Dataset Information

Defining HLA-II ligand processing and binding rules with mass spectrometry enhances cancer epitope prediction

ABSTRACT: Increasing evidence indicates CD4+ T cells can recognize cancer-specific antigens and control tumor growth. However, it remains difficult to predict the antigens that will be presented by human leukocyte antigen class II molecules (HLA-II) - hindering efforts to optimally target them therapeutically. Obstacles include inaccurate peptide-binding prediction and unsolved complexities of the HLA-II pathway. To address these challenges, we introduce an improved technology for discovering HLA-II binding motifs and conduct a comprehensive analysis of tumor-ligandomes to learn processing rules relevant in the tumor microenvironment (TME). We profiled HLA-II alleles and showed that binding motifs are highly sensitive to HLA-DM, a peptide loading chaperone. We also revealed that intratumoral HLA-II presentation is dominated by professional antigen presenting cells (APCs), rather than cancer cells. Integrating these observations, we developed algorithms that accurately predict APC ligandomes, including peptides from phagocytosed cancer cells. These tools and biological insights will enhance HLA-II directed cancer therapies.

INSTRUMENT(S): Orbitrap Fusion Lumos

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Jennifer Abelin