Abstract
Antigen recognition by CD8+ T-cell receptors (TCR) is crucial for immune responses to pathogens and tumors. TCRs are cross-reactive, a single TCR can recognize multiple peptide-Human Leukocyte Antigen (HLA) complexes. The study of cross-reactivity can support the development of therapies focusing on immune modulation, such as the expansion of pre-existing T-cell clones to fight pathogens and tumors. The peptide-HLA (pHLA) surface has previously been used to identify TCR cross-reactivities. In the present work, we sought to perform a comprehensive analysis of peptide-HLA by selecting thousands of human and viral epitopes. We profit from established docking models to identify features from different spatial perspectives of HLA-A*02:01, explore similarities between self and non-self epitopes, and list potential cross-reactive epitopes of therapeutic interest. A total of 2631 unique epitopes from representative viral proteins or human proteins were modeled. We were able to demonstrate that cross-reactive CDR3 sequences from public databases recognize epitopes with similar electrostatic potential, charge, and spatial location. Using data from published studies that measured T-cell reactivity to mutated epitopes, we observed a negative correlation between epitope dissimilarity and T-cell activation. Most analysed cancer epitopes were more similar to self epitopes, yet we identified features distinguishing those more similar to viral antigens. Finally, we enumerated potential cross-reactivities between tumoral and viral epitopes and highlighted some challenges in their identification for therapeutic use. Moreover, the thousands of peptide-HLA complexes generated in our work constitute a valuable resource to study T-cell cross-reactivity.