Immunologic Risk Stratification of Pediatric Heart Transplant Patients by Combining Hlamatchmaker and PIRCHE-II

Positive Long-Term Outcome of Kidney Allocation via Acceptable Mismatch Program in Highly Sensitized Patients

Introduction

Eurotransplant established the acceptable mismatch (AM) program to facilitate timely kidney transplantations of highly sensitized patients, but long-term granular clinical and immunological outcomes regarding overall graft survival and de novo DSA (dnDSA) formation are still intensively researched. The right choice of induction therapy in patients with differing immunological risk is not conclusively determined, as well as the impact of human leukocyte antigen (HLA) epitope matching on dnDSA formation.

Methods

This monocentric, retrospective study analyzed 94 patients transplanted within the AM program between 2000 and 2019 compared to case-control matched cohorts of non- (PRA 0-5%; PRA-0) and intermediately sensitized (PRA 6-84%; PRA-6/84) patients transplanted through Eurotransplant Kidney Allocation System.

Results

Estimated 10-year overall graft survival between the PRA-0 and AM cohorts was similar, whereas PRA-6/84 was significantly disadvantageous compared to PRA-0. Estimated 10-year incidence of antibody-mediated rejection rates was significantly lower in the PRA-0 group compared to AM and PRA-6/84 groups. Compared to the AM group, estimated incidence of de novo donor-specific antibody (dnDSA) was significantly lower in PRA-0 patients, with no differences between the AM and PRA-6/84 cohorts. The PRA-6/84 cohort was the only subgroup in which interleukin-2 receptor antagonist (IL2RA) induction was associated with longer overall graft survival, patient survival, and graft survival compared to depleting induction (ATG or OKT3). Broad HLA-A, -B, -DR mismatches (mmABDR) and HLA epitope mismatches determined by Eplets and PIRCHE-II were predictive for dnDSA formation in the total cohort, and the AM subgroup.

Discussion

The high efforts expended on AM patients are justified to allow timely organ transplantation with acceptable risk profile and non-inferior outcomes. IL2RA induction in intermediately sensitized patients is associated with superior overall graft survival, patient survival, and graft survival compared to ATG/OKT3 induction, without negative effects on rejection episodes or dnDSA formation. In silico epitope matching might further help reduce dnDSA formation, particularly in high-risk AM patients.

PIRCHE application major versions 3 and 4 lead to equivalent T cell epitope mismatch scores in solid organ and stem cell transplantation modules

PIRCHE scores in organ and stem cell transplantation have been shown to correlate with increased risk of donor-specific HLA antibodies and graft-versus-host disease, respectively. With advancements of the PIRCHE application server, it is critical to compare the predicted scores with previous versions. This manuscript compares the newly introduced PIRCHE version 4.2 with its predecessor version 3.3, which was widely used in retrospective studies, using a virtual cohort of 10,000 transplant pairs. In the stem cell transplantation module, both versions yield identical results in 100% of the test population. In the solid organ module, 97% of the test population has identical PIRCHE scores. The deviating cases (3%) were attributed to refinements in the PIRCHE algorithm's specification. Furthermore, the magnitude of the difference is likely to be below the detection limit for clinical effects, confirming the equivalence in PIRCHE scores between versions 3.3 and 4.2.

Role of HLA in cardiothoracic transplantation

In current clinical practice, transplant clinicians create collaborative working relationships with histocompatibility laboratory scientists to identify the risk of long-term graft failure, which may assist in establishing strategies for treatment and surveillance. Transplant immunology research also focuses on optimizing human leukocyte antibody tissue typing and defines the most effective test for detecting the presence of donor-specific antibodies. Although several studies have been conducted, data on pediatric heart transplant recipients are limited. Epitope load information may be utilized to identify donors with permissible human leukocyte antibody mismatches to increase transplant success. Although current guidelines do not consider human leukocyte antibody epitope-based matching tools, these guidelines could be useful for identifying recipients at a high risk of donor-specific antibody production, which would be appropriate for routine donor-specific antibody screening to initiate early interventions to prevent antibody-mediated rejection. Human leukocyte antibody matching at the epitope level offers an effective approach for identifying acceptable mismatches in sensitized patients and provides information about epitope loads. In the future, eplet matching may be used to define the best immunosuppressive therapy protocol for cardiothoracic organ transplantation. This report provides an overview of the role of human leukocyte antibodies in heart and lung transplantation.

