@article{d7567b242d9249af8fa733f9200fdf1a,
title = "pVAC-Seq: A genome-guided in silico approach to identifying tumor neoantigens",
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.",
author = "Jasreet Hundal and Carreno, {Beatriz M.} and Petti, {Allegra A.} and Linette, {Gerald P.} and Griffith, {Obi L.} and Mardis, {Elaine R.} and Malachi Griffith",
note = "Funding Information: We are grateful for creative and computational input from Zachary L. Skidmore, Susanna Siebert, Todd N. Wylie, Jason R. Walker, and Chris A. Miller. We thank Dr. Robert D. Schreiber for his expertise and guidance on foundational mouse models work. Dr. William E. Gillanders provided important scientific input to the pipeline development work. MG was supported by the National Human Genome Research Institute (K99 HG007940). OLG was supported by the National Cancer Institute (K22 CA188163). BC, GPL, and JH were supported by the National Cancer Institute (R21 CA179695). ERM was supported by the National Cancer Institute (R21 CA179695) and the National Human Genome Research Institute (NIH NHGRI U54 HG003079). AAP was supported by the National Human Genome Research Institute (NHGRI U54 HG003079). Publisher Copyright: {\textcopyright} 2016 Hundal et al.",
year = "2016",
month = jan,
day = "29",
doi = "10.1186/s13073-016-0264-5",
language = "English",
volume = "8",
journal = "Genome Medicine",
issn = "1756-994X",
number = "1",
}