Identification of functional TF-miRNA-hub gene regulatory network associated with ovarian endometriosis - Li, Lu; Sun, Bo; Sun, Yingpu (Frontiers in Genetics, 2022)
Endometriosis (EMs), one of the most common gynecological diseases, seriously affects the health and wellness of women; however, the underlying pathogenesis remains unclear. This study focused on dysregulated genes and their predicted transcription factors (TFs) and miRNAs, which may provide ideas for further mechanistic research. The microarray expression dataset GSE58178, which included six ovarian endometriosis (OE) samples and six control samples, was downloaded from the Gene Expression Omnibus (GEO) to identify differentially expressed genes (DEGs). Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to study the cellular and organism-level functions of DEGs. The protein-protein interaction (PPI) network was built and visualized using Cytoscape, and modules and hub genes were explored using various algorithms. Furthermore, we predicted miRNAs and TFs of hub genes using online databases, and constructed the TF-miRNA-hub gene network. There were 124 upregulated genes and 66 downregulated genes in EMs tissues. GO enrichment analysis showed that DEGs were concentrated in reproductive structure development and collagen-containing extracellular matrix, while KEGG pathway analysis showed that glycolysis/gluconeogenesis and central carbon metabolism in cancer require further exploration. Subsequently, HIF1A, LDHA, PGK1, TFRC, and CD9 were identified as hub genes, 22 miRNAs and 34 TFs were predicted to be upstream regulators of hub genes, and these molecules were pooled together. In addition, we found three key feedback loops in the network, MYC-miR-34a-5p-LDHA, YY1-miR-155-5p-HIF1A, and RELA-miR-93-5p-HIF1A, which may be closely related to OE development. Taken together, our study structured a TF-miRNA-hub gene network to decipher the molecular mechanism of OE, which may provide novel insights for clinical diagnosis and treatment.