PIRCHE-II Risk and Acceptable Mismatch Profile Analysis in Solid Organ Transplantation

To optimize outcomes in solid organ transplantation, the HLA genes are regularly compared and matched between the donor and recipient. However, in many cases a transplant cannot be fully matched, due to widespread variation across populations and the hyperpolymorphism of HLA alleles. Mismatches of the HLA molecules in transplanted tissue can be recognized by immune cells of the recipient, leading to immune response and possibly organ rejection. These adverse outcomes are reduced by analysis using epitope-focused models that consider the immune relevance of the mismatched HLA.PIRCHE, an acronym for Predicted Indirectly ReCognizable HLA Epitopes, aims to categorize and quantify HLA mismatches in a patient-donor pair by predicting HLA-derived T cell epitopes. Specifically, the algorithm predicts and counts the HLA-derived peptides that can be presented by the host HLA, known as indirectly-presented T cell epitopes. Looking at the immune-relevant epitopes within HLA allows a more biologically relevant understanding of immune response, and provides an expanded donor pool for a more refined matching strategy compared with allele-level matching. This PIRCHE algorithm is available for analysis of single transplantations, as well as bulk analysis for population studies and statistical analysis for comparison of probability of organ availability and risk profiles.

Epitopes, paratopes, and other topes 30 years on: Understanding what we are talking about

The question of which protein antigens, such as HLA class I or class II molecules, will bind, and how well, to a given antibody is often assumed to depend exclusively on the details of protein surface structure. These structures are usually based on static models resulting from X-ray crystallography. While these notions are useful, the ultimate causal factors determining how well a given antigen binds a given antibody are based in thermodynamics and can include atomic mobility and the time-varying conformations of proteins. In this article, fundamental biophysical principles of antibody-antigen interaction are discussed, concepts critical for a deeper understanding of the pertinent molecular phenomena are highlighted, and common misunderstandings are identified and debunked.

Predictive value of molecular matching tools for the development of donor specific HLA-antibodies in patients undergoing lung transplantation

Molecular matching is a new approach for virtual histocompatibility testing in organ transplantation. The aim of our study was to analyze whether the risk for de novo donor-specific HLA antibodies (dnDSA) after lung transplantation (LTX) can be predicted by molecular matching algorithms (MMA) and their combination. In this retrospective study we included 183 patients undergoing LTX at our center from 2012-2020. We monitored dnDSA development for 1 year. Eplet mismatches (epMM) using HLAMatchmaker were calculated and highly immunogenic eplets based on their ElliPro scores were identified. PIRCHE-II scores were calculated using PIRCHE-II algorithm (5- and 11-loci). We compared epMM and PIRCHE-II scores between patients with and without dnDSA using t-test and used ROC-curves to determine optimal cut-off values to categorize patients into four groups. We used logistic regression with AIC to compare the predictive value of PIRCHE-II, epMM, and their combination. In total 28.4% of patients developed dnDSA (n = 52), 12.5% class I dnDSA (n = 23), 24.6% class II dnDSA (n = 45), and 8.7% both class II and II dnDSA (n = 16). Mean epMMs (p-value = 0.005), mean highly immunogenic epMMs (p-value = 0.003), and PIRCHE-II (11-loci) (p = 0.01) were higher in patients with compared to without class II dnDSA. Patients with highly immunogenic epMMs above 30.5 and PIRCHE-II 11-loci above 560.0 were more likely to develop dnDSA (31.1% vs. 14.8%, p-value = 0.03). The logistic regression model including the grouping variable showed the best predictive value. MMA can support clinicians to identify patients at higher or lower risk for developing class II dnDSA and might be helpful tools for immunological risk assessment in LTX patients.

