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Updated: Apr 28, 2026
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Published on: March 24, 2015
HLA-binding properties of tumor neoepitopes in humans
Edward F Fritsch1, Mohini Rajasagi2, Patrick A Ott2
1Authors' Affiliations: Cancer Vaccine Center; Department of Medical Oncology, Dana-Farber Cancer Institute; The Division of Allergy, Immunology, and Rheumatology, Department of Medicine, Massachusetts General Hospital; Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston; and Broad Institute of MIT and Harvard, Cambridge, MassachusettsAuthors' Affiliations: Cancer Vaccine Center; Department of Medical Oncology, Dana-Farber Cancer Institute; The Division of Allergy, Immunology, and Rheumatology, Department of Medicine, Massachusetts General Hospital; Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston; and Broad Institute of MIT and Harvard, Cambridge, MassachusettsAuthors' Affiliations: Cancer Vaccine Center; Department of Medical Oncology, Dana-Farber Cancer Institute; The Division of Allergy, Immunology, and Rheumatology, Department of Medicine, Massachusetts General Hospital; Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston; and Broad Institute of MIT and Harvard, Cambridge, Massachusetts.
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.
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