局解手术学杂志2024，Vol.33Issue(2)：106-111,6.DOI:10.11659/jjssx.03E023022
基于生物信息学分析肝纤维化的关键基因及相关通路研究
Key genes and related pathways of hepatic fibrosis based on bioinformatics analysis
摘要
Abstract
Objective By screening key genes and related pathways for hepatic fibrosis treatment through bioinformatics analysis,the differentially expressed genes of hepatic fibrosis patients were mined to predict potential therapeutic targets for liver fibrosis.Methods Gene expression profiles GSE197112 were obtained from GEO database.Differentially expressed genes were screened by Limma.DAVID online database was used to conduct GO enrichment analysis and KEGG signaling pathway enrichment analysis of differentially expressed genes.The protein-protein interaction(PPI)network diagram of differentially expressed genes were obtained from STRING database and visualize by Cytoscape software.At the same time,the plug-in CytoHubba in Cytoscape software was used to screen the target genes of hepatic fibrosis.Results A total of 399 differentially expressed genes were screened(P<0.01,∣log2FC∣>1.5),including 300 down-regulated genes and 99 up-regulated genes.These genes were mainly involved in GO biological processes such as mitosis checkpoint,DNA replication,chromosome segregation,cell division,apoptosis,adaptive immune response and so on,and mainly regulated the intestinal immune network for IgA production,progesterone-mediated oocyte maturation,human T-cell leukemia virus 1 infection,cell cycle,antigen processing and presentation,p53 signaling pathway,cancer transcription disorder,cell adhesion molecules and so on.Five target genes were screened by Cytoscape software:TTK,KIF2C,ASPM,DLGAP5,PBK.Conclusion In this study,399 differentially expressed genes and 5 target genes in hepatic fibrosis were screened by bioinformatics methods,which play key roles in the biological processes related to hepatic fibrosis,and provide a new direction for the pharmacological treatment of liver fibrosis.关键词
生物信息学/肝纤维化/差异表达基因/GEO数据库/靶点Key words
bioinformatics/hepatic fibrosis/differentially expressed genes/GEO database/targets分类
医药卫生引用本文复制引用
张腊英,何安玲,陈明锴..基于生物信息学分析肝纤维化的关键基因及相关通路研究[J].局解手术学杂志,2024,33(2):106-111,6.基金项目
湖北省重点研发项目(2020BCB007) （2020BCB007）
