Hu Youwen, Xiao Yangyang
Department of Gastroenterology, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi Province, China.
Department of Gerontology, Jiangxi University of Traditional Chinese Medicine Affiliated Hospital, No 445, Bayi Avenue, Nanchang, 330006, Jiangxi Province, China.
Naunyn Schmiedebergs Arch Pharmacol. 2025 May;398(5):5693-5703. doi: 10.1007/s00210-024-03598-3. Epub 2024 Nov 28.
Hepatocellular carcinoma (HCC) is a tumor with high morbidity and mortality. Current research suggests that statins may aid in its prevention and treatment, while studies on the associated mechanisms remain limited. Therefore, we aim to reveal the mechanism of atorvastatin treatment for HCC by using network pharmacology and bioinformatics methods. The databases SwissTargetPrediction, PharmMapper, and DrugBank were utilized to obtain targets of atorvastatin, while GSE169289, GSE135631, and GSE207435 were used to identify differentially expressed genes (DEGs) for HCC. The overlap between the two groups was used to identify atorvastatin's target for treating HCC. Following protein-protein interaction (PPI) analysis, hub genes were identified using Cytoscape software and LASSO analysis. The hub genes were further validated using data from The Cancer Genome Atlas (TCGA) and The Human Protein Atlas (HPA) databases. To evaluate the clinical significance of the hub genes, Kaplan-Meier (KM) survival analysis and Cox analysis were conducted. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA) were performed to investigate potential mechanisms. Finally, molecular docking analysis was performed to validate the interaction between atorvastatin and the hub genes. A total of 1948 DEGs of HCC and 380 targets of atorvastatin were identified, respectively. After taking the intersection, 79 genes were identified as potential targets of atorvastatin for HCC treatment. After multiple screening methods, CYP2C9 was ultimately identified as the hub gene. Analysis of data from TCGA and HPA databases showed reduced expression of CYP2C9 in HCC tissues. KM and Cox analysis showed a favorable prognosis for HCC patients with high CYP2C9 expression. KEGG and GSEA indicated that metabolism of xenobiotics by cytochrome P450, and PPAR signaling pathway could be the potential mechanisms for atorvastatin in treating HCC. Molecular docking analysis revealed that atorvastatin binds to CYP2C9 with a binding energy of - 8.837, indicating highly stable binding. CYP2C9 is associated with the prognosis of HCC patients and could serve as a potential target for atorvastatin treatment in HCC.
肝细胞癌(HCC)是一种发病率和死亡率都很高的肿瘤。目前的研究表明,他汀类药物可能有助于其预防和治疗,而相关机制的研究仍然有限。因此,我们旨在通过网络药理学和生物信息学方法揭示阿托伐他汀治疗HCC的机制。利用SwissTargetPrediction、PharmMapper和DrugBank数据库获取阿托伐他汀的靶点,同时使用GSE169289、GSE135631和GSE207435来鉴定HCC的差异表达基因(DEG)。两组之间的重叠部分用于确定阿托伐他汀治疗HCC的靶点。经过蛋白质-蛋白质相互作用(PPI)分析后,使用Cytoscape软件和LASSO分析来鉴定枢纽基因。使用来自癌症基因组图谱(TCGA)和人类蛋白质图谱(HPA)数据库的数据对枢纽基因进行进一步验证。为了评估枢纽基因的临床意义,进行了Kaplan-Meier(KM)生存分析和Cox分析。进行京都基因与基因组百科全书(KEGG)和基因集富集分析(GSEA)以研究潜在机制。最后,进行分子对接分析以验证阿托伐他汀与枢纽基因之间的相互作用。分别鉴定出1948个HCC的DEG和380个阿托伐他汀的靶点。取交集后,79个基因被确定为阿托伐他汀治疗HCC的潜在靶点。经过多种筛选方法,最终确定CYP2C9为枢纽基因。对TCGA和HPA数据库数据的分析表明,HCC组织中CYP2C9的表达降低。KM和Cox分析表明,CYP2C9高表达的HCC患者预后良好。KEGG和GSEA表明,细胞色素P450对外源生物的代谢以及PPAR信号通路可能是阿托伐他汀治疗HCC的潜在机制。分子对接分析显示,阿托伐他汀与CYP2C9结合,结合能为 - 8.837,表明结合高度稳定。CYP2C9与HCC患者的预后相关,可作为阿托伐他汀治疗HCC的潜在靶点。