The HLA System in Hematopoietic Stem Cell Transplantation

Chapter 2

The HLA System in Hematopoietic Stem Cell Transplantation Effie Petersdorf1 and Ge´rard Socie´2 1

Division of Clinical Research, Fred Hutchinson Cancer Research Center, Seattle, WA, United States; 2Department of Hematology, Paris, France

Chapter Outline Introduction Classical HLA Genes Organization Classical Class I Genes Nonclassical MHC Genes: HLA-E, HLA-F, HLA-G, and MIC HLA-E Human Leukocyte Antigen G MIC Genes Class II Genes Class III Genes Nomenclature LD and Haplotypes The Role of Classical HLA in Unrelated Donor Hematopoietic Cell Transplantation

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Alleles and Antigens Additive Effects of HLA Disparity Beneficial Effects of HLA Mismatching: Graft-VersusLeukemia New Approaches for Defining Permissive HLA Mismatches Toward a Haplotypic View of Allogenecity The Clinical Significance of Nonclassical HLA Genes: HLA-E, HLA-F, HLA-G, and MIC Genes HLA-E in HCT: GVH HLA-G in HCT-GVH MIC Genes in HCT-GVH Conclusions Acknowledgments References

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The human major histocompatibility complex (MHC) is residence to the human leukocyte antigen (HLA) genes that play a fundamental role in the acceptance of transplanted tissues. The ubiquitous expression of HLA antigens on nucleated cells is a key feature of their function in both health and disease. In this chapter, the content, organization, and diversity of genes within the MHC are discussed, and the clinical implications of genetic polymorphism on risks of graft-versus-host disease (GVHD) in hematopoietic stem cell transplantation (HSCT) are summarized.

INTRODUCTION Since the discovery of the HLA system [1,2], there has been unprecedented discovery of the gene number, structure and sequences, polymorphism, haplotype composition, and linkage disequilibrium (LD) within the major histocompatibility complex (MHC) [3]. More than 300 genes reside within the MHC, and of these, approximately 15%e20% have immunerelated function including antigen processing and presentation, immune regulation, inflammation, complement, maternalfetal immunology, stress response, leukocyte maturation, and the immunoglobulin superfamily [3]. New information on the regulatory polymorphisms is emerging from efforts of the Human Epigenome Project and provides insight into methylation and histone acetylation profiles within the MHC [4,5].

Immune Biology of Allogeneic Hematopoietic Stem Cell Transplantation. https://doi.org/10.1016/B978-0-12-812630-1.00002-5 Copyright © 2019 Elsevier Inc. All rights reserved.

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Immune Biology of Allogeneic Hematopoietic Stem Cell Transplantation

CLASSICAL HLA GENES Organization The MHC is composed of three regions termed class I, class III, and class II (Fig. 2.1). The HLA system includes the classical loci HLA-A, HLA-C, and HLA-B and the nonclassical genes HLA-E, HLA-F, HLA-G, MICA, and MICB that reside within the class I region. HLA-DR, HLA-DQ, and HLA-DP reside within the class II region. The class III region comprises genes of importance to the stress response (TNF, HSP, LTA) and the complement cascade.

Classical Class I Genes Class I HLA-A, -B, and -C genes are each composed of a series of eight exons delineated by intervening introns. Each class I exon has a unique function: exon 1 encodes the leader sequence; exons 2, 3, and 4 encode the a1, 2, and 3 domains, respectively; exon 5 encodes the transmembrane portion, and exons 6, 7, and 8 encode the cytoplasmic tail. These products give rise to the “heavy” a chain of the mature HLA class I molecule and define the HLA phenotype (e.g., HLA-A1 or HLA-A2). The heavy chain is noncovalently bound to a b2-microglobulin “light” chain whose gene resides on chromosome 15. The delineation of the crystallographic structure of HLA-A2 in 1987 was pivotal to understanding the structureefunction relationship of MHC molecules. Those landmark studies revealed that class I molecules are composed of two a-helical regions that overlay an eight-stranded antiparallel b-pleated sheet; together, these form the functional groove of class I molecules for peptide binding [6]. Sequence variation in exons 2, 3, and 4 define the allospecificity of HLA-A, HLA-B, and HLA-C antigens, respectively. As of June 2017, over 3913 HLA-A, 4765 HLA-B, and 3510 HLA-C alleles are recognized by the World Health Organization Nomenclature Committee for Factors of the HLA System [7,8]. The nucleotide substitutions in exons 2, 3, and 4 are commonly observed at hypervariable positions that define the peptide-binding groove and T-cell receptor (TCR) contact residues of the a1 and a2 domains [9]. In addition to interactions with the TCR, HLA-C and some HLA-B and HLA-A molecules serve as ligands for natural killer inhibitory receptors (KIRs). The specificity of ligandereceptor interactions is defined by residues 77e80 for HLA-C and by residues 77e83 (the Bw4 epitope) for HLA-B.

Nonclassical MHC Genes: HLA-E, HLA-F, HLA-G, and MIC In addition to the classical class I HLA loci, the class I region of the MHC encodes a series of genes that are termed the “nonclassical” class I genes, HLA-E, HLA-F, HLA-G, and the MHC class Ierelated chain A and B genes (MICA and MICB, respectively). Known as the class 1b family [10], these genes share homology but differ with respect to their specific regulation, expression patterns, and epigenetic profiles. A role of MICA ligands in transplantation outcome has recently been elucidated (Table 2.1).

HLA-E HLA-E is an extensively studied MHC class Ib antigen. In contrast to the exceptional diversity of classical MHC class I HLA-A, HLA-B, and HLA-C genes, HLA-E encodes 18 recognized proteins, with HLA-E*01:01 and HLA-E*01:03 the most frequently observed alleles worldwide [8]. HLA-E*01:03 differs from HLA-E*01:01 by a single amino acid substitution (gly to arg) at position 107 of the a2 heavy chain domain [8]. Although the two alleles appear to be evenly distributed in the human population (approximately 50% each), they differ with respect to their quantitative cell surface expression. HLA-E*01:03 is expressed at higher concentration on transfected cells compared to HLA-E*01:01 [11]. The HLA-E molecules preferentially bind nonameric self-peptides derived from the leader sequences of the various HLA class I

FIGURE 2.1 Map of the human major histocompatibility complex (MHC). The MHC is encoded on chromosome 6p21 and is organized into three major regions: class I, class III, and class II. The figure shows the location of each of the classical and nonclassical HLA genes that have been described as playing a role in hematopoietic cell transplantation. HLA, human leukocyte antigen.

