Publication

pVAC-Seq: A genome-guided in silico approach to identifying tumor neoantigens.

Genome Med. 2016 Jan 29;8(1):11. doi: 10.1186/s13073-016-0264-5.

Abstract

Cancer immunotherapy has gained significant momentum from recent clinical successes of checkpoint blockade inhibition. Massively parallel sequence analysis suggests a connection between mutational load and response to this class of therapy. Methods to identify which tumor-specific mutant peptides (neoantigens) can elicit anti-tumor T cell immunity are needed to improve predictions of checkpoint therapy response and to identify targets for vaccines and adoptive T cell therapies. Here, we present a flexible, streamlined computational workflow for identification of personalized Variant Antigens by Cancer Sequencing (pVAC-Seq) that integrates tumor mutation and expression data (DNA- and RNA-Seq). pVAC-Seq is available at https://github.com/griffithlab/pVAC-Seq .

Authors

Hundal J, Carreno BM, Petti AA, Linette GP, Griffith OL, Mardis ER, Griffith M.