摘要
目的采用加权基因共表达网络分析(WGCNA)法探讨龙葵抗肺腺癌的潜在生物靶标。方法基于中药系统药理学技术平台(TCMSP)及文献检索,以口服利用度(OB)、类药性(DL)构建龙葵活性成分数据库,采用DRAR-CPI服务器反向模拟分子-靶蛋白对接龙葵预测成分可能的作用靶标,并结合WGCNA挖掘在美国国立生物技术信息中心(NCBI)的GEO数据库中的GSE10072数据集得到共表达基因模块,并与龙葵预测靶标匹配映射,得到龙葵潜在抗肺腺癌靶点。将预测靶标与抗肺腺癌基因分别利用生物学信息注释数据库(Metascape)进行GO生物学过程富集分析和KEGG通路富集分析,并用STRING数据库结合Cytoscape软件可视化龙葵潜在抗肺腺癌靶点蛋白相互作用网络并进行网络拓扑学分析,同时构建龙葵活性成分-抗癌靶点-通路网络,探讨龙葵抗癌作用的机制。并通过UALCAN及Kaplan Meier plotter数据库分析关键基因在肺腺癌组织中转录水平的变化,通过KM plotter分析关键基因与肺腺癌患者预后的关系。结果共收集龙葵活性成分9个,包括皮树脂醇、谷甾醇、薯蓣皂苷元、辣茄碱、槲皮素、α-茄碱、澳洲茄碱、澳洲茄边碱、澳洲茄胺,预测成分作用靶标271个,筛选龙葵潜在抗癌靶点41个,其潜在调控通路包括癌症通路、PI3K-Akt信号通路、化学物致癌作用、癌症的中心碳代谢等通路。由蛋白互作网络分析可得关键基因为EGFR、CASP8、HPGDS、FYN,且证实高表达的EGFR和CASP8、低表达的HPGDS及FYN与肺腺癌患者不良预后紧密相关。结论龙葵抗肺腺癌具有多成分、多靶点、多途径作用的特点,为其抗癌物质基础及作用机制的阐明提供了科学依据。
Objective The potential biological targets for anti-lung adenocarcinoma of Solanum nigrum were scored using the weighted co-expression network analysis(WGCNA)method.Methods A database of chemical components of S.nigrum was established through oral bioavailability(OB),drug-likeness(DL)based on Traditional Chinese Medicine Systems Pharmacology(TCMSP)and literature retrieval.The targets of active ingredients of S.nigrum were predicted based on reverse docking with DRAR-CPI server,and combined with WGCNA to mine GSE10072 dataset in Gene Expression Omnibus(GEO)database to obtain coexpression gene module.Furthermore,the potential anti-lung adenocarcinoma targets of S.nigrum were confirmed under intersected with predicted targets and coexpression genes.The GO terms of biological processes and KEGG pathway enrichment analysis of predicted targets and anti-lung adenocarcinoma targets were performed by Metascape database,respectively.Using the targets-pathways networks to study the mechanisms of S.nigrum in the fight against cancer.The transcriptional level expression of key String database combined with Cytoscape software to draw the proteins-proteins interactions(PPI),and active ingredients-targets-pathways networks to study the mechanisms of S.nigrum in the fight against cancer.The transcriptional level expression of key genes in lung adenocarcinoma cancer tissues and normal lung tissues was assessed based on UALCAN dataset.And the correlation between key genes and prognosis of lung cancer patients was calculated by KM plotter analysis.Results This study collected nine active components of S.nigrum,including medioresinol,sitosterol,diosgenin,solanocapsine,quercetin,α-chaconine,solasonin,solamargine,and solasodine.Totally 271 targets were predicted,and 41 potential anticancer targets were confirmed.The potential regulatory pathways included pathway in cancer,PI3K-Akt signaling pathway,chemical carcinogenesis,central carbon metabolism in cancer and so on.From the PPI network,we found that hub genes EGFR,CASP8,HPGDS,FYN,a
作者
刘燕玲
吴美玲
胡莹
王旭景
陈卓
张爱琴
LIU Yan-ling;WU Mei-ling;HU Ying;WANG Xu-jing;CHEN Zhuo;ZHANG Ai-qin(Jinhua Hospital of TCM,Jinhua 321017,China;The affiliated Zhejiang Cancer Hospital of Zhejiang Chinese Medical University,Hangzhou 310022,China)
出处
《中草药》
CAS
CSCD
北大核心
2019年第24期6073-6083,共11页
Chinese Traditional and Herbal Drugs
基金
浙江省自然科学基金项目(LY18H290002)
浙江省中医药管理局基金重点项目(2019ZZ002)。
关键词
加权基因共表达网络分析
龙葵
肺腺癌
GEO数据库
作用机制
weighted co-expression network analysis
Solanum nigrum L.
lung adenocarcinoma
GEO database
mechanisms
