Abstract 4413: Accurate neoantigen prediction depends on mutation position relative to patient-specific MHC anchor location

Abstract

Abstract Neoantigens (neoAgs) are short peptide sequences resulting from somatic mutations specifically found in tumor populations. They can be loaded onto major histocompatibility complex (MHC) class I or II molecules to allow recognition by cytotoxic T cells. Accurate neoAg prediction is critical for the design of personalized vaccines and may improve prediction of response to immune checkpoint blockade therapy. The effectiveness of a neoAg-based vaccine relies in part on whether the sequence presented to T cells has previously been exposed to the immune system. Incorrectly selecting for wildtype (WT) peptides will result in susceptibility to central tolerance and potentially induce auto-immunity. As the vast majority of somatic mutations found are single nucleotide variants, changes between the WT and mutant (MT) peptide are subtle and must be interpreted cautiously. An important yet currently overlooked factor in neoAg predicting pipelines is the position of the mutation within the peptide relative to its anchor positions for the patient's human leukocyte antigen (HLA) alleles. Current pipelines consider simple filtering strategies (e.g. MT peptide IC50 < 500 nM and WT/MT binding affinity fold change (agretopicity) > 1); however, only a subset of positions on the loaded peptide sequence are presented to the T cell receptor for recognition, while other positions are responsible for anchoring to the MHC, making these positional considerations critical for predicting T cell responses. We have collected peptide data, through clinical collaborations and The Cancer Genome Atlas (TCGA), for over 200 commonly observed HLA alleles and computationally predicted high probability anchor positions with respect to different peptide lengths (8-11mers). We observed unique anchoring patterns among different HLA alleles, varying in sequence positions and number of anchoring locations within the binding groove. To demonstrate the importance of positional information on prioritization of neoAgs, we are additionally analyzing 1000 TCGA patient samples where potential neoAgs are filtered according to different criteria including: A) MT IC50 < 500 nM, B) MT IC50 < 500 nM and agretopicity > 1, C) MT IC50 < 500 nM with data-driven filtering based on peptide mutation position, MHC anchor position and WT IC50 value. The number of potentially misclassified neoAg candidates will be accessed using experimentally validated neoAg datasets. Currently, prediction pipelines have relatively low accuracy when prioritizing neoAgs for T cell response in patients. By accounting for additional positional information, we hope to significantly reduce the number of false positive neoAgs and increase prediction accuracy. Our anchor results will be implemented as a visualization guide for tumor immunogenomics boards for clinical trials and incorporated into our existing neoAg prioritization pipeline, pVACtools. Citation Format: Huiming Xia, Megan M. Richters, Cody A. Ramirez, Cristina Puig-Saus, Kelsy C. Cotto, Gavin P. Dunn, Todd Fehniger, Antoni Ribas, William E. Gillanders, Obi L. Griffith, Malachi Griffith. Accurate neoantigen prediction depends on mutation position relative to patient-specific MHC anchor location [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4413.