Next generation predictive biomarkers for immune checkpoint inhibition

With the advent of targeted therapies, there has been a revolution in the treatment of cancer across multiple histologies. Immune checkpoint blockade has made it possible to take advantage of receptor-ligand interactions between immune and tumor cells in a wide spectrum of malignancies. Toxicity in healthy tissue, however, can limit our use of these agents. Immune checkpoint blockade has been approved in advanced melanoma, renal cell cancer, non-small cell lung cancer, relapsed refractory Hodgkin's lymphoma, and urothelial cancer. Though FDA-approved indications for use of some of these novel agents depend on current protein-based programmed death 1 (PD-1) and programmed death ligand 1 (PD-L1) assays, detection methods come with several caveats. Additional predictive tools must be interrogated to discern responders from non-responders. Some of these include measurement of microsatellite instability, PD-L1 amplification, cluster of differentiation 8 (CD8) infiltrate density, and tumor mutational burden. This review serves to synthesize biomarker detection at the DNA, RNA, and protein level to more accurately forecast benefit from these novel agents.