Categorical mismatched epitopes and methods for predicting an immune response against mismatched human leukocyte antigens

Abstract

Development of de novo donor specific antibodies (dnDSA) and antibody mediated rejection (AMR) remain to be a barrier for long term graft and patient survival. Most dnDSA are against mismatched donor HLA-DQ antigens. New methods for evaluating HLA-DQ mismatches are provided based on assessment of compositions and locations of categorical amino acid mismatched epitope (CAME). Specifically, amino acid residues of the HLA-DQ protein can be categorized into four groups, and categorical mismatched peptides are ranked in terms of likelihood of presentation by the recipient HLA-DRB1. Applicant has discovered the presence of DQB1 mismatches with %Ranking score ≤1 (corresponding to a binding strength between mismatched DQB1 and DQR1 between donor and recipient being in top 1%) is associated with development of dnDSA in heart transplant recipients, and dnDSA increases the risk of AMR only in recipients who have DQ mismatches with %Ranking score ≤ 1.

Description

CATEGORICAL MISMATCHED EPITOPES AND METHODS FOR PREDICTING AN IMMUNE RESPONSE AGAINST MISMATCHED HUMAN LEUKOCYTE ANTIGENSCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application includes a claim of priority under 35 U.S.C. §119(e) to U.S. provisional patent application No. 63 / 631,693, filed April 9, 2024, the entirety of which is hereby incorporated by reference.REFERENCE TO SEQUENCE LISTING

[0002] This application contains a Sequence Listing submitted as a computer readable form named “065472_000976WOPT_SequenceListing.xml”, having a size in bytes of 78,630 bytes, and created on April 9, 2025. The information contained in this computer readable form is hereby incorporated by reference in its entirety.FIELD OF INVENTION

[0003] This invention relates to methods of evaluating HLA mismatches between donors and recipients of allogeneic transplantation, predicting immune responses posttransplantation, and selecting and / or screening donor material with permissible mismatches for allogeneic transplantation.BACKGROUND

[0004] Despite the improvement in immunosuppression regimen, development of de novo donor specific antibody (dnDSA) and antibody mediated rejection (AMR) remain one of major obstacles for long term graft survival and patient survival in solid organ transplant.

[0005] The Major Histocompatibility complex (MHC) system is known as the human leukocyte antigen (HLA) in humans, which contains the most polymorphic gene cluster of the entire human genome. The immune system uses the HLAs to differentiate self cells and nonself cells. The HLA gene complex consists of three regions, and HLA molecules are categorized into three classes as: class I, class II, and class III based on the structure and function of gene products; and each region contains numerous loci (genes). The main function of HLA class I gene products (HLA- A, -B, and -C) is to present peptides from inside the cell to CD8+ T Cells (cytotoxic T cells). The class II coded molecules, HLA-DR, -DP, and -DQ, are primarily expressed on the surface of antigen-presenting cells like dendritic cells, macrophages, and B cells, and bind to and process exogenous peptides (from pathogens or other sources) for presentation to CD4+ T cells to stimulate multiplication of the CD4+T cells which in turn stimulate antibody-producing B-cells to produce antibodies against that specificantigen. Predicting which (fragments of) antigens will be presented to the immune system by a certain HLA type may be challenging. And the class III region contains genes which encode for immune regulatory molecules, e.g., tumor necrosis factor (TNF) and the complement system.

[0006] HLA class II molecules are heterodimers composed of an a chain and a P chain. As a whole, there are five isotypes of the class II HLA protein designated as HLA-DM, -DO, -DP, -DQ, -DR; wherein three are human HLA class II isotypes (HLA-DP, HLA-DQ, and HLA-DR), and HLA-DM and HLA-DO are non-classical HLA class II molecules. To classify them into their respective loci on the chromosome, there is a nomenclature of three letters for the genetic loci: the first (D) indicates the class, the second (M, O, P, Q, or R) the family, and the third (A or B) the chain (a or P respectively). For example, the protein - HLA class II histocompatibility antigen DQ beta 1 chain (DQB1) - has a UnitProt number of P01920 and is encoded by the gene HLA-DQB1.

[0007] Alloimmunity (e.g., the development of dnDSA) not only against HLA-DR but also and likely mostly against HLA-DQ plays a significant role. However, the contribution of dnDSA varies in clinical manifestation, as patients with dnDSA do not always develop AMR.

[0008] HLA genes are highly polymorphic. A transplant recipient and a donor may carry different HLA alleles, because HLA matching is not practical due to the medical emergency and limited number of donors. There is a long-standing need to stratify the risk of HLA mismatches between the recipient and the donor, in the hope of identifying “permissible” mismatches which are less likely to stimulate dnDSA and cause AMR. It also remains unclear what characteristics of HLA mismatches can stimulate robust allo-immune response, as not all mismatched epitopes can stimulate the same robust immune response.

[0009] Therefore, it is an object of the present disclosure to provide methods in assessing likelihood of developing dnDSA, and even AMR, in transplant recipients; thereby stratifying recipients and / or identifying “permissible” transplant for the recipients.

[0010] It is another object of the present disclosure to provide methods for selecting and transplanting organs, cells, or tissue preparation for allogeneic transplantation.

[0011] All publications herein are incorporated by reference to the same extent as if each individual publication or patent application was specifically and individually indicated to be incorporated by reference. The following description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.SUMMARY OF THE INVENTION

[0012] The following embodiments and aspects thereof are described and illustrated in conjunction with compositions and methods which are meant to be exemplary and illustrative, not limiting in scope.

[0013] Various embodiments provide methods for selecting an organ, a tissue preparation, or cells for allogeneic transplantation based on the presence and location of categorically mismatched amino acid(s) in the potential donor’s and potential recipient’s HLA- DQ proteins and the predicted binding strength between HLA-DQ and HLA-DR proteins between the potential donor and potential recipient. In various embodiments, the methods are computer-implemented methods. In various embodiments, the methods assess likelihood of an immune response after transplantation, such as T-cell-alloreactivity against human leukocyte antigens (HLA) that are mismatched between potential donors and recipients. In various embodiments, the methods guide selection of allograft for the allogeneic transplantation. In various embodiments, the methods further include performing the transplantation. In various embodiments, the methods identify likelihood of dnDSA development, and hence provide for desensitization therapy to the transplant recipient. In various embodiments, the methods identify likelihood of antibody -mediated rejection (AMR) development or existence, and hence provide for therapy to treat AMR to the transplant recipient.

[0014] In some embodiments, the methods include the steps of:(i) HLA-typing of samples obtained from multiple potential donors and from one or more recipients and / or providing HLA typing data from the multiple potential donors and from the one or more recipients, and generating, via a computer, a listing of mismatched HLA-DQB1 proteins between the multiple potential donors and the one or more recipients, wherein a mismatched donor- or recipient-specific HLA-DQB1 allele has at least one amino acid mismatched with both alleles of a recipient- or donor-specific HLA-DQB1, respectively; (preferably, the HLA-typing and the listing of mismatched HLA-DQB1 include extracellular domain 1 and / or extracellular domain 2 of an HLA-DQB1);(ii) determining two or more core peptides and respective rank scores for each pair of the multiple potential donors and the one or more recipients, wherein the core peptides are each a donor- or recipient-specific HLA-DQB1 -derived peptide (or, also referred to as, peptidic fragment of HLA-DQB1 protein) which is predicted to bind in direct contact with a recipi enter donor- HLA-DRB 1 protein, respectively, and wherein the rank scores are each a number correlated with a binding strength between respectively core peptide and the HLA-DRB 1 protein; in various aspect, rank scores and binding strengths are negatively correlated (e.g., ahigher rank score corresponds to a lower binding strength, and a lower rank score corresponds to a higher binding strength);(iii) determining for each pair of the multiple potential donors and the one or more recipients, a presence or absence of a categorically mismatched amino acid on an outer surface of the extracellular domain 1 of a mismatched HLA-DQB1 protein, and, if the outer surface of the extracellular domain 1 has a categorically mismatched amino acid present, also determining a presence or absence of a categorically mismatched amino acid in at least one of the core peptides at a residue position configured for interacting with a T cell receptor, wherein the categorically mismatched amino acid on the outer surface of the extracellular domain 1 of the mismatched HLA-DQB1 protein and the categorically mismatched amino acid in the core peptides at the residue positions configured for interacting with the T cell receptor are, each, amino acid residues of the donor-specific HLA-DQB1 protein and of the recipient-specific HLA-DQB1 protein belonging to different categorical groups of amino acids, said different categorical groups being two or more selected from a nonpolar group, a polar group, a basic group, and an acidic group, (see Table 1 for amino acid residues in different categorical groups); and(iv) recording for each pair of the multiple potential donors and the one or more recipients: a rank score correlated with a greatest one of the binding strength out of the two or more core peptides determined from step (ii) as a recorded rank score for the mismatched HLA-DQB1 allele when step (iii) determines that the categorically mismatched amino acid is present on the outer surface of the extracellular domain 1 and that that the categorically mismatched amino acid is present in the core peptides at the residue position configured for interacting with the T cell receptor, recording a user-selected number that indicates none, substantially none, or a least one of the binding strength as a recorded rank score for the mismatched HLA-DQB1 allele when step (iii) determines that the categorically mismatched amino acid is absent on the outer surface of the extracellular domain 1 or step (iii) determines that the categorically mismatched amino acid is absent in the two or more core peptides at the residue positions configured for interacting with the T cell receptor; and selecting an organ, a tissue preparation, or cells from a donor having a recorded rank score that is correlated with a binding strength below a reference binding-strength amount for the allogenic transplantation in a recipient of the pair for which the recorded rank score is performed, (e.g., the reference binding-strength amount, also called the ‘reference amount’ inthis context, is greater than the none, substantially none, or least one of the binding strength from step (ii)), or determining that an organ, a tissue preparation, or cells from a donor having a recorded rank score that is correlated with a binding strength equal to or greater than the reference binding-strength amount as inappropriate for the allogeneic transplantation or as likely to develop de novo donor specific antibody after the allogeneic transplantation in the recipient from the pair.

[0015] In some embodiments, the methods further include step (v): repeating steps (i) through (iv) for a different allele of the HLA subtype. Typically, a higher binding strength (or its correlated rank score) out of the two alleles is selected.

[0016] In some embodiments, the methods further include transplanting into the recipient the organ, the tissue preparation, or the cells of the donor recorded with the recorded rank score correlated with the binding strength below the reference binding-strength amount.

[0017] In some embodiments, the reference binding-strength amount is top 1% of binding strengths for HLA-DQ in a distribution from a plurality of random natural peptides. In some embodiment, the reference binding-strength amount is at the 1stpercentile (from high to low). Alternatively speaking, the reference binding-strength amount and above is the top 1%, or within the top 1%.

[0018] In various aspects, the core peptide is 9 amino acids in length, and the residue position configured for interacting with the T cell receptor comprises positions 2, 3, 5, 7, and / or 8 (also referred to as P2, P3, P5, P7, P8) from N- to C- terminus of the core peptide.

[0019] The transplantation referred to herein may include any type of organ, tissue preparation, or cells. In some embodiments, the transplantation includes heart, heart tissue, or heart cell transplantation. In some embodiments, the transplantation include kidney, kidney tissue, or kidney cell transplantation. In some embodiments, the transplantation is a heart transplant. In some embodiments, the transplantation is a kidney transplant.

[0020] In some embodiments, the methods further assess transplantation outcome such as de novo donor-specific HLA antibodies (dnDSA) development, antibody-mediated rejection of the transplant, patient survival, disease free survival, and / or transplant-related mortality. In some embodiments, the methods assess likelihood of developing dnDSA.

[0021] In some embodiments, the immune response assessed by the methods include an antibody-mediated response; a graft versus host disease (GVHD); and / or de novo development of donor specific HLA IgG antibodies after the transplantation.

[0022] In some embodiments, the HLA typing is carried out with sequence-based typing, and / or comprises serological and / or molecular typing.

[0023] In some embodiments, the methods include selecting the donor with the recorded rank score that is correlated with a least amount of the binding strength below the reference binding-strength amount for the allogenic transplantation, and / or thereby determining alloreactivity between multiple donors.

[0024] In some embodiments, the methods further include abstaining from transplanting in the recipient the organ, tissue preparation or cells having a recorded rank score that is correlated with the binding strength equal to or greater than the reference bindingstrength amount. In some embodiments, the methods further include administering a desensitization therapy to the recipient who receives transplant of the organ, tissue preparation or cells having the recorded rank score that is correlated with the binding strength equal to or greater than the reference binding-strength amount.

