Unveiling Key Biomarkers and Therapeutic Drugs in Polycystic Ovary Syndrome (PCOS) Through Pathway Enrichment Analysis and Hub Gene-miRNA Networks

Abstract

Background: Polycystic ovary syndrome (PCOS) affects women of reproductive age globally with an incidence rate of 5% - 26%. Growing evidence reports important roles for microRNAs (miRNAs) in the pathophysiology of granulosa cells (GCs) in PCOS.

Objectives: The objectives of this study were to identify the top differentially expressed miRNAs (DE-miRNAs) and their corresponding targets in hub gene-miRNA networks, as well as identify novel DE-miRNAs by analyzing three distinct microarray datasets. Additionally, functional enrichment analysis was performed using bioinformatics approaches. Finally, interactions between the 5 top-ranked hub genes and drugs were investigated.

Methods: Using bioinformatics approaches, three GC profiles from the gene expression omnibus (GEO), namely gene expression omnibus series (GSE)-34526, GSE114419, and GSE137684, were analyzed. Targets of the top DE-miRNAs were predicted using the multiMiR R package, and only miRNAs with validated results were retrieved. Genes that were common between the "DE-miRNA prediction results" and the "existing tissue DE-mRNAs" were designated as differentially expressed genes (DEGs). Gene ontology (GO) and pathway enrichment analyses were implemented for DEGs. In order to identify hub genes and hub DE-miRNAs, the protein-protein interaction (PPI) network and miRNA-mRNA interaction network were constructed using Cytoscape software. The drug-gene interaction database (DGIdb) database was utilized to identify interactions between the top-ranked hub genes and drugs.

Results: Out of the top 20 DE-miRNAs that were retrieved from the GSE114419 and GSE34526 microarray datasets, only 13 of them had "validated results" through the multiMiR prediction method. Among the 13 DE-miRNAs investigated, only 5, namely hsa-miR-8085, hsa-miR-548w, hsa-miR-612, hsa-miR-1470, and hsa-miR-644a, demonstrated interactions with the 10 hub genes in the hub gene-miRNA networks in our study. Except for hsa-miR-612, the other 4 DE-miRNAs, including hsa-miR-8085, hsa-miR-548w, hsa-miR-1470, and hsa-miR-644a, are novel and had not been reported in PCOS pathogenesis before. Also, GO and pathway enrichment analyses identified "pathogenic E. coli infection" in the Kyoto encyclopedia of genes and genomes (KEGG) and "regulation of Rac1 activity" in FunRich as the top pathways. The drug-hub gene interaction network identified ACTB, JUN, PTEN, KRAS, and MAPK1 as potential targets to treat PCOS with therapeutic drugs.

Conclusions: The findings from this study might assist researchers in uncovering new biomarkers and potential therapeutic drug targets in PCOS treatment.

Keywords: Bioinformatics; Biomarkers; Drug-Target Network; MicroRNAs; Polycystic Ovary Syndrome.

Figure 1.. Venn diagram and gene ontology (GO) enrichment analysis of differentially expressed genes (DEGs): A, Venn diagram of 352 DEGs from three microarray datasets: DEGs are defined as genes that are common between the “validated multiMiR prediction results of the top 13 differentially expressed (DE)-miRNAs” and “existing tissue DE-miRNAs”; B, GO of biological processes (BP) enrichment analysis; C, GO of molecular function (MF) enrichment analysis; D, GO of cellular component (CC) enrichment analysis; E, Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis; F, FunRich pathway enrichment analysis.

Figure 2.. Hub gene-miRNA networks and drug-hub gene interactions; A, hub gene-miRNA networks: Blue rectangles are hub genes, including ACTB, JUN, PTEN, KRAS, MAPK1, SMAD3, FYN, ARRB1, CFL1, and SIN3A and oval red nodes are DE-miRNAs; B, drug-hub gene interactions: Oval pink nodes are the initial top 5 ranked hub genes, including ACTB, JUN, PTEN, KRAS, and MAPK1, which serve as potential gene targets for drugs. Green octagon nodes indicate FDA-approved drugs. Yellow octagon nodes indicate FDA-approved drugs for polycystic ovary syndrome (PCOS).