Characterizing neoantigens for personalized cancer immunotherapy

Curr Opin Immunol. 2017 Jun;46:58-65. doi: 10.1016/j.coi.2017.04.007. Epub 2017 May 4.

Abstract

Somatic mutations can generate neoantigens that are presented on MHC molecules and drive effective T cells responses against cancer. Mutation load in cancer patients predicts response to immune checkpoint blockade therapy. Additionally, vaccination targeting neoantigens controls established tumor growth in preclinical models. These recent findings led to a renewed interest in the field of cancer vaccines and the development of antigen-targeted cancer immunotherapies. However, targeting neoantigens is challenging, as most mutations are unique to each cancer patient. In addition, only a small fraction of the mutations are immunogenic and therefore their accurate prediction is critical. In this review, we discuss the properties of neoantigens that influence their immunogenicity, along with questions that remain to be addressed in order to improve prediction algorithms.

Publication types

  • Review

MeSH terms

  • Algorithms
  • Antigen Presentation / immunology
  • Antigens, Neoplasm / genetics
  • Antigens, Neoplasm / immunology*
  • Clonal Evolution / genetics
  • Endoplasmic Reticulum / metabolism
  • Epitopes / chemistry
  • Epitopes / immunology
  • Histocompatibility Antigens Class I / immunology
  • Histocompatibility Antigens Class I / metabolism
  • Humans
  • Immunotherapy* / methods
  • Mutation
  • Neoplasms / genetics
  • Neoplasms / immunology*
  • Neoplasms / metabolism
  • Neoplasms / therapy*
  • Peptides / chemistry
  • Peptides / immunology
  • Precision Medicine* / methods
  • Protein Binding / immunology
  • Protein Transport
  • Receptors, Antigen, T-Cell / metabolism
  • T-Lymphocyte Subsets / immunology
  • T-Lymphocyte Subsets / metabolism

Substances

  • Antigens, Neoplasm
  • Epitopes
  • Histocompatibility Antigens Class I
  • Peptides
  • Receptors, Antigen, T-Cell