基于网络药理学分析“附子-白术”药对治疗乳腺癌骨转移的作用机制

Analysis of the Mechanism of“Radix Aconiti Lateralis Preparata-Rhizoma Atractylodis Macrocephalae”Medicine on Bone Metastasis of Breast Cancer Based on Network Pharmacology

目的:基于网络药理学分析“附子-白术”治疗乳腺癌骨转移的作用机制。方法:利用中药系统药理学数据库与分析平台(TCMSP)数据库并结合文献筛选附子和白术的活性成分,使用TCMSP及Swiss Target Prediction数据库预测作用靶点,通过GeneCards数据库收集乳腺癌骨转移的治疗靶点,绘制韦恩图获取药物疾病共同靶点,并导入Cytoscape3.7.1软件构建“药物-成分-疾病-靶点”网络。利用STRING数据库构建蛋白质-蛋白质相互作用(PPI)网络,同时利用R软件进行基因本体(GO)富集分析和京都基因和基因组百科全书(KEGG)富集分析。结果:“附子-白术”通过25个活性成分作用于205个乳腺癌骨转移治疗靶点。主要通过9种核心活性成分,作用于AKT1、IL6、MAPK3等30个核心靶点,调控雌激素、破骨细胞分化、PI3K-AKT、HIF-1、MAPK等信号通路,发挥治疗乳腺癌骨转移的作用。结论:“附子-白术”通过多成分、多靶点、多通路来调控乳腺肿瘤增殖、凋亡、转移并减轻骨破坏、骨痛。

Objective:To analyze the mechanism of“Radix Aconiti Lateralis Preparata-Rhizoma Atractylodis Macrocephalae”treatment of breast cancer bone metastasis based on network pharmacology.Methods:TCMSP database and literature were used to screen the active ingredients of Radix Aconiti Lateralis Preparata-Rhizoma Atractylodis Macrocephalae.TCMSP and Swiss Target Prediction database were used to predict the action target,and the therapeutic target of breast cancer bone metastasis was collected through GeneCards database.Venn diagram was draw to obtain the common target of drug disease,and Cytoscape 3.7.1 software was constructed to construct“drug-component-disease-Target”network.The STRING database was used to construct the protein interaction network,and the R software was used for GO and KEGG enrichment analysis.Results:“Radix Aconiti Lateralis Preparata-Rhizoma Atractylodis Macrocephalae”acted on 205 breast cancer bone metastasis treatment targets through 25 active ingredients.It was mainly through 9 core active ingredients to act on 30 core targets such as AKT1,IL6,MAPK3,regulating signal pathways such as estrogen,osteoclast differentiation,PI3K-AKT,HIF-1,MAPK function etc.Conclusion:“Radix Aconiti Lateralis Preparata-Rhizoma Atractylodis Macrocephalae”regulates breast tumor proliferation,apoptosis,metastasis and relieves bone destruction and bone pain through multiple components,multiple targets,and multiple pathways.