Identification of hub genes and key pathways of paraquat-induced human embryonic pulmonary fibrosis by bioinformatics analysis and in vitro studies.

AGING-US(2021)

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摘要
OBJECTIVE:Paraquat (N,N0-dimethyl-4,40-bipyridinium dichloride;PQ) is a highly toxic pesticide, which usually leads to acute lung injury and subsequent development of pulmonary fibrosis. The exact mechanism underlying PQ-induced lung fibrosis remain largely unclear and as yet, no specific treatment drugs have been approved. Our study aimed to identify its potential mechanisms of PQ-induced fibrosis through a modeling study in vitro studies and bioinformatics analysis. METHODS:Gene expression datasets associated with PQ-induced lung fibrosis were obtained from the Gene Expression Omnibus, wherefrom differentially expressed genes (DEGs) were identified using GEO2R. Functional enrichment analyses were performed using the Database for Annotation Visualization and Integrated Discovery. The DEGs analyzed by a protein-protein interaction network was constructed with the Search Tool for the Retrieval of Interacting Genes database. MCODE, a Cytoscape plugin, was subsequently used to identify the most significant modules. The expression of the key genes in PQ-induced pulmonary fibrotic tissues was verified by reverse transcription-quantitative PCR (RT-qPCR). RESULTS:Two datasets were analyzed and revealed 92 overlapping DEGs. Functional analysis demonstrated that these 92 DEGs were enriched in the 'TNF signaling pathway', 'CXCR chemokine receptor binding', and 'core promoter binding'. Moreover, nine hub genes were identified from the protein-protein interaction network formed from the DEGs. These results suggested that the TNF signaling pathway and nine hub genes are possibly involved in PQ-induced lung fibrosis progression. CONCLUSIONS:This integrative analysis identified candidate genes and pathways potentially involved in PQ-induced lung fibrosis, and could benefit future development of novel approaches for controlling and treating this disease.
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关键词
paraquat, pulmonary fibrosis, bioinformatics analysis, in vitro experiments
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