neoantigen-vaccine-design

To design a canine neoantigen vaccine, you integrate tumor-normal sequencing to call somatic variants, perform DLA/MHC typing, and predict neoantigens using pvactools. The workflow outputs a ranked candidate list and guidance for constructing mRNA or peptide vaccines.

Veterinary MHC typing and neoantigen prediction for feline and equine cancers adapt pvactools and NetMHCpan cross-species. The process involves identifying somatic variants from sequencing data and using MHC binding predictions to prioritize strong neoantigen candidates for vaccine development.

You need tumor and normal tissue sequencing data to start a personalized animal cancer vaccine pipeline. This data drives somatic variant calling, DLA/MHC typing, and neoantigen prediction to ultimately produce a ranked list of vaccine candidates.

Yes, you can use AlphaFold and MHCflurry for veterinary neoantigen prediction. The neoantigen design pipeline integrates these tools alongside NetMHCpan to evaluate MHC binding and structural characteristics, yielding ranked neoantigen candidates for mRNA or peptide vaccines.

Cross-species MHC binding prediction for veterinary immunotherapy relies on adapting tools like NetMHCpan to non-human DLA and MHC alleles. Limitations include prediction accuracy constraints for less-characterized species, requiring careful candidate prioritization and veterinary immunology considerations.