摘要
目的 利用数据挖掘与生物信息学分析方法,探索中药治疗非小细胞肺癌(NSCLC)的用药规律及药理分析。方法 以“非小细胞肺癌”为主题词,限定学科目录在“中医学”、“中西医结合学”和限定主题“临床观察”或“临床研究”下检索CNKI数据库、中国生物医学文献数据库、中国学术期刊数据库中数据,检索时间为2000—2023年,通过筛选标准,其结果作为研究的数据,并进行处方分析。关联分析将关联强的药物进行网络药理学分析,采用TCSMP数据库和对应的文献构建活性成分数据库、靶点数据库,在Genecards数据库等相关数据库预测疾病的靶点基因。使用Venny建立中药与疾病的共同靶点库,在R软件中引用Bioconductor数据库做基因本体论(GO)和京都基因与基因组百科全书(KEGG)富集分析。结果 检索得到152剂处方,分析得到高频药物黄芪(95)、茯苓(76)、麦冬(65)、白术(64)、党参(63)、白花蛇舌草(55)、北沙参(54)、甘草(52)、陈皮(50)的频数最高,中医处方所用的中药多为补气药、补虚药以及化痰止咳平喘药;所用中药药味主要为甘、苦、辛;归经则以肺、脾、胃、肝为主;关联规则分析排名前3位的依次为“白花蛇舌草、半枝莲”、“黄芪、麦冬→茯苓”和“黄芪、女贞子”;系统聚类分析得到3个主要的核心中药组;GO功能富集分析,共获取总计1 603条数据,这之中生物过程(BP)包含了1 324条,细胞组成(CC)共90条,分子功能(MF)共188条。KEGG信号通路富集分析,共得到信号通路185个。结论 中医古方中治疗NSCLC的核心药物主要有黄芪、茯苓、麦冬、白术等中药,这些中药的功效以补气、补虚、化痰止咳平喘为主,其主要通过丝氨酸/苏氨酸蛋白激酶1(AKT1)、信号传导与转录激活因子3(STAT3)、非受体型酪氨酸蛋白激酶(SRC)、热休克蛋白90α家族A类成员1(HSP90AA1)、激素调控因子雌激素受体1(ESR1)、JUN原癌基因(JUN)核心靶点发挥治疗NSCLC的作用。
Objective To explore the drug use and pharmacological analysis of traditional Chinese medicine in the treatment of non-small cell lung cancer(NSCLC)by data mining and bioinformatics analysis.Methods With"non-small cell lung cancer"as the main topic,data from CNKI database,Chinese Biomedical Literature database and Chinese academic journal database were searched under"Traditional Chinese Medicine","Integrative Chinese and Western Medicine"and"clinical observation"or"clinical research"in the restricted subject catalog.The search time was 2000-2023.The results were used as data for the study and prescription analysis was performed.Association analysis was carried out for network pharmacological analysis of strongly associated drugs.TCSMP database and corresponding literature were used to build active ingredient database and target database,and the target genes of diseases were predicted in related databases such as Genecards database.Venny was used to establish a common target library of Chinese medicine and diseases,and the Bioconductor database was referenced in R software for gene ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis.Results 152 prescriptions were retrieved,and the frequency of high frequency drugs was the highest in Huangqi(95),Fuling(76),Maidong(65),Baizhu(64),Dangshen(63),Baihuasheshecao(55),Beishashen(54),Gancao(52)and Chenpi(50).Most of the traditional Chinese medicines used in TCM prescription are qi tonifying medicine,deficiency tonifying medicine and phlegm-relieving cough antiasthmatic medicine.The main taste of Chinese medicine used is sweet,bitter and xin.Lung,spleen,stomach and liver were the main methods of channeling.In the analysis of association rules,the top 3 were“Baihuasheshecao、Banzhilian”,“Huangqi,Maidong→Fuling”and“Huangqi,Nüzhenzi”.Three main core TCM groups were obtained by systematic cluster analysis.A total of 1603 data sets were obtained by GO functional enrichment analysis,including 1324 biological processes(BP),90 cell components(CC),and 188 molecular functions(MF).By enrichment analysis of KEGG signal pathways,185 signal pathways were obtained.Conclusion The core drugs in traditional Chinese medicine prescriptions for NSCLC mainly include Huangqi,Fuling,Maidong,Baizhu,etc.The efficacy of these Chinese medicines is mainly to nourish one's vitality,tonify deficiency,eliminate phlegm,relieving cough and preventing asthma.It is mainly mediated by serine/threonine protein kinase 1(AKT1),signaling and transcriptional activator 3(STAT3),non-receptor tyrosine protein kinase(SRC),Class A member of the heat shock protein 90αfamily 1(HSP90AA1),hormone regulatory factor estrogen receptor 1(ESR1),and JUN proto-oncogene(JUN)core The target plays a role in the treatment of NSCLC.
作者
吉钊
苏子婷
周言
李芸芸
张玲玉
王诗瑶
孟新源
Zhao;SU Ziting;ZHOU Yan;LI Yunyun;ZHANG Lingyu;WANG Shiyao;MENG Xinyuan(Department of Pharmacy,Cancer Hospital Affiliated to Xinjiang Medical University,Urumqi 830011,China)
出处
《中国煤炭工业医学杂志》
2024年第5期461-468,共8页
Chinese Journal of Coal Industry Medicine
基金
省部共建中亚高发病成因与防治国家重点实验室开放课题面上项目(编号:SKL-HIDCA-2020-8)
关键词
中医治疗
用药规律
非小细胞肺癌
肺肿瘤
中药
TCM treatment
Drug use rule
Non-small cell lung cancer
Lung tumor
Traditional Chinese medicine
