Bioinformatics for Cancer Immunotherapy

Methods Mol Biol. 2020;2120:1-9. doi: 10.1007/978-1-0716-0327-7_1.

Abstract

Our immune system plays a key role in health and disease as it is capable of responding to foreign antigens as well as acquired antigens from cancer cells. Latter are caused by somatic mutations, the so-called neoepitopes, and might be recognized by T cells if they are presented by HLA molecules on the surface of cancer cells. Personalized mutanome vaccines are a class of customized immunotherapies, which is dependent on the detection of individual cancer-specific tumor mutations and neoepitope (i.e., prediction, followed by a rational vaccine design, before on-demand production. The development of next generation sequencing (NGS) technologies and bioinformatic tools allows a large-scale analysis of each parameter involved in this process. Here, we provide an overview of the bioinformatic aspects involved in the design of personalized, neoantigen-based vaccines, including the detection of mutations and the subsequent prediction of potential epitopes, as well as methods for associated biomarker research, such as high-throughput sequencing of T-cell receptors (TCRs), followed by data analysis and the bioinformatics quantification of immune cell infiltration in cancer samples.

Keywords: Bioinformatics; Cancer; Immunotherapy; Mutation; T cell.

Publication types

  • Review

MeSH terms

  • Animals
  • Cancer Vaccines / immunology
  • Cancer Vaccines / therapeutic use
  • Computational Biology / methods*
  • Humans
  • Immunotherapy / methods*
  • Mutation
  • Neoplasms / genetics
  • Neoplasms / immunology
  • Neoplasms / therapy*
  • T-Lymphocytes / immunology

Substances

  • Cancer Vaccines