Exploration of the Pathogenesis of Chronic Obstructive Pulmonary Disease Caused by Smoking-Based on Bioinformatics Analysis and In Vitro Experimental Evidence

Yingchi Zhang, Yuxin Sheng, Yanrong Gao,Yujia Lin, Bin Cheng,Hongmei Li,Ling Zhang,Haiming Xu

Toxics(2023)

引用 0|浏览8
暂无评分
摘要
This study was aimed at investigating the pathogenesis of chronic obstructive pulmonary disease (COPD) caused by smoking-based on bioinformatics analysis and in vitro experimental evidence. The GEO, GEO2R, TargetScan, miRDB, miRWalk, DAVID, and STRING databases were used for bioinformatics analysis. The mRNA expression and the protein levels were determined by real-time PCR and ELISA. After taking the intersection of the diversified results of the databases, four differentially expressed miRNAs (hsa-miR-146a, hsa-miR-708, hsa-miR-150, and hsa-miR-454) were screened out. Subsequently, a total of 57 target genes of the selected miRNAs were obtained. The results of DAVID analysis showed that the selected miRNAs participated in COPD pathogenesis through long-term potentiation, the TGF-beta signaling pathway, the PI3K-Akt signaling pathway, etc. The results of STRING prediction showed that TP53, EP300, and MAPK1 were the key nodes of the PPI network. The results of the confirmatory experiment showed that, compared with the control group, the mRNA expression of ZEB1, MAPK1, EP300, and SP1 were up-regulated, while the expression of MYB was down-regulated and the protein levels of ZEB1, MAPK1, and EP300 were increased. Taken together, miRNAs (hsa-miR-146a, hsa-miR-708, hsa-miR-150, and hsa-miR-454) and their regulated target genes and downstream protein molecules (ZEB1, EP300, and MAPK1) may be closely related to the pathological process of COPD.
更多
查看译文
关键词
smoking,COPD,Go analysis,KEGG analysis,protein interaction network,miRNA,validation
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要