| 引用本文: | 张泽鑫,林思其,刘紫凤,吴汶丰,黄子怡,陈祎琦,李菁,林丽珠,于奕.基于网络药理学和生物信息学的大黄牡丹汤治疗结肠癌的分子靶点鉴定和预后模型构建[J].中国现代应用药学,2022,39(15):1925-1937. |
| ZHANG Zexin,LIN Siqi,LIU Zifeng,WU Wenfeng,HUANG Ziyi,CHEN Yiqi,LI Jing,LIN Lizhu,YU Yi.Network Pharmacology Integrated Bioinformatics Explores the Mechanism of Dahuang-Mudan Decoction for Colon Cancer and Construction of Prognostic Model[J].Chin J Mod Appl Pharm(中国现代应用药学),2022,39(15):1925-1937. |
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| 基于网络药理学和生物信息学的大黄牡丹汤治疗结肠癌的分子靶点鉴定和预后模型构建 |
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张泽鑫1, 林思其2, 刘紫凤2, 吴汶丰2, 黄子怡2, 陈祎琦2, 李菁3, 林丽珠4, 于奕3
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1.广州中医药大学, 第一临床医学院, 广州 510405;2.广州中医药大学, 第二临床医学院, 广州 510405;3.湖南中医药大学第一附属医院, 长沙 410000;4.广州中医药第一附属医院, 广州 510405
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| 摘要: |
| 目的 鉴定大黄牡丹汤治疗结肠癌的核心化合物和靶点，以及构建预后模型来评估患者的总体生存情况。方法 通过检索多个数据库筛选得到大黄牡丹汤治疗结肠癌的靶点；通过GO和KEGG富集分析探讨大黄牡丹汤治疗结肠癌的作用机制；在使用单因素Cox分析筛选出与生存相关的靶点后，使用LASSO回归构建预后模型，计算模型风险评分；KM生存分析和ROC曲线用以验证和评估模型的可靠性；构建蛋白互作（protein protein interaction，PPI）网络和疾病-药物-化合物-靶点网络以筛选出核心靶点；使用HPA免疫组化数据库和Image J软件对核心靶点进行蛋白表达的验证；分子对接和分子动力学以评估核心化合物和靶点的结合情况。结果 共筛选出22个大黄牡丹汤治疗结肠癌的靶点，其主要参与调控对酮、氧水平的反应等生物学过程，与胃泌素信号、DNA损伤应答通路有关。LASSO回归去除冗杂因素，对单因素Cox分析筛选出的5个基因（CHEK1、BIRC5、GSTM2、CCNB1、VEGFA）构建预后模型。疾病-药物-化合物-靶点网络共筛选出2个核心化合物：槲皮素和芦荟大黄素。PPI网络共筛选出4个核心靶点：CCNB1、MYC、CCND1、PCNA。将核心靶点和预后模型的基因取交集，得到核心的1个靶点：CCNB1。生存分析显示CCNB1在高低风险组之间具有显著性差异。免疫组化结果表明，CCNB1在正常组织和结肠癌组织中差异表达，其差异具有统计学意义（P<0.01）。分子对接和分子动力学结果验证了芦荟大黄素、槲皮素和CCNB1具有稳定的结合能。结论 大黄牡丹汤治疗结肠癌发挥作用主要可能通过槲皮素、芦荟大黄素靶向CCNB1来实现，大黄牡丹汤治疗结肠癌的预后模型可以用于患者预后的评估，效能良好。 |
| 关键词: 分子对接 分子动力学 免疫组化 大黄牡丹汤 结肠癌 预后模型 |
| DOI：10.13748/j.cnki.issn1007-7693.2022.15.002 |
| 分类号:R979 |
| 基金项目:湖南省卫生健康委2020年度科研立项课题（20200949） |
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| Network Pharmacology Integrated Bioinformatics Explores the Mechanism of Dahuang-Mudan Decoction for Colon Cancer and Construction of Prognostic Model |
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ZHANG Zexin1, LIN Siqi2, LIU Zifeng2, WU Wenfeng2, HUANG Ziyi2, CHEN Yiqi2, LI Jing3, LIN Lizhu4, YU Yi3
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1.Guangzhou University of Chinese Medicine, The First Clinical Medical College, Changsha 410000, China;2.Guangzhou University of Chinese Medicine, The Second Clinical Medical College, Guangzhou 510405, China;3.The First Hospital of Hunan University of Chinese Medicine, Changsha 410000, China;4.The First Hospital of Guangzhou University of Chinese Medicine, Guangzhou 510405, China
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| Abstract: |
| OBJECTIVE To identify the core compounds and targets of Dahuang-Mudan decoction for colon cancer, and construct a prognostic model to evaluate the overall survival of patients. METHODS Targets of Dahuang-Mudan decoction for colon cancer were screened from multiple databases. GO analysis and KEGG pathway enrichment analysis were performed to explore the possible mechanisms of targets. After screening for survival-related targets by univariate Cox analysis, LASSO regression were used to construct a prognostic model and calculate the scores of the model. KM survival analysis and ROC curve were adopted to verify and evaluate the model's feasibility. Protein protein interaction(PPI) network and Disease-Drug- Compound-Target network were constructed to screen the core target. HPA immunohistochemistry database and Image J software were employed to demonstrate the protein expression of the core target. Molecular docking and dynamics were evaluated to the binding activity of the core compounds and targets. RESULTS A total of 22 targets in Dahuang-Mudan decoction for colon cancer had been screened. These targets participated in regulating ketone and oxygen level reaction and were related to gastrin signaling and DNA injury response pathway. After removing the redundant factors, five genes including CHEK1, BIRC5, GSTM2,CCNB1 and VEGFA, which were screened by univariate Cox analysis, were used to construct a model by LASSO regression. Two core compounds including aloe-emodin and quercetin were screened by Disease-Drug-Compound-Target network. Four core targets including CCNB1, MYC, CCND1 and PCNA were screened via PPI network. One core target including CCNB1 was obtained by crossing the genes of prognostic model and four core targets. KM analysis showed significant difference in CCNB1 between high and low risk groups. Immunocytochemistry indicated that CCNB1 was differentially expressed in normal and colon cancer tissues. The difference was statistically significant(P<0.01). Molecular docking and dynamics demonstrated that the bindings of quercetin and aloe-emodin to CCNB1 were stable. CONCLUSION The role of Dahuang-Mudan decoction for colon cancer may be achieved by quercetin and aloe-emodin targeting CCNB1. The prognostic model have a good efficacy in assessing patients' prognosis. |
| Key words: molecular docking molecular dynamics immunocytochemistry Dahuang-Mudan decoction colon cancer prognostic model |
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