Abstract
Immune checkpoint inhibitors produce durable antitumor effects in various cancers, but not all patients respond. High tumor mutational burden (TMB) is a known predictor of clinical benefit. In this study, we focused on the MHC-I-dependent neoantigen presentation pathway to enhance predictive capabilities beyond TMB. Using pan-cancer immunogenomic analyses of somatic mutation data from The Cancer Genome Atlas (TCGA) and The International Cancer Genome Consortium (ICGC), we analyzed 33 cancer types. Objective response rates (ORRs) to PD-1/PD-L1 inhibitors were evaluated in relation to immune characteristics, including TMB, neoantigen load, MHC-I gene expression, and CD8+ T cell fraction. Spearman's rank correlation was used to assess these relationships. TMB showed the strongest correlation with ORR (r = 0.783, P = 2.17 × 10⁻⁵). However, integrating TMB, HLA-A expression, and CD8+ T cell fraction significantly improved predictive accuracy (r = 0.865, P = 1.80 × 10⁻⁶). Validation in external cohorts confirmed these findings, revealing notable differences in MHC-I pathway activity between responders and non-responders to immunotherapy. Our results demonstrate that the MHC-I antigen presentation pathway is strongly associated with response to PD-1/PD-L1 inhibitors. Importantly, combining antigen expression, processing, presentation, and recognition features provides superior predictive power compared to TMB alone. This integrated approach could improve treatment outcome predictions and advance personalized immunotherapy strategies.