Objective DNA methylation is a key regulator of gene expression and plays a crucial role in cancer development. However, the mechanisms driving gene-specific methylation remain unclear. This study investigates the role of microRNAs (miRNAs) in regulating promoter methylation of specific genes, aiming to uncover miRNA-driven modulation of gene methylation in cancer. Methods We analyzed data from the Cancer Cell Line Encyclopedia (CCLE) database, comprising 813 cell lines. Spearman's rank correlation was performed between the expression levels of 734 miRNAs and the methylation levels of 20,587 genes, focusing on CpG islands in promoter regions. Linear regression analysis was used to validate the relationship between selected miRNAs and gene clusters. Bioinformatics screening identified statistically significant miRNA-gene pairs involved in promoter methylation. Results The analysis revealed 25 target genes whose promoter methylation was significantly associated with the expression of four miRNAs (hsa-miR-200a, hsa-miR-200b, hsa-miR-200c, and hsa-miR-141). These correlations were most pronounced in colorectal, gastric, lung, and ovarian cancers. Notably, cancer-related genes such as ST14, OVOL1, and EPCAM were identified as targets, supporting the hypothesis that miRNAs regulate promoter methylation in these genes. Conclusion Our findings suggest that specific miRNAs induce promoter methylation in cancer-related genes, thereby influencing gene expression. This study expands our understanding of the role of miRNAs in tumor development and highlights the potential of miRNA-based therapies in cancer treatment. As this is a computational study, further experimental validation is required to confirm the proposed regulatory mechanisms.
Investigating miRNA-driven DNA methylation: Statistical evidence of gene-specific modulation
Seyeon Jeon,H. Jun,Ji-Young Lee,C. O. Sung,Sung-Min Chun
Published 2025 in Science in progress
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- Publication year
2025
- Venue
Science in progress
- Publication date
2025-07-01
- Fields of study
Biology, Medicine
- Identifiers
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- Source metadata
Semantic Scholar, PubMed
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