Autophagy-related gene expression in pulmonary fibrosis models:bioinformatic analysis and experimental validation
- VernacularTitle:自噬相关基因在肺纤维化模型中的表达:生物信息学分析及实验验证
- Author:
Kexin LIU
1
;
Kaimin HAO
;
Wenyue ZHUANG
;
Zhengyi LI
Author Information
- Publication Type:Journal Article
- Keywords: pulmonary fibrosis; autophagy; bioinformatics; differentially expressed genes; prognostic model; R programming language; bleomycin; TGF-β1
- From: Chinese Journal of Tissue Engineering Research 2026;30(5):1129-1138
- CountryChina
- Language:Chinese
- Abstract: BACKGROUND:The stress effect of autophagy on epithelial cells,fibroblasts and myofibroblasts is closely related to the formation process of pulmonary fibrosis.OBJECTIVE:To screen the genes related to autophagy in patients with pulmonary fibrosis,and explore their correlation with the prognosis of patients with pulmonary fibrosis,in order to provide a new target for clinical intervention in pulmonary fibrosis.METHODS:The gene expression profiling dataset downloaded from GSE70866 was used as a training set,differentially expressed genes between pulmonary fibrosis patients and normal healthy individuals was analyzed using the R language and intersected with autophagy-related genes to identify the differentially expressed genes with the most significant changes.Multiple analysis methods were used to identify key prognostic genes and construct genetic prognostic models.Patients with pulmonary fibrosis were divided into high-risk and low-risk groups according to their risk scores,and the validity of the prognostic model was verified using the Siena cohort and Leuven cohort validation sets.A cell model of pulmonary fibrosis was established by inducing HFL-1 cells(human embryonic lung fibroblasts)with transforming growth factor-β1,and an animal model of pulmonary fibrosis was established in mice by tracheal instillation of bleomycin to validate the expressions of prognostic genes.RESULTS AND CONCLUSION:(1)There were 2 650 differentially expressed genes between fibrotic tissue and normal tissue.Among them,34 genes related to autophagy showed significant expression changes.(2)Kaplan-Meier survival analysis curves for the Siena cohort and Leuven cohort validation sets showed significantly lower survival in the high-risk group than in the low-risk group.(3)Three autophagy genes related to prognosis were screened out:myelocytomatosis viral oncogene(MYC),C-C motif chemokine ligand 2(CCL2),and GABA type a receptor associated protein like 1(GABARAPL1).(4)Both in vivo and in vitro studies showed that compared with the control group,the expression levels of myelocytomatosis viral oncogene and C-C motif chemokine ligand 2 mRNA and protein were significantly higher in the lung fibrosis model group(P＜0.01,P＜0.05),while the expression levels of GABA type a receptor associated protein like 1 mRNA and protein were lower(P＜0.001).To conclude,bioinformatics methods are used to analyze the expression of three autophagy-related genes in pulmonary fibrosis and their correlation with the prognosis of patients with pulmonary fibrosis.The constructed prognostic model has good predictive ability for the 1-,2-,and 3-year survival rates of patients with pulmonary fibrosis.Moreover,in vivo and in vitro models have been used to verify that myelocytomatosis viral oncogene and C-C motif chemokine ligand 2 are highly expressed in lung fibroblasts and tissues,and that GABA type a receptor associated protein like 1 is lowly expressed.
