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

Area of Science:

• Computational biology
• Immunoinformatics
• Cancer immunology

Background:

• Checkpoint blockade therapies and neoantigen vaccines are advancing.
• Computational tools are crucial for identifying and prioritizing neoantigens.
• pVACtools is an established open-source suite for neoantigen research.

Purpose of the Study:

• To describe major updates to the pVACtools suite.
• To enhance neoantigen prediction, prioritization, and vaccine design capabilities.
• To reinforce pVACtools as a comprehensive toolkit for neoantigen research.

Main Methods:

• Expanded quality and safety assessment features for neoantigens.
• Introduced pVACsplice for splicing mutation neoantigens and pVACbind for noncanonical sources.
• Improved pVACvector algorithm for vaccine design and added pVACcompare for result comparison.
• Extended support for non-human species and synthetic long peptide vaccine design.

Main Results:

• Enhanced neoantigen assessment including peptide presentation, immunogenicity, and similarity analysis.
• New tools facilitate neoantigen discovery from splicing mutations and other sources.
• Improved vaccine vector design algorithms and comparison utilities.
• Expanded species support for broader research applications.

Conclusions:

• The updated pVACtools suite provides advanced capabilities for neoantigen discovery and prioritization.
• New features enhance the design and execution of personalized cancer vaccine clinical trials.
• pVACtools remains a leading comprehensive toolkit for neoantigen research from discovery to clinical application.