[0025] Various embodiments provide a method for identification of a solid organ transplantation material having an HLA mismatch likely to elicit de novo donor-specific HLA antibodies (dnDSA) development in a recipient and / or for identification of impermissible HLA mismatches for solid organ transplantation in the recipient, and the method includes: carrying out a computer-implemented method comprising:(i) HLA-typing of samples obtained from multiple potential donors and from one or more recipients and / or providing HLA typing data from the multiple potential donors and from the one or more recipients, wherein the HLA-typing is carried out on an HLA subtype comprising extracellular domain 1 and / or extracellular domain 2 of an HLA-DQB1, and generating, via a computer, a listing of mismatched HLA-DQB1 proteins in the extracellular domain 1 and / or the extracellular domain 2 between the multiple potential donors and the one or more recipients, wherein a mismatched donor- or recipient-specific HLA-DQB1 allele has at least one amino acid mismatched with both alleles of a recipient- or donor-specific HLA- DQB1, respectively;(ii) determining two or more core peptides for each pair of the multiple potential donors and the one or more recipients, wherein the two or more core peptides are each a donor- or recipient-specific HLA-DQB1 peptide fragment, which is predicted to bind in direct contact with a recipient- or donor- HLA-DRB1 protein, respectively, said predicted presentation being determined based on a binding strength for binding between each of the core peptides and the HLA-DRB1 protein; and(iii) determining for each pair of the multiple potential donors and the one or more recipients, a presence or absence of a categorically mismatched amino acid on an outer surface of the extracellular domain 1 of a mismatched HLA-DQB1 protein, and a presence or absence of a categorically mismatched amino acid in the core peptide at a residue position configured for interacting with a T cell receptor, wherein the categorically mismatched amino acid on the outer surface of the extracellular domain 1 of the mismatched HLA-DQB1 protein and the categorically mismatched amino acid in the core peptides at the residue positions configured for interacting with the T cell receptor are each amino acid residues of the donor-specific HLA- DQB1 protein and of the recipient-specific HLA-DQB1 protein belonging to different categorical groups of amino acids, said different categorical groups being two or more selected from a nonpolar group, a polar group, a basic group, and an acidic group, wherein the solid organ transplantation material is identified as likely to elicit the dnDSA development in the recipient and / or as impermissible for the transplantation in the recipient when the categorically mismatched amino acid is present on the outer surface of the extracellular domain 1 of the mismatched HLA-DQB1 protein, and the categorically mismatched amino acid is present in at least one of the core peptides at the residue position configured for interacting with the T cell receptor, AND a binding strength between the at least one of the core peptide peptides and the recipient- or donor- HLA-DRB1 protein, respectively, is equal to or greater than a reference binding-strength amount, or wherein the solid organ transplantation material is identified as unlikely to elicit the dnDSA development in the recipient and / or as permissible for the transplantation in the recipient when the categorically mismatched amino acid is absent on the outer surface of the extracellular domain 1 of the mismatched HLA-DQB1 protein, or when the categorically mismatched amino acid is absent in at least one of the core peptides at the residue position configured for interacting with the T cell receptor, or a binding strength between the at least one of the core peptide peptides and the recipient- or donor- HLA-DRB1 protein, respectively, is less than, preferably at least 100%, 200%, or 300% less than, the reference binding-strength amount.

[0026] In some embodiments, the binding strength is quantified as a rank score which normalizes a prediction score by comparing the prediction score to predictions for a set of random peptides, wherein the prediction score indicates likelihood of the core peptide to be presented by the HLA-DRB1 protein. In various aspects, the rank score (correlated with the binding strength) is calculated / determined via NetMHCIIpan method / algorithm.

[0027] Various embodiments provide an ex vivo method of assessing likelihood of developing or having antibody -mediated rejection (AMR) in a recipient of a solid-organallograft transplantation, wherein the recipient is positive for DQ de novo donor-specific antibody (dnDSA) after the transplantation, and the method includes: carrying out a computer-implemented method comprising:(i) HLA-typing of a sample of the allograft or from a donor of the allograft and a sample from the recipient, wherein the HLA-typing is carried out on an HLA subtype comprising extracellular domain 1 and / or extracellular domain 2 of an HLA-DQB1, and generating a listing of a mismatched HLA-DQB1 protein in the extracellular domain 1 and / or the extracellular domain 2 between the allograft or the donor and the recipient, wherein a mismatched donor-specific HLA-DQB1 allele has at least one amino acid mismatched with both alleles of a recipient-specific HLA-DQB1;(ii) determining, via the computer, two or more core peptides, wherein the two or more core peptides are each a donor-specific HLA-DQB1 -derived peptides from the mismatched HLA-DQB1 protein, which is predicted to bind in direct contact with a recipient HLA-DRB1 protein, said predicted presentation being determined by determining a binding strength between each of the core peptides and the HLA-DRB 1 protein; and(iii) determining, via the computer, a presence or absence of a categorically mismatched amino acid on an outer surface of the extracellular domain 1 of the mismatched HLA-DQB1 protein, and a presence or absence of a categorically mismatched amino acid in at least one of the core peptides at a residue position configured for interacting with a T cell receptor, wherein the categorically mismatched amino acid on the outer surface of the extracellular domain 1 of the mismatched HLA-DQB1 protein and the categorically mismatched amino acid in the at least one of the core peptides at the residue position configured for interacting with the T cell receptor are, each, amino acid residues of the donor-specific HLA-DQB1 protein and of the recipient-specific HLA-DQB1 protein belonging to different categorical groups of amino acids, said different categorical groups being two or more selected from a nonpolar group, a polar group, a basic group, and an acidic group, wherein the recipient is indicated as likely to develop or as having the AMR when the categorically mismatched amino acid is present on the outer surface of the extracellular domain 1 of the mismatched HLA-DQB1 protein, the categorically mismatched amino acid is present in the at least one of the core peptides at the residue position configured for interacting with the T cell receptor, AND a binding strength between the at least one of the core peptide peptides and the recipient- HLA-DRB 1 protein is equal to or greater than a reference bindingstrength amount, andwherein the recipient is indicated as unlikely to develop or as free from the AMR when the categorically mismatched amino acid is absent on the outer surface of the extracellular domain 1 of the mismatched HLA-DQB 1 protein, the categorically mismatched amino acid is absent in the at least one of the core peptides at the residue position configured for interacting with the T cell receptor, OR the binding strength between the at least one of the core peptide peptides and the recipient- HLA-DRB1 protein is less than the reference binding-strength amount.

[0028] In some embodiments, the reference binding-strength amount or greater is top 1% of binding strengths for HLA-DQ in a distribution from a plurality of random natural peptides. In some embodiments, the reference binding-strength amount is at the 1stpercentile from high to low of binding strengths. In other embodiments, the reference binding-strength amount is at the 2nd, 3rd, 4th, 5th, 6th, 7th, 8th, 9th, 10th, 11th, 12th, 13th, 14th, 15th, 16th, 17th, 18th, 19th, or 20thpercentile from high-to-low of binding strengths.

[0029] In some embodiments, the recipient is positive for DQB1 dnDSA. In some embodiments, the recipient is positive for dnDSA against DQB1 and DQA1.

[0030] Additional embodiments provide a method for treating a solid-organ allograft recipient indicated as likely to develop or having antibody -mediated rejection as determined above, and the method includes administering to the recipient an effective amount of a therapy comprising an anti-IL-6 antibody, an anti-IL-6R antibody, a Cl esterase inhibitor, eculizumab, an anti-CD20 antibody, daratumumab, a protease inhibitor, a corticosteroid, tacrolimus, mycophenolate mofetil, sirolimus, anti-thymocyte globulin, intravenous immunoglobulin, plasmapheresis, or a combination thereof.

[0031] Additional embodiments provide a method for treating a recipient of a solidorgan transplantation material likely to elicit dnDSA in the recipient, which includes: administering to the recipient an effective amount of a desensitization therapy such as plasmapheresis, intravenous immunoglobulin, rituximab, eculizumab, an anti-IL-6 antibody, an anti-IL-6R antibody, antithymocyte globulin, or a combination thereof.

[0032] Other features and advantages of the invention will become apparent from the following detailed description, taken in conjunction with the accompanying drawings, which illustrate, by way of example, various features of embodiments of the invention.BRIEF DESCRIPTION OF THE FIGURES

[0033] Exemplary embodiments are illustrated in referenced figures. It is intended that the embodiments and figures disclosed herein are to be considered illustrative rather than restrictive.

[0034] Figure 1A. The model of evaluation of categorical amino acid mismatched epitopes. If a mismatched HLA-DQB1 donor allele did not have a categorical amino acid mismatched residue in the surface position of the extracellular domain 1, we would assign a %Rank score of 99 for this allele. Otherwise, the presentation of donor-derived core peptides by the recipient’ s DRB 1 was predicted by the program NetMHCIIpan EL. Amino acid residues were assigned into 4 categories (nonpolar, polar, acidic, and basic). Only donor core peptides that had amino acid residues in different categories from the recipient at positions 2, 3, 5, 7, and 8, were considered categorically mismatched. For example, amino acid residue glutamic acid (E) at position 3 of the core peptide belonged to the polar category, and the corresponding recipient residue alanine (A) belonged to the nonpolar category. Thus, they were categorically mismatched. The NetMHCIIpan EL program generated a %Rank score for each core peptide. The lowest %Rank score of all core peptides from 1 donor allele was assigned as the %Rank score for this allele.

[0035] Figure IB. Alignment of the extracellular domains 1 and 2 of mature proteins of an exemplary donor DQBl*03:01 (SEQ ID NO:81) and recipient DQBl*05:01 (SEQ ID NO: 82) and 06:02 (SEQ ID NO: 83) in Example 1-1.

[0036] Figure 1C. 3-D structure of DQBl*03:01( / DQAl*02:01). Blue: alpha chain (DQAl*02:01). Violet: beta chain (DQBl*03:01). Green: a peptide presented by donor HLA. The categorically mismatched amino acid residue 45E, shown in red, is exposed on the protein surface.

[0037] Figure ID. DQ dnDSA are developed earlier in recipients with %Rank < 1 than that with %Rank > 1 in a validation cohort.

[0038] Figure 2. Donor HLA-DQ alleles targeted by dnDSA had lower %Rank scores compared with non-targeted alleles in individuals. Each line represents 1 recipient. dnDSA, de novo donor-specific antibodies.

[0039] Figures 3A-3C. %Rank score <1 predicts the development of DQ dnDSA in heart transplant recipients. (3 A) Recipients were divided into 4 groups based on %Rank scores. The red, turquoise, pink, and green lines represent recipients with %Rank score <1, recipients with 1 <%Rank score <2, recipients with 2 <%Rank score <5, and recipients with %Rank score >5, respectively. (3B) Recipients were divided into 2 groups. The red and blue lines represent recipients with a %Rank score <1 and recipients %Rank score >1, respectively. (3C) Recipients were divided into 2 groups based on the number of mismatched DQB1 PIRCHE epitopes. The black and red lines represent recipients with numbers of mismatched epitopes <median value21 and >21, respectively. AMR, antibody-mediated rejection; dnDSA, de novo donor-specific antibodies; PIRCHE, predicted indirectly recognizable HLA epitopes.

[0040] Figures 4A and 4B. The presence of dnDSA is associated with AMR in recipients with %Rank score < 1. (4A) Comparison of the freedom from AMR among four groups. The red, turquoise, pink, and green lines represent recipients with DQ dnDSA and %Rank score <1, recipients with DQ dnDSA and %Rank score >1, recipients without dnDSA but with %Rank score <1, and recipients who were dnDSA negative and had %Rank score >1, respectively. (4B) Comparison of the freedom from AMR between recipients who had dnDSA and %Rank score <1 (red line), and all other recipients who had dnDSA but %Rank score >1, or did not have dnDSA (blue line). AMR, antibody-mediated rejection; dnDSA, de novo donorspecific antibodies.

[0041] Figure 5. The MFI of DQ dnDSA in recipients with %Ranking score < 1 is not different from recipients with %Ranking Score >1.

[0042] Figure 6. Freedom from anti-DQ dnDSA in the heart transplant recipients in Example 1 according to HLA MatchMarker Epitope algorithm or according to PIRCHE algorithm. This is in contrast to Applicant’s method herein whose result is depicted in figure 3A or 3B.

[0043] Figure 7 depicts that about 3 quarters of dnDSA are against HLA-DQ antigens.DESCRIPTION OF THE INVENTION

[0044] All references cited herein are incorporated by reference in their entirety as though fully set forth. Unless defined otherwise, technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0045] One skilled in the art will recognize many methods and materials similar or equivalent to those described herein, which could be used in the practice of the present invention. Indeed, the present invention is in no way limited to the methods and materials described. For purposes of the present invention, the following terms are defined below.

[0046] “Allogeneic transplantation” or “allotransplantation” is the transplantation of cells, tissues, or organs, to a recipient from a genetically non-identical donor of the same species. The transplant is called an allograft, allogeneic transplant, or homograft. Most human tissue and organ transplants are allografts. Allografts can either be from a living donor or a deceased donor. In various embodiments, organs that can be transplanted are the heart, kidneys, liver, lungs, pancreas, intestine, and thymus. Tissues include bones, tendons (both referred toas musculoskeletal grafts), cornea, skin, heart valves, nerves and veins. In some embodiments, the allogeneic transplantation in one or more methods disclosed herein is heart transplantation.

[0047] The term “immune response” refers to a response from a part of the immune system to an antigen that occurs when the antigen is identified as foreign, which preferably subsequently induces the production of antibodies and / or lymphocytes capable of destroying or immobilizing the “foreign” antigen or making it harmless. In various embodiments, an immune response relates to a response of the immune system of the recipient against the transplanted material. In other embodiments, an immune response relates to one effected by cells of the transplanted organs, tissue or cells, whereby T cells of the transplanted material react against and / or attack recipient antigens or tissue.

[0048] The “human leukocyte antigen (HLA)” system is the major histocompatibility complex (MHC) in humans. The super locus contains a large number of genes related to immune system function in humans. This group of genes resides on chromosome 6, and encodes cell-surface antigen-presenting proteins and has many other functions. The proteins encoded by certain genes are also known as antigens, as a result of their historic discovery as factors in organ transplants. The major HLA antigens are essential elements for immune function. In various aspects, “HLA” refers to the human leukocyte antigen locus on chromosome 6p21, consisting of HLA genes (HLA- A, HLA-B, HLA-C, HLA-DRB1, HLA- DQB 1 , etc.) that are used to determine the degree of matching, for example, between a recipient and a donor of a tissue graft. “HLA allele” means a nucleotide sequence within a locus on one of the two parental chromosomes.

[0049] HLAs corresponding to MHC class I (A, B, and C) present peptides from inside the cell (including viral peptides if present). These peptides are produced from digested proteins that are broken down in the proteasomes. In general, these particular peptides are small polymers, about 9 amino acids in length. Foreign antigens attract killer T-cells (also called CD8 positive- or cytotoxic T-cells) that destroy cells. HLAs corresponding to MHC class II (DP, DM, DOA, DOB, DQ, and DR) present antigens from outside of the cell to T-lymphocytes. These particular antigens stimulate the multiplication of T-helper cells, which in turn stimulate antibody-producing B-cells to produce antibodies to that specific antigen. MHC loci are some of the most genetically variable coding loci in mammals, and so are the human HLA loci. Most HLA loci show a dozen or more allele-groups for each locus. Six loci have over 100 alleles that have been detected in the human population. Of these, the most variable are HLA-B and HLA-DRB1.

