD88, STAT1, PLD4, CLEC4C, LILRA4, TPM2, MZB1, SCT, IRF4, SMPD3, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, MKI67, GBP1, IRF1, TAP1, WARS1, IDO1, CLEC10A, CD1C, FCER1A, CD1E, CD1D, CCR2, CSF3R, FCGR3B, FPR1, ALPL, MGAM, CXCR1, MXD1, and CXCR2, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0028] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft 9 314164997v1Attorney Docket No: 243735.000437 rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes MS4A1, CD19, AIM2, BANK1, CD79A, TNFRSF13C, BLK, IGHM, IGHD, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, CD3G, THEMIS, CD5, CD6, CD8B, CD8A, KLRG1, GZMK, CST7, GZMH, LEF1, TCF7, SELL, CD27, CD55, CCR7, CD4, CD40LG, CCR2, CCR6, DPP4, CTLA4, FOXP3, IKZF2, RTKN2, IRF4, IL21, IL2RA, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, and MKI67, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0029] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from porcine genes SPP1, COLEC11, S100A6, NFKBIZ, CLDN1, THBS1, HIF1A, STMN1, ICAM1, TNFRSF1B, CXCL14, IL1RL1, and NREP, wherein the sample is a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0030] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from porcine genes C3, CXCL2, C4A, LYZ, S100A6, S100A11, MX1, MX2, IL33, and HIF1A, wherein the sample is a xenograft tissue biopsy; and 10 314164997v1Attorney Docket No: 243735.000437 b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0031] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from porcine genes PDGFRB, PECAM1, STAT3, IL33, RGS5, CD163, C3, VCAM1, TNC, CD74, SERPINE1, CCR5, TEK, RUNX1, MX2, IFIT1, COL1A1, CXCL14, MRC1, CD68, CD14, MX1, and LYVE1, wherein the sample is a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0032] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from porcine genes HIF1A, LMNA, EMP1, EIF4A1, DHX9, LYVE1, YWHAQ, CD163, VCAM1, MKI67, IFIT1, ICAM1, STAT1, STAT3, TOP2A, S100A6, WARS1, S100A1, SERPINH1, TOP2A, MX1, MX2, CD14, HSPA9, and HSPD1, wherein the sample is a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0033] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from porcine genes SPP1, COLEC11, S100A6, NFKBIZ, CLDN1, THBS1, HIF1A, STMN1, ICAM1, TNFRSF1B, CXCL14, IL1RL1, NREP, C3, CXCL2, C4A, LYZ, S100A6, S100A11, MX1, MX2, IL33, HIF1A, PDGFRB, PECAM1, STAT3, IL33, RGS5, 11 314164997v1Attorney Docket No: 243735.000437 CD163, C3, VCAM1, TNC, CD74, SERPINE1, CCR5, TEK, RUNX1, MX2, IFIT1, COL1A1, CXCL14, MRC1, CD68, CD14, MX1, LYVE1, HIF1A, LMNA, EMP1, EIF4A1, DHX9, LYVE1, YWHAQ, CD163, VCAM1, MKI67, IFIT1, ICAM1, STAT1, STAT3, TOP2A, S100A6, WARS1, S100A1, SERPINH1, TOP2A, MX1, MX2, CD14, HSPA9, and HSPD1, wherein the sample is a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0034] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from 1) human genes MS4A1, CD19, AIM2, BANK1, CD79A, TNFRSF13C, BLK, IGHM, IGHD, XBP1, MZB1, TNFRSF17, CD27, TENT5C, POU2AF1, PRDM1, NUGGC, SDC1, KLRC1, GZMB, TRDC, KLRF1, GNLY, LYZ, MRC1, STAB1, SLCO2B1, F13A1, CD163, MSR1, SLC40A1, CD14, IRF7, TLR7, TLR9, MYD88, STAT1, PLD4, CLEC4C, LILRA4, TPM2, MZB1, SCT, IRF4, SMPD3, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, CD3G, THEMIS, CD5, CD6, CD8B, CD8A, KLRG1, GZMK, CST7, GZMH, LEF1, TCF7, SELL, CD27, CD55, CCR7, CD4, CD40LG, CCR2, CCR6, DPP4, CTLA4, FOXP3, IKZF2, RTKN2, IRF4, IL21, IL2RA, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, MKI67, GBP1, IRF1, TAP1, WARS1, IDO1, CLEC10A, CD1C, FCER1A, CD1E, CD1D, CCR2, CSF3R, FCGR3B, FPR1, ALPL, MGAM, CXCR1, MXD1, and CXCR2, and 2) porcine genes SPP1, COLEC11, S100A6, NFKBIZ, CLDN1, THBS1, HIF1A, STMN1, ICAM1, TNFRSF1B, CXCL14, IL1RL1, NREP, C3, CXCL2, C4A, LYZ, S100A6, S100A11, MX1, MX2, IL33, HIF1A, PDGFRB, PECAM1, STAT3, IL33, RGS5, CD163, C3, VCAM1, TNC, CD74, SERPINE1, CCR5, TEK, RUNX1, MX2, IFIT1, COL1A1, CXCL14, MRC1, CD68, CD14, MX1, LYVE1, HIF1A, LMNA, EMP1, EIF4A1, DHX9, LYVE1, YWHAQ, CD163, VCAM1, MKI67, IFIT1, ICAM1, STAT1, STAT3, TOP2A, S100A6, WARS1, S100A1, 12 314164997v1Attorney Docket No: 243735.000437 SERPINH1, TOP2A, MX1, MX2, CD14, HSPA9, and HSPD1, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0035] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from 1) human genes XBP1, MZB1, TNFRSF17, CD27, TENT5C, POU2AF1, PRDM1, NUGGC, SDC1, KLRC1, GZMB, TRDC, KLRF1, GNLY, LYZ, MRC1, STAB1, SLCO2B1, F13A1, CD163, MSR1, SLC40A1, CD14, IRF7, TLR7, TLR9, MYD88, STAT1, PLD4, CLEC4C, LILRA4, TPM2, MZB1, SCT, IRF4, SMPD3, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, MKI67, GBP1, IRF1, TAP1, WARS1, IDO1, CLEC10A, CD1C, FCER1A, CD1E, CD1D, CCR2, CSF3R, FCGR3B, FPR1, ALPL, MGAM, CXCR1, MXD1, and CXCR2, and 2) porcine genes SPP1, COLEC11, S100A6, NFKBIZ, CLDN1, THBS1, HIF1A, STMN1, ICAM1, TNFRSF1B, CXCL14, IL1RL1, NREP, C3, CXCL2, C4A, LYZ, S100A6, S100A11, MX1, MX2, IL33, HIF1A, PDGFRB, PECAM1, STAT3, IL33, RGS5, CD163, C3, VCAM1, TNC, CD74, SERPINE1, CCR5, TEK, RUNX1, MX2, IFIT1, COL1A1, CXCL14, MRC1, CD68, CD14, MX1, LYVE1, HIF1A, LMNA, EMP1, EIF4A1, DHX9, LYVE1, YWHAQ, CD163, VCAM1, MKI67, IFIT1, ICAM1, STAT1, STAT3, TOP2A, S100A6, WARS1, S100A1, SERPINH1, TOP2A, MX1, MX2, CD14, HSPA9, and HSPD1, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0036] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft 13 314164997v1Attorney Docket No: 243735.000437 rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from 1) human genes MS4A1, CD19, AIM2, BANK1, CD79A, TNFRSF13C, BLK, IGHM, IGHD, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, CD3G, THEMIS, CD5, CD6, CD8B, CD8A, KLRG1, GZMK, CST7, GZMH, LEF1, TCF7, SELL, CD27, CD55, CCR7, CD4, CD40LG, CCR2, CCR6, DPP4, CTLA4, FOXP3, IKZF2, RTKN2, IRF4, IL21, IL2RA, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, and MKI67, and 2) porcine genes SPP1, COLEC11, S100A6, NFKBIZ, CLDN1, THBS1, HIF1A, STMN1, ICAM1, TNFRSF1B, CXCL14, IL1RL1, NREP, C3, CXCL2, C4A, LYZ, S100A6, S100A11, MX1, MX2, IL33, HIF1A, PDGFRB, PECAM1, STAT3, IL33, RGS5, CD163, C3, VCAM1, TNC, CD74, SERPINE1, CCR5, TEK, RUNX1, MX2, IFIT1, COL1A1, CXCL14, MRC1, CD68, CD14, MX1, LYVE1, HIF1A, LMNA, EMP1, EIF4A1, DHX9, LYVE1, YWHAQ, CD163, VCAM1, MKI67, IFIT1, ICAM1, STAT1, STAT3, TOP2A, S100A6, WARS1, S100A1, SERPINH1, TOP2A, MX1, MX2, CD14, HSPA9, and HSPD1, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0037] In some embodiments, the method further comprises step c) (i) determining that the subject has a xenograft rejection or is at a risk of a xenograft rejection when the expression levels of at least one of the genes determined in step (a) are increased as compared to the control by 1.5-fold or more; or (ii) determining that the subject does not have a xenograft rejection or is not at a risk of a xenograft rejection when the expression levels of at least one of the genes determined in step (a) are decreased, not increased or increased by less than 1.5-fold as compared to the control.

[0038] In some embodiments, the control is a predetermined value or a value determined from a sample taken from the subject before the xenograft transplantation. In some embodiments, the control may be a value determined from a sample taken from the subject at a quiescent timepoint post xenograft transplant where there are nonrejection tractors. 14 314164997v1Attorney Docket No: 243735.000437

[0039] In some embodiments, the control is a predetermined value or a value determined from a sample taken from the xenograft before the xenograft transplantation. In some embodiments, the control may be a value determined from a sample taken from the xenograft at a quiescent timepoint post xenograft transplant where there are nonrejection tractors.

[0040] In some embodiments, the method further comprises administering to the subject a treatment that targets plasma cells and / or a complement inhibitory agent, when the subject is determined to have a xenograft rejection or is at a risk of a xenograft rejection.

[0041] In some embodiments, the method further comprises administering to the subject a treatment that targets T cells when the subject is determined to have a xenograft rejection or is at a risk of a xenograft rejection.

[0042] In some embodiments, the method further comprises administering to the subject a treatment that targets plasma cells, a treatment that targets T cells, a complement inhibitory agent, or a combination thereof, when the subject is determined to have a xenograft rejection or is at a risk of a xenograft rejection.

[0043] In some embodiments, the treatment that targets plasma cells is plasmapheresis.

[0044] In some embodiments, the treatment that targets T cells is rabbit anti-thymocyte globulin (rATG).

[0045] In some embodiments, wherein the complement inhibitory agent is a C3 inhibitor.

[0046] In some embodiments, the method further comprises administering an immunosuppressive agent to the subject when the subject is determined to have a xenograft rejection or is at a risk of a xenograft rejection.

[0047] In some embodiments, the subject has received a kidney, heart, lung, liver, bone marrow, pancreas, or islet cell transplantation from a porcine donor.

[0048] In some embodiments, the expression levels are determined based on RNA expression, protein expression, epigenetic regulation, or a combination thereof.

[0049] In some embodiments, the expression levels are determined using RNA sequencing, targeted RNA panel, a quantitative PCR assay, an antibody-based method, an epigenetic assay, a single-cell technology, a spatial transcriptomics technology, or a multiplexed approach combining RNA and protein measurements.

[0050] In some embodiments, the antibody-based method is flow cytometry, immunohistochemistry, or enzyme-linked immunosorbent assay (ELISA). 15 314164997v1Attorney Docket No: 243735.000437

[0051] In some embodiments, the single-cell technology is single-cell RNA sequencing (scRNA-seq) or cellular indexing of transcriptomes and epitopes (CITE-seq).

[0052] In some embodiments, the sample is collected from the subject 3 days after the xenograft transplantation.

[0053] In some embodiments, the method comprises obtaining two or more samples from the subject at different time points after the xenograft transplantation and repeating the method for each sample.

[0054] In another aspect, provided herein is a kit comprising: 1) one or more sets of probe nucleic acids useful for detecting two or more genes selected from: i. human genes MS4A1, CD19, AIM2, BANK1, CD79A, TNFRSF13C, BLK, IGHM, and IGHD; ii. human genes XBP1, MZB1, TNFRSF17, CD27, TENT5C, POU2AF1, PRDM1, NUGGC, and SDC1; iii. human genes KLRC1, GZMB, TRDC, KLRF1, and GNLY; iv. human genes LYZ, MRC1, STAB1, SLCO2B1, F13A1, CD163, MSR1, SLC40A1, and CD14; v. human genes IRF7, TLR7, TLR9, MYD88, and STAT1; vi. human genes PLD4, CLEC4C, LILRA4, TPM2, MZB1, SCT, IRF4, and SMPD3; vii. human genes STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, and CLEC10A; viii. human genes MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, and IFIH1; ix. human genes CD3G, THEMIS, CD5, and CD6; x. human genes CD8B, and CD8A; xi. human genes KLRG1, GZMK, CST7, and GZMH; xii. human genes LEF1, TCF7, SELL, CD27, CD55, and CCR7; xiii. human genes CD4, CD40LG, CCR2, CCR6, DPP4; xiv. human genes CTLA4, FOXP3, IKZF2, RTKN2, IRF4, IL21, and IL2RA; xv. human genes ITGAE, CD38, TNFRSF9, and MKI67; xvi. human genes GZMA, PRF1, and FASLG; 16 314164997v1Attorney Docket No: 243735.000437 xvii. human genes TOP2A, TYMS, and MKI67; xviii. human genes GBP1, IRF1, TAP1, WARS1, and IDO1; xix. human genes CLEC10A, CD1C, FCER1A, CD1E, CD1D, and CCR2; xx. human genes CSF3R, FCGR3B, FPR1, ALPL, MGAM, CXCR1, MXD1, CXCR2; xxi. human genes MS4A1, CD19, AIM2, BANK1, CD79A, TNFRSF13C, BLK, IGHM, IGHD, XBP1, MZB1, TNFRSF17, CD27, TENT5C, POU2AF1, PRDM1, NUGGC, SDC1, KLRC1, GZMB, TRDC, KLRF1, GNLY, LYZ, MRC1, STAB1, SLCO2B1, F13A1, CD163, MSR1, SLC40A1, CD14, IRF7, TLR7, TLR9, MYD88, STAT1, PLD4, CLEC4C, LILRA4, TPM2, MZB1, SCT, IRF4, SMPD3, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, CD3G, THEMIS, CD5, CD6, CD8B, CD8A, KLRG1, GZMK, CST7, GZMH, LEF1, TCF7, SELL, CD27, CD55, CCR7, CD4, CD40LG, CCR2, CCR6, DPP4, CTLA4, FOXP3, IKZF2, RTKN2, IRF4, IL21, IL2RA, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, MKI67, GBP1, IRF1, TAP1, WARS1, IDO1, CLEC10A, CD1C, FCER1A, CD1E, CD1D, CCR2, CSF3R, FCGR3B, FPR1, ALPL, MGAM, CXCR1, MXD1, and CXCR2; xxii. human genes XBP1, MZB1, TNFRSF17, CD27, TENT5C, POU2AF1, PRDM1, NUGGC, SDC1, KLRC1, GZMB, TRDC, KLRF1, GNLY, LYZ, MRC1, STAB1, SLCO2B1, F13A1, CD163, MSR1, SLC40A1, CD14, IRF7, TLR7, TLR9, MYD88, STAT1, PLD4, CLEC4C, LILRA4, TPM2, MZB1, SCT, IRF4, SMPD3, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, MKI67, GBP1, IRF1, TAP1, WARS1, IDO1, CLEC10A, CD1C, FCER1A, CD1E, CD1D, CCR2, CSF3R, FCGR3B, FPR1, ALPL, MGAM, CXCR1, MXD1, and CXCR2; xxiii. human genes MS4A1, CD19, AIM2, BANK1, CD79A, TNFRSF13C, BLK, IGHM, IGHD, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, 17 314164997v1Attorney Docket No: 243735.000437 IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, CD3G, THEMIS, CD5, CD6, CD8B, CD8A, KLRG1, GZMK, CST7, GZMH, LEF1, TCF7, SELL, CD27, CD55, CCR7, CD4, CD40LG, CCR2, CCR6, DPP4, CTLA4, FOXP3, IKZF2, RTKN2, IRF4, IL21, IL2RA, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, and MKI67; xxiv. porcine genes SPP1, COLEC11, S100A6, NFKBIZ, CLDN1, THBS1, HIF1A, STMN1, ICAM1, TNFRSF1B, CXCL14, IL1RL1, and NREP; xxv. porcine genes C3, CXCL2, C4A, LYZ, S100A6, S100A11, MX1, MX2, IL33, and HIF1A; xxvi. porcine genes PDGFRB, PECAM1, STAT3, IL33, RGS5, CD163, C3, VCAM1, TNC, CD74, SERPINE1, CCR5, TEK, RUNX1, MX2, IFIT1, COL1A1, CXCL14, MRC1, CD68, CD14, MX1, and LYVE1; xxvii. porcine genes HIF1A, LMNA, EMP1, EIF4A1, DHX9, LYVE1, YWHAQ, CD163, VCAM1, MKI67, IFIT1, ICAM1, STAT1, STAT3, TOP2A, S100A6, WARS1, S100A1, SERPINH1, TOP2A, MX1, MX2, CD14, HSPA9, and HSPD1; and / or xxviii. porcine genes SPP1, COLEC11, S100A6, NFKBIZ, CLDN1, THBS1, HIF1A, STMN1, ICAM1, TNFRSF1B, CXCL14, IL1RL1, NREP, C3, CXCL2, C4A, LYZ, S100A6, S100A11, MX1, MX2, IL33, HIF1A, PDGFRB, PECAM1, STAT3, IL33, RGS5, CD163, C3, VCAM1, TNC, CD74, SERPINE1, CCR5, TEK, RUNX1, MX2, IFIT1, COL1A1, CXCL14, MRC1, CD68, CD14, MX1, LYVE1, HIF1A, LMNA, EMP1, EIF4A1, DHX9, LYVE1, YWHAQ, CD163, VCAM1, MKI67, IFIT1, ICAM1, STAT1, STAT3, TOP2A, S100A6, WARS1, S100A1, SERPINH1, TOP2A, MX1, MX2, CD14, HSPA9, and HSPD1; or any combination of the genes listed above, and 2) optionally, packaging and / or instructions for using the same. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 shows study design and sampling timeline. For both decedents, left and right ventricle tissue samples were obtained 66 h post-transplantation for snRNA-seq and spatial transcriptomic analyses. Peripheral blood samples were collected at 6-h intervals for comprehensive analysis, including metabolomic, proteomic, lipidomic, cytokine profiling, bulk 18 314164997v1Attorney Docket No: 243735.000437 RNA-seq, scRNA-seq and flow cytometry. Specifically, for D2, tissue samples at 66 h were analyzed via scRNA-seq and bulk RNA-seq. For D1, blood samples at 64 h, 65 h and 65.5 h were exclusively collected. The figure’s lower section illustrates the timeline of blood assay execution post-transplantation. The timing at which each assay from blood was carried out is indicated with a circle for sampling from both decedents and diamonds or triangles for sampling from only D1 or D2, respectively. Routine clinical measurements including INR, ALT and AST, in addition to arterial blood gases, comprehensive metabolic panels, complete blood counts, lactate dehydrogenase and troponin levels were measured via blood. This figure was created with BioRender.

[0056] Figures 2A-H show transcriptomic signature of PBMCs following transplantation. Figures 2A-C show single-cell RNA-seq derived proportion (percentages) of the indicated cell types at the indicated time points for D1 (left) and D2 (right) in all PBMC cell types (Figure 2A), T / NK cells subtypes (Figure 2B) and B cells (Figure 2C). Percentages are calculated based on the total number of cells in each sample. Figures 2D-F show bulk RNA-seq expression of cell-type specific markers, to validate scRNA-seq based cell-type proportions (shown on the left for T / NK and B cells, in Figure 2D and Figure 2F, respectively). For bulk RNA-seq, min– max normalized expression (transcript per million (TPM), length normalized) from B and NK / T cell marker genes (Figures 18I-J) were averaged for each sample (shown on the right in Figure 2D and Figure 2F, respectively) and for marker genes of CD8+and CD4+T cells in Figure 2E. Figure 2G shows validation of the proportions of different cell types using flow cytometry. PBMCs were subdivided based on protein expression into NK cells (CD56+), CD4+T cells (CD56−CD3+CD4+CD8−), CD8+T cells (CD56−CD3+CD8+CD4−), CD19+B cells (CD56−CD3−CD19+) and plasmablast B cells (CD56−CD3−CD19+CD27+CD38+). Figure 2H shows the top 20 enriched pathways (GSEA) in D1 from the bulk RNA-seq DEA. The gray scale depicts the normalized enrichment score (NES) indicating negative and positive scores. A white star denotes that the false discovery rate (FDR) is below 0.05 and the dot size denotes the negative logarithm of the FDR.

[0057] Figures 3A-D show integration of transcriptomic, proteomic, metabolomic, lipidomic and cytokine analyses. Figures 3A-B show integrative clustering of bulk omics and cytokines using fuzzy c-means clustering across all time points. Normalized multi-omics analyte levels revealed trends of upregulation from 42 h onward post-xenotransplant, particularly evident in D1 19 314164997v1Attorney Docket No: 243735.000437 and correlated with clinical variables INR, AST and ALT in the time course. Shown are data for D1 (Figure 3A) and D2 (Figure 3B). The different omics are in greyscale according to the legend. Figure 3C shows pathways that are significantly associated with the cluster of interest. The highlighted cluster was one of an optimal number of clusters based on identifying the minimum distance between cluster centroids during soft clustering. Hits pertains to the number of analytes from the cluster of interest that are involved in the significant pathway. Figure 3D shows temporal distribution of cytokine levels (IL-6, IL-8, IL-10 and IL-13) (indicated by the line) and analyte upregulation in the cluster of interest, for both decedents.

[0058] Figures 4A-L show xenograft snRNA-seq analysis. Figure 4A shows a cell-type 2D map of pig nuclei snRNA-seq data, showing all xenograft samples (both decedents) integrated with the publicly available (Andrijevic, et al., 2022) in vivo pig heart snRNA-seq data. LEC, lymphatic endothelial cells; L2, lymphoid cells 2; L3, lymphoid cells 3; L4, lymphoid cells 4; MP, macrophages / monocytes; DIV, dividing cells; SC, Schwann cells. Figure 4B shows cell- type percentage distribution. D1 LV / RV and D2 LV / RV denote the left and right ventricles in D1 and D2, respectively. PMI times of 0 h, 1 h and 7 h indicate ischemia durations, as per the publicly available in vivo pig heart snRNA-seq data (Andrijevic, et al., 2022). ‘ECMO’ and ‘OrganEx’ are reperfusion conditions within this dataset. Figure 4C shows transcriptomic 2D map of human nuclei from the xenograft (snRNA-seq) by cell type. Figure 4D shows human NK / T nuclei count distribution. Figure 4E shows the number of significantly (Padj < 0.05) overexpressed (log fold change (FC) > 0) and underexpressed (logFC < 0) DEGs, comparing each condition to 0 h of ischemia. DEA was performed using DESeq2 on Pseudobulk raw counts, calculated independently for each cell type per sample. The logFC and adjusted P value (Wald test P value, two-tailed, adjusted with the Benjamini–Hochberg method) were obtained directly from the DESeq2 DEA output. Figures 4F-G show enrichment of biological pathways in CMs (Figure 4F) and FBs (Figure 4G) from DE results. The top pathways enriched in D1 xenograft versus control are shown, with enrichments calculated using GSEA of DESeq2 results. Greyscale depicts the NES indicating negative and positive scores. A white star denotes an FDR below 0.05 and the dot size denotes the negative logarithm of the FDR. Figures 4H-J shows subclustering analysis of FBs (all samples integrated). Figure 4H shows a two-dimension map of FBs, sorted by their clusters. Figure 4I shows cell cycle score distribution by subclusters. Figure 4J shows proportion distribution for subclusters FB-4 and FB-6. Percentages based on total 20 314164997v1Attorney Docket No: 243735.000437 number of FBs in each sample. Figure 4K shows GSEA of cluster FB-4 marker genes. Figure 4L shows differential strength interaction analysis using CellChat cell–cell communication analysis.

[0059] Figures 5A-M show spatial transcriptomics analysis that highlights vascular remodeling and ischemia. Figure 5A shows spatial transcriptomic slide, mapped with spots corresponding to arterial signal. Clustering analysis was performed on the spatial transcriptomic data, based solely on expression information. Spatial clusters expressing endothelial and vascular markers (clusters 5, 7, 8 and 9) are indicated in the left ventricle of D1 (left) and the right ventricle of D2 (right). Each slide has two technical replicates (A and B). D1-LV-A, D1, left ventricle, replicate A; D2-RV-A, D2, right ventricle, replicate A. Scale bar, 1 mm. Figure 5B shows a close up of the histology of the left ventricle of D1 (corresponding to the area bounded by the black square in Figure 5A, left). Scale bar, 200 µm. Figure 5C shows a close up of the histology of the right ventricle of D2 (corresponding to the area bounded by the black square in Figure 5A, right). Scale bar, 200 µm. Figures 5D-E show spatial transcriptomics data after deconvolution, based on the snRNA-seq signal for SMCs (Figure 5D) and FBs (Figure 5E). Scale bar, 1 mm. Figure 5F shows expression of selected marker genes of cluster 7, across all spatial clusters. Figure 5G shows expression of selected marker genes of cluster 7, across all spatial transcriptomics samples. Figure 5H shows cell–cell interaction analysis of the IL-1 signaling network across cell types (based on snRNA-seq data), in D1-LV. Figure 5I shows analysis of IL33 signaling between cell types in D1-LV (based on snRNA-seq) data. Figure 5J shows H&E staining of pig xenograft endomyocardial biopsies from D1 showing ‘lifting’ of endothelium (white arrow), with few inflammatory cells present (black and grey arrow). Scale bar, 1 mm. Figure 5K shows EM micrograph from a biopsy of the xenograft from D1, showing endothelial cell swelling (white arrow) and sarcolemma disruption (grey arrow). Scale bar, 5 µm. Figure 5L shows DE of hypoxia- and damage-associated genes based on snRNA-seq (pseudobulk) data in FBs, CMs and VECs. Figure 5M shows expression of the genes shown in Figure 5L in SMCs, across conditions. For dot-plots, dot size reflects the percentage of nuclei in each group with gene expression above zero. Dot saturation displays each group’s mean gene expression, min–max scaled.

[0060] Figures 6A-6J show PCXD and vascular remodeling in the xenograft. Figure 6A shows DE of PCXD-related genes in snRNA-seq data for VECs, CMs, FBs and MPs. Dot size 21 314164997v1Attorney Docket No: 243735.000437 reflects the −log10(FDR) from pseudobulk DESeq results and the saturation reflects log2FC. Significance (Padj < 0.05) is denoted by a black star. The logFC and adjusted P value (Wald test P value, two-tailed, adjusted with the Benjamini–Hochberg method) were obtained directly from the DESeq2 DEA output. Genes labeled as PCXDplus were previously described (Byrne, et al., 2011) as being overexpressed in PCXD, whereas those labeled as PCXDminus were underexpressed. Figure 6B shows top enrichments in D1 for VECs from the pseudobulk-based DEA. Figures 6C-F show subclustering analysis of VECs (all samples integrated). Figure 6C shows low-dimensional embedding representation of VECs, sorted by their subclusters. Figure 6D shows vascular subtype markers. Figure 6E shows proportion distribution of subclusters VEC-4 and VEC-9 across samples. Figure 6F shows GSEA of cluster VEC-4 marker genes. Figures 6G-J show subclustering analysis of PERs and SMCs (all samples integrated). Figure 6G shows low-dimensional embedding representation of SMC–PER subclusters. Figure 6H shows cell cycle score distribution across clusters. Figure 6I shows proportion distribution of subclusters SMC–PER-4 and SMC–PER-6 across samples. Figure 6J shows GSEA of cluster SMC–PER-4 marker genes.

[0061] Figures 7A-7L show detailed PBMC scRNA-seq data analysis. For dot-plots, dot size reflects the percentage of cells in each group with gene expression above zero. Dot saturation displays each group's mean gene expression, min-max scaled. Figure 7A shows low dimension embedding representation of the PBMC scRNA-seq data, sorted by cell types. HSC-CD34+: Hematopoietic stem cells. Figure 7B shows expression distribution of selected marker genes of the main cell types, basis for their identification. Figure 7C shows low dimension embedding representation of the T / NK cells, sorted by subtype. NK: Natural Killer cells, CD8 T: CD8+T cells, CD4 T: CD4+T cells, Treg: T-regulatory cells. Figure 7D shows expression distribution of selected marker genes of the subtype, basis for their identification. Figures 7E-F show further dissection of CD8 T (Figure 7E) and CD4 T (Figure 7F) cells. Figure 7G shows low dimension embedding representation of the B cells, sorted by subtype. Figure 7H shows expression distribution of selected marker genes of the subtype, basis for their identification. Figure 7I shows proportion differences across time points, for both decedents, in selected cell types and subtypes (labeled on each plot). Percentages are calculated based on the total number of cells (all cell types) in each sample. Figures 7J-K show genes selected as highly specific for the B cell (Figure 7J) and T / NK (Figure 7K) population, used for bulk RNA-seq proportion validation in 22 314164997v1Attorney Docket No: 243735.000437 Figure 1. Figure 7L shows a summary of DEG analysis from PBMC scRNA-seq. Number of overexpressed genes (left, LFC > 0 and padj < 0.05) and underexpressed genes (right, LFC < 0 and padj < 0.05). The LFC and adjusted p value (Wald test p value, two-tailed, adjusted with the Benjamini–Hochberg method) were obtained directly from the DESeq2 DEA output.

[0062] Figures 8A-D show multi-omics DE integration. Comparative temporal DEA of individual omics analyses. Bulk transcriptomics, proteomics, lipidomics and metabolomics for blood samples of two pig heart to human xenotransplantations spanning 26 time points are illustrated. The early phase encompasses the 6 hr and 12 hr post-transplant time points, the mid- phase includes 18 hr to 36 hr post-transplant, while the late phase comprises all time points beyond 36 hr. For each panel, the x-axis represents the fold change in log2 scale, and the y-axis depicts the -log10 transformed unadjusted p value. These analyses were run individually for decedent 1 (top) and decedent 2 (bottom). The individual omics are as follows: Figure 8A shows transcriptomics. DEA analysis using DESeq2 is limited to genes whose average expression exceeds 4 counts across samples. Genes with significant expression changes (FDR<0.05) are shown in dark grey. Only the top 10 most significant genes were labeled due to space limitation. The LFC and adjusted p value (Wald test p value, two-tailed, adjusted with the Benjamini– Hochberg method) were obtained directly from the DESeq2 DEA output. Figure 8B shows proteomics. Proteins were present in more than half of the samples, yielding a total of 895 proteins. Proteins with significant changes (FDR < 0.05) are shown in dark grey. Figure 8C shows metabolomics. DEA was performed for 459 metabolites. Metabolites with significant changes (FDR < 0.05) are shown in dark grey. Figure 8D shows lipidomics. The analysis included 720 lipids. Lipids showing significant changes (FDR < 0.05) are shown in dark grey. In the metabolomics and lipidomics panels, only the top features are highlighted with the molecule names. In all panels, molecules without significant changes are represented in light gray. Corrected p-values (FDR, from two-tailed moderated t-tests, adjusted using the Benjamini– Hochberg method) and log fold changes (LFC) were derived from limma outputs.

[0063] Figures 9A-B show intersection between clinical measurements and multi-omics integration. Figure 9A shows overlap of clinical blood markers (Lactate, Troponin, Fibrinogen, Ferritin, SBP, BNP, DBP, IL-2R) and multi-omics integration-based cluster of analytes upregulated in D1. The blood marker level is shown in bold line. For each marker, decedent 1 measures are shown on the top graph, decedent 2 on the bottom. Figure 9B shows cardiac 23 314164997v1Attorney Docket No: 243735.000437 output, cardiac index measurements and vasopressor dose (bottom graphs) put in perspective with the multi-omics integration-based cluster of analytes upregulated in D1 (top graph). Decedent 1 is shown on the left and decedent 2 on the right.

[0064] Figures 10A-I show xenograft snRNA-seq based gene expression dissection. Figures 10A-B show top marker genes (Wilcoxon rank-sum) for human nuclei (Figure 10A) and pig nuclei (Figure 10B) in the xenograft snRNA-seq data. Dot size reflects the percentage of nuclei in each group with gene expression above zero. Dot saturation displays each group's mean gene expression, min-max scaled. Figure 10C shows cell-type proportions for pig nuclei. Figure 10D shows cell-type proportion of human nuclei. Figure 10E shows human T / NK subtypes markers expression within xenograft T / NK human population, across samples. Figure 10F shows NK / T cell activity markers expression across samples. Figures 10G-I show expression distribution of lead genes in D1 which contributed to the Reactome Interleukin Signaling enrichment in CM (Figure 10G), NIK to Non-canonical NF-kB signaling in CM (Figure 10H), and Bioplanet 2019 DNA replication in FB (Figure 10I). Dot size reflects the -log10(FDR) from DESeq result, saturation reflects log2FC. Significance (padj < 0.05) is denoted by a black star. The LFC and adjusted p value (Wald test p value, two-tailed, adjusted with the Benjamini–Hochberg method) were obtained directly from the DESeq2 DEA output.

[0065] Figures 11A-H show spatial transcriptomics composition. Figure 11A shows spatial transcriptomic slide mapped with each spatial cluster, in all samples. Scale bar: 1mm. Figures 11B-C show spatial transcriptomics cell type deconvolution (Cell2location) signal, min–max scaled, across Spatial clusters (Figure 11B), Visium samples (Figure 11C), and their combination (Figure 11D). Figure 11E shows cluster proportion distribution across samples. Figure 11F shows spatial distribution of IL1RL1 expression, represented by the grey scale (log norm expression). Scale bar: 1mm. Figure 11G shows spatial distribution of IL33 expression, represented by the grey scale (log norm expression). Scale bar: 1mm. Figure 11H shows snRNA-seq based cell–cell communication inference results for IL33 signaling.