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TABLE 2.1 The Role of MHC Genes in Hematopoietic Cell Transplantation Mismatched Locus

Survival

GVHD

HLA-A

Y

[

[68,69,71e73,80,81,83,86]

HLA-B

Y

[

[68,69,71e73,80,81,83,85,86,107,108,112]

HLA-C

Y

[

[68,69,71,73,80e83,86,87,108,112,129]

HLA-DRB1

Y

[ [

HLA-DPB1

Relapse

References

[68,69,71e73,80,83,86,88,90,114] Y

[69,74e78,114e126,130]

HLA-E*

Y

[

[152e158]

HLA-G*

Y

[

[160e162,174e177]

[

[178,179,181,182]

MICA*

GVHD, graft-versus-host disease; HLA, human leukocyte antigen; MHC, major histocompatibility complex.

molecules. HLA-E also presents noncanonical peptides derived from pathogens or stress-related proteins. Overall, the HLA-E/peptide complexes differ in thermal stability [12]. As a ligand for the CD94/NKG2 receptors on NK cells [13] and for the TCR on NKT cells, HLA-E molecules are involved in both innate and adaptive immunity. Recent evidence supports a role for the involvement of HLA-E in presentation of peptides to the ab TCR expressed on CD8þ T cells. The HLA-E CD94/NKG2 A/C system modulates either inhibition or activation of the NK cellemediated cytotoxicity and cytokine production; at the same time, HLA-E can present microbial-derived peptides from human viruses or bacteria, thereby inducing T-cell responses. These diverse roles highlight the importance of HLA-E molecules as restriction elements for the specific T-cell responses against pathogens such as CMV, EpsteineBarr virus (EBV), or mycobacteria (Mycobacterium tuberculosis) [14e16]. In the same way, the Qa-1 molecule, a murine counterpart of the human HLA-E, has been shown to bind and present an immunodominant peptide recognized by salmonella-specific CD8þ T lymphocytes (CTL) and also participates in the host response against Listeria monocytogenes.

Human Leukocyte Antigen G The human leukocyte antigen G (HLA-G) is a nonclassical HLA class Ib locus whose products have distinct immunomodulatory, anti-inflammatory, and tolerogenic properties. HLA-G maps telomeric to HLA-A (Fig. 2.1). Although HLA-G molecules are structurally similar to their classical counterparts, they are distinguished by their limited tissue distribution in physiological conditions, the diversity of isoforms generated by alternative splicing (four membrane-bound [HLA-G1 to G4] and three soluble [HA-G5 to G7] isoforms [sHLA-G]) [17e19], and their unique pattern of polymorphisms in the noncoding regions, especially within the promoter and the 30 -untranslated region (30 UTR; [20]). To date, HLA-G alleles encode a limited number of exonic mutations; these polymorphisms are often silent mutations that result in 53 unique alleles that give rise to 18 protein variants [8]. HLA-G allele frequencies vary extensively between Caucasian, Asian, and African populations. HLA-G mediates immune responses of NK and T lymphocytes by interacting directly with a series of inhibitory receptors: KIR 2DL4 (CD158d) on NK and a subpopulation of T cells; ILT2 (CD85j) on T, B, NK, dendritic cell (DC) and monocytes, and ILT4 (CD85d) expressed exclusively on antigen presenting cells. HLA-G expression is regulated by variation within its 50 and 30 untranslated regions [21e23]. Furthermore, each HLA-G allele bears either a 14-base pair (bp) insertion (ins) or deletion (del) polymorphism in the 30 UTR which influences HLA-G expression through the shortening of exon 8 [24,25]. Such indels have functional consequences. The insertion allele (þ14 bp), albeit initially described to increase HLA-G mRNA stability, was subsequently correlated with lower levels of HLA-G mRNA and serum sHLA-G isoforms [25,26] with likely functional consequences on the properties of HLA-G molecules. Most recently, the rs1063320 single nucleotide polymorphism (SNP) has been shown to regulate HLA-G expression and correlate with disease risk [23,27e29]. Cell surface HLA-G was first found on cytotrophoblasts and shown to maintain fetalematernal tolerance, and it has been the maternalefetal tolerance model in which HLA-G has been studied most extensively [30,31]. HLA-G is also physiologically expressed on CD14þ monocytes and thymic epithelium. Overall, HLA-G molecules are involved in the

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inhibition of NK cell activity, CD4þ T lymphocyte and DC maturation, apoptosis of CD8þ cytotoxic T cells (CTL), and development of regulatory T cells (Tregs). A role of HLA-G in both T and NK pathways has been studied in models of cancer, transplantation, and autoimmunity [19,20,32e35].

MIC Genes The MIC gene family comprises two expressed genes (MICA and MICB) and five pseudo genes (MICC, MICD, MICE, MICF, and MICG) [36]. Located at the centromeric end of HLA classical class I region, MICA maps approximately 46 kb from HLA-B. MICA is the most polymorphic nonclassical class I gene with over 106 alleles and 82 recognized proteins reported so far [8]. A distinguishing feature of MICA sequence variation is the presence of polymorphism in both the a2 and the a3 domains. In fact, none of the polymorphic residues of MICA correlate with those of the a1 and a2 domains of classical class I molecules, the latter of which contact the antigenic peptide and/or TCR. Overall, the significance of most MICA/B polymorphisms remains to be elucidated in terms of their ancestral origins and evolution. It is suggested that, based on the a3 domain polymorphisms, MICA alleles can be divided into two large families that might have evolved from two different ancestral lineages. From a functional point of view, a methionine (met) to valine (val) change at position 129 of the a2-heavy domain categorizes MICA alleles into strong (MICA-129 met) and weak (MICA-129 val) binders of the NKG2D receptor involved in activation and costimulation of NK and T cells [37]. Another level of diversity has been identified in the transmembrane (TM) region of MICA with the insertion of short tandem repeats (STRs) that result in a series of alleles (A4eA10). In addition, a nucleotide insertion (GCT / GGCT) in the TM region of the A5.1STR allele results in a premature stop codon. This sequence is present in MICA*008, the most frequent MICA allele described in various populations. Although similar in structure to an HLA class I heavy chain, MICA does not bind b2 microglobulin or any specific peptide. Therefore, MICA molecules are not involved in TCR-mediated immunity but rather engage NKG2D, a C-type lectin expressed on effector cells, including NK and ab- and gd-T cells [38e44]. Such engagement triggers NK cells and costimulates T lymphocytes to mount subsequent immune responses. Furthermore, a soluble isoform of MICA (sMICA), resulting from the proteolytic shedding of the membrane-bound molecules, was shown to result in NKG2D receptor downregulation. The ensuing immune modulation highlights the functional duality of the membrane-bound and soluble MICA isoforms. MICA expression is induced by cellular stress [45]. Preferentially expressed on epithelial and endothelial cells, MICA and MICB appear more ubiquitous at the mRNA level. Expression has also been reported in activated immune cells including DCs and T lymphocytes. The specific patterns of expression of MICA/B are related to the regulatory sequences that are devoid of interferon response elements, while a stress response element has been identified in the promoter region [46].

