Automating biomarker identification for immunotherapies: Non-canonical peptides presented on MHC molecules

Abstract

Neo-antigens are a promising area of research in the development of immunotherapies against cancer. The neo-antigens arise due to mutations in cancerous cell, which often helps the cancer cell to hide from the surveillance of the immune system. In the last decade, the amount of mass spectrometry data has been growing exponentially. Researchers often found that the origin of all peptides eluted from cancer cells could not be mapped, which suggest that the tumor alters the translation process to generate new peptides that are presented in the MHC-complex on the cell surface. Obviously, this finding opens up a totally new area for cancer specific biomarkers. Here we present our pipeline to identify these non-canonical (cryptic) peptide candidates from RNA count data.