Identification of microRNAs with therapeutic potentials on prostate cancer drug targets: In-silico prediction and In-vitro validation

Abstract Developing novel strategies for cancer treatment is essential in modern medicine. MiRNAs are master regulators of gene expression and act as control nodes or hubs in regulatory networks. Thus, we hypothesized that miRNAs could be an appropriate and novel therapeutic tool simultaneously targeting a candidate gene set. We defined a set of druggable genes with approved clinical outcomes in prostate cancer by a literature review (i.e., AR, PIK3CA, PIK3CB, MET, FGFR4, EGFR). We conducted gene ontology (GO) enrichment and KEGG pathway analyses using DAVID and BINGO. The gene-gene interaction network was evaluated by GeneMANIA. The protein-protein interaction analysis was performed by STRING. Visualization and integration of biological networks were performed by Cytoscape. These analyses showed selected genes' importance in prostate cancer and its related pathways. Then we applied three bioinformatics algorithms to predict the candidate miRNAs, including mirDip, TarBase v8, and miRTarbase. As a result, miR-124-3p, miR-16-5p, and miR-27a-3p were retrieved through in-silico analyses. The quantitative characteristics of extracted miRNAs with mRNAs were determined using MIRANDA and BiBiServ-Services. The binding features included the miRNA binding site (BS) of mRNA, the locations of miRNA BS (3 UTR,5 UTR, CDS), and the interaction free energy (ΔG, kcal/mole). Next, we performed some experimental techniques to examine the validity of the results. After transfecting the PC-3 and LNCaP cell lines with miRNA overexpressing vectors, the mRNA level of the target gene was examined by RT-PCR. The effects of candidate miRNAs on cell viability were evaluated using MTT assays. The cell cycle distribution was studied by flow cytometry. Our findings suggest that this novel approach may have higher clinical benefits in cancer treatment by concurrent targeting therapeutically relevant gene sets by miRNAs.