Construction of a TFs-miRNA-mRNA network related to idiopathic pulmonary fibrosis.

Abstract

The transcription factors (TFs)-microRNA (miRNA)-messenger RNA (mRNA) network plays an important role in a variety of diseases. However, the relationship between the TFs-miRNA-mRNA network and idiopathic pulmonary fibrosis (IPF) remains unclear. The GSE110147 and GSE53845 datasets from the Gene Expression Omnibus (GEO) database were used to process differentially expressed genes (DEGs) analysis, gene set enrichment analysis (GSEA), weighted gene co-expression network analysis (WGCNA), as well as Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. The GSE13316 dataset was used to perform differentially expressed miRNAs (DEMs) analysis and TFs prediction. Finally, a TFs-miRNA-mRNA network related to IPF was constructed, and its function was evaluated by Gene Ontology (GO) and KEGG analyses. Also, 19 TFs in the network were verified by quantitative real time polymerase chain reaction (qRT-PCR). Through our analysis, 53 DEMs and 2,630 DEGs were screened. The GSEA results suggested these genes were mainly related to protein digestion and absorption. The WGCNA results showed that these DEGs were divided into eight modules, and the GO and KEGG analyses results of blue module genes showed that these 86 blue module genes were mainly enriched in cilium assembly and cilium organization. Moreover, a TFs-miRNA-mRNA network comprising 25 TFs, 11 miRNAs, and 60 mRNAs was constructed. Ultimately, the functional enrichment analysis showed that the TFs-miRNA-mRNA network was mainly related to the cell cycle and the phosphatidylinositol 3 kinase-protein kinase B (PI3K-Akt) signaling pathway. Furthermore, experimental verification of the TFs showed that ARNTL, TRIM28, EZH2, BCOR, and ASXL1 were sufficiently up-regulated in the transforming growth factor (TGF)-β1 treatment groups, while BCL6, BHLHE40, FOXA1, and EGR1 were significantly down-regulated. The novel TFs-miRNA-mRNA network that we constructed could provide new insights into the underlying molecular mechanisms of IPF. ARNTL, TRIM28, EZH2, BCOR, ASXL1, BCL6, BHLHE40, FOXA1, and EGR1 may play important roles in IPF and become effective biomarkers for diagnosis and treatment.