HLA Epitopes Research Articles

Abstract 1898: Accurate modeling of antigen processing and MHC peptide presentation using large-scale immunopeptidomes and a novel machine learning framework

Abstract Neoantigens, which are antigens specific to cancer cells, can be harnessed to develop precision immunotherapies, such as personalized cancer vaccines, and prognostic biomarkers for checkpoint blockade inhibition. Next generation sequencing technologies have enabled comprehensive profiling of putative neoantigens by interrogating the tumor exome and transcriptome, but accurate prediction of peptides presented by MHC complexes remains a significant challenge. We present here Systematic HLA Epitope Ranking Pan Algorithm (SHERPA™) that addresses this critical need. SHERPA comprises highly sensitive, accurate and pan-allelic MHC-peptide (MHCp) binding and presentation prediction models, that were built using a multi-pronged strategy. First, we generated a large-scale, high-quality HLA ligandome using approximately 75 stably transfected mono-allelic K562 cell lines. Intact MHCp complexes were immunoprecipitated using W6/32 antibody and profiled using LC/MS-MS. Second, we trained models that predict both MHCp binding and presentation. Briefly, MHCp binding was modeled using the amino acid sequences of the ligand and the binding pocket of the cognate allele. MHCp presentation, which encompasses in vivo antigen processing, was modeled using multiple features including the expression level of the source protein, proteasomal cleavage, and two novel features representing presentation propensities of genes and regions within gene bodies. Third, we expanded the scale and scope of our in-house dataset using a large curated repository of publicly available mono- and multi-allelic datasets resulting in > 160 alleles and > 1.6 million peptides. Integrating data from diverse cell line and tissue types improved the generalizability of our models, a critically important aspect when applying our models to patient samples. Finally, we implemented a model-based deconvolution of multi-allelic datasets to generate pseudo mono-allelic data, and developed an integrative machine learning architecture to model our expanded HLA-ligandome. We evaluated the performance of our binding and prediction models on 10% held-out mono-allelic test data from multiple cell line sources. The precision at various recall values of both binding and prediction models was markedly higher than NetMHCPan 4.0, and the positive predictive values were 0.59 and 0.73 respectively, significantly higher compared to NetMHCpan 4.0 (PPV = 0.38). Additionally, a strong concordance of raw and predicted motifs for alleles excluded from training data indicated a robust pan-allelic performance. When evaluated on 12 tissue samples profiled in-house, the SHERPA presentation model had a consistently high recall (90%) compared to NetMHCpan 4.0 (63%). This trend holds true on external immunopeptidomics datasets from tumor samples. In summary, SHERPA enables precision neoantigen discovery. Citation Format: Rachel Marty Pyke, Dattatreya Mellacheruvu, Steven Dea, Charles Abbott, Nick Phillips, Sejal Desai, Rena McClory, Steven Ketelaars, Pia Kvistborg, John West, Richard Chen, Sean Michael Boyle. Accurate modeling of antigen processing and MHC peptide presentation using large-scale immunopeptidomes and a novel machine learning framework [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1898.

Intravenous immunoglobulins do not prove beneficial to reduce alloimmunity among kidney transplant recipients with BKV-associated nephropathy.