[0050] An “allele” is a variant of the nucleotide (DNA) sequence at a locus, such that each allele differs from all other alleles by at least one (single nucleotide polymorphism, SNP) position. Most of these changes result in a change in the amino acid sequences that result in slight to major functional differences in the protein.

[0051] A “core peptide” (also called “binding core”) refers to a minimal region of a peptide that is directly in contact with the MHC-II binding cleft, which is important for peptide- MHC-II interaction. In various aspects, ‘HLA-DQB1 -derived peptide’ is HLA-DQBl’s core peptide. Without wishing to be bound by a particular theory, MHC class II molecules present peptides to T helper lymphocytes, and these peptides are typically 12-25 amino acids long. In various embodiments, the binding core consists of a linear 9-mer (9 amino acids) that makes most of the interactions with the MHC-II binding site, with flanking residues extending on the N- and C-terminal parts of the binding core. In various embodiments, specific pockets within the MHC-II binding site accommodate residues at anchor positions (Pl, P4, P6, and P9) in the binding core. So, in various embodiments, residues for interacting with T cells (such as T cell receptor) are at other positions, i.e., P2, P3, P5, P7, and P8 in the binding core. In various embodiments, known techniques / tools such as NetMHCIIpan, NetMHCpan, MHCII3D, MMPred, PUFFIN, MixMHC2pred-1.216, NeonMHC215, MHCnuggets25, RPEMHC, CapHLA can predict peptide binding to MHC class II molecules and identify the binding core.

[0052] “HLA typing” means the identification of an HLA allele of a given locus (HLA-A, HLA-B, HLA-C, HLA-DRB1, HLA-DQB1, etc ). Gene sequencing may be applied. In preferable embodiments, ex vivo gene sequencing is applied in HLA typing. Samples may be obtained from blood or other body samples from donor and / or donor material and recipient, which may subsequently be analyzed. In general, the sequence of the antigens determines the antibody reactivities, and so having a good sequencing capability (or sequence-based typing) obviates the need for serological reactions. Sequencing approaches to HLA-typing are preferred. Sequencing may relate to techniques such as Maxam-Gilbert sequencing, Chaintermination methods, advanced methods and de novo sequencing such as shotgun sequencing orbridge PCR, or the so-called “next-generation” methods, such as massively parallel signature sequencing (MPSS), 454 pyrosequencing, Illumina (Solexa) sequencing, SOLID sequencing, or other similar methods.

[0053] In transplant medicine, mismatched donor HLA-DQ molecules can be processed and presented by recipient HLA-DR molecules, leading to allo-antigen presentation and potential humoral alloimmunity. When there’s a mismatch between donor and recipient HLA molecules, the recipient’s antigen-presenting cells (APCs) can internalize the donor HLAmolecules (including HLA-DQ). These donor HLA molecules are then processed into peptide fragments by the recipient's APCs. These peptides, derived from the donor HLA (including HLA-DQ), can be presented by the recipient’s HLA-DR molecules on the surface of the APCs. This presentation of donor-derived peptides by recipient HLA-DR molecules can lead to T-cell activation, specifically CD4+ T cells, which are important for humoral alloimmunity. This T-cell activation can then lead to the development of donor-specific antibodies (DS A), which can target the transplanted organ and cause rejection. Algorithms like PIRCHE-II are used to predict the number of mismatched HLA-derived peptides that can be presented by recipient HLA class II molecules, including HLA-DR. A software program, HLAMatchmaker, combines eplets (i.e., small polymorphic amino acid fragments) from both donor alleles into an “eplet universe,” compares it to the eplet universe of the recipient, and outputs the number of eplets present only in the donor antigens as the mismatch load. All these algorithms stratify the risk based on the number of mismatched epitopes or eplets, but not every mismatched epitope can stimulate the same robust immune response. The characteristics of HLA mismatching that can stimulate robust allo-immune responses remain unknown, before Applicant’s disclosure.

[0054] The term “sample” or “biological sample” as used herein denotes a sample taken or isolated from a biological organism.

[0055] The term “statistically significant” or “significantly” refers to statistical evidence that there is a difference. It is defined as the probability of making a decision to reject the null hypothesis when the null hypothesis is actually true. The decision is often made using the p-value.

[0056] A “subject,” “patient,” “individual,” “donor,” or “recipient” means a human or animal. In various embodiments, the subject, patient, or individual is a human. In various embodiments, a donor and a recipient are both a human.

[0057] The terms “treat,” “treatment,” “treating,” or “amelioration” refer to therapeutic treatments, wherein the object is to reverse, alleviate, ameliorate, inhibit, slow down or stop the progression or severity of a condition associated with, a disease or disorder. The term “treating” includes reducing or alleviating at least one adverse effect or symptom of a condition, disease or disorder, such as DS A development or antibody mediated rejection. Alternatively, treatment is “effective” if the progression of a disease is reduced or halted.

[0058] The term “administering,” refers to the placement an agent as disclosed herein into a subject by a method or route which results in at least partial localization of the agents at a desired site.

[0059] The term “antibody” refers to an intact immunoglobulin or to a monoclonal or polyclonal antigen-binding fragment with the Fc (crystallizable fragment) region or FcRn binding fragment of the Fc region, referred to herein as the “Fc fragment” or “Fc domain”. Antigen-binding fragments may be produced by recombinant DNA techniques or by enzymatic or chemical cleavage of intact antibodies. Antigen-binding fragments include, inter alia, Fab, Fab', F(ab')2, Fv, dAb, and complementarity determining region (CDR) fragments, singlechain antibodies (scFv), single domain antibodies, chimeric antibodies, diabodies and polypeptides that contain at least a portion of an immunoglobulin that is sufficient to confer specific antigen binding to the polypeptide. The Fc domain includes portions of two heavy chains contributing to two or three classes of the antibody. The Fc domain may be produced by recombinant DNA techniques or by enzymatic (e.g. papain cleavage) or via chemical cleavage of intact antibodies.

[0060] The term “antibody fragment,” as used herein, refer to a protein fragment that comprises only a portion of an intact antibody, generally including an antigen binding site of the intact antibody and thus retaining the ability to bind antigen.

[0061] “Transplant” in various embodiments includes an organ, tissue preparation, or cells from one or more organs such as kidney, heart, liver, lung, small bowel, pancreas or bone marrow. In some embodiments, the transplant comprises heart allograft or tissue preparation or cells therefrom. In some embodiments, the transplant is heart allograft. In some embodiments, the transplant comprises kidney allograft or tissue preparation or cells therefrom. In some embodiments, the transplant is kidney allograft.

[0062] Herein methods are provided to select and transplant an organ, tissue preparation, or cells, and / or to stratify the risk of development of dnDSA and antibody- mediated rejection (AMR) in transplant recipients, based on categorical amino acid mismatched epitope (CAME) to evaluate HLA-DQ mismatches. It has been shown before that the HLA-DRB1 gene is constitutively expressed, and expression of HLA-DR is higher than that of HLA-DQ and HLA-DP in mononuclear cells; and that in heart transplant patients, most dnDSA are against HLA-DQ. Herein new methods involve evaluating binding between recipient’s HLA-DRB1 and allo-peptides derived from mismatched donor HLA-DQB1 antigens and assessing locations of mismatched amino acids with regards to exposure on protein surface in extracellular domain 1 as well as presentation by recipient-specific HLA-DR to T cell receptor. Herein, inventor(s) look at four categories of amino acids based on chemical characteristics: nonpolar, polar, basic, and acidic; and postulate that only mismatched amino acids in different categories between the recipient and donor HLA may potentially effectivelystimulate production of donor specific antibodies, whereas mismatched amino acids belonging to the same category have inferior ability to trigger immune response. Furthermore, in various embodiments, the core peptide presented by HLA class II to T cell receptor (TCR) is a 9-mer. Most MHC class II molecules have four binding pockets occupied by amino acids 1, 4, 6, and 9 of the minimal peptide epitope, while the residues at positions 2, 3, 5, 7, and 8 are available to interact with the T cell receptor (TCR). Herein, it is conceived that only HLA amino acid residues mismatched in different categories of nonpolar, polar, basic, and acidic amino acids at positions 2, 3, 5, 7, and / or 8 of the core peptide may effectively stimulate donor HLA specific antibody production. Thus, inventor(s) have also demonstrated that transplant recipients having strong-binding categorical amino acid mismatched epitope (CAME) at the HLA-DQB1 locus are at higher risk of development of HLA-DQ dnDSA and AMR.

[0063] In various aspects of the algorithm / process provided herein, amino acid residues of HLA-DQ protein are categorized into 4 groups based on their chemical characteristics: nonpolar, polar, basic, and acidic. The likelihood of categorically mismatched HLA-DQ peptides presented by the recipient’s HLA-DRB1, also referred to as binding strength between the mismatched peptide and HLA-DRB1, is expressed as a normalized value, %Rank score. Categorical HLA-DQ mismatches were analyzed in 386 heart transplant recipients who were mismatched with their donors at the HLA-DQB1 locus. The inventor found that the presence of DQB1 mismatches with %Rank score <1 was associated with the development of dnDSA (P = 0.002). Furthermore, dnDSA increased the risk of AMR only in recipients who had DQ mismatches with %Rank score <1 (hazard ratio = 5.8), but the freedom from AMR was comparable between recipients with dnDSA and those without dnDSA if %Rank scores of DQ mismatching were >1. Therefore, HLA-DQ mismatches evaluated by the categorical amino acid mismatched epitope algorithm can stratify the risk of development of dnDSA and AMR in heart transplant recipients.

[0064] Various embodiments provide methods for selecting and / or screening donor material for allogeneic transplantation with acceptable mismatches based on a prediction of an immune response against human leukocyte antigens (HLA) after transplantation, and the methods include: carrying out a computer-implemented method comprising all or one or more of:(i) HLA-typing of samples obtained from one or multiple potential donors and from one or more recipients and / or providing HLA typing data from the one or multiple potential donors and from the one or more recipients, wherein the HLA-typing is preferably carried out on an HLA subtype comprising HLA-DQ, and more preferably HLA-DQB1,(ii) generating, e.g., via a computer, a listing of mismatched HLA-DQ (more preferably HLA-DQB1) proteins between the one or multiple potential donors and the one or more recipients, and in various embodiments a mismatched donor- or recipient-specific HLA- DQB1 allele has at least one amino acid mismatched with both alleles of a recipient- or donorspecific HL A-DQB1, respectively,(iii) determining, e.g., via the computer, for each donor-recipient pair of the one or more multiple potential donors and the one or more recipients a number of predicted core peptides - predicted to bind with and be presented by another HLA molecule - and corresponding rank numbers based on the binding affinity, elution profile, or both between the core peptides and the another HLA molecule, preferably wherein the core peptides are donor- or recipient-specific HLA-DQB1- derived peptides from a mismatched donor- or recipient- HLA-DQB1 protein, respectively, and are predicted, by the computer, to be presented by a recipient- or donor- HLA-DRB1 protein, respectively, said predicted presentation being determined by the computer by determining binding strength for binding between the core peptides and the HLA-DRB1 protein, and preferably wherein the rank numbers are based on the binding strength, wherein the rank numbers are smaller with a higher binding strength for binding between the core peptides and the HL A-DRB 1 protein, and(iv) determining, e.g., via the computer, for each donor-recipient pair of the one or multiple potential donors and the one or more recipients, a presence or absence of categorically mismatched amino acid(s) on an outer surface of extracellular domain 1 in a predicted structure of a mismatched HLA-DQ (preferably HLA-DQB1) protein, and a presence or absence of categorically mismatched amino acid(s) in the predicted core peptide at residue positions configured for interacting with a T cell receptor, wherein the categorically mismatched amino acid(s) are amino acid residue(s) of the donor-specific HLA-DQB1 protein and of the recipient-specific HLA-DQB1 protein being derived from or selected from different categorical groups of amino acids, said different categorical groups being a nonpolar group, a polar group, a basic group, and an acidic group according to Table 1.

[0065] Table 1. Four categorical groups of amino acids

[0066] Some embodiments of the computer-implemented methods further include:(v) recording the smallest rank number determined for each donor-recipient pair in step (iii) above as a rank score for the mismatched HLA-DQB1 allele if the categorically mismatched amino acid(s) are determined in step (iv) as present on the outer surface of the extracellular domain 1 and present in the predicted core peptide at the residue positions configured for interacting with the T cell receptor, or recording a user-determined high number as the rank score if the categorically mismatched amino acid(s) are determined as absent on the outer surface of the extracellular domain 1, said user-determined high number being greater than the rank numbers determined from step (iii);

[0067] In various embodiments, methods for selecting and / or screening donor material for allogeneic transplantation with acceptable mismatches include: selecting the organ, the tissue preparation, or the cells for the allogenic transplantation from a donor of the one or multiple potential donors recorded with the highest rank score, or having the lowest binding strength between the mismatched HLA-DQB1 protein and the HLR- DR protein, from the computer-implemented methods above, and transplanting the organ, the tissue preparation, or the cells of the donor with the highest rank score into the one or more recipients.

