Abstract
Despite the central role of human leukocyte antigen class I (HLA-I) in tumor neoantigen presentation, quantitative determination of presentation capacity remains elusive. Based on a pooled pan-cancer genomic dataset of 885 patients treated with immune checkpoint inhibitors (ICIs), we developed a score integrating the binding affinity of neoantigens to HLA-I, as well as HLA-I allele divergence, termed the HLA tumor-Antigen Presentation Score (HAPS). Patients with a high HAPS were more likely to experience survival benefit following ICI treatment. Analysis of the tumor microenvironment indicated that the antigen presentation pathway was enriched in patients with a high HAPS. Finally, we built a neural network incorporating factors associated with neoantigen production, presentation, and recognition, which exhibited potential for differentiating cancer patients likely to benefit from ICIs. Our findings highlight the clinical utility of evaluating HLA-I tumor antigen presentation capacity and describe how ICI response may depend on HLA-mediated immunity.