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REVIEW article

Front. Oncol.
Sec. Cancer Immunity and Immunotherapy
Volume 14 - 2024 | doi: 10.3389/fonc.2024.1483454
This article is part of the Research Topic Immune Plasticity and Cancer: Augmenting Therapeutic Potential of Immunotherapy against Tumor Diseases View all articles

Potential Predictive Biomarkers in Antitumor Immunotherapy: Navigating the Future of Antitumor Treatment and Immune Checkpoint Inhibitor Efficacy

Provisionally accepted
Xiangyu Yin Xiangyu Yin 1,2,3Yunjie Song Yunjie Song 3Wanglong Deng Wanglong Deng 3*Neil Blake Neil Blake 2*Xinghong Luo Xinghong Luo 3*Jia Meng Jia Meng 1,4,5*
  • 1 Department of Biological Sciences, School of Science, AI University Research Centre, Xi’an Jiaotong-Liverpool University, Suzhou, Liaoning Province, China
  • 2 Institute of Infection, Veterinary and Ecological Sciences, Faculty of Health and Life Sciences, University of Liverpool, Liverpool, North West England, United Kingdom
  • 3 Jiangsu Simcere Diagnostics Co., Ltd., Nanjing Simcere Medical Laboratory Science Co., Ltd., The State Key Laboratory of Neurology and Oncology Drug Development, Nanjing, Liaoning Province, China
  • 4 Liver Cancer Shiyan Key Laboratory, Hubei Provincial Clinical Research Center for Precise Diagnosis and Treatment of Liver Cancer, Taihe Hospital, Hubei University of Medicine, Shiyan, China
  • 5 Institute of Systems, Molecular and Integrative Biology, Faculty of Health and Life Sciences, University of Liverpool, Liverpool, United Kingdom

The final, formatted version of the article will be published soon.

    Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment modality, offering promising outcomes for various malignancies. However, the efficacy of ICIs varies among patients, highlighting the essential need of accurate predictive biomarkers. This review synthesizes the current understanding of biomarkers for ICI therapy, and discusses the clinical utility and limitations of these biomarkers in predicting treatment outcomes. It discusses three US Food and Drug Administration (FDA)-approved biomarkers, programmed cell death ligand 1 (PD-L1) expression, tumor mutational burden (TMB), and microsatellite instability (MSI), and explores other potential biomarkers, including tumor immune microenvironment (TIME)-related signatures, human leukocyte antigen (HLA) diversity, non-invasive biomarkers such as circulating tumor DNA (ctDNA), and combination biomarker strategies. The review also addresses multivariable predictive models integrating multiple features of patients, tumors, and TIME, which could be a promising approach to enhance predictive accuracy. The existing challenges are also pointed out, such as the tumor heterogeneity, the inconstant nature of TIME, nonuniformed thresholds and standardization approaches. The review concludes by emphasizing the importance of biomarker research in realizing the potential of personalized immunotherapy, with the goal of improving patient selection, treatment strategies, and overall outcomes in cancer treatment.

    Keywords: Immunotherapy, immune checkpoint inhibitors, PD-L1, TMB, MSI, emerging biomarkers

    Received: 20 Aug 2024; Accepted: 04 Nov 2024.

    Copyright: © 2024 Yin, Song, Deng, Blake, Luo and Meng. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Wanglong Deng, Jiangsu Simcere Diagnostics Co., Ltd., Nanjing Simcere Medical Laboratory Science Co., Ltd., The State Key Laboratory of Neurology and Oncology Drug Development, Nanjing, Liaoning Province, China
    Neil Blake, Institute of Infection, Veterinary and Ecological Sciences, Faculty of Health and Life Sciences, University of Liverpool, Liverpool, CH64 7TE, North West England, United Kingdom
    Xinghong Luo, Jiangsu Simcere Diagnostics Co., Ltd., Nanjing Simcere Medical Laboratory Science Co., Ltd., The State Key Laboratory of Neurology and Oncology Drug Development, Nanjing, Liaoning Province, China
    Jia Meng, Department of Biological Sciences, School of Science, AI University Research Centre, Xi’an Jiaotong-Liverpool University, Suzhou, Liaoning Province, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.