[0068] Various embodiments provide a method for assessing an organ, a tissue preparation, or cells for allogeneic transplantation, wherein the method includes:(i) HLA-typing of samples obtained from multiple potential donors and from one or more recipients and / or providing HLA typing data from the multiple potential donors and from the one or more recipients, wherein the HLA-typing is carried out on an HLA subtype comprising extracellular domain 1 and / or extracellular domain 2 of an HLA-DQB1, and generating a listing of mismatched HLA-DQB1 proteins in the extracellular domain 1 and / or the extracellular domain 2 between the multiple potential donors and the one or more recipients, wherein a mismatched donor- or recipient-specific HLA-DQB1 allele has at least one amino acid mismatched with both alleles of a recipient- or donor-specific HLA-DQB1, respectively;(ii) determining one or more core peptides and respective binding strength for each pair of the multiple potential donors and the one or more recipients, wherein the core peptides are regions of a mismatched donor- or recipientspecific HLA-DQB 1 protein capable of being in direct contact with a recipient- or donor- HLA-DRB1 protein binding cleft, respectively, for presentation to T cells, and wherein the binding strength is for binding between respective core peptide and the HL A-DRB 1 protein; and(iii) determining for each pair of the multiple potential donors and the one or more recipients, a presence or absence of a categorically mismatched amino acid on an outer surface of the extracellular domain 1 of the mismatched HLA-DQB 1 protein, and optionally a presence or absence of a categorically mismatched amino acid in at least one of the core peptides at a residue position configured for interacting with the T cell, wherein the categorically mismatched amino acid on the outer surface of the extracellular domain 1 of the mismatched HLA-DQB 1 protein and the categorically mismatched amino acid in the core peptides at the residue positions configured for interacting with the T cell are amino acid residues belonging to different categorical groups per Table 1; and(iv) recording for each pair of the multiple potential donors and the one or more recipients: a rank score that corresponds to a greatest one of the binding strength out of the rank scores corresponding to the one or more core peptides determined from step (ii) as a rank score for the mismatched HLA-DQB 1 allele, when step (iii) determines that the categorically mismatched amino acid is present on the outer surface of the extracellular domain 1 and that if determined the categorically mismatched amino acid is present in the core peptides at the residue position configured for interacting with the T cell receptor, and a user-selected number that indicates none or substantially none binding between the mismatched HLA-DQB 1 and the HLA-DRB1 as a rank score for the mismatched HLA-DQB 1 allele when step (iii) determines that the categorically mismatched amino acid is absent from the outer surface of the extracellular domain 1and selecting an organ, a tissue preparation, or cells from a donor recorded with a rank score that corresponds to below a reference amount, or determining that an organ, a tissue preparation, or cells from a donor that is recorded with a rank score that corresponds to the reference amount or above as inappropriate for the allogeneic transplantation or as likely to elicit de novo donor specific antibody development after the allogeneic transplantation in the recipient from the pair.

[0069] In various embodiments, the reference amount of the binding strength is top 1% of binding strengths for HLA-DQ in a distribution from a plurality of random natural peptides. In various embodiments, a target rank score, or associated target binding strength, suitable for allogeneic transplantation (for being unlikely to elicit dnDSA development) is one that is not within top 1% in the distribution.

[0070] In various embodiments, the reference amount %rank score as determined via NetMHCIIpan is 1. In other embodiments, the reference amount %rank score as determined via NetMHCIIpan is 2.

[0071] In various embodiments, the method selects the donor with a rank score that corresponds to the least amount of the binding strength below the reference amount for the allogenic transplantation.

[0072] Various embodiments provide methods for identifying HLA mismatches likely to develop de novo donor-specific HLA antibodies (dnDSA) and antibody-mediated rejection (AMR) of an allograft in a recipient, and the methods include carrying out a computer- implemented method above including steps (i)-(iv), wherein the solid organ transplantation material is identified as impermissible and / or likely to develop dnDSA and AMR when the categorically mismatched amino acid(s) are determined in step (iv) as present on the outer surface of the extracellular domain 1 of HLA-DQB1 and present in the predicted core peptide at the residue positions configured for interacting with the T cell receptor, AND when the smallest rank number determined in step (iii) is within top 1% compared to a distribution of rank numbers for HLA-DQ estimated from a plurality of random natural peptides, or the smallest rank number (%) is <1.

[0073] Some embodiments provide a method for identifying a solid organ transplantation material having an HLA mismatch likely to elicit de novo donor-specific HLA antibodies (dnDSA) development in a recipient. Some embodiments provide a method for identifying impermissible HLA mismatches for solid organ transplantation in the recipient. In these embodiments, the method includes:(i) HLA-typing of samples obtained from multiple potential donors and from one or more recipients and / or providing HLA typing data from the multiple potential donors and from the one or more recipients, wherein the HLA-typing is carried out on an HLA subtype comprising extracellular domain 1 and / or extracellular domain 2 of an HLA-DQB1, and generating a listing of mismatched HLA-DQB1 proteins in the extracellular domain 1 and / or the extracellular domain 2 between the multiple potential donors and the one or more recipients, wherein a mismatched donor- or recipient-specific HLA-DQB1 allele has at least one amino acid mismatched with both alleles of a recipient- or donor-specific HLA-DQB1, respectively;(ii) determining one or more core peptides and respective binding strength for each pair of the multiple potential donors and the one or more recipients, wherein the core peptides are regions of a mismatched donor- or recipient-specific HLA-DQB1 protein capable of being in direct contact with a recipient- or donor- HLA-DRB1 protein binding cleft, respectively, for presentation to T cells, and wherein the binding strength is for binding between respective core peptide and the HLA-DRB1 protein; and(iii) determining for each pair of the multiple potential donors and the one or more recipients, a presence or absence of a categorically mismatched amino acid on an outer surface of the extracellular domain 1 of the mismatched HLA-DQB 1 protein, and a presence or absence of a categorically mismatched amino acid in at least one of the core peptides at a residue position configured for interacting with the T cell, wherein the categorically mismatched amino acid on the outer surface of the extracellular domain 1 of the mismatched HLA-DQB 1 protein and the categorically mismatched amino acid in the core peptides at the residue positions configured for interacting with the T cell are amino acid residues belonging to different categorical groups per Table 1; wherein the solid organ transplantation material is identified as likely to elicit the dnDSA development in the recipient and / or as impermissible for the transplantation in the recipient when the categorically mismatched amino acid is present on the outer surface of the extracellular domain 1 of the mismatched HLA-DQB 1 protein, the categorically mismatched amino acid is present in at least one of the core peptides at the residue position configured for interacting with the T cell receptor, AND a binding strength between the at least one of the core peptide peptides and the recipient- or donor- HLA-DRB1 protein, respectively, is equal to or greater than a reference amount.

[0074] In various embodiments, the equality to or greater than the reference amount is top 1% in a distribution from a plurality of random natural peptides. In some embodiments, the plurality of random natural peptides is at least 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 150, 200, 250, 300, 400, 500, 600, 700, 800, 900, or 1,000 peptides.

[0075] In various aspects, one or more of all of the HLA-typing, the generating of mismatched HLA-DQB1 proteins, and multiple determination steps are performed via a computer.

[0076] Further embodiments provide an ex vivo method of assessing likelihood of developing or having antibody -mediated rejection (AMR) in a recipient of a solid-organ allograft transplantation, wherein the recipient is positive for DQ de novo donor-specific antibody (dnDSA) after the transplantation, and the method includes:(i) HLA-typing of a sample of the allograft or from a donor of the allograft and a sample from the recipient, wherein the HLA-typing is carried out on an HLA subtype comprising extracellular domain 1 and / or extracellular domain 2 of an HLA-DQB1, and generating, via a computer, a listing of a mismatched HLA-DQB1 protein in the extracellular domain 1 and / or the extracellular domain 2 between the allograft or the donor and the recipient, wherein a mismatched donor-specific HLA-DQB1 allele has at least one amino acid mismatched with both alleles of a recipient-specific HLA-DQB1;(ii) determining, via the computer, one or more core peptides, wherein the core peptides are donor-specific HLA-DQB1 -derived peptides from the mismatched HLA-DQB1 protein, and the core peptides are predicted, by the computer, to be presented by a recipient HLA-DRB1 protein, said predicted presentation being determined by the computer by determining a binding strength between each of the core peptides and the HLA-DRB1 protein; and(iii) determining, via the computer, a presence or absence of a categorically mismatched amino acid on an outer surface of the extracellular domain 1 of the mismatched HLA-DQB1 protein, and a presence or absence of a categorically mismatched amino acid in at least one of the core peptides at a residue position configured for interacting with a T cell receptor, wherein the categorically mismatched amino acid on the outer surface of the extracellular domain 1 of the mismatched HLA-DQB1 protein and the categorically mismatched amino acid in the at least one of the core peptides at the residue position configured for interacting with the T cell receptor are amino acid residues belonging to different categorical groups of amino acids per Table 1,wherein the recipient is indicated as likely to develop or as having the AMR when the categorically mismatched amino acid is present on the outer surface of the extracellular domain 1 of the mismatched HLA-DQB1 protein, the categorically mismatched amino acid is present in the at least one of the core peptides at the residue position configured for interacting with the T cell receptor, AND a binding strength between the at least one of the core peptide peptides and the recipient- HLA-DRB1 protein is equal to or greater than a reference amount, and wherein the recipient is indicated as unlikely to develop or as free from the AMR when the categorically mismatched amino acid is absent on the outer surface of the extracellular domain 1 of the mismatched HLA-DQB1 protein, the categorically mismatched amino acid is absent in the at least one of the core peptides at the residue position configured for interacting with the T cell receptor, OR the binding strength between the at least one of the core peptide peptides and the recipient- HLA-DRB1 protein is less than a reference amount.

[0077] Various embodiments provide methods for selecting an organ, a tissue preparation, or cells with impermissible HLA mismatches for allogeneic transplantation and / or HLA mismatches likely to develop de novo donor-specific HLA antibodies (dnDSA) and antibody-mediated rejection (AMR) thereof in one or more recipients, wherein the methods include carrying out a computer-implemented method above including steps (i)-(iv), wherein the organ, tissue preparation, or cells are identified as impermissible and / or likely to develop dnDSA and AMR when the categorically mismatched amino acid(s) are determined in step (iv) as present on the outer surface of the extracellular domain 1 of HLA-DQB1 and present in the predicted core peptide at the residue positions configured for interacting with the T cell receptor, AND when the smallest rank number determined in step (iii) is within top / % compared to a distribution of rank numbers for HLA-DQ estimated from a plurality of random natural peptides, or the smallest rank number (%) is <1.

[0078] In various embodiments, amino acid residues of the HLA-DQ protein are categorized into four groups and the likelihood of categorical mismatched peptides presented by HLA-DRB1 (e.g., donor HLA-DQ derived allopeptide to be presented by recipient’s HLA- DRB1) are ranked. In various embodiments, transplant recipients having the DQB1 mismatches with %Ranking score <1 is associated with developing dnDSA. In further embodiments, dnDSA increases the risk of developing antibody-mediated rejection (AMR) only in recipients who have DQ mismatches with Ranking score < 1 (hazard ratio= 5.8), whereas recipients with dnDSA having Ranking scores of DQ mismatches being > 1 aresimilarly free from developing AMR compared to recipients who do not have or are undetected with dnDSA.

[0079] Existing algorithms to evaluate the risk of mismatches include: Eplet mismatching using HLAMatchmaker (Duquesnoy et al., Hum Immunol. 2007 Jan;68(l): 12- 25), T cell epitope mismatch by Predicted Indirectly Recognizable HLA Epitopes (PIRCHE) (Otten et al., Hum Immunol. 2013 Mar;74(3):290-6), HLA epitope mismatch algorithm (HLA- EMMA) (Kramer et al., HLA. 2020 Jul; 96(1): 43-51.), and SnowFlake (Niemann et al., Front Immunol. 2022 Jul 29: 13:937587). While HLAMatchmaker, HLA-EMMA and SnowFlake algorithms scan mismatched amino acid residues of HLA that can be potentially recognized by antibodies, these three algorithms do not consider the contributions of T help cells in B cell maturation and antibody production. The PIRCHE algorithm seems to evaluate mismatched peptides which can be presented efficiently to the T cell receptor (TCR) of T cells. All the current algorithms stratify the risk based on the numbers of mismatched epitopes or eplets, but recent discoveries showed that not all mismatched epitopes can stimulate the same robust immune response. Therefore, the computer-implemented methods described herein provide an improvement in immune response evaluation / prediction based on categorically mismatched amino acids and their locations relative to core peptide predicted to be presented by another HLA molecule and locations relative to extracellular domain 1 of the whole HLA-DQ protein.

[0080] Typically binding of peptides (such as allopeptide) to HLA molecules can be predictable. The differences between predicted binding affinities and experimental measurements have been shown to be as small as the differences in measurements between different laboratories. Peptides of different lengths can bind to HLA class II molecules using different positions as anchor residues. Nielsen et al. used a core predictor to estimate how a peptide positions in the class II binding groove, which allowed for the development of an accurate HLA class-II predictor, called NetMHCII (BMC. Bioinformatics. 2007; 8: 238; BMC. Bioinformatics. 2009; 10: 296). This program can predict the binding of a peptide to MHC alleles, and is used in various embodiments in the computer-implemented methods described herein. Strong binding alleles and weak binding alleles in each major MHC allele group (DR, DQ, and DP) can be tallied separately. The number of peptides of a specific length within the sequence (e.g., a ‘core’ peptide that can be nine residues long) that are immunogenic can also be tallied.

[0081] Specifically, MHC binding prediction tools can be trained on binding affinity (BA) data, mass spectrometry-eluted ligands (EL) data, or an integration of both data types to boost predictive performances. Reynisson et al. described NetMHCpan-4.1 and NetMHCIIpan-4.0, two web servers created to predict binding between peptides and MHC-I and MHC-II, respectively, which exploit tailored machine learning strategies to integrate different training data types (Nucleic Acids Research, 2020, Vol. 48, W449-W454). Both NetMHCpan methods inform if a sequence is a strong MHC binder (SB) or a weak MHC binder (WB) based on a %Rank score. Briefly, %Rank is a transformation that normalizes prediction scores across different MHC molecules and permits interspecific MHC binding prediction comparisons. %Rank of a query sequence is computed by comparing its prediction score to a distribution of prediction scores for the MHC in question, estimated from a set of random natural peptides. Given this, for example, a %Rank value of 1% means that a queried sequence obtains a prediction score that corresponds to the top 1% scores obtained from random natural peptides.

[0082] In some embodiments, HLA typing is carried out on HLA-A, -B, -C, -DRB1 and -DQB1. In some embodiments, HLA typing includes serological and / or molecular typing. In a preferred embodiment, HLA typing is carried out at high resolution level with sequencebased typing, such as through sequence-specific oligonucleotide (SSO) primed PCR and / or next generation sequencing. In some embodiments, the HLA typing includes sequencing of one or more of exon 1-6 for HLA class II alleles.

[0083] In some embodiments, methods for prediction of therapeutic outcome of a transplantation are provided, which includes performing one or more computer-implemented methods described herein. In various aspects, the therapeutic outcome includes but is not limited to de novo development of HLA antibodies, development of antibody-mediated rejection or immune response, patient survival, disease free survival, and / or transplant-related mortality.

