👤 Anveshika Manoj

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. Show less

Prostate cancer is an adenocarcinoma that involves epithelial-mesenchymal transition (EMT) for metastasis. To uncover novel insights into the development of prostate tumors and to identify important genes and putative microRNAs (miRs) for patient care, this study performed an in-depth bioinformatics analysis using dbDEMC3.0 (Zhejiang University, Hangzhou, China), MIENTURNET (University of Rome Tor Vergata, Rome, Italy), and DIANA-miTED (University of Thessaly, Thessaly, Greece) to explore miRs regulating tumorigenesis, proliferation, and potential therapeutic targets. A total of 373 differently expressed miRs were examined in this study, of which 87 had significant upregulation and 85 had significant downregulation. Our results from the MIENTURNET software showed that miR-141-3p, miR-200a-3p, miR-200b-3p, miR-200c-3p, miR-203a-3p, miR-429, miR-34a-5p, and miR-509-3-5p interact with the transcription factors CDH1, CDH2, SNAI1, ZEB1, and ZEB2, which play a significant role in the core EMT regulatory network. The Encyclopedia of RNA Interactomes (ENCORI) miR-target interaction co-expression analysis observed that miR-34a-5p had a strong interaction with CDH1 as compared to other genes. The results of DIANA-plasmiR analysis showed that miR-34a-5p is a useful prognostic and diagnostic biomarker. Our results suggest that this study advances our knowledge of the molecular mechanism underlying prostate adenocarcinoma and that the interaction between the EMT gene and differentially expressed miR (DEmiR) in prostate adenocarcinoma may represent a target for prostate cancer diagnosis and treatment. Show less

As human progenitor cells differentiate into neurons, the activities of many genes change; these changes are maintained within a narrow range, referred to as genome homeostasis. This process, which alters the synchronization of the entire expressed genome, is distorted in neurodevelopmental diseases such as schizophrenia. The coordinated gene activity networks formed by altering sets of genes comprise recurring coordination modules, governed by the entropy-controlling action of nuclear FGFR1, known to be associated with DNA topology. These modules can be modeled as energy-transferring circuits, revealing that genome homeostasis is maintained by reducing oscillations (noise) in gene activity while allowing gene activity changes to be transmitted across networks; this occurs more readily in neuronal committed cells than in neural progenitors. These findings advance a model of an "entangled" global genome acting as a flexible, coordinated homeostatic system that responds to developmental signals, is governed by nuclear FGFR1, and is reprogrammed in disease. Show less