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INTERNATIONAL CONGRESS OF

CancerGenetics

• Epigenetic Regulation of MicroRNAs in Cancer: A Mechanistic Review with Clinical and Artificial Intelligence Perspectives

• Shirin Dehghan,^1,* Abolfazl Mohammadi,² Sara parvizifara,³ Arezoo Mohammadlo,⁴ Niayesh Eivani,⁵
  1. Genetics graduate, Kharazmi University
  2. Azad Islamic University, Karaj
  3. Department of Biology- Kharazmi University
  4. Microbiology department
  5. Department of cell and molecular biology, Isfahan University
  
  
  
• Introduction: The emerging paradigm of epigenetic regulation has positioned microRNAs (miRNAs) as critical molecular intermediaries in oncogenesis. Evidence suggests that approximately 60% of human miRNA genes reside within cancer-associated genomic regions or fragile sites, rendering them particularly susceptible to epigenetic perturbations. Contemporary research identifies three principal modes of interaction between miRNAs and epigenetic mechanisms in cancer: direct epigenetic modification of miRNA loci, miRNA-mediated regulation of epigenetic modulators, and bidirectional feedback circuits. This review integrates findings from seven seminal studies to construct a cohesive model of these interactions and explores their translational relevance through the lens of artificial intelligence-enabled precision oncology.
• Methods: Mechanistic Basis of miRNA Epigenetics DNA Methylation Genome-wide methylation analyses have revealed cancer-specific patterns that profoundly influence miRNA expression. In colorectal cancer, promoter hypermethylation of miR-34b/c is observed in the vast majority of cases, correlating with advanced tumor stage and reduced five-year survival. Similarly, in glioblastoma, miR-155 promoter methylation is prevalent in IDH-wildtype tumors and is associated with chemotherapy resistance and elevated recurrence risk. Progressive hypermethylation of miR-29b in prostate cancer exemplifies a continuum from premalignant lesions to metastatic disease, underscoring the dynamic nature of epigenetic dysregulation during tumor evolution. Histone Modification Landscapes Dynamic histone marks further govern miRNA expression in a context-dependent manner. Histone deacetylase inhibition, for example, enhances H3K27ac occupancy at tumor-suppressive miRNA loci, restoring their function. Conversely, EZH2-mediated H3K27 trimethylation silences miR-200c in aggressive breast cancers, driving epithelial-to-mesenchymal transition. Loss of DNMT3b reduces repressive H3K9me2 marks on miR-34a, increasing radiosensitivity, demonstrating the intricate interplay between DNA and histone modifications in regulating miRNA activity. Bidirectional Regulatory Circuits Integrated omics analyses highlight self-reinforcing epigenetic-miRNA networks. The miR-29b/DNMT3b axis exemplifies reciprocal regulation, wherein miR-29b suppresses DNMT3b while DNMT3b concurrently methylates the miR-29b promoter. Similar feed-forward circuits have been observed in CpG island methylator phenotype-high colorectal cancers, emphasizing the capacity of miRNA-epigenetic loops to amplify oncogenic signaling.
• Results: Clinical Translation and Therapeutic Potential Diagnostic Applications Epigenetic profiling of miRNA loci has yielded promising biomarkers. Panels assessing methylation of miR-34b/c and miR-9-1 demonstrate high sensitivity and specificity for the detection of early-stage colorectal cancer, while circulating methylated miR-155 levels provide a minimally invasive tool for monitoring glioma progression. Therapeutic Development Targeted epigenetic interventions can restore tumor-suppressive miRNA function. For instance, treatment with DNA demethylating agents reactivates miR-29b and synergizes with conventional chemotherapies. HDAC inhibitors can potentiate miRNA-mediated suppression of anti-apoptotic targets, reducing therapeutic resistance in preclinical models. AI-Enabled Advancements Artificial intelligence has accelerated the translation of miRNA-epigenetic insights into clinical practice. Machine learning frameworks, such as DeepMethyl, outperform traditional methods in predicting functional miRNA methylation from sequencing data. Graph neural networks integrating miRNA, mRNA, and epigenetic interactions offer predictive insights into treatment response, while in silico optimization algorithms enable rational design of combination therapies with reduced toxicity. Challenges and Future Directions Despite promising progress, several barriers remain. Current methylation arrays survey less than half of miRNA promoters, highlighting the need for single-cell and high-resolution epigenomic technologies. Tissue-specific variations in regulatory circuits, such as the miR-29b/DNMT pathway, complicate translational generalization. Clinically, only a minority of miRNA-epigenetic biomarkers have advanced to late-phase trials, reflecting biological heterogeneity and methodological variability. Future studies should prioritize the development of miRNA-specific epigenetic editors, global standardization of methylation quantification protocols, and federated learning frameworks to enable robust multi-center analyses.
• Conclusion: This integrative review establishes miRNA epigenetics as a cornerstone of cancer biology, with significant implications for early detection, rational epigenetic therapy, and AI-driven personalized treatment. By shifting the paradigm from static biomarker categorization toward dynamic network targeting, combined modulation of miRNAs and epigenetic pathways holds the potential to overcome contemporary therapeutic resistance, heralding a new era in precision oncology.
• Keywords: microRNAs-miRNA epigenetics-DNA methylation-histone modification