| DOI: 10.29090/psa.2025.01.24.1659 | Pharm Sci Asia 2025; 52(1), 11-29 |
Unveiling Potential Therapeutic Targets for Colon Cancer: A Comprehensive Bioinformatics Analysis of miRNA-Mediated RegulationFachrur Rizal Mahendra1,2, Gusnia Meilin Gholam1,2, Muhammad Musthofa1, Muhammad Marsha Azzami Hasibuan1, Akbar Rafiqi1, Hafizh Zahra1, Rahadian Pratama1, Laksmi Ambarsari1, I Made Artika1, Waras Nurcholis1,3,*
1 Department of Biochemistry, Faculty of Mathematics and Natural Sciences, Bogor 8 Agricultural University, Bogor 16680, Indonesia
2
Bioinformatics Research Center, Indonesian Institute of Bioinformatics (INBIO), Malang, 10 Indonesia
3
Tropical Biopharmaca Research Center, Bogor Agricultural University, Kampus IPB Taman 12 Kencana, Bogor, 16128, Jawa Barat, Indonesia
Cancer remains a significant health challenge in Asia, with lung, breast, and colorectal cancers ranking among the most prevalent and lethal. Colon cancer, when detected early, offers the prospect of successful treatment; however, late-stage diagnosis often limits curative interventions. Recent advances have proposed microRNAs (miRNAs) as promising elements in cancer therapy, acting as either tumor suppressor genes or inhibitors of oncogenic miRNAs. This study employed topology and centrality analyses to identify pivotal genes in colon cancer and explore dysregulated miRNAs with high binding probability to their target proteins. This investigation extends to the assessment of miRNA-mRNA interactions and duplex complexes with argonaute (AGO) proteins, shedding light on potential therapeutic avenues. Notably, our bioinformatics predictions potential upregulated genes in colon cancer of Asia population such CAV1, KLF4, and TAGLN and the potential of miRNA suppressing these genes are hsa-miR-429, hsa-miR-200c, and hsa-miR-22 respectively, as robust candidates for suppressing oncogene expression in colon cancer. Detailed scrutiny of the binding affinity, conformation, and conformational stability through molecular dynamics enhances the precision of these findings. This study provides valuable insights into the selection of optimal miRNA candidates for targeted utilization in colon cancer therapy.
Keyword:
Colon Cancer; miRNA; Network Analysis; In silico
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