- uProteins session contribution -
The identification of non-canonical antigens has emerged as an essential aspect of immunopeptidomics, driving advancements in our understanding of immune responses and disease mechanisms which were missed with conventional approaches and hence left unexplored. As the field evolves, stringent quality control measures are essential to ensure high confidence in peptide identifications, particularly for peptides encoded by non-canonical genome regions and uncharacterised RNA variants. Emerging strategies including machine learning models, Omics data integration, and improved de novo sequencing algorithms enhance our ability of non-canonical antigen identification using mass spectrometry. Streamlining these approaches will enable us to systematically explore non-canonical, HLA-presented peptide repertoires, and facilitate the development of therapeutics targeting this novel space of antigens.