Reduced immunosuppression during BKV-DNAemia has been associated with T-cell mediated rejection (TCMR), de novo donor-specific antibodies (DSA) and antibody-mediated rejection (ABMR). Intravenous immunoglobulins (IVIG) may reduce alloimmunity. We studied 860 kidney transplant recipients (KTRs) for the development of BKV-DNAuria and BKV-DNAemia (low-level <10000IE/ml, high-level >10000IE/ml). 52/131 KTRs with high-level BKV-DNAemia received IVIG. The HLA-related immunological risk was stratified by the Predicted Indirectly Recognizable HLA Epitopes (PIRCHE) algorithm. BKV-DNAuria only was observed in 86 KTRs (10.0%), low-level BKV-DNAemia in 180 KTRs (20.9%) and high-level BKV-DNAemia in 131 KTRs (15.2%). KTRs with low-level BKV-DNAemia showed significantly less TCMR compared to KTRs with high-level BKV-DNAemia (5.2% vs. 25.5%; P<0.001) and no BKV-replication (13.2%; P=0.014), lowest rates of de novo DSA (21.3%), ABMR (9.2%) and flattest glomerular filtration rate (GFR) slope (-0.8ml/min). KTRs with low-level BKV-DNAemia showed significantly higher median (interquartile range) total PIRCHE if they developed TCMR [100.22 (72.6) vs. 69.52 (49.97); P=0.020] or ABMR [128.86 (52.99) vs. 69.52 (49.96); P=0.005]. Administration of IVIG did not shorten duration of BKV-DNAemia (P=0.798) or reduce TCMR, de novo DSA and ABMR (P>0.05). KTRs with low-level BKV-DNAemia showed best protection against alloimmunity, with a high number of PIRCHE co-determining the remaining risk. The administration of IVIG, however, was not beneficial in reducing alloimmunity.

FC 128NON-HLA ANTIBODIES AND EPLET MISMATCHES IN KIDNEY TRANSPLANT RECIPIENTS WITH A HISTOLOGICAL PICTURE OF ANTIBODY-MEDIATED REJECTION WITH AND WITHOUT HLA DONOR-SPECIFIC ANTIBODIES

Abstract Background and Aims Correlation between antibody-mediated rejection (ABMR) and HLA donor-specific antibodies (DSA) is strong but imperfect in kidney transplant (KT) recipients, raising the possibility of other detrimental antibodies contributing to ABMR. The role of non-HLA antibodies on outcomes is not well known. Method We retrospectively assessed KT biopsies scored according to Banff’15 classification. Pre- and post-KT serum samples were checked for HLA and non-HLA antibodies (MICA-Ab, angiotensin II type 1 receptor (AT1R)-Ab, endothelin-1 type A receptor (ETAR)-Ab and crossmatches with primary aortic endothelial cells (EC-XM)). We also analyzed HLA epitope mismatches between donors and recipients. Results One-hundred eighteen patients with normal (n=19), ABMR histology (n=52) or IFTA (n=47) in their biopsy were studied. Graft survival was worse in ABMR patients (p=0.003). Pre-KT HLA-DSA were more frequent in ABMR cases (p=0.006). At biopsy, 73% ABMR patients had HLA-DSA (p&amp;lt;0.001). Pre-KT AT1R-Ab were more frequent in ABMR compared with IFTA and normal cases (p=0.003), without differences in other non-HLA antibodies. Fourteen patients with histological ABMR (27%) had no detectable HLA-DSA post-KT and only 3 had non-HLA Ab. However, these ABMR-DSA- cases showed similar biopsy changes and graft survival compared with ABMR-DSA+. Pre- or post-KT non-HLA antibodies other than AT1R-Ab were detected similarly in ABMR and in normal or IFTA cases. Both total class II and DRB1 epitope mismatches were associated with postransplant DSA and ABMR-DSA+. Multivariate analysis showed that both pre-KT HLA-DSA and AT1R-Ab (DSA: OR: 3.39 [1.20-9.59], p=0.021; AT1R-Ab: OR: 5.31 [1.75-16.10], p=0.003) were strong independent predictors of postransplant ABMR-DSA+ (Table 1). Conclusion Despite highly prevalent HLA-DSA before and after transplantation in KT with histological ABMR, 27% of cases did not show circulating HLA-DSA. Pre-KT AT1R-Ab associated with ABMR-DSA+, but not MICA-Ab, ETAR-Ab or EC-XM+. Any of them associated significantly with ABMR-DSA-. Epitope mismatch predicted both postransplant DRB-DSA and ABMR-DSA+. Detection of pre-KT HLA-DSA and/or AT1R-Ab, together with HLA epitope mismatch assessment, are valuable tools for better DSA and ABMR prediction in KT patients.

