PRJNA489332
Functional mutations under positive selection in cancer predict therapeutic resistance to checkpoint blockade
Tumor mutation burden has a limited predictive value because a sizeable fraction of mutations is not immunogenic, and increased functional mutations can cause therapeutic resistance. Here, we investigated our patient cohort together with public cohort data by our algorithms for the modelling of peptide-MHC binding and inter-cohort genomic prediction of therapeutic resistance. We first identified samples that did not respond to checkpoint blockade despite high MHC-binding mutation load. We found that mutations responsible for therapeutic resistance disrupt the function of immune genes or their interacting proteins whose mutational patterns across a large number of tumors reflect positive selection. These functional mutations hold remarkably higher explanatory power than known resistance factors. In particular, CSMD gene mutations highlight the emerging role of the complement system as immunotherapeutic targets. Our results suggest that a systematic and evolutionary characterization of functional mutations across multiple cohorts can profoundly enhance the predictive value of mutational data.