[0066] Figures 12A-J show xenograft tissue imaging. Figures 12A-D show H&E staining of Pig Xenograft Endomyocardial Biopsies from decedent 1 (Figures 12A-B) and decedent 2 (Figures 12C-D). Scale bar: 1mm. Figure 12A shows contraction band necrosis, with interstitial edema and endothelial swelling of small interstitial capillary. Figure 12B shows endothelial swelling of intramyocardial muscular artery and detached endothelial cells with perivascular 24 314164997v1Attorney Docket No: 243735.000437 edema. Figure 12C shows endothelial swelling in the intramyocardial muscular artery. Figure 12D shows endothelial swelling and lifting of small interstitial capillary. Figures 12E-K show electron microscopy (EM) images of the xenograft samples. Figure 12E shows electron microscopy image of D2 transplanted xenograft. Scale bar: 5 µm. Figure 12F shows EM image of D1 transplanted xenograft. Ultrastructural changes in the capillary endothelial cells are characterized by endothelial swelling with narrowing of the capillary lumen and enlarged vacuoles in the cytoplasm. There is perivascular edema resulting in separation of the collagen fibrils. The myocytes have an intact sarcolemma; however, the cytoplasm shows decrease to loss of myofibrils under the sarcolemma. Scale bar: 5 µm. Figure 12G shows D1: accumulation of mitochondria (grey arrow) as a result of degenerated myofibrils, widened disorganized Z-lines (black arrow) in degenerating myofibrils, and swollen interstitial capillary endothelial cell (white arrow). Scale bar: 10 µm. Figure 12H shows D1: degenerating myofibrils (black arrow), swollen endothelial cells in intramyocardial capillary (grey arrow), and sarcolemma disruption (white arrow). Scale bar: 5 µm. Figure 12I shows D1: endothelial cell swelling with near collapse in an intramyocardial capillary lumen. Scale bar: 5 µm. Figure 12J shows D2: endothelial swelling (white arrow). Scale bar: 5 µm.

[0067] Figures 13A-J show graft PCXD and hypoxia signal. Figure 13A shows expression of genes of interest and hypoxia related genes across Visium samples (within spots from clusters 7 and 8). Figure 13B shows top enrichments for Visium cluster 7 markers (from GSEA on Wilcoxon rank-sum based marker discovery). Saturation depicts the NES, indicating negative and positive scores. When the false discovery rate (FDR) is below 0.05, numbers are displayed, denoting the negative logarithm of the FDR. Figure 13C shows top enrichments for D1-LV-A sample, from Visium data (from GSEA on Wilcoxon rank-sum based DE, at sample level, each sample vs. the others together). Figures 13D-E show hypoxia and damage-associated genes expression changes in snRNA-seq. With DEA (pseudobulk) signals in dividing cells, LEC, L2, MP and SMC and VEC (Figure 13D), and across cell types (Figure 13E). Figures 13F-J show expression of genes associated with PCXD in the spatial transcriptomics and snRNA-seq data. Dot size reflects the percentage of spots in each group with gene expression above zero. Dot saturation displays each group’s mean gene expression, min–max scaled. Genes labeled as PCXDplus were previously described (Byrne, et al., 2011) as being overexpressed in PCXD, while PCXDminus as underexpressed. Figure 13F shows expression distribution across spatial 25 314164997v1Attorney Docket No: 243735.000437 clusters. Figure 13G shows expression distribution within all spots, between samples. Figure 13H shows expression distribution within vascular spatial clusters (only spots of cluster 8 and 7 are included), between samples. Figure 13I shows expression distribution across cell types (snRNA-seq). Figure 13J shows expression distribution across conditions (snRNA-seq).

[0068] Figures 14A-C show further dissection of vascular remodeling in xenografts. Figure 14A shows top enrichments in D1 for PER from pseudobulk based DE analysis. Figure 14B shows top enrichments for SMC in D1 left ventricle. Here, GSEA was performed from Wilcoxon rank-sum test DE analysis at the nuclei level (each condition vs. non-ischemic in vivo pig cardiac tissue, within snRNA-seq, selecting for SMC). Saturation depicts the NES, indicating negative and positive scores. A white star denotes a false discovery rate (FDR) is below 0.05, while dot size denotes the negative logarithm of the FDR. Figure 14C shows expression distribution of lead genes in D1 which contributed to the MSigDB Hallmark 2020 EMT enrichment (top), MSigDB Myc Targets V1 enrichment (middle) and MSigDB TNF-alpha Signaling via NF-kB (bottom), all in VEC. Dot size reflects the -log10(FDR) from DESEQ result, saturation reflects log2FC. Significance (padj < 0.05) is denoted by a black star. The LFC and adjusted p value (Wald test p value, two-tailed, adjusted with the Benjamini–Hochberg method) were obtained directly from the DESeq2 DEA output.

[0069] Figures 15A-G show lymphatic endothelial cells (LECs) dissection. Figure 15A shows top enrichments in D1 for LECs from pseudo-bulk based DE analysis. Figures 15B-G show LEC sub-clustering analysis. Figure 15B shows UMAP of LECs sorted by spatial subclusters, and dotplot of cell cycle score. Figure 15C shows correlation of subcluster expression signal. Figure 15D shows cell cycle score distribution. Figure 15E shows proportion distribution of subclusters LEC-3 and LEC-6 across samples. Figure 15F shows gene set enrichment analysis of subcluster LEC-3 marker genes. Figure 15G shows GSEA analysis of LEC-3 DEA results.

[0070] Figures 16A-I show dividing cells dissection. Figure 16A shows subtyping and re- embedding of the dividing cells population, low dimensional embedding representation of the dividing cells sorted by their associated cell types. Cells belonging to the dividing group in Figure 3A were isolated and re-clustered. Marker gene expression was used to label them. Figure 16B shows top marker based GSEA results in DIV-PER and Figure 16C shows top marker based GSEA results in DIV-VEC2. Saturation depicts the NES, indicating negative and positive scores. A white star denotes a false discovery rate (FDR) is below 0.05, while dot size 26 314164997v1Attorney Docket No: 243735.000437 denotes the negative logarithm of the FDR Figure 16D shows proportion distribution of dividing cells subtypes between samples and conditions. Percentages are calculated based on the total number of cells, from all cell types. Figure 16E shows top marker genes of the DIV-VEC2 cells population. Figures 16F-I show expression of ICAM1, P-selectin (SELP), E-selectin (SELE), across all cell types (Figure 16F) Pseudobulk level DE results in VEC population (Figure 16G), dividing cells subtypes (Figure 16H), across conditions in DIV-VEC1 and DIV-VEC2 (Figure 16I).

[0071] Figures 17A-C show quality control of decedent PBMC scRNA-seq. Figure 17A shows distribution of the main CellRanger sample-level QC metrics, across all PBMC scRNA- seq samples. Each sample makes a data point (black dots). The quartiles of that distribution are represented within the box (median as the center bar), while the distribution's remaining data points are indicated by the whiskers, extending from the box. Points considered "outliers" are those beyond 1.5 times the interquartile range (IQR) and are not included within the whiskers' span. N = 26 scRNA-seq samples (14 for D1, 12 for D2). Figures 17B-C show distribution of cell level QC metrics before (Figure 17B) and after (Figure 17C) filtering.

[0072] Figures 18A-B show additional flow cytometry data. Figure 18A shows flow cytometry gating scheme for one representative sample. Light grey boxes indicate analyzed populations, and dark grey boxes indicate subsets that were further subdivided. Figure 18B shows monocytes identified as CD56-CD3-CD19-HLA-DR+cells and subdivided into classical (CD14+CD16-), non-intermediate (CD14+CD16+), and non-classical subsets (CD14-CD16+).

[0073] Figures 19A-B show pig and human nuclei categorization. Number of unique molecular indices (UMI) counts mapping to the human (x-axis) or pig (y-axis) genome from the xenograft snRNA-seq, resulting from the CellRanger ‘Barnyard’ experiment multiple genome aligner. Nuclei are then assigned a genome based on that distribution, and cross-species multiplets are called. Figure 19A shows linear scale. Figure 19B shows logarithmic scale. This partition was used to separate pig and human nuclei in the Xenograft snRNA-seq, for downstream analysis.

[0074] Figures 20A-F show quality control of heart xenograft sn-RNAseq data. Figure 20A shows distribution of the main CellRanger sample-level QC metrics, across all heart xenograft sn-RNAseq samples (pig genome alignment). Each sample makes a data point (black dots). The quartiles of their distribution are represented within the box (median as the center bar), while the 27 314164997v1Attorney Docket No: 243735.000437 distribution's remaining data points are indicated by the whiskers, extending from the box. Points considered "outliers" are those beyond 1.5 times the interquartile range (IQR) and are not included within the whiskers' span. N = 4 snRNA-seq samples (D1-LV, D1-RV, D2-LV, D2- RV). Figure 20B shows cell level QC metrics before and after filtering for pig (top) and human (bottom) nuclei. Figures 20C-D show human transgene expression levels in the pig heart snRNA-seq data. Expression is shown among the heart xenograft samples, and, for negative control, the integrated public pig dataset (Andrijevic, et al., 2022) (nuclei separated by condition), non-normalized (Figure 20C), average expression per cell, min-max scaled (Figure 20D). Figures 20E-F show human transgene expression levels in the xenotransplant Visium Spatial Transcriptomics data, spots grouped by Spatial Clusters (Figure 20E), and by sample (Figure 20F).

[0075] Figures 21A-F show top enrichments from cell type marker gene based GSEA for pig nuclei. Saturation depicts the normalized enrichment score (NES), indicating negative and positive scores. When the false discovery rate (FDR) is below 0.05, a white star is plotted, while dot size denotes the negative logarithm of the FDR. Figure 21A shows CM, Figure 21B shows SMC, Figure 21C shows VEC, Figure 21D shows LEC, Figure 21E shows MP, and Figure 21F shows FB.

[0076] Figures 22A-22G show differential expression analysis of heart xenograft pig nuclei. Figures 22A-F show top enriched pathways (from GSEA analysis of DE results), in CM (Figures 22A-C) and in FB (Figures 22D-F), for Ecmo, Ischemia 7 hr and decedent 2 conditions. Saturation depicts the normalized enrichment score (NES), indicating negative and positive scores. When the false discovery rate (FDR) is below 0.05, a white star is plotted, while dot size denotes the negative logarithm of the FDR. Figure 22G shows expression distribution of lead genes in decedent 1 which contributed to specific pathways in GSEA. Dot size reflects the - log10FDR from DESEQ result, saturation reflects log2FC. Significance (padj < 0.05) is denoted by a black star. The LFC and adjusted p-value (Wald test p-value, twotailed, adjusted with the Benjamini Hochberg method) were obtained directly from the DESeq2 DEA output.

[0077] Figures 23A-23F shows fibroblast sub-clustering analysis. Figure 23A shows top 5 marker genes (Wilcoxon rank sum test) for FB subclusters. Figure 23B shows top 50 marker genes (Wilcoxon rank sum test) for subcluster FB4. Figure 23C shows top 50 marker genes (Wilcoxon rank sum test) for subcluster FB2. Figure 23D shows correlation of subcluster 28 314164997v1Attorney Docket No: 243735.000437 expression signal. Figure 23E shows subclusters proportion distribution Figure 23F shows gene set enrichment analysis of subcluster FB2 marker genes.

[0078] Figures 24A-G show cardiomyocytes sub-clustering analysis. Figure 24A shows UMAP of CMs sorted by subclusters. Figure 24B shows correlation of subcluster expression signal. Figure 24C shows gene set enrichment analysis of subcluster CM4 marker genes. Figure 24D shows top 5 marker genes (Wilcoxon rank sum test) for CM subclusters. Figure 24E shows top 50 marker genes (Wilcoxon rank sum test) for subcluster CM2. Figure 24F shows top 50 marker genes (Wilcoxon rank sum test) for subcluster CM4. Figure 24G shows subclusters proportion distribution.

[0079] Figures 25A-B show cell-cell communication analysis from heart xenograft. Number of interactions (Figure 25A) and strength of interactions (Figure 25B) are shown between cell types, across conditions, predicted by CellChat.

[0080] Figures 26A-C show spatial transcriptomics deconvolution with cell2location. For each cell-type, the deconvolution posterior distribution is plotted on the spatial transcriptomics slide. Scale bar: 1 mm. Figure 26A shows D1-LV-B, Figure 26B shows D1-RV-B, and Figure 26C shows D2-RV-B.

[0081] Figures 27A-C show spatial transcriptomics deconvolution with DestVI. For each cell type, the DestVI-predicted cell-type proportions are plotted on the spatial transcriptomics slide. Scale bar: 1 mm. Figure 27A shows D1-LV-B, Figure 27B shows D1-RV-B, and Figure 27C shows D2-RV-B.

[0082] Figures 28A-C show spatial transcriptomics deconvolution signal. Spatial transcriptomics cell type deconvolution (Cell2location) signal, min max-scaled, is shown across Spatial clusters (Figure 28A), Visium samples (Figure 28B), and their combination (Figure 28C). The signal is shown for Cell2location (unscaled), and DestVI (unscaled, left; min-max normalized, right).

[0083] Figures 29A-D show marker genes for spatial transcriptomics clusters of interest. Top 60 marker genes (Wilcoxon rank sum test) for vascular Spatial transcriptomics clusters are shown. Dot size reflects the percentage of spots in each group with gene expression above zero. Dot saturation displays each group's mean gene expression, min-max scaled. Figure 29A shows Cluster 7. Figure 29B shows Cluster 8. Figure 29C shows Cluster 9. Figure 29D shows Cluster 10. 29 314164997v1Attorney Docket No: 243735.000437

[0084] Figures 30A-H show vascular endothelial cells sub-clustering analysis. Figure 30A shows top 5 marker genes (Wilcoxon rank sum test) for VEC subclusters. Figures 30B-D show top 50 marker genes (Wilcoxon rank sum test) for subclusters VEC5 (Figure 30B), VEC4 (Figure 30C), and VEC9 (Figure 30D). Figures 30E-F show gene set enrichment analysis of subclusters VEC5 (Figure 30E) and VEC9 (Figure 30F) marker genes. Figure 30G shows correlation of subcluster expression signal. Figure 30H shows subclusters proportion distribution.

[0085] Figures 31A-G show pericytes and smooth muscle cells sub-clustering analysis. Figure 31A shows top 5 marker genes (Wilcoxon rank sum test) for PER-SMC subclusters. Figure 31B shows top 50 marker genes (Wilcoxon rank sum test) for subcluster PER-SMC4. Figure 31C shows top 50 marker genes (Wilcoxon rank sum test) for subcluster PER-SMC1. Figure 31D shows correlation of subcluster expression signal. Figure 31E shows expression of SMC and PER markers across subclusters. Figure 31F shows gene set enrichment analysis of subcluster PER-SMC1 marker genes. Figure 31G shows subclusters proportion distribution.

[0086] Figures 32A-D show lymphatic endothelial cells sub-clustering analysis. Figure 32A shows top 5 marker genes (Wilcoxon rank sum test) for LEC subclusters. Figure 32B shows top 50 marker genes (Wilcoxon rank sum test) for subcluster LEC2. Figure 32C shows gene set enrichment analysis of subcluster LEC2 marker genes. Figure 32D shows subclusters proportion distribution.

[0087] Figures 33A-D show single-cell RNA-seq analyses of pig-to-human kidney xenotransplantation. Figure 33A shows a schematic overview of the transcriptomic analyses of pig-to-human kidney xenotransplantation. Parts of the figure were created with BioRender. Figure 33B shows unsupervised clustering of the merged single cell transcriptomes across all samples (left) and visualization by cell types (right). UMAP, Uniform Manifold Approximation and Projection (McInnes, et al., 2018). Figure 33C shows UMAP visualization of single cell distribution from each kidney sample. Figure 33D shows a dot plot of marker genes indicating cell-type identity across all cell populations. The saturation intensity and dot size represent average expression level and the percentage of expressed cells, respectively. Endo, endothelial cells; IC_NS, nonspecific intercalated cells; IC_TypeB, Type B intercalated cells, IC_TypeA, Type A intercalated cells; DTC, distal tubule cells; TAL_1, thick ascending limb population 1; 30 314164997v1Attorney Docket No: 243735.000437 TAL_2, thick ascending limb population 2; PT, proximal tubule cells; PT_VIM+, vimentin- positive proximal tubule cells; PT_Prolif, proliferating proximal tubule cells.

[0088] Figures 34A-F show that human NK cells and macrophages infiltrate into porcine kidney xenograft. Figure 34A shows UMAP visualization of human (dark grey) and porcine (light grey) cell distribution. The immune cell cluster is enlarged for detail. Figure 34B shows UMAP visualization of sub-clustered human and porcine immune cell types. Figure 34C shows a heatmap of human-to-porcine raw reads counting ratios (H / P ratio) of macrophage and NK cell marker genes. Figure 34D shows violin plots of interferon-gamma signaling gene expressions in human and porcine immune cell populations in single-cell transcriptome data. Figures 34E-F show xenotransplantation time-resolved gene expression levels (Figure 34E) and human / porcine transcript (H / P) ratio (Figure 34F) of interferon-gamma signaling genes in the longitudinal bulk RNA-seq of xenograft biopsies. Statistical significance is indicated by asterisks above to the violin plots: * for p < 0.05, ** for p < 0.01, *** for p < 0.001, and **** for p < 0.0001.

[0089] Figures 35A-D show identification of rejection signals in porcine endothelial cells and in immune cells. Figures 35A-B show relative gene expression levels of AbMR (Figure 35A) and TCMR (Figure 35B) marker genes over the period of the xenotransplantation. Genes with dramatic expression changes (>2 folds) at the last time-point were shown in a bigger font size relative to other genes. Figures 35C-D show violin plots of AbMR marker gene expression in porcine endothelial cells (Figure 35C) and TCMR marker gene expression (Figure 35D) in immune cells. Gene expression levels were detected in single-cell RNA-seq data. Statistical significance is indicated by asterisks above to the violin plots: * for p < 0.05, ** for p < 0.01, *** for p < 0.001, and **** for p < 0.0001.

[0090] Figures 36A-J show xenotransplantation-associated porcine kidney damage and the activation of a cell proliferation program. Figure 36A shows volcano plots of differentially expressed genes between xenograft and control for the first (left) and second (right) cases of xenotransplantation. Representative genes (biomarkers of kidney-injury and proliferation) were labeled. A few data dots in the plot reached a ceiling value on the y-axis, indicating system’s default lowest p-value. Figure 36B shows violin plots of kidney-injury biomarker expression levels across major cell types in the nephron. Figure 36C shows a UMAP highlight of the proliferating cell population. Figures 36D-E show UMAP visualization of the sub-clustered proliferating cell cluster signified by organismal origin (Figure 36D) and cell cycle phase 31 314164997v1Attorney Docket No: 243735.000437 assignment (Figure 36E). Figure 36F shows ridge plots of top marker genes in cells across G1, S, and G2 phases. Figures 36G-I show gene expression levels of proliferation marker (STMN1, Figure 36G), proximal tubule cell marker (SLC34A1, Figure 36H), and T-cell marker (CD3E, Figure 36I) in the proliferating cell population. The smaller cluster of cells expressing T cell markers but not PTC markers (CD3E+; SLC34A1–) is shown. Figure 36J shows time-resolved gene expression levels of kidney tissue injury marker genes (labeled damage-related) and cell cycle genes (labeled proliferation-related) in longitudinal RNA-seq.

[0091] Figures 37A-E show recipient’s PBMCs showing two waves of immune response expression signatures. Figure 37A shows Uniform Manifold Approximation and Projection (UMAP) visualization of the second kidney xenograft recipient’s PBMC clusters. mono-CD14, Monocytes CD14; mono-CD16, CD16-positive monocytes; M1, macrophage 1; M2, Macrophage 2; NK, natural killer cells; NKT1, natural killer T cells 1; NKT2, natural killer T cells 2; T-CD8, CD8 T cells; T-CD4, CD4 T cells; T-Reg, T Regulatory cells, N.B, naïve B cells; M.B, memory B cells; P.B, plasma B cells; MGK-P, Megakaryocyte Progenitor cells; MGK, Megakaryocytes; RBC, Red blood cells (Erythrocytes). Figure 37B shows cell type proportions of PBMC populations across the six timepoints. Figure 37C shows temporally variable MHC class II genes expression pattern across the period of xenotransplantation in representative antigen presenting cell types. Figures 37D-E show relative gene expression levels of gene sets enriched at 12 hours pXTx (Figure 37D) and 48-53 hours pXTx (Figure 37E) across the period of xenotransplantation in representative cell types.

[0092] Figures 38A-D show violin plots of quality control features for all cell types across each kidney single-cell RNA-seq dataset. Figure 38A shows xenograft 1, Figure 38B shows xenograft 2, Figure 38C shows control kidney 1, and Figure 38D shows control kidney 2 data. Each panel presents the total number of expressed genes (nFeature_RNA, top) and total number of transcripts (nCount_RNA, bottom) of each cell.

[0093] Figures 39A-F show feature plots of marker genes for identifying cell types. Figures 39A-D show UMAP visualization of marker genes used for identifying cell types in kidney single-cell RNA sequencing datasets. The genes correspond to the marker genes in Figure 33D. Figures 39E-F show podocyte marker gene expression levels presented as violin plot (left) across all cell clusters and as scatter plot (right) in the VIM-positive proximal tubule (PT-VIM+) 32 314164997v1Attorney Docket No: 243735.000437 cells. Saturation intensity in the scatter plots indicate marker gene expression levels, with a zoom-in highlight of the podocyte cell group.

[0094] Figures 40A-E show immune cell type characterization and gene function enrichment analyses of the two xenografts. Figures 40A-C show clustering and cell-type identification of immune cells. Feature plots for marker genes for macrophage (CD163, TYROBP) (Figure 40A), NK cell (NKG7, GNLY) (Figure 40B), and T cell (CD3E, CD3G) (Figure 40C) identifies human cells to be macrophages and NK cells, and porcine cells to be NK, NKT, and T cells, respectively. Figure 40D shows gene ontology enrichment analysis for Top 1000 Differentially Expressed Genes (DEG) ranked by average log2 fold change for xenograft 1 (top) and xenograft 2 (bottom). Figure 40E shows KEGG Enrichment Analysis for xenograft 1 (top) and xenograft 2 (bottom).

[0095] Figures 41A-G show violin plots of PBMC single-cell RNA-seq data and the cell type marker genes. Figures 41A-F show PBMCs collected at 0h, 6h, 12h, 24h, 48h, and 53h post- xenotransplantation. Each panel presents the total number of expressed genes (nFeature_RNA, top) and total number of transcripts (nCount_RNA, bottom) of each cell. Figure 41G shows a violin plot visualization of marker genes used for cell type identification in PBMCs. The cell type annotations correspond to Figure 37A.

[0096] Figures 42A-C show gene expression signatures in recipient’s PBMCs across the period of xenotransplantation. Figures 42A-B show gene ontology enrichment of enriched gene sets. Significantly enriched GO term corresponds to the gene sets of cell types at 12 hours pXTx (Figure 42A) and at 48-53 hours pXTx (Figure 42B) presented in Figure 37. Figure 42C shows a dot plot of interferon-gamma expression in PBMCs across the period of the study. NK cells and NKT cells were the main cell types of expression interferon-gamma.

[0097] Figure 43 shows a graphical abstract of the studies performed herein. The figure was made with BioRender.

[0098] Figure 44 shows a study overview. A schematic of the study is shown, indicating the major modalities (top) as well as the tissue and blood timepoints, assays utilized at each respective timepoint, treatments / medications utilized, and clinical microbiology testing performed (bottom) in the 61-day period following the pig-to-human Gal-KO thymokidney xenotransplant. The “CTRL” samples from the 5.1k ST panel data correspond to contralateral pig kidney (only pig cells) and native human kidney (only human cells), which act as positive 33 314164997v1Attorney Docket No: 243735.000437 and negative controls for human cell selection in the analysis herein. BAL: bronchoalveolar lavage, EBV: Epstein-Barr virus, Gal-KO: α-1,3-galactosyltransferase (GGTA1) knockout, HBV: hepatitis B virus, rATG: rabbit anti-thymocyte globulin. Figure generated with BioRender.

[0099] Figures 45A-M show that high-resolution spatial-transcriptional profiling reveals infiltrating human cells in porcine kidneys. Figure 45A shows images illustrating the analytical steps performed for spatial high-resolution tissue transcriptomic profiling (Xenium); examples are from POD49. Figure 45B shows separation of pig (dots above the dotted line) and human (dots below the dotted line) nuclei based on the number of identified transcripts originating from both genomes (sample POD33 is shown as an example). Figure 45C shows human / pig gene expression distribution among cells profiled with the 5.1k ST panel, separated by their assigned species. The x-axis represents the fraction of normalized expression attributed to human probes and the y-axis represents the percentage of cells in that group (pig or human). Figure 45D shows spatial transcriptomics cell-type labeling. Transplanted tissue H&E image (top panel), and corresponding spatial transcriptomics DAPI (4′,6-diamidino-2-phenylindole (DNA stain)) fluorescence image (bottom panel) with segmentation-based cells are notated by cell type. Figure 45E shows human cells infiltrating the renal cortex with their cell type annotation and associated markers (POD49). Figure 45F shows glomerulus and infiltrating human cells with cell-type annotation and associated markers (POD49). Figures 45G-L show dimension reduction maps of cells identified in the xenograft tissue, notated by identified cell type, for human (Figures 45G, I, K), and pig (Figures 45H, J, L) cells, in the 478 Xenium panel (Figures 45G- H), the 5.1k Xenium panel (Figures 45I-J), and snRNA-seq (Figures 45K-L) modalities. Figure 45M shows dimension-reduction map of cells identified in recipient PBMC scRNA-seq, notated by cell type. Left: main cell-types, right-up: T and NK cells, right-down: B cells, plasma cells, dendritic cells. Figures 45A, D, E, F show data from the 478 ST panel. MP: Macrophages, CD8T: CD8+T cells, CD4T: CD4+T cells, NK: NK cells, pDC: plasmacytoid dendritic cells, FB: Fibroblasts, EC: Endothelial cells, SMC: Smooth muscle cells, vSMC: vascular smooth muscle cells, fSMC: fibroblast-associated smooth muscle cells, VEC: vascular endothelial cells, cDC: classical dendritic cells, TEM: T effector memory cells, MK: Megakaryocytes, HSC: Hematopoietic stem cells, TCM: T central memory cells, MAIT: Mucosal-Associated Invariant T cells, Treg: Regulatory T cells. 34 314164997v1Attorney Docket No: 243735.000437

[0100] Figures 46A-K show early host immune cell response involving macrophages, NK cells, pDCs, and plasma / B cells. Figure 46A shows percentage of human cells identified by spatial transcriptomics in the xenograft tissue (5.1k ST panel) across all identified cells. Figure 46B shows plasmablast levels measured in the recipient PBMC scRNA-seq (top), and B marker expression levels from PBMC bulk RNA-seq (bottom). Figure 46C shows human B cell levels measured by spatial transcriptomics in the xenograft tissue (5.1k ST panel, top), in the recipient PBMC scRNA-seq (middle), and marker expression levels identified by PBMC bulk RNA-seq (bottom). Figure 46D shows human NK cell levels measured by spatial transcriptomics in the xenograft tissue (5.1k ST panel, top), in recipient PBMC scRNA-seq (middle), and by PBMC bulk RNA-seq marker expression (bottom). Figure 46E shows flow cytometry levels of NK and B cells. Figure 46F shows human pDC levels measured by spatial transcriptomics in the xenograft tissue (5.1k ST panel, top), in recipient PBMC scRNA-seq (middle), and by PBMC bulk RNA-seq marker expression (bottom). Figure 46G shows quantification of unique BCR clones from bulk BCR-Seq divided by clonal expansion level. Figure 46H shows quantification of unique BCR clones from bulk BCR-Seq divided by BCR isotype family. Figure 46I shows percentage of human macrophages / monocytes (top), CXCL9⁺ macrophages (middle), and interferon⁺ immune cells (bottom) in the xenograft tissue (5.1k ST panel). Figure 46J shows gene set enrichment analysis (GO Biological process) of cell type markers for CXCL9⁺ macrophages (top) and interferon⁺ cells (bottom). Figure 46K shows expression of CXCL9, CXCL10, and CXCL11 from the infiltrating human immune cells in the xenograft (from 5.1k ST data). ST: spatial transcriptomics, NK: Natural Killer cells, pDC: plasmacytoid dendritic cells.

[0101] Figures 47A-T show human T-cell response to xenotransplantation. Figures 47A-D show percentage of T cell subpopulations in the PBMC scRNA-seq data. This includes CD8 TEM (Figure 47A), Naive CD8 T (Figure 47B), CD4 TCM-TEM (Figure 47C) and Tregs (Figure 47D). Figures 47E-H show percentage of T cell subtypes observed in the 5.1k panel ST data, including CD8 TEM (Figure 47E), naive CD8T (Figure 47F), CD4T (Figure 47G) and Tregs (Figure 47H). Figure 47I shows percentage of all T cells from blood scRNA-seq data. Figures 47J-L show T-cell subtypes marker expression in blood bulk RNA-seq data, for CD8T markers CD8A and CD8B (Figure 47J), the CD4T marker TSHZ2 (Figure 47K) and Treg markers RTKN2 and CTLA4 (Figure 47L). Figures 47M-P show T-cell levels in flow cytometry data, for all T cells (Figure 47M). Figure 47Q shows T and NK cell subtypes expression of 35 314164997v1Attorney Docket No: 243735.000437 ITGAE (CD103), CD38 and TNFRSF9 across data modalities. Samples that have less than 5 cells of the population in question are excluded from the graph. Figure 47R shows quantification of unique TCR clones from bulk TCR-seq divided by clonal expansion level. Figure 47S shows V+J gene expression levels of TCR Beta clones from bulk TCR-seq. Figure 47T shows tracking of the top TCR Beta clones in bulk TCR-seq postoperative time course. TEM: T effector memory cells, TCM: T central memory cells, Treg: Regulatory T cells, UMI: Unique molecular identifier, NK: Natural killer cells. Figure 47T discloses SEQ ID NO: 1.

[0102] Figures 48A-H show that the transplanted porcine tissue response highlights the damage signaling at POD21 and POD33. Figure 48A shows expression of inflammatory related genes (FOS, FOSB, CXCL12) in the tissue xenograft porcine cells (from the 478 ST panel). Figure 48B shows the proportion of COLEC11+ cells across timepoints (5.1k panel). Figure 48C shows the proportion of SPP1+ cells across timepoints (478 panel). Figures 48D-E show expression of markers of interest for SPP1+ cells in the 478 panel (Figure 48D) and COLEC11+ cells in the 5.1k panel (Figure 48E). Figure 48F shows POD21 biopsy region corresponding to high levels of SPP1+ cells (478 panel). Figure 48G shows POD33 biopsy (H&E and ST) with high levels of human immune cells (478 panel). Figure 48H shows POD33 biopsy highlighting expression of pig and human genes of interest near human cells and COLEC11+ cells (5.1k panel). FB: Fibroblasts, EC: Endothelial cells, MP: Macrophages, NK: Natural Killer cells, pDC: Plasmacytoid Dendritic Cells, CD8T: CD8+T cells, CD4T: CD4+T cells, fSMC: fibroblast associated smooth muscle cells, vSMC: vascular smooth muscle cells, SMC: Smooth muscle cells, ST: spatial transcriptomics.

[0103] Figures 49A-I show identification of pig and human cells from ST data. Figures 49A- C, G pertain to the 478 ST panel data and Figures 49D-F, H-I to the 5.1k ST panel data. Figure 49A shows the distribution of total human and pig probe counts for each identified cell (dots). Cells are notated by their assigned groups (pig, dots above the dotted line; human, dots below the dotted line). Figure 49B shows the distribution of the fraction of counts originating from human probes. Figure 49C shows the distribution of mean expression of human and pig genes, with cells represented as dots notated by their assigned group. Figure 49D shows joint dimension reduction plots from all samples integrated, notated by sample ID (top) and highlighting human kidney cells that were subsequently removed (they originate from the human native kidney sample). Figure 49E shows the resulting integration dimension reduction plots, notated by 36 314164997v1Attorney Docket No: 243735.000437 fraction of normalized gene expression originating from human (top), by sample ID (left) and highlighting the selected human cluster (right). Figure 49F shows dimension reduction of the human cell clusters, highlighting human gene expression (top), pig gene expression (left), and basis for the identification of a doublet population (right), which is subsequently removed from the human cluster. Figure 49G shows the percentage of human cells found in the 478 ST panel across samples. Figure 49H shows the percentage of human cells found in the 5.1k ST panel across samples. Figure 49I shows the percentage of immune cells from the human native kidney sample sorted by their partition.

[0104] Figures 50A-D show identification of pig and human cells from xenograft ST and snRNA-seq data. Figure 50A shows human / pig gene expression distribution among 5.1k ST panel transcriptomics data cells, separated by their assigned species. The metric is the fraction of normalized expression of human probes, against all other probes (x-axis). The y-axis shows the percentage of cells of that group (pig or human). Plots are shown for each biopsy timepoint. Figure 50B shows the distribution of the fraction of gene expression originating from human genes in the xenograft snRNA-seq data (log scale). Figure 50C shows joint dimension reduction plots from all snRNA-seq samples integrated, highlighting the fraction of gene expression originating from human genes (left), and the cluster subsequently selected as containing human cells (right). Figure 50D shows dimension reduction plot of the selected human cells, notated by their fraction of human gene expression.

