Abstract B071: Validating sequence similarity-driven neoepitope fitness models via immunogenomics on TCGA and multiregional tumor data

Abstract

Abstract Clonal fitness and survival models for checkpoint blockade response prediction have recently been proposed on the basis of ranking neoepitopes via an interaction between a proxy of T-cell recognition, a nonlinear function of neoepitope sequence similarity to known antigens, and neoantigen relative MHC binding affinity. In this work we examine the SKCM (n = 337) and NSCLC (n = 305) TCGA datasets to explicitly test if sequence similarity to known antigens from the IEDB is associated with tumor infiltrating lymphocyte (TIL) burden in patients, as measured by TCR sequencing and CDR reconstruction in RNA-seq data. We find that there is no statistically significant association between either the inferred clonality or magnitude of TIL response and neoepitope sequence similarity to known antigens. We do, however, find significant, moderate associations of TIL response to neoepitope burden. Further, we examined the LIHC (n = 193) and UCEC (n = 245) TCGA cohorts to explicitly derive tumor and virally derived epitopes (HepB, HPV respectively) and ranked their relative predicted MHC binding affinity profiles. We find a greater MHC binding affinity bias exists towards neoepitopes compared to virally derived peptides in a natural setting where both viral and tumor antigens are simultaneously present. Moreover, we find low and significant associations between TIL burden and overall neoepitope burden, but no association with overall viral epitope or expression burden. Finally, we used multiregionally sampled data (12 patients, 72 regions) from HepB-positive HCC liver cancer patients to confirm preferential MHC binding affinity and TIL response bias towards neoepitopes still holds and is significant. Our results suggest that neoepitopes dominate in their recruitment potential of, and association with, TIL burden compared to viral-cofactors. They also suggest that neoepitope sequence similarity to known antigens does not recapitulate patient TIL burden to first approximation. Citation Format: Adrian Bubie, Nicholas Akers, Augusto Villanueva, Bojan Losic. Validating sequence similarity-driven neoepitope fitness models via immunogenomics on TCGA and multiregional tumor data [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr B071.