• Jasreet Hundal, Beatriz M Carreno, Allegra A Petti, Gerald P Linette, Obi L Griffith, Elaine R Mardis, and Malachi Griffith.
• McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA. jhundal@genome.wustl.edu.
• Genome Med. 2016 Jan 29; 8 (1): 11.

AbstractCancer 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 .

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