FOLLOWUS
Department of Oncology and Haematology, the Fourth Clinical Medical College of Guangzhou University of Chinese Medicine,Shenzhen, Guangdong Province (518033), China
Prof. OUYANG Chen-sheng, E-mail:chensheng_ouyang@126.com.
纸质出版日期:2021-11-15,
网络出版日期:2020-06-22,
录用日期:2020-04-22
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Li-na YANG, Zhu-lin WU, Zhen-jiang YANG, 等. 数据挖掘联合网络药理学方法探索核心中药治疗乳腺癌的作用机制[J]. Chinese Journal of Integrative Medicine, 2021,27(12):919-926.
Li-na YANG, Zhu-lin WU, Zhen-jiang YANG, et al. Exploring Mechanism of Key Chinese Herbal Medicine on Breast Cancer by Data Mining and Network Pharmacology Methods*[J]. Chinese Journal of Integrative Medicine, 2021,27(12):919-926.
Li-na YANG, Zhu-lin WU, Zhen-jiang YANG, 等. 数据挖掘联合网络药理学方法探索核心中药治疗乳腺癌的作用机制[J]. Chinese Journal of Integrative Medicine, 2021,27(12):919-926. DOI: 10.1007/s11655-020-3422-y.
Li-na YANG, Zhu-lin WU, Zhen-jiang YANG, et al. Exploring Mechanism of Key Chinese Herbal Medicine on Breast Cancer by Data Mining and Network Pharmacology Methods*[J]. Chinese Journal of Integrative Medicine, 2021,27(12):919-926. DOI: 10.1007/s11655-020-3422-y.
目的:
2
利用数据挖掘技术筛选治疗乳腺癌的核心中药
并利用网络药理学方法分析其潜在的作用机制.
方法:
2
收集治疗乳腺癌的中医临床处方
应用中医传承辅助平台(TCMISS) 筛选核心中药. 然后
利用中药系统药理学数据库与分析平台(TCMSP) 检索核心中药的活性成分和对应的靶点
并使用OMIM和MalaCards数据库获取乳腺癌的靶点基因. 随后筛选核心中药与乳腺癌的共同靶点
并构建蛋白质-蛋白质相互作用(PPI) 网络. 此外
通过Cytoscape 3.7.1构建 "核心中药-活性成分-乳腺癌-靶点" 的网络. 最后
利用David数据库进行京都基因和基因组百科全书(KEGG) 和基因本体论(GO) 分析
以揭示核心中药的作用机制.
结果:
2
共鉴定出7味核心中药
其有效成分包括槲皮素、木犀草素、川陈皮素、山奈酚、异鼠李素、柚皮素、β-谷甾醇等. PPI分析结果显示核心中药的关键靶点为ESR1、MYC、CCND1、EGFR、CASP3、ERBB2
KEGG通路分析富集在PI3K-Akt、p53、ErbB和HIF-1等信号通路.
结论:
2
基于数据挖掘和网络药理学方法
本研究发现治疗乳腺癌的核心中药可能通过影响与乳腺癌发生发展相关的靶点和通路来发挥抗乳腺癌作用.
Objective:
2
To screen the key Chinese herbal medicines (KCHMs) against breast cancer by data mining
and analyze the potential mechanism of KCHMs using network pharmacology method.
Methods:
2
Clinical prescriptions consisted of Chinese herbal medicines for treating breast cancer were screened
and then Traditional Chinese Medicine Inheritance Support System (TCMISS) was applied to obtain the KCHMs. Subsequently
active ingredients and corresponding target genes of KCHMs were searched by Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) database
and target genes of breast cancer were collected using OMIM and MalaCards. After that
the overlapping target genes of KCHMs and breast cancer were screened
and the protein-protein interaction (PPI) network was built. In addition
a network of "KCHMs-active ingredients-breast cancer-targets" was constructed by Cytoscape 3.7.1. Finally
Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analysis were performed with Database for Annotation
Visualization and Integrated Discovery (DAVID) database to reveal the action mechanism of KCHMs.
Results:
2
A total of 7 KCHMs were identified
whose active ingredients include quercetin
luteolin
nobiletin
kaempferol
isorhamnetin
naringenin
and be-ta-sitosterol
etc. Based on protein-protein interaction analysis
core targets were ESR1
MYC
CCND1
EGFR
CASP3
ERBB2
etc. Several KEGG pathways (e.g
PI3K-Akt
p53
ErbB
and HIF-1 signaling pathways) were found.
Conclusion:
2
Based on the combination of the data mining method and network pharmacology approach
the therapeutic effect of KCHMs on breast cancer may be realized by acting on target genes and signaling pathways related to the formation and progression of breast cancer.
breast cancerChinese medicineChinese herbal medicinepharmacology
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