Whole-genome methylation profiling of extracellular vesicle DNA in gastric cancer identifies intercellular communication features

Bingqian Lin, Zhenna Jiao, Shouquan Dong, Weikai Yan, Jinting Jiang, Yanfang Du, Xiaocheng Weng (), Hongling Wang (), Zhiyuan Hu (), Yibin Liu () and Xiang Zhou ()
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Bingqian Lin: Wuhan University
Zhenna Jiao: Wuhan University
Shouquan Dong: Department of Gastroenterology of Zhongnan Hospital of Wuhan University
Weikai Yan: Wuhan University
Jinting Jiang: Wuhan University
Yanfang Du: Wuhan University
Xiaocheng Weng: Wuhan University
Hongling Wang: Department of Gastroenterology of Zhongnan Hospital of Wuhan University
Zhiyuan Hu: Wuhan University
Yibin Liu: Wuhan University
Xiang Zhou: Wuhan University

Nature Communications, 2025, vol. 16, issue 1, 1-12

Abstract: Abstract Extracellular vesicles (EVs) are promising biomarkers for cancer diagnosis and prognosis due to their ability to carry specific biomolecular cargo, including DNA. However, the clinical utility of DNA methylation-based liquid biopsies using EV-DNA remains underexplored. The low quantity and relatively long length of EV-DNA complicate whole-genome methylation profiling. To address this, we develop Tn5-assisted Enzymatic Methyl-sequencing with Post-conversion Tailing (TEMPT), a bisulfite-free whole-genome profiling method for EV-DNA. TEMPT employs single-adapter Tn5 tagmentation, enzymatic conversion of unmodified cytosines, and post-conversion tailing to generate high-depth whole-genome EV-DNA methylomes. We apply TEMPT to EV-DNA from 58 gastric cancer and polyp samples, generating methylomes from sub-nanogram inputs and identifying differentially methylated regions (DMRs) that distinguish cancer from controls. We identify potential cancer biomarkers through DMR-associated genes, highlighting the roles of EVs in cellular communication. Our findings suggest that immune cells may serve as an alternative source of EV-DNA. This approach holds significant promise for advancing EV-DNA research and its applications in early disease diagnosis.

Date: 2025
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DOI: 10.1038/s41467-025-63435-w

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