Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2021 Jun 7:11:683419.
doi: 10.3389/fonc.2021.683419. eCollection 2021.

FDA-Approved and Emerging Next Generation Predictive Biomarkers for Immune Checkpoint Inhibitors in Cancer Patients

Ye Wang  1 , Zhuang Tong  2 , Wenhua Zhang  1 , Weizhen Zhang  3 , Anton Buzdin  4   5   6 , Xiaofeng Mu  1   7 , Qing Yan  1 , Xiaowen Zhao  1 , Hui-Hua Chang  8 , Mark Duhon  8 , Xin Zhou  9 , Gexin Zhao  8 , Hong Chen  9 , Xinmin Li  8
Affiliations
Review

FDA-Approved and Emerging Next Generation Predictive Biomarkers for Immune Checkpoint Inhibitors in Cancer Patients

Ye Wang et al. Front Oncol. .

Abstract

A patient's response to immune checkpoint inhibitors (ICIs) is a complex quantitative trait, and determined by multiple intrinsic and extrinsic factors. Three currently FDA-approved predictive biomarkers (progra1mmed cell death ligand-1 (PD-L1); microsatellite instability (MSI); tumor mutational burden (TMB)) are routinely used for patient selection for ICI response in clinical practice. Although clinical utility of these biomarkers has been demonstrated in ample clinical trials, many variables involved in using these biomarkers have poised serious challenges in daily practice. Furthermore, the predicted responders by these three biomarkers only have a small percentage of overlap, suggesting that each biomarker captures different contributing factors to ICI response. Optimized use of currently FDA-approved biomarkers and development of a new generation of predictive biomarkers are urgently needed. In this review, we will first discuss three widely used FDA-approved predictive biomarkers and their optimal use. Secondly, we will review four novel gene signature biomarkers: T-cell inflamed gene expression profile (GEP), T-cell dysfunction and exclusion gene signature (TIDE), melanocytic plasticity signature (MPS) and B-cell focused gene signature. The GEP and TIDE have shown better predictive performance than PD-L1, and PD-L1 or TMB, respectively. The MPS is superior to PD-L1, TMB, and TIDE. The B-cell focused gene signature represents a previously unexplored predictive biomarker to ICI response. Thirdly, we will highlight two combined predictive biomarkers: TMB+GEP and MPS+TIDE. These integrated biomarkers showed improved predictive outcomes compared to a single predictor. Finally, we will present a potential nucleic acid biomarker signature, allowing DNA and RNA biomarkers to be analyzed in one assay. This comprehensive signature could represent a future direction of developing robust predictive biomarkers, particularly for the cold tumors, for ICI response.

Keywords: FDA-approved biomarkers; PD-1; TMB; immune checkpoint inhibitors; predictive biomarkers.

PubMed Disclaimer

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Intrinsic and extrinsic biomarkers predictive of ICI response. Intrinsic biomarkers are tumor cell-related, extrinsic biomarkers are tumor microenvironment-related.
Figure 2
Figure 2
Patient response to ICIs is a quantitative trait. Each biomarker only captures a unique feature of the contributing factor (s).
See this image and copyright information in PMC

References

    1. Vaddepally RK, Kharel P, Pandey R, Garje R, Chandra AB. Review of Indications of FDA-Approved Immune Checkpoint Inhibitors Per NCCN Guidelines With the Level of Evidence. Cancers (Basel) (2020) 12(3):738–57. 10.3390/cancers12030738 - DOI - PMC - PubMed
    1. Davis AA, Patel VG. The Role of PD-L1 Expression as a Predictive Biomarker: An Analysis of All US Food and Drug Administration (FDA) Approvals of Immune Checkpoint Inhibitors. J Immunother Cancer (2019) 7(1):278. 10.1186/s40425-019-0768-9 - DOI - PMC - PubMed
    1. Gascon M, Isla D, Cruellas M, Galvez EM, Lastra R, Ocariz M, et al. . Intratumoral Versus Circulating Lymphoid Cells as Predictive Biomarkers in Lung Cancer Patients Treated With Immune Checkpoint Inhibitors: Is the Easiest Path the Best One? Cells (2020) 9(6):1525–41. 10.3390/cells9061525 - DOI - PMC - PubMed
    1. Hennequart M, Pilotte L, Cane S, Hoffmann D, Stroobant V, Plaen E, et al. . Constitutive IDO1 Expression in Human Tumors is Driven by Cyclooxygenase-2 and Mediates Intrinsic Immune Resistance. Cancer Immunol Res (2017) 5(8):695–709. 10.1158/2326-6066.CIR-16-0400 - DOI - PubMed
    1. Shin DS, Zaretsky JM, Escuin-Ordinas H, Garcia-Diaz A, Hu-Lieskovan S, Kalbasi A, et al. . Primary Resistance to PD-1 Blockade Mediated by JAK1/2 Mutations. Cancer Discov (2017) 7(2):188–201. 10.1158/2159-8290.CD-16-1223 - DOI - PMC - PubMed