[0105] Figures 51A-M show further dissection of human macrophages, NK cells, B cells and dendritic cells. Figures 51A-B show dimension reduction graph (Figure 51A) and percentage across all cells by timepoint (Figure 51B) of human macrophage, monocytes and dendritic subtypes found in the 5.1k panel ST data notated by cell-type. Figures 51C-D show dimension reduction graph (Figure 51C) and percentage across all cells by timepoint (Figure 51D) for B cells, plasma cells, mast cells and neutrophils found in the 5.1k panel ST data, notated by their names. Figures 51E-G show marker gene expression of those populations in the 5.1k panel ST data. Figure 51H shows percentage levels for additional cell-type populations not already shown in this figure. Figures 51I-J show cell-type markers (Figure 51I) and associated percentage (Figure 51J) of B, plasma, and dendritic cell populations found in the PBMC scRNA-seq data. Figure 51K shows percentage of human macrophages, pDC and NK cells found in the 478 panel ST data. Figures 51L-M show pDC activation marker genes and CXCL9–CXCL11 expression 37 314164997v1Attorney Docket No: 243735.000437 in pDC-cDC1 populations in 5.1k ST data (Figure 51L) and PBMC scRNA-seq data (Figure 51M).

[0106] Figures 52A-L show early response from human macrophages and B cells as evidenced by ST and snRNA-seq in addition to BCR-seq. Figure 52A shows expression of immunoglobulin genes in PBMC bulk RNA-seq. Figure 52B shows CDR3 length (nt) distribution in bulk BCR-seq. Figure 52C shows somatic hypermutation frequency in bulk BCR- seq divided by isotype. Figure 52D shows shared overlapping clonotypes across bulk BCR-seq postoperative timepoints. Figure 52E shows tracking of the top BCR IgH clones in bulk BCR- seq postoperative time course. Figures 52F-I show 478 panel ST data highlighting human subpopulation of macrophages and NK cells expressing CXCL9, CXLC10, and CXCL11 as shown in a dimension reduction map (Figure 52F), distribution of these markers across those subpopulations (Figure 52G) and across time in the NK-MP populations (Figure 52H) and percentage distribution of these subpopulations across time (Figure 52I). Figures 52J-K show similar populations of interest in snRNA-seq data, as shown in expression of markers corresponding to the 5.1k panel data subtypes markers (Figure 52J) and their distribution over time (Figure 52K). Figure 52L shows expression of human CXCL9, CXCL10, CXCL11 observed in the tissue bulk RNA-seq.

[0107] Figures 53A-K show further human T cell response dissection. Figures 53A-C show human T cell subtypes found in 5.1k ST data, as shown via dimension reduction plot (Figure 53A), percentage across all cells in each timepoint (Figure 53B), and marker genes defining these cells (Figure 53C). Figure 53D shows cell type markers of PBMC NK and T cells populations. Figure 53E shows proportion of proliferative human NK found in the 5.1k ST data. Figures 53F-G show proportions (Figure 53F) and marker gene expression (Figure 53G) of human CD8T and CD4T from the 478 panel ST data. Figure 53H shows distribution of T and NK subtypes found in the PBMC scRNA-seq data, as percentage of all cells across timepoints (for subtypes not shown in Figure 47). Figure 53I shows percentage of human dividing and T cells found in snRNA-seq data. Figure 53J shows expression levels of CD8T markers (CD8A, CD8B, top) and Tregs markers (RTKN2, CTLA4, bottom), from PBMC bulk RNA-seq. Figure 53K shows flow cytometry T cells distributions, CD8+T cells (left) and CD4+T cells (right), separated by central memory and effector memory cells. 38 314164997v1Attorney Docket No: 243735.000437

[0108] Figures 54A-D show distribution of marker genes delineating resident and circulating T and NK cells. Figure 54A shows NK markers from 5.1k panel ST data. Figure 54B shows T cell markers from 5.1k panel ST data. Figure 54C shows NK markers from PBMC scRNA-seq data. Figure 54D shows T cell markers from PBMC scRNA-seq data.

[0109] Figures 55A-J show porcine transcriptional response from tissue and porcine resident immune cells. Figure 55A shows inflammatory gene clusters identified by bulk RNAseq longitudinal analysis. Expression over time (top) and top pathway enrichment (bottom) are shown. Figure 55B shows gene-set enrichment of genes overexpressed in specific PODs in the 478 ST panel. Figure 55C shows colocalization analysis of SPP1+ cells (top) and pig immune cells (bottom) from the 478 panel ST data. Figure 55D shows colocalization analysis of COLEC11+ cells (top) and pig immune cells (bottom) from the 5.1k panel ST data. Figures 55E-F show macrophage and T-cell marker expression across cell-types in the 5.1k panel (Figure 55E) and 478 panel (Figure 55F) ST data. Figure 55G shows T-cell marker expression across timepoints, shown in pig immune cells in the 5.1k panel (left) and 478 panel (right) ST data. Figure 55H shows the top 80 marker genes for POD33 pig immune cells, identified by Wilcoxon rank-sum analysis comparing their transcriptomic profile to all other time points. Figures 55I-J show expression of marker genes of interest across timepoints in specific pig cell populations, in snRNA-seq samples of the xenograft (Figure 55I) and in 5.1k ST data (Figure 55J).

[0110] Figures 56A-G show B-HOT AbMR signature revealed by ST. Figures 56A-D show B-HOT AbMR signature expression in the 478-gene ST panel, using genes identified as differentially expressed (DEG post- vs. pre-transplantation) in xenografts from Loupy, et al. (Loupy, et al., 2023). Figures 56E-G show B-HOT AbMR signature expression in the 5.1k-gene ST panel, using the entire B-HOT panel, regardless of overlap with Loupy, et al. (Loupy, et al., 2023) results. Figure 56A shows spatial distribution of the B-HOT AbMR signature in POD33 tissue. Figure 56B shows B-HOT signature enrichment in UMAP, overlaid with cell-type composition. Figure 56C shows AbMR signature enrichment across time points. Figure 56D shows marker expression of B-HOT AbMR genes. Figure 56E shows expression of genes (human probes) belonging to the B-HOT AbMR signature across timepoints in all human cells. Figure 56F shows expression of pig genes whose human orthologues are part of the B-HOT 39 314164997v1Attorney Docket No: 243735.000437 panel, across timepoints in all pig cells. Figure 56G shows spatial distribution in POD33 of the AbMR gene set score, and pig SERPINE1 expression.

[0111] Figure 57 shows dynamics of selected complement pathway elements protein levels in the serum. Serum abundance over time is shown for the indicated complement factors. Statistical analysis of protein regulation was based on XT2 Proteograph XT measurements of serum samples. The middle line, shaded region, and dashed line bands correspond to the median and 50% and 95% credible intervals of the protein intensity posterior distribution, respectively.

[0112] Figures 58A-D show expression of pig and human probes from Xenium ST data. Figures 58A-C show expression from the 5.1k ST panel data and Figure 58D shows expression from the 478 panel ST data. Figures 58A-B show expression of human and pig probes for orthologous genes across samples in pig (Figure 58A) and human (Figure 58B) immune cells. Figure 58C shows expression of human and pig probes targeting orthologous genes, across cell- types in human immune cells (5.1k panel). In this panel, only probes targeting orthologues with a mean log-normalized expression of at least 0.15 in at least one cell type are shown. Figure 58D shows expression of all human and pig probes targeting orthologous genes, across all human and pig cell types.

[0113] Figures 59A-E show dissection of human cells found in the xenograft 478 panel Xenium ST data. Figure 59A shows a dimension reduction map of the data notated by timepoint. Figure 59B shows a dimension reduction map of the data notated by cell-type. Figure 59C shows cell type proportion across timepoints. Figure 59D shows Wilcoxon-based differential expression results (top genes for each cell type). Figure 59E shows a dimension reduction map of the data for each timepoint.

[0114] Figures 60A-E show dissection of pig cells found in the xenograft 478 panel Xenium ST data. Figure 60A shows a dimension reduction map of the data notated by timepoint. Figure 60B shows dimension reduction map of the data notated by cell-type. Figure 60C shows cell type percentage across timepoints. Figure 60D shows Wilcoxon based differential expression results (top genes for each cell type). Figure 60E shows dimension reduction map of the data for each timepoint.

[0115] Figures 61A-G show dissection of human cells found in the xenograft 5.1k panel Xenium ST data. Figure 61A shows dimension reduction map of the data notated by timepoint. Figure 61B shows dimension reduction map of the data notated by cell-type. Figure 61C shows 40 314164997v1Attorney Docket No: 243735.000437 cell type percentage across timepoints. Figures 61D-G show Wilcoxon based differential expression results (top genes for each cell type), for all cells (Figure 61D), monocytes / macrophages and dendritic cells (Figure 61E), NK and T cells (Figure 61F), and Mast, B and plasma cells (Figure 61G).

[0116] Figure 62 shows dimension reduction map of the data for each timepoint for the 5.1k panel Xenium ST data.

[0117] Figures 63A-E show dissection of pig cells found in the xenograft 5.1k panel Xenium ST data. Figure 63A shows dimension reduction map of the data notated by timepoint. Figure 63B shows dimension reduction map of the data notated by cell-type. Figure 63C shows cell type proportion across timepoints. Figure 63D shows Wilcoxon based differential expression results (top genes for each cell type). Figure 63E shows dimension reduction map of the data for each timepoint.

[0118] Figures 64A-E show dissection of human cells found in the xenograft snRNA seq data (all human cells). Figure 64A shows dimension reduction map of the data notated by timepoint. Figure 64B shows dimension reduction map of the data notated by cell-type. Figure 64C shows cell type proportion across timepoints. Figure 64D shows Wilcoxon based differential expression results (top genes for each cell type). Figure 64E shows dimension reduction map of the data for each timepoint.

[0119] Figures 65A-E show dissection of human cells found in the xenograft snRNA seq data (lymphocytes and NK cells). Figure 65A shows dimension reduction map of the data notated by timepoint. Figure 65B shows dimension reduction map of the data notated by cell-type. Figure 65C shows cell type proportion across timepoints. Figure 65D shows Wilcoxon based differential expression results (top genes for each cell type). Figure 65E shows dimension reduction map of the data for each timepoint.

[0120] Figures 66A-E show dissection of pig cells found in the xenograft snRNA-seq data. Figure 66A shows dimension reduction map of the data notated by timepoint. Figure 66B shows dimension reduction map of the data notated by cell-type. Figure 66C shows cell type proportion across timepoints. Figure 66D shows Wilcoxon based differential expression results (top genes for each cell type). Figure 66E shows dimension reduction map of the data for each timepoint. 41 314164997v1Attorney Docket No: 243735.000437

[0121] Figures 67A-E show dissection of main cell types found in the PBMC scRNA-seq data. Figure 67A shows dimension reduction map of the data notated by timepoint. Figure 67B shows dimension reduction map of the data notated by cell-type. Figure 67C shows cell type proportion across timepoints. Figure 67D shows Wilcoxon based differential expression results (top genes for each cell type). Figure 67E shows dimension reduction map of the data for each timepoint.

[0122] Figures 68A-E show dissection of T and NK cells found in the PBMC scRNA-seq data. Figure 68A shows dimension reduction map of the data notated by timepoint. Figure 68B shows dimension reduction map of the data notated by cell-type. Figure 68C shows cell type proportion across timepoints. Figure 68D shows Wilcoxon based differential expression results (top genes for each cell type). Figure 68E shows dimension reduction map of the data for each timepoint.

[0123] Figures 69A-E show dissection of B, plasma and dendritic cells found in the PBMC scRNA-seq data. Figure 69A shows dimension reduction map of the data notated by timepoint. Figure 69B shows dimension reduction map of the data notated by cell-type. Figure 69C shows cell type proportion across timepoints. Figure 69D shows Wilcoxon based differential expression results (top genes for each cell type). Figure 69E shows dimension reduction map of the data for each timepoint.

[0124] Figures 70A-B show dissection of B-HOT annotation in the Xenograft ST data. Figures 70A-B show levels of scores derived from the B-HOT signature gene set shown across cell types (Figure 70A) and timepoints (Figure 70B), in the human cells of the 5.1k genes panel ST dataset.

[0125] Figure 71 shows dynamics of human complement pathway elements protein levels in the serum. Statistical analysis of protein regulation was based on XT2 Proteograph XT measurements of serum samples. The middle line, shaded region, and dashed line bands correspond to the median and 50% and 95% credible intervals of the protein intensity posterior distribution, respectively.

[0126] Figure 72 shows dynamics of porcine complement pathway elements protein levels in the serum. Statistical analysis of protein regulation was based on XT2 and XT1 Proteograph XT measurements of serum samples. The middle line, shaded region, and dashed line bands 42 314164997v1Attorney Docket No: 243735.000437 correspond to the median and 50% and 95% credible intervals of the protein intensity posterior distribution, respectively. DETAILED DESCRIPTION

[0127] Considerable progress has been made in pig genome editing to reduce the immunological barriers and incompatibilities between pigs and humans (Cooper, et al., 2012; Montgomery, Mehta, et al., 2022). Advances in research using recently deceased brain-dead human donors (decedents) and genetic knockout models of key xeno-antigens, including α-1,3- galactosyltransferase (α-1,3-Gal), has enabled the transition of xenotransplantation from preclinical primate experiments (Ekser, et al., 2009; Pintore, et al., 2013) to humans (Mohiuddin, et al., 2023; Moazami, et al., 2023). Galactose-α-1,3-galactose (α-Gal), a ubiquitous terminal carbohydrate modification on glycoproteins and glycolipids in the animal kingdom, is synthesized by α-1,3-Gal (GGTA1) (Galili, et al., 1993; Galili, et al., 1988). Unlike most species, humans and some non-human primates (NHPs) have a GGTA1 pseudogene, allowing the development of strong anti-α-Gal antibodies (Abs) that precipitate hyperacute rejection of α-Gal- expressing xenografts (Griesemer, et al., 2014).

[0128] By knocking out α-1,3-Gal (α-Gal-KO), genetically modified porcine organs can substantially reduce hyperacute rejection risk in non-human primates (Phelps, et al., 2003; Yamada, et al., 2005; Cooper, et al., 2007; Pintore, et al., 2013; Ekser, et al., 2009). This generation of GGTA1 pig knockout (GT-KO) mutants to overcome the described major immunological barrier in xenotransplantation (Wolbrom, et al., 2023) led to Food and Drug Administration (FDA) approval of the use of GalSafe™ GT-KO pigs for human food consumption and potential downstream therapeutics in December 2020. While genetic differences in pigs compared to primates constitute a substantial reservoir of potential xeno- antigens, gene-edited pig organs have been successfully transplanted into NHPs with survival rates in excess of a year (Adams, et al., 2018; Butler, et al., 2016; Kim, et al., 2019; Yamamoto, et al., 2020).

[0129] These positive results led the way to the first pig-to-human kidney xenotransplantation into brain-dead decedents to evaluate the safety and feasibility of the genetically engineered porcine kidney in humans (Montgomery, Stern, et al., 2022; Porrett, et al., 2022). Xenograft transplantation into brain-dead humans (decedents) offers a unique opportunity to evaluate 43 314164997v1Attorney Docket No: 243735.000437 xenografts in the intended recipient model, and to obtain extensive longitudinally-collected blood and tissue samples in a ‘fail-safe’ manner (Montgomery, et al., 2024). In 2021, the successful GalSafe™ thymus-kidney (“thymokidney”) xenograft transplants were performed in two decedents (Montgomery, Stern, et al., 2022; Loupy, et al., 2023). The surgical placement of thymus tissues under the capsule of the kidney several months before procurement is designed to have a tolerogenic effect through deletion of xeno-reactive T-cells after transplant into human recipients (Sykes, et al., 2022).

[0130] In parallel with developments in xenotransplantation procedures, recent technological advancements in in situ spatial transcriptomics (ST), single-cell (sc)- and single nuclei (sn)-RNA profiling, immune repertoire sequencing, and deep proteomic analyses have enhanced the ability to generate dense, longitudinal omics datasets that offer an unprecedented view into the biomolecular underpinnings of health and disease (Donovan, et al., 2023; Ferdosi, et al., Adv Mater, 2022; Ferdosi, et al., Proc Natl Acad Sci U S A, 2022; Huang, et al., 2023). Longitudinal multi-omics profiling has emerged as a powerful tool for uncovering new biomarkers in biological and disease contexts, including obesity and space flight (Zhou, et al., 2019; Garrett- Bakelman, et al., 2019; Piening, et al., 2018; Schüssler-Fiorenza Rose, et al., 2019; Ghaemi, et al., 2019; Shaked, et al., 2017; Piening, et al., 2022).

[0131] The key advantage of longitudinal ‘omics’ comparisons within individual subjects lies in using individual time points as internal controls, greatly enhancing statistical power compared to cross-sectional studies (Piening, et al., 2018) and allowing for deep insights into the biological dynamics of processes including post-transplant complications (Piening, et al., 2022; Shaked, et al., 2017; Krupickova, et al., 2021). Recent advancements in single-cell and spatial transcriptomics now allow for detailed RNA expression analysis and understanding of cellular interactions, offering critical insights into complex biological processes (Long, et al., 2023; Ospina, et al., 2023; Finn, et al., 2019). There remains a need to better understand the molecular landscape following xenotransplantation to improve outcomes as xenotransplantation of genetically engineered porcine organs has the potential to address the challenge of organ donor shortage.

[0132] Two pig heart xenografts were transplanted into two human decedents (D1 and D2) with the primary aim of assessing the presence of hyperacute antibody-mediated rejection (AbMR) and sustained xenograft functioning over a 3-day protocol (Moazami, et al., 2023). 44 314164997v1Attorney Docket No: 243735.000437 Integrative multi-omics profiling was performed in human decedents receiving pig heart xenografts. In a previous study, heart xenografts from 10-gene-edited pigs transplanted into two human decedents did not show evidence of acute-onset cellular- or antibody-mediated rejection. In attempts to elucidate the molecular underpinnings of xenotransplantation success, longitudinal multi-omics profiling was performed to assess the dynamic interactions in these first two pig heart xenografts transplanted into two human decedents. To better understand the detailed molecular landscape following xenotransplantation, lipidomic, metabolomic, and comprehensive proteomic datasets, in addition to transcriptomics (bulk RNA sequencing (RNA-seq) and single- cell RNA sequencing (scRNA-seq)), were generated across blood and single-nucleotide RNA sequencing (snRNA-seq) and spatial transcriptomic datasets in tissue samples collected throughout the 3-day xenotransplant protocols (Figure 1). Also, systems-level analysis was performed through integration of the respective omics datasets to assess global changes.

[0133] Substantial early immune responses were observed in peripheral blood mononuclear cells and xenograft tissue obtained from decedent 1 (male), associated with downstream T cell and natural killer cell activity. Longitudinal analyses indicated the presence of ischemia reperfusion injury, exacerbated by inadequate immunosuppression of T cells. Moreover, at 42 h after transplantation, substantial alterations in cellular metabolism and liver-damage pathways occurred, correlating with profound organ-wide physiological dysfunction. In contrast, relatively minor changes in RNA, protein, lipid and metabolism profiles were observed in decedent 2 (female) as compared to decedent 1. Overall, these multi-omics analyses delineate distinct responses to cardiac xenotransplantation in the two human decedents and reveal new insights into early molecular and immune responses after xenotransplantation. These findings may aid in the development of targeted therapeutic approaches to limit ischemia reperfusion injury-related phenotypes and improve outcomes.

[0134] Further, two cases of porcine-to-human kidney xenotransplantation were performed, yet the physiological effects on the xenografts and the recipients’ immune responses remained largely uncharacterized. The porcine kidney transplants showed promising physiological functioning during the ~3 day study period, producing urine and not showing evidence of hyperacute rejection (Montgomery, Stern, et al., 2022). Initial histological analyses of the kidney biopsy samples during and after xenotransplantation did not detect obvious evidence of antibody- mediated rejection (AbMR), nor strong indications of porcine kidney injury (Montgomery, Stern, 45 314164997v1Attorney Docket No: 243735.000437 et al., 2022). However, due to the short duration of these human xenotransplantation trials, it is possible that the histological markers were not yet strongly expressed to a detectable level, rendering standard methods ineffective to capture signs of pathophysiological changes of the xenograft and the recipient’s immune response post xenotransplantation (Halloran, et al., 2018).

[0135] Single-cell transcriptomic technology enables a comprehensive analysis of cellular physiology of organ transplantation and the recipient’s immune response (Varma, et al., 2021; Wu, et al., 2018; Malone, et al., 2020; Andrijevic, et al., 2022). In the study herein (Figure 43), comprehensive single-cell RNA sequencing (scRNA-seq) analyses were conducted on the first porcine-to-human kidney xenografts to characterize the intricate xenotransplantation-associated cellular and molecular dynamics and xenograft-recipient interactions. Additionally, longitudinal scRNA-seq of the peripheral blood mononuclear cells (PBMCs) was performed to detect recipient immune responses across time.

[0136] Such comprehensive analyses enabled the detection of major changes in both human and porcine cells upon xenotransplantation. Although no hyperacute rejection signals were detected, evidence of endothelial cell and immune response activation found within the scRNA- seq analyses of the xenografts revealed early signs of AbMR. Tracing the species origin of cells, evidence was found for human immune cell infiltration in both xenografts. Human transcripts in the longitudinal bulk-RNA-seq revealed that human immune cell infiltration into the porcine kidney and the activation of interferon gamma-induced chemokines expression occurred by 12 hours and 48 hours post-xenotransplantation, respectively. Concordantly, longitudinal scRNA- seq of recipient PBMCs also revealed two phases of the recipients’ biphasic immune responses at 12 and 48-53 hours post-xenotransplantation. Lastly, global expression signatures of xenotransplantation-associated kidney tissue damage were observed in the xenografts. Surprisingly, a rapid increase of proliferative cells in both porcine kidney xenografts was detected upon xenotransplantation. These proliferative cells express proximal tubule cell marker genes, indicating a rapid activation of a porcine kidney tissue repair program. Longitudinal and single-cell RNA-seq analyses of porcine kidneys and recipient PBMCs revealed time-resolved cellular dynamics (e.g., dynamic xenograft tissue physiology and time-resolved immune responses) of xenograft-recipient interactions during xenotransplantation. These cues can be leveraged for designing gene edits of pigs for xenotransplantation and immunosuppression regimens to optimize xenotransplantation outcomes. 46 314164997v1Attorney Docket No: 243735.000437

[0137] Additionally, immune responses were studied over 61 days following pig-to-human thymokidney xenotransplantation, integrating spatial transcriptomics, single-nucleus and single- cell RNA-sequencing, bulk RNA-sequencing, and proteomics. High-throughput molecular characterization studies have used transcriptomics panels, single-cell, and spatial technologies to investigate pig-to-human kidney and heart xenografts in decedents, but these efforts were limited to 2–3 days post-transplant (Loupy, et al., 2023; Pan, et al., 2024; Schmauch, et al., 2024; Cheung, et al., 2024). It was found herein that blood plasmablasts, natural killer (NK) cells, and dendritic cells increased between postoperative day (POD)10 and 28, concordant with expansion of immunoglobulin G (IgG) / immunoglobulin A (IgA) B-cell clonotypes, and subsequent biopsy- confirmed antibody-mediated rejection (AbMR) at POD33. Human T-cell frequencies increased from POD21 and peaked around POD45 in the blood and xenograft, coinciding with T-cell receptor diversification, expansion of a restricted TRBV2 / J1 clonotype, and histological evidence of a cell-mediated component to the rejection. At POD33, the most abundant human immune population in the graft was CXCL9+ macrophages, aligning with IFN-γ-driven inflammation and Type I immune response. In addition, activated pig-resident macrophages colocalized with infiltrating human cells, suggesting cross-species interactions. Xenograft tissue showed pro-fibrotic tubular and interstitial injury, marked by S100A6, SPP1 (secreted phosphoprotein 1, Osteopontin), and COLEC11, on POD21-POD33. Proteomics revealed complement activation through porcine and human pathways, peaking at POD20 and declining after AbMR therapy including complement inhibition. Collectively, the molecular orchestration of human immune responses to a porcine kidney reveals potential immunomodulatory targets for improving xenograft survival. Definitions

[0138] To facilitate an understanding of the principles and features of the various embodiments of the invention, various illustrative embodiments are explained below. Although exemplary embodiments of the invention are explained in detail, it is to be understood that other embodiments are contemplated. Accordingly, it is not intended that the invention is limited in its scope to the details of construction and arrangement of components set forth in the following description or examples. The invention is capable of other embodiments and of being practiced or carried out in various ways. Also, in describing the exemplary embodiments, specific terminology will be resorted to for the sake of clarity. 47 314164997v1Attorney Docket No: 243735.000437

[0139] Unless otherwise defined herein, scientific and technical terms used in connection with the present invention shall have the meanings that are commonly understood by those of ordinary skill in the art. Further, unless otherwise required by context, singular terms shall include pluralities and plural terms shall include the singular. Generally, nomenclatures used in connection with, and techniques of, cell and tissue culture, molecular biology, immunology, microbiology, genetics and protein and nucleic acid chemistry and hybridization described herein are those well-known and commonly used in the art.

[0140] The methods and techniques of the present invention are generally performed according to conventional methods well known in the art and as described in various general and more specific references that are cited and discussed throughout the present specification unless otherwise indicated. See, e.g., Sambrook et al., Molecular Cloning: A Laboratory Manual, 2d ed., Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y. (1989); Ausubel et al., Current Protocols in Molecular Biology, Greene Publishing Associates (1992); and Harlow and Lane Antibodies: A Laboratory Manual, Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y. (1990), which are incorporated herein by reference. Enzymatic reactions and purification techniques are performed according to manufacturer’s specifications, as commonly accomplished in the art or as described herein. The implementation of the present invention can utilize, unless otherwise specified, standard techniques in immunology, biochemistry, genetics, computational biology, molecular biology, cell biology, genomics, epigenomics, and bioinformatics, which are well-known to those skilled in the field.

[0141] The term “about” or “approximately” means within a statistically meaningful range of a value. Such a range can be within an order of magnitude, preferably within 50%, more preferably within 20%, still more preferably within 10%, and even more preferably within 5% of a given value or range. The allowable variation encompassed by the term “about” or “approximately” depends on the particular system under study, and can be readily appreciated by one of ordinary skill in the art.

[0142] It must also be noted that, as used in the specification and the appended claims, the singular forms “a,” “an” and “the” include plural references unless the context clearly dictates otherwise. For example, reference to a component is intended also to include composition of a plurality of components. References to a composition containing “a” constituent is intended to include other constituents in addition to the one named. In other words, the terms “a,” “an,” and 48 314164997v1Attorney Docket No: 243735.000437 “the” do not denote a limitation of quantity, but rather denote the presence of “at least one” of the referenced item.

[0143] The terms “treat” or “treatment” of a state, disorder or condition include: (1) preventing, delaying, or reducing the incidence and / or likelihood of the appearance of at least one clinical or sub-clinical symptom of the state, disorder or condition developing in a subject that may be afflicted with or predisposed to the state, disorder or condition but does not yet experience or display clinical or subclinical symptoms of the state, disorder or condition; or (2) inhibiting the state, disorder or condition, i.e., arresting, reducing or delaying the development of the disease or a relapse thereof (in case of maintenance treatment) or at least one clinical or sub- clinical symptom thereof; or (3) relieving the disease, i.e., causing regression of the state, disorder or condition or at least one of its clinical or sub-clinical symptoms. The benefit to a subject to be treated is either statistically significant or at least perceptible to the patient or to the physician.

[0144] The terms “diagnose” or “diagnosis” of xenograft status or outcome include predicting or diagnosing the xenograft status or outcome, determining predisposition to a xenograft status or outcome, monitoring treatment of a xenograft subject, diagnosing a therapeutic response of a xenograft subject, and prognosis of xenograft status or outcome, xenograft progression, and response to treatment.

[0145] The terms “subject”, “patient”, “individual”, “recipient”, and “animal” are used interchangeably herein and refer to mammals, including, without limitation, human and veterinary animals (e.g., cats, dogs, cows, horses, sheep, pigs, etc.) and experimental animal models. In a preferred embodiment, the subject is a human.

[0146] The terms “sample”, “subject sample” and “test sample” are used herein to refer to any biological specimen obtained from a subject or patient. Samples that can be used in the methods of the present disclosure include, without limitation, serum, plasma, whole blood, red blood cells, white blood cells (e.g., peripheral blood mononuclear cells (PBMCs)), polymorphonuclear (PMN) cells, pericardial fluid, ductal lavage fluid, nipple aspirate, lymph (e.g., disseminated tumor cells of the lymph node), bone marrow aspirate, buccal swabs, saliva, urine, stool (i.e., feces), sputum, bronchial lavage fluid, tears, fine needle aspirate (e.g., harvested by random periareolar fine needle aspiration), any other bodily fluid, xenograft sample, a tissue sample such as a biopsy of a site of the xenograft (e.g., needle biopsy), and cellular extracts thereof. In some 49 314164997v1Attorney Docket No: 243735.000437 embodiments, the sample comprises peripheral blood mononuclear cells (PBMCs) or a biopsy of a site of the xenograft.

[0147] Also, in describing the exemplary embodiments, terminology will be resorted to for the sake of clarity. It is intended that each term contemplates its broadest meaning as understood by those skilled in the art and includes all technical equivalents which operate in a similar manner to accomplish a similar purpose.

[0148] It is also to be understood that the mention of one or more method steps does not preclude the presence of additional method steps or intervening method steps between those steps expressly identified. Similarly, it is also to be understood that the mention of one or more components in a composition does not preclude the presence of additional components than those expressly identified.

[0149] The terms “comprising” or “containing” or “including” are meant that at least the named element, or method step is present in article or method, but does not exclude the presence of other elements or method steps, even if the other such elements or method steps have the same function as what is named.

[0150] The materials described hereinafter as making up the various elements of the present invention are intended to be illustrative and not restrictive. Many suitable materials that would perform the same or a similar function as the materials described herein are intended to be embraced within the scope of the invention. Such other materials not described herein can include, but are not limited to, materials that are developed after the time of the development of the invention, for example. Any dimensions listed in the various drawings are for illustrative purposes only and are not intended to be limiting. Other dimensions and proportions are contemplated and intended to be included within the scope of the invention. Methods

[0151] In one aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes MS4A1, CD19, AIM2, BANK1, CD79A, TNFRSF13C, BLK, 50 314164997v1Attorney Docket No: 243735.000437 IGHM, and IGHD, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0152] In some embodiments, the expression levels are determined for three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, eight or more genes, or nine genes selected from human genes MS4A1, CD19, AIM2, BANK1, CD79A, TNFRSF13C, BLK, IGHM, and IGHD. In some embodiments, the expression levels of the three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, eight or more genes, or nine genes are compared to a corresponding control. In another embodiment, the expression levels are determined for two, three, four, five, six, seven, eight, or nine genes selected from human genes MS4A1, CD19, AIM2, BANK1, CD79A, TNFRSF13C, BLK, IGHM, and IGHD. In some embodiments, the expression levels of the two, three, four, five, six, seven, eight, or nine genes are compared to a corresponding control.

[0153] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes XBP1, MZB1, TNFRSF17, CD27, TENT5C, POU2AF1, PRDM1, NUGGC, and SDC1, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs); and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0154] In some embodiments, the expression levels are determined for three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, eight or more genes, or nine genes selected from human genes XBP1, MZB1, TNFRSF17, CD27, TENT5C, POU2AF1, PRDM1, NUGGC, and SDC1. In some embodiments, the expression levels of the three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, eight or more genes, or nine genes are compared to a corresponding control. In another embodiment, the expression levels are determined for two, three, four, five, six, seven, eight, or 51 314164997v1Attorney Docket No: 243735.000437 nine genes selected from human genes XBP1, MZB1, TNFRSF17, CD27, TENT5C, POU2AF1, PRDM1, NUGGC, and SDC1. In some embodiments, the expression levels of the two, three, four, five, six, seven, eight, or nine genes are compared to a corresponding control.

[0155] In a further aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes KLRC1, GZMB, TRDC, KLRF1, and GNLY, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0156] In some embodiments, the expression levels are determined for three or more genes, four or more genes, or five genes selected from human genes KLRC1, GZMB, TRDC, KLRF1, and GNLY. In some embodiments, the expression levels of the three or more genes, four or more genes, or five genes are compared to a corresponding control. In another embodiment, the expression levels are determined for two, three, four, or five genes selected from human genes KLRC1, GZMB, TRDC, KLRF1, and GNLY. In some embodiments, the expression levels of the two, three, four, or five genes are compared to a corresponding control.

[0157] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes LYZ, MRC1, STAB1, SLCO2B1, F13A1, CD163, MSR1, SLC40A1, and CD14, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0158] In some embodiments, the expression levels are determined for three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, eight or more 52 314164997v1Attorney Docket No: 243735.000437 genes, or nine genes selected from human genes LYZ, MRC1, STAB1, SLCO2B1, F13A1, CD163, MSR1, SLC40A1, and CD14. In some embodiments, the expression levels of the three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, eight or more genes, or nine genes are compared to a corresponding control. In another embodiment, the expression levels are determined for two, three, four, five, six, seven, eight, or nine genes selected from human genes LYZ, MRC1, STAB1, SLCO2B1, F13A1, CD163, MSR1, SLC40A1, and CD14. In some embodiments, the expression levels of the two, three, four, five, six, seven, eight, or nine genes are compared to a corresponding control.

[0159] In a further aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes IRF7, TLR7, TLR9, MYD88, and STAT1, wherein the sample is a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0160] In some embodiments, the expression levels are determined for three or more genes, four or more genes, or five genes selected from human genes IRF7, TLR7, TLR9, MYD88, and STAT1. In some embodiments, the expression levels of the three or more genes, four or more genes, or five genes are compared to a corresponding control. In another embodiment, the expression levels are determined for two, three, four, or five genes selected from human genes IRF7, TLR7, TLR9, MYD88, and STAT1. In some embodiments, the expression levels of the two, three, four, or five genes are compared to a corresponding control.

