Computational Analysis of Differentially Expressed Circulating MicroRNA and Identification of Key Genes in Prostate Cancer.

Abstract

Bioinformatics is considered a powerful tool to investigate and deeply analyze large datasets. A significant quantity of data is generated by prostate cancer and dysregulation of microRNA (miRNA) in tissues and bodily fluids (serum, plasma, urine). Screening dysregulated miRNA is currently more accessible, more reliable, and more precise with the help of insilico approaches. Hence the objective of the study is to identify miRNAs and explore their mRNA interaction in prostate cancer development. Here in the present study, we analyzed the GEO dataset GSE112264 and performed GEO-2R analysis to segregate significantly upregulated and downregulated miRNAs. The targetome of each miRNA containing several target genes was analyzed and put in an interactive network form. Functional enrichment analysis using DAVID 6.8 and GSEA was carried out to get KEGG, Reactome, and GO-BP analysis. Our analysis revealed that out of 190 overlapped significant miRNAs, only 9 miRNAs (hsa-miRNA-185-5p, hsa-miRNA-211-5p, hsa-miRNA-330-3p, hsa-miRNA-342-3p, hsa-miRNA-3622b-5p, hsa-miRNA-486-5p, hsa-miRNA-520a-3p, hsa-miRNA-550a-3p, hsa-miRNA-574-3p) were found to target 20 unique target genes (AKT1, EP300, E2F1, KRAS, AR, CREB5, CCND1, CDKNA1, EGFR, ERBB2, FGFR1, FOXO1, IKBKG, IGF1R, MAPK1, PTEN, PIK3R1, and TP53) that were involved in Prostate cancer survival and proliferation. Out of 9 miRNAs, two miRNAs (miRNA-520a-3p and miRNA-550a-3p) are novel miRNAs that have yet to be explored in Prostate cancer pathogenesis. To conclude and for future research, 8 miRNAs are yet to be explored for non-invasive potential as diagnostic and prognostic biomarkers in Prostate cancer progression and development. The target genes of each miRNA could provide novel insights in developing therapeutics for better management of disease.