Strategies for Predicting Response to Checkpoint Inhibitors

Purpose of ReviewDespite the clinical successes of immune checkpoint blockade across multiple tumor types, many patients do not respond to these therapies or become resistant after an initial response. This underscores the need to improve our understanding of the molecular determinants of response to guide more personalized and rational utilization of these therapies. Here, we describe available biomarkers of checkpoint blockade activity by classifying them into four major categories: tumor-intrinsic, immune microenvironmental, host-related, and dynamic factors.Recent FindingsThe clinical experience accumulated thus far with checkpoint blockade now offers the opportunity to comprehensively study the molecular and immune features associated with response. This is yielding a growing set of biomarkers whose integration will be key to more accurately predict clinical outcome.SummaryWe propose a model for systematic assessment of available baseline and dynamic biomarkers in relationship with patients' outcomes. This will improve our understanding of the tumor-immune interactions and dynamics that predict a clinical response and will provide key information to develop more personalized and effective treatment strategies.