基于生物信息技术的肝纤维化关键基因及相关转录因子分析
Analysis of key genes and related transcription factors in liver fibrosis based on bioinformatic technology.
作者信息
Yang Xue, Cheng Qi-Ni, Wu Jiang-Feng, Ai Wen-Bing, Ma Lan
机构信息
Medical College, China Three Gorges University Yichang, China.
Hubei Key Laboratory of Tumor Microenvironment and Immunotherapy, China Three Gorges University Yichang, China.
出版信息
Int J Clin Exp Pathol. 2021 Apr 15;14(4):444-454. eCollection 2021.
OBJECTIVE
To analyze differentially expressed genes (DEGs) related to liver fibrosis, and clarify the key genes and the possible targets in the progression of liver fibrosis.
METHODS
Using microarray datasets, GSE38199 was extracted from Gene Expression Omnibus (GEO), and a bioinformatics method was performed to find DEGs and transcription factors related to liver fibrosis.
RESULTS
A total of 58 DEGs were screened out according to GEO2R online analysis tool, which included 49 up-regulated and 9 down-regulated genes. These DEGs were mainly involved in formation with the extracellular region and extracellular exosome through gene ontology (GO) enrichment analysis. Kyoto Encyclopedia of Gene and Genome (KEGG) pathway enrichment analysis showed that DEGs mainly participated in the PI3K-Akt signaling pathway, focal adhesion, ECM-receptor interaction, and metabolic pathways. Based on the results of the Protein-Protein Interaction (PPI) network and Molecular Complex Detection (MCODE) analysis, 9 key genes () were screened out. A total of 30 transcription factors were found according to these 9 key genes, of which 4 transcription factors (Stat3, Trp53, NF-κB1, Sp1) were enriched.
CONCLUSION
Stat3, Trp53, NF-κB1, and Sp1 were all related to the development of liver fibrosis, and might be a target for liver fibrosis.
目的
分析与肝纤维化相关的差异表达基因（DEGs），明确肝纤维化进展中的关键基因及可能的靶点。
方法
利用微阵列数据集，从基因表达综合数据库（GEO）中提取GSE38199，并采用生物信息学方法寻找与肝纤维化相关的DEGs和转录因子。
结果
根据GEO2R在线分析工具共筛选出58个DEGs，其中包括49个上调基因和9个下调基因。通过基因本体论（GO）富集分析，这些DEGs主要参与细胞外区域和细胞外囊泡的形成。京都基因与基因组百科全书（KEGG）通路富集分析表明，DEGs主要参与PI3K-Akt信号通路、粘着斑、细胞外基质-受体相互作用和代谢通路。基于蛋白质-蛋白质相互作用（PPI）网络和分子复合物检测（MCODE）分析结果，筛选出9个关键基因（）。根据这9个关键基因共发现30个转录因子，其中4个转录因子（Stat3、Trp53、NF-κB1、Sp1）富集。
结论
Stat3、Trp53、NF-κB1和Sp1均与肝纤维化的发生发展相关，且可能是肝纤维化的一个靶点。
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