[0161] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes PLD4, CLEC4C, LILRA4, TPM2, MZB1, SCT, IRF4, and SMPD3, 53 314164997v1Attorney Docket No: 243735.000437 wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0162] In some embodiments, the expression levels are determined for three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, or eight genes selected from human genes PLD4, CLEC4C, LILRA4, TPM2, MZB1, SCT, IRF4, and SMPD3. In some embodiments, the expression levels of the three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, or eight genes are compared to a corresponding control. In another embodiment, the expression levels are determined for two, three, four, five, six, seven, or eight genes selected from human genes PLD4, CLEC4C, LILRA4, TPM2, MZB1, SCT, IRF4, and SMPD3. In some embodiments, the expression levels of the two, three, four, five, six, seven, or eight genes are compared to a corresponding control.

[0163] In a further aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, and CLEC10A, wherein the sample is a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0164] In some embodiments, the expression levels are determined for three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, eight or more genes, nine or more genes, ten or more genes, eleven or more genes, twelve or more genes, or thirteen genes selected from human genes STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, and CLEC10A. In some embodiments, the expression levels of the three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, eight or more genes, nine or more genes, ten or more genes, eleven or more genes, twelve or more genes, or thirteen genes are compared to a corresponding 54 314164997v1Attorney Docket No: 243735.000437 control. In another embodiment, the expression levels are determined for two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, or thirteen genes selected from human genes STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, and CLEC10A. In some embodiments, the expression levels of the two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, or thirteen genes are compared to a corresponding control.

[0165] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, and IFIH1, wherein the sample is a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0166] In some embodiments, the expression levels are determined for three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, eight or more genes, nine or more genes, ten or more genes, eleven or more genes, twelve or more genes, or thirteen genes selected from human genes MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, and IFIH1. In some embodiments, the expression levels of the three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, eight or more genes, nine or more genes, ten or more genes, eleven or more genes, twelve or more genes, or thirteen genes are compared to a corresponding control. In another embodiment, the expression levels are determined for two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, or thirteen genes selected from human genes MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, and IFIH1. In some embodiments, the expression levels of the two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, or thirteen genes are compared to a corresponding control.

[0167] In a further aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: 55 314164997v1Attorney Docket No: 243735.000437 a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes CD3G, THEMIS, CD5, and CD6, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0168] In some embodiments, the expression levels are determined for three or more genes, or four genes selected from human genes CD3G, THEMIS, CD5, and CD6. In some embodiments, the expression levels of the three or more genes, or four genes are compared to a corresponding control. In another embodiment, the expression levels are determined for two, three, or four genes selected from human genes CD3G, THEMIS, CD5, and CD6. In some embodiments, the expression levels of the two, three, or four genes are compared to a corresponding control.

[0169] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of CD8B and / or CD8A, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the gene(s) determined in step (a) to a corresponding control.

[0170] In a further aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes KLRG1, GZMK, CST7, and GZMH, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0171] In some embodiments, the expression levels are determined for three or more genes, or four genes selected from human genes KLRG1, GZMK, CST7, and GZMH. In some 56 314164997v1Attorney Docket No: 243735.000437 embodiments, the expression levels of the three or more genes, or four genes are compared to a corresponding control. In another embodiment, the expression levels are determined for two, three, or four genes selected from human genes KLRG1, GZMK, CST7, and GZMH. In some embodiments, the expression levels of the two, three, or four genes are compared to a corresponding control.

[0172] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes LEF1, TCF7, SELL, CD27, CD55, and CCR7, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0173] In some embodiments, the expression levels are determined for three or more genes, four or more genes, five or more genes, or six genes selected from human genes LEF1, TCF7, SELL, CD27, CD55, and CCR7. In some embodiments, the expression levels of the three or more genes, four or more genes, five or more genes, or six genes are compared to a corresponding control. In another embodiment, the expression levels are determined for two, three, four, five, or six genes selected from human genes LEF1, TCF7, SELL, CD27, CD55, and CCR7. In some embodiments, the expression levels of the two, three, four, five, or six genes are compared to a corresponding control.

[0174] In a further aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes CD4, CD40LG, CCR2, CCR6, and DPP4, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control. 57 314164997v1Attorney Docket No: 243735.000437

[0175] In some embodiments, the expression levels are determined for three or more genes, four or more genes, or five genes selected from human genes CD4, CD40LG, CCR2, CCR6, and DPP4. In some embodiments, the expression levels of the three or more genes, four or more genes, or five genes are compared to a corresponding control. In another embodiment, the expression levels are determined for two, three, four, or five genes selected from human genes CD4, CD40LG, CCR2, CCR6, and DPP4. In some embodiments, the expression levels of the two, three, four, or five genes are compared to a corresponding control.

[0176] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes CTLA4, FOXP3, IKZF2, RTKN2, IRF4, IL21, and IL2RA, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0177] In some embodiments, the expression levels are determined for three or more genes, four or more genes, five or more genes, six or more genes, or seven genes selected from human genes CTLA4, FOXP3, IKZF2, RTKN2, IRF4, IL21, and IL2RA. In some embodiments, the expression levels of the three or more genes, four or more genes, five or more genes, six or more genes, or seven genes are compared to a corresponding control. In another embodiment, the expression levels are determined for two, three, four, five, six, or seven genes selected from human genes CTLA4, FOXP3, IKZF2, RTKN2, IRF4, IL21, and IL2RA. In some embodiments, the expression levels of the two, three, four, five, six, or seven genes are compared to a corresponding control.

[0178] In a further aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: 58 314164997v1Attorney Docket No: 243735.000437 a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes ITGAE, CD38, TNFRSF9, and MKI67, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0179] In some embodiments, the expression levels are determined for three or more genes, or four genes selected from human genes ITGAE, CD38, TNFRSF9, and MKI67. In some embodiments, the expression levels of the three or more genes, or four genes are compared to a corresponding control. In another embodiment, the expression levels are determined for two, three, or four genes selected from human genes ITGAE, CD38, TNFRSF9, and MKI67. In some embodiments, the expression levels of the two, three, or four genes are compared to a corresponding control.

[0180] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes GZMA, PRF1, and FASLG, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0181] In another embodiment, the expression levels are determined for two or three genes selected from human genes GZMA, PRF1, and FASLG. In some embodiments, the expression levels of the two or three genes are compared to a corresponding control.

[0182] In a further aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes TOP2A, TYMS, and MKI67, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and 59 314164997v1Attorney Docket No: 243735.000437 b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0183] In another embodiment, the expression levels are determined for two or three genes selected from human genes TOP2A, TYMS, and MKI67. In some embodiments, the expression levels of the two or three genes are compared to a corresponding control.

[0184] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes GBP1, IRF1, TAP1, WARS1, and IDO1, wherein the sample is a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0185] In some embodiments, the expression levels are determined for three or more genes, four or more genes, or five genes selected from human genes GBP1, IRF1, TAP1, WARS1, and IDO1. In some embodiments, the expression levels of the three or more genes, four or more genes, or five genes are compared to a corresponding control. In another embodiment, the expression levels are determined for two, three, four, or five genes selected from human genes GBP1, IRF1, TAP1, WARS1, and IDO1. In some embodiments, the expression levels of the two, three, four, or five genes are compared to a corresponding control.

[0186] In a further aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes CLEC10A, CD1C, FCER1A, CD1E, CD1D, and CCR2, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control. 60 314164997v1Attorney Docket No: 243735.000437

[0187] In some embodiments, the expression levels are determined for three or more genes, four or more genes, five or more genes, or six genes selected from human genes CLEC10A, CD1C, FCER1A, CD1E, CD1D, and CCR2. In some embodiments, the expression levels of the three or more genes, four or more genes, five or more genes, or six genes are compared to a corresponding control. In another embodiment, the expression levels are determined for two, three, four, five, or six genes selected from human genes CLEC10A, CD1C, FCER1A, CD1E, CD1D, and CCR2. In some embodiments, the expression levels of the two, three, four, five, or six genes are compared to a corresponding control.

[0188] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes CSF3R, FCGR3B, FPR1, ALPL, MGAM, CXCR1, MXD1, and CXCR2, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0189] In some embodiments, the expression levels are determined for three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, or eight genes selected from human genes CSF3R, FCGR3B, FPR1, ALPL, MGAM, CXCR1, MXD1, and CXCR2. In some embodiments, the expression levels of the three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, or eight genes are compared to a corresponding control. In another embodiment, the expression levels are determined for two, three, four, five, six, seven, or eight genes selected from human genes CSF3R, FCGR3B, FPR1, ALPL, MGAM, CXCR1, MXD1, and CXCR2. In some embodiments, the expression levels of the two, three, four, five, six, seven, or eight genes are compared to a corresponding control.

[0190] In a further aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: 61 314164997v1Attorney Docket No: 243735.000437 a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes MS4A1, CD19, AIM2, BANK1, CD79A, TNFRSF13C, BLK, IGHM, IGHD, XBP1, MZB1, TNFRSF17, CD27, TENT5C, POU2AF1, PRDM1, NUGGC, SDC1, KLRC1, GZMB, TRDC, KLRF1, GNLY, LYZ, MRC1, STAB1, SLCO2B1, F13A1, CD163, MSR1, SLC40A1, CD14, IRF7, TLR7, TLR9, MYD88, STAT1, PLD4, CLEC4C, LILRA4, TPM2, MZB1, SCT, IRF4, SMPD3, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, CD3G, THEMIS, CD5, CD6, CD8B, CD8A, KLRG1, GZMK, CST7, GZMH, LEF1, TCF7, SELL, CD27, CD55, CCR7, CD4, CD40LG, CCR2, CCR6, DPP4, CTLA4, FOXP3, IKZF2, RTKN2, IRF4, IL21, IL2RA, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, MKI67, GBP1, IRF1, TAP1, WARS1, IDO1, CLEC10A, CD1C, FCER1A, CD1E, CD1D, CCR2, CSF3R, FCGR3B, FPR1, ALPL, MGAM, CXCR1, MXD1, and CXCR2, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0191] In some embodiments, the expression levels are determined for three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, eight or more genes, nine or more genes, ten or more genes, eleven or more genes, twelve or more genes, thirteen or more genes, fourteen or more genes, fifteen or more genes, sixteen or more genes, seventeen or more genes, eighteen or more genes, nineteen or more genes, twenty or more genes, twenty-one or more genes, twenty-two or more genes, twenty-three or more genes, twenty-four or more genes, twenty-five or more genes, twenty-six or more genes, twenty-seven or more genes, twenty-eight or more genes, twenty-nine or more genes, thirty or more genes, thirty-one or more genes, thirty-two or more genes, thirty-three or more genes, thirty-four or more genes, thirty-five or more genes, thirty-six or more genes, thirty-seven or more genes, thirty-eight or more genes, thirty-nine or more genes, forty or more genes, forty-one or more genes, forty-two or more genes, forty-three or more genes, forty-four or more genes, forty-five or more genes, forty-six or more genes, forty-seven or more genes, forty-eight or more genes, forty-nine or more genes, fifty or more genes, fifty-one or more genes, fifty-two or more genes, fifty-three or more genes, fifty-four or more genes, fifty-five or more genes, fifty-six or more genes, fifty-seven or 62 314164997v1Attorney Docket No: 243735.000437 more genes, fifty-eight or more genes, fifty-nine or more genes, sixty or more genes, sixty-one or more genes, sixty-two or more genes, sixty-three or more genes, sixty-four or more genes, sixty- five or more genes, sixty-six or more genes, sixty-seven or more genes, sixty-eight or more genes, sixty-nine or more genes, seventy or more genes, seventy-one or more genes, seventy-two or more genes, seventy-three or more genes, seventy-four or more genes, seventy-five or more genes, seventy-six or more genes, seventy-seven or more genes, seventy-eight or more genes, seventy-nine or more genes, eighty or more genes, eighty-one or more genes, eighty-two or more genes, eighty-three or more genes, eighty-four or more genes, eighty-five or more genes, eighty- six or more genes, eighty-seven or more genes, eighty-eight or more genes, eighty-nine or more genes, ninety or more genes, ninety-one or more genes, ninety-two or more genes, ninety-three or more genes, ninety-four or more genes, ninety-five or more genes, ninety-six or more genes, ninety-seven or more genes, ninety-eight or more genes, ninety-nine or more genes, one hundred or more genes, one hundred and one or more genes, one hundred and two or more genes, one hundred and three or more genes, one hundred and four or more genes, one hundred and five or more genes, one hundred and six or more genes, one hundred and seven or more genes, one hundred and eight or more genes, one hundred and nine or more genes, one hundred and ten or more genes, one hundred and eleven or more genes, one hundred and twelve or more genes, one hundred and thirteen or more genes, or one hundred and fourteen genes selected from human genes MS4A1, CD19, AIM2, BANK1, CD79A, TNFRSF13C, BLK, IGHM, IGHD, XBP1, MZB1, TNFRSF17, CD27, TENT5C, POU2AF1, PRDM1, NUGGC, SDC1, KLRC1, GZMB, TRDC, KLRF1, GNLY, LYZ, MRC1, STAB1, SLCO2B1, F13A1, CD163, MSR1, SLC40A1, CD14, IRF7, TLR7, TLR9, MYD88, STAT1, PLD4, CLEC4C, LILRA4, TPM2, MZB1, SCT, IRF4, SMPD3, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, CD3G, THEMIS, CD5, CD6, CD8B, CD8A, KLRG1, GZMK, CST7, GZMH, LEF1, TCF7, SELL, CD27, CD55, CCR7, CD4, CD40LG, CCR2, CCR6, DPP4, CTLA4, FOXP3, IKZF2, RTKN2, IRF4, IL21, IL2RA, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, MKI67, GBP1, IRF1, TAP1, WARS1, IDO1, CLEC10A, CD1C, FCER1A, CD1E, CD1D, CCR2, CSF3R, FCGR3B, FPR1, ALPL, MGAM, CXCR1, MXD1, and CXCR2. In some embodiments, the expression levels of the three or more genes, four or more genes, five or more genes, six or more genes, 63 314164997v1Attorney Docket No: 243735.000437 seven or more genes, eight or more genes, nine or more genes, ten or more genes, eleven or more genes, twelve or more genes, thirteen or more genes, fourteen or more genes, fifteen or more genes, sixteen or more genes, seventeen or more genes, eighteen or more genes, nineteen or more genes, twenty or more genes, twenty-one or more genes, twenty-two or more genes, twenty-three or more genes, twenty-four or more genes, twenty-five or more genes, twenty-six or more genes, twenty-seven or more genes, twenty-eight or more genes, twenty-nine or more genes, thirty or more genes, thirty-one or more genes, thirty-two or more genes, thirty-three or more genes, thirty-four or more genes, thirty-five or more genes, thirty-six or more genes, thirty-seven or more genes, thirty-eight or more genes, thirty-nine or more genes, forty or more genes, forty-one or more genes, forty-two or more genes, forty-three or more genes, forty-four or more genes, forty-five or more genes, forty-six or more genes, forty-seven or more genes, forty-eight or more genes, forty-nine or more genes, fifty or more genes, fifty-one or more genes, fifty-two or more genes, fifty-three or more genes, fifty-four or more genes, fifty-five or more genes, fifty-six or more genes, fifty-seven or more genes, fifty-eight or more genes, fifty-nine or more genes, sixty or more genes, sixty-one or more genes, sixty-two or more genes, sixty-three or more genes, sixty-four or more genes, sixty-five or more genes, sixty-six or more genes, sixty-seven or more genes, sixty-eight or more genes, sixty-nine or more genes, seventy or more genes, seventy-one or more genes, seventy-two or more genes, seventy-three or more genes, seventy-four or more genes, seventy-five or more genes, seventy-six or more genes, seventy-seven or more genes, seventy-eight or more genes, seventy-nine or more genes, eighty or more genes, eighty-one or more genes, eighty-two or more genes, eighty-three or more genes, eighty-four or more genes, eighty-five or more genes, eighty-six or more genes, eighty-seven or more genes, eighty-eight or more genes, eighty-nine or more genes, ninety or more genes, ninety-one or more genes, ninety- two or more genes, ninety-three or more genes, ninety-four or more genes, ninety-five or more genes, ninety-six or more genes, ninety-seven or more genes, ninety-eight or more genes, ninety- nine or more genes, one hundred or more genes, one hundred and one or more genes, one hundred and two or more genes, one hundred and three or more genes, one hundred and four or more genes, one hundred and five or more genes, one hundred and six or more genes, one hundred and seven or more genes, one hundred and eight or more genes, one hundred and nine or more genes, one hundred and ten or more genes, one hundred and eleven or more genes, one hundred and twelve or more genes, one hundred and thirteen or more genes, or one hundred and 64 314164997v1Attorney Docket No: 243735.000437 fourteen genes are compared to a corresponding control. In another embodiment, the expression levels are determined for two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen, twenty, twenty-one, twenty- two, twenty-three, twenty-four, twenty-five, twenty-six, twenty-seven, twenty-eight, twenty- nine, thirty, thirty-one, thirty-two, thirty-three, thirty-four, thirty-five, thirty-six, thirty-seven, thirty-eight, thirty-nine, forty, forty-one, forty-two, forty-three, forty-four, forty-five, forty-six, forty-seven, forty-eight, forty-nine, fifty, fifty-one, fifty-two, fifty-three, fifty-four, fifty-five, fifty-six, fifty-seven, fifty-eight, fifty-nine, sixty, sixty-one, sixty-two, sixty-three, sixty-four, sixty-five, sixty-six, sixty-seven, sixty-eight, sixty-nine, seventy, seventy-one, seventy-two, seventy-three, seventy-four, seventy-five, seventy-six, seventy-seven, seventy-eight, seventy- nine, eighty, eighty-one, eighty-two, eighty-three, eighty-four, eighty-five, eighty-six, eighty- seven, eighty-eight, eighty-nine, ninety, ninety-one, ninety-two, ninety-three, ninety-four, ninety- five, ninety-six, ninety-seven, ninety-eight, ninety-nine, one hundred, one hundred and one, one hundred and two, one hundred and three, one hundred and four, one hundred and five, one hundred and six, one hundred and seven, one hundred and eight, one hundred and nine, one hundred and ten, one hundred and eleven, one hundred and twelve, one hundred and thirteen, or one hundred and fourteen genes selected from human genes MS4A1, CD19, AIM2, BANK1, CD79A, TNFRSF13C, BLK, IGHM, IGHD, XBP1, MZB1, TNFRSF17, CD27, TENT5C, POU2AF1, PRDM1, NUGGC, SDC1, KLRC1, GZMB, TRDC, KLRF1, GNLY, LYZ, MRC1, STAB1, SLCO2B1, F13A1, CD163, MSR1, SLC40A1, CD14, IRF7, TLR7, TLR9, MYD88, STAT1, PLD4, CLEC4C, LILRA4, TPM2, MZB1, SCT, IRF4, SMPD3, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, CD3G, THEMIS, CD5, CD6, CD8B, CD8A, KLRG1, GZMK, CST7, GZMH, LEF1, TCF7, SELL, CD27, CD55, CCR7, CD4, CD40LG, CCR2, CCR6, DPP4, CTLA4, FOXP3, IKZF2, RTKN2, IRF4, IL21, IL2RA, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, MKI67, GBP1, IRF1, TAP1, WARS1, IDO1, CLEC10A, CD1C, FCER1A, CD1E, CD1D, CCR2, CSF3R, FCGR3B, FPR1, ALPL, MGAM, CXCR1, MXD1, and CXCR2. In some embodiments, the expression levels of the two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen, twenty, twenty-one, twenty-two, twenty-three, twenty-four, twenty-five, twenty-six, twenty- 65 314164997v1Attorney Docket No: 243735.000437 seven, twenty-eight, twenty-nine, thirty, thirty-one, thirty-two, thirty-three, thirty-four, thirty- five, thirty-six, thirty-seven, thirty-eight, thirty-nine, forty, forty-one, forty-two, forty-three, forty-four, forty-five, forty-six, forty-seven, forty-eight, forty-nine, fifty, fifty-one, fifty-two, fifty-three, fifty-four, fifty-five, fifty-six, fifty-seven, fifty-eight, fifty-nine, sixty, sixty-one, sixty-two, sixty-three, sixty-four, sixty-five, sixty-six, sixty-seven, sixty-eight, sixty-nine, seventy, seventy-one, seventy-two, seventy-three, seventy-four, seventy-five, seventy-six, seventy-seven, seventy-eight, seventy-nine, eighty, eighty-one, eighty-two, eighty-three, eighty- four, eighty-five, eighty-six, eighty-seven, eighty-eight, eighty-nine, ninety, ninety-one, ninety- two, ninety-three, ninety-four, ninety-five, ninety-six, ninety-seven, ninety-eight, ninety-nine, one hundred, one hundred and one, one hundred and two, one hundred and three, one hundred and four, one hundred and five, one hundred and six, one hundred and seven, one hundred and eight, one hundred and nine, one hundred and ten, one hundred and eleven, one hundred and twelve, one hundred and thirteen, or one hundred and fourteen genes are compared to a corresponding control.

[0192] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes XBP1, MZB1, TNFRSF17, CD27, TENT5C, POU2AF1, PRDM1, NUGGC, SDC1, KLRC1, GZMB, TRDC, KLRF1, GNLY, LYZ, MRC1, STAB1, SLCO2B1, F13A1, CD163, MSR1, SLC40A1, CD14, IRF7, TLR7, TLR9, MYD88, STAT1, PLD4, CLEC4C, LILRA4, TPM2, MZB1, SCT, IRF4, SMPD3, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, MKI67, GBP1, IRF1, TAP1, WARS1, IDO1, CLEC10A, CD1C, FCER1A, CD1E, CD1D, CCR2, CSF3R, FCGR3B, FPR1, ALPL, MGAM, CXCR1, MXD1, and CXCR2, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control. 66 314164997v1Attorney Docket No: 243735.000437

[0193] In some embodiments, the expression levels are determined for three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, eight or more genes, nine or more genes, ten or more genes, eleven or more genes, twelve or more genes, thirteen or more genes, fourteen or more genes, fifteen or more genes, sixteen or more genes, seventeen or more genes, eighteen or more genes, nineteen or more genes, twenty or more genes, twenty-one or more genes, twenty-two or more genes, twenty-three or more genes, twenty-four or more genes, twenty-five or more genes, twenty-six or more genes, twenty-seven or more genes, twenty-eight or more genes, twenty-nine or more genes, thirty or more genes, thirty-one or more genes, thirty-two or more genes, thirty-three or more genes, thirty-four or more genes, thirty-five or more genes, thirty-six or more genes, thirty-seven or more genes, thirty-eight or more genes, thirty-nine or more genes, forty or more genes, forty-one or more genes, forty-two or more genes, forty-three or more genes, forty-four or more genes, forty-five or more genes, forty-six or more genes, forty-seven or more genes, forty-eight or more genes, forty-nine or more genes, fifty or more genes, fifty-one or more genes, fifty-two or more genes, fifty-three or more genes, fifty-four or more genes, fifty-five or more genes, fifty-six or more genes, fifty-seven or more genes, fifty-eight or more genes, fifty-nine or more genes, sixty or more genes, sixty-one or more genes, sixty-two or more genes, sixty-three or more genes, sixty-four or more genes, sixty- five or more genes, sixty-six or more genes, sixty-seven or more genes, sixty-eight or more genes, sixty-nine or more genes, seventy or more genes, seventy-one or more genes, seventy-two or more genes, seventy-three or more genes, seventy-four or more genes, seventy-five or more genes, seventy-six or more genes, seventy-seven or more genes, seventy-eight or more genes, seventy-nine or more genes, eighty or more genes, eighty-one or more genes, eighty-two or more genes, eighty-three or more genes, eighty-four or more genes, eighty-five or more genes, eighty- six or more genes, eighty-seven or more genes, eighty-eight or more genes, eighty-nine or more genes, ninety or more genes, or ninety-one genes, selected from human genes XBP1, MZB1, TNFRSF17, CD27, TENT5C, POU2AF1, PRDM1, NUGGC, SDC1, KLRC1, GZMB, TRDC, KLRF1, GNLY, LYZ, MRC1, STAB1, SLCO2B1, F13A1, CD163, MSR1, SLC40A1, CD14, IRF7, TLR7, TLR9, MYD88, STAT1, PLD4, CLEC4C, LILRA4, TPM2, MZB1, SCT, IRF4, SMPD3, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, 67 314164997v1Attorney Docket No: 243735.000437 FASLG, TOP2A, TYMS, MKI67, GBP1, IRF1, TAP1, WARS1, IDO1, CLEC10A, CD1C, FCER1A, CD1E, CD1D, CCR2, CSF3R, FCGR3B, FPR1, ALPL, MGAM, CXCR1, MXD1, and CXCR2. In some embodiments, the expression levels of the three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, eight or more genes, nine or more genes, ten or more genes, eleven or more genes, twelve or more genes, thirteen or more genes, fourteen or more genes, fifteen or more genes, sixteen or more genes, seventeen or more genes, eighteen or more genes, nineteen or more genes, twenty or more genes, twenty-one or more genes, twenty-two or more genes, twenty-three or more genes, twenty-four or more genes, twenty-five or more genes, twenty-six or more genes, twenty-seven or more genes, twenty-eight or more genes, twenty-nine or more genes, thirty or more genes, thirty-one or more genes, thirty-two or more genes, thirty-three or more genes, thirty-four or more genes, thirty-five or more genes, thirty-six or more genes, thirty-seven or more genes, thirty-eight or more genes, thirty-nine or more genes, forty or more genes, forty-one or more genes, forty-two or more genes, forty-three or more genes, forty-four or more genes, forty-five or more genes, forty-six or more genes, forty-seven or more genes, forty-eight or more genes, forty-nine or more genes, fifty or more genes, fifty-one or more genes, fifty-two or more genes, fifty-three or more genes, fifty- four or more genes, fifty-five or more genes, fifty-six or more genes, fifty-seven or more genes, fifty-eight or more genes, fifty-nine or more genes, sixty or more genes, sixty-one or more genes, sixty-two or more genes, sixty-three or more genes, sixty-four or more genes, sixty-five or more genes, sixty-six or more genes, sixty-seven or more genes, sixty-eight or more genes, sixty-nine or more genes, seventy or more genes, seventy-one or more genes, seventy-two or more genes, seventy-three or more genes, seventy-four or more genes, seventy-five or more genes, seventy- six or more genes, seventy-seven or more genes, seventy-eight or more genes, seventy-nine or more genes, eighty or more genes, eighty-one or more genes, eighty-two or more genes, eighty- three or more genes, eighty-four or more genes, eighty-five or more genes, eighty-six or more genes, eighty-seven or more genes, eighty-eight or more genes, eighty-nine or more genes, ninety or more genes, or ninety-one genes are compared to a corresponding control. In another embodiment, the expression levels are determined for two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen, twenty, twenty-one, twenty-two, twenty-three, twenty-four, twenty-five, twenty-six, twenty- seven, twenty-eight, twenty-nine, thirty, thirty-one, thirty-two, thirty-three, thirty-four, thirty- 68 314164997v1Attorney Docket No: 243735.000437 five, thirty-six, thirty-seven, thirty-eight, thirty-nine, forty, forty-one, forty-two, forty-three, forty-four, forty-five, forty-six, forty-seven, forty-eight, forty-nine, fifty, fifty-one, fifty-two, fifty-three, fifty-four, fifty-five, fifty-six, fifty-seven, fifty-eight, fifty-nine, sixty, sixty-one, sixty-two, sixty-three, sixty-four, sixty-five, sixty-six, sixty-seven, sixty-eight, sixty-nine, seventy, seventy-one, seventy-two, seventy-three, seventy-four, seventy-five, seventy-six, seventy-seven, seventy-eight, seventy-nine, eighty, eighty-one, eighty-two, eighty-three, eighty- four, eighty-five, eighty-six, eighty-seven, eighty-eight, eighty-nine, ninety, or ninety-one genes, selected from human genes XBP1, MZB1, TNFRSF17, CD27, TENT5C, POU2AF1, PRDM1, NUGGC, SDC1, KLRC1, GZMB, TRDC, KLRF1, GNLY, LYZ, MRC1, STAB1, SLCO2B1, F13A1, CD163, MSR1, SLC40A1, CD14, IRF7, TLR7, TLR9, MYD88, STAT1, PLD4, CLEC4C, LILRA4, TPM2, MZB1, SCT, IRF4, SMPD3, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, MKI67, GBP1, IRF1, TAP1, WARS1, IDO1, CLEC10A, CD1C, FCER1A, CD1E, CD1D, CCR2, CSF3R, FCGR3B, FPR1, ALPL, MGAM, CXCR1, MXD1, and CXCR2. In some embodiments, the expression levels of the two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen, twenty, twenty-one, twenty-two, twenty- three, twenty-four, twenty-five, twenty-six, twenty-seven, twenty-eight, twenty-nine, thirty, thirty-one, thirty-two, thirty-three, thirty-four, thirty-five, thirty-six, thirty-seven, thirty-eight, thirty-nine, forty, forty-one, forty-two, forty-three, forty-four, forty-five, forty-six, forty-seven, forty-eight, forty-nine, fifty, fifty-one, fifty-two, fifty-three, fifty-four, fifty-five, fifty-six, fifty- seven, fifty-eight, fifty-nine, sixty, sixty-one, sixty-two, sixty-three, sixty-four, sixty-five, sixty- six, sixty-seven, sixty-eight, sixty-nine, seventy, seventy-one, seventy-two, seventy-three, seventy-four, seventy-five, seventy-six, seventy-seven, seventy-eight, seventy-nine, eighty, eighty-one, eighty-two, eighty-three, eighty-four, eighty-five, eighty-six, eighty-seven, eighty- eight, eighty-nine, ninety, or ninety-one genes are compared to a corresponding control.

[0194] In a further aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: 69 314164997v1Attorney Docket No: 243735.000437 a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes MS4A1, CD19, AIM2, BANK1, CD79A, TNFRSF13C, BLK, IGHM, IGHD, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, CD3G, THEMIS, CD5, CD6, CD8B, CD8A, KLRG1, GZMK, CST7, GZMH, LEF1, TCF7, SELL, CD27, CD55, CCR7, CD4, CD40LG, CCR2, CCR6, DPP4, CTLA4, FOXP3, IKZF2, RTKN2, IRF4, IL21, IL2RA, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, and MKI67, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0195] In some embodiments, the expression levels are determined for three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, eight or more genes, nine or more genes, ten or more genes, eleven or more genes, twelve or more genes, thirteen or more genes, fourteen or more genes, fifteen or more genes, sixteen or more genes, seventeen or more genes, eighteen or more genes, nineteen or more genes, twenty or more genes, twenty-one or more genes, twenty-two or more genes, twenty-three or more genes, twenty-four or more genes, twenty-five or more genes, twenty-six or more genes, twenty-seven or more genes, twenty-eight or more genes, twenty-nine or more genes, thirty or more genes, thirty-one or more genes, thirty-two or more genes, thirty-three or more genes, thirty-four or more genes, thirty-five or more genes, thirty-six or more genes, thirty-seven or more genes, thirty-eight or more genes, thirty-nine or more genes, forty or more genes, forty-one or more genes, forty-two or more genes, forty-three or more genes, forty-four or more genes, forty-five or more genes, forty-six or more genes, forty-seven or more genes, forty-eight or more genes, forty-nine or more genes, fifty or more genes, fifty-one or more genes, fifty-two or more genes, fifty-three or more genes, fifty-four or more genes, fifty-five or more genes, fifty-six or more genes, fifty-seven or more genes, fifty-eight or more genes, fifty-nine or more genes, sixty or more genes, sixty-one or more genes, sixty-two or more genes, sixty-three or more genes, sixty-four or more genes, sixty- five or more genes, sixty-six or more genes, sixty-seven or more genes, sixty-eight or more genes, sixty-nine or more genes, seventy or more genes, seventy-one or more genes, seventy-two 70 314164997v1Attorney Docket No: 243735.000437 or more genes, or seventy-three genes selected from human genes MS4A1, CD19, AIM2, BANK1, CD79A, TNFRSF13C, BLK, IGHM, IGHD, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, CD3G, THEMIS, CD5, CD6, CD8B, CD8A, KLRG1, GZMK, CST7, GZMH, LEF1, TCF7, SELL, CD27, CD55, CCR7, CD4, CD40LG, CCR2, CCR6, DPP4, CTLA4, FOXP3, IKZF2, RTKN2, IRF4, IL21, IL2RA, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, and MKI67. In some embodiments, the expression levels of the three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, eight or more genes, nine or more genes, ten or more genes, eleven or more genes, twelve or more genes, thirteen or more genes, fourteen or more genes, fifteen or more genes, sixteen or more genes, seventeen or more genes, eighteen or more genes, nineteen or more genes, twenty or more genes, twenty-one or more genes, twenty-two or more genes, twenty-three or more genes, twenty-four or more genes, twenty-five or more genes, twenty-six or more genes, twenty-seven or more genes, twenty-eight or more genes, twenty-nine or more genes, thirty or more genes, thirty-one or more genes, thirty-two or more genes, thirty-three or more genes, thirty-four or more genes, thirty-five or more genes, thirty-six or more genes, thirty-seven or more genes, thirty-eight or more genes, thirty-nine or more genes, forty or more genes, forty-one or more genes, forty-two or more genes, forty-three or more genes, forty-four or more genes, forty-five or more genes, forty-six or more genes, forty-seven or more genes, forty-eight or more genes, forty-nine or more genes, fifty or more genes, fifty-one or more genes, fifty-two or more genes, fifty-three or more genes, fifty- four or more genes, fifty-five or more genes, fifty-six or more genes, fifty-seven or more genes, fifty-eight or more genes, fifty-nine or more genes, sixty or more genes, sixty-one or more genes, sixty-two or more genes, sixty-three or more genes, sixty-four or more genes, sixty-five or more genes, sixty-six or more genes, sixty-seven or more genes, sixty-eight or more genes, sixty-nine or more genes, seventy or more genes, seventy-one or more genes, seventy-two or more genes, or seventy-three genes are compared to a corresponding control. In another embodiment, the expression levels are determined for two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen, twenty, twenty-one, twenty-two, twenty-three, twenty-four, twenty-five, twenty-six, twenty-seven, twenty-eight, twenty-nine, thirty, thirty-one, thirty-two, thirty-three, thirty-four, thirty-five, thirty-six, thirty- 71 314164997v1Attorney Docket No: 243735.000437 seven, thirty-eight, thirty-nine, forty, forty-one, forty-two, forty-three, forty-four, forty-five, forty-six, forty-seven, forty-eight, forty-nine, fifty, fifty-one, fifty-two, fifty-three, fifty-four, fifty-five, fifty-six, fifty-seven, fifty-eight, fifty-nine, sixty, sixty-one, sixty-two, sixty-three, sixty-four, sixty-five, sixty-six, sixty-seven, sixty-eight, sixty-nine, seventy, seventy-one, seventy-two, or seventy-three genes selected from human genes MS4A1, CD19, AIM2, BANK1, CD79A, TNFRSF13C, BLK, IGHM, IGHD, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, CD3G, THEMIS, CD5, CD6, CD8B, CD8A, KLRG1, GZMK, CST7, GZMH, LEF1, TCF7, SELL, CD27, CD55, CCR7, CD4, CD40LG, CCR2, CCR6, DPP4, CTLA4, FOXP3, IKZF2, RTKN2, IRF4, IL21, IL2RA, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, and MKI67. In some embodiments, the expression levels of the two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen, twenty, twenty-one, twenty-two, twenty-three, twenty-four, twenty-five, twenty-six, twenty- seven, twenty-eight, twenty-nine, thirty, thirty-one, thirty-two, thirty-three, thirty-four, thirty- five, thirty-six, thirty-seven, thirty-eight, thirty-nine, forty, forty-one, forty-two, forty-three, forty-four, forty-five, forty-six, forty-seven, forty-eight, forty-nine, fifty, fifty-one, fifty-two, fifty-three, fifty-four, fifty-five, fifty-six, fifty-seven, fifty-eight, fifty-nine, sixty, sixty-one, sixty-two, sixty-three, sixty-four, sixty-five, sixty-six, sixty-seven, sixty-eight, sixty-nine, seventy, seventy-one, seventy-two, or seventy-three genes are compared to a corresponding control.