Construction and Expression of Eukaryotic and Prokaryotic Recombinant Vectors of Pepck and Gp63 Dominant Epitopes of Leishmania infantum

To construct eukaryotic and prokaryotic recombinant vectors containing Pepck- Gp63 and to achieve protein expression by selecting the dominant epitope genes of Pepck and Gp63 of Leishmania infantum. The secondary structure and HLA epitopes of phosphoenolpyruvate carboxylase (PEPCK) were predicted by in silico analysis, and the dominant epitopes were picked out. According to the analysis results of glycoprotein of 63×10 3(GP63) epitopes identified by the same method in our laboratory, the dominant epitope genes of Pepck and Gp63 were used to construct pET32a- Pepck- Gp63 and pVAX1- Pepck- Gp63 by overlapping PCR and enzyme reaction. Then, for protein expression, the prokaryotic vectors were transfected into E.coil while the eukaryotic vectors were transfected into NIH3T3 cells by liposome transfection. There were multiple dominant epitopes in Pepckand there were Pepck-Gp63 sequences in the polyclonal site of expression vector. The expression of Pepck-Gp63 in E.coil appeared in inclusion form and led to 74 kDa band in SDS-PAGE. The immunofluorescence results of NIH3T3 cells transfected by pVAX1- Pepck-Gp63 were positive. The recombinant prokaryotic expression plasmids pET32a- Pepck-Gp63 and eukaryotic expression plasmids pVAX1- P epck -Gp63 were successfully constructed, and it was shown that the recombinant plasmids were able to express the corresponding target proteins in E. coli and NIH3T3 cells, respectively, providing a preliminary experimental basis for the subsequent study of immunization strategies.

Can PIRCHE-II Matching Outmatch Traditional HLA Matching?

We analyzed in a cohort of 68,606 first deceased donor kidney transplantations reported to the Collaborative Transplant Study whether an epitope-based matching of donor-recipient pairs using the Predicted Indirectly ReCognizable HLA Epitopes algorithm (PIRCHE-II) is superior to currently applied HLA antigen matching. PIRCHE-II scores were calculated based on split antigen HLA-A, -B, -DRB1 typing and adjusted to the 0–6 range of HLA mismatches. PIRCHE-II scores correlated strongly with the number of HLA mismatches (Spearman ρ = 0.65, P < 0.001). In multivariable analyses both parameters were found to be significant predictors of 5-year death-censored graft loss with high prognostic power [hazard ratio (HR) per adjusted PIRCHE-II score = 1.102, per HLA mismatch = 1.095; z-value PIRCHE-II: 9.8, HLA: 11.2; P < 0.001 for both]. When PIRCHE-II scores and HLA mismatches were analyzed simultaneously, their predictive power decreased but remained significant (PIRCHE-II: P = 0.002; HLA: P < 0.001). Influence of PIRCHE-II was especially strong in presensitized and influence of HLA mismatches in non-sensitized recipients. If the level of HLA-incompatibility was low (0–3 mismatches), PIRCHE-II scores showed a low impact on graft survival (HR = 1.031) and PIRCHE-II matching did not have additional significant benefit (P = 0.10). However, if the level of HLA-incompatibility was high (4–6 mismatches), PIRCHE-II improved the positive impact of matching compared to applying the traditional HLA matching alone (HR = 1.097, P = 0.005). Our results suggest that the PIRCHE-II score is useful and can be included into kidney allocation algorithms in addition to HLA matching; however, at the resolution level of HLA typing that is currently used for allocation it cannot fully replace traditional HLA matching.

Emerging monitoring technologies in kidney transplantation.

Non-invasive technologies to monitor kidney allograft health utilizing high-throughput assays of blood and urine specimens are emerging out of the research realm and slowly becoming part of everyday clinical practice. HLA epitope analysis and eplet mismatch score determination promise a more refined approach to the pre-transplant recipient-donor HLA matching that may lead to reduced rejection risk. High-resolution HLA typing and multiplex single antigen bead assays are identifying potential new offending HLA antibody subtypes. There is increasing recognition of the deleterious role non-HLA antibodies play in post-transplant outcomes. Donor-derived cell-free DNA detected by next-generation sequencing is a promising biomarker for kidney transplant rejection. Multi-omics techniques are shedding light on discrete genomic, transcriptomic, proteomic, and metabolomic signatures that correlate with and predict allograft outcomes. Over the next decade, a comprehensive approach to optimize kidney matching and monitor transplant recipients for acute and chronic graft dysfunction will likely involve a combination of those emerging technologies summarized in this review.