Class II Genes Historically the class II region has been known as the “HLA-D” region following the characterization of HLA-A, HLA-B, and HLA-C. The class II region has since been extensively sequenced, and its organization has been well defined in many populations [3]. Not only does the class II region encode genes that define the classical HLA-DR, HLA-DQ, and HLA-DP alloantigens, but also it contains genes that play a critical role in antigen loading and presentation (TAP and LMP); the concentration of genes with related function make class II a truly unique region of the human genome. The specific genes that define class II phenotypes are DRA1 and DRB1 (HLA-DR), DRB3 (HLA-DR52), DRB4 (HLA-DR53), DRB5 (HLA-DR54), DQA1 and DQB1 (HLA-DQ), and DPA1 and DPB1 (HLA-DP). The A genes (DRA1, DQA1, and DPA1) each encode the a chain of the mature class II molecule and have limited sequence diversity. The B genes (DRB1, DQB1, and DPB1) are each defined by a highly polymorphic exon 2 that gives rise to the b chain of the molecule. The a chain is noncovalently bound to the b chain [47]. The a-b heterodimer defines the phenotype of the antigen (e.g., DR1 or DQ2), with the b chain contributing the majority of the polymorphism that distinguishes unique allelic variants. The “supratypic” loci, DRB3, DRB4, and DRB5, are highly organized on DRB1 haplotypes, such that certain DRB1 genes have DRB3, DRB4, or DRB5 genes linked to their haplotype, whereas other DRB1 genes have no additional supratypic loci. In summary, DR1 and DR10 phenotypes have no additional supratypic gene; DR2 phenotypes have DRB5 that defines DR52; DR3, DR5, and DR6 have the DRB3 gene that defines the DR53 specificity, and DR4, DR7, and DR9 have the DRB4 gene that defines the DR54 specificity. Since a variable number of DRB genes are linked on haplotypes, different haplotypes have different lengths within the class II region. Yet another source of potential variation arising from

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class II is contributed by DQA1 and DQB1. Trans pairing of DQ a encoded by one parental chromosome with a DQ b encoded by the other parental chromosome can give rise to up to four unique HLA-DQ antigens [48]. Like class I genes, HLA-DRB1, HLA-DQB1, and HLA-DPB1 genes are highly polymorphic, with more than 2311 HLA-DRB1, 1079 HLA-DQB1, and 828 DPB1 alleles recognized as of June 2017 [7,8]. Also similar to class I, the polymorphic sites within class II molecules are localized to discrete regions of the a1 and b1 domains of the a and b chains, respectively, to promote a large array of peptides that can be presented [9,49].

Class III Genes The Class III region resides in between class I and II and is now known to be the most gene-dense region of the entire human genome [50,51]. Importantly, the class III region displays strong positive LD with HLA class I loci to its telomere and with class II loci to its centromere; this LD is what characterizes the highly conserved “ancestral” haplotypes that have been defined in many human populations [52]. The class III region harbors genes that participate in the stress response, several of which have been found to influence risk of GVHD after allogeneic transplantation [53e55].

NOMENCLATURE The application of DNA-based methods for typing HLA genes has resulted in the discovery of novel alleles at an extraordinary rate [7,8]. To accommodate new sequence information, HLA nomenclature was recently modified using a naming system that offers unlimited numerical digits. The nomenclature captures four properties of sequences, in the following order: the serological equivalent of the allele, the unique sequence that gives rise to the unique protein, synonymous (silent) substitutions, and level of expression of the molecule. Each of these four characteristics is delimited by a colon (:). Using HLA-A*02:101:01:02N as an example, this name provides information on the serological specificity (02), the unique sequence (101), the synonymous substitution (01), and the null allele (02N). Additional letter suffixes denote proteins whose expression is low (L), soluble (S), aberrant (A), or whose product is cytoplasmic (C), or of questionable expression (Q).

LD and Haplotypes A hallmark of the MHC is its long-range positive LD, a mathematical measurement of two or more markers that have a higher observed frequency than would be predicted by their individual allele frequencies [56,57]. LD across the MHC demonstrates that occurrence of HLA tissue types is not random [52]. Linked HLA genes are inherited from each parent as a haplotype in classical Mendelian fashion. “Ancestral” haplotypes represent highly conserved HLA-A, HLA-B, HLA-DR haplotypes that display conservation for “blocks” or stretches of sequences in the class I, III, and II regions [52]. In disease mapping, haplotypes serve as proxies for ungenotyped markers because haplotypes define not one but many physically linked markers. In hematopoietic cell transplantation from unrelated donors, LD can both help and hinder the identification of suitable donors. In general, the probability of identifying an HLA-matched donor is higher when the patient and donor share a similar ethnic background [58e62]. When high LD exists, such as with the HLA-A1, -B8, -DR3 haplotype, the probability of finding donors with the same genotype is very high; when a patient has inherited a maternal or paternal recombination event, however, LD is disrupted, and the likelihood of identifying matched donors will then depend on the frequency of those alleles and antigens in the donor pool [63,64]. This is the case even for patients of European Caucasian background. In a recent analysis by the National Marrow Donor Program (NMDP), the overall rate of donorerecipient matching for HLA-A, HLA-B, HLA-C, HLA-DRB1, and HLA-DQB1 alleles was higher for Caucasian-Americans than for patients of all other races and ethnicities [65]. The likelihood of a patient identifying a donor with one HLA mismatch at either HLAA, HLA-B, HLA-C, or HLA-DRB1 was also higher for Caucasian-American patients but significantly increased the chances that a patient of non-Caucasian background could find an acceptable donor for transplantation [66]. These data suggest that understanding the properties of HLA mismatch combinations that are not associated with higher transplantrelated risks remains an important research effort so that more patients can benefit from transplantation.

