TY - JOUR T1 - A comprehensive library of canonical and non-canonical MHC class I antigens for cancer vaccine development JF - bioRxiv DO - 10.1101/2022.01.13.475872 SP - 2022.01.13.475872 AU - Georges Bedran AU - Tongjie Wang AU - Dominika Pankanin AU - Kenneth Weke AU - Alexander Laird AU - Christophe Battail AU - Fabio Massimo Zanzotto AU - Catia Pesquita AU - Håkan Axelson AU - Ajitha Rajan AU - David J. Harrison AU - Aleksander Palkowski AU - Maciej Pawlik AU - Maciej Parys AU - Robert O’Neill AU - Paul M. Brennan AU - Stefan Symeonides AU - David R. Goodlett AU - Kevin Litchfield AU - Robin Fahraeus AU - Ted R. Hupp AU - Sachin Kote AU - Javier A. Alfaro Y1 - 2022/01/01 UR - http://biorxiv.org/content/early/2022/01/17/2022.01.13.475872.abstract N2 - A longstanding disconnect between the growing number of MHC Class I immunopeptidomic studies and genomic medicine hinders cancer vaccine design. We develop COD-dipp to genomically map the full spectrum of detected canonical and non-canonical (non-exonic) MHC Class I antigens from 26 cancer studies. We demonstrate that patient mutations in regions overlapping physically identified antigens better predict immunotherapy response when compared to neoantigen predictions. We suggest a vaccine design approach using 140,966 highly immune-visible regions of the genome annotated by their expression and haplotype frequency in the human population. These regions tend to be highly conserved, mutated in cancer and harbor 7.8 times more immunogenicity. Intersecting pan-cancer mutations with these immune surveilled regions revealed a potential to create off-the-shelf multi-epitope vaccines against public neoantigens. Here we release COD-dipp, a cancer vaccine toolkit as a web-application (https://www.proteogenomics.ca/COD-dipp) and open-source high-throughput resource.Competing Interest StatementThe authors have declared no competing interest. ER -