Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive lung disease, but its pathogenesis is still unclear. Bioinformatics methods were used to explore the differentially expressed genes (DEGs) and to elucidate the pathogenesis of IPF at the genetic level. The microarray datasets GSE110147 and GSE53845 were downloaded from the Gene Expression Omnibus (GEO) database and analyzed using GEO2R to obtain the DEGs. The DEGs were further analyzed for Gene Ontology (GO) and Kyoto Encyclopedia of Genomes (KEGG) pathway enrichment using the DAVID database. Then, using the STRING database and Cytoscape, a protein-protein interaction (PPI) network was created and the hub genes were selected. In addition, lung tissue from a mouse model was validated. Lastly, the network between the target microRNAs (miRNAs) and the hub genes was constructed with NetworkAnalyst. A summary of 240 genes were identified as DEGs, and functional analysis highlighted their role in cell adhesion molecules and ECM-receptor interactions in IPF. In addition, eight hub genes were selected. Four of these hub genes (VCAM1, CDH2, SPP1, and POSTN) were screened for animal validation. The IHC and RT-qPCR of lung tissue from a mouse model confirmed the results above. Then, miR-181b-5p, miR-4262, and miR-155-5p were predicted as possible key miRNAs. Eight hub genes may play a key role in the development of IPF. Four of the hub genes were validated in animal experiments. MiR-181b-5p, miR-4262, and miR-155-5p may be involved in the pathophysiological processes of IPF by interacting with hub genes.
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