Integrated germline and somatic features reveal divergent immune pathways driving ICB response.

We used machine learning to study ICB response across 708 patients from 8 studies across 3 tumor types (melanoma, RCC, and NSCLC).Combining germline and somatic features improves prediction of ICB responseInteractions between germline and somatic features reveal mechanisms contributing to ICB sensitivity.MHC-I vs. MHC-II reliance implicates LAG3 as a prognostic biomarker in the context of CD4 T cell driven responses.MHC-II neoantigen reliant responses provide superior durable clinical benefit in response to ICB.