Integrated bioinformatic analysis of dysregulated microRNA-mRNA co-expression network in ovarian endometriosis

Abstract

Introduction: Ovarian endometriosis is a frequently occurring gynecological disease with large socioeconomic impact. Accumulating evidence has suggested that aberrant miRNA-mRNA interactions are involved in the pathogenesis and progression of ovarian endometriosis. This study aims to identify key miRNAs in ovarian endometriosis by using integrated bioinformatic analysis of a dysregulated miRNA-mRNA co-expression network.

Material and methods: Expression profiling of miRNA and mRNA in three normal endometria and five pairs of ectopic/eutopic endometria from patients with ovarian endometriosis was determined by high-throughput sequencing techniques. The data were then integrated with the public sequencing datasets (GSE105764 and GSE105765) using a non-biased approach and a miRNA-mRNA co-expression regulatory network was constructed by in-depth bioinformatic analysis.

Results: The constructed miRNA-mRNA network included 87 functionally DEMs, 482 target mRNAs and 1850 paired miRNA-mRNA regulatory interactions. Specifically, five miRNAs (miR-141-3p, miR-363-3p, miR-577, miR-767-5p, miR-96-5p) were gradually decreased and two miRNAs (miR-493-5p, miR-592) were gradually increased from normal endometria to eutopic endometria, and then ectopic endometria tissues. Importantly, miR-141-3p, miR-363-3p and miR-96-5p belonged to the miR-200 family, miR-106a-363 cluster and miR-183/96/182 cluster, respectively. Their target mRNAs were mainly associated with cell adhesion, locomotion and binding, which are suggested to play vital regulatory roles in the pathogenesis of ovarian endometriosis.

Conclusions: Integrated bioinformatic analysis of the miRNA-mRNA co-expression network defines the crucial roles of the miR-200 family, miR-106a-363 cluster and miR-183/96/182 cluster in the pathogenesis of ovarian endometriosis. Further in-depth functional studies are needed to unveil the molecular mechanisms of these miRNAs, and may provide clues for the optimization of therapeutic strategies for ovarian endometriosis.

Keywords: expression profiling; integrative analysis; miRNAs; ovarian endometriosis; pathogenesis.

FIGURE 1

Flow chart of the construction of the miRNA‐mRNA regulatory network in ovarian endometriosis. DEG, differentially expressed gene; DEM, differentially expressed miRNA; EC, ectopic endometrium; EU; eutopic endometrium; OEM, ovarian endometriosis.

FIGURE 2

Differentially expressed genes (DEGs) in normal endometria of three volunteers and paired ectopic/eutopic endometria of five patients with OEM. Volcano plot of DEGs in (A) EC (n = 5) compared with normal endometria (n = 3); (B) in EU (n = 5) compared to normal endometria (n = 3); (C) in EC (n = 5) compared to EU (n = 5). Venn diagrams of (D) down‐regulated (D) and (E) up‐regulatedDEGs in normal, eutopic and ectopic endometria. (F) Heat map of gradually increased and decreased DEGs from normal to EU, and then in EC tissues. The relative expression is depicted by color: red indicates up‐regulation; green indicates down‐regulation. EC, ectopic endometrium; EU, eutopic endometrium; Normal, normal endometrium.

FIGURE 3

Differentially expressed miRNAs (DEMs) in normal endometria of three volunteers and paired ectopic/eutopic endometria of five patients with OEM. Volcano plot of DEMs in (A) EC (n = 5) compared with normal endometria (n = 3); (B) in EU (n = 5) compared with normal endometria (n = 3); (C) in EC (n = 5) compared with EU (n = 5). Venn diagrams of down‐regulated (D) and up‐regulated (E) DEMs in normal, eutopic and ectopic endometria. (F) Heat map of gradually increased and decreased DEMs from normal to EU, and then in EC tissues is presented. The relative expression is depicted by color: red indicates up‐regulation; green indicates down‐regulation. EC, ectopic endometrium; EU, eutopic endometrium; Normal, normal endometrium.

FIGURE 4

Differentially expressed genes (DEGs) and miRNAs (DEMs) in EC compared with EU tissues of OEM patients in integrated sequencing data. The miRNA and mRNA‐sequencing data of EC and EU tissues from five patients were normalized with sequencing datasets (GSE105764 for mRNA sequencing and GSE105765 for miRNA sequencing) of EC and EU tissues from eight patients. (A) Volcano plot of all DEGs in paired EC (n = 13) compared with EU tissues (n = 13). (B) Heat map of nine mRNAs that gradually increased/decreased in Figure 2F in paired EC (n = 13) compared with EU tissues (n = 13). (C) Volcano plot of all DEMs in paired EC (n = 13) compared with EU tissues (n = 13). (D) Heat map of 12 miRNAs that gradually increased/decreased in Figure 3F or the top five miRNAs in node degree analysis in paired EC (n = 13) compared with EU tissues (n = 13). The relative expression is depicted by color: Red indicates up‐regulation; green indicates down‐regulation. EC, ectopic endometrium; EU; eutopic endometrium.

FIGURE 5

The integrated ovarian endometriosis‐related key miRNA‐mRNA co‐expression regulatory network: (A) miRNA‐mRNA co‐expression regulatory network of 12 important miRNAs and their target mRNAs in integrated sequencing data; (B) miRNA‐mRNA co‐expression regulatory network of nine important mRNAs and their corresponding miRNAs in integrated sequencing data. Red indicates up‐regulation; green indicates down‐regulation; orange indicates no significant change. Circles indicate mRNAs and triangles indicate miRNAs.

FIGURE 6

Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of miRNA‐targeted mRNAs that involved in the key regulatory network. (A) Biological processes. (B) Cellular components. (C) Molecular functions. (D) KEGG pathways.