[0084] In various embodiments, a donor material for allogeneic transplantation in one or more methods disclosed herein originates from a donor with an HLA-DQ mismatch. In further embodiments, the donor material originates from a donor with an HLA-DQ mismatch that includes categorically mismatched amino acids. In some embodiments, a donor material for allogeneic transplantation in one or more methods disclosed herein originates from a donor with one allelic match. In some embodiments, a donor material for allogeneic transplantation in one or more methods disclosed herein originates from a donor with no allelic match.

[0085] In various embodiments, methods, preferably computer implemented methods, are provided that determines which donor is suited for transplantation when a completely matched donor is not available, without the need for laborious compatibility assays. The present invention for example is applicable to multiple transplant settings, such as solid organ, stem cells, or cord blood cells transplantation, amongst others. Essentially any transplantation, inwhich HLA-matching plays a role in determining alloreactivity or tissue rejection after transplantation, is encompassed by the present invention.

[0086] Additional embodiments provide a method for treating a transplant recipient indicated as likely to develop or having antibody-mediated rejection to one or more assessment or identification methods disclosed herein, which includes administering to the transplant recipient a therapy for treating or preventing antibody-mediated rejection. Exemplary therapy for treating or preventing antibody-mediated rejection includes an IL-6 inhibitor (e.g., anti-IL- 6 antibody, an anti-IL-6R antibody), a Cl esterase inhibitor, eculizumab, an anti-CD20 antibody, daratumumab, a corticosteroid, tacrolimus, mycophenolate mofetil, sirolimus, antithymocyte globulin, intravenous immunoglobulin, plasmapheresis, or a combination thereof.

[0087] Additional embodiments provide a method for treating a recipient of a transplant likely to elicit dnDSA in the recipient as identified by one or more assessment or identification methods disclosed herein, which includes administering to the recipient a desensitization therapy for treating or preventing sensitization. Exemplary therapy for treating or preventing sensitization includes plasmapheresis, intravenous immunoglobulin, rituximab, eculizumab, an IL-6 inhibitor (e.g., an anti-IL-6 antibody or an anti-IL-6R antibody), antithymocyte globulin, or a combination thereof.

[0088] Exemplary IL-6 inhibitors include tocilizumab, sarilumab, siltuximab, clazakizumab, olokizumab, elsilimomab, sirukumab, and levilimab. Exemplary Cl esterase inhibitors include BERINERT, CINRYZE, HAEGARDA, and RUCONEST.

[0089] Further embodiments provide systems for performing the computer- implemented methods described herein. For example, an aspect of the invention also relates to computer software. The data processed by the software can be handled in a completely or partially automatic manner, thereby allowing for in a preferred embodiment an automated computer-implemented method. Data regarding the HLA typing of donor and recipient, as well as the presence or absence of, and even the number of, categorically mismatched amino acids for HLA-DQ, particularly within or outside of predicted core peptide sequences for binding with HLA-DR and within or outside of the protein surface of extracellular domain I, as determined for any donor-recipient pair, can be stored electronically and maintained in appropriate databases. As such, the invention further relates to a preferably automated computer-implemented method for prediction of an immune response against human leukocyte antigens (HLA) after transplantation. In some embodiments, a computer-implemented method for assessing a likelihood of an immune response after transplantation is provided, and the computer-implemented method performs the following:(i) HLA-typing of samples obtained from multiple potential donors and from one or more recipients and / or providing HLA typing data from the multiple potential donors and from the one or more recipients, wherein the HLA-typing is carried out on an HLA subtype comprising extracellular domain 1 and / or extracellular domain 2 of an HLA-DQB1, and generating, via a computer, a listing of mismatched HLA-DQB1 proteins in the extracellular domain 1 and / or the extracellular domain 2 between the multiple potential donors and the one or more recipients, wherein a mismatched donor- or recipientspecific HLA-DQB1 allele has at least one amino acid mismatched with both alleles of a recipient- or donor-specific HLA-DQB1, respectively;(ii) determining, via the computer, for each pair of the multiple potential donors and the one or more recipients one or more core peptides and corresponding rank scores, wherein the core peptides are donor- or recipient-specific HLA-DQB1 peptide fragments which are predicted, by the computer, to bind in direct contact with a recipient- or donor- HLA-DRB1 protein, respectively, said predicted binding being determined by a binding strength between each of the core peptides and the HLA-DRB 1 protein, and wherein the rank scores are numbers correlated with the binding strength between the core peptides and the recipient- or donor- HLA-DRB 1 protein, respectively, optionally wherein the rank scores and the binding strength are negatively correlated,(iii) determining, via the computer, for each pair of the multiple potential donors and the one or more recipients, a presence or absence of a categorically mismatched amino acid on an outer surface of the extracellular domain 1 of a mismatched HLA-DQB1 protein, and optionally a presence or absence of a categorically mismatched amino acid in at least one of the core peptides at a residue position configured for interacting with a T cell receptor, wherein the categorically mismatched amino acid on the outer surface of the extracellular domain 1 of the mismatched HLA-DQB1 protein and the categorically mismatched amino acid in the core peptides at the residue positions configured for interacting with the T cell receptor are, each, amino acid residues of the donor-specific HLA-DQB1 protein and of the recipient-specific HLA-DQB1 protein belonging to different categorical groups of amino acids, said different categorical groups being twoor more selected from a nonpolar group, a polar group, a basic group, and an acidic group, wherein: the nonpolar group consists of Alanine, Glycine, Isoleucine, Leucine, Methionine, Tryptophan, Phenylalanine, Proline, and Valine, the polar group consists of Cysteine, Serine, Threonine, Tyrosine, Asparagine, and Glutamine, the basic group consists of Histidine, Lysine, and Arginine, and the acidic group consists of Aspartic acid and Glutamic acid; and(iv) recording for each pair of the multiple potential donors and the one or more recipients: a rank score that corresponds to a greatest one of the binding strength out of the rank scores corresponding to the one or more core peptides determined from step (ii) as a rank score for the mismatched HLA-DQB1 allele when step (iii) determines that the categorically mismatched amino acid is present on the outer surface of the extracellular domain 1 and that if determined the categorically mismatched amino acid is present in the core peptides at the residue position configured for interacting with the T cell receptor, or a user-selected number that indicates none, substantially none, or a least one of the binding strength as a rank score for the mismatched HLA-DQB1 allele when step (iii) determines that the categorically mismatched amino acid is absent from the outer surface of the extracellular domain 1

[0090] The system preferably comprises a database with information on published HLA alleles. The database may be updated as new HLA allele sequences are published. Computer software can be used for generating and / or updating the databases, in relation to the respective programs required for predicting the presentation of allopeptides by HLA molecules, preferably by HLA-DR, DQ or DP, (for example NetMHC including NetMHCIIpan), and for identifying surface residues in predicted three-dimensional structure of HLA proteins.

[0091] The disclosure further comprises a system for preferably pre-transplantation prediction of an immune response against human leukocyte antigens (HLA), which may occur after transplantation, wherein said immune response is associated with HLA-mismatches between donor and recipient. The system may comprise computing devices, data storage devices and / or appropriate software, for example individual software modules, which interact with each other to carry out the method as described herein.

[0092] In some embodiments, a system includes databanks or databases of an allograft bank, whereby each sample is tested for HLA-type, and the information is stored electronically. In some embodiments, a system further includes a connection to an additional computing device, for example a device for a clinician, transplant center, or hospital, in which the HLA- type data for the recipient is stored. Through a connection between the two databases, for example over the internet, the methods described herein can be carried out using appropriate software. HLA-types of multiple potential donor samples and the patient may be compared; and the presence or absence of categorically mismatched amino acids in HLA-DQ proteins, preferably HLA-DQB1, in residues of predicted core peptide sequences to be presented by HLA-DR molecules, preferably residues configured for interacting with T cell receptor and not being bound in the HLA-DR groove, as well as in extracellular domain 1 on protein surface according to a predicted (3 -dimensional) structure of HLA-DQ, for any given donor-recipient pair may be determined. In light of the analysis based on the methods described herein, a clinically relevant prediction can be made whether any given donor material is suitable for transplantation. In additional embodiments, the invention also relates to a software suitable for carrying out the methods described herein. In one embodiment the method of the invention therefore comprises comparison of data regarding HLA-typing from the recipient with multiple potential donor samples, in order to identify suitable transplantation material.EXAMPLES

[0093] The following examples are provided to better illustrate the claimed invention and are not to be interpreted as limiting the scope of the invention. To the extent that specific materials are mentioned, it is merely for purposes of illustration and is not intended to limit the invention. One skilled in the art may develop equivalent means or reactants without the exercise of inventive capacity and without departing from the scope of the invention.

[0094] Example 1-1. HLA Mismatches Identified by A New Algorithm Predict Risk of Antibody-Mediated Rejection from de novo donor-specific antibodies (DnDSA).

[0095] Most dnDSA are against HLA-DQB1 in heart transplant recipients, but many recipients who are mismatched with the donor at HLA-DQB1 do not develop DQ dnDSA. Amino acids can be classified into 4 categories based on their chemical characteristics: nonpolar, polar, basic, and acidic. Inventor postulates that only mismatched amino acids that are in different categories between recipients and donors can effectively stimulate production of DSAs, while those mismatched amino acids that belong to the same category have an inferior ability to trigger immune responses.

[0096] B cell activation is initiated when the B cell receptor binding to antigens, and eventually, B cells can differentiate into antibody-secreting cells. Maturation and differentiation of antigen-specific B cells are tightly controlled by T cells. CD4 T helper cells with TCR recognizing an antigen peptide in the context of HLA class II (HLA-DR, HLA-DQ, and HLA-DP) are required for the differentiation of B cells whose B cell receptor binds the same antigen.

[0097] To decipher mismatches which are prone to stimulating dnDSA, a new method is developed to evaluate HLA-DQ mismatch between recipients and donors, taking into considerations four factors: (1) chemical characteristics of amino acid residues, (2) position of mismatched residues at the core peptide presented on the recipient HLA-DR, (3) binding strength of allo-peptides, and (4) surface localization of mismatched residues. Briefly, core peptides derived from donor mismatched HLA-DQ allele were predicted. The binding strength of peptides to the recipient HLA-DR, as measured by %Rank score, was calculated. The core peptide presented by HLA class II to TCR is 9-mer, where amino acid residues at positions 2, 3, 5, 7, and 8 are important for TCR binding, while residues at positions 1, 4, 6, and 9 anchor the peptide to HLA class II. Inventor hypothesized that that only amino acid residues of HLA that were mismatched in different categories at positions 2, 3, 5, 7, and 8 of the core peptide could effectively stimulate donor HLA-specific antibody production.

[0098] The HLA-DRB1 gene is constitutively expressed, and the expression of HLA- DR is higher than that of HLA-DQ and HLA-DP in mononuclear cells. In heart transplant recipients, most dnDSA are directed against HLA-DQ. Described herein is a new algorithm to evaluate binding between the recipient’s HLA-DRB1 and allopeptides derived from mismatched donor HLA-DQB 1 antigens as a model to examine if strong-binding allo-peptides are more likely to stimulate dnDSA. We found that recipients who had strong-binding categorical amino acid mismatched epitope (CAME) at the HLA-DQB 1 locus were at higher risk of developing HLA-DQ dnDSA and AMR. The lowest %Rank score was assigned as the Ranking score for the mismatched HLA-DQ allele (Figure 1).

[0099] To validate if our algorithm, which is termed as the CAME algorithm, could identify mismatches which predispose patients to a higher risk of dnDSA, inventor(s) first applied the algorithm to recipients who mismatched with the donor for two HLA-DQ antigens but developed dnDSA against only one of them. Of 386 recipients, 8 met this criterion. These 8 recipients comprised an ideal cohort to pairwise compare the contribution of different DQ mismatches in of the development of dnDSA, because the medication and genetic background were identical for both mismatched DQ alleles in each individual. Mismatch analysis by theCAME algorithm showed the mismatched HLA-DQ alleles targeted by dnDSA had a lower %Rank score than the alleles not targeted by dnDSA in each recipient (P< 0.008) (Figure 2). The alleles targeted by dnDSA had a %Rank score <1 in 5 recipients, and < 2 in two recipients. Peptides with a %Rank score <1 or < 2 are considered as strong-binding peptides and more likely to stimulate immune response. In 1 recipient (recipient 8), DQ dnDSA was developed against an allele with a %Rank score of 12 after infection, but the %Rank score of the nontargeted allele was 53 which was much higher than the dnDSA targeted allele. This case indicates that the CAME algorithm can still identify more immunogenic alleles even in recipients who are under inflammatory conditions.

[0100] Next, we evaluated HLA-DQB1 mismatches by the CAME algorithm in the whole cohort of 386 patients. An HLA-DQB1 have more than one core peptides (or many core peptides). The lowest score of all core peptides is assigned as the score for this allele. Here, we compared scores of entire alleles to identify presence of any categorically mismatched amino acids, whose data is shown in figures 2-5. The default threshold of the %Rank score offset by the NetMHCIIpan EL program is 1 for strong-binding peptide and 5 for weak-binding peptides. The threshold of %Rank score 2 had also been indicated for strong-binding peptides. We divided the cohort into four groups based on %Rank scores of mismatched HLA-DQB 1 alleles (Group 1 : %Rank score < 1; Group 2: 1 < %Rank score < 2; Group 3: 2 < %Rank score < 5; Group 4: %Rank score >5), and estimated the freedom from development of DQB1 dnDSA. The freedom from dnDSA was significantly different among four groups (P=0.025). The Kaplan-Meier curve analysis showed recipients with %Rank score < 1 had apparent lower survival than other three groups, and the curves for the other three groups were largely overlapped (Figure 3A). Therefore, we combined groups 2, 3 and 4 into one group (%Rank score >1) and compared its freedom from dnDSA with the group having %Rank score <1. We found that the presence of mismatched DQB1 alleles with a %Rank Score <1 was associated with the development of DQB1 dnDSA (P=0.002) (Figure 3B).

