Identification of functional TF-miRNA-hub gene regulatory network associated with ovarian endometriosis

Abstract

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.

Keywords: Endometriosis; HIF1A; bioinformatics analysis; microRNA; transcription factor.

FIGURE 1

The flow chart of the study.

FIGURE 2

Identification of DEGs Associated with OE. (A) the volcano plot of DEGs, red dots indicate upregulated genes and blue dots indicate downregulated genes in OE tissue. (B) the heatmap of DEGs, different colors in the heatmap represent the trend of gene expression in different tissues.

FIGURE 3

GO Functional Annotation Analysis. The GO analysis displayed top five enriched terms about BP, CC and MF. (A), (C), and (E). dot plot for BP, CC, MF enrichment analysis of DEGs. (B), (D), and (F). the relationship between DEGs and each term. MF, molecular function; BP, biological process; CC, cellular component.

FIGURE 4

KEGG Pathway Enrichment Analysis. (A) bar plot for KEGG pathway enrichment of DEGs. (B) the relationship between DEGs and each pathway.

FIGURE 5

PPI Network, including 133 nodes and 186 edges. The color of a node depends on its degree; the darker the color, the higher the connectivity. Nodes in darker color represent their importance to the network.

FIGURE 6

(A). Module in MCODE analysis, the clustering score was 6.0. (B). KEGG pathway analysis of the module.

FIGURE 7

Selection of Hub Genes and Analysis of TF-miRNA-Hub Gene Network. (A) hub gene correlated with OE. (B) predicted TFs of hub gene, the circles indicate target genes and the triangles indicate predicted TFs. (C) predicted miRNAs of hub gene, the circles indicate target genes and the squares indicate predicted miRNAs. (D). Construction of TF-miRNA-hub gene network, the squares indicate predicted miRNAs, the triangles indicate predicted TFs and the circles indicate target genes.