Biological Network Analysis of Genes and Non-coding RNAs in Polycystic Ovary Syndrome
Abstract
BACKGROUND/AIMS: Polycystic ovary syndrome (PCOS) is a neuroendocrine and metabolic disorder.This study aimed to explore interactions among differentially expressed genes (DEGs) and Food and Drug Administration (FDA)-approved drugs relevant to PCOS using bioinformatics approaches.The relationships between top-ranked hub genes, DE-microRNAs (miRNAs), and DE-long non-coding RNAs (lncRNAs) within the competing endogenous RNA (ceRNA) network framework were also investigated. MATERIALS AND METHODS:Expression profiles for miRNA (GSE138572), lncRNA (GSE159466), and mRNA (GSE84958, GSE156067) were obtained from the GEO database.Data analysis was performed using R Project and relevant annotation packages.Drug-gene interactions (DGI) were explored using DGIdb, and Cytoscape software was employed to construct DEG-drug interaction networks.RESULTS: Analysis of GSE84958 and GSE156067 datasets identified 71 common DEGs.Moreover, 11 DE-miRNAs and 203 DE-lncRNAs were DE in PCOS samples compared to controls.DGIdb analysis showed that FDA-approved drugs could potentially target the identified DEGs.Nine genes-PDE5A, ETFB, COL11A1, SLC25A20, DAPK1, ICAM1, FABP5, GBE1, and SLC2A3-were identified as hub genes within the DGI network and were considered promising therapeutic targets.Dysregulated miRNAs were significantly enriched in the ceRNA network.This suggests their potential role in PCOS therapeutic strategies.gene ontology and kyoto encyclopedia of genes and genomes enrichment analyses…
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