BMC Pulmonary Medicine (Oct 2023)

Integrated bioinformatics analysis for the identification of idiopathic pulmonary fibrosis–related genes and potential therapeutic drugs

  • Zhenzhen Zhang,
  • Qingzhou Guan,
  • Yange Tian,
  • Xuejie Shao,
  • Peng Zhao,
  • Lidong Huang,
  • Jiansheng Li

DOI
https://doi.org/10.1186/s12890-023-02678-z
Journal volume & issue
Vol. 23, no. 1
pp. 1 – 13

Abstract

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Abstract Objective The pathogenesis of idiopathic pulmonary fibrosis (IPF) remains unclear. We sought to identify IPF-related genes that may participate in the pathogenesis and predict potential targeted traditional Chinese medicines (TCMs). Methods Using IPF gene-expression data, Wilcoxon rank-sum tests were performed to identify differentially expressed genes (DEGs). Protein–protein interaction (PPI) networks, hub genes, and competitive endogenous RNA (ceRNA) networks were constructed or identified by Cytoscape. Quantitative polymerase chain reaction (qPCR) experiments in TGF-β1-induced human fetal lung (HFL) fibroblast cells and a pulmonary fibrosis mouse model verified gene reliability. The SymMap database predicted potential TCMs targeting IPF. The reliability of TCMs was verified in TGF-β1-induced MRC-5 cells. Materials Multiple gene-expression profile data of normal lung and IPF tissues were downloaded from the Gene Expression Omnibus database. HFL fibroblast cells and MRC-5 cells were purchased from Wuhan Procell Life Science and Technology Co., Ltd. (Wuhan, China). C57BL/12 mice were purchased from Beijing Vital River Laboratory Animal Technology Co., Ltd. (Beijing, China). Results In datasets GSE134692 and GSE15197, DEGs were identified using Wilcoxon rank-sum tests (both p < 0.05). Among them, 1885 DEGs were commonly identified, and 87% (1640 genes) had identical dysregulation directions (binomial test, p < 1.00E-16). A PPI network with 1623 nodes and 8159 edges was constructed, and 18 hub genes were identified using the Analyze Network plugin in Cytoscape. Of 18 genes, CAV1, PECAM1, BMP4, VEGFA, FYN, SPP1, and COL1A1 were further validated in the GeneCards database and independent dataset GSE24206. ceRNA networks of VEGFA, SPP1, and COL1A1 were constructed. The genes were verified by qPCR in samples of TGF-β1-induced HFL fibroblast cells and pulmonary fibrosis mice. Finally, Sea Buckthorn and Gnaphalium Affine were predicted as potential TCMs for IPF. The TCMs were verified by qPCR in TGF-β1-induced MRC-5 cells. Conclusion This analysis strategy may be useful for elucidating novel mechanisms underlying IPF at the transcriptome level. The identified hub genes may play key roles in IPF pathogenesis and therapy.

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