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基于网络药理学和生物信息学的姜黄素抑制肾透明细胞癌增殖的机制研究 被引量:2

The mechanism of curcumin inhibiting the proliferation of clear cell renal cell carcinoma based on network pharmacology and bioinformatics
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摘要 目的通过网络药理学和生物信息学挖掘并验证姜黄素抑制肾透明细胞癌增殖的作用机制。方法从PharmMapper、GeneCards数据库筛选肾透明细胞癌和姜黄素共同靶点基因;应用TCGA数据库数据分析筛选出在肾透明细胞癌组织样本和正常组织样本中的差异表达并影响预后的共同靶点基因;利用STRING平台构建姜黄素-肾透明细胞癌靶点交互网络(protein-protein interaction,PPI);利用R软件对上述筛选靶点蛋白进行GO生物过程分析及KEGG通路富集分析;姜黄素和(或)活性氧抑制剂N-乙酰基-L-半胱氨酸(N-acetyl-L-cysteine,NAC)作用于肾癌786-O、ACHN细胞后,通过CCK8检测不同浓度姜黄素对细胞增殖及细胞活力影响,通过活性氧检测试剂盒(2′,7′-dichlorodihydrofluorescein diacetate,DCFH-DA)检测细胞内活性氧水平,丙二醛(malondialdehyde,MDA)测定试剂盒测定细胞内MDA变化。结果PharmMapper网站及GeneCards数据库筛选出姜黄素和肾癌共同靶点109个;TCGA数据库数据分析筛选出37个差异基因可能影响患者的总体生存期;PPI筛选出姜黄素抑制肾透明细胞癌生物学行为的核心靶标蛋白主要涉及CASP3、EGFR、CHEK1、HSP90AA1、AR等。GO富集分析确定213个条目,主要包括活性氧代谢过程、对类固醇激素的反应、纤维蛋白溶解等生物活性过程;KEGG富集分析确定24个条目,主要涉及丙酮酸代谢、糖酵解/糖异生、FoxO信号通路、大肠癌、酪氨酸代谢、IL-17信号通路、细胞凋亡等信号通路;姜黄素以时间和剂量依赖性方式降低了786-O、ACHN的细胞活力(P<0.05);姜黄素处理肾癌细胞后活性氧水平及MDA水平显著升高(P<0.05);加入NAC后逆转了姜黄素对786-O和ACHN细胞的细胞活力影响(P<0.05)。结论姜黄素可能参与氧化应激途径抑制肾细胞癌的增殖。 Objective To explore and verify the mechanism of curcumin’s inhibition of the proliferation of renal clear cell carcinoma(RCCC)based on network pharmacology and bioinformatics.Methods We screened common target genes of RCCC and curcumin from PharmMapper and GeneCards databases.We used TCGA database data analysis to screen out common target genes which not only differentially expressed between RCCC tissue samples and normal tissue samples but also affected prognosis.We also used STRING platform to construct curcumin-RCCC targets interaction network,used R software to perform GO biological process analysis and KEGG pathway enrichment analysis based on the above-mentioned screening target proteins.After curcumin and/or active oxygen inhibitor N-acetyl-L-cysteine(NAC)were incubated in renal cancer 786-O and ACHN cells,CCK8 was used to detect the effects of different concentrations of curcumin on cell proliferation and cell viability.Reactive oxygen detection kit(DCFH-DA)was used to detect the level of intracellular reactive oxygen species,and malondialdehyde(MDA)determination kit(TBA method)to detect intracellular malondialdehyde changes.Results PharmMapper website and GeneCards database screened out 109 common targets of curcumin and RCCC.TCGA database data analysis screened out 37 differentially expressed genes(DEGs)that might affect the overall survival of patients.The core target proteins of curcumin screened out by protein-protein interaction(PPI)that inhibited the biological behavior of RCCC mainly involved CASP3,EGFR,CHEK1,HSP90 AA1,and AR.GO enrichment analysis identified 213 items,mainly including reactive oxygen species metabolic process,response to steroid hormones,fibrinolysis and other biologically active processes.KEGG enrichment analysis identified 24 items,which were mainly related to pyruvate metabolism,glycolysis/gluconeogenesis,FoxO signaling pathway,colorectal cancer,tyrosine metabolism,IL-17 signaling pathway,apoptosis and other signaling pathways.Curcumin reduced the cell viability of 786-O and ACHN in a time-and dose-dependent manner(P<0.05).After curcumin was incubated with kidney cancer cells,the level of reactive oxygen species and MDA increased significantly(P<0.05).The addition of NAC reversed the effect of curcumin on the cell viability of 786-O and ACHN cells(P<0.05).Conclusion Curcumin may participate in the oxidative stress pathway to inhibit the proliferation of renal cell carcinoma.
作者 段万里 翟宇瑶 潘思源 杨海燕 程永毅 孙羿 邓骞 DUAN Wanli;ZHAI Yuyao;PAN Siyuan;YANG Haiyan;CHENG Yongyi;SUN Yi;DENG Qian(Department of Urology,The Third Affiliated Hospital of Xi’an Jiaotong University/Shaanxi Provincial People’s Hospital,Xi’an 710068;Shaanxi Provincial Key Laboratory of Infection and Immune Diseases,Xi’an 710068;Department of Pharmacy,Xi’an No.4 Hospital,Xi’an 710004,China)
出处 《西安交通大学学报(医学版)》 CAS CSCD 北大核心 2022年第2期278-285,共8页 Journal of Xi’an Jiaotong University(Medical Sciences)
基金 陕西省自然科学基础研究计划项目(No.2020JQ-945)。
关键词 肾透明细胞癌 姜黄素 氧化应激 增殖 网络药理学 生物信息学 renal clear cell carcinoma curcumin oxidative stress proliferation network pharmacology bioinformatics
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