Prostate cancer presents a major health issue, with its progression influenced by intricate molecular factors. Notably, the interplay between miRNAs and changes in transcriptomic patterns is not fully understood. Our study seeks to bridge this knowledge gap, employing computational techniques to explore how miRNAs and transcriptomic alterations jointly regulate the development of prostate cancer. The study involved retrieving miRNA expression data from the GEO database specific to prostate cancer. Identification of DEMs was conducted using the ‘limma’ package in R. Integration of these DEMs with mRNA interactions was done using the MiRTarBase database. Finally, a network depicting miRNA-mRNA interactions was constructed using Cytoscape software to analyze the regulatory network of prostate cancer. The study pinpointed seven pivotal differentially expressed microRNAs (DEmiRNAs) in prostate cancer: hsa-miR-185-5p, hsa-miR-153-3p, hsa-miR-198, hsa-miR-182-5p, hsa-miR-223-3p, hsa-miR-372-3p, and hsa-miR-188-5p. These miRNAs influence key genes, including FOXO3, NFAT3, PTEN, RHOA, VEGFA, SMAD7, and CDK2, playing significant roles in both tumor suppression and oncogenesis. The analysis revealed a complex network of miRNA-mRNA interactions, comprising 1849 nodes and 3604 edges. Functional Enrichment Analysis through ClueGO highlighted 74 GO terms associated with these mRNA targets. This analysis uncovered their substantial impact on critical biological processes and molecular functions, such as cyclin-dependent protein kinase activity, mitotic DNA damage checkpoint signalling, stress-activated MAPK cascade, regulation of extrinsic apoptotic signalling pathway, and positive regulation of cell adhesion. Our analysis of miRNAs and DEGs genes revealed an intriguing mix of established and potentially novel regulators in prostate cancer development. These findings both reinforce our current understanding of prostate cancer’s molecular landscape and point to unexplored pathways that could lead to novel therapeutic strategies. By mapping these regulatory relationships, our work contributes to the growing knowledge base needed for developing more targeted and effective treatments.
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