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DNA methylation heterogeneity in complex tumor microenvironment: Quantitative methods, influencing factors, and clinical implications

Review Articles

DNA methylation heterogeneity in complex tumor microenvironment: Quantitative methods, influencing factors, and clinical implications

Xu Yongle
Ma Shuangyue
Xu Manyi
Zhu Hongbo
Wang Yuncong
Dong Wenbo
Gan Jing
Zhao Yusen
Li Xinrong
Wang Shuangshuang
Hu Haoyu
He Jiaheng
Ning Shangwei
Zhi Hui
Genes & Diseases第13卷, 第3期纸质出版 2026-05-01在线发表 2025-08-25
300

5-Methylcytosine (5-mC) is the most prevalent DNA methylation modification in the human genome, and its abnormal patterns are strongly associated with tumor progression. Intratumoral and intertumoral DNA methylation heterogeneity (DNAmeH) primarily arises from cancer epigenome heterogeneity and the diverse cell compositions within the tumor microenvironment (TME). Furthermore, recent advancements in high-throughput sequencing and microarray technologies have facilitated the development of quantitative methods for measuring DNAmeH, enabling a more thorough exploration of the factors influencing it. Moreover, investigating various DNA methylation patterns at the single-cell level within the intricate TME sheds light on DNAmeH being driven by cellular heterogeneity. In addition, accumulating studies on the selection of methylation biomarkers in tissue or circulating DNA elucidate the cell specificity of DNA methylation, which is valuable for early cancer detection and personalized therapy. In this review, we elucidate the characteristics of intratumoral and intertumoral DNAmeH, considering DNAmeH differences across cancer types, among individual cells, and at allele-specific hemimethylation sites. Several metrics are summarized to quantitatively assess DNAmeH. We evaluate the factors that influence DNAmeH via these metrics, including the cell cycle phase, tumor mutational burden (TMB), cellular stemness, copy number variation (CNV), tumor subtype, tumor characteristics, tumor stage, state of tumor cells, hypoxia, and tumor purity. Finally, we highlight the deconvolution of TME cellular components and the application of predictive methylation biomarkers in cancer clinical research.

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Circulating DNADNAmeHHemimethylationMethylation biomarkersTumor microenvironment