An Analysis of Natural T Cell Responses to Predicted Tumor Neoepitopes

Anne-Mette Bjerregaard, Morten Nielsen, Vanessa Isabell Jurtz, Carolina M. Barra, Sine Reker Hadrup, Zoltan Imre Szallasi, Aron Charles Eklund

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    Abstract

    Personalization of cancer immunotherapies such as therapeutic vaccines and adoptive T-cell therapy may benefit from efficient identification and targeting of patient-specific neoepitopes. However, current neoepitope prediction methods based on sequencing and predictions of epitope processing and presentation result in a low rate of validation, suggesting that the determinants of peptide immunogenicity are not well understood. We gathered published data on human neopeptides originating from single amino acid substitutions for which T cell reactivity had been experimentally tested, including both immunogenic and non-immunogenic neopeptides. Out of 1,948 neopeptide-HLA (human leukocyte antigen) combinations from 13 publications, 53 were reported to elicit a T cell response. From these data, we found an enrichment for responses among peptides of length 9. Even though the peptides had been pre-selected based on presumed likelihood of being immunogenic, we found using NetMHCpan-4.0 that immunogenic neopeptides were predicted to bind significantly more strongly to HLA compared to non-immunogenic peptides. Investigation of the HLA binding strength of the immunogenic peptides revealed that the vast majority (96%) shared very strong predicted binding to HLA and that the binding strength was comparable to that observed for pathogen-derived epitopes. Finally, we found that neopeptide dissimilarity to self is a predictor of immunogenicity in situations where neo- and normal peptides share comparable predicted binding strength. In conclusion, these results suggest new strategies for prioritization of mutated peptides, but new data will be needed to confirm their value.
    Original languageEnglish
    Article number1566
    JournalFrontiers in Immunology
    Volume8
    ISSN1664-3224
    DOIs
    Publication statusPublished - 2017

    Bibliographical note

    This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY).

    Keywords

    • Neoepitopes
    • Neoantigens
    • Prediction
    • Immunogenicity
    • Mutations
    • MHC binding

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