THE ROLE OF CLASSICAL HLA IN UNRELATED DONOR HEMATOPOIETIC CELL TRANSPLANTATION The degree of HLA matching at the DNA or allele level is one of the strongest factors for transplant success [67e71]. Based on extensive worldwide data, HLA matching of the patient and the unrelated donor for HLA-A, -C, -B, -DRB1,

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Immune Biology of Allogeneic Hematopoietic Stem Cell Transplantation

and -DQB1 alleles is associated with lower posttransplant risks and higher survival compared to mismatching [68,71e73]. Recent data support the prospective typing and matching of HLA-DPB1 to lower risks of GVHD [74e78]. Inclusion of HLA-DPB1 in standard HLA typing gives rise to 6 HLA loci, 12 determinants, and “12/12” matching with the patient and unrelated donor are HLA-A, HLA-B, HLA-C, HLA-DRB1, HLA-DQB1, HLA-DPB1 matched.

Alleles and Antigens Clinical practice in unrelated donor transplantation has mirrored the advances in HLA typing methodology over the past 4 decades. Antigens are defined by serological reagents in microcytotoxicity assays [79]. Alleles are defined by DNA-based methods that permit ascertainment of selected nucleotide positions of exons or full-length sequences. Since the definition of alleles and antigens is, in part, methodological, intense efforts have been made to determine whether there are biological differences associated with HLA mismatches that are detectable using serology (“antigen-level” or “low-resolution” mismatches) apart from mismatches that can only be detected using DNA-based methods (“allele-level” or “highresolution” mismatches). With the availability of molecular typing assays, it was appreciated that among phenotypically matched patients and unrelated donors, DNA-based typing methods can detect allelic differences that are clinically relevant [68,72,80e83]. One of the earliest demonstrations that alleles can be highly immunogenic came from observations in the setting of graft rejection after transplantation of a B*44:03 donor for a B*44:02 patient [84]. Donor-derived cytotoxic T lymphocytes could selectively recognize the patient’s HLA-B*44:02 allele. Following this report, the application of molecular methods was used to identify HLA-C allele mismatching and its role in graft failure [85]. These early studies firmly placed DNAbased typing methods at the forefront of clinical testing. Subsequently, large retrospective analyses have extended those findings to other HLA loci [68,71]. In a study from the NMDP-CIBMTR [68], survival was decreased by 10% for each mismatched HLA-A, HLA-B, HLA-C, or HLA-DRB1 locus. Allele mismatches were as detrimental as antigen mismatches with the exception being HLA-C, where antigen mismatches were more detrimental than allele mismatches. In peripheral blood stem cell transplantation [86], pronounced differences in mortality among patients mismatched with their donors for alleles versus antigens were found for HLA-C, but not for other loci. HLA-C has served as an important model for understanding differential risks conferred by allele and antigen mismatches [68,72,81,85]. Since its discovery as a classical transplantation antigen [87], donor mismatching for HLA-C has consistently been shown to be a risk factor after myeloablative, nonmyeloablative, unrelated donor, cord blood, marrow, and peripheral blood stem cell transplantation. In the era of growth factoremobilized peripheral blood stem cell transplantation, the potential effects of HLA disparity on outcome have been reassessed [86]. In a large retrospective analysis of HLA-A, -C, -B, -DRB1 alleleematched transplants, “8/8” donor matching was associated with improved 1-year survival compared to any single mismatch (“7/8”). Clinical differences in risks associated with HLA-C antigen versus HLA-C allele mismatches were observed. Specifically, donor HLA-C antigen mismatching was associated with the worst outcomes compared to HLA-A, -B, or -DRB1 mismatching. Whereas HLA-C antigen mismatching was associated with increased mortality, lowered disease-free survival, and increased grades IIIeIV acute GVHD, HLA-C allele mismatches did not increase risks. HLA-B allele or antigen mismatches were associated with GVHD; there were no statistically significant associations of HLA-A, -DRB1, or -DQB1 mismatches with transplant outcomes. These data suggest that for peripheral blood stem cell recipients, criteria for the selection of mismatched donors may not necessarily be the same as that for marrow sources. Future studies are warranted to fully evaluate the clinical significance of the stem cell source on the risks conferred by specific loci and resolution of donor matching.

Additive Effects of HLA Disparity A step-up of risks associated with increasing numbers of HLA mismatches is in keeping with a biological model for alloreactivity. Such multilocus mismatch effects have been observed in graft failure, GVHD, and mortality [68,72,81,83,85,88e91]. Clinical evidence demonstrating the deleterious nature of multilocus mismatching has led to the current practice of limiting the total number of HLA mismatches to one [67,69,70,74,78,85,92]. The impact of mismatching at a single HLA locus also depends on nongenetic factors that influence transplant outcome. Of these nongenetic factors, the stage of disease at the time of transplantation remains a strong factor for risk of disease recurrence and survival. Among good (low)-risk patients, the risks associated with donor HLA mismatching appear to be higher than those in patients with high-risk disease [68,88]. These observations are likely due to the cumulative effects of genetic and

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nongenetic factors. Given the importance of an efficient search [93,94], careful consideration should be taken for extending a search when no HLA-matched donors are available. Not only is the total number of HLA mismatches an important determinant of risks, but the specific combination of mismatched loci can also define relative risks [68]. The criteria for prioritizing the selection of mismatched donors indicate that of all the classical HLA loci, an isolated HLA-DQB1 mismatch is better tolerated than mismatching at HLA-A, -C, -B, or -DRB1 [68,71]. Recently, the JMDP analyzed the effect of single DRB1, single DQB1, and two-locus DRB1/DQB1 mismatches; whereas single-locus mismatches did not increase risk, two-locus mismatches were associated with significantly inferior overall outcomes [69]. HLA-C disparity in the presence of mismatching at any other HLA locus (class I and/or class II) is associated with significantly increased incidence of grades IIeIV acute GVHD [72]. In the Japanese experience, HLA-C allele mismatching was an independent risk factor for severe acute GVHD. Lower rates of relapse among patients with GVHD were observed (the “graft-versus-leukemia effect” or GVLE as described below); when HLA-C mismatching occurred together with HLA-A, -B, -DR, or -DQ mismatching, survival was significantly lower.