[0101] To validate if we can use the %Rank score <1 as the cutoff to stratify the risk of development of dnDSA, we applied the CAME algorithm to a cohort of 10 recipients in whom DQ dnDSA was detected recently. We found recipients with %Rank <1 developed DQB1 dnDSA earlier than recipients with %Rank >1 (Figure ID). The P value (P = 0.081) did not reach statistical significance, although, likely because of the small number of subjects. Furthermore, we examined if the PIRCHE algorithm can predict the risk of development of DQ dnDSA in our cohort. The PIRCHE algorithm, like the CAME algorithm, also considers the contribution of T cell receptor epitopes in antibody development. We divided the originalcohort of 386 recipients into 2 groups based on the median numbers of PIRCHE DQB1 mismatched epitopes. The PIRCHE algorithm failed to predict the development of DQB1 dnDSA. Recipients with the number of PIRCHE DQB1 mismatched epitopes >21 had similar freedom of DQB 1 dnDSA compared with recipients with PIRCHE DQB 1 mismatched epitopes <21 (Figure 3C).

[0102] Although the development of DSAs increases the risk of graft dysfunction, the majority of heart recipients who have dnDSA are not diagnosed with AMR on biopsy, indicating that DSA alone does not always cause AMR. To examine if the presence of categorically mismatched amino acids could distinguish recipients who would develop AMR, inventor compared the freedom from AMR among 4 groups: 1) anti-DQBl dnDSA positive + %Rank score < 1; 2) anti-DQBl dnDSA positive + %Rank score > 1; 3) anti-DQBl dnDSA negative + %Rank score < 1; and 4) anti-DQBl dnDSA negative + %Rank score > 1. Anti- DQBl DSA is most frequent de novo DSA. The curve of Group 1 (dnDSA positive + %Rank score <=1) was clearly separated from the other three groups, while the other 3 groups had a similar risk of AMR (Figure 4A). Of interest, dnDSA did not increase risk of AMR in recipients whose %Rank scores were > 1 (Group 2 vs. Group 4). Then, we combined the three groups (dnDSA positive + %Rank score >1, dnDSA negative + %Rank score < 1, and dnDSA negative + %Rank score >1) which had similar freedom from AMR into one, and compared its freedom from AMR with recipients who had dnDSA + %Rank score < 1. Recipients who had %Rank score <1 and developed DQ dnDSA, had lower freedom of AMR (P< 0.001) (Figure 4B). Multivariates analysis showed that recipients with dnDSA and %Rank score < 1 were at increased risk of AMR (hazard ratio= 5.576) (Table 2). Induction with antithymocyte globulin (ATG) was not associated with AMR.Table 2. Multivariates analysis of dnDSA + %Rank Score and other variables on AMR.ATG, antithymocyte globulin; AMR, antibody-mediated rejection; dnDSA, de novo donorspecific antibodies.

[0103] To exclude the possibility that lower freedom of AMR observed in recipients with dnDSA + Ranking score < 1 was caused by higher levels of dnDSA in these recipients, we compared the MFI of DQ dnDSA between recipients with Ranking score < 1 and recipients with Ranking score > 1. The median MFI in 16 patients who had dnDSA and Ranking score < 1 was 5546, and median MFI in 20 patients who had dnDSA and Ranking Score >1 was 7099. The difference of MFI between these two groups was not significant (p=0.301 ).

[0104] Overall, inventor developed a new algorithm to evaluate HLA mismatches in transplant patients to stratify the risk of dnDSA and AMR. Because most dnDSA are against HLA-DQ in solid organ transplant, this algorithm focuses on HLA-DQB1 mismatches. Inventor demonstrated that the presence of HLA-DQ mismatches with a %Rank score < 1 was associated with development of dnDSA. Inventor also found that DQ dnDSA increased the risk of AMR only in recipients who had HLA mismatches with a Rank score <1. In other embodiments, the methods / algorithms disclosed herein are for use with other dnDSA than those against HLA-DQB 1. In preferable embodiments, the algorithms are for use with anti- HLA-DQB1 dnDSA, as most dnDSA are against HLA-DQB 1.

[0105] Our algorithm considers four parameters: the strength of peptide binding, chemical characteristics of amino acid mismatches, the position of mismatched amino acid resides at the core peptide, and whether the donor and recipient have mismatched amino acid residues exposed on the protein surface. Unlike other algorithms that stratify the risk of HLA mismatching in AMR based on the number of mismatched peptides, our algorithm focuses on the “quality“ instead of “quantity“ of mismatches and does not count on the number of mismatches. The goal of the CAME algorithm is to identify the most immune dominant epitope. Different from other algorithms, the CAME algorithm only considers two amino acids in different chemical categories as mismatched. Changes between amino acids within one category, such as leucine and isoleucine which belong to the same nonpolar category and have a similar structure, is less likely to stimulate immune response. Increased number of peptides with change in the same category may not raise the risk of development of dnDSA. In addition, to identify mismatches which can trigger the most vigorous immune response, the CAME algorithm factors in the position of mismatched residues in the core peptide. The PICHE-II algorithm also uses the program NetMHC to predict core peptides which can be recognized by TCR but the PICHE-II algorithm does not consider positions of mismatched amino acid residues. Amino acid residues at positions 1,4, 6, 9 do not interact with TCR and the differencein amino acid residues at these positions may not be that important to stimulate T helper cells whose activation is prerequisite for antibody production.

[0106] The presence of dnDSA can lead to graft injury, even graft failure in some recipients, but graft function is not compromised in other recipients. It is not uncommon that recipients have developed dnDSA but do not have rejection on endomyocardial biopsies. In pediatrics heart transplants, only 24% of patients who have DNAs are diagnosed with AMR. It has been a puzzle why some recipients progress to AMR while others do not after the development of dnDSA. The results herein demonstrated that dnDSA was associated with AMR only in recipients who had a mismatching %Rank Score < 1, but not in recipients with a %Rank score >1. These results indicate that %Rank score can be used to predict the risk of AMR in heart transplants. Because dnDSA is not associated with AMR in recipients with a %Rank score >1, it may not be necessary to perform frequent routine surveillance biopsies, for AMR diagnosis on these patients, even if they have developed dnDSA. For-cause heart biopsies with potential AMR therapies may be saved only for recipients with %Rank scores <1.

[0107] The reason that dnDSA did not increase the risk of AMR in recipients with mismatching %Rank score > 1 is likely because these antibodies have low affinity to the native form of donor HL A antigens. Two dnDSA positive recipients who had %Rank score >1 but were not diagnosed with AMR, did not have CAME mismatched epitopes exposed on the surface of HLA-DQB1 protein, indicating that the dnDSA in these 2 recipients only recognize epitopes exposed on HLA antigens in in vitro assays, such as in the single antigen beads-based assay, but not on the surface of cells of the allograft. The CAME algorithm identifies the most immunogenic alleles which have categorical mismatched amino acid residues with the recipient on protein surface of the extracellular domain 1 of HLA-DQB 1. Mismatched donor alleles with %Rank score >1 may not be presented efficiently to TCR, and therefore the engagement of T helper cells may be lacking. Interaction between B cells and T helper cells is required for somatic hypermutation in B cells to produce high-affinity antibodies. We conceive that the CAME algorithm may also be applied to kidney or lung transplant recipients for AMR risk stratification and / or donor selection.

[0108] Inventor compared the MFI of DQ dnDSA between recipients with a %Rank score <1 and recipients with a %Rank score >1. The difference in MFI was not significant (5546 versus 7099, P = 0.301), indicating that the lower freedom from AMR observed in recipients with dnDSA + %Rank score <1 was not caused by higher levels of dnDSA in these recipients. We recognize that antibody testing on neat sera may not fully reveal antibody levels,but inventor does not routinely perform dilution or Clq antibody tests for all recipients as part of the center’s clinical practice.

[0109] Exisiting algorithms to evaluate the risk of HLA mismatching in AMR stratify the risk based on the number of mismatched peptides. Various cutoffs for the number of mismatched peptides have been proposed in these prior studies, which could lead to varied results between studies. The goal of the CAME algorithm is to identify the most immunodominant epitope which is designated by the lowest %Rank score, irrespective of how many mismatched epitopes there are. This is opposite to the other published algorithms, in which a higher number of mismatched epitopes indicates a stronger antibody response. The major difference between our CAME algorithm and other algorithms is that our CAME algorithm focuses on the “quality” instead of the “quantity” of mismatches. Unlike other algorithms, the CAME algorithm does not add together the numbers of mismatches from different alleles or antigens. Instead, the CAME algorithm assigns a single %Rank score for each mismatched allele or antigen. For example, the CAME algorithm would assign a %Rank score for the DQB1 allele and a %Rank score for the DQA1 allele. But few patients had developed dnDSA against DQA1 alleles.

[0110] Distinct from other algorithms, the CAME algorithm considers 2 amino acids mismatched only when they are in different chemical categories. Changes between amino acids within 1 category, such as leucine and isoleucine, which belong to the same nonpolar category and have a similar structure, are less likely to stimulate immune responses. Increased numbers of peptides with this kind of change may not raise the risk of the development of dnDSA. Amino acids in the same category can still vary in their sizes, charges, and structures. For example, both glycine and alanine belong to the nonpolar category, but glycine contains only a single hydrogen atom as its side chain, which may be essential for a tight turn in a protein structure. Substitution of glycine with other amino acids may disrupt the protein structure. However, this difference may not be important for antibody-antigen recognition, as demonstrated in SARS-CoV-2 antibody studies.[OHl] In addition, to find mismatches that can trigger the most vigorous immune response, the CAME algorithm factors in the position of mismatched residues in the core peptide. The PIRCHE algorithm also uses the program NetMHC to predict core peptides which can be recognized by TCR, but the PIRCHE algorithm does not consider the positions of mismatched amino acid residues. Amino acid residues at positions 1,4, 6, and 9 do not interact with TCR, and the difference at these positions may not be important to stimulate T helper cells whose activation is a prerequisite for IgG production.

[0112] Eleven recipients in the original cohort developed DQB 1 dnDSA even if %Rank scores for mismatched DQB1 alleles were >1. Two of them had dnDSA against both DQB1 and DQA1. DQB 1 protein associates with DQ Al protein to form a functional dimer on the cell surface. To determine if mismatched DQA1 stimulated the development of dnDSA against DQB1, we evaluated the %Rank score of mismatched DQA1 alleles in these 2 recipients. The %Ranks for the mismatched DQA1 in both recipients were >5, indicating that the development of dnDSA against mismatched DQB 1 alleles with %Rank >1 is likely not stimulated by DQA1 mismatches.

[0113] In all, HLA mismatches evaluated by the CAME algorithm can stratify the risk of development of DQ dnDSA and AMR in transplant recipients, such as heart transplant recipients. It is also conceived that the CAME algorithm can also be applied to kidney or lung or another organ’s transplant recipients for AMR risk stratification and / or donor selection.

[0114] Materials and Techniques2.1. Patient Population

[0115] This study was approved by the institutional review board of Cedars-Sinai Medical Center (Pro00047925). The original cohort was described by Zhang et al. in Human Immunology, volume 81, issue 7, July 2020, pages 330-336. To study the association of HLA mismatching with DQ dnDSA, 427 heart recipients transplanted at Cedar-Sinai Medical Center between 01 / 01 / 2011 and 12 / 31 / 2015 were enrolled. The mean of follow up days is 965 (standard deviation: 648). Recipients with multiorgan transplant which involves heart were excluded. Recipients who had pre-formed DSA before transplant, or dnDSA against HLA loci other than HLA-DQB1 were also excluded. 386 of 427 recipients who had at least one HLA- DQB1 allele mismatch with the donor were included for analysis of association between HLA matching and outcomes. The remaining 41 recipients, who had zero mismatchH LA-DOB 1 locus, were not included to avoid inflating the contribution of HLA-DQ mismatching, because these recipients usually do not develop DSA.

[0116] AMR was defined on endomyocardial biopsy according to the International Society for Heart and Lung Transplantation (ISHLT) criteria as described in J Heart Lung Transplant, 32 (2013), pp. 1147-1162. 14 patients developed pAMR 2 and two patients developed pAMR 1H. Freedom from AMR was evaluated in 351 recipients who had clinical follow-ups. In various embodiments involving heart transplantation, criteria for the diagnosis of AMR are according to the guidelines by the International Society for Heart and Lung Transplantation (ISHLT).2.2. Antibody test

[0117] HL A antibodies were evaluated at 1, 3, 6, and 12 months post-transplantation during the first year and yearly thereafter. The specificity of HLA antibodies was determined by the single antigen bead-based assay (ONE LAMBDA, West Hills). Sera were pretreated with ethylenediaminetetraacetic acid (EDTA) at 37 °C for 30 min before antibody testing. Mean fluorescence intensity (MFI) of 2,500 was used as the cutoff for the single antigen beadbased assay. DnDSA was defined as antibodies which were not present before transplant but were detected after 4wk posttransplant. The specificity of dnDSA was assigned when recipients displayed dnDSA for the first time. When dnDSA was assigned, pre-transplant tests were reviewed to confirm low levels of the DSA were not present in pre-transplant samples.2.3. HLA typing

[0118] Recipient and donor HLA typing was performed by sequence-specific oligonucleotide (SSO) and analyzed by the program Fusion (One lambda, West Hills) as a standard of care. The most frequent paired alleles from “group 1” obtained from Fusion were assigned as HLA-DRB1 and DQB1 high-resolution typing. To verify the accuracy of the assignment, 91 recipients were re-typed by next generation sequencing (NGS) using the AlloSeq platform (CareDx, Brisbane). NGS typing results were concordant with the SSO- derived high-resolution typing for all these recipients, indicating that it is feasible to assign high-resolution typing of HLA-DRB1 and DQB1 from SSO raw data.2.4. Evaluation of categorical amino acid mismatched epitopes (CAME)

[0119] First, one donor HLA-DQB1 allele was aligned with each of a recipient’s two HLA-DQB 1 alleles. Amino acid residues that were different between the donor allele and both recipient alleles were assigned into one of four categories: Nonpolar amino acids, Polar amino acids, Basic amino acids, and Acidic amino acids (Table 1). Amino acid residues that belonged to different categories were considered as Categorical Amino Acid Mismatched Epitopes (CAME). Amino acid residues which belong to the same category (for example, Isoleucine and Leucine, which were in the nonpolar category) were not considered as categorically mismatched.

