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Медицинская библиотека · ArXiv · 2026

pVACtools v6: A comprehensive suite for neoantigen prediction, visualization, and therapy design.

Hoang My H, Kiwala Susanna, Richters Megan, Hendrickson Luke, Xia Huiming, Schmidt Evelyn, Miller Christopher A, Cotto Kelsy C, Lichti Cheryl F, Skidmore Zach, Singhal Kartik, Yao Jennie X, Li Jinglun, Khanfar Mariam, Risch Isabel, Ward Jeffrey, Govindan Ramaswamy, Dunn Gavin, Johanns Tanner M, Goedegebuure S Peter, Fehniger Todd A, Karchin Rachel, Schreiber Robert D, Gillanders William, Griffith Obi L, Griffith Malachi

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With the rise of checkpoint blockade therapies and neoantigen-based vaccines reaching later-stage trials, there is a growing need for computational tools to identify and prioritize neoantigens. pVACtools, initially introduced in 20161, is an open-source informatic suite designed to support basic and translational neoantigen research. pVACtools assists prediction, prioritization, and visualization of neoantigens, as well as design of neoantigen-based therapies. We describe several major advances to pVACtools since the last update: (1) expanded neoantigen quality and safety assessment features, including support for peptide presentation scoring, immunogenicity prediction, anchor residue analysis, reference proteome similarity, percentile score calculation; (2) addition of pVACsplice, a new tool for predicting neoantigens from tumor-specific cis-splicing mutations; (3) addition of pVACbind, a flexible tool that supports noncanonical neoantigen sources; (4) improvement in neoantigen selection strategies; (5) a substantially improved pVACvector algorithm that achieves higher DNA/mRNA vector vaccine design success rates with shorter runtimes; (6) new utilities to support synthetic long peptide vaccine design; (7) extended prediction support for many non-human species; and (8) addition of pVACcompare, a tool to support comparison between two pVACseq results. Together, these updates reinforce pVACtools as the field's most comprehensive toolkit for neoantigen research, from basic discovery to the design and execution of personalized cancer vaccine clinical trials.

Для цитирования: Hoang My H, Kiwala Susanna, Richters Megan, Hendrickson Luke, Xia Huiming, Schmidt Evelyn, Miller Christopher A, Cotto Kelsy C, Lichti Cheryl F, Skidmore Zach, Singhal Kartik, Yao Jennie X, Li Jinglun, Khanfar Mariam, Risch Isabel, Ward Jeffrey, Govindan Ramaswamy, Dunn Gavin, Johanns Tanner M, Goedegebuure S Peter, Fehniger Todd A, Karchin Rachel, Schreiber Robert D, Gillanders William, Griffith Obi L, Griffith Malachi. pVACtools v6: A comprehensive suite for neoantigen prediction, visualization, and therapy design.. ArXiv. 2026.
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