An epitope-based approach of HLA-matched platelets for transfusion: a noninferiority crossover randomized trial

AbstractPlatelet transfusion refractoriness results in adverse outcomes and increased health care costs. Managing refractoriness resulting from HLA alloimmunization necessitates the use of HLA antigen–matched platelets but requires a large platelet donor pool and does not guarantee full matching. We report the first randomized, double-blind, noninferiority, crossover trial comparing HLA epitope–matched (HEM) platelets with HLA standard antigen–matched (HSM) platelet transfusions. Alloimmunized, platelet-refractory, thrombocytopenic patients with aplastic anemia, myelodysplastic syndrome, or acute myeloid leukemia were eligible. HEM platelets were selected using HLAMatchMaker epitope (specifically eplet) matching. Patients received up to 8 prophylactic HEM and HSM transfusions provided in random order. The primary outcome was 1-hour posttransfusion platelet count increment (PCI). Forty-nine patients were randomized at 14 UK hospitals. For intention to treat, numbers of evaluable transfusions were 107 and 112 for HEM and HSM methods, respectively. Unadjusted mean PCIs for HEM and HSM methods were 23.9 (standard deviation [SD], 15) and 23.5 (SD, 14.1), respectively (adjusted mean difference, −0.1; 95% confidence interval [CI], −2.9 to 2.8). Because the lower limit of the 95% CI was not greater than the predefined noninferiority limit, the HEM approach was declared noninferior to the HSM approach. There were no differences in secondary outcomes of platelet counts, transfusion requirements, and bleeding events. Adequate 1-hour PCI was more frequently observed, with a mean number of 3.2 epitope mismatches, compared with 5.5 epitope mismatches for inadequate 1-hour increments. For every additional epitope mismatch, the likelihood of an adequate PCI decreased by 15%. Epitope-matched platelets should be considered to support HLA alloimmunized patients. This trial was registered at www.isrctn.com as #ISRCTN23996532.

Influence of HLA epitope mismatch on the kidney allograft after transplantation

Influence of HLA epitope mismatch on the kidney allograft after transplantation

Precision Neoantigen Discovery Using Large-scale Immunopeptidomes and Composite Modeling of MHC Peptide Presentation

Major histocompatibility complex (MHC)-bound peptides that originate from tumor-specific genetic alterations, known as neoantigens, are an important class of anticancer therapeutic targets. Accurately predicting peptide presentation by MHC complexes is a key aspect of discovering therapeutically relevant neoantigens. Technological improvements in mass-spectrometry-based immunopeptidomics and advanced modeling techniques have vastly improved MHC presentation prediction over the past two decades. However, improvement in the sensitivity and specificity of prediction algorithms is needed for clinical applications such as the development of personalized cancer vaccines, the discovery of biomarkers for response to checkpoint blockade, and the quantification of autoimmune risk in gene therapies. Toward this end, we generated allele-specific immunopeptidomics data using 25 monoallelic cell lines and created Systematic HLA Epitope Ranking Pan Algorithm (SHERPA), a pan-allelic MHC-peptide algorithm for predicting MHC-peptide binding and presentation. In contrast to previously published large-scale monoallelic data, we used an HLA-null K562 parental cell line and a stable transfection of HLA alleles to better emulate native presentation. Our dataset includes five previously unprofiled alleles that expand MHC-binding pocket diversity in the training data and extend allelic coverage in under profiled populations. To improve generalizability, SHERPA systematically integrates 128 monoallelic and 384 multiallelic samples with publicly available immunoproteomics data and binding assay data. Using this dataset, we developed two features that empirically estimate the propensities of genes and specific regions within gene bodies to engender immunopeptides to represent antigen processing. Using a composite model constructed with gradient boosting decision trees, multiallelic deconvolution, and 2.15 million peptides encompassing 167 alleles, we achieved a 1.44-fold improvement of positive predictive value compared with existing tools when evaluated on independent monoallelic datasets and a 1.15-fold improvement when evaluating on tumor samples. With a high degree of accuracy, SHERPA has the potential to enable precision neoantigen discovery for future clinical applications.