Beneficial Effects of HLA Mismatching: Graft-Versus-Leukemia The lower risk of relapse observed in patients with GVHD is known as the graft-versus-leukemia effect [95e98]. Data demonstrate that of all the HLA loci, HLA-C and HLA-DPB1 mismatches are most strongly associated with graft-versusleukemia (GVL) [69], suggesting that not all allotypes can impart equivalent GVLE. In vitro data support the powerful GVLE of HLA-DPB1 allotypes [99] and the potential to harness this effect clinically to lower posttransplant disease recurrence.

NEW APPROACHES FOR DEFINING PERMISSIVE HLA MISMATCHES The feasibility of identifying HLA-matched donors depends on the HLA alleles, antigens and haplotypes of the patient, along with the size and composition of donor registries [58,61,100e106]. However, since every patient has a mismatched donor, intense efforts have been made to determine the characteristics of HLA mismatches that do not increase posttransplant risks (“permissive” or “tolerable” HLA mismatches). There are two models for permissive HLA mismatching that have substantial independent validation to support their use clinically: mismatching at key residues or epitopes of class I and II allotypes, and the level of HLA expression. The basis for the residue approach is the potential that certain HLA mismatches may be matched at key residues that define the peptide-binding grove of HLA molecules and that matching for such residues may be associated with lower risks than HLA mismatches that involve mismatching at key residues. Among the earliest studies, donorerecipient mismatching for residue 116 of HLA-B was significantly associated with increased risk of acute GVHD and transplant-related mortality [107]. In more recent analyses, donorerecipient mismatching for Tyr9ePhe9 of HLA-A and for Tyr9eSer9, Asn77e Ser77, Lys80eAsn80, Tyr99ePhe99, Leu116eSer116, and Arg156eLeu156 of HLA-C were identified in Japanese patients to be associated with increased risk of acute GVHD [108]. Since HLA-C serves as a ligand for the natural KIR (refer to section below), HLA-C mismatched pairs were further evaluated for the presence of residues that could be associated with GVHD risk beyond the two positions that define KIR receptor binding (positions 77 and 80); donore recipient mismatching at positions 9, 99, 156, and 163 strongly correlated with GVHD risk. In a subsequent analysis, certain HLA-C and HLA-DPB1 mismatch combinations were associated with both relapse and GVHD [109]. This study demonstrates that risks are not necessarily the same for every HLA mismatch; future studies are needed to separate mismatch combinations involved in GVL from those influencing GVHD. To this end, the use of statistical and structural modeling has been explored to identify HLA alleles with diverse peptide-binding repertoires [110,111]. Most recently, donorerecipient mismatching at residue 116 of class I was validated to be a risk factor for mortality [112]. HLA-DP has served as a model locus for understanding the immunogenicity of residue mismatching by way of in vitro cytotoxicity assays to identify the most immunogenetic epitopes [74,113]. Population studies have shown that HLA-DP is unique among other HLA genes because of very weak LD between HLA-DP and HLA-A, HLA-B, HLA-C, HLA-DR, and HLA-DQ. As a result, less than 20% of HLA-A, HLA-B, HLA-C, HLA-DRB1, and HLA-DQB1-matched unrelated donor pairs are also matched for HLA-DP. Retrospective examination of HLA-DP has required very large transplant populations so that sufficient numbers of HLA-DP-matched pairs can be compared with mismatched pairs [114e119]. Furthermore, the measured effects attributed to single loci in early studies likely measured additive effects of HLA-DP with HLA-A, HLA-B, and HLA-DR. HLA-DP does function as a classical transplantation antigen with respect to GVHD [117e119].

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Mismatching for two DPB1 alleles increases the risk of acute GVHD compared to one or no HLA-DP mismatch [74]. More recent genome-wide association studies have validated HLA-DP as a classical transplantation determinant [75,77]. Given that 80% of HLA 10/10 allele matched donors are DPB1-mismatched, the frequencies suggest that for patients with common HLA haplotypes who can identify several HLA-A, HLA-C, HLA-B, DRB1, DQB1-matched donors, one of five donors could be DPB1-matched. Hence, the patients who are likely to benefit from prospective evaluation of DPB1 are patients who have common HLA haplotypes and for whom transplantation is not urgent. Considering that every patient has a DPB1-mismatched donor, studies have addressed whether all DPB1 mismatches are equally detrimental. These analyses have focused on the identification of donorerecipient mismatching at specific T-cell epitopes (TCEs) defined by exon 2 sequence variation, that are most closely associated with GVHD risk [120e123]. Using T-cell clones to identify DPB1 alleles that generate high cytotoxic potential, a schema for predicting high immunogenetic combinations of DPB1 alleles is possible. The TCE model has been independently validated in a large cohort of HLA-matched and -mismatched unrelated donor transplants from the International Histocompatibility Working Group in HCT as a clinically practical approach for selecting DPB1-mismatched donors whose mismatch may not increase risks [123]. The study furthermore demonstrates that the presence of permissive DPB1 mismatches in HLA-A-, HLA-C-, HLA-B-, DRB1-, or DQB1-mismatched transplants, may afford comparable outcomes with those observed after HLA 10/10-matched nonpermissive DPB1 mismatches. These data collectively suggest that when HLA 10/10-matched donors are not available, DPB1 typing and selection of TCE permissible donors may afford these patients similar favorable outcomes as a traditional HLA 10/10-matched transplant [120e126]. The second model for identifying permissive HLA mismatches focuses on the level of HLA expression of the patient’s mismatched HLA allotype that is recognized by the donor as foreign. Allotype-specific HLA-C expression has been elegantly demonstrated in cohorts of patients with HIV-AIDS and hepatitis [127,128]. In both scenarios, higher HLA-C expression is associated with lower progression to HIV-AIDS, and higher HLA-DP expression is associated with lower progression of hepatitis viremia. Recently, the impact of level of HLA-C and HLA-DP expression on GVH recognition was explored in two independent cohorts. Among unrelated donor transplants mismatched for a single HLA-C allotype, GVHD risk increased as the mean fluorescence intensity of the patient’s mismatched HLA-C increased [129]. Among HLA-A-, HLA-B-, HLA-C-, HLA-DRB1-, HLA-DQB1-matched unrelated donor transplants with a single HLA-DPB1 mismatch, mismatching against a high-expression HLA-DPB1 recipient allotype was associated with significantly increased GVHD [130]. Both the HLA-C and the HLA-DP models demonstrate that quantitative as well as qualitative differences between HLA-mismatched allotypes contribute to graft-versus-host allorecognition.

