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Review
. 2020 Aug 26:8:34.
doi: 10.1186/s40364-020-00209-0. eCollection 2020.

Predictive biomarkers for cancer immunotherapy with immune checkpoint inhibitors

Rilan Bai  1 , Zheng Lv  1 , Dongsheng Xu  1 , Jiuwei Cui  1
Affiliations
Review

Predictive biomarkers for cancer immunotherapy with immune checkpoint inhibitors

Rilan Bai et al. Biomark Res. .

Abstract

Although the clinical development of immune checkpoint inhibitors (ICIs) therapy has ushered in a new era of anti-tumor therapy, with sustained responses and significant survival advantages observed in multiple tumors, most patients do not benefit. Therefore, more and more attention has been paid to the identification and development of predictive biomarkers for the response of ICIs, and more in-depth and comprehensive understanding has been continuously explored in recent years. Predictive markers of ICIs efficacy have been gradually explored from the expression of intermolecular interactions within tumor cells to the expression of various molecules and cells in tumor microenvironment, and been extended to the exploration of circulating and host systemic markers. With the development of high-throughput sequencing and microarray technology, a variety of biomarker strategies have been deeply explored and gradually achieved the process from the identification of single marker to the development of multifactorial synergistic predictive markers. Comprehensive predictive-models developed by integrating different types of data based on different components of tumor-host interactions is the direction of future research and will have a profound impact in the field of precision immuno-oncology. In this review, we deeply analyze the exploration course and research progress of predictive biomarkers as an adjunctive tool to tumor immunotherapy in effectively identifying the efficacy of ICIs, and discuss their future directions in achieving precision immuno-oncology.

Keywords: Immune checkpoint inhibitor; Neoplasm; Predictive biomarker; Programmed death ligand-1; Tumor mutation burden.

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Conflict of interest statement

Competing interestsThe authors declare that there are no conflicts of interest.

Figures

Fig. 1
Fig. 1
An overview of predictive biomarkers for immune checkpoint inhibitors efficacy. Key elements in predictive biomarker development for the efficacy of immune checkpoint inhibitors therapy are briefly described in the figure, including tumor cells-related biomarkers, tumor immune microenvironment phenotype biomarkers, circulating factors, host-related factors, and immune-related adverse events
See this image and copyright information in PMC

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