Off-the-shelf EBV-specific T-cell Immunotherapy for EBV-associated PTLD.

Off-the-shelf EBV-specific T-cell Immunotherapy for EBV-associated PTLD.

Analysis of T and B Cell Epitopes to Predict the Risk of de novo Donor-Specific Antibody (DSA) Production After Kidney Transplantation: A Two-Center Retrospective Cohort Study.

Risk prediction of de novo donor specific antibody (DSA) would be very important for long term graft outcome after organ transplantation. The purpose of this study was to elucidate the association of eplet mismatches and predicted indirectly recognizable HLA epitopes (PIRCHE) scores with de novo DSA production. Our retrospective cohort study enrolled 691 living donor kidney transplantations. HLA-A, B, DRB and DQB eplet mismatches and PIRCHE scores (4 digit of HLA-A, B, DR, and DQ) were determined by HLA matchmaker (ver 2.1) and PIRCHE-II Matching Service, respectively. Weak correlation between eplet mismatches and PIRCHE scores was identified, although both measurements were associated with classical HLA mismatches. Class II (DRB+DQB) eplet mismatches were significantly correlated with the incidence of de novo class II (DR/DQ) DSA production [8/235 (3.4%) in eplet mismatch ≤ 13 vs. 92/456 (20.2%) in eplet mismatch ≥ 14, p < 0.001]. PIRCHE scores were also significantly correlated with de novo class II DSA production [26/318 (8.2%) in PIRCHE ≤ 175 vs. 74/373 (19.8%) in PIRCHE ≥ 176, p < 0.001]. Patients with low levels of both class II eplet mismatches and PIRCHE scores developed de novo class II DSA only in 4/179 (2.2%). Analysis of T cell and B cell epitopes can provide a beneficial information on the design of individualized immunosuppression regimens for prevention of de novo DSA production after kidney transplantation.

Predictive value of HLAMatchmaker and PIRCHE-II scores for de novo donor-specific antibody formation after adult and pediatric liver transplantation

Production of de novo DSA (dnDSA) is associated with an increased risk of antibody mediated rejection after liver transplantation. Antibodies not only recognize the entire antigen but are able to bind specific functional epitopes present on the HLA molecule surface. The HLAMatchmaker and the PIRCHE-II (predicted indirectly recognizable HLA epitopes) algorithms are able to determine predictive epitope mismatches scores and de novo DSA (dnDSA) synthesis based on alloreactive eplets' identification. The aim of the present study was to assess, for the first time in liver transplantation, the complementarity between these two algorithms. We retrospectively analyzed a cohort of 407 adult and 133 pediatric liver transplant patients without preformed DSA, transplanted between 1991 and 2019 in Lyon and Montpellier. HLA antibodies were detected by single antigen bead assay. HLA typing of the donor-recipient pair was achieved by serological and/or DNA-based techniques. PIRCHE-II and HLAMatchmaker algorithms were then applied on both groups. During follow-up, 27.3% of adults and 38.3% of children developed dnDSA. HLA-DRB1 and DQB1-PIRCHE-II and HLAMatchmaker scores were significantly higher in dnDSA group compared to no DSA group for both pediatric and adult patients (except for PIRCHE-II HLA-DRB1 locus score in pediatrics). ROC curves allowed determining score thresholds classifying patients in low- and high-risk of dnDSA synthesis. The two algorithms' Kaplan-Meier curves showed a predicted incidence of dnDSA 20 years after transplantation significantly lower in the low-risk group compare with the high-risk group (log rank <0.05), in both cohorts, with a good negative predictive value. In conclusion, HLAMatchmaker and PIRCHE-II algorithms both are effective tools to identify anti-HLA immunization risk and to predict dnDSA formation after liver transplantation.

