应用网络药理学结合生物信息学预测芦荟大黄素治疗肝癌的潜在靶点。

IF 2.8 4区 医学 Q3 ENDOCRINOLOGY & METABOLISM
Jinlong Wei, Haosong Chen, Maoqi Xu, Zhenglin Zhang, Jin Wang, Wen Jiang, Weiguo Zhou, Maoming Xiong
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引用次数: 0

摘要

背景:肝细胞癌是世界范围内最常见的恶性肿瘤之一。芦荟大黄素(AE)是一种纯天然药物,虽然能有效杀伤肝癌细胞,但其内部分子机制尚未完全阐明。本研究利用网络药理学和生物信息学方法预测AE的抗肝癌靶点。方法:首先鉴定肝细胞癌与正常组织之间的差异表达基因,然后与AE的潜在药理靶基因相交进行后续分析。此外,我们还对AE的潜在靶点进行了富集和分析,以确定潜在的下游通路。通过分子对接分析上述药物靶点与AE的结合能力和相互作用。通过单因素Cox回归分析、LASSO回归分析和多因素Cox回归分析构建肝细胞癌预后模型。最后,通过分子动力学模拟进一步筛选能稳定结合AE的潜在靶点。最后,我们通过体外实验验证了AE在治疗肝细胞癌中的潜在效用。结果:将90个AE相关靶基因与肝癌差异基因进行交叉,得到13个交叉基因。上述13个基因可能通过p53信号通路、细胞周期、细胞感觉、错配修复、凋亡多规范、碱基样例修复和DNA复制等途径作用于肝癌。分子对接发现BAX、FASN、CDK1、PCNA、CLIC1、VWF、RAN、FOXM1、TGM3、CANT1、NSMCE2等蛋白与AE的结合较为稳定。进一步构建4基因预后模型。ROC曲线上1年、3年和5年生存率的曲线下面积(AUC)值分别为0.809、0.673和0.641。分子动力学分析表明,CDK1和PCNA是上述蛋白中最稳定的结合靶点。CCK8和伤口愈合实验显示,AE在增加浓度时抑制肝癌细胞的增殖和迁移。Western blot实验表明,AE通过促进肝癌细胞凋亡达到治疗肝癌的目的。结论:基于网络药理学、生物信息学、分子动力学模拟及体外实验验证,我们发现AE通过促进肝癌细胞凋亡达到治疗肝癌的作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prediction of potential targets of aloe-emodin in the treatment of hepatocellular carcinoma using network pharmacology combined with bioinformatics.

Background: Hepatocellular carcinoma is one of the most common and malignant tumors worldwide. Although aloe-emodin (AE), a pure natural drug, can effectively kill hepatocellular carcinoma cells, its internal molecular mechanism has not been fully elucidated. In this study, the anti-hepatocellular carcinoma targets of AE were predicted using network pharmacology and bioinformatics.

Methods: The differentially expressed genes between hepatocellular carcinoma and normal tissues were first identified and then further intersected with the potential pharmacological target genes of AE for subsequent analysis. Moreover, the potential targets of AE were enriched and analyzed to identify potential downstream pathways. The binding ability and interaction between the above drug targets and AE were analyzed by molecular docking. The prognostic model of hepatocellular carcinoma was subsequently constructed via univariate Cox regression analysis, LASSO regression analysis and multivariate Cox regression analysis. Finally, the potential targets that can stably bind to AE were further screened through molecular dynamics simulation. Finally, we validated the potential utility of AE in treating hepatocellular carcinoma through in vitro experiments.

Results: After 90 target genes related to AE were crossed with hepatocellular carcinoma differential genes, 13 cross genes were obtained. The above 13 genes might act on hepatocellular carcinoma through the following pathways: p53 signaling pathway, cell cycle, cellular sense, mismatch repair, apoptosis-multiple specifications, base example repair and DNA replication. Molecular docking revealed that the combination of the BAX, FASN, CDK1, PCNA, CLIC1, VWF, RAN, FOXM1, TGM3, CANT1, and NSMCE2 proteins with AE was relatively stable. A 4-gene prognostic model was further constructed. The area under the curve (AUC) values of the 1-year, 3-year and 5-year survival rates from the ROC curve were 0.809, 0.673 and 0.641, respectively. Molecular dynamics analysis revealed that CDK1 and PCNA were the most stable binding targets among the above proteins. CCK8 and wound healing assays revealed that AE inhibited the proliferation and migration of hepatocellular carcinoma cells at increasing concentrations. Western blot experiments revealed that AE achieved therapeutic effects on hepatocellular carcinoma by promoting apoptosis of hepatocellular carcinoma cells.

Conclusions: Based on network pharmacology, bioinformatics, molecular dynamics simulation, and in vitro experimental verification, we found that AE achieved a therapeutic effect on hepatocellular carcinoma by promoting apoptosis of hepatocellular carcinoma cells.

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来源期刊
Discover. Oncology
Discover. Oncology Medicine-Endocrinology, Diabetes and Metabolism
CiteScore
2.40
自引率
9.10%
发文量
122
审稿时长
5 weeks
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