Objectives/Goals: We aim to enhance risk prediction in kidney transplantation outcomes by improving models of peptide antigen presentation of mismatched HLA molecules. HLA-derived peptides presented by recipient HLA Class II to T-cells can activate an immune response ultimately leading to graft failure. Methods/Study Population: T-cell epitope models for HLA mismatching struggle to predict which peptides are presented because antigen processing by proteases is not well modeled. We model antigen processing of HLA Class II proteins using 3D HLA structures (crystallography data) to create an HLA-specific Antigen Processing Likelihood (APL) model. APL uses conformational stability measurements to predict cleavage sites from proteolysis. We integrated APL into a T-cell epitope prediction tool for HLA-derived peptides called PIRCHE-II that is currently used to risk-stratify risk of kidney allograft failure based on donor and recipient HLA genotypes. To measure risk stratification of APL-informed peptide predictions, we will use a historical kidney transplant cohort from 2000 to 2023. Results/Anticipated Results: We expect the application of APL could reduce false- positive peptide binders that influence risk prediction scores. We anticipate improved peptide prediction accuracy compared to existing tools such as NetMHCIIPan which assumes all possible peptides are equally likely to emerge from antigen processing. NetMHCIIPan is currently used by PIRCHE-II HLA mismatch risk algorithm. Out of 12 donor–recipient transplant pairs, NetMHCIIPan has found an average of 41 peptides per pairing and APL found an average of 62 peptides per pairing. These peptides are unique to each prediction, so a combined prediction could reduce the peptide list. We expect that merging antigen processing (APL) and peptide binding (NetMHCIIPan) models into a unified model would enhance risk stratification for graft failure compared to PIRCHE-II. Discussion/Significance of Impact: More holistic modeling of immune pathways can lead to more realistic numbers of peptides found from mismatched HLA proteins. Understanding how HLA matching contributes to kidney transplant outcomes can better stratify risks for recipients, enabling personalized treatment to induce immune tolerance and ultimately improving outcomes.
Paynter et al. (Wed,) studied this question.