TOWARD A HAPLOTYPIC VIEW OF ALLOGENECITY HLA haplotypes represent a series of HLA genes and other loci that are physically linked on the same chromosomal strand (Fig. 2.1). The HLA region has served as a model for understanding patterns of LD [5,52,131e139]. HLA haplotypes are characterized by conserved “blocks” of genes and sequences of variable lengths [52]. This block-like structure distinguishes “ancestral” haplotypes that carry HLA-A, HLA-C, HLA-B, HLA-DRB1, and HLA-DQB1 alleles in strong positive LD with one another, and with key markers that reside in between the classical HLA loci [52]. Since the five classical HLA loci represent a fraction of the total gene content of the MHC [3], undetectable haplotypelinked variation could be responsible for increased risks after HLA-matched unrelated donor transplantation. Early observations pointed to donor-recipient disparity for variation that resides outside of the classical HLA loci [140,141]. In the DNA typing era, even with HLA 10/10 allele matching of unrelated donors, patients are at increased risk of GVHD and mortality. Since HLA-matched patients and unrelated donors are not identical by descent, it is possible that patient and donor HLA-A, HLA-B, and HLA-DR haplotypes are not the same. Using a patient and donor who are both HLA-A1,2/ B7,8/DR2,3 matched as an example, the HLA-A antigen could be linked to different HLA-B/DR antigens: A1/B8/DR3, A2/B7/DR2, A2/B8/DR3, and A1/B7/DR2. To test the hypothesis that HLA-A, HLA-B, HLA-DR-defined haplotypes can serve as markers for undetected linked genes that confer clinical effects, a novel method for phasing HLA alleles was developed to physically separate the two HLA haplotypes [142]. Application of the phasing method to HLA 10/10 allelematched unrelated patients and donors has revealed that a subset of identical pairs encode different HLA-A, HLA-B, HLADR haplotypes [143]. Patients transplanted from HLA-matched but haplotype-mismatched donors had significantly increased risk of severe acute GVHD. These observations suggest that there are undetected differences contributed by different haplotypes. What are the candidates within the MHC that could be responsible for GVHD risk? Microsatellite markers have been instrumental in probing the gene-dense MHC region for potential areas that harbor new transplantation determinants [144]. One of the earliest studies to define susceptibility genes was conducted in a Japanese population using microsatellite

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markers to query the MHC [145]. Among patients who developed clinical acute GVHD, variation within the TNF complex was associated with lower survival. The importance of TNF polymorphisms has recently been confirmed in a study of Caucasian patients and transplant donors [54]. Microsatellites were used to define TNF alleles in HLA 10/10-matched transplant pairs. The pairs were further defined by their HLA-DPB1 match status. The presence of DPB1 mismatching concurrent with TNFd alleles was associated with increased GVHD risk and poorer overall outcome compared to their absence. This study suggests that variation within the class III TNF-defined region has clinical relevance. Furthermore, negative additive effects can be measured at both the TNF and the DP loci. The application of microsatellite markers paved the way for the use of state-of-the-art SNP platforms to understand haplotype content [146]. In a recent study by the Japanese Marrow Donor Program [147], HLA 10/10-matched patientedonor pairs were characterized using an SNP-based genotyping platform. Three high-frequency Japanese haplotypes were fully characterized for SNP content and LD. Interestingly, the Japanese patients and donors displayed a very high degree of SNP conservation across the MHC and precluded an analysis of the effect of SNP mismatching. However, a high frequency of HLA homozygosity permitted the presence of certain haplotypes to be analyzed for associated transplant risks. Three major haplotypes were identified, each having a different association to posttransplant complications. This study highlights the fundamental role of haplotypes and their associated variants in transplant outcome. In North American transplants, SNPs have been used to identify candidate regions for fine-mapping genes that influence clinical outcome after unrelated donor HCT. SNPs have been identified as markers for susceptibility genes in the class I and II regions in HLA-matched unrelated donor transplants [148]. In HLA-mismatched transplantation, candidate SNP markers provide a means to interrogate the gene-dense MHC for an efficient approach to identifying novel genes encoded on HLA haplotypes responsible for GVHD and mortality [149]. Future efforts to identify clinically relevant MHC region variants will be facilitated by the availability of nextgeneration sequencing methods [150]. Next-generation sequencing technology may permit phase to be established between markers and will significantly advance understanding of HLA haplotype content. The diversity of haplotypes in certain populations may permit donorerecipient mismatching of non-HLA variants to be more fully defined. The characterization of both common and rare haplotypes for the entire MHC region will greatly facilitate mapping efforts to localize novel transplantation determinants.

THE CLINICAL SIGNIFICANCE OF NONCLASSICAL HLA GENES: HLA-E, HLA-F, HLA-G, AND MIC GENES The measurement of transplant-associated risks conferred by the nonclassical HLA genes has been successful in selected sibling cohorts that limit the confounding effects of the classical HLA genes; however, due to the inherent long-range LD of the MHC, the number of sibling transplant pairs required to analyze the differential effect of the nonclassical HLA genes is necessarily high to reach sufficient statistical power [55,151].