Treatment with Banked 3rd Party Donor Derived Virus Specific T Cells: The Advantages of Pre-Defined HLA restriction and Epitope Specificity

Background & Aim For patients lacking a matched donor, transplant (HCT) from umbilical cord or T cell depleted (TCD) grafts, is potentially curative. However, these transplants are associated with high morbidity and mortality from reactivation of latent viruses. Adoptive therapy with CMV and EBV specific T cells expanded in vitro (CMV-CTLs and EBV-CTLs) is increasingly available to clear drug resistant CMV infections and induce durable remissions of refractory EBV+ lymphomas. Here we present studies that help elucidate mechanisms of T cell control of CMV and EBV in both the primary HCT and the adoptive T cell settings and provide rationale for pre-defined characterization of T cells generated for adoptive therapy. Methods, Results & Conclusion In a cohort (N=39) of CMV seropositive recipients of mismatched TCD-HCT, we established the HLA-restriction of the donor's endogenous CMV response. To evaluate instances where viral specific T cells failed to induce responses, we compared in vitro cytotoxicity of CMV-CTLs and EBV-CTLs against targets presenting CMVpp65 15-mers or lab strain EBV B95.8 to patient derived CMV or EBV targets. . Results In 15 of 39 recipients at risk for reactivation of CMV, the donor CMV response was restricted by an un-shared HLA allele.. Furthermore, 53% of these recipients developed persistent CMV viremia or invasive disease compared to none of those whosedonors CMV response was restricted by a shared HLA allele Our analyses show several mechanisms of immune escape leading to for the failure of CMV-CTLs or EBV-CTLs to recognize patient derived targets 1) deficient production of the viral protein (eg EBNA3B) 2) mutations of the viral epitopes (eg EBNA3B presented by HLA A1101) or 3) impaired processing or presentation of these epitopes (eg IPSI peptide of CMVpp65 presented by HLA B3501). In such cases, selection of 3rd party CTLs restricted by a different HLA allele (i.e. restriction switch) has induced remissions of EBV+ lymphomas in 60% of patients. Conclusions In HLA disparate HCT recipients, donor-derived virus-specific T-cells may be ineffective if the HLA restriction is not shared between the T-cells and the recipient. Even in the 3rd-party setting, where there is appropriate selection of shared HLA restrictions, clinical responses may be impacted by immune escape. Our banks of 3rd party virus-specific T-cells characterized by HLA restrictions permit accurate selection of T-cells. Importantly, restriction switch can overcome viral mechanisms of immune evasion.

Rapid high-resolution HLA genotyping by MinION Oxford nanopore sequencing for deceased donor organ allocation.

Recently, HLA epitopes on donor HLA molecules have been shown to be important in the success of solid organ transplantation. However, these epitopes can only be defined using high-resolution typing results of which are often not available prior to deceased donor allocation. The ability to perform high-resolution typing at all HLA loci for deceased organ donor allocation prior to transplantation would have major clinical benefits, in particular for highly sensitised recipients. We, therefore, developed a rapid high-resolution next generation sequencing (NGS) HLA typing (ONT-Rapid HR HLA) method for on-call deceased donor allocation using the AllType 11 loci single-tube assay (OneLambda Inc), modified in-house to reduce polymerase chain reaction amplification time, and the Oxford Nanopore single-molecule sequencing platform on the Flongle flow cell. The ONT-Rapid HR HLA method was validated on 42 samples previously typed by current on-call sequence-specific oligonucleotide (HistoSpot) and NGS methods (AllType/Ion Torrent). High-resolution typing obtained using the ONT-Rapid HR HLA typing method was 100% concordant with both the current SSO and NGS methods, and in some cases, obtained higher resolution than either of the current methods. The rapid ONT-Rapid HR HLA typing method was able to obtain these typing results at all loci in 4 to 4.5 hours. The novel ONT-Rapid HR HLA typing method is the first reported NGS HLA typing method utilised for deceased donor allocation. The ability to provide high-resolution HLA typing on deceased donors before implantation will in the future allow improvements in matching, which will ultimately provide clinical benefits to patients.

HLA-EMMA: A user-friendly tool to analyse HLA class I and class II compatibility on the amino acid level.