[0196] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from porcine genes SPP1, COLEC11, S100A6, NFKBIZ, CLDN1, THBS1, HIF1A, STMN1, ICAM1, TNFRSF1B, CXCL14, IL1RL1, and NREP, wherein the sample is a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control. 72 314164997v1Attorney Docket No: 243735.000437

[0197] In some embodiments, the expression levels are determined for three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, eight or more genes, nine or more genes, ten or more genes, eleven or more genes, twelve or more genes, or thirteen genes selected from porcine genes SPP1, COLEC11, S100A6, NFKBIZ, CLDN1, THBS1, HIF1A, STMN1, ICAM1, TNFRSF1B, CXCL14, IL1RL1, and NREP. In some embodiments, the expression levels of the three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, eight or more genes, nine or more genes, ten or more genes, eleven or more genes, twelve or more genes, or thirteen genes are compared to a corresponding control. In another embodiment, the expression levels are determined for two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, or thirteen genes selected from porcine genes SPP1, COLEC11, S100A6, NFKBIZ, CLDN1, THBS1, HIF1A, STMN1, ICAM1, TNFRSF1B, CXCL14, IL1RL1, and NREP. In some embodiments, the expression levels of the two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, or thirteen genes are compared to a corresponding control.

[0198] In a further aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from porcine genes C3, CXCL2, C4A, LYZ, S100A6, S100A11, MX1, MX2, IL33, and HIF1A, wherein the sample is a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0199] In some embodiments, the expression levels are determined for three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, eight or more genes, nine or more genes, or ten genes selected from porcine genes C3, CXCL2, C4A, LYZ, S100A6, S100A11, MX1, MX2, IL33, and HIF1A. In some embodiments, the expression levels of the three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, eight or more genes, nine or more genes, or ten genes are compared to a corresponding control. In another embodiment, the expression levels are determined for two, three, four, five, six, seven, eight, nine, or ten genes selected from porcine genes C3, CXCL2, 73 314164997v1Attorney Docket No: 243735.000437 C4A, LYZ, S100A6, S100A11, MX1, MX2, IL33, and HIF1A. In some embodiments, the expression levels of the two, three, four, five, six, seven, eight, nine, or ten genes are compared to a corresponding control.

[0200] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from porcine genes PDGFRB, PECAM1, STAT3, IL33, RGS5, CD163, C3, VCAM1, TNC, CD74, SERPINE1, CCR5, TEK, RUNX1, MX2, IFIT1, COL1A1, CXCL14, MRC1, CD68, CD14, MX1, and LYVE1, wherein the sample is a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0201] In some embodiments, the expression levels are determined for three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, eight or more genes, nine or more genes, ten or more genes, eleven or more genes, twelve or more genes, thirteen or more genes, fourteen or more genes, fifteen or more genes, sixteen or more genes, seventeen or more genes, eighteen or more genes, nineteen or more genes, twenty or more genes, twenty-one or more genes, twenty-two or more genes, or twenty-three genes selected from porcine genes PDGFRB, PECAM1, STAT3, IL33, RGS5, CD163, C3, VCAM1, TNC, CD74, SERPINE1, CCR5, TEK, RUNX1, MX2, IFIT1, COL1A1, CXCL14, MRC1, CD68, CD14, MX1, and LYVE1. In some embodiments, the expression levels of the three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, eight or more genes, nine or more genes, ten or more genes, eleven or more genes, twelve or more genes, thirteen or more genes, fourteen or more genes, fifteen or more genes, sixteen or more genes, seventeen or more genes, eighteen or more genes, nineteen or more genes, twenty or more genes, twenty-one or more genes, twenty-two or more genes, or twenty-three genes are compared to a corresponding control. In another embodiment, the expression levels are determined for two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen, twenty, twenty-one, twenty-two, or twenty-three genes selected from porcine genes PDGFRB, PECAM1, STAT3, IL33, RGS5, CD163, C3, VCAM1, TNC, 74 314164997v1Attorney Docket No: 243735.000437 CD74, SERPINE1, CCR5, TEK, RUNX1, MX2, IFIT1, COL1A1, CXCL14, MRC1, CD68, CD14, MX1, and LYVE1. In some embodiments, the expression levels of the two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen, twenty, twenty-one, twenty-two, or twenty-three genes are compared to a corresponding control.

[0202] In a further aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from porcine genes HIF1A, LMNA, EMP1, EIF4A1, DHX9, LYVE1, YWHAQ, CD163, VCAM1, MKI67, IFIT1, ICAM1, STAT1, STAT3, TOP2A, S100A6, WARS1, S100A1, SERPINH1, TOP2A, MX1, MX2, CD14, HSPA9, and HSPD1, wherein the sample is a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0203] In some embodiments, the expression levels are determined for three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, eight or more genes, nine or more genes, ten or more genes, eleven or more genes, twelve or more genes, thirteen or more genes, fourteen or more genes, fifteen or more genes, sixteen or more genes, seventeen or more genes, eighteen or more genes, nineteen or more genes, twenty or more genes, twenty-one or more genes, twenty-two or more genes, twenty-three or more genes, twenty-four or more genes, or twenty-five genes selected from porcine genes HIF1A, LMNA, EMP1, EIF4A1, DHX9, LYVE1, YWHAQ, CD163, VCAM1, MKI67, IFIT1, ICAM1, STAT1, STAT3, TOP2A, S100A6, WARS1, S100A1, SERPINH1, TOP2A, MX1, MX2, CD14, HSPA9, and HSPD1. In some embodiments, the expression levels of the three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, eight or more genes, nine or more genes, ten or more genes, eleven or more genes, twelve or more genes, thirteen or more genes, fourteen or more genes, fifteen or more genes, sixteen or more genes, seventeen or more genes, eighteen or more genes, nineteen or more genes, twenty or more genes, twenty-one or more genes, twenty-two or more genes, twenty-three or more genes, twenty-four or more genes, 75 314164997v1Attorney Docket No: 243735.000437 or twenty-five genes are compared to a corresponding control. In another embodiment, the expression levels are determined for two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen, twenty, twenty-one, twenty-two, twenty-three, twenty-four, or twenty-five genes selected from porcine genes HIF1A, LMNA, EMP1, EIF4A1, DHX9, LYVE1, YWHAQ, CD163, VCAM1, MKI67, IFIT1, ICAM1, STAT1, STAT3, TOP2A, S100A6, WARS1, S100A1, SERPINH1, TOP2A, MX1, MX2, CD14, HSPA9, and HSPD1. In some embodiments, the expression levels of the two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen, twenty, twenty-one, twenty-two, twenty-three, twenty-four, or twenty-five genes are compared to a corresponding control.

[0204] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from porcine genes SPP1, COLEC11, S100A6, NFKBIZ, CLDN1, THBS1, HIF1A, STMN1, ICAM1, TNFRSF1B, CXCL14, IL1RL1, NREP, C3, CXCL2, C4A, LYZ, S100A6, S100A11, MX1, MX2, IL33, HIF1A, PDGFRB, PECAM1, STAT3, IL33, RGS5, CD163, C3, VCAM1, TNC, CD74, SERPINE1, CCR5, TEK, RUNX1, MX2, IFIT1, COL1A1, CXCL14, MRC1, CD68, CD14, MX1, LYVE1, HIF1A, LMNA, EMP1, EIF4A1, DHX9, LYVE1, YWHAQ, CD163, VCAM1, MKI67, IFIT1, ICAM1, STAT1, STAT3, TOP2A, S100A6, WARS1, S100A1, SERPINH1, TOP2A, MX1, MX2, CD14, HSPA9, and HSPD1, wherein the sample is a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0205] In some embodiments, the expression levels are determined for three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, eight or more genes, nine or more genes, ten or more genes, eleven or more genes, twelve or more genes, thirteen or more genes, fourteen or more genes, fifteen or more genes, sixteen or more genes, seventeen or more genes, eighteen or more genes, nineteen or more genes, twenty or more genes, twenty-one or more genes, twenty-two or more genes, twenty-three or more genes, twenty-four 76 314164997v1Attorney Docket No: 243735.000437 or more genes, twenty-five or more genes, twenty-six or more genes, twenty-seven or more genes, twenty-eight or more genes, twenty-nine or more genes, thirty or more genes, thirty-one or more genes, thirty-two or more genes, thirty-three or more genes, thirty-four or more genes, thirty-five or more genes, thirty-six or more genes, thirty-seven or more genes, thirty-eight or more genes, thirty-nine or more genes, forty or more genes, forty-one or more genes, forty-two or more genes, forty-three or more genes, forty-four or more genes, forty-five or more genes, forty-six or more genes, forty-seven or more genes, forty-eight or more genes, forty-nine or more genes, fifty or more genes, fifty-one or more genes, fifty-two or more genes, fifty-three or more genes, fifty-four or more genes, fifty-five or more genes, fifty-six or more genes, fifty-seven or more genes, fifty-eight or more genes, fifty-nine or more genes, sixty or more genes, sixty-one or more genes, sixty-two or more genes, sixty-three or more genes, sixty-four or more genes, sixty- five or more genes, sixty-six or more genes, sixty-seven or more genes, sixty-eight or more genes, sixty-nine or more genes, seventy or more genes, or seventy-one genes selected from porcine genes SPP1, COLEC11, S100A6, NFKBIZ, CLDN1, THBS1, HIF1A, STMN1, ICAM1, TNFRSF1B, CXCL14, IL1RL1, NREP, C3, CXCL2, C4A, LYZ, S100A6, S100A11, MX1, MX2, IL33, HIF1A, PDGFRB, PECAM1, STAT3, IL33, RGS5, CD163, C3, VCAM1, TNC, CD74, SERPINE1, CCR5, TEK, RUNX1, MX2, IFIT1, COL1A1, CXCL14, MRC1, CD68, CD14, MX1, LYVE1, HIF1A, LMNA, EMP1, EIF4A1, DHX9, LYVE1, YWHAQ, CD163, VCAM1, MKI67, IFIT1, ICAM1, STAT1, STAT3, TOP2A, S100A6, WARS1, S100A1, SERPINH1, TOP2A, MX1, MX2, CD14, HSPA9, and HSPD1. In some embodiments, the expression levels of the three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, eight or more genes, nine or more genes, ten or more genes, eleven or more genes, twelve or more genes, thirteen or more genes, fourteen or more genes, fifteen or more genes, sixteen or more genes, seventeen or more genes, eighteen or more genes, nineteen or more genes, twenty or more genes, twenty-one or more genes, twenty-two or more genes, twenty-three or more genes, twenty-four or more genes, twenty-five or more genes, twenty-six or more genes, twenty-seven or more genes, twenty-eight or more genes, twenty-nine or more genes, thirty or more genes, thirty-one or more genes, thirty-two or more genes, thirty-three or more genes, thirty-four or more genes, thirty-five or more genes, thirty-six or more genes, thirty- seven or more genes, thirty-eight or more genes, thirty-nine or more genes, forty or more genes, forty-one or more genes, forty-two or more genes, forty-three or more genes, forty-four or more 77 314164997v1Attorney Docket No: 243735.000437 genes, forty-five or more genes, forty-six or more genes, forty-seven or more genes, forty-eight or more genes, forty-nine or more genes, fifty or more genes, fifty-one or more genes, fifty-two or more genes, fifty-three or more genes, fifty-four or more genes, fifty-five or more genes, fifty- six or more genes, fifty-seven or more genes, fifty-eight or more genes, fifty-nine or more genes, sixty or more genes, sixty-one or more genes, sixty-two or more genes, sixty-three or more genes, sixty-four or more genes, sixty-five or more genes, sixty-six or more genes, sixty-seven or more genes, sixty-eight or more genes, sixty-nine or more genes, seventy or more genes, or seventy-one genes are compared to a corresponding control. In another embodiment, the expression levels are determined for two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen, twenty, twenty-one, twenty-two, twenty-three, twenty-four, twenty-five, twenty-six, twenty-seven, twenty-eight, twenty-nine, thirty, thirty-one, thirty-two, thirty-three, thirty-four, thirty-five, thirty-six, thirty- seven, thirty-eight, thirty-nine, forty, forty-one, forty-two, forty-three, forty-four, forty-five, forty-six, forty-seven, forty-eight, forty-nine, fifty, fifty-one, fifty-two, fifty-three, fifty-four, fifty-five, fifty-six, fifty-seven, fifty-eight, fifty-nine, sixty, sixty-one, sixty-two, sixty-three, sixty-four, sixty-five, sixty-six, sixty-seven, sixty-eight, sixty-nine, seventy, or seventy-one genes selected from porcine genes SPP1, COLEC11, S100A6, NFKBIZ, CLDN1, THBS1, HIF1A, STMN1, ICAM1, TNFRSF1B, CXCL14, IL1RL1, NREP, C3, CXCL2, C4A, LYZ, S100A6, S100A11, MX1, MX2, IL33, HIF1A, PDGFRB, PECAM1, STAT3, IL33, RGS5, CD163, C3, VCAM1, TNC, CD74, SERPINE1, CCR5, TEK, RUNX1, MX2, IFIT1, COL1A1, CXCL14, MRC1, CD68, CD14, MX1, LYVE1, HIF1A, LMNA, EMP1, EIF4A1, DHX9, LYVE1, YWHAQ, CD163, VCAM1, MKI67, IFIT1, ICAM1, STAT1, STAT3, TOP2A, S100A6, WARS1, S100A1, SERPINH1, TOP2A, MX1, MX2, CD14, HSPA9, and HSPD1. In some embodiments, the expression levels of the two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen, twenty, twenty- one, twenty-two, twenty-three, twenty-four, twenty-five, twenty-six, twenty-seven, twenty-eight, twenty-nine, thirty, thirty-one, thirty-two, thirty-three, thirty-four, thirty-five, thirty-six, thirty- seven, thirty-eight, thirty-nine, forty, forty-one, forty-two, forty-three, forty-four, forty-five, forty-six, forty-seven, forty-eight, forty-nine, fifty, fifty-one, fifty-two, fifty-three, fifty-four, fifty-five, fifty-six, fifty-seven, fifty-eight, fifty-nine, sixty, sixty-one, sixty-two, sixty-three, 78 314164997v1Attorney Docket No: 243735.000437 sixty-four, sixty-five, sixty-six, sixty-seven, sixty-eight, sixty-nine, seventy, or seventy-one genes are compared to a corresponding control.

[0206] In a further aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from 1) human genes MS4A1, CD19, AIM2, BANK1, CD79A, TNFRSF13C, BLK, IGHM, IGHD, XBP1, MZB1, TNFRSF17, CD27, TENT5C, POU2AF1, PRDM1, NUGGC, SDC1, KLRC1, GZMB, TRDC, KLRF1, GNLY, LYZ, MRC1, STAB1, SLCO2B1, F13A1, CD163, MSR1, SLC40A1, CD14, IRF7, TLR7, TLR9, MYD88, STAT1, PLD4, CLEC4C, LILRA4, TPM2, MZB1, SCT, IRF4, SMPD3, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, CD3G, THEMIS, CD5, CD6, CD8B, CD8A, KLRG1, GZMK, CST7, GZMH, LEF1, TCF7, SELL, CD27, CD55, CCR7, CD4, CD40LG, CCR2, CCR6, DPP4, CTLA4, FOXP3, IKZF2, RTKN2, IRF4, IL21, IL2RA, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, MKI67, GBP1, IRF1, TAP1, WARS1, IDO1, CLEC10A, CD1C, FCER1A, CD1E, CD1D, CCR2, CSF3R, FCGR3B, FPR1, ALPL, MGAM, CXCR1, MXD1, and CXCR2, and 2) porcine genes SPP1, COLEC11, S100A6, NFKBIZ, CLDN1, THBS1, HIF1A, STMN1, ICAM1, TNFRSF1B, CXCL14, IL1RL1, NREP, C3, CXCL2, C4A, LYZ, S100A6, S100A11, MX1, MX2, IL33, HIF1A, PDGFRB, PECAM1, STAT3, IL33, RGS5, CD163, C3, VCAM1, TNC, CD74, SERPINE1, CCR5, TEK, RUNX1, MX2, IFIT1, COL1A1, CXCL14, MRC1, CD68, CD14, MX1, LYVE1, HIF1A, LMNA, EMP1, EIF4A1, DHX9, LYVE1, YWHAQ, CD163, VCAM1, MKI67, IFIT1, ICAM1, STAT1, STAT3, TOP2A, S100A6, WARS1, S100A1, SERPINH1, TOP2A, MX1, MX2, CD14, HSPA9, and HSPD1, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

[0207] In some embodiments, the expression levels are determined for three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, eight or more 79 314164997v1Attorney Docket No: 243735.000437 genes, nine or more genes, ten or more genes, eleven or more genes, twelve or more genes, thirteen or more genes, fourteen or more genes, fifteen or more genes, sixteen or more genes, seventeen or more genes, eighteen or more genes, nineteen or more genes, twenty or more genes, twenty-one or more genes, twenty-two or more genes, twenty-three or more genes, twenty-four or more genes, twenty-five or more genes, twenty-six or more genes, twenty-seven or more genes, twenty-eight or more genes, twenty-nine or more genes, thirty or more genes, thirty-one or more genes, thirty-two or more genes, thirty-three or more genes, thirty-four or more genes, thirty-five or more genes, thirty-six or more genes, thirty-seven or more genes, thirty-eight or more genes, thirty-nine or more genes, forty or more genes, forty-one or more genes, forty-two or more genes, forty-three or more genes, forty-four or more genes, forty-five or more genes, forty-six or more genes, forty-seven or more genes, forty-eight or more genes, forty-nine or more genes, fifty or more genes, fifty-one or more genes, fifty-two or more genes, fifty-three or more genes, fifty-four or more genes, fifty-five or more genes, fifty-six or more genes, fifty-seven or more genes, fifty-eight or more genes, fifty-nine or more genes, sixty or more genes, sixty-one or more genes, sixty-two or more genes, sixty-three or more genes, sixty-four or more genes, sixty- five or more genes, sixty-six or more genes, sixty-seven or more genes, sixty-eight or more genes, sixty-nine or more genes, seventy or more genes, seventy-one or more genes, seventy-two or more genes, seventy-three or more genes, seventy-four or more genes, seventy-five or more genes, seventy-six or more genes, seventy-seven or more genes, seventy-eight or more genes, seventy-nine or more genes, eighty or more genes, eighty-one or more genes, eighty-two or more genes, eighty-three or more genes, eighty-four or more genes, eighty-five or more genes, eighty- six or more genes, eighty-seven or more genes, eighty-eight or more genes, eighty-nine or more genes, ninety or more genes, ninety-one or more genes, ninety-two or more genes, ninety-three or more genes, ninety-four or more genes, ninety-five or more genes, ninety-six or more genes, ninety-seven or more genes, ninety-eight or more genes, ninety-nine or more genes, one hundred or more genes, one hundred and one or more genes, one hundred and two or more genes, one hundred and three or more genes, one hundred and four or more genes, one hundred and five or more genes, one hundred and six or more genes, one hundred and seven or more genes, one hundred and eight or more genes, one hundred and nine or more genes, one hundred and ten or more genes, one hundred and eleven or more genes, one hundred and twelve or more genes, one hundred and thirteen or more genes, one hundred and fourteen or more genes, one hundred and 80 314164997v1Attorney Docket No: 243735.000437 fifteen or more genes, one hundred and sixteen or more genes, one hundred and seventeen or more genes, one hundred and eighteen or more genes, one hundred and nineteen or more genes, one hundred and twenty or more genes, one hundred and twenty-one or more genes, one hundred and twenty-two or more genes, one hundred and twenty-three or more genes, one hundred and twenty-four or more genes, one hundred and twenty-five or more genes, one hundred and twenty-six or more genes, one twenty-seven or more genes, one hundred and twenty-eight or more genes, one hundred and twenty-nine or more genes, one hundred and thirty or more genes, one hundred and thirty-one or more genes, one hundred and thirty-two or more genes, one hundred and thirty-three or more genes, one hundred and thirty-four or more genes, one hundred and thirty-five or more genes, one hundred and thirty-six or more genes, one hundred and thirty- seven or more genes, one hundred and thirty-eight or more genes, one hundred and thirty-nine or more genes, one hundred and forty or more genes, one hundred and forty-one or more genes, one hundred and forty-two or more genes, one hundred and forty-three or more genes, one hundred and forty-four or more genes, one hundred and forty-five or more genes, one hundred and forty- six or more genes, one hundred and forty-seven or more genes, one hundred and forty-eight or more genes, one hundred and forty-nine or more genes, one hundred and fifty or more genes, one hundred and fifty-one or more genes, one hundred and fifty-two or more genes, one hundred and fifty-three or more genes, one hundred and fifty-four or more genes, one hundred and fifty-five or more genes, one hundred and fifty-six or more genes, one hundred and fifty-seven or more genes, one hundred and fifty-eight or more genes, one hundred and fifty-nine or more genes, one hundred and sixty or more genes, one hundred and sixty-one or more genes, one hundred and sixty-two or more genes, one hundred and sixty-three or more genes, one hundred and sixty-four or more genes, one hundred and sixty-five or more genes, one hundred and sixty-six or more genes, one hundred and sixty-seven or more genes, one hundred and sixty-eight or more genes, one hundred and sixty-nine or more genes, one hundred and seventy or more genes, one hundred and seventy-one or more genes, one hundred and seventy-two or more genes, one hundred and seventy-three or more genes, one hundred and seventy-four or more genes, one hundred and seventy-five or more genes, one hundred and seventy-six or more genes, one hundred and seventy-seven or more genes, one hundred and seventy-eight or more genes, one hundred and seventy-nine or more genes, one hundred and eighty or more genes, one hundred and eighty-one or more genes, one hundred and eighty-two or more genes, one hundred and eighty-three or more 81 314164997v1Attorney Docket No: 243735.000437 genes, one hundred and eighty-four or more genes, one hundred and eighty-five or more genes, one hundred and eighty-six or more genes, one hundred and eighty-seven or more genes, one hundred and eighty-eight or more genes, one hundred and eighty-nine or more genes, one hundred and ninety or more genes, one hundred and ninety-one or more genes, one hundred and ninety-two or more genes, one hundred and ninety-three or more genes, one hundred and ninety- four or more genes, one hundred and ninety-five or more genes, one hundred and ninety-six or more genes, one hundred and ninety-seven or more genes, one hundred and ninety-eight or more genes, or one hundred and ninety-nine genes selected from 1) human genes MS4A1, CD19, AIM2, BANK1, CD79A, TNFRSF13C, BLK, IGHM, IGHD, XBP1, MZB1, TNFRSF17, CD27, TENT5C, POU2AF1, PRDM1, NUGGC, SDC1, KLRC1, GZMB, TRDC, KLRF1, GNLY, LYZ, MRC1, STAB1, SLCO2B1, F13A1, CD163, MSR1, SLC40A1, CD14, IRF7, TLR7, TLR9, MYD88, STAT1, PLD4, CLEC4C, LILRA4, TPM2, MZB1, SCT, IRF4, SMPD3, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, CD3G, THEMIS, CD5, CD6, CD8B, CD8A, KLRG1, GZMK, CST7, GZMH, LEF1, TCF7, SELL, CD27, CD55, CCR7, CD4, CD40LG, CCR2, CCR6, DPP4, CTLA4, FOXP3, IKZF2, RTKN2, IRF4, IL21, IL2RA, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, MKI67, GBP1, IRF1, TAP1, WARS1, IDO1, CLEC10A, CD1C, FCER1A, CD1E, CD1D, CCR2, CSF3R, FCGR3B, FPR1, ALPL, MGAM, CXCR1, MXD1, and CXCR2, and 2) porcine genes SPP1, COLEC11, S100A6, NFKBIZ, CLDN1, THBS1, HIF1A, STMN1, ICAM1, TNFRSF1B, CXCL14, IL1RL1, NREP, C3, CXCL2, C4A, LYZ, S100A6, S100A11, MX1, MX2, IL33, HIF1A, PDGFRB, PECAM1, STAT3, IL33, RGS5, CD163, C3, VCAM1, TNC, CD74, SERPINE1, CCR5, TEK, RUNX1, MX2, IFIT1, COL1A1, CXCL14, MRC1, CD68, CD14, MX1, LYVE1, HIF1A, LMNA, EMP1, EIF4A1, DHX9, LYVE1, YWHAQ, CD163, VCAM1, MKI67, IFIT1, ICAM1, STAT1, STAT3, TOP2A, S100A6, WARS1, S100A1, SERPINH1, TOP2A, MX1, MX2, CD14, HSPA9, and HSPD1. In some embodiments, the expression levels of the three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, eight or more genes, nine or more genes, ten or more genes, eleven or more genes, twelve or more genes, thirteen or more genes, fourteen or more genes, fifteen or more genes, sixteen or more genes, seventeen or more genes, eighteen or more genes, nineteen or more genes, twenty or more genes, twenty-one or 82 314164997v1Attorney Docket No: 243735.000437 more genes, twenty-two or more genes, twenty-three or more genes, twenty-four or more genes, twenty-five or more genes, twenty-six or more genes, twenty-seven or more genes, twenty-eight or more genes, twenty-nine or more genes, thirty or more genes, thirty-one or more genes, thirty- two or more genes, thirty-three or more genes, thirty-four or more genes, thirty-five or more genes, thirty-six or more genes, thirty-seven or more genes, thirty-eight or more genes, thirty- nine or more genes, forty or more genes, forty-one or more genes, forty-two or more genes, forty-three or more genes, forty-four or more genes, forty-five or more genes, forty-six or more genes, forty-seven or more genes, forty-eight or more genes, forty-nine or more genes, fifty or more genes, fifty-one or more genes, fifty-two or more genes, fifty-three or more genes, fifty- four or more genes, fifty-five or more genes, fifty-six or more genes, fifty-seven or more genes, fifty-eight or more genes, fifty-nine or more genes, sixty or more genes, sixty-one or more genes, sixty-two or more genes, sixty-three or more genes, sixty-four or more genes, sixty-five or more genes, sixty-six or more genes, sixty-seven or more genes, sixty-eight or more genes, sixty-nine or more genes, seventy or more genes, seventy-one or more genes, seventy-two or more genes, seventy-three or more genes, seventy-four or more genes, seventy-five or more genes, seventy- six or more genes, seventy-seven or more genes, seventy-eight or more genes, seventy-nine or more genes, eighty or more genes, eighty-one or more genes, eighty-two or more genes, eighty- three or more genes, eighty-four or more genes, eighty-five or more genes, eighty-six or more genes, eighty-seven or more genes, eighty-eight or more genes, eighty-nine or more genes, ninety or more genes, ninety-one or more genes, ninety-two or more genes, ninety-three or more genes, ninety-four or more genes, ninety-five or more genes, ninety-six or more genes, ninety- seven or more genes, ninety-eight or more genes, ninety-nine or more genes, one hundred or more genes, one hundred and one or more genes, one hundred and two or more genes, one hundred and three or more genes, one hundred and four or more genes, one hundred and five or more genes, one hundred and six or more genes, one hundred and seven or more genes, one hundred and eight or more genes, one hundred and nine or more genes, one hundred and ten or more genes, one hundred and eleven or more genes, one hundred and twelve or more genes, one hundred and thirteen or more genes, one hundred and fourteen or more genes, one hundred and fifteen or more genes, one hundred and sixteen or more genes, one hundred and seventeen or more genes, one hundred and eighteen or more genes, one hundred and nineteen or more genes, one hundred and twenty or more genes, one hundred and twenty-one or more genes, one hundred 83 314164997v1Attorney Docket No: 243735.000437 and twenty-two or more genes, one hundred and twenty-three or more genes, one hundred and twenty-four or more genes, one hundred and twenty-five or more genes, one hundred and twenty-six or more genes, one twenty-seven or more genes, one hundred and twenty-eight or more genes, one hundred and twenty-nine or more genes, one hundred and thirty or more genes, one hundred and thirty-one or more genes, one hundred and thirty-two or more genes, one hundred and thirty-three or more genes, one hundred and thirty-four or more genes, one hundred and thirty-five or more genes, one hundred and thirty-six or more genes, one hundred and thirty- seven or more genes, one hundred and thirty-eight or more genes, one hundred and thirty-nine or more genes, one hundred and forty or more genes, one hundred and forty-one or more genes, one hundred and forty-two or more genes, one hundred and forty-three or more genes, one hundred and forty-four or more genes, one hundred and forty-five or more genes, one hundred and forty- six or more genes, one hundred and forty-seven or more genes, one hundred and forty-eight or more genes, one hundred and forty-nine or more genes, one hundred and fifty or more genes, one hundred and fifty-one or more genes, one hundred and fifty-two or more genes, one hundred and fifty-three or more genes, one hundred and fifty-four or more genes, one hundred and fifty-five or more genes, one hundred and fifty-six or more genes, one hundred and fifty-seven or more genes, one hundred and fifty-eight or more genes, one hundred and fifty-nine or more genes, one hundred and sixty or more genes, one hundred and sixty-one or more genes, one hundred and sixty-two or more genes, one hundred and sixty-three or more genes, one hundred and sixty-four or more genes, one hundred and sixty-five or more genes, one hundred and sixty-six or more genes, one hundred and sixty-seven or more genes, one hundred and sixty-eight or more genes, one hundred and sixty-nine or more genes, one hundred and seventy or more genes, one hundred and seventy-one or more genes, one hundred and seventy-two or more genes, one hundred and seventy-three or more genes, one hundred and seventy-four or more genes, one hundred and seventy-five or more genes, one hundred and seventy-six or more genes, one hundred and seventy-seven or more genes, one hundred and seventy-eight or more genes, one hundred and seventy-nine or more genes, one hundred and eighty or more genes, one hundred and eighty-one or more genes, one hundred and eighty-two or more genes, one hundred and eighty-three or more genes, one hundred and eighty-four or more genes, one hundred and eighty-five or more genes, one hundred and eighty-six or more genes, one hundred and eighty-seven or more genes, one hundred and eighty-eight or more genes, one hundred and eighty-nine or more genes, one 84 314164997v1Attorney Docket No: 243735.000437 hundred and ninety or more genes, one hundred and ninety-one or more genes, one hundred and ninety-two or more genes, one hundred and ninety-three or more genes, one hundred and ninety- four or more genes, one hundred and ninety-five or more genes, one hundred and ninety-six or more genes, one hundred and ninety-seven or more genes, one hundred and ninety-eight or more genes, or one hundred and ninety-nine genes are compared to a corresponding control. In another embodiment, the expression levels are determined for two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen, twenty, twenty-one, twenty-two, twenty-three, twenty-four, twenty-five, twenty-six, twenty- seven, twenty-eight, twenty-nine, thirty, thirty-one, thirty-two, thirty-three, thirty-four, thirty- five, thirty-six, thirty-seven, thirty-eight, thirty-nine, forty, forty-one, forty-two, forty-three, forty-four, forty-five, forty-six, forty-seven, forty-eight, forty-nine, fifty, fifty-one, fifty-two, fifty-three, fifty-four, fifty-five, fifty-six, fifty-seven, fifty-eight, fifty-nine, sixty, sixty-one, sixty-two, sixty-three, sixty-four, sixty-five, sixty-six, sixty-seven, sixty-eight, sixty-nine, seventy, seventy-one, seventy-two, seventy-three, seventy-four, seventy-five, seventy-six, seventy-seven, seventy-eight, seventy-nine, eighty, eighty-one, eighty-two, eighty-three, eighty- four, eighty-five, eighty-six, eighty-seven, eighty-eight, eighty-nine, ninety, ninety-one, ninety- two, ninety-three, ninety-four, ninety-five, ninety-six, ninety-seven, ninety-eight, ninety-nine, one hundred, one hundred one, one hundred two, one hundred three, one hundred four, one hundred five, one hundred six, one hundred seven, one hundred eight, one hundred nine, one hundred ten, one hundred eleven, one hundred twelve, one hundred thirteen, one hundred fourteen, one hundred fifteen, one hundred sixteen, one hundred seventeen, one hundred eighteen, one hundred nineteen, one hundred twenty, one hundred twenty-one, one hundred twenty-two, one hundred twenty-three, one hundred twenty-four, one hundred twenty-five, one hundred twenty-six, one hundred twenty-seven, one hundred twenty-eight, one hundred twenty- nine, one hundred thirty, one hundred thirty-one, one hundred thirty-two, one hundred thirty- three, one hundred thirty-four, one hundred thirty-five, one hundred thirty-six, one hundred thirty-seven, one hundred thirty-eight, one hundred thirty-nine, one hundred forty, one hundred forty-one, one hundred forty-two, one hundred forty-three, one hundred forty-four, one hundred forty-five, one hundred forty-six, one hundred forty-seven, one hundred forty-eight, one hundred forty-nine, one hundred fifty, one hundred fifty-one, one hundred fifty-two, one hundred fifty- three, one hundred fifty-four, one hundred fifty-five, one hundred fifty-six, one hundred fifty- 85 314164997v1Attorney Docket No: 243735.000437 seven, one hundred fifty-eight, one hundred fifty-nine, one hundred sixty, one hundred sixty-one, one hundred sixty-two, one hundred sixty-three, one hundred sixty-four, one hundred sixty-five, one hundred sixty-six, one hundred sixty-seven, one hundred sixty-eight, one hundred sixty-nine, one hundred seventy, one hundred seventy-one, one hundred seventy-two, one hundred seventy- three, one hundred seventy-four, one hundred seventy-five, one hundred seventy-six, one hundred seventy-seven, one hundred seventy-eight, one hundred seventy-nine, one hundred eighty, one hundred eighty-one, one hundred eighty-two, one hundred eighty-three, one hundred eighty-four, one hundred eighty-five, one hundred eighty-six, one hundred eighty-seven, one hundred eighty-eight, one hundred eighty-nine, one hundred ninety, one hundred ninety-one, one hundred ninety-two, one hundred ninety-three, one hundred ninety-four, one hundred ninety-five, one hundred ninety-six, one hundred ninety-seven, one hundred ninety-eight, or one hundred ninety-nine genes selected from 1) human genes MS4A1, CD19, AIM2, BANK1, CD79A, TNFRSF13C, BLK, IGHM, IGHD, XBP1, MZB1, TNFRSF17, CD27, TENT5C, POU2AF1, PRDM1, NUGGC, SDC1, KLRC1, GZMB, TRDC, KLRF1, GNLY, LYZ, MRC1, STAB1, SLCO2B1, F13A1, CD163, MSR1, SLC40A1, CD14, IRF7, TLR7, TLR9, MYD88, STAT1, PLD4, CLEC4C, LILRA4, TPM2, MZB1, SCT, IRF4, SMPD3, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, CD3G, THEMIS, CD5, CD6, CD8B, CD8A, KLRG1, GZMK, CST7, GZMH, LEF1, TCF7, SELL, CD27, CD55, CCR7, CD4, CD40LG, CCR2, CCR6, DPP4, CTLA4, FOXP3, IKZF2, RTKN2, IRF4, IL21, IL2RA, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, MKI67, GBP1, IRF1, TAP1, WARS1, IDO1, CLEC10A, CD1C, FCER1A, CD1E, CD1D, CCR2, CSF3R, FCGR3B, FPR1, ALPL, MGAM, CXCR1, MXD1, and CXCR2, and 2) porcine genes SPP1, COLEC11, S100A6, NFKBIZ, CLDN1, THBS1, HIF1A, STMN1, ICAM1, TNFRSF1B, CXCL14, IL1RL1, NREP, C3, CXCL2, C4A, LYZ, S100A6, S100A11, MX1, MX2, IL33, HIF1A, PDGFRB, PECAM1, STAT3, IL33, RGS5, CD163, C3, VCAM1, TNC, CD74, SERPINE1, CCR5, TEK, RUNX1, MX2, IFIT1, COL1A1, CXCL14, MRC1, CD68, CD14, MX1, LYVE1, HIF1A, LMNA, EMP1, EIF4A1, DHX9, LYVE1, YWHAQ, CD163, VCAM1, MKI67, IFIT1, ICAM1, STAT1, STAT3, TOP2A, S100A6, WARS1, S100A1, SERPINH1, TOP2A, MX1, MX2, CD14, HSPA9, and HSPD1. In some embodiments, the expression levels of the two, three, four, five, six, seven, eight, nine, ten, 86 314164997v1Attorney Docket No: 243735.000437 eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen, twenty, twenty- one, twenty-two, twenty-three, twenty-four, twenty-five, twenty-six, twenty-seven, twenty-eight, twenty-nine, thirty, thirty-one, thirty-two, thirty-three, thirty-four, thirty-five, thirty-six, thirty- seven, thirty-eight, thirty-nine, forty, forty-one, forty-two, forty-three, forty-four, forty-five, forty-six, forty-seven, forty-eight, forty-nine, fifty, fifty-one, fifty-two, fifty-three, fifty-four, fifty-five, fifty-six, fifty-seven, fifty-eight, fifty-nine, sixty, sixty-one, sixty-two, sixty-three, sixty-four, sixty-five, sixty-six, sixty-seven, sixty-eight, sixty-nine, seventy, seventy-one, seventy-two, seventy-three, seventy-four, seventy-five, seventy-six, seventy-seven, seventy- eight, seventy-nine, eighty, eighty-one, eighty-two, eighty-three, eighty-four, eighty-five, eighty- six, eighty-seven, eighty-eight, eighty-nine, ninety, ninety-one, ninety-two, ninety-three, ninety- four, ninety-five, ninety-six, ninety-seven, ninety-eight, ninety-nine, one hundred, one hundred one, one hundred two, one hundred three, one hundred four, one hundred five, one hundred six, one hundred seven, one hundred eight, one hundred nine, one hundred ten, one hundred eleven, one hundred twelve, one hundred thirteen, one hundred fourteen, one hundred fifteen, one hundred sixteen, one hundred seventeen, one hundred eighteen, one hundred nineteen, one hundred twenty, one hundred twenty-one, one hundred twenty-two, one hundred twenty-three, one hundred twenty-four, one hundred twenty-five, one hundred twenty-six, one hundred twenty- seven, one hundred twenty-eight, one hundred twenty-nine, one hundred thirty, one hundred thirty-one, one hundred thirty-two, one hundred thirty-three, one hundred thirty-four, one hundred thirty-five, one hundred thirty-six, one hundred thirty-seven, one hundred thirty-eight, one hundred thirty-nine, one hundred forty, one hundred forty-one, one hundred forty-two, one hundred forty-three, one hundred forty-four, one hundred forty-five, one hundred forty-six, one hundred forty-seven, one hundred forty-eight, one hundred forty-nine, one hundred fifty, one hundred fifty-one, one hundred fifty-two, one hundred fifty-three, one hundred fifty-four, one hundred fifty-five, one hundred fifty-six, one hundred fifty-seven, one hundred fifty-eight, one hundred fifty-nine, one hundred sixty, one hundred sixty-one, one hundred sixty-two, one hundred sixty-three, one hundred sixty-four, one hundred sixty-five, one hundred sixty-six, one hundred sixty-seven, one hundred sixty-eight, one hundred sixty-nine, one hundred seventy, one hundred seventy-one, one hundred seventy-two, one hundred seventy-three, one hundred seventy-four, one hundred seventy-five, one hundred seventy-six, one hundred seventy-seven, one hundred seventy-eight, one hundred seventy-nine, one hundred eighty, one hundred eighty- 87 314164997v1Attorney Docket No: 243735.000437 one, one hundred eighty-two, one hundred eighty-three, one hundred eighty-four, one hundred eighty-five, one hundred eighty-six, one hundred eighty-seven, one hundred eighty-eight, one hundred eighty-nine, one hundred ninety, one hundred ninety-one, one hundred ninety-two, one hundred ninety-three, one hundred ninety-four, one hundred ninety-five, one hundred ninety-six, one hundred ninety-seven, one hundred ninety-eight, or one hundred ninety-nine genes are compared to a corresponding control.

