HLA-binding properties of tumor neoepitopes in humans.

Cancer Immunol Res
Publication type
Journal Article
Authors
Keywords
Abstract

Cancer genome sequencing has enabled the rapid identification of the complete repertoire of coding sequence mutations within a patient's tumor and facilitated their use as personalized immunogens. Although a variety of techniques are available to assist in the selection of mutation-defined epitopes to be included within the tumor vaccine, the ability of the peptide to bind to patient MHC is a key gateway to peptide presentation. With advances in the accuracy of predictive algorithms for MHC class I binding, choosing epitopes on the basis of predicted affinity provides a rapid and unbiased approach to epitope prioritization. We show herein the retrospective application of a prediction algorithm to a large set of bona fide T cell-defined mutated human tumor antigens that induced immune responses, most of which were associated with tumor regression or long-term disease stability. The results support the application of this approach for epitope selection and reveal informative features of these naturally occurring epitopes to aid in epitope prioritization for use in tumor vaccines.

Year of Publication
2014
Journal
Cancer Immunol Res
Volume
2
Issue
6
Pages
522-9
Date Published
2014 Jun
ISSN
2326-6074
URL
DOI
10.1158/2326-6066.CIR-13-0227
PubMed ID
24894089
PubMed Central ID
PMC4049249
Links
Grant list
R01 CA155010 / CA / NCI NIH HHS / United States
R01 HL103532 / HL / NHLBI NIH HHS / United States
1R01CA155010-02 / CA / NCI NIH HHS / United States
R01 HL103532-03 / HL / NHLBI NIH HHS / United States