HLA-E IN HCT: GVH As described previously, HLA-E can participate in the innate and adaptive immune pathways and has been studied as a transplantation determinant in related and unrelated donor transplantation [152e156]. The effect of HLA-E*01:03 homozygosity was first assessed in a cohort of 187 HLA-matched genotypically identical siblings from a single institution and revealed a protective effect for acute GVHD and transplant-related mortality (TRM) [152]. Patients with HLAE*01:01,01:01 or 01:01,01:03 genotypes showed a higher incidence of acute GVHD compared with patients with the HLA-E*01:03,01:03 genotype. This protective role was subsequently confirmed [154]. Similarly, a significant reduction of TRM was associated with HLA-E*01:03 homozygosity in a cohort of 83 related and unrelated HLA-matched transplants and translated into better overall survival [157]. The role of the HLA-E was confirmed in a study on 124 patients receiving an unrelated donor HCT, showing a decreased risk of acute GVHD, but no effect on survival [153], while in another study of 116 HLA-matched unrelated donor transplants, HLA-E polymorphism did not influence acute GVHD, TRM, or diseasefree survival [156]. The number of confounding factors is likely to be higher in unrelated donor than in sibling HCT and may very well explain the heterogeneous results in the two most recent studies. Interestingly, combined data from siblings and unrelated donor marrow transplants suggest a potential paradigm of an HLA-E*01:03 molecule that may present minor histocompatibility antigen peptides inefficiently without inducing T-cell recognition, while HLA-E*01:01 displays a lower capacity to present nominal antigen from pathogens [158]. More functionally integrated data are needed to elucidate and quantify the impact of HLA-E on GVH and overall in HCT outcomes. In addition, identification in renal transplantation of

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anti-HLA-E antibodies that account for nonedonor-specific antibodies and correlate with lower graft survival may well have to be taken into account in the near future in HCT [159].

HLA-G IN HCT-GVH The pleiomorphic role in modulating immune responses justifies the interest of studying the HLA-G system in HCT both at genetic and functional pathophysiological levels [160e175]. The first study of HLA-G in transplantation was performed in 53 HLA-matched unrelated donor transplants for b thalassemia and found that the HLA-G 14-bp deletion polymorphism correlated with acute GVHD. While the acute GVHD risk associated with the HLA-G 14-bp del/del genotype [160] appears to be in contradiction with the established fact that the 14-bp del allele is associated with higher levels of sHLA-G than the 14-bp ins allele, the mechanism leading to clinical acute GVHD could however be different in the unrelated donor transplant situation. Because the HLA-matched unrelated donorerecipient pairs are not identical by descent, it could be possible that the HLA-G 14-bp del/del genotype may reflect the MHC non-HLA haplotype disparity. More recently, an analysis of 47 transplant patients with a variety of hematological malignancies failed to observe any significant association between the HLA-G 14-bp ins/del polymorphism and acute GVHD [161] but found that patients homozygous for the 14-bp ins allele were characterized by lower survival rate and disease-free survival. The authors related their findings to the possible relationship between HLA-G 14-bp dimorphism, methotrexate (MTX)-based acute GVHD prophylaxis and HLA-G expression. By contrast, in a recent series of 157 sibling pairs from a single institution, the HLA-G low expression genotype (ins/ins) was associated with severe acute GVHD [162]. In this study, the donorerecipient sibling pairs were fully matched for HLA-G genotypes with frequencies comparable to those previously reported. Univariate analysis using competing risk showed that the homozygous state of the HLA-G 14-bp ins/ins genotype was more prevalent among patients who experienced acute GVHD (grade 0, vs. II, III, IV) but failed to reach statistical significance (P ¼ .06). Nevertheless, additional univariate analyses after patient stratification based on acute GVHD severity (grade 0, I, II, vs. III, IV) revealed a significant association between the HLA-G 14bp ins/ins genotype and severe acute GVHD (22% in HLA-G 14-bp ins/ins vs. 6% in other; P ¼ .008). These data were further confirmed using two different multivariate analyses adjusted for confounding variables (gender, CMV status, age of recipient, and disease status). The only factor that remained statistically significant was the HLA-G 14-bp ins/ins genotype. Given the potential effect of MTX on HCT outcome in the context of HLA-G polymorphism [161], the subgroup who received this drug for acute GVHD prophylaxis (n ¼ 144) was reanalyzed. No change was found in the aforementioned association, which was strengthened despite a reduction in the sample size. These findings are in line with the data published in different clinical settings including gestational complications, auto-immunity, infections, cancers, as well as solid organ transplantation [163], although recent analysis has not observed correlations between regulatory region, 14 bp indel, and clinical outcomes [174,175]. Taken together, these results suggest that further investigation in larger transplant populations is warranted. The ins/del polymorphic variation in HLA-G seems to influence the RNA splicing stability by mechanisms that are yet to be understood. The presence of the 14-bp insertion introduces an additional splice site which results in the removal of the first 92 bp of exon 8 thereby generating more stable HLA-G mRNAs species than the complete mRNA [21,24,164]. In fact, the 30 UTR 14-bp insertion has been consistently associated with low expression of HLA-G mRNA and low serum sHLA-G [25,26]. Such a discrepancy between stability and output, termed “the 14-bp polymorphism paradox”, predicts complex mechanisms of regulation of HLA-G expression. Recent studies implicate the potential role of micro-RNAs which, by interacting with the HLA-G 30 mRNA region, may regulate its phenotypic expression [23,165]. Indeed, the observed effect of the insertion allele on acute GVHD could be either due to a haplotypic effect or due to another yet to be identified linked functional variant. The 14-bp ins/þ3142G/þ3187A haplotype has been studied with respect to risk of preeclampsia [163]. Data on the effect of the insertion allele in the incidence of acute GVHD are internally consistent with the concept that downregulated expression of HLA-G molecules could decrease immunosuppressive/tolerogenic properties that consequently result in the development of acute GVHD. The data are also in concordance with those showing that high pretransplantation and posttransplantation levels of sHLA-G molecules correlate not only with a decreased incidence of acute GVHD but also with a high frequency of circulating Tregs. Similar correlation between sHLA-G and Treg cells was also observed in in vitro mixed leukocyte reaction assay [166], in the context of liver transplantation [167] and in the transgenic murine model system [168]. These findings are also in agreement with most expression studies of HLA-G in solid organ transplantation that show beneficial effects of HLA-G molecules and lowered acute rejection/chronic dysfunction of the transplanted heart and kidney [169,170] and also with those establishing correlations between the presence of the HLA-G 14-bp ins allele and organ rejection [171e173]. HCT is a sensitive in vivo setting capable of revealing fine immune

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response traits, undetectable in physiological situations. This may be a plausible reason why the effect of the ins/ins HLAG genotype on conferring low immune tolerance has been uncovered. More recently, studies have shown an increased level of HLA-G expression in GVHD target organs in patients receiving allogeneic hematopoietic stem cell transplants [176]. Furthermore, higher levels of soluble HLA-G can be found in the weeks after transplantation and correlate with protection against GVHD [177]. These studies collectively provide evidence for soluble HLA-G as an important factor in GVH responses.

