Bioinformatics analysis of competing endogenous RNA network in decidual natural killer cell from unexplained recurrent spontaneous abortion

Abstract

Background: Decidual natural killer (dNK) cell plays a pivotal role in maintaining pregnancy, especially in the first trimester. Noncoding-RNAs (ncRNAs) are critical regulators of transcription and protein expression. Dysregulation of ncRNAs may be involved in the pathogenesis of unexplained recurrent spontaneous abortion (URSA). However, the role of competing endogenous RNA (ceRNA) based on mRNA–miRNA–lncRNA network in regulating the incidence and progression of URSA remains elusive. The aim of the study is to identify the regulatory network of mRNA–miRNA–LncRNA ceRNA based on bioinformatics analysis in dNK from patients with URSA. Methods: Eligible studies were retrieved from PubMed, Embase, and the Gene Expression Omnibus (GEO) databases to identify differentially expressed genes (DEGs), miRNAs and LncRNAs in dNK cells of patients with URSA. Protein–protein interaction (PPI) network was constructed by STRING database and Cytoscape software. Potential regulatory miRNAs and lncRNAs of mRNAs were predicted by miRTarBase and RNA22 and subject to bioinformatics analysis. Results: A total of 634 DEGs were screened, including 290 upregulated and 344 downregulated DEGs. Among 207 differentially expressed lncRNAs, 110 lncRNAs were upregulated and 97 were downregulated. According to node degree, 30 hub genes were identified for subsequent research. After drawing the Venn diagram and matching to Cytoscape, an mRNA–miRNA–lncRNA network linked to the pathogenesis of URSA in dNK cells was constructed. Conclusions: A novel regulatory network of mRNA–miRNA–lncRNA ceRNA is established in dNK cells from patients with URSA. All RNAs might be used as the biomarkers of the pathogenesis of URSA.