[0120] Second, the localization of mismatched amino acid residues was visualized by using the online program pHLA3D (phla3d.com.br; the program pHLA3D shows whether amino acids are on the surface or not) (Deylane Menezes Teles E Oliveira et al., Hum Immunol. 2019 Oct;80(10):834-841; Deylane Menezes Teles E Oliveira et al., Hum Immunol. 2021 Jan;82(l):8-10). Antibodies can only access amino acid residues exposed on the protein surface. If no categorically mismatched amino acid residues were exposed on the surface of extracellular domain 1 of the donor’s HLA-DQB 1, we presumed that the recipient would notdevelop antibodies against this donor allele (or the antibodies could not bind the native form of the donor antigen even if such antibodies existed), and we would assign 99, the maximum possible %Rank score, for this allele (the extracellular domain 2 of HLA-DQB1 is close to the plasma membrane and might be embedded by other membrane proteins. Therefore, this domain was likely less accessible by antibodies and was not evaluated for surface localization). If the extracellular domain 1 of a donor HLA-DQB1 allele had any categorically mismatched residues on its surface, mismatching was further evaluated as described below.

[0121] Third, donor HLA-DQB1 -derived peptides presented on the recipient’s HLA- DRB1 was predicted by using the program NetMHCIIpan EL program (tools.immuneepitope.org / mhcii / ). NetMHCIIpan is a method to predict TCR binding peptide presented on HLA class II molecules (see Reynisson et al., Nucleic Acids Research, 2020, Vol. 48, W449-W454). 9-mer core peptides presented by recipient’s HLA-DRB1 were identified by the program. For example, only one HLA-DQB1 allele for a certain allograft was entered in the program if another allele is the same as the recipient’s.

[0122] During T cell development, T cells with TCR having high affinity for the self- peptide-MHC complex are deleted in the negative selection. TCR binds amino acid residues at positions 2, 3, 5, 7, and 8 of 9-mer core peptides presented by MHC (Nelson et al., Immunity. 2015 January 20; 42(1): 95-107; D. B. Sant’ Angelo et al., Eur. J. Immunol. 2002. 32: 2510- 2520). Inventor conceives that a donor HLA-derived core peptide that had similar amino acid residues at these positions to the corresponding recipient’s would mimic the conformation of self-peptides and would not elicit strong immune response. Specifically, recipient’s HLA- DRB1 and DQB1 sequences were obtained, e.g., through SSO primed PCR; then donor DQB1 derived 9-mer core peptides (predicted by NetMHC program, for presentation in recipient’s HLA-DRB1) were aligned with recipient’s DQB1 sequence for comparison. Therefore, only donor core peptides which had amino acid residues in different categories from the recipient’s both alleles at any one, two, three, four, or all five of positions 2, 3, 5, 7, and 8 of the 9-mer core peptide were considered mismatched peptides that could stimulate immune response. The binding strength between core peptides and the recipient’s HLA-DRB1 was expressed as a normalized value, the %Rank score. The %Rank score, which ranges from 0 to 99, was calculated by the program NetMHCIIpan EL. Peptides with a lower %Rank score are more likely to be presented and to stimulate immune response. Peptides with %Rank scores of <1 or <2 are considered as strong binding peptides; Peptides with %Rank scores of <5 or <10 are considered as weak binding peptides. The lowest %Rank score of all core peptides from amismatched donor HL A-DQB 1 allele was assigned as %Rank score for this allele. An example of assigning %Rank scores is detailed in Example 1-1 and figures 1B-1D.

[0123] 2.5. Statistical analysis

[0124] Freedom from the development of dnDSA and rejection was estimated by the Kaplan-Meier method and assessed across groups by the log-rank test. Group comparison of median fluorescence intensity (MFI) and %Rank scores was performed by the Wilcoxon signed-rank test or Mann-Whitney rank sum test. Categorical variables were compared using the Chi-square test. Multivariate analysis was performed using the Cox proportional hazards regression model. P <0.05 was considered significant. SigmaPlot version 14.0 was used for statistical analysis.

[0125] Example 1-1. An example showing how to use CAME algorithm to evaluate HLA-DQB1 mismatches.HL A typing:Patient: HLA-DRB 1*01:01, 15:01; HLA-DQB 1*05:01, 06:02;Donor: HLA-DQB 1*03:01, DQBl*03:02.Step 1. Align donor HLA-DQB 1*03:01 with the recipient HLA-DQBl*05:01 and 06:02 for the extracellular domain 1 and 2. (The HLA-DQB 1 gene has five or six exons: exon 1 encodes the leader peptide, exons 2 and 3 encode the two extracellular domains, exon 4 encodes the transmembrane domain, and exon 5 encodes the cytoplasmic tail.)Amino acid residue A at the position 13 of the donor HLA-DQB 1*03:01 was not categorically mismatched with G of the recipient because A and G belong to the same Nonpolar group (Figure IB). The categorically mismatched amino acid residues (For example, Y at the position 26 of the donor belongs Polar group, while G and L at the position 26 of the recipient belong to Nonpolar group) were highlighted in yellow in Figure IB.Step2. Evaluate if there are any categorically mismatched amino acid residue of the extracellular domain 1 in the surface position. If so, it is postulated that the recipient can potentially develop antibodies against this HLA allele, and the algorithm will continue to Step 3 for further analysis. If not, assign 99 as %Rank score for the mismatched donor allele.In this recipient / donor pair, the categorically mismatched amino acid residue 45E is exposed on the protein surface (Figure IB and 1C), so the algorithm continues to Step 3 for further analysis.Step 3.Use NetMHCIIpan to find the core peptides derived from HLA-DQB 1*03:01 extracellular domain 1 and 2 (presented by the recipient DRBl*01 :01 and DRBl*15:01) and their associated %Rank scores (Table 3).Step 4. Find all core peptides derived from extracellular domain 1 and 2 harboring the categorically mismatched amino acid residues at position 2, 3, 5, 7, and 8. For example, the core peptide VRYVTRYIY (SEQ ID NO:6) harboring 26Y categorical mismatch at the position 3 was presented by HLA- DRBl*01 :01 and DRB1*15:O1 (Rows’ ID = 19-22, Table 3); the core peptide VEVYRAVTP (SEQ ID NO: 12) harboring 45E categorical mismatch at the position 2 was presented by HLA-DRB 1*01 :01 and DRBl*15:01 (Rows’ ID = 38-42, Table 3). Record all corresponding %Rank scores (Table 3). (Note: A categorically mismatched amino acid residue identified from Step 4 does not necessarily need to be on the surface like Step 2. Step 2 is a filter for those qualifying to move on to Step 3.)Step 5.Find the smallest %Rank score from step 4, which is 0.85 (Row ID = 41, Table 3) and assign this number as %Rank score for the mismatched HLA-DQB 1*03:01 allele.Step 6.Repeat steps 1-5 for the second mismatched donor allele HLA-DQB 1*03:02. (Note: when having the %Rank score from step 5 (or 2) for respective allele, the smaller one of the two alleles is taken.)Table 3. Core peptides and Rank scores predicted by NetMHCIIpan. (The predicted%Rank score may be affected by the sequences flanking the core peptide. Hence there can be different scores predicted for a score core peptide presented by a given HLA-DRB1.)

[0126] Example 2. Identified HLA mismatches predicted risk of antibody- mediated rejection from dnDSA.

[0127] Development of de novo donor specific antibodies (dnDSA) and antibody mediated rejection (AMR) remain to be a barrier for long term graft and patient survival. Most dnDSA are against mismatched donor HLA-DQ antigens. Here we developed a new algorithm to evaluate HLA-DQ mismatches and to stratify the risk of dnDSA and AMR.

[0128] Methods: 352 cardiac allograft recipients were included in the study. Recipients who had DSA pretransplant or developed non-DQ dnDSA were not included. Recipients who had zero DQ antigen mismatch with donors usually do not develop DQ dnDSA and were also excluded. HLA-DQB1 mismatches between the recipient and donor was evaluated by a new algorithm: categorical amino acid mismatched epitope (CAME). Briefly, amino acids of the HLA-DQ protein were categorized into 4 groups and the likelihood of categorical mismatched peptides presented by the recipient DRB 1 were ranked.

[0129] Results: 8 recipients who had two HLA-DQ antigen mismatches with the donor but developed dnDSA against only one mismatched allele, comprise an ideal cohort to pairwise compare DQ mismatches in formation of dnDSA. Mismatch analysis by the CAME algorithm showed HLA-DQ alleles targeted by dnDSA had lower rank score than the allele not targeted by dnDSA in each recipient (P< 0.008). Next, we evaluated rank scores of HLA-DQ mismatches in all 352 recipients. We found the presence of DQ mismatches with rank score <1 was associated with development of dnDSA (P=0.002). Furthermore, we determined if HLA- DQ mismatch was associated with AMR. Of interest, recipients with dnDSA had similar freedom from AMR compared to dnDSA negative group when rank score of DQ mismatches was > 1 (Fig. 4A). DnDSA increased the risk of AMR only in recipients who had DQ mismatches with rank score < 1 (hazard ratio= 5.8) (Fig. 4B).

[0130] Conclusion: HLA DQ mismatches evaluated by the CAME algorithm can help stratify the risk of development of dnDSA and AMR. Lower rank scores of HLA-DQ mismatches are associated with development of dnDSA and increased risk of AMR in heart transplant.Example 3. Steps to evaluate mismatch.

[0131] An exemplary process includes steps below:1. Analyze / predict the presentation of peptides derived from (mismatched) donor HLA- DQB1 alleles by the recipient HLA-DRB1 alleles vis online program NetMHCIIpan. 9-mer core peptides and Rank number were identified.2. Align donor HLA-DQB1 alleles with two recipient’s HLA-DQB1 alleles. When an amino acid of the donor HLA -DQB1 allele is different with both alleles of the recipient, we consider this amino acid as mismatch. Categorize mismatched amino acids into four groups: Nonpolar amino acids, Polar amino acids, Basic amino acids, and Acidic amino acids (Table1). If mismatched amino acids in the donor and recipient belong to different categories, we consider this amino acid as category mismatch (or categorically mismatched).3. Check if the category mismatched amino acids in the extracellular domain (alpha 1 and2) are located at the position 2, 3, 5, 7, and 8 of a core peptide. If yes, record the Rank number of this mismatched peptides. One HLA-DQB1 allele can give many core peptides. If a core peptide does not have a requisite mismatch, no rank number is recorded for this core peptide, and a next 9-mer core peptide is checked until a categorical mismatch is identified at position 2, 3, 5, 7, and 8.4. Evaluate if the donor allele and the recipient’s alleles have a category mismatch exposed on the protein surface by (dev.phla3d.com.br / ). If not, we presume that the recipientwill not develop antibodies against this donor allele and record the Rank number as 99 for this mismatched allele (Or the antibodies could not bind the HLA antigens in vivo and the current test platform cannot detected them even if such antibodies developed).5. If there is a category mismatched amino acid in extracellular domain 1 of HLA-DQB1 exposed on the protein surface, the smallest rank number of category-mismatched peptides obtained from step 3 will be the Rank number of this mismatched donor HLA-DQ allele.6. Repeat step 3 to 5 for the second mismatched donor allele.7. Rank number <=1 is associated with dnDSA and AMR.

[0132] Various embodiments of the invention are described above in the Detailed Description. While these descriptions directly describe the above embodiments, it is understood that those skilled in the art may conceive modifications and / or variations to the specific embodiments shown and described herein. Any such modifications or variations that fall within the purview of this description are intended to be included therein as well. Unless specifically noted, it is the intention of the inventors that the words and phrases in the specification and claims be given the ordinary and accustomed meanings to those of ordinary skill in the applicable art(s).

[0133] The foregoing description of various embodiments of the invention known to the applicant at this time of filing the application has been presented and is intended for the purposes of illustration and description. The present description is not intended to be exhaustive nor limit the invention to the precise form disclosed and many modifications and variations are possible in the light of the above teachings. The embodiments described serve to explain the principles of the invention and its practical application and to enable others skilled in the art to utilize the invention in various embodiments and with various modifications as are suited to the particular use contemplated. Therefore, it is intended that the invention not be limited to the particular embodiments disclosed for carrying out the invention.

