Identification of transcriptomic markers for developing idiopathic pulmonary fibrosis: an integrative analysis of gene expression profiles.

Idiopathic pulmonary fibrosis (IPF) remains a lethal disease with unknown etiology and unmet medical need. The aim of this study was to perform an integrative analysis of multiple public microarray datasets to investigate gene expression patterns between IPF patients and healthy controls. Moreover, functional interpretation of differentially expressed genes (DEGs) was performed to assess the molecular mechanisms underlying IPF progression. DEGs between IPF and normal lung tissues were picked out by GEO2R tool and Venn diagram software. Database for Annotation, Visualization and Integrated Discovery (DAVID) was applied to analyze gene ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway. Protein-protein interaction (PPI) of these DEGs was visualized by Cytoscape with Search Tool for the Retrieval of Interacting Genes (STRING). 5520 DEGs were identified in IPF based on six profile datasets, including 3714 up-regulated genes and 1806 down-regulated genes. Using Venn software, a total of 367 commonly altered DEGs were revealed, including 259 up-regulated genes mostly enriched in collagen catabolic process, heparin binding, and the extracellular region. For pathway analysis, up-regulated DEGs were mainly enriched in ECM-receptor interaction, protein digestion and absorption, and focal adhesion. Finally, 24 DEGs with degrees ≥10 were screened as hub genes from the PPI network, which were enriched in protein digestion and absorption, ECM-receptor interaction, focal adhesion, PI3K-Akt signaling pathway, amoebiasis, and platelet activation. The present integrative study identified DEGs and hub genes that may be diagnostic biomarkers or therapeutic targets, and provide novel insights into the pathogenesis of IPF.