[0208] In another aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from 1) human genes XBP1, MZB1, TNFRSF17, CD27, TENT5C, POU2AF1, PRDM1, NUGGC, SDC1, KLRC1, GZMB, TRDC, KLRF1, GNLY, LYZ, MRC1, STAB1, SLCO2B1, F13A1, CD163, MSR1, SLC40A1, CD14, IRF7, TLR7, TLR9, MYD88, STAT1, PLD4, CLEC4C, LILRA4, TPM2, MZB1, SCT, IRF4, SMPD3, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, MKI67, GBP1, IRF1, TAP1, WARS1, IDO1, CLEC10A, CD1C, FCER1A, CD1E, CD1D, CCR2, CSF3R, FCGR3B, FPR1, ALPL, MGAM, CXCR1, MXD1, and CXCR2, and 2) porcine genes SPP1, COLEC11, S100A6, NFKBIZ, CLDN1, THBS1, HIF1A, STMN1, ICAM1, TNFRSF1B, CXCL14, IL1RL1, NREP, C3, CXCL2, C4A, LYZ, S100A6, S100A11, MX1, MX2, IL33, HIF1A, PDGFRB, PECAM1, STAT3, IL33, RGS5, CD163, C3, VCAM1, TNC, CD74, SERPINE1, CCR5, TEK, RUNX1, MX2, IFIT1, COL1A1, CXCL14, MRC1, CD68, CD14, MX1, LYVE1, HIF1A, LMNA, EMP1, EIF4A1, DHX9, LYVE1, YWHAQ, CD163, VCAM1, MKI67, IFIT1, ICAM1, STAT1, STAT3, TOP2A, S100A6, WARS1, S100A1, SERPINH1, TOP2A, MX1, MX2, CD14, HSPA9, and HSPD1, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control. 88 314164997v1Attorney Docket No: 243735.000437

[0209] In some embodiments, the expression levels are determined for three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, eight or more genes, nine or more genes, ten or more genes, eleven or more genes, twelve or more genes, thirteen or more genes, fourteen or more genes, fifteen or more genes, sixteen or more genes, seventeen or more genes, eighteen or more genes, nineteen or more genes, twenty or more genes, twenty-one or more genes, twenty-two or more genes, twenty-three or more genes, twenty-four or more genes, twenty-five or more genes, twenty-six or more genes, twenty-seven or more genes, twenty-eight or more genes, twenty-nine or more genes, thirty or more genes, thirty-one or more genes, thirty-two or more genes, thirty-three or more genes, thirty-four or more genes, thirty-five or more genes, thirty-six or more genes, thirty-seven or more genes, thirty-eight or more genes, thirty-nine or more genes, forty or more genes, forty-one or more genes, forty-two or more genes, forty-three or more genes, forty-four or more genes, forty-five or more genes, forty-six or more genes, forty-seven or more genes, forty-eight or more genes, forty-nine or more genes, fifty or more genes, fifty-one or more genes, fifty-two or more genes, fifty-three or more genes, fifty-four or more genes, fifty-five or more genes, fifty-six or more genes, fifty-seven or more genes, fifty-eight or more genes, fifty-nine or more genes, sixty or more genes, sixty-one or more genes, sixty-two or more genes, sixty-three or more genes, sixty-four or more genes, sixty- five or more genes, sixty-six or more genes, sixty-seven or more genes, sixty-eight or more genes, sixty-nine or more genes, seventy or more genes, seventy-one or more genes, seventy-two or more genes, seventy-three or more genes, seventy-four or more genes, seventy-five or more genes, seventy-six or more genes, seventy-seven or more genes, seventy-eight or more genes, seventy-nine or more genes, eighty or more genes, eighty-one or more genes, eighty-two or more genes, eighty-three or more genes, eighty-four or more genes, eighty-five or more genes, eighty- six or more genes, eighty-seven or more genes, eighty-eight or more genes, eighty-nine or more genes, ninety or more genes, ninety-one or more genes, ninety-two or more genes, ninety-three or more genes, ninety-four or more genes, ninety-five or more genes, ninety-six or more genes, ninety-seven or more genes, ninety-eight or more genes, ninety-nine or more genes, one hundred or more genes, one hundred and one or more genes, one hundred and two or more genes, one hundred and three or more genes, one hundred and four or more genes, one hundred and five or more genes, one hundred and six or more genes, one hundred and seven or more genes, one hundred and eight or more genes, one hundred and nine or more genes, one hundred and ten or 89 314164997v1Attorney Docket No: 243735.000437 more genes, one hundred and eleven or more genes, one hundred and twelve or more genes, one hundred and thirteen or more genes, one hundred and fourteen or more genes, one hundred and fifteen or more genes, one hundred and sixteen or more genes, one hundred and seventeen or more genes, one hundred and eighteen or more genes, one hundred and nineteen or more genes, one hundred and twenty or more genes, one hundred and twenty-one or more genes, one hundred and twenty-two or more genes, one hundred and twenty-three or more genes, one hundred and twenty-four or more genes, one hundred and twenty-five or more genes, one hundred and twenty-six or more genes, one twenty-seven or more genes, one hundred and twenty-eight or more genes, one hundred and twenty-nine or more genes, one hundred and thirty or more genes, one hundred and thirty-one or more genes, one hundred and thirty-two or more genes, one hundred and thirty-three or more genes, one hundred and thirty-four or more genes, one hundred and thirty-five or more genes, one hundred and thirty-six or more genes, one hundred and thirty- seven or more genes, one hundred and thirty-eight or more genes, one hundred and thirty-nine or more genes, one hundred and forty or more genes, one hundred and forty-one or more genes, one hundred and forty-two or more genes, one hundred and forty-three or more genes, one hundred and forty-four or more genes, one hundred and forty-five or more genes, one hundred and forty- six or more genes, one hundred and forty-seven or more genes, one hundred and forty-eight or more genes, one hundred and forty-nine or more genes, one hundred and fifty or more genes, one hundred and fifty-one or more genes, one hundred and fifty-two or more genes, one hundred and fifty-three or more genes, one hundred and fifty-four or more genes, one hundred and fifty-five or more genes, one hundred and fifty-six or more genes, one hundred and fifty-seven or more genes, one hundred and fifty-eight or more genes, one hundred and fifty-nine or more genes, one hundred and sixty or more genes, one hundred and sixty-one or more genes, or one hundred and sixty-two genes selected from 1) human genes XBP1, MZB1, TNFRSF17, CD27, TENT5C, POU2AF1, PRDM1, NUGGC, SDC1, KLRC1, GZMB, TRDC, KLRF1, GNLY, LYZ, MRC1, STAB1, SLCO2B1, F13A1, CD163, MSR1, SLC40A1, CD14, IRF7, TLR7, TLR9, MYD88, STAT1, PLD4, CLEC4C, LILRA4, TPM2, MZB1, SCT, IRF4, SMPD3, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, MKI67, GBP1, IRF1, TAP1, WARS1, IDO1, CLEC10A, CD1C, FCER1A, CD1E, CD1D, CCR2, 90 314164997v1Attorney Docket No: 243735.000437 CSF3R, FCGR3B, FPR1, ALPL, MGAM, CXCR1, MXD1, and CXCR2, and 2) porcine genes SPP1, COLEC11, S100A6, NFKBIZ, CLDN1, THBS1, HIF1A, STMN1, ICAM1, TNFRSF1B, CXCL14, IL1RL1, NREP, C3, CXCL2, C4A, LYZ, S100A6, S100A11, MX1, MX2, IL33, HIF1A, PDGFRB, PECAM1, STAT3, IL33, RGS5, CD163, C3, VCAM1, TNC, CD74, SERPINE1, CCR5, TEK, RUNX1, MX2, IFIT1, COL1A1, CXCL14, MRC1, CD68, CD14, MX1, LYVE1, HIF1A, LMNA, EMP1, EIF4A1, DHX9, LYVE1, YWHAQ, CD163, VCAM1, MKI67, IFIT1, ICAM1, STAT1, STAT3, TOP2A, S100A6, WARS1, S100A1, SERPINH1, TOP2A, MX1, MX2, CD14, HSPA9, and HSPD1. In some embodiments, the expression levels of the three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, eight or more genes, nine or more genes, ten or more genes, eleven or more genes, twelve or more genes, thirteen or more genes, fourteen or more genes, fifteen or more genes, sixteen or more genes, seventeen or more genes, eighteen or more genes, nineteen or more genes, twenty or more genes, twenty-one or more genes, twenty-two or more genes, twenty-three or more genes, twenty-four or more genes, twenty-five or more genes, twenty-six or more genes, twenty-seven or more genes, twenty-eight or more genes, twenty-nine or more genes, thirty or more genes, thirty-one or more genes, thirty-two or more genes, thirty-three or more genes, thirty-four or more genes, thirty-five or more genes, thirty-six or more genes, thirty-seven or more genes, thirty-eight or more genes, thirty-nine or more genes, forty or more genes, forty-one or more genes, forty-two or more genes, forty-three or more genes, forty-four or more genes, forty-five or more genes, forty-six or more genes, forty-seven or more genes, forty-eight or more genes, forty-nine or more genes, fifty or more genes, fifty-one or more genes, fifty-two or more genes, fifty-three or more genes, fifty-four or more genes, fifty-five or more genes, fifty-six or more genes, fifty-seven or more genes, fifty-eight or more genes, fifty-nine or more genes, sixty or more genes, sixty-one or more genes, sixty-two or more genes, sixty-three or more genes, sixty-four or more genes, sixty-five or more genes, sixty-six or more genes, sixty-seven or more genes, sixty-eight or more genes, sixty-nine or more genes, seventy or more genes, seventy-one or more genes, seventy-two or more genes, seventy-three or more genes, seventy-four or more genes, seventy-five or more genes, seventy-six or more genes, seventy-seven or more genes, seventy-eight or more genes, seventy-nine or more genes, eighty or more genes, eighty-one or more genes, eighty-two or more genes, eighty-three or more genes, eighty-four or more genes, eighty-five or more genes, eighty-six or more genes, eighty-seven or more genes, eighty-eight or 91 314164997v1Attorney Docket No: 243735.000437 more genes, eighty-nine or more genes, ninety or more genes, ninety-one or more genes, ninety- two or more genes, ninety-three or more genes, ninety-four or more genes, ninety-five or more genes, ninety-six or more genes, ninety-seven or more genes, ninety-eight or more genes, ninety- nine or more genes, one hundred or more genes, one hundred and one or more genes, one hundred and two or more genes, one hundred and three or more genes, one hundred and four or more genes, one hundred and five or more genes, one hundred and six or more genes, one hundred and seven or more genes, one hundred and eight or more genes, one hundred and nine or more genes, one hundred and ten or more genes, one hundred and eleven or more genes, one hundred and twelve or more genes, one hundred and thirteen or more genes, one hundred and fourteen or more genes, one hundred and fifteen or more genes, one hundred and sixteen or more genes, one hundred and seventeen or more genes, one hundred and eighteen or more genes, one hundred and nineteen or more genes, one hundred and twenty or more genes, one hundred and twenty-one or more genes, one hundred and twenty-two or more genes, one hundred and twenty- three or more genes, one hundred and twenty-four or more genes, one hundred and twenty-five or more genes, one hundred and twenty-six or more genes, one twenty-seven or more genes, one hundred and twenty-eight or more genes, one hundred and twenty-nine or more genes, one hundred and thirty or more genes, one hundred and thirty-one or more genes, one hundred and thirty-two or more genes, one hundred and thirty-three or more genes, one hundred and thirty- four or more genes, one hundred and thirty-five or more genes, one hundred and thirty-six or more genes, one hundred and thirty-seven or more genes, one hundred and thirty-eight or more genes, one hundred and thirty-nine or more genes, one hundred and forty or more genes, one hundred and forty-one or more genes, one hundred and forty-two or more genes, one hundred and forty-three or more genes, one hundred and forty-four or more genes, one hundred and forty- five or more genes, one hundred and forty-six or more genes, one hundred and forty-seven or more genes, one hundred and forty-eight or more genes, one hundred and forty-nine or more genes, one hundred and fifty or more genes, one hundred and fifty-one or more genes, one hundred and fifty-two or more genes, one hundred and fifty-three or more genes, one hundred and fifty-four or more genes, one hundred and fifty-five or more genes, one hundred and fifty-six or more genes, one hundred and fifty-seven or more genes, one hundred and fifty-eight or more genes, one hundred and fifty-nine or more genes, one hundred and sixty or more genes, one hundred and sixty-one or more genes, or one hundred and sixty-two genes are compared to a 92 314164997v1Attorney Docket No: 243735.000437 corresponding control. In another embodiment, the expression levels are determined for two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen, twenty, twenty-one, twenty-two, twenty-three, twenty-four, twenty-five, twenty-six, twenty-seven, twenty-eight, twenty-nine, thirty, thirty-one, thirty-two, thirty-three, thirty-four, thirty-five, thirty-six, thirty-seven, thirty-eight, thirty-nine, forty, forty- one, forty-two, forty-three, forty-four, forty-five, forty-six, forty-seven, forty-eight, forty-nine, fifty, fifty-one, fifty-two, fifty-three, fifty-four, fifty-five, fifty-six, fifty-seven, fifty-eight, fifty- nine, sixty, sixty-one, sixty-two, sixty-three, sixty-four, sixty-five, sixty-six, sixty-seven, sixty- eight, sixty-nine, seventy, seventy-one, seventy-two, seventy-three, seventy-four, seventy-five, seventy-six, seventy-seven, seventy-eight, seventy-nine, eighty, eighty-one, eighty-two, eighty- three, eighty-four, eighty-five, eighty-six, eighty-seven, eighty-eight, eighty-nine, ninety, ninety- one, ninety-two, ninety-three, ninety-four, ninety-five, ninety-six, ninety-seven, ninety-eight, ninety-nine, one hundred, one hundred one, one hundred two, one hundred three, one hundred four, one hundred five, one hundred six, one hundred seven, one hundred eight, one hundred nine, one hundred ten, one hundred eleven, one hundred twelve, one hundred thirteen, one hundred fourteen, one hundred fifteen, one hundred sixteen, one hundred seventeen, one hundred eighteen, one hundred nineteen, one hundred twenty, one hundred twenty-one, one hundred twenty-two, one hundred twenty-three, one hundred twenty-four, one hundred twenty-five, one hundred twenty-six, one hundred twenty-seven, one hundred twenty-eight, one hundred twenty- nine, one hundred thirty, one hundred thirty-one, one hundred thirty-two, one hundred thirty- three, one hundred thirty-four, one hundred thirty-five, one hundred thirty-six, one hundred thirty-seven, one hundred thirty-eight, one hundred thirty-nine, one hundred forty, one hundred forty-one, one hundred forty-two, one hundred forty-three, one hundred forty-four, one hundred forty-five, one hundred forty-six, one hundred forty-seven, one hundred forty-eight, one hundred forty-nine, one hundred fifty, one hundred fifty-one, one hundred fifty-two, one hundred fifty- three, one hundred fifty-four, one hundred fifty-five, one hundred fifty-six, one hundred fifty- seven, one hundred fifty-eight, one hundred fifty-nine, one hundred sixty, one hundred sixty-one, or one hundred sixty-two genes selected from 1) human genes XBP1, MZB1, TNFRSF17, CD27, TENT5C, POU2AF1, PRDM1, NUGGC, SDC1, KLRC1, GZMB, TRDC, KLRF1, GNLY, LYZ, MRC1, STAB1, SLCO2B1, F13A1, CD163, MSR1, SLC40A1, CD14, IRF7, TLR7, TLR9, MYD88, STAT1, PLD4, CLEC4C, LILRA4, TPM2, MZB1, SCT, IRF4, SMPD3, 93 314164997v1Attorney Docket No: 243735.000437 STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, MKI67, GBP1, IRF1, TAP1, WARS1, IDO1, CLEC10A, CD1C, FCER1A, CD1E, CD1D, CCR2, CSF3R, FCGR3B, FPR1, ALPL, MGAM, CXCR1, MXD1, and CXCR2, and 2) porcine genes SPP1, COLEC11, S100A6, NFKBIZ, CLDN1, THBS1, HIF1A, STMN1, ICAM1, TNFRSF1B, CXCL14, IL1RL1, NREP, C3, CXCL2, C4A, LYZ, S100A6, S100A11, MX1, MX2, IL33, HIF1A, PDGFRB, PECAM1, STAT3, IL33, RGS5, CD163, C3, VCAM1, TNC, CD74, SERPINE1, CCR5, TEK, RUNX1, MX2, IFIT1, COL1A1, CXCL14, MRC1, CD68, CD14, MX1, LYVE1, HIF1A, LMNA, EMP1, EIF4A1, DHX9, LYVE1, YWHAQ, CD163, VCAM1, MKI67, IFIT1, ICAM1, STAT1, STAT3, TOP2A, S100A6, WARS1, S100A1, SERPINH1, TOP2A, MX1, MX2, CD14, HSPA9, and HSPD1. In some embodiments, the expression levels of the two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen, twenty, twenty-one, twenty- two, twenty-three, twenty-four, twenty-five, twenty-six, twenty-seven, twenty-eight, twenty- nine, thirty, thirty-one, thirty-two, thirty-three, thirty-four, thirty-five, thirty-six, thirty-seven, thirty-eight, thirty-nine, forty, forty-one, forty-two, forty-three, forty-four, forty-five, forty-six, forty-seven, forty-eight, forty-nine, fifty, fifty-one, fifty-two, fifty-three, fifty-four, fifty-five, fifty-six, fifty-seven, fifty-eight, fifty-nine, sixty, sixty-one, sixty-two, sixty-three, sixty-four, sixty-five, sixty-six, sixty-seven, sixty-eight, sixty-nine, seventy, seventy-one, seventy-two, seventy-three, seventy-four, seventy-five, seventy-six, seventy-seven, seventy-eight, seventy- nine, eighty, eighty-one, eighty-two, eighty-three, eighty-four, eighty-five, eighty-six, eighty- seven, eighty-eight, eighty-nine, ninety, ninety-one, ninety-two, ninety-three, ninety-four, ninety- five, ninety-six, ninety-seven, ninety-eight, ninety-nine, one hundred, one hundred one, one hundred two, one hundred three, one hundred four, one hundred five, one hundred six, one hundred seven, one hundred eight, one hundred nine, one hundred ten, one hundred eleven, one hundred twelve, one hundred thirteen, one hundred fourteen, one hundred fifteen, one hundred sixteen, one hundred seventeen, one hundred eighteen, one hundred nineteen, one hundred twenty, one hundred twenty-one, one hundred twenty-two, one hundred twenty-three, one hundred twenty-four, one hundred twenty-five, one hundred twenty-six, one hundred twenty- seven, one hundred twenty-eight, one hundred twenty-nine, one hundred thirty, one hundred 94 314164997v1Attorney Docket No: 243735.000437 thirty-one, one hundred thirty-two, one hundred thirty-three, one hundred thirty-four, one hundred thirty-five, one hundred thirty-six, one hundred thirty-seven, one hundred thirty-eight, one hundred thirty-nine, one hundred forty, one hundred forty-one, one hundred forty-two, one hundred forty-three, one hundred forty-four, one hundred forty-five, one hundred forty-six, one hundred forty-seven, one hundred forty-eight, one hundred forty-nine, one hundred fifty, one hundred fifty-one, one hundred fifty-two, one hundred fifty-three, one hundred fifty-four, one hundred fifty-five, one hundred fifty-six, one hundred fifty-seven, one hundred fifty-eight, one hundred fifty-nine, one hundred sixty, one hundred sixty-one, or one hundred sixty-two genes are compared to a corresponding control.

[0210] In a further aspect, provided herein is a method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from 1) human genes MS4A1, CD19, AIM2, BANK1, CD79A, TNFRSF13C, BLK, IGHM, IGHD, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, CD3G, THEMIS, CD5, CD6, CD8B, CD8A, KLRG1, GZMK, CST7, GZMH, LEF1, TCF7, SELL, CD27, CD55, CCR7, CD4, CD40LG, CCR2, CCR6, DPP4, CTLA4, FOXP3, IKZF2, RTKN2, IRF4, IL21, IL2RA, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, and MKI67, and 2) porcine genes SPP1, COLEC11, S100A6, NFKBIZ, CLDN1, THBS1, HIF1A, STMN1, ICAM1, TNFRSF1B, CXCL14, IL1RL1, NREP, C3, CXCL2, C4A, LYZ, S100A6, S100A11, MX1, MX2, IL33, HIF1A, PDGFRB, PECAM1, STAT3, IL33, RGS5, CD163, C3, VCAM1, TNC, CD74, SERPINE1, CCR5, TEK, RUNX1, MX2, IFIT1, COL1A1, CXCL14, MRC1, CD68, CD14, MX1, LYVE1, HIF1A, LMNA, EMP1, EIF4A1, DHX9, LYVE1, YWHAQ, CD163, VCAM1, MKI67, IFIT1, ICAM1, STAT1, STAT3, TOP2A, S100A6, WARS1, S100A1, SERPINH1, TOP2A, MX1, MX2, CD14, HSPA9, and HSPD1, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control. 95 314164997v1Attorney Docket No: 243735.000437

