Integrated Germline and Somatic Features Reveal Divergent Immune Pathways Driving Response to Immune Checkpoint Blockade.

ABSTRACT: Immune checkpoint blockade (ICB) has revolutionized cancer treatment; however, the mechanisms determining patient response remain poorly understood. Here, we used machine learning to predict ICB response from germline and somatic biomarkers and interpreted the learned model to uncover putative mechanisms driving superior outcomes. Patients with higher infiltration of T-follicular helper cells had responses even in the presence of defects in the MHC class-I (MHC-I). Further investigation uncovered different ICB responses in tumors when responses were reliant on MHC-I versus MHC-II neoantigens. Despite similar response rates, MHC II-reliant responses were associated with significantly longer durable clinical benefits (discovery: median overall survival of 63.6 vs. 34.5 months; P = 0.0074; va

SUBMITTER: Sears TJ 

PROVIDER: S-EPMC11612627 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature