遵义医科大学学报2026，Vol.49Issue(3)：239-251,13.
基于生物信息学方法筛选肝纤维化关键基因及潜在治疗药物预测
Screening of key genes for liver fibrosis based on bioinformatics methods and potential therapeutic drug prediction
摘要
Abstract
Objective To identify key genes involved in the pathogenesis of liver fibrosis and validate their ex-pression in animal models,assessing their significance and potential biological functions in liver fibrosis and hep-atocellular carcinoma.Methods We integrated and analyzed GEO datasets(GSE174099,GSE83596,GSE35961,GSE55747)from bile duct ligation(BDL),high-fat diet,methionine-and choline-deficient(MCD)diet,and CCl4-induced liver fibrosis models to screen for differentially expressed genes(DEGs).GO and KEGG enrichment analyses were performed using DAVID,a protein-protein interaction(PPI)network was constructed with STRING,and protein distribution was queried via the HPA database.Animal models were es-tablished,and key protein expression was validated by western blot.Immune correlation and ROC diagnostic val-ue were analyzed.Potential drugs,miRNAs,and transcription factors were predicted.Results We identified 105 common DEGs,enriched in processes such as cell migration,adhesion,apoptosis,and kinase activity.Key genes including Cd44,Col1a1,Col4a1,Nid1,Lgals3,Trem2,and Anxa2 were screened based on the degree algorithm,with Anxa2 and Lgals3 further identified as core genes.Both were upregulated in hepatocellular carci-noma and highly correlated with various immune checkpoint factors.Animal experiments confirmed significantly elevated Anxa2 expression in liver fibrosis,demonstrating good diagnostic performance.Drug prediction sugges-ted artesunate,fluocinolone acetonide,among others,as potential targeted drugs for Anxa2.miRNAs like mmu-miR-101a-3p and transcription factors like RCOR1 and HCFC1 were predicted to be involved in its regulation.Conclusion Anxa2 is a potential key gene for the diagnosis and treatment of liver fibrosis and may serve as a common therapeutic target for both liver fibrosis and hepatocellular carcinoma.关键词
肝纤维化/多模型和多组学分析/差异表达基因/膜联蛋白A2/治疗靶点Key words
liver fibrosis/multi-model and multi-omics analysis/differentially expressed genes/Anxa2/ther-apeutic targets分类
医药卫生引用本文复制引用
李嘉静,曹志豪,欧玲,陈浩,李兵,杜倩,朱厅厅,孟令杰..基于生物信息学方法筛选肝纤维化关键基因及潜在治疗药物预测[J].遵义医科大学学报,2026,49(3):239-251,13.基金项目
国家自然科学基金资助项目(NO:82460759) （NO:82460759）
贵州省卫健委科技专项(NO:gzwkj2024-348) （NO:gzwkj2024-348）
贵州大学大学生创新创业训练计划项目(NO:gzusc2023127). （NO:gzusc2023127）
