To investigate the molecular mechanisms underlying idiopathic pulmonary fibrosis (IPF), we analyzed the GSE173355 and GSE173356 datasets obtained from the NCBI-GEO database. We identified differentially expressed genes (DEGs) and differentially methylated sites. Functional enrichment analysis was conducted for both DEGs and differentially methylated sites. Functional enrichment analysis was performed for both DEGs and differentially methylated sites, alongside an examination of immune-related scores, proportions, and GSVA enrichment scores of immune cells in IPF versus control samples. An integrated gene-methylation association analysis revealed 8 genes with expression levels negatively influenced by methylation. The Rap1 pathway, Focal adhesion, and Axon guidance were significantly enriched among both DEGs and differentially methylated sites. Immune-related scores were notably lower in the IPF group compared to the control group, with marked differences in immune cell proportions and GSVA enrichment scores. Screening of DEGs identified 361 differentially expressed immune-related genes (IRGs). Protein-protein interaction (PPI) network analysis using the STRING database and Cytoscape software unveiled 10 key genes and 3 core subnetworks. RT-qPCR validation in bleomycin-induced IPF mouse model and A549 EMT model confirmed the reliability of most findings. These results provide new insights into IPF pathogenesis and potential therapeutic strategies, necessitating further functional validation.
Integrated bioinformatics analysis screened the key genes and pathways of idiopathic pulmonary fibrosis.
综合生物信息学分析筛选出特发性肺纤维化的关键基因和通路
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作者:Wu Juan, Wei Yangyang, Kang Hong, Yu Xiao, Wei Shuting, Xue Ting, Kong Xiaomei
| 期刊: | Scientific Reports | 影响因子: | 3.900 |
| 时间: | 2025 | 起止号: | 2025 Apr 25; 15(1):14448 |
| doi: | 10.1038/s41598-025-97037-9 | 研究方向: | 信号转导 |
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