In renal transplantation, polymorphic amino acids on mismatched donor HLA molecules can lead to the induction of de novo donor‐specific antibodies (DSA), which are associated with inferior graft survival. To ultimately prevent de novo DSA formation without unnecessarily precluding transplants it is essential to define which polymorphic amino acid mismatches can actually induce an antibody response. To facilitate this, we developed a user‐friendly software program that establishes HLA class I and class II compatibility between donor and recipient on the amino acid level. HLA epitope mismatch algorithm (HLA‐EMMA) is a software program that compares simultaneously the HLA class I and class II amino acid sequences of the donor with the HLA amino acid sequences of the recipient and determines the polymorphic solvent accessible amino acid mismatches that are likely to be accessible to B cell receptors. Analysis can be performed for a large number of donor‐recipient pairs at once. As proof of principle, a previously described study cohort of 191 lymphocyte immunotherapy recipients was analysed with HLA‐EMMA and showed a higher frequency of DSA formation with higher number of solvent accessible amino acids mismatches. Overall, HLA‐EMMA can be used to analyse compatibility on amino acid level between donor and recipient HLA class I and class II simultaneously for large cohorts to ultimately determine the most immunogenic amino acid mismatches.

Evidence for the alloimmune basis and prognostic significance of Borderline T cell-mediated rejection.

Prognostic biomarkers of T cell–mediated rejection (TCMR) have not been adequately studied in the modern era. We evaluated 803 renal transplant recipients and correlated HLA‐DR/DQ molecular mismatch alloimmune risk categories (low, intermediate, high) with the severity, frequency, and persistence of TCMR. Allograft survival was reduced in recipients with Banff Borderline (hazard ratio [HR] 2.4, P = .003) and Banff ≥ IA TCMR (HR 4.3, P < .0001) including a subset who never developed de novo donor‐specific antibodies (P = .002). HLA‐DR/DQ molecular mismatch alloimmune risk categories were multivariate correlates of Banff Borderline and Banff ≥ IA TCMR and correlated with the severity and frequency of rejection episodes. Recipient age, HLA‐DR/DQ molecular mismatch category, and cyclosporin vs tacrolimus immunosuppression were independent correlates of Banff Borderline and Banff ≥ IA TCMR. In the subset treated with tacrolimus (720/803) recipient age, HLA‐DR/DQ molecular mismatch category, and tacrolimus coefficient of variation were independent correlates of TCMR. The correlation of HLA‐DR/DQ molecular mismatch category with TCMR, including Borderline, provides evidence for their alloimmune basis. HLA‐DR/DQ molecular mismatch may represent a precise prognostic biomarker that can be applied to tailor immunosuppression or design clinical trials based on individual patient risk.

HLA Epitope Mismatch Load (epMM) Allows Classification of Immunological Risk and Correlates with Patient Survival Following Lung Transplantation (LTx)

Currently, the assessment of immunological risk in LTx fails to consider HLA compatibility at molecular level, which would allow greater definition of risk of rejection and help clinicians determine best recipients for transplant. The aim of this study was to evaluate HLAMatchmaker epMM in predicting risk of chronic lung allograft rejection (CLAD) and patient survival following LTx. We retrospectively analysed all 310 primary LTx undertaken between 01/08/2008-31/12/2015. Recipient and donors were high resolution HLA typed for all HLA loci and HLAMatchmaker (v2.1) used to calculate amino acid differences between them. The epMM was calculated based on the number of epitopes present in donor but not in patient. BOS and RAS CLAD phenotypes were determined using the 2019 ISHLT guidelines. EpMM were split into tertiles, with Kaplan Meier analysis and log-ranked tests to compare groups. The total HLA class II epMM range was 0-95, and tertiles used were; 1=0-31, 2=32-50, 3=>51. The lowest HLA class II epMM had significantly better patient survival (p<0.001) when compared to the highest epMM group (fig 1a). When splitting DR (fig 1b) and DQ (fig 1c), both were significant when comparing lowest and highest epMM groups in predicting patient survival (DR p=<0.05, DQ p=<0.005). Looking at time to CLAD, the lowest combined HLA Class I and II epMM group (0-48) demonstrated increased days to CLAD when compared to the higher epMM group (p=0.01). HLA Class I alone was not seen to be significant in any statistical analysis. Recipients with HLA Class II total epMM ≤ 31 demonstrated significantly better patient survival compared to higher epMM. The prospective use of HLA epitope compatibility matching has the potential to identify recipients with lower immunological risk, therefore improving overall patient survival and reducing incidence of CLAD and allowing risk-stratification of immunosuppression.

