2022 Volume 1 Issue 1
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Genetic and Epigenetic Indicators Predicting Response to Immune Checkpoint Inhibitors


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  1. School of Exercise and Health, Shanghai University of Sport, Shanghai 200438, China.
  2. Key Laboratory of Hebei Province for Molecular Biophysics, Institute of Biophysics, School of Health Science & Biomedical Engineering, Hebei University of Technology, Tianjin 300130, China.
Abstract

Immune checkpoint inhibitor therapy has emerged as a highly promising approach for cancer treatment by targeting inhibitory pathways that suppress T cell cytotoxic activity. Recent landmark clinical trials have shown that immune checkpoint blockade (ICB) can induce durable anti-tumor responses with manageable toxicity, leading to the approval of eight checkpoint inhibitors across 15 different cancer types. Nevertheless, a significant proportion of patients—up to approximately 85%—exhibit either primary or acquired resistance, which constrains the broad effectiveness of ICB. Existing biomarkers for predicting response, such as tumor mutational burden, neoantigen load, immune cell profiles, and programmed death-ligand 1 (PD-L1) expression, provide only limited predictive power. Consequently, discovering novel biomarkers that more accurately identify patients likely to benefit from ICB represents a critical focus in immunotherapy research. Aberrant DNA methylation (5mC) and hydroxymethylation (5hmC) have been observed in various cancers, and dynamic epigenomic changes occur during T cell differentiation and activation. Although their precise contribution to cancer-induced immune suppression remains unclear, emerging evidence indicates that 5mC and 5hmC may function as prognostic and predictive biomarkers for ICB-responsive tumors. This review discusses the influence of epigenetic mechanisms on tumor immunoediting and immune evasion, provides an updated overview of current ICB response biomarkers, and highlights promising epigenomic candidates with potential predictive value.


How to cite this article
Vancouver
Yang J, Bin W, Sun Q, Cai D. Genetic and Epigenetic Indicators Predicting Response to Immune Checkpoint Inhibitors. Bull Pioneer Res Med Clin Sci. 2022;1(1):41-68. https://doi.org/10.51847/Jv5FAvSXwc
APA
Yang, J., Bin, W., Sun, Q., & Cai, D. (2022). Genetic and Epigenetic Indicators Predicting Response to Immune Checkpoint Inhibitors. Bulletin of Pioneering Researches of Medical and Clinical Science, 1(1), 41-68. https://doi.org/10.51847/Jv5FAvSXwc
Issue 1 Volume 5 - 2026