[0211] In some embodiments, the expression levels are determined for three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, eight or more genes, nine or more genes, ten or more genes, eleven or more genes, twelve or more genes, thirteen or more genes, fourteen or more genes, fifteen or more genes, sixteen or more genes, seventeen or more genes, eighteen or more genes, nineteen or more genes, twenty or more genes, twenty-one or more genes, twenty-two or more genes, twenty-three or more genes, twenty-four or more genes, twenty-five or more genes, twenty-six or more genes, twenty-seven or more genes, twenty-eight or more genes, twenty-nine or more genes, thirty or more genes, thirty-one or more genes, thirty-two or more genes, thirty-three or more genes, thirty-four or more genes, thirty-five or more genes, thirty-six or more genes, thirty-seven or more genes, thirty-eight or more genes, thirty-nine or more genes, forty or more genes, forty-one or more genes, forty-two or more genes, forty-three or more genes, forty-four or more genes, forty-five or more genes, forty-six or more genes, forty-seven or more genes, forty-eight or more genes, forty-nine or more genes, fifty or more genes, fifty-one or more genes, fifty-two or more genes, fifty-three or more genes, fifty-four or more genes, fifty-five or more genes, fifty-six or more genes, fifty-seven or more genes, fifty-eight or more genes, fifty-nine or more genes, sixty or more genes, sixty-one or more genes, sixty-two or more genes, sixty-three or more genes, sixty-four or more genes, sixty- five or more genes, sixty-six or more genes, sixty-seven or more genes, sixty-eight or more genes, sixty-nine or more genes, seventy or more genes, seventy-one or more genes, seventy-two or more genes, seventy-three or more genes, seventy-four or more genes, seventy-five or more genes, seventy-six or more genes, seventy-seven or more genes, seventy-eight or more genes, seventy-nine or more genes, eighty or more genes, eighty-one or more genes, eighty-two or more genes, eighty-three or more genes, eighty-four or more genes, eighty-five or more genes, eighty- six or more genes, eighty-seven or more genes, eighty-eight or more genes, eighty-nine or more genes, ninety or more genes, ninety-one or more genes, ninety-two or more genes, ninety-three or more genes, ninety-four or more genes, ninety-five or more genes, ninety-six or more genes, ninety-seven or more genes, ninety-eight or more genes, ninety-nine or more genes, one hundred or more genes, one hundred and one or more genes, one hundred and two or more genes, one hundred and three or more genes, one hundred and four or more genes, one hundred and five or more genes, one hundred and six or more genes, one hundred and seven or more genes, one hundred and eight or more genes, one hundred and nine or more genes, one hundred and ten or 96 314164997v1Attorney Docket No: 243735.000437 more genes, one hundred and eleven or more genes, one hundred and twelve or more genes, one hundred and thirteen or more genes, one hundred and fourteen or more genes, one hundred and fifteen or more genes, one hundred and sixteen or more genes, one hundred and seventeen or more genes, one hundred and eighteen or more genes, one hundred and nineteen or more genes, one hundred and twenty or more genes, one hundred and twenty-one or more genes, one hundred and twenty-two or more genes, one hundred and twenty-three or more genes, one hundred and twenty-four or more genes, one hundred and twenty-five or more genes, one hundred and twenty-six or more genes, one twenty-seven or more genes, one hundred and twenty-eight or more genes, one hundred and twenty-nine or more genes, one hundred and thirty or more genes, one hundred and thirty-one or more genes, one hundred and thirty-two or more genes, one hundred and thirty-three or more genes, one hundred and thirty-four or more genes, one hundred and thirty-five or more genes, one hundred and thirty-six or more genes, one hundred and thirty- seven or more genes, one hundred and thirty-eight or more genes, one hundred and thirty-nine or more genes, one hundred and forty or more genes, one hundred and forty-one or more genes, one hundred and forty-two or more genes, one hundred and forty-three or more genes, or one hundred and forty-four genes selected from 1) human genes MS4A1, CD19, AIM2, BANK1, CD79A, TNFRSF13C, BLK, IGHM, IGHD, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, CD3G, THEMIS, CD5, CD6, CD8B, CD8A, KLRG1, GZMK, CST7, GZMH, LEF1, TCF7, SELL, CD27, CD55, CCR7, CD4, CD40LG, CCR2, CCR6, DPP4, CTLA4, FOXP3, IKZF2, RTKN2, IRF4, IL21, IL2RA, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, and MKI67, and 2) porcine genes SPP1, COLEC11, S100A6, NFKBIZ, CLDN1, THBS1, HIF1A, STMN1, ICAM1, TNFRSF1B, CXCL14, IL1RL1, NREP, C3, CXCL2, C4A, LYZ, S100A6, S100A11, MX1, MX2, IL33, HIF1A, PDGFRB, PECAM1, STAT3, IL33, RGS5, CD163, C3, VCAM1, TNC, CD74, SERPINE1, CCR5, TEK, RUNX1, MX2, IFIT1, COL1A1, CXCL14, MRC1, CD68, CD14, MX1, LYVE1, HIF1A, LMNA, EMP1, EIF4A1, DHX9, LYVE1, YWHAQ, CD163, VCAM1, MKI67, IFIT1, ICAM1, STAT1, STAT3, TOP2A, S100A6, WARS1, S100A1, SERPINH1, TOP2A, MX1, MX2, CD14, HSPA9, and HSPD1. In some embodiments, the expression levels of the three or more genes, four or more genes, five or more genes, six or more genes, seven or more genes, eight or more genes, nine or more genes, ten or 97 314164997v1Attorney Docket No: 243735.000437 more genes, eleven or more genes, twelve or more genes, thirteen or more genes, fourteen or more genes, fifteen or more genes, sixteen or more genes, seventeen or more genes, eighteen or more genes, nineteen or more genes, twenty or more genes, twenty-one or more genes, twenty- two or more genes, twenty-three or more genes, twenty-four or more genes, twenty-five or more genes, twenty-six or more genes, twenty-seven or more genes, twenty-eight or more genes, twenty-nine or more genes, thirty or more genes, thirty-one or more genes, thirty-two or more genes, thirty-three or more genes, thirty-four or more genes, thirty-five or more genes, thirty-six or more genes, thirty-seven or more genes, thirty-eight or more genes, thirty-nine or more genes, forty or more genes, forty-one or more genes, forty-two or more genes, forty-three or more genes, forty-four or more genes, forty-five or more genes, forty-six or more genes, forty-seven or more genes, forty-eight or more genes, forty-nine or more genes, fifty or more genes, fifty-one or more genes, fifty-two or more genes, fifty-three or more genes, fifty-four or more genes, fifty- five or more genes, fifty-six or more genes, fifty-seven or more genes, fifty-eight or more genes, fifty-nine or more genes, sixty or more genes, sixty-one or more genes, sixty-two or more genes, sixty-three or more genes, sixty-four or more genes, sixty-five or more genes, sixty-six or more genes, sixty-seven or more genes, sixty-eight or more genes, sixty-nine or more genes, seventy or more genes, seventy-one or more genes, seventy-two or more genes, seventy-three or more genes, seventy-four or more genes, seventy-five or more genes, seventy-six or more genes, seventy-seven or more genes, seventy-eight or more genes, seventy-nine or more genes, eighty or more genes, eighty-one or more genes, eighty-two or more genes, eighty-three or more genes, eighty-four or more genes, eighty-five or more genes, eighty-six or more genes, eighty-seven or more genes, eighty-eight or more genes, eighty-nine or more genes, ninety or more genes, ninety-one or more genes, ninety-two or more genes, ninety-three or more genes, ninety-four or more genes, ninety-five or more genes, ninety-six or more genes, ninety-seven or more genes, ninety-eight or more genes, ninety-nine or more genes, one hundred or more genes, one hundred and one or more genes, one hundred and two or more genes, one hundred and three or more genes, one hundred and four or more genes, one hundred and five or more genes, one hundred and six or more genes, one hundred and seven or more genes, one hundred and eight or more genes, one hundred and nine or more genes, one hundred and ten or more genes, one hundred and eleven or more genes, one hundred and twelve or more genes, one hundred and thirteen or more genes, one hundred and fourteen or more genes, one hundred and fifteen or more genes, 98 314164997v1Attorney Docket No: 243735.000437 one hundred and sixteen or more genes, one hundred and seventeen or more genes, one hundred and eighteen or more genes, one hundred and nineteen or more genes, one hundred and twenty or more genes, one hundred and twenty-one or more genes, one hundred and twenty-two or more genes, one hundred and twenty-three or more genes, one hundred and twenty-four or more genes, one hundred and twenty-five or more genes, one hundred and twenty-six or more genes, one twenty-seven or more genes, one hundred and twenty-eight or more genes, one hundred and twenty-nine or more genes, one hundred and thirty or more genes, one hundred and thirty-one or more genes, one hundred and thirty-two or more genes, one hundred and thirty-three or more genes, one hundred and thirty-four or more genes, one hundred and thirty-five or more genes, one hundred and thirty-six or more genes, one hundred and thirty-seven or more genes, one hundred and thirty-eight or more genes, one hundred and thirty-nine or more genes, one hundred and forty or more genes, one hundred and forty-one or more genes, one hundred and forty-two or more genes, one hundred and forty-three or more genes, or one hundred and forty-four genes are compared to a corresponding control. In another embodiment, the expression levels are determined for two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen, twenty, twenty-one, twenty-two, twenty- three, twenty-four, twenty-five, twenty-six, twenty-seven, twenty-eight, twenty-nine, thirty, thirty-one, thirty-two, thirty-three, thirty-four, thirty-five, thirty-six, thirty-seven, thirty-eight, thirty-nine, forty, forty-one, forty-two, forty-three, forty-four, forty-five, forty-six, forty-seven, forty-eight, forty-nine, fifty, fifty-one, fifty-two, fifty-three, fifty-four, fifty-five, fifty-six, fifty- seven, fifty-eight, fifty-nine, sixty, sixty-one, sixty-two, sixty-three, sixty-four, sixty-five, sixty- six, sixty-seven, sixty-eight, sixty-nine, seventy, seventy-one, seventy-two, seventy-three, seventy-four, seventy-five, seventy-six, seventy-seven, seventy-eight, seventy-nine, eighty, eighty-one, eighty-two, eighty-three, eighty-four, eighty-five, eighty-six, eighty-seven, eighty- eight, eighty-nine, ninety, ninety-one, ninety-two, ninety-three, ninety-four, ninety-five, ninety- six, ninety-seven, ninety-eight, ninety-nine, one hundred, one hundred one, one hundred two, one hundred three, one hundred four, one hundred five, one hundred six, one hundred seven, one hundred eight, one hundred nine, one hundred ten, one hundred eleven, one hundred twelve, one hundred thirteen, one hundred fourteen, one hundred fifteen, one hundred sixteen, one hundred seventeen, one hundred eighteen, one hundred nineteen, one hundred twenty, one hundred twenty-one, one hundred twenty-two, one hundred twenty-three, one hundred twenty-four, one 99 314164997v1Attorney Docket No: 243735.000437 hundred twenty-five, one hundred twenty-six, one hundred twenty-seven, one hundred twenty- eight, one hundred twenty-nine, one hundred thirty, one hundred thirty-one, one hundred thirty- two, one hundred thirty-three, one hundred thirty-four, one hundred thirty-five, one hundred thirty-six, one hundred thirty-seven, one hundred thirty-eight, one hundred thirty-nine, one hundred forty, one hundred forty-one, one hundred forty-two, one hundred forty-three, or one hundred forty-four genes selected from 1) human genes MS4A1, CD19, AIM2, BANK1, CD79A, TNFRSF13C, BLK, IGHM, IGHD, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, CD3G, THEMIS, CD5, CD6, CD8B, CD8A, KLRG1, GZMK, CST7, GZMH, LEF1, TCF7, SELL, CD27, CD55, CCR7, CD4, CD40LG, CCR2, CCR6, DPP4, CTLA4, FOXP3, IKZF2, RTKN2, IRF4, IL21, IL2RA, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, and MKI67, and 2) porcine genes SPP1, COLEC11, S100A6, NFKBIZ, CLDN1, THBS1, HIF1A, STMN1, ICAM1, TNFRSF1B, CXCL14, IL1RL1, NREP, C3, CXCL2, C4A, LYZ, S100A6, S100A11, MX1, MX2, IL33, HIF1A, PDGFRB, PECAM1, STAT3, IL33, RGS5, CD163, C3, VCAM1, TNC, CD74, SERPINE1, CCR5, TEK, RUNX1, MX2, IFIT1, COL1A1, CXCL14, MRC1, CD68, CD14, MX1, LYVE1, HIF1A, LMNA, EMP1, EIF4A1, DHX9, LYVE1, YWHAQ, CD163, VCAM1, MKI67, IFIT1, ICAM1, STAT1, STAT3, TOP2A, S100A6, WARS1, S100A1, SERPINH1, TOP2A, MX1, MX2, CD14, HSPA9, and HSPD1. In some embodiments, the expression levels of the two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen, twenty, twenty- one, twenty-two, twenty-three, twenty-four, twenty-five, twenty-six, twenty-seven, twenty-eight, twenty-nine, thirty, thirty-one, thirty-two, thirty-three, thirty-four, thirty-five, thirty-six, thirty- seven, thirty-eight, thirty-nine, forty, forty-one, forty-two, forty-three, forty-four, forty-five, forty-six, forty-seven, forty-eight, forty-nine, fifty, fifty-one, fifty-two, fifty-three, fifty-four, fifty-five, fifty-six, fifty-seven, fifty-eight, fifty-nine, sixty, sixty-one, sixty-two, sixty-three, sixty-four, sixty-five, sixty-six, sixty-seven, sixty-eight, sixty-nine, seventy, seventy-one, seventy-two, seventy-three, seventy-four, seventy-five, seventy-six, seventy-seven, seventy- eight, seventy-nine, eighty, eighty-one, eighty-two, eighty-three, eighty-four, eighty-five, eighty- six, eighty-seven, eighty-eight, eighty-nine, ninety, ninety-one, ninety-two, ninety-three, ninety- four, ninety-five, ninety-six, ninety-seven, ninety-eight, ninety-nine, one hundred, one hundred 100 314164997v1Attorney Docket No: 243735.000437 one, one hundred two, one hundred three, one hundred four, one hundred five, one hundred six, one hundred seven, one hundred eight, one hundred nine, one hundred ten, one hundred eleven, one hundred twelve, one hundred thirteen, one hundred fourteen, one hundred fifteen, one hundred sixteen, one hundred seventeen, one hundred eighteen, one hundred nineteen, one hundred twenty, one hundred twenty-one, one hundred twenty-two, one hundred twenty-three, one hundred twenty-four, one hundred twenty-five, one hundred twenty-six, one hundred twenty- seven, one hundred twenty-eight, one hundred twenty-nine, one hundred thirty, one hundred thirty-one, one hundred thirty-two, one hundred thirty-three, one hundred thirty-four, one hundred thirty-five, one hundred thirty-six, one hundred thirty-seven, one hundred thirty-eight, one hundred thirty-nine, one hundred forty, one hundred forty-one, one hundred forty-two, one hundred forty-three, or one hundred forty-four genes are compared to a corresponding control.

[0212] In some embodiments, the sample can comprise functionally-related cells or adjacent cells. Samples may comprise complex populations of cells, which can be assayed together as a population or separated into sub-populations. Cellular and acellular samples can be separated by elutriation, centrifugation, centrifugation with Hypaque, apheresis, density gradient separation, affinity selection, panning, FACS, etc. A homogeneous population of cells may be obtained via use of antibodies specific for markers identified with particular cell types. Instead, a heterogeneous cell population can be used. Cells may be separated using filters. For example, whole blood can be applied to filters that contain pore sizes that select for the desired cell class or type. Cells can be filtered out of diluted, whole blood after the lysis of red blood cells through the use of filters with pore sizes (e.g., between 5 to 10 μm, see U.S. Pat. No.09 / 790,673). Other devices can separate cells from the bloodstream (see e.g., Demirci, Toner, Direct etch method for microfluidic channel and nanoheight post-fabrication by picoliter droplets, Applied Physics Letters, 2006; 88 (5), 053117; and Irimia, Geba, Toner, Universal microfluidic gradient generator, Analytical Chemistry, 2006; 78: 3472-3477). Once a sample is obtained, it may be used directly, frozen, or maintained in suitable culture medium.

[0213] To obtain a blood sample, any technique or protocol known in the art may be used (e.g., a syringe or other device that uses vacuum suction). A blood sample may be optionally pre- treated or processed before enrichment. Examples of pre-treatment steps may include the addition of a reagent (e.g., a fixant, a stabilizer, a preservative, a lysing reagent, a diluent, a magnetic property regulating reagent, an anti-apoptotic reagent, an anti-thrombotic reagent, an 101 314164997v1Attorney Docket No: 243735.000437 anti-coagulation reagent, a buffering reagent, a cross-linking reagent, an osmolality regulating reagent, and / or a pH regulating reagent).

[0214] Once a blood sample is obtained, a preservative (e.g., an anti-coagulation agent and / or a stabilizer) may be added to the sample before enrichment. Addition of a preservative allows for extended time for analysis and / or detection. Thus, a sample (e.g., a blood sample) may be analyzed using any of the methods and systems herein within over 1 week, 1 week, 6 days, 5 days, 4 days, 3 days, 2 days, 1 day, 18 hours, 12 hours, 6 hours, 3 hours, 2 hours, 1 hour, or less than 1 hour from the time the sample is obtained.

[0215] In some embodiments, a blood sample may be combined with an agent that selectively lyses one or more components (e.g., one or more cells) in a blood sample. For example, enucleated red blood cells and / or platelets can be selectively lysed to generate a sample enriched in nucleated cells. Afterwards, cells of interest can be separated from the sample using methods and / or processes known in the art.

[0216] When obtaining a sample (e.g., a blood sample) from a subject, the amount of sample can vary depending upon the condition being screened and the subject size. In some embodiments, up to 50 mL, 40 mL, 30 mL, 20 mL, 15 mL, 10 mL, 9 mL, 8 mL, 7 mL, 6 mL, 5 mL, 4 mL, 3 mL, 2 mL, or 1 mL of a sample is obtained. In some embodiments, about 1-50 mL, about 2-40 mL, about 3-30 mL, or about 4-20 mL of sample is obtained. In some embodiments, more than 5 mL, 10 mL, 15 mL, 20 mL, 25 mL, 30 mL, 35 mL, 40 mL, 45 mL, 50 mL, 55 mL, 60 mL, 65 mL, 70 mL, 75 mL, 80 mL, 85 mL, 90 mL, 95 mL, or 100 mL of a sample is obtained.

[0217] In some embodiments, the method further comprises step c) (i) determining that the subject has a xenograft rejection or is at a risk of a xenograft rejection when the expression levels of at least one of the genes determined in step (a) are increased as compared to the control by 1.5-fold or more; or (ii) determining that the subject does not have a xenograft rejection or is not at a risk of a xenograft rejection when the expression levels of at least one of the genes determined in step (a) are decreased, not increased or increased by less than 1.5-fold as compared to the control.

[0218] In some embodiments, the expression levels are determined for at least two of the genes, at least three of the genes, at least four of the genes, at least five of the genes, at least six of the genes, at least seven of the genes, at least eight of the genes, at least nine of the genes, at 102 314164997v1Attorney Docket No: 243735.000437 least ten of the genes, at least eleven of the genes, at least twelve of the genes, at least thirteen of the genes, at least fourteen of the genes, at least fifteen of the genes, at least sixteen of the genes, at least seventeen of the genes, at least eighteen of the genes, at least nineteen of the genes, at least twenty of the genes, at least twenty-one of the genes, at least twenty-two of the genes, at least twenty-three of the genes, at least twenty-four of the genes, at least twenty-five of the genes, at least twenty-six of the genes, at least twenty-seven of the genes, at least twenty-eight of the genes, at least twenty-nine of the genes, at least thirty of the genes, at least thirty-one of the genes, at least thirty-two of the genes, at least thirty-three of the genes, at least thirty-four of the genes, at least thirty-five of the genes, at least thirty-six of the genes, at least thirty-seven of the genes, at least thirty-eight of the genes, at least thirty-nine of the genes, at least forty of the genes, at least forty-one of the genes, at least forty-two of the genes, at least forty-three of the genes, at least forty-four of the genes, at least forty-five of the genes, at least forty-six of the genes, at least forty-seven of the genes, at least forty-eight of the genes, at least forty-nine of the genes, at least fifty of the genes, at least fifty-one of the genes, at least fifty-two of the genes, at least fifty-three of the genes, at least fifty-four of the genes, at least fifty-five of the genes, at least fifty-six of the genes, at least fifty-seven of the genes, at least fifty-eight of the genes, at least fifty-nine of the genes, at least sixty of the genes, at least sixty-one of the genes, at least sixty-two of the genes, at least sixty-three of the genes, at least sixty-four of the genes, at least sixty-five of the genes, at least sixty-six of the genes, at least sixty-seven of the genes, at least sixty-eight of the genes, at least sixty-nine of the genes, at least seventy of the genes, at least seventy-one of the genes, at least seventy-two of the genes, at least seventy-three of the genes, at least seventy-four of the genes, at least seventy-five of the genes, at least seventy-six of the genes, at least seventy-seven of the genes, at least seventy-eight of the genes, at least seventy- nine of the genes, at least eighty of the genes, at least eighty-one of the genes, at least eighty-two of the genes, at least eighty-three of the genes, at least eighty-four of the genes, at least eighty- five of the genes, at least eighty-six of the genes, at least eighty-seven of the genes, at least eighty-eight of the genes, at least eighty-nine of the genes, at least ninety of the genes, at least ninety-one of the genes, at least ninety-two of the genes, at least ninety-three of the genes, at least ninety-four of the genes, at least ninety-five of the genes, at least ninety-six of the genes, at least ninety-seven of the genes, at least ninety-eight of the genes, at least ninety-nine of the genes, at least one hundred of the genes, at least one hundred one of the genes, at least one 103 314164997v1Attorney Docket No: 243735.000437 hundred two of the genes, at least one hundred three of the genes, at least one hundred four of the genes, at least one hundred five of the genes, at least one hundred six of the genes, at least one hundred seven of the genes, at least one hundred eight of the genes, at least one hundred nine of the genes, at least one hundred ten of the genes, at least one hundred eleven of the genes, at least one hundred twelve of the genes, at least one hundred thirteen of the genes, at least one hundred fourteen of the genes, at least one hundred fifteen of the genes, at least one hundred sixteen of the genes, at least one hundred seventeen of the genes, at least one hundred eighteen of the genes, at least one hundred nineteen of the genes, at least one hundred twenty of the genes, at least one hundred twenty-one of the genes, at least one hundred twenty-two of the genes, at least one hundred twenty-three of the genes, at least one hundred twenty-four of the genes, at least one hundred twenty-five of the genes, at least one hundred twenty-six of the genes, at least one hundred twenty-seven of the genes, at least one hundred twenty-eight of the genes, at least one hundred twenty-nine of the genes, at least one hundred thirty of the genes, at least one hundred thirty-one of the genes, at least one hundred thirty-two of the genes, at least one hundred thirty- three of the genes, at least one hundred thirty-four of the genes, at least one hundred thirty-five of the genes, at least one hundred thirty-six of the at least one hundred thirty-seven of the genes, at least one hundred thirty-eight of the genes, at least one hundred thirty-nine of the genes, at least one hundred forty of the genes, at least one hundred forty-one of the genes, at least one hundred forty-two of the genes, at least one hundred forty-three of the genes, at least one hundred forty-four of the genes, at least one hundred forty-five of the genes, at least one hundred forty-six of the genes, at least one hundred forty-seven of the genes, at least one hundred forty- eight of the genes, at least one hundred forty-nine of the genes, at least one hundred fifty of the genes, at least one hundred fifty-one of the genes, at least one hundred fifty-two of the genes, at least one hundred fifty-three of the genes, at least one hundred fifty-four of the genes, at least one hundred fifty-five of the genes, at least one hundred fifty-six of the genes, at least one hundred fifty-seven of the genes, at least one hundred fifty-eight of the genes, at least one hundred fifty-nine of the genes, at least one hundred sixty of the genes, at least one hundred sixty-one of the genes, at least one hundred sixty-two of the genes, at least one hundred sixty- three of the genes, at least one hundred sixty-four of the genes, at least one hundred sixty-five of the genes, at least one hundred sixty-six of the genes, at least one hundred sixty-seven of the genes, at least one hundred sixty-eight of the genes, at least one hundred sixty-nine of the genes, 104 314164997v1Attorney Docket No: 243735.000437 at least one hundred seventy of the genes, at least one hundred seventy-one of the genes, at least one hundred seventy-two of the genes, at least one hundred seventy-three of the genes, at least one hundred seventy-four of the genes, at least one hundred seventy-five of the genes, at least one hundred seventy-six of the genes, at least one hundred seventy-seven of the genes, at least one hundred seventy-eight of the genes, at least one hundred seventy-nine of the genes, at least one hundred eighty of the genes, at least one hundred eighty-one of the genes, at least one hundred eighty-two of the genes, at least one hundred eighty-three of the genes, at least one hundred eighty-four of the genes, at least one hundred eighty-five of the genes, at least one hundred eighty-six of the genes, at least one hundred eighty-seven of the genes, at least one hundred eighty-eight of the genes, at least one hundred eighty-nine of the genes, at least one hundred ninety of the genes, at least one hundred ninety-one of the genes, at least one hundred ninety-two of the genes, at least one hundred ninety-three of the genes, at least one hundred ninety-four of the genes, at least one hundred ninety-five of the genes, at least one hundred ninety-six of the genes, at least one hundred ninety-seven of the genes, at least one hundred ninety-eight of the genes, or one hundred ninety-nine genes in step (a). In some embodiments, the expression levels are determined for two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen, twenty, twenty-one, twenty-two, twenty-three, twenty-four, twenty-five, twenty-six, twenty-seven, twenty-eight, twenty-nine, thirty, thirty-one, thirty-two, thirty-three, thirty-four, thirty-five, thirty-six, thirty- seven, thirty-eight, thirty-nine, forty, forty-one, forty-two, forty-three, forty-four, forty-five, forty-six, forty-seven, forty-eight, forty-nine, fifty, fifty-one, fifty-two, fifty-three, fifty-four, fifty-five, fifty-six, fifty-seven, fifty-eight, fifty-nine, sixty, sixty-one, sixty-two, sixty-three, sixty-four, sixty-five, sixty-six, sixty-seven, sixty-eight, sixty-nine, seventy, seventy-one, seventy-two, seventy-three, seventy-four, seventy-five, seventy-six, seventy-seven, seventy- eight, seventy-nine, eighty, eighty-one, eighty-two, eighty-three, eighty-four, eighty-five, eighty- six, eighty-seven, eighty-eight, eighty-nine, ninety, ninety-one, ninety-two, ninety-three, ninety- four, ninety-five, ninety-six, ninety-seven, ninety-eight, ninety-nine, one hundred, one hundred one, one hundred two, one hundred three, one hundred four, one hundred five, one hundred six, one hundred seven, one hundred eight, one hundred nine, one hundred ten, one hundred eleven, one hundred twelve, one hundred thirteen, one hundred fourteen, one hundred fifteen, one hundred sixteen, one hundred seventeen, one hundred eighteen, one hundred nineteen, one 105 314164997v1Attorney Docket No: 243735.000437 hundred twenty, one hundred twenty-one, one hundred twenty-two, one hundred twenty-three, one hundred twenty-four, one hundred twenty-five, one hundred twenty-six, one hundred twenty- seven, one hundred twenty-eight, one hundred twenty-nine, one hundred thirty, one hundred thirty-one, one hundred thirty-two, one hundred thirty-three, one hundred thirty-four, one hundred thirty-five, one hundred thirty-six, one hundred thirty-seven, one hundred thirty-eight, one hundred thirty-nine, one hundred forty, one hundred forty-one, one hundred forty-two, one hundred forty-three, one hundred forty-four, one hundred forty-five, one hundred forty-six, one hundred forty-seven, one hundred forty-eight, one hundred forty-nine, one hundred fifty, one hundred fifty-one, one hundred fifty-two, one hundred fifty-three, one hundred fifty-four, one hundred fifty-five, one hundred fifty-six, one hundred fifty-seven, one hundred fifty-eight, one hundred fifty-nine, one hundred sixty, one hundred sixty-one, one hundred sixty-two, one hundred sixty-three, one hundred sixty-four, one hundred sixty-five, one hundred sixty-six, one hundred sixty-seven, one hundred sixty-eight, one hundred sixty-nine, one hundred seventy, one hundred seventy-one, one hundred seventy-two, one hundred seventy-three, one hundred seventy-four, one hundred seventy-five, one hundred seventy-six, one hundred seventy-seven, one hundred seventy-eight, one hundred seventy-nine, one hundred eighty, one hundred eighty- one, one hundred eighty-two, one hundred eighty-three, one hundred eighty-four, one hundred eighty-five, one hundred eighty-six, one hundred eighty-seven, one hundred eighty-eight, one hundred eighty-nine, one hundred ninety, one hundred ninety-one, one hundred ninety-two, one hundred ninety-three, one hundred ninety-four, one hundred ninety-five, one hundred ninety-six, one hundred ninety-seven, one hundred ninety-eight, or one hundred ninety-nine genes in step (a). In some embodiments, the expression levels are determined for each of the genes in step (a).

[0219] In some embodiments, the control is a predetermined value or a value determined from a sample taken from the subject before the xenograft transplantation.

[0220] In some embodiments, the control is a predetermined value or a value determined from a sample taken from the xenograft before the xenograft transplantation.

[0221] In some embodiments, the corresponding control is a predetermined standard. In some embodiments, the corresponding control is a level or proportion of the expression levels of the one or more genes determined in a sample obtained from the subject at an earlier time point. In some embodiments, the corresponding control is generated in one or more subjects that did not undergo xenograft transplantation. In some embodiments, the corresponding control is generated 106 314164997v1Attorney Docket No: 243735.000437 in one or more subjects on the day of xenograft transplantation (POD 0). In some embodiments, the corresponding control is generated in one or more subjects before the day of xenograft transplantation (before POD 0). In some embodiments, the corresponding control is generated is generated in the xenograft (e.g., organ, tissue, or cells) to be transplanted on the day of xenograft transplantation (POD 0). In some embodiments, the corresponding control is generated in the xenograft (e.g., organ, tissue, or cells) to be transplanted before the day of xenograft transplantation (before POD 0).

[0222] In some embodiments, the method further comprises administering to the subject a treatment that targets plasma cells and / or a complement inhibitory agent, when the subject is determined to have a xenograft rejection or is at a risk of a xenograft rejection.

[0223] In some embodiments, the method further comprises administering to the subject a treatment that targets T cells when the subject is determined to have a xenograft rejection or is at a risk of a xenograft rejection.

[0224] In some embodiments, the method further comprises administering to the subject a treatment that targets plasma cells, a treatment that targets T cells, a complement inhibitory agent, or a combination thereof, when the subject is determined to have a xenograft rejection or is at a risk of a xenograft rejection.

[0225] Treatments that target plasma cells may include, but are not limited to, proteasome inhibitors (e.g., bortezomib (Velcade) and carfilzomib (Kyprolis)), immunomodulatory drugs (IMiDs) (e.g., lenalidomide (Revlimid) and pomalidomide (Pomalyst)), monoclonal antibodies (e.g., daratumumab (Darzalex) and isatuximab (Sarclisa)), antibody-drug conjugates (e.g., Belantamab mafodotin (Blenrep)), B-cell maturation antigen (BCMA) targeted therapies (e.g., idecabtagene vicleucel (Abecma) and bispecific antibodies like teclistamab (Tecvayli)).

[0226] In some embodiments, the treatment that targets plasma cells is plasmapheresis. Plasmapheresis (i.e., plasma exchange) may be used to removes plasma from the blood, which can help reduce the levels of certain antibodies and other proteins circulating in the bloodstream.

[0227] Treatments that target T cells may comprise CAR T-cell therapy, checkpoint inhibitors (e.g., inhibitors that target PD-1, PD-L1, and / or CTLA-4), T-cell transfer therapy (i.e., adoptive cell therapy), immunosuppressive drugs (e.g., cyclosporine and tacrolimus), vaccines, and bi- specific T-cell engagers (BiTEs). Rabbit anti-thymocyte globulin (rATG) is an immunosuppressive medication that targets T cells. Other treatments to target T cells may 107 314164997v1Attorney Docket No: 243735.000437 include, but are not limited to, horse anti-thymocyte globulin (hATG), alemtuzumab (Campath), basiliximab (Simulect), daclizumab, and muromonab-CD3 (Orthoclone OKT3).

[0228] In some embodiments, the treatment that targets T cells is rabbit anti-thymocyte globulin (rATG).

[0229] Without wishing to be limited by theory, the complement system, consisting of approximately 30 proteins, is a crucial component of the immune system's effector mechanisms. It is primarily activated through two pathways: the classical pathway, which typically depends on antibodies, and the alternative pathway, which generally operates independently of antibodies. Activation through either pathway results in the formation of C3 convertase, the central enzymatic complex of the cascade. This complex cleaves serum C3 into C3a and C3b. C3b binds covalently at the activation site, facilitating further C3 convertase generation in an amplification loop. C3b, along with C4b (produced exclusively via the classical pathway), and their breakdown products serve as significant opsonins. They play a role in promoting cell-mediated lysis of target cells by phagocytes and NK cells, as well as in the transport and solubilization of immune complexes. Additionally, C3 / C4 activation products and their receptors on various immune cells are vital for modulating the cellular immune response.

[0230] C3 convertases also contribute to the formation of C5 convertase, which cleaves C5 into C5a and C5b. C5a possesses strong pro-inflammatory and chemotactic properties, enabling it to recruit and activate immune effector cells. The formation of C5b triggers the terminal complement pathway, leading to the sequential assembly of complement proteins C6, C7, C8, and (C9)n, forming the membrane attack complex (MAC or C5b-9). The presence of MAC in a target cell membrane can cause direct cell lysis or induce cell activation, resulting in the expression and release of various inflammatory modulators.

[0231] There are two main categories of membrane complement inhibitors: those that block the complement activation pathway by preventing C3 convertase formation, and those that inhibit the terminal complement pathway by stopping MAC formation. Membrane inhibitors of complement activation include complement receptor 1 (CR1), decay-accelerating factor (DAF or CD55), and membrane cofactor protein (MCP or CD46). These proteins share a structural feature of repeating units, known as short consensus repeats (SCR), each consisting of about 60-70 amino acids, which are common in C3 / C4 binding proteins. In rodents, homologues of human complement activation inhibitors have been identified. The rodent protein CR1 is a broadly 108 314164997v1Attorney Docket No: 243735.000437 distributed inhibitor of complement activation, functioning similarly to both DAF and MCP. In addition, complement activation blocker-2 (CAB-2), a recombinant soluble chimeric protein derived from human DAF and MCP, inhibits C3 and C5 convertases of both classical and alternative pathways.

[0232] In some embodiments, the complement inhibitory agent is a C3 inhibitor.

[0233] In some embodiments, the method further comprises administering an immunosuppressive agent to the subject when the subject is determined to have a xenograft rejection or is at a risk of a xenograft rejection.

[0234] In some embodiments, the treatment may comprise an immunosuppressive agent, including, but not limited to a Janus kinase inhibitor, a corticosteroid, a mTOR inhibitor, a calcineurin inhibitor, an inosine-5′-monophosphate dehydrogenase (IMPDH) inhibitor, a biologic (e.g., infliximab, adalimumab, abatacept, certolizumab, anakinra, etanercept, golimumab, natalizumab, tocilizumab, ustekinumab, rituximab, secukinumab, vedolizumab, ixekizumab), or a monoclonal antibody (e.g., daclizumab, basilivimab).

[0235] In some embodiments, the treatment may comprise an anti-inflammatory agent, including, but not limited to a steroidal anti-inflammatory agent or a non-steroidal anti- inflammatory agent (e.g., naproxen, ketorolac, diclofenac, meloxicam, etodolac, esomeprazole, misoprostol, ibuprofen, famotidine, nabumetone, mefenamic acid, indomethacin, piroxicam, sulindac, ketoprofen, flurbiprofen, diflunisal, oxaprozin, nabumetone, tolmetin). In some embodiments, the treatment may comprise an antibacterial or antiviral therapy.

[0236] In some embodiments, the method further comprises administering to the subject a treatment for elevated immune activity, inflammation, xenograft damage or dysfunction, or rejection response. In some embodiments, the method further comprises administering to the subject a treatment for the xenograft damage or dysfunction, or rejection response based on the type of xenograft damage or dysfunction, or rejection response. In some embodiments, the method comprises administering a treatment to the subject when elevated immune activity, inflammation, xenograft damage or dysfunction, or rejection response is detected. Detection of elevated immune activity, inflammation, xenograft damage or dysfunction, or rejection response may be in accordance with the methods described herein. 109 314164997v1Attorney Docket No: 243735.000437

[0237] In some embodiments, the type of xenograft damage or dysfunction, or rejection response described herein is an antibody-mediated rejection, acute cellular rejection (e.g., T-cell mediated rejection), podocyte damage, ischemia damage, and any other cellular damage.

[0238] In some embodiments, the method comprises determining cell type(s) of recipient- derived cells present in a graft after the graft has been transplanted in a subject. Cellular origins are associated with different types of tissue, for example, mature B-cells can be associated with blood or bone marrow; naïve B-cells can be associated with blood or bone marrow; biliary epithelial cells can be associated with liver tissue; breast basal cells can be associated with breast tissue; breast luminal cells can be associated with breast tissue; bulk endothelial cells can be associated with blood vessels; bulk epithelial cells can be associated with any epithelia; bulk immune cells can be associated with immune organs; cardiomyocytes can be associated with heart tissue; cardiopulmonary endothelial cells can be associated with heart or lung tissues; colon epithelial cells can be associated with colon tissue; dermal epithelial cells can be associated with skin tissue; granulocytes can be associated with blood or bone marrow; hepatocytes can be associated with liver tissue; keratinocytes can be associated with skin tissue; kidney epithelial cells can be associated with kidney tissue; liver endothelial cells can be associated with liver tissue; liver stromal cells can be associated with liver tissue; liver resident immune cells can be associated with liver tissue; lung epithelial cells can be associated with lung tissue; megakaryocytes can be associated with bone marrow; monocytes and macrophages can be associated with blood; neurons can be associated with neural tissue; natural killer cells can be associated with blood; pancreatic cells can be associated with pancreas tissue; prostate epithelial cells can be associated with prostate tissue; skeletal muscular cells can be associated with skeletal muscle tissue; and mature T-cells can be associated with blood.