Immunologic risk stratification of pediatric heart transplant patients by combining HLA-EMMA and PIRCHE-II

Human leukocyte antigen (HLA) molecular mismatch is a powerful biomarker of rejection. Few studies have explored its use in assessing rejection risk in heart transplant recipients. We tested the hypothesis that a combination of HLA Epitope Mismatch Algorithm (HLA-EMMA) and Predicted Indirectly Recognizable HLA Epitopes (PIRCHE-II) algorithms can improve risk stratification of pediatric heart transplant recipients. Class I and II HLA genotyping were performed by next-generation sequencing on 274 recipient/donor pairs enrolled in the Clinical Trials in Organ Transplantation in Children (CTOTC). Using high-resolution genotypes, we performed HLA molecular mismatch analysis with HLA-EMMA and PIRCHE-II, and correlated these findings with clinical outcomes. Patients without pre-formed donor specific antibody (DSA) (n=100) were used for correlations with post-transplant DSA and antibody mediated rejection (ABMR). Risk cut-offs were determined for DSA and ABMR using both algorithms. HLA-EMMA cut-offs alone predict the risk of DSA and ABMR; however, if used in combination with PIRCHE-II, the population could be further stratified into low-, intermediate-, and high-risk groups. The combination of HLA-EMMA and PIRCHE-II enables more granular immunological risk stratification. Intermediate-risk cases, like low-risk cases, are at a lower risk of DSA and ABMR. This new way of risk evaluation may facilitate individualized immunosuppression and surveillance.

Dissecting the impact of molecular T-cell HLA mismatches in kidney transplant failure: A retrospective cohort study

Introduction

Kidney transplantation is the optimal treatment in end-stage kidney disease, but de-novo donor specific antibody development continues to negatively impact patients undergoing kidney transplantation. One of the recent advances in solid organ transplantation has been the definition of molecular mismatching between donors and recipients' Human Leukocyte Antigens (HLA). While not fully integrated in standard clinical care, cumulative molecular mismatch at the level of eplets (EMM) as well as the PIRCHE-II score have shown promise in predicting transplant outcomes. In this manuscript, we sought to study whether certain T-cell molecular mismatches (TcEMM) were highly predictive of death-censored graft failure (DCGF).

Methods

We studied a retrospective cohort of kidney donor:recipient pairs from the Scientific Registry of Transplant Recipients (2000-2015). Allele level HLA-A, B, C, DRB1 and DQB1 types were imputed from serologic types using the NMDP algorithm. TcEMMs were then estimated using the PIRCHE-II algorithm. Multivariable Accelerated Failure Time (AFT) models assessed the association between each TcEMM and DCGF. To discriminate between TcEMMs most predictive of DCGF, we fit multivariable Lasso penalized regression models. We identified co-expressed TcEMMs using weighted correlation network analysis (WGCNA). Finally, we conducted sensitivity analyses to address PIRCHE and IMGT/HLA version updates.

Results

A total of 118,309 donor:recipient pairs meeting the eligibility criteria were studied. When applying the PIRCHE-II algorithm, we identified 1,935 distinct TcEMMs at the population level. A total of 218 of the observed TcEMM were independently associated with DCGF by AFT models. The Lasso penalized regression model with post selection inference identified a smaller subset of 86 TcEMMs (56 and 30 TcEMM derived from HLA Class I and II, respectively) to be highly predictive of DCGF. Of the observed TcEMM, 38.14% appeared as profiles of highly co-expressed TcEMMs. In addition, sensitivity analyses identified that the selected TcEMM were congruent across IMGT/HLA versions.

