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Cancer Metastasis Rev. 2017 Mar;36(1):179-190. doi: 10.1007/s10555-016-9652-y.

Next generation predictive biomarkers for immune checkpoint inhibition.

Author information

1
Center for Personalized Cancer Therapy, Division of Hematology and Oncology, University of California San Diego Moores Cancer Center, 3855 Health Sciences Dr., La Jolla, CA, 92093, USA. ykhagi@ucsd.edu.
2
Center for Personalized Cancer Therapy, Division of Hematology and Oncology, University of California San Diego Moores Cancer Center, 3855 Health Sciences Dr., La Jolla, CA, 92093, USA.

Abstract

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.

KEYWORDS:

Checkpoint inhibitor; Immunooncology; Neoantigen presentation; Predictive biomarker; Tumor microenvironment; Tumor mutational burden

PMID:
27873079
PMCID:
PMC5385298
DOI:
10.1007/s10555-016-9652-y
[Indexed for MEDLINE]
Free PMC Article

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