Can Avoiding So-Called HLA High Risk Epitope Mismatches (REM) Improve Lung Transplant (LTx) Outcomes?

HLA epitope mismatches can determine risk of graft rejection and de novo Donor Specific Antibodies (dnDSA) formation. Recently (McCaughan 2018) noted some epitopes posed a greater risk of developing dnDSA post-LTx and assumed this correlated with CLAD and survival. Using these reported REM we aim to determine associations between REM and actual LTx outcomes. We retrospectively analysed all 310 primary LTx undertaken Aug 2008-Dec 2015, with both patients and donors' high resolution HLA typed for all HLA loci. Using HLAMatchmaker (v2.1), LTx were assessed for the presence of REM (45GE3 or 45EV/55PP) and DQA1*05. BOS and RAS were determined using the most recent 2019 ISHLT guidelines. Kaplan Meier analysis with log-ranked tests compared groups. Within our cohort, 82 (27%) LTx occurred in the presence of a REM from the donor. Of these, 43 developed CLAD (BOS n=28 RAS n=15). REM was not a predictor of overall patient survival (fig 1a) (p=0.52) or time to CLAD (fig 1b) (p=0.32). As previously published (McCaughan 2018) the development of dnDSA directed to HLA-DQ was frequent (ie 75% of those tested post-LTx) this did not correlate to time to CLAD or overall patient survival in our cohort. Although avoiding REM has been reported to reduce risk of dnDSA following LTx, in our cohort this does not strongly correlate to overall patient survival or time to CLAD. Further studies are still warranted to identify the riskiest of epitopes to avoid in LTx and how the correlate to LTx outcomes.

Not all HLA epitope mismatches are equal

The future of HLA matching in solid organ transplantation lies in epitope matching. The article by Sapir-Pichhadze etal. provides indirect evidence that there is a difference in immunogenicity between antibody-verified versus non-verified eplets. However, this difference was less clear for HLA class II, showing the need for additional efforts to identify truly immunogenic HLA class II epitope mismatches.

Exploring predicted indirectly recognizable HLA epitopes (PIRCHE-II) in liver transplant recipients on calcineurin inhibitor-free maintenance immunosuppression. A retrospective single center study

The PIRCHE (Predicted Indirectly ReCognizable HLA Epitopes) score is an HLA epitope matching algorithm. PIRCHE algorithm estimates the level of presence of T-cell epitopes in mismatched HLA. The PIRCHE-II numbers associate with de novo donor-specific antibody (dnDSA) formation following liver transplantation and kidney allograft survival following renal transplantation. The aim of our study was to assess the PIRCHE-II score in calcineurin inhibitor (CNI)-free maintenance immunosuppression recipients.This was a retrospective study of forty-one liver transplant recipients on CNI-free immunosuppression and with available liver allograft biopsies. Donors and recipients were HLA typed. The HLA-derived mismatched peptide epitopes that could be presented by the recipient's HLA-DRB1 molecules were calculated using PIRCHE-II algorithm. The associations between PIRCHE-II scores and graft immune-mediated events were assessed using receiver operating characteristics curves and subsequent univariate and multivariate analyses.CNI-free patients with cellular rejection, humoral rejection, or severe portal inflammation had higher mean PIRCHE-II scores compared to patients with normal liver allografts. PIRCHE-II score and donor age were independent risk factors for liver graft survival in CNI-free patients (HR: 8.0, 95% CI: 1.3–49, p = .02; and HR: 0.88, 95% CI: 0.00–0.96, p = .007, respectively).PIRCHE-II scores could be predictive of liver allograft survival in CNI-free patients following liver transplantation. Larger studies are needed to confirm these results.