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

Area of Science:

• Bioinformatics
• Molecular Biology
• Oncology

Background:

• Prostate cancer generates large datasets, including dysregulated microRNAs (miRNAs) in tissues and bodily fluids.
• In silico approaches enhance the accuracy and accessibility of screening dysregulated miRNAs.

Purpose of the Study:

• To identify microRNAs and explore their messenger RNA (mRNA) interactions in prostate cancer development.
• To investigate the potential of identified miRNAs as diagnostic and prognostic biomarkers.

Main Methods:

• Analysis of the GEO dataset GSE112264 using GEO-2R to identify significantly up- and down-regulated miRNAs.
• Targetome analysis to map miRNA-target gene interactions and construct interactive networks.
• Functional enrichment analysis (DAVID 6.8, GSEA) for KEGG, Reactome, and Gene Ontology-Biological Process (GO-BP) pathways.

Main Results:

• Identified 190 significant miRNAs, with 9 miRNAs targeting 20 unique genes crucial for prostate cancer survival and proliferation.
• Discovered two novel miRNAs (miRNA-520a-3p and miRNA-550a-3p) implicated in prostate cancer pathogenesis.
• Highlighted 8 miRNAs with potential for non-invasive diagnostic and prognostic biomarker applications.

Conclusions:

• The identified miRNAs and their target genes offer insights into prostate cancer progression.
• Eight miRNAs warrant further investigation as potential non-invasive biomarkers for prostate cancer.
• Target gene analysis may guide the development of novel therapeutics for prostate cancer management.