Informatics for cancer immunotherapy

Abstract

The rapid development of immunomodulatory cancer therapies has led to a concurrent increase in the application of informatics techniques to the analysis of tumors, the tumor microenvironment, and measures of systemic immunity. In this review, the use of tumors to gather genetic and expression data will first be explored. Next, techniques to assess tumor immunity are reviewed, including HLA status, predicted neoantigens, immune microenvironment deconvolution, and T-cell receptor sequencing. Attempts to integrate these data are in early stages of development and are discussed in this review. Finally, we review the application of these informatics strategies to therapy development, with a focus on vaccines, adoptive cell transfer, and checkpoint blockade therapies.

Keywords: adoptive cell transfer; bioinformatics; checkpoint blockade; computational biology; immunotherapy; neoantigens.

Figure 1.

A sample workflow for informatics in cancer immunotherapy.

Figure 2.

Quantifying heterogeneity across and within tumors. Simple mutations correspond to single-nucleotide variants and short (e.g. 30 nucleotides) insertions and deletions (i.e. indels); complex mutations include all other genome alterations.

Figure 3.

Antigen processing and presentation.

Figure 4.

Local and systemic cancer–immune interactions.

Figure 5.

Categories of therapeutic interventions in cancer immunotherapy.