MIC GENES IN HCT-GVH The investigation of MICA and MICB genes in transplantation has been hampered by the strong positive LD between these two loci and HLA-B; the LD favors MICA matching among HLA-matched transplants, thus necessitating very large transplant populations to isolate potential effects contributed by MICA. Nonetheless, the functional implications of the MICA 129 dimorphism have been investigated in many clinical settings including transplantation. In a cohort of 211 consecutive patients who underwent noneT-celledepleted allogenic HCT in a single institution from HLA identical siblings [178], MICA 129 genotyping (val/met) revealed that a recipient MICA 129 val/val genotype is a risk factor for chronic GVHD (63% vs. 45% at 3 years, P ¼ .03). The data were confirmed in multivariate analysis adjusted for confounding variables. Because acute GVHD is a major risk factor for subsequent chronic GVHD, acute GVHD was introduced as a time-dependent covariate in the multivariate analysis model. This analysis confirmed that the risk conferred by the MICA 129 val/val genotype is independent from acute GVHD. In an exploratory study of 236 URD transplants of which 73% of pairs were matched for HLA 10/10 alleles (HLA-A, -B, -C, -DRB1, -DQB1), MICA polymorphism was assessed by sequence-based typing methods and MICA mismatching was observed in 8.4%. A higher rate of grade IIeIV acute GVHD was observed in MICA disparate pairs (80% vs. 40%, P ¼ .003) irrespective of the degree of HLA matching. Furthermore, the rate of gastrointestinal acute GVHD was higher in MICA-mismatched patients (35% vs. 17%, P ¼ .5) [179] although the association of MICA mismatching with gastrointestinal GVHD was not observed in an independent study [180]. These results are reminiscent of the data obtained using the MHC block matching technique, a DNA-based MHC matching approach that uses non-HLA DNA polymorphisms in the MHC as markers of blocks of ancestral haplotypes. Matching for the MHC beta block inclusive of MIC genes was found to be beneficial over the classical HLA-B, HLA-C matching for survival in HCT [141]. In addition to MICA genetic polymorphism effects, additional MICA-related phenotypic features could influence the outcome of HCT. An elevated serum level of MICA was found to be associated with the incidence of chronic GVHD while the presence of MICA antibodies before transplantation was shown to confer protection against chronic GVHD [178]. The inverse relationship between MICA antibodies and sMICA suggests an antibody-based neutralization of deleterious effects of sMICA. Therefore, both genotypes and phenotypes of MICA represent important integrated biomarkers in HCT monitoring. One can speculate that the lower engagement of NKG2D receptors by the weak binder MICA 129val allele could impair the NK/cytotoxic T lymphocyte cell activation costimulation and possibly skew Th1 toward Th2 and subsequent B-cell activation and antibody production, two hallmarks of chronic GVHD pathogenesis. This is corroborated by the recent observation that sMICA-NKG2D engagement upregulates INF-g expression by CD56 bright NK cells and therefore contributes to systemic inflammation, a feature of chronic GVHD [162]. Two recent studies provide the most convincing evidence of MICA as a transplantation determinant [181,182]. In a large multicenter analysis coordinated in France [181], 922 HLA-10/10-matched unrelated donor transplants were evaluated and MICA mismatching was significantly associated with increased risk of clinical severe grade IIIeIV acute GVHD. In an independent study conducted by the German Registry for Stem Cell Transplantation [182], 2172 matched or mismatched patients were evaluated, and HLA 12/12,MICA-matched transplants had superior outcomes. By contrast, an analysis of North American patients by the CIBMTR did not observe an association between MICA mismatching and risks after transplantation [183]. Differing patient populations and transplant procedures may have contributed to these heterogeneous results. Future validation studies are needed to establish the rationale for prospective MICA typing and matching in unrelated donor transplantation.

CONCLUSIONS The assessment of the genetic risks associated with each locus of the MHC provides critical information for implementing comprehensive pretransplant genetic assessment and matching to lower risks for patients and for developing algorithms for targeted GVHD prevention strategies in HCT. A systems biology approach based on data from experimental and modeling outcomes represents a forward-looking strategy in this field. Analysis of the sequence, polymorphism, transcription, and

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protein expression profiles of MHC and of the three-dimensional structure of the histocompatibility antigens has enabled the elucidation of the structureefunction relationship using innovative experimental approaches and computational tools. Gene expression profiling applied to an in situ skin explant model of GVHD was recently used to identify new candidate genes for controlling the risk of GVHD [184]. Hematopoietic cell transplantation is a unique model with which to understand the complex and systemic effects of introducing a healthy new genome into a patient to cure hematologic disorders. The drastic biological perturbations caused depend on both the genetic make-up of the donor and that of the recipient. Donor/recipient histocompatibility can be assessed by correlating biological and physiological effects, thus identifying the genetic contribution of MHC alleles, haplotypes, and their combined effects. This opens up, for example, the possibility of neutralizing MHC genetic differences by performing hematopoietic cell transplantation between HLA identical siblings. Such a clinical setting makes it possible to highlight the effects of other immunogenetic systems, such as minor histocompatibility loci, cytokines, receptors, which currently may have a more limited yet significant influence on the outcome of transplantation. Among the major bottlenecks in translating systems biology into individualized systems medicine is the limited number of clinical cases that can be included in randomized trials and the number of genetic and environmental variables that cannot be easily accounted for. With the increasing number of genetic systems and alleles that have to be taken into account, the number of transplants available for investigation is a major limiting factor. Are virtual patient models that mimic the patients’ main characteristics, from which testable hypotheses can be generated and validated on the small number of actual patients available, one solution? In the future, a systems biology approach and integrative methodologies will undoubtedly be needed to unravel the role of immunogenetics in transplantation to bring tailored and personalized treatment to the individual patient [185].

ACKNOWLEDGMENTS EWP is supported by grants CA18029, CA100019, CA162194, and AI069197 from the National Institutes of Health.

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