[0239] In some embodiments, the cell type(s) identified may be indicative of the type of xenograft damage or dysfunction, or rejection response. For example, the method may involve determining the type of xenograft damage or dysfunction, or rejection response is an antibody- mediated rejection when the cell type is determined to be endothelial cells.

[0240] In some embodiments, the invention herein provides methods for diagnosis of xenograft or graft rejection. Xenograft or graft rejection encompasses both acute and chronic xenograft or graft rejection. Acute xenograft or graft rejection is the rejection by the immune system of a xenograft or graft transplant recipient when the transplanted xenograft or graft is 110 314164997v1Attorney Docket No: 243735.000437 immunologically foreign. Acute xenograft or graft rejection is characterized by infiltration of the transplanted xenograft or graft by immune cells of the recipient, which carry out their effector function and work to destroy the transplanted xenograft or graft. Acute xenograft or graft rejection onset is rapid and generally occurs in humans within a few weeks after xenograft or graft transplant surgery. Generally, acute xenograft or graft rejection can be suppressed or inhibited with immunosuppressive agents such as a Janus kinase inhibitor, a corticosteroid, a mTOR inhibitor, a calcineurin inhibitor, an inosine-5′-monophosphate dehydrogenase (IMPDH) inhibitor, a biologic (e.g., infliximab, adalimumab, abatacept, certolizumab, anakinra, etanercept, golimumab, natalizumab, tocilizumab, ustekinumab, rituximab, secukinumab, vedolizumab, ixekizumab), or a monoclonal antibody (e.g., daclizumab, basilivimab), or the like.

[0241] Chronic xenograft or graft rejection generally occurs in humans within months to years after transplant, after successful immunosuppression of acute xenograft or graft rejection. Fibrosis is a common factor in chronic xenograft or graft rejection of organ xenograft or graft transplants. Chronic xenograft or graft rejection can typically be described by a range of disorders that are characteristic of the particular organ. For example, in heart transplants or transplants of cardiac tissue (e.g., valve replacements), such disorders may include fibrotic atherosclerosis; in lung transplants, such disorders may include fibroproliferative destruction of the airway (e.g., bronchiolitis obliterans); in liver transplants, such disorders may include disappearing bile duct syndrome; and in kidney transplants, such disorders may include obstructive nephropathy, nephrosclerosis, or tubulointerstitial nephropathy. Chronic xenograft or graft rejection can also be characterized by denervation of the transplanted tissue, ischemic insult, hypertension accompanying immunosuppressive drugs, and hyperlipidemia.

[0242] In some embodiments, the invention herein provides methods for diagnosis of xenograft damage or dysfunction. Xenograft damage or dysfunction may include, but is not limited to, viral infection, ischemic injury, reperfusion injury, peri-operative ischemia, hypertension, injuries due to reactive oxygen species, injuries caused by pharmaceutical agents, and physiological stress.

[0243] The xenograft transplant may comprise any cell, tissue, or organ from a donor of one species to a recipient of a different species. In some embodiments, the donor may be a non- human primate, cat, cow, dog, goat, horse, pig, rodent, sheep, reptile, or another non-human animal. In some embodiments, the rodent may be a beaver, guinea pig, hamster, mouse, 111 314164997v1Attorney Docket No: 243735.000437 porcupine, prairie dog, rat, squirrel, or another rodent. In some embodiments, the non-human primate may be an ape or a monkey. In some embodiments, the non-human primate may be an African green monkey, baboon, bonobo, capuchin monkey, chimpanzee, cynomolgus monkey, gorilla, marmoset, orangutan, owl monkey, pig-tailed monkey, rhesus monkey, spider monkey, squirrel monkey, vervet monkey, or another non-human primate. In some embodiments, the donor is a pig.

[0244] In some embodiments, the donor is a genetically modified animal. In one embodiment, the donor is a genetically modified pig.

[0245] In some embodiments, the xenotransplant recipient may be a human, and the xenotransplant donor may be a pig. In some embodiments, the pig may be a Sus scrofa, Sus scrofa domesticus, Phacochoerus aethiopicus, Potamochoerus porcus, or Babirousa babyrussa species. In some embodiments, the pig may be a Hanford pig, mini- or micro-pig, Yucatan pig, Yucatan micro pig, Sinclair pig, Gottingen pig, Duroc pig, Yorkshire pig, Landrace pig, or a combination, hybrid, or cross-species thereof.

[0246] The transplant may be any biological material comprising cells that have DNA and that can be transplanted from a donor to a subject. The cells may be organized as a tissue or portion thereof, an organ or portion thereof, or a population of cells not organized as a tissue or organ. The population of cells may be a population of the same cell type or of different cell types.

[0247] In some embodiments, the xenograft transplant may comprise an organ or portion thereof. Examples include, but are not limited to, kidney, blood vessel, liver, heart, pancreas, lung, colon, skin, bone, prostate, and muscle. In one embodiment, the xenograft transplant comprises a kidney. In one embodiment, the xenograft transplant comprises a heart.

[0248] In some embodiments, the xenograft transplant comprises a tissue or portion thereof. Examples include, but are not limited to, cardiac tissue, liver tissue, pancreatic tissue, vascular tissue, esophageal tissue, splenic tissue, intestinal tissue, gastric tissue, colon tissue, tracheal tissue, lung tissue, skin tissue, subcutaneous tissue, kidney tissue, hair tissue, connective tissue, muscular tissue, cartilage tissue, skeletal tissue, prostate tissue, bladder tissue, uterine tissue, penile tissue, gonadal tissue, neural tissue, ophthalmologic tissue, corneal tissue, and bone marrow tissue. 112 314164997v1Attorney Docket No: 243735.000437

[0249] In some embodiments, the xenograft transplant comprises a population of cells. Examples include, but are not limited to, natural killer cells, granulocytes, mature B-cells, naïve B-cells, mature T-cells, macrophages, monocytes, and stem cells.

[0250] In some embodiments, the subject has received a kidney, heart, lung, liver, bone marrow, pancreas, or islet cell transplantation from a porcine donor.

[0251] In some embodiments, the cell comprises an adipocyte, adrenal cell, antigen presenting cell, aortic endothelial cell, aortic smooth muscle cell, astrocyte, basophil, B cell, bladder cell, blood cell, blood precursor cell, bone cell, bone precursor cell, cardiac muscle cell, cardiac myocyte, cervical cell, chondrocyte, ciliated cell, cumulus cell, columnar epithelial cell, cone cell, dopaminergic cell, egg cell, embryonic stem cell, endothelial cell, endometrial cell, epidermal cell, epithelial cell, erythrocyte, fibroblast cell, fibroblast and fetal fibroblast, follicle cell, germ cell, glial cell, goblet cell, granulosa cell, hair cell, heart cell, hematopoietic cell, hepatocyte, Islets of Langerhans cell, keratinized epithelial cell, keratinocyte, kidney cell, Kupffer cell, leydig cell, liver stellate cell, lung cell, lutein cell, lymphocyte (B and T), macrophage, mammary cell, melanocyte, memory cell, microvascular endothelial cell, monocyte, mononuclear cell, mucous cell, muscle cell, neural cell, neuron, neuronal stem cell, neutrophil, nonkeratinized epithelial cell, ovarian cell, pacemaker cell, pancreatic alpha-1 cell, pancreatic alpha-2 cell, pancreatic beta cell, pancreatic insulin secreting cell, pancreatic islet cell, parathyroid cell, parotid cell, peritubular cell, pituitary cell, plasma cell, platelet, primordial stem cell, prostate cell, red blood cell, retinal cell, rod cell, Schwann cell, sertoli cell, smooth muscle cell, somatic cell, sperm cell, spleen cell, squamous epithelial cell, testicular cell, thyroid cell, T cell, tumor cell, umbilical vein endothelial cell, uterine cell, vaginal epithelial cell, and / or white blood cell.

[0252] In some embodiments, the subject has received a cartilage, bone, adipose, pancreatic islet, muscle, vascular tissue, heart valve, retinal tissue, neural tissue, or corneal tissue transplantation from a porcine donor.

[0253] In some embodiments, the tissue comprises adipose, areolar, blood, bone, bone marrow, brown adipose, cancellous, cartilage, cartilaginous, cavernous, chondroid, chromaffin, connective tissue, dartoic, elastic, epithelial, epithelium, fatty, fibro-hyaline, fibrous, Gamgee, gelatinous, granulation, gut-associated lymphoid, Haller's vascular, hard hemopoietic, indifferent, interstitial, investing, islet, lymphatic, lymphoid, mesenchymal, mesonephric, 113 314164997v1Attorney Docket No: 243735.000437 mucous connective, multilocular adipose, muscle, myeloid, nasion soft, nephrogenic, nerve, nodal, osseous, osteogenic, osteoid, periapical, reticular, retiform, rubber, skeletal muscle, smooth muscle, subcutaneous tissue, vascular tissue, heart valve, retinal tissue, neural tissue, and / or corneal tissue.

[0254] In some embodiments, the subject has received a heart, liver, kidney, pancreas, lung, thyroid or skin organ transplantation from a porcine donor.

[0255] In some embodiments, the organ comprises adrenal glands, anus, bladder, blood, blood vessels, bones, brain, cartilage, ears, esophagus, eye, glands, gums, hair, heart, hypothalamus, intestines, kidneys, large intestine, ligaments, lips, liver, lungs, lymph, lymph nodes, lymph vessels, mammary glands, mouth, nails, nose, ovaries, oviducts, pancreas, penis, pharynx, pituitary, pylorus, rectum, salivary glands, seminal vesicles, skeletal muscles, skin, small intestine, smooth muscles, spinal cord, spleen, stomach, suprarenal capsule, teeth, tendons, testes, thymus gland, thyroid gland, tongue, tonsils, trachea, ureters, urethra, uterus, and / or vagina.

[0256] In some embodiments, the expression levels are determined based on RNA expression, protein expression, epigenetic regulation, or a combination thereof.

[0257] In some embodiments, the expression levels are determined using RNA sequencing, targeted RNA panel, a quantitative PCR assay, an antibody-based method, an epigenetic assay, a single-cell technology, a spatial transcriptomics technology, or a multiplexed approach combining RNA and protein measurements.

[0258] In some embodiments, the antibody-based method is flow cytometry, immunohistochemistry, or enzyme-linked immunosorbent assay (ELISA).

[0259] In some embodiments, the single-cell technology is single-cell RNA sequencing (scRNA-seq) or cellular indexing of transcriptomes and epitopes (CITE-seq).

[0260] In some embodiments of any of the above-described methods, the expression level may be determined at the protein, mRNA, and / or gene level using an...

Claims

Attorney Docket No: 243735.000437 Claims 1. A method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes MS4A1, CD19, AIM2, BANK1, CD79A, TNFRSF13C, BLK, IGHM, and IGHD, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

2. A method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes XBP1, MZB1, TNFRSF17, CD27, TENT5C, POU2AF1, PRDM1, NUGGC, and SDC1, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs); and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

3. A method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes KLRC1, GZMB, TRDC, KLRF1, and GNLY, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control. 326 314164997v1Attorney Docket No: 243735.000437 4. A method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes LYZ, MRC1, STAB1, SLCO2B1, F13A1, CD163, MSR1, SLC40A1, and CD14, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

5. A method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes IRF7, TLR7, TLR9, MYD88, and STAT1, wherein the sample is a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

6. A method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes PLD4, CLEC4C, LILRA4, TPM2, MZB1, SCT, IRF4, and SMPD3, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control. 327 314164997v1Attorney Docket No: 243735.000437 7. A method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, and CLEC10A, wherein the sample is a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

8. A method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, and IFIH1, wherein the sample is a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

9. A method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes CD3G, THEMIS, CD5, and CD6, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

10. A method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: 328 314164997v1Attorney Docket No: 243735.000437 a) determining in a sample collected from the subject expression levels of CD8B and / or CD8A, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the gene(s) determined in step (a) to a corresponding control.

11. A method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes KLRG1, GZMK, CST7, and GZMH, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

12. A method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes LEF1, TCF7, SELL, CD27, CD55, and CCR7, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

13. A method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes CD4, CD40LG, CCR2, CCR6, and DPP4, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and 329 314164997v1Attorney Docket No: 243735.000437 b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

14. A method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes CTLA4, FOXP3, IKZF2, RTKN2, IRF4, IL21, and IL2RA, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

15. A method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes ITGAE, CD38, TNFRSF9, and MKI67, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

16. A method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes GZMA, PRF1, and FASLG, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control. 330 314164997v1Attorney Docket No: 243735.000437 17. A method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes TOP2A, TYMS, and MKI67, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

18. A method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes GBP1, IRF1, TAP1, WARS1, and IDO1, wherein the sample is a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

19. A method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes CLEC10A, CD1C, FCER1A, CD1E, CD1D, and CCR2, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

20. A method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: 331 314164997v1Attorney Docket No: 243735.000437 a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes CSF3R, FCGR3B, FPR1, ALPL, MGAM, CXCR1, MXD1, and CXCR2, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

21. A method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes MS4A1, CD19, AIM2, BANK1, CD79A, TNFRSF13C, BLK, IGHM, IGHD, XBP1, MZB1, TNFRSF17, CD27, TENT5C, POU2AF1, PRDM1, NUGGC, SDC1, KLRC1, GZMB, TRDC, KLRF1, GNLY, LYZ, MRC1, STAB1, SLCO2B1, F13A1, CD163, MSR1, SLC40A1, CD14, IRF7, TLR7, TLR9, MYD88, STAT1, PLD4, CLEC4C, LILRA4, TPM2, MZB1, SCT, IRF4, SMPD3, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, CD3G, THEMIS, CD5, CD6, CD8B, CD8A, KLRG1, GZMK, CST7, GZMH, LEF1, TCF7, SELL, CD27, CD55, CCR7, CD4, CD40LG, CCR2, CCR6, DPP4, CTLA4, FOXP3, IKZF2, RTKN2, IRF4, IL21, IL2RA, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, MKI67, GBP1, IRF1, TAP1, WARS1, IDO1, CLEC10A, CD1C, FCER1A, CD1E, CD1D, CCR2, CSF3R, FCGR3B, FPR1, ALPL, MGAM, CXCR1, MXD1, and CXCR2, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

22. A method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: 332 314164997v1Attorney Docket No: 243735.000437 a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes XBP1, MZB1, TNFRSF17, CD27, TENT5C, POU2AF1, PRDM1, NUGGC, SDC1, KLRC1, GZMB, TRDC, KLRF1, GNLY, LYZ, MRC1, STAB1, SLCO2B1, F13A1, CD163, MSR1, SLC40A1, CD14, IRF7, TLR7, TLR9, MYD88, STAT1, PLD4, CLEC4C, LILRA4, TPM2, MZB1, SCT, IRF4, SMPD3, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, MKI67, GBP1, IRF1, TAP1, WARS1, IDO1, CLEC10A, CD1C, FCER1A, CD1E, CD1D, CCR2, CSF3R, FCGR3B, FPR1, ALPL, MGAM, CXCR1, MXD1, and CXCR2, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

23. A method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from human genes MS4A1, CD19, AIM2, BANK1, CD79A, TNFRSF13C, BLK, IGHM, IGHD, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, CD3G, THEMIS, CD5, CD6, CD8B, CD8A, KLRG1, GZMK, CST7, GZMH, LEF1, TCF7, SELL, CD27, CD55, CCR7, CD4, CD40LG, CCR2, CCR6, DPP4, CTLA4, FOXP3, IKZF2, RTKN2, IRF4, IL21, IL2RA, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, and MKI67, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control. 333 314164997v1Attorney Docket No: 243735.000437 24. A method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from porcine genes SPP1, COLEC11, S100A6, NFKBIZ, CLDN1, THBS1, HIF1A, STMN1, ICAM1, TNFRSF1B, CXCL14, IL1RL1, and NREP, wherein the sample is a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

25. A method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from porcine genes C3, CXCL2, C4A, LYZ, S100A6, S100A11, MX1, MX2, IL33, and HIF1A, wherein the sample is a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

26. A method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from porcine genes PDGFRB, PECAM1, STAT3, IL33, RGS5, CD163, C3, VCAM1, TNC, CD74, SERPINE1, CCR5, TEK, RUNX1, MX2, IFIT1, COL1A1, CXCL14, MRC1, CD68, CD14, MX1, and LYVE1, wherein the sample is a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control. 334 314164997v1Attorney Docket No: 243735.000437 27. A method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from porcine genes HIF1A, LMNA, EMP1, EIF4A1, DHX9, LYVE1, YWHAQ, CD163, VCAM1, MKI67, IFIT1, ICAM1, STAT1, STAT3, TOP2A, S100A6, WARS1, S100A1, SERPINH1, TOP2A, MX1, MX2, CD14, HSPA9, and HSPD1, wherein the sample is a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

28. A method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from porcine genes SPP1, COLEC11, S100A6, NFKBIZ, CLDN1, THBS1, HIF1A, STMN1, ICAM1, TNFRSF1B, CXCL14, IL1RL1, NREP, C3, CXCL2, C4A, LYZ, S100A6, S100A11, MX1, MX2, IL33, HIF1A, PDGFRB, PECAM1, STAT3, IL33, RGS5, CD163, C3, VCAM1, TNC, CD74, SERPINE1, CCR5, TEK, RUNX1, MX2, IFIT1, COL1A1, CXCL14, MRC1, CD68, CD14, MX1, LYVE1, HIF1A, LMNA, EMP1, EIF4A1, DHX9, LYVE1, YWHAQ, CD163, VCAM1, MKI67, IFIT1, ICAM1, STAT1, STAT3, TOP2A, S100A6, WARS1, S100A1, SERPINH1, TOP2A, MX1, MX2, CD14, HSPA9, and HSPD1, wherein the sample is a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

29. A method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from 1) human genes MS4A1, CD19, AIM2, BANK1, CD79A, TNFRSF13C, BLK, 335 314164997v1Attorney Docket No: 243735.000437 IGHM, IGHD, XBP1, MZB1, TNFRSF17, CD27, TENT5C, POU2AF1, PRDM1, NUGGC, SDC1, KLRC1, GZMB, TRDC, KLRF1, GNLY, LYZ, MRC1, STAB1, SLCO2B1, F13A1, CD163, MSR1, SLC40A1, CD14, IRF7, TLR7, TLR9, MYD88, STAT1, PLD4, CLEC4C, LILRA4, TPM2, MZB1, SCT, IRF4, SMPD3, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, CD3G, THEMIS, CD5, CD6, CD8B, CD8A, KLRG1, GZMK, CST7, GZMH, LEF1, TCF7, SELL, CD27, CD55, CCR7, CD4, CD40LG, CCR2, CCR6, DPP4, CTLA4, FOXP3, IKZF2, RTKN2, IRF4, IL21, IL2RA, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, MKI67, GBP1, IRF1, TAP1, WARS1, IDO1, CLEC10A, CD1C, FCER1A, CD1E, CD1D, CCR2, CSF3R, FCGR3B, FPR1, ALPL, MGAM, CXCR1, MXD1, and CXCR2, and 2) porcine genes SPP1, COLEC11, S100A6, NFKBIZ, CLDN1, THBS1, HIF1A, STMN1, ICAM1, TNFRSF1B, CXCL14, IL1RL1, NREP, C3, CXCL2, C4A, LYZ, S100A6, S100A11, MX1, MX2, IL33, HIF1A, PDGFRB, PECAM1, STAT3, IL33, RGS5, CD163, C3, VCAM1, TNC, CD74, SERPINE1, CCR5, TEK, RUNX1, MX2, IFIT1, COL1A1, CXCL14, MRC1, CD68, CD14, MX1, LYVE1, HIF1A, LMNA, EMP1, EIF4A1, DHX9, LYVE1, YWHAQ, CD163, VCAM1, MKI67, IFIT1, ICAM1, STAT1, STAT3, TOP2A, S100A6, WARS1, S100A1, SERPINH1, TOP2A, MX1, MX2, CD14, HSPA9, and HSPD1, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

30. A method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from 1) human genes XBP1, MZB1, TNFRSF17, CD27, TENT5C, POU2AF1, PRDM1, NUGGC, SDC1, KLRC1, GZMB, TRDC, KLRF1, GNLY, LYZ, MRC1, STAB1, SLCO2B1, F13A1, CD163, MSR1, SLC40A1, CD14, IRF7, TLR7, TLR9, MYD88, STAT1, PLD4, CLEC4C, LILRA4, TPM2, MZB1, SCT, IRF4, SMPD3, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, 336 314164997v1Attorney Docket No: 243735.000437 STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, MKI67, GBP1, IRF1, TAP1, WARS1, IDO1, CLEC10A, CD1C, FCER1A, CD1E, CD1D, CCR2, CSF3R, FCGR3B, FPR1, ALPL, MGAM, CXCR1, MXD1, and CXCR2, and 2) porcine genes SPP1, COLEC11, S100A6, NFKBIZ, CLDN1, THBS1, HIF1A, STMN1, ICAM1, TNFRSF1B, CXCL14, IL1RL1, NREP, C3, CXCL2, C4A, LYZ, S100A6, S100A11, MX1, MX2, IL33, HIF1A, PDGFRB, PECAM1, STAT3, IL33, RGS5, CD163, C3, VCAM1, TNC, CD74, SERPINE1, CCR5, TEK, RUNX1, MX2, IFIT1, COL1A1, CXCL14, MRC1, CD68, CD14, MX1, LYVE1, HIF1A, LMNA, EMP1, EIF4A1, DHX9, LYVE1, YWHAQ, CD163, VCAM1, MKI67, IFIT1, ICAM1, STAT1, STAT3, TOP2A, S100A6, WARS1, S100A1, SERPINH1, TOP2A, MX1, MX2, CD14, HSPA9, and HSPD1, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

31. A method of detecting a xenograft rejection in a subject, or monitoring a xenograft rejection in a subject, or predicting a likelihood of a xenograft rejection in a subject, wherein the subject has received a xenograft transplantation, said method comprising: a) determining in a sample collected from the subject expression levels of two or more genes selected from 1) human genes MS4A1, CD19, AIM2, BANK1, CD79A, TNFRSF13C, BLK, IGHM, IGHD, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, CD3G, THEMIS, CD5, CD6, CD8B, CD8A, KLRG1, GZMK, CST7, GZMH, LEF1, TCF7, SELL, CD27, CD55, CCR7, CD4, CD40LG, CCR2, CCR6, DPP4, CTLA4, FOXP3, IKZF2, RTKN2, IRF4, IL21, IL2RA, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, and MKI67, and 2) porcine genes SPP1, COLEC11, S100A6, NFKBIZ, CLDN1, THBS1, HIF1A, STMN1, ICAM1, TNFRSF1B, CXCL14, IL1RL1, NREP, C3, CXCL2, C4A, LYZ, S100A6, S100A11, MX1, MX2, IL33, HIF1A, PDGFRB, PECAM1, STAT3, IL33, RGS5, CD163, C3, VCAM1, TNC, CD74, SERPINE1, CCR5, TEK, RUNX1, MX2, IFIT1, COL1A1, CXCL14, MRC1, CD68, CD14, MX1, LYVE1, HIF1A, LMNA, EMP1, EIF4A1, DHX9, LYVE1, YWHAQ, CD163, 337 314164997v1Attorney Docket No: 243735.000437 VCAM1, MKI67, IFIT1, ICAM1, STAT1, STAT3, TOP2A, S100A6, WARS1, S100A1, SERPINH1, TOP2A, MX1, MX2, CD14, HSPA9, and HSPD1, wherein the sample is isolated peripheral blood mononuclear cells (PBMCs) and / or a xenograft tissue biopsy; and b) comparing the expression levels of the two or more genes determined in step (a) to a corresponding control.

32. The method of any one of claims 1-31, wherein the method further comprises step c) (i) determining that the subject has a xenograft rejection or is at a risk of a xenograft rejection when the expression levels of at least one of the genes determined in step (a) are increased as compared to the control by 1.5-fold or more; or (ii) determining that the subject does not have a xenograft rejection or is not at a risk of a xenograft rejection when the expression levels of at least one of the genes determined in step (a) are decreased, not increased or increased by less than 1.5-fold as compared to the control.

33. The method of any one of claims 1-4, 6, 10-17, 19-23, and 29-32, wherein the control is a predetermined value or a value determined from a sample taken from the subject before the xenograft transplantation.

34. The method of any one of claims 1 and 3-32, wherein the control is a predetermined value or a value determined from a sample taken from the xenograft before the xenograft transplantation.

35. The method of any one of claims 1-6, 18-20, and 24-28, wherein the method further comprises administering to the subject a treatment that targets plasma cells and / or a complement inhibitory agent, when the subject is determined to have a xenograft rejection or is at a risk of a xenograft rejection.

36. The method of any one of claims 9-14, wherein the method further comprises administering to the subject a treatment that targets T cells when the subject is determined to have a xenograft rejection or is at a risk of a xenograft rejection. 338 314164997v1Attorney Docket No: 243735.000437 37. The method of any one of claims 7-8, 15-17, 21-23, and 29-31, wherein the method further comprises administering to the subject a treatment that targets plasma cells, a treatment that targets T cells, a complement inhibitory agent, or a combination thereof, when the subject is determined to have a xenograft rejection or is at a risk of a xenograft rejection.

38. The method of claim 35 or 37, wherein the treatment that targets plasma cells is plasmapheresis.

39. The method of claim 36 or 37, wherein the treatment that targets T cells is rabbit anti- thymocyte globulin (rATG).

40. The method of claim 35 or 37, wherein the complement inhibitory agent is a C3 inhibitor.

41. The method of any one of previous claims, wherein the method further comprises administering an immunosuppressive agent to the subject when the subject is determined to have a xenograft rejection or is at a risk of a xenograft rejection.

42. The method of any one of previous claims, wherein the subject has received a kidney, heart, lung, liver, bone marrow, pancreas, or islet cell transplantation from a porcine donor.

43. The method of any one of previous claims, wherein the expression levels are determined based on RNA expression, protein expression, epigenetic regulation, or a combination thereof.

44. The method of any one of previous claims, wherein the expression levels are determined using RNA sequencing, targeted RNA panel, a quantitative PCR assay, an antibody- based method, an epigenetic assay, a single-cell technology, a spatial transcriptomics technology, or a multiplexed approach combining RNA and protein measurements. 339 314164997v1Attorney Docket No: 243735.000437 45. The method of claim 44, wherein the antibody-based method is flow cytometry, immunohistochemistry, or enzyme-linked immunosorbent assay (ELISA).

46. The method of claim 44, wherein the single-cell technology is single-cell RNA sequencing (scRNA-seq) or cellular indexing of transcriptomes and epitopes (CITE-seq).

47. The method of any one of previous claims, wherein the sample is collected from the subject 3 days after the xenograft transplantation.

48. The method of any one of previous claims, wherein the method comprises obtaining two or more samples from the subject at different time points after the xenograft transplantation and repeating the method for each sample.

49. A kit comprising: 1) one or more sets of probe nucleic acids useful for detecting two or more genes selected from: i. human genes MS4A1, CD19, AIM2, BANK1, CD79A, TNFRSF13C, BLK, IGHM, and IGHD; ii. human genes XBP1, MZB1, TNFRSF17, CD27, TENT5C, POU2AF1, PRDM1, NUGGC, and SDC1; iii. human genes KLRC1, GZMB, TRDC, KLRF1, and GNLY; iv. human genes LYZ, MRC1, STAB1, SLCO2B1, F13A1, CD163, MSR1, SLC40A1, and CD14; v. human genes IRF7, TLR7, TLR9, MYD88, and STAT1; vi. human genes PLD4, CLEC4C, LILRA4, TPM2, MZB1, SCT, IRF4, and SMPD3; vii. human genes STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, and CLEC10A; viii. human genes MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, and IFIH1; ix. human genes CD3G, THEMIS, CD5, and CD6; x. human genes CD8B, and CD8A; 340 314164997v1Attorney Docket No: 243735.000437 xi. human genes KLRG1, GZMK, CST7, and GZMH; xii. human genes LEF1, TCF7, SELL, CD27, CD55, and CCR7; xiii. human genes CD4, CD40LG, CCR2, CCR6, DPP4; xiv. human genes CTLA4, FOXP3, IKZF2, RTKN2, IRF4, IL21, and IL2RA; xv. human genes ITGAE, CD38, TNFRSF9, and MKI67; xvi. human genes GZMA, PRF1, and FASLG; xvii. human genes TOP2A, TYMS, and MKI67; xviii. human genes GBP1, IRF1, TAP1, WARS1, and IDO1; xix. human genes CLEC10A, CD1C, FCER1A, CD1E, CD1D, and CCR2; xx. human genes CSF3R, FCGR3B, FPR1, ALPL, MGAM, CXCR1, MXD1, CXCR2; xxi. human genes MS4A1, CD19, AIM2, BANK1, CD79A, TNFRSF13C, BLK, IGHM, IGHD, XBP1, MZB1, TNFRSF17, CD27, TENT5C, POU2AF1, PRDM1, NUGGC, SDC1, KLRC1, GZMB, TRDC, KLRF1, GNLY, LYZ, MRC1, STAB1, SLCO2B1, F13A1, CD163, MSR1, SLC40A1, CD14, IRF7, TLR7, TLR9, MYD88, STAT1, PLD4, CLEC4C, LILRA4, TPM2, MZB1, SCT, IRF4, SMPD3, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, CD3G, THEMIS, CD5, CD6, CD8B, CD8A, KLRG1, GZMK, CST7, GZMH, LEF1, TCF7, SELL, CD27, CD55, CCR7, CD4, CD40LG, CCR2, CCR6, DPP4, CTLA4, FOXP3, IKZF2, RTKN2, IRF4, IL21, IL2RA, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, MKI67, GBP1, IRF1, TAP1, WARS1, IDO1, CLEC10A, CD1C, FCER1A, CD1E, CD1D, CCR2, CSF3R, FCGR3B, FPR1, ALPL, MGAM, CXCR1, MXD1, and CXCR2; xxii. human genes XBP1, MZB1, TNFRSF17, CD27, TENT5C, POU2AF1, PRDM1, NUGGC, SDC1, KLRC1, GZMB, TRDC, KLRF1, GNLY, LYZ, MRC1, STAB1, SLCO2B1, F13A1, CD163, MSR1, SLC40A1, CD14, IRF7, TLR7, TLR9, MYD88, STAT1, PLD4, CLEC4C, LILRA4, TPM2, MZB1, SCT, IRF4, SMPD3, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, 341 314164997v1Attorney Docket No: 243735.000437 FASLG, TOP2A, TYMS, MKI67, GBP1, IRF1, TAP1, WARS1, IDO1, CLEC10A, CD1C, FCER1A, CD1E, CD1D, CCR2, CSF3R, FCGR3B, FPR1, ALPL, MGAM, CXCR1, MXD1, and CXCR2; xxiii. human genes MS4A1, CD19, AIM2, BANK1, CD79A, TNFRSF13C, BLK, IGHM, IGHD, STAT1, GBP1, GBP5, WARS1, IRF1, CXCL10, CXCL9, CXCL11, TAP1, SLAMF7, APOL3, LILRB1, CLEC10A, MX1, STAT1, IFIT3, IFIT1, IFIT2, IFI44L, GBP1, OAS3, CXCL10, RSAD2, TNFSF10, OAS1, IFIH1, CD3G, THEMIS, CD5, CD6, CD8B, CD8A, KLRG1, GZMK, CST7, GZMH, LEF1, TCF7, SELL, CD27, CD55, CCR7, CD4, CD40LG, CCR2, CCR6, DPP4, CTLA4, FOXP3, IKZF2, RTKN2, IRF4, IL21, IL2RA, ITGAE, CD38, TNFRSF9, MKI67, GZMA, PRF1, FASLG, TOP2A, TYMS, and MKI67; xxiv. porcine genes SPP1, COLEC11, S100A6, NFKBIZ, CLDN1, THBS1, HIF1A, STMN1, ICAM1, TNFRSF1B, CXCL14, IL1RL1, and NREP; xxv. porcine genes C3, CXCL2, C4A, LYZ, S100A6, S100A11, MX1, MX2, IL33, and HIF1A; xxvi. porcine genes PDGFRB, PECAM1, STAT3, IL33, RGS5, CD163, C3, VCAM1, TNC, CD74, SERPINE1, CCR5, TEK, RUNX1, MX2, IFIT1, COL1A1, CXCL14, MRC1, CD68, CD14, MX1, and LYVE1; xxvii. porcine genes HIF1A, LMNA, EMP1, EIF4A1, DHX9, LYVE1, YWHAQ, CD163, VCAM1, MKI67, IFIT1, ICAM1, STAT1, STAT3, TOP2A, S100A6, WARS1, S100A1, SERPINH1, TOP2A, MX1, MX2, CD14, HSPA9, and HSPD1; and / or xxviii. porcine genes SPP1, COLEC11, S100A6, NFKBIZ, CLDN1, THBS1, HIF1A, STMN1, ICAM1, TNFRSF1B, CXCL14, IL1RL1, NREP, C3, CXCL2, C4A, LYZ, S100A6, S100A11, MX1, MX2, IL33, HIF1A, PDGFRB, PECAM1, STAT3, IL33, RGS5, CD163, C3, VCAM1, TNC, CD74, SERPINE1, CCR5, TEK, RUNX1, MX2, IFIT1, COL1A1, CXCL14, MRC1, CD68, CD14, MX1, LYVE1, HIF1A, LMNA, EMP1, EIF4A1, DHX9, LYVE1, YWHAQ, CD163, VCAM1, MKI67, IFIT1, ICAM1, STAT1, STAT3, TOP2A, S100A6, WARS1, S100A1, SERPINH1, TOP2A, MX1, MX2, CD14, HSPA9, and HSPD1; or any combination of the genes listed above, and 2) optionally, packaging and / or instructions for using the same. 342 314164997v1

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