Conclusion

In this study, we identified subsets of TcEMMs highly predictive of DCGF and profiles of co-expressed mismatches. Experimental verification of these TcEMMs determining immune responses and how they may interact with EMM as predictors of transplant outcomes would justify their consideration in organ allocation schemes and for modifying immunosuppression regimens.

Snowflake epitope matching correlates with child-specific antibodies during pregnancy and donor-specific antibodies after kidney transplantation

Development of donor-specific human leukocyte antigen (HLA) antibodies (DSA) remains a major risk factor for graft loss following organ transplantation, where DSA are directed towards patches on the three-dimensional structure of the respective organ donor's HLA proteins. Matching donors and recipients based on HLA epitopes appears beneficial for the avoidance of DSA. Defining surface epitopes however remains challenging and the concepts underlying their characterization are not fully understood. Based on our recently implemented computational deep learning pipeline to define HLA Class I protein-specific surface residues, we hypothesized a correlation between the number of HLA protein-specific solvent-accessible interlocus amino acid mismatches (arbitrarily called Snowflake) and the incidence of DSA. To validate our hypothesis, we considered two cohorts simultaneously. The kidney transplant cohort (KTC) considers 305 kidney-transplanted patients without DSA prior to transplantation. During the follow-up, HLA antibody screening was performed regularly to identify DSA. The pregnancy cohort (PC) considers 231 women without major sensitization events prior to pregnancy who gave live birth. Post-delivery serum was screened for HLA antibodies directed against the child's inherited paternal haplotype (CSA). Based on the involved individuals' HLA typings, the numbers of interlocus-mismatched antibody-verified eplets (AbvEPS), the T cell epitope PIRCHE-II model and Snowflake were calculated locus-specific (HLA-A, -B and -C), normalized and pooled. In both cohorts, Snowflake numbers were significantly elevated in recipients/mothers that developed DSA/CSA. Univariable regression revealed significant positive correlation between DSA/CSA and AbvEPS, PIRCHE-II and Snowflake. Snowflake numbers showed stronger correlation with numbers of AbvEPS compared to Snowflake numbers with PIRCHE-II. Our data shows correlation between Snowflake scores and the incidence of DSA after allo-immunization. Given both AbvEPS and Snowflake are B cell epitope models, their stronger correlation compared to PIRCHE-II and Snowflake appears plausible. Our data confirms that exploring solvent accessibility is a valuable approach for refining B cell epitope definitions.

Pediatric Kidney Transplantation-Can We Do Better? The Promise and Limitations of Epitope/Eplet Matching

Kidney transplant is the optimal treatment for end-stage kidney disease as it offers significant survival and quality of life advantages over dialysis. While recent advances have significantly improved early graft outcomes, long-term overall graft survival has remained largely unchanged for the last 20 years. Due to the young age at which children receive their first transplant, most children will require multiple transplants during their lifetime. Each subsequent transplant becomes more difficult because of the development of de novo donor specific HLA antibodies (dnDSA), thereby limiting the donor pool and increasing mortality and morbidity due to longer time on dialysis awaiting re-transplantation. Secondary prevention of dnDSA through increased post-transplant immunosuppression in children is constrained by a significant risk for viral and oncologic complications. There are currently no FDA-approved therapies that can meaningfully reduce dnDSA burden or improve long-term allograft outcomes. Therefore, primary prevention strategies aimed at reducing the risk of dnDSA formation would allow for the best possible long-term allograft outcomes without the adverse complications associated with over-immunosuppression. Epitope matching, which provides a more nuanced assessment of immunological compatibility between donor and recipient, offers the potential for improved donor selection. Although epitope matching is promising, it has not yet been readily applied in the clinical setting. Our review will describe current strengths and limitations of epitope matching software, the evidence for and against improved outcomes with epitope matching, discussion of eplet load vs. variable immunogenicity, and conclude with a discussion of the delicate balance of improving matching without disadvantaging certain populations.