Quantitative and large-scale investigation of human TCR-HLA cross-reactivity

The interaction between human leukocyte antigens (HLAs) and T cell receptor (TCR) is essential for adaptive immune recognition. While it is known that one TCR can map to multiple HLA alleles, the extent of this cross-reactivity remains poorly understood. Here, we introduce THNet, a TCR-based HLA similarity network, and present a comprehensive analysis of HLA-TCR cross-reactivity, which is built upon more than 9 million significantly associated HLA-TCR pairs. We created similarity networks for both class I and class II HLA alleles, illustrating how peptide cross-presentation contributes to HLA-TCR cross-reactivity. Our analysis revealed disease susceptibilities missed by single-HLA enrichment analyses, especially in the Black population. Last, we demonstrated that THNet can prioritize optimal HLA mismatch candidates across different transplantation contexts, supporting its potential utility in donor selection strategies. In summary, our investigation of the HLA-TCR cross-reactive network provides useful insights into autoimmune risk prediction and improved transplantation outcomes.