[0134] While particular embodiments of the present invention have been shown and described, it will be obvious to those skilled in the art that, based upon the teachings herein, changes and modifications may be made without departing from this invention and its broader aspects and, therefore, the appended claims are to encompass within their scope all such changes and modifications as are within the true spirit and scope of this invention. It will be understood by those within the art that, in general, terms used herein are generally intended as “open“ terms (e.g., the term “including should be interpreted as “including but not limited to,“ the term “having“ should be interpreted as “having at least, “ the term “included should be interpreted as “includes but is not limited to,“ etc.). As used herein the term “comprising or“comprised is used in reference to compositions, methods, and respective component(s) thereof, that are useful to an embodiment, yet open to the inclusion of unspecified elements, whether useful or not. It will be understood by those within the art that, in general, terms used herein are generally intended as “open“ terms (e.g., the term “including should be interpreted as “including but not limited to,“ the term “having“ should be interpreted as “having at least, “ the term “includes“ should be interpreted as “includes but is not limited to,“ etc.). Although the open-ended term “comprising, “ as a synonym of terms such as including, containing, or having, is used herein to describe and claim the invention, the present invention, or embodiments thereof, may alternatively be described using alternative terms such as “consisting of‘ or “consisting essentially of. “

Claims

WHAT IS CLAIMED IS:

1. A method for selecting an organ, a tissue preparation, or cells for allogeneic transplantation, comprising: carrying out a computer-implemented method for assessing a likelihood of an immune response after transplantation, wherein the immune response comprises T-cell-alloreactivity against human leukocyte antigens (HLA) that are mismatched between one or more donors and one or more recipients, the computer-implemented method comprising:(i) HLA-typing of samples obtained from multiple potential donors and from one or more recipients and / or providing HLA typing data from the multiple potential donors and from the one or more recipients, wherein the HLA-typing is carried out on an HLA subtype comprising extracellular domain 1 and / or extracellular domain 2 of an HLA-DQB1, and generating, via a computer, a listing of mismatched HLA-DQB1 proteins in the extracellular domain 1 and / or the extracellular domain 2 between the multiple potential donors and the one or more recipients, wherein a mismatched donor- or recipientspecific HLA-DQB1 allele has at least one amino acid mismatched with both alleles of a recipient- or donor-specific HLA-DQB1, respectively;(ii) determining, via the computer, two or more core peptides and respective rank scores for each pair of the multiple potential donors and the one or more recipients , wherein the core peptides are each a donor- or recipient-specific HLA-DQB1- derived peptide from a mismatched donor- or recipient- HLA-DQB1 protein, respectively, which is predicted, by the computer, to bind in direct contact with a recipient- or donor- HLA-DRB1 protein, respectively, said predicted binding being determined by a binding strength between the core peptide and the HLA-DRB 1 protein, and wherein the rank scores are each a number correlated with the binding strength between respectively core peptide and the HLA-DRB 1 protein, optionally wherein each of the rank score and the respective binding strength are negatively correlated,(iii) determining, via the computer, for each pair of the multiple potential donors and the one or more recipients, a presence or absence of a categorically mismatched amino acid on an outer surface of the extracellular domain 1 of a mismatched HLA-DQB1 protein, and, if the outer surface of the extracellular domain 1 has a categorically mismatched amino acid present, also determining a presence or absence of acategorically mismatched amino acid in at least one of the core peptides at a residue position configured for interacting with a T cell receptor, wherein the categorically mismatched amino acid on the outer surface of the extracellular domain 1 of the mismatched HLA-DQB1 protein and the categorically mismatched amino acid in the core peptides at the residue positions configured for interacting with the T cell receptor are, each, amino acid residues of the donor-specific HLA-DQB1 protein and of the recipient-specific HLA-DQB1 protein belonging to different categorical groups of amino acids, said different categorical groups being two or more selected from a nonpolar group, a polar group, a basic group, and an acidic group, wherein: the nonpolar group consists of Alanine, Glycine, Isoleucine, Leucine, Methionine, Tryptophan, Phenylalanine, Proline, and Valine, the polar group consists of Cysteine, Serine, Threonine, Tyrosine, Asparagine, and Glutamine, the basic group consists of Histidine, Lysine, and Arginine, and the acidic group consists of Aspartic acid and Glutamic acid; and (iv) recording for each pair of the multiple potential donors and the one or more recipients: a rank score correlated with a greatest one of the binding strength out of the two or more core peptides determined from step (ii) as a recorded rank score for the mismatched HLA-DQB1 allele when step (iii) determines that the categorically mismatched amino acid is present on the outer surface of the extracellular domain 1 and that that the categorically mismatched amino acid is present in the core peptides at the residue position configured for interacting with the T cell receptor, and a user-selected number that indicates none, substantially none, or a least one of the binding strength as a recorded rank score for the mismatched HLA-DQB1 allele when step (iii) determines that the categorically mismatched amino acid is absent on the outer surface of the extracellular domain 1 or step (iii) determines that the categorically mismatched amino acid is absent in the two or more core peptides at the residue positions configured for interacting with the T cell receptor; andselecting an organ, a tissue preparation, or cells from a donor having a recorded rank score that is correlated with a binding strength below a reference binding-strength amount for the allogenic transplantation in a recipient of the pair for which the recorded rank score is performed, or determining that an organ, a tissue preparation, or cells from a donor having a recorded rank score that is correlated with a binding strength equal to or greater than the reference binding-strength amount as inappropriate for the allogeneic transplantation or as likely to develop de novo donor specific antibody after the allogeneic transplantation in the recipient from the pair.

2. The method of claim 1, further comprising transplanting into the recipient the organ, the tissue preparation, or the cells of the donor recorded with the recorded rank score correlated with the binding strength below the reference binding-strength amount.

3. The method of claim 1, wherein the reference binding-strength amount is the 1stpercentile of binding strengths from high-to-low for HLA-DQ in a distribution from a plurality of random natural peptides.

4. The method of claim 1, wherein the core peptide is 9 amino acids in length.

5. The method of claim 4, wherein the residue position configured for interacting with the T cell receptor comprises positions 2, 3, 5, 7, and / or 8 from N- to C- terminus of the core peptide.

6. The method of claim 1, wherein the computer-implemented method comprises repeating steps (i) through (iv) for a different allele of the HLA subtype.

7. The method of claim 1, wherein the transplantation comprising heart transplantation, or kidney transplantation.

8. The method of claim 1, wherein the method further includes assessing transplantation outcome comprising de novo development of donor- specific HLA antibodies, antibody- mediated rejection of the transplant, patient survival, disease free survival, and / or transplant- related mortality.

9. The method of claim 1, wherein the immune response comprises: an antibody-mediated response; a graft versus host disease (GVHD); and / or de novo development of donor specific HLA IgG antibodies after the transplantation.

10. The method of claim 1, wherein the HLA typing is carried out with sequence-based typing, and / or comprises serological and / or molecular typing.

11. The method of claim 1, comprising the analysis of multiple HLA mismatched donors, thereby selecting the donor with the recorded rank score that is correlated with a least amountof the binding strength below the reference binding-strength amount for the allogenic transplantation, and / or thereby determining alloreactivity between multiple donors.

12. The method of claim 1, wherein the method further comprises abstaining from transplanting in the recipient the organ, tissue preparation or cells having a recorded rank score that is correlated with the binding strength equal to or greater than the reference bindingstrength amount, or wherein the method further comprises administering to the recipient a desensitization therapy who receives transplant of the organ, tissue preparation or cells having the recorded rank score that is correlated with the binding strength equal to or greater than the reference binding-strength amount.

13. A method for identification of a solid organ transplantation material having an HL A mismatch likely to elicit de novo donor-specific HLA antibodies (dnDSA) development in a recipient and / or for identification of impermissible HLA mismatches for solid organ transplantation in the recipient, the method comprising: carrying out a computer-implemented method for assessing a likelihood of an immune response after transplantation, wherein the immune response comprises T-cell-alloreactivity against human leukocyte antigens (HLA) that are mismatched in donor-recipient pairs, wherein each of the donor-recipient pair comprises multiple of one or more donors with one recipient, or multiple of one or more recipients with one donor, the computer-implemented method comprising:(i) HLA-typing of samples obtained from multiple potential donors and from one or more recipients and / or providing HLA typing data from the multiple potential donors and from the one or more recipients, wherein the HLA-typing is carried out on an HLA subtype comprising extracellular domain 1 and / or extracellular domain 2 of an HLA- DQB1, and generating, via a computer, a listing of mismatched HLA-DQB1 proteins in the extracellular domain 1 and / or the extracellular domain 2 between the multiple potential donors and the one or more recipients, wherein a mismatched donor- or recipientspecific HLA-DQB1 allele has at least one amino acid mismatched with both alleles of a recipient- or donor-specific HLA-DQB1, respectively;(ii) determining, via the computer, two or more core peptides for each pair of the multiple potential donors and the one or more recipients, wherein the two or more core peptides are each a donor- or recipient-specific HLA-DQB1 peptide fragment, which is predicted to bind in direct contact with a recipient- or donor- HLA-DRB 1 protein, respectively, said predicted presentation beingdetermined by the computer by determining a binding strength for binding between each of the core peptides and the HLA-DRB 1 protein; and(iii) determining, via the computer, for each pair of the multiple potential donors and the one or more recipients, a presence or absence of a categorically mismatched amino acid on an outer surface of the extracellular domain 1 of a mismatched HLA-DQB1 protein, and a presence or absence of a categorically mismatched amino acid in the core peptide at a residue position configured for interacting with a T cell receptor, wherein the categorically mismatched amino acid on the outer surface of the extracellular domain 1 of the mismatched HLA-DQB1 protein and the categorically mismatched amino acid in the core peptides at the residue positions configured for interacting with the T cell receptor are each amino acid residues of the donor-specific HLA-DQB1 protein and of the recipient-specific HLA-DQB1 protein belonging to different categorical groups of amino acids, said different categorical groups being two or more selected from a nonpolar group, a polar group, a basic group, and an acidic group, wherein: the nonpolar group consists of Alanine, Glycine, Isoleucine, Leucine, Methionine, Tryptophan, Phenylalanine, Proline, and Valine, the polar group consists of Cysteine, Serine, Threonine, Tyrosine, Asparagine, and Glutamine, the basic group consists of Histidine, Lysine, and Arginine, and the acidic group consists of Aspartic acid and Glutamic acid; wherein the solid organ transplantation material is identified as likely to elicit the dnDSA development in the recipient and / or as impermissible for the transplantation in the recipient when the categorically mismatched amino acid is present on the outer surface of the extracellular domain 1 of the mismatched HLA-DQB1 protein, the categorically mismatched amino acid is present in at least one of the core peptides at the residue position configured for interacting with the T cell receptor, AND a binding strength between the at least one of the core peptide peptides and the recipient- or donor- HLA-DRB 1 protein, respectively, is equal to or greater than a reference binding-strength amount.

14. The method of claim 13, wherein the reference binding-strength amount or greater is top 1% of binding strengths for HLA-DQ in a distribution from a plurality of random natural peptides.

15. The method of claim 13, wherein the binding strength is quantified as a rank score which normalizes a prediction score by comparing the prediction score to predictions for a set of random peptides, wherein the prediction score indicates likelihood of the core peptide to be presented by the HLA-DRB1 protein.

16. An ex vivo method of assessing likelihood of developing or having antibody -mediated rejection (AMR) in a recipient of a solid-organ allograft transplantation, wherein the recipient is positive for DQ de novo donor-specific antibody (dnDSA) after the transplantation, the method comprising: carrying out a computer-implemented method comprising:(i) HLA-typing of a sample of the allograft or from a donor of the allograft and a sample from the recipient, wherein the HLA-typing is carried out on an HLA subtype comprising extracellular domain 1 and / or extracellular domain 2 of an HLA-DQB1, and generating, via a computer, a listing of a mismatched HLA-DQB 1 protein in the extracellular domain 1 and / or the extracellular domain 2 between the allograft or the donor and the recipient, wherein a mismatched donor-specific HLA- DQB 1 allele has at least one amino acid mismatched with both alleles of a recipient-specific HLA-DQB 1 ;(ii) determining, via the computer, two or more core peptides, wherein the two or more core peptides are each a donor-specific HLA-DQB 1- derived peptides from the mismatched HLA-DQB 1 protein, which is predicted to bind in direct contact with a recipient HLA-DRB1 protein, said predicted presentation being determined by the computer by determining a binding strength between each of the core peptides and the HLA-DRB 1 protein; and(iii) determining, via the computer, a presence or absence of a categorically mismatched amino acid on an outer surface of the extracellular domain 1 of the mismatched HLA-DQB 1 protein, and a presence or absence of a categorically mismatched amino acid in at least one of the core peptides at a residue position configured for interacting with a T cell receptor, wherein the categorically mismatched amino acid on the outer surface of the extracellular domain 1 of the mismatched HLA-DQB 1 protein and the categorically mismatched amino acid in the at least one of the core peptides at the residue position configured for interacting with the T cell receptor are, each, amino acid residues of the donor-specific HLA-DQB 1 protein and of the recipient-specific HLA-DQB 1 proteinbelonging to different categorical groups of amino acids, said different categorical groups being two or more selected from a nonpolar group, a polar group, a basic group, and an acidic group, wherein: the nonpolar group consists of Alanine, Glycine, Isoleucine, Leucine, Methionine, Tryptophan, Phenylalanine, Proline, and Valine, the polar group consists of Cysteine, Serine, Threonine, Tyrosine, Asparagine, and Glutamine, the basic group consists of Histidine, Lysine, and Arginine, and the acidic group consists of Aspartic acid and Glutamic acid; wherein the recipient is indicated as likely to develop or as having the AMR when the categorically mismatched amino acid is present on the outer surface of the extracellular domain 1 of the mismatched HLA-DQB1 protein, the categorically mismatched amino acid is present in the at least one of the core peptides at the residue position configured for interacting with the T cell receptor, AND a binding strength between the at least one of the core peptide peptides and the recipient- HLA-DRB1 protein is equal to or greater than a reference bindingstrength amount, and wherein the recipient is indicated as unlikely to develop or as free from the AMR when the categorically mismatched amino acid is absent on the outer surface of the extracellular domain 1 of the mismatched HLA-DQB1 protein, the categorically mismatched amino acid is absent in the at least one of the core peptides at the residue position configured for interacting with the T cell receptor, OR the binding strength between the at least one of the core peptide peptides and the recipient- HLA-DRB1 protein is less than the reference binding-strength amount.

17. The method of claim 16, wherein the reference binding-strength amount or greater is top 1% of binding strengths for HLA-DQ in a distribution from a plurality of random natural peptides.

18. The method of claim 16, wherein the DQ dnDSA that the recipient is positive for comprises DQB1, and optionally further comprising DQA1.

19. A method for treating a solid-organ allograft recipient indicated as likely to develop or having antibody-mediated rejection according to claim 16, the method comprising: administering to the recipient an effective amount of a therapy comprising an anti-IL-6 antibody, an anti-IL-6R antibody, a Cl esterase inhibitor, eculizumab, an anti-CD20 antibody, daratumumab, a protease inhibitor, a corticosteroid, tacrolimus, mycophenolate mofetil,sirolimus, anti -thymocyte globulin, intravenous immunoglobulin, plasmapheresis, or a combination thereof.

20. A method for treating a recipient of a solid-organ transplantation material likely to elicit dnDSA in the recipient according to the method of claim 12, the method comprising: administering to the recipient an effective amount of a desensitization therapy selected from plasmapheresis, intravenous immunoglobulin, rituximab, eculizumab, an anti-IL-6 antibody, an anti-IL-6R antibody, antithymocyte globulin, or a combination thereof.

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