jiangxi university of Chinese Medicine
目的：运用数据挖掘、网络药理学、分子对接方法探究中药复方治疗肺癌的用药规律及核心中药,为临床治疗肺癌提供有效的处方用药参考。方法：采用Excel2019收集整理临床治疗肺癌的常用中药复方,筛选有效复方,并通过中医传承辅助平台(V2.5)、SPSS Modeler 18.0、SPSS Statistics 25、cytoscape3.6等分析患者的证型分布、药物频次规律、核心药物组合以及药物关联规则等并得出核心中药；将核心中药运用TCMSP、Genecards、CTD等数据库收集有效成分、药物靶点、疾病靶点并获取交集,通过cytoscape3.9.0构建“中药-化合物-靶点-疾病”网络、再通过String平台、可视化驱动的生物信息学分析网站构建蛋白互作网络、最后进行基因本体论(gene ontology,GO)和京都基因与基因组百科全书(Kyoto encyclopedia of genes and genomes,KEGG)通路富集分析,由以上分析结果得出重要化合物以及关键靶点做分子对接；结果：筛选得到有效处方407个,涉及中药324味,药物使用频次最高依次为甘草、茯苓、白术、陈皮、半夏、黄芪、党参、浙贝母、白花蛇舌草、薏苡仁；肺癌中医证型诊断中以痰瘀互结证(45.99%),治则治法以化痰散结和解毒抗癌为主,(28.99%、29.25%),中药以补虚药为主,(32.69%)；性味归经统计为温性(41.39%)；苦味(45.5%),肺经(25.82%)为主；关联规则表明,茯苓-半夏、茯苓,半夏-白术、茯苓,浙贝母-半夏-白术分别为同一组中支持度最高的组合；复杂网络中核心药物有党参、茯苓、白术、陈皮、浙贝母、黄芪、甘草。核心中药为白术、茯苓、半夏、浙贝母；网络药理学获得作用靶点89个、核心中药主要有效成分为12-千里光酰基-8-反式白术三醇、14-乙酰基各里光酰基-8-反式白术三醇、β-谷甾醇等,重要靶点为AKT1、EGFR、TP53等,GO分子功能富集结果显示可能与RNA聚合酶II转录调节、细胞对化学压力的反应、金属离子的反应等有关,KEGG通路富集分析结果显示,关键通路富集为肿瘤坏死因子信号通路、铂耐药通路、IL-17信号通路等；关键靶点与重要化合物的对接能量均小于0kJ/mol,对接构象稳定。结论：真实世界抗肺癌中药以味苦、性温,平,寒、补虚为主,针对肺癌发病机制正气亏虚、血瘀、痰、邪毒进入,以补气和中助阳、清热解毒泻火之法来达到治疗效果,基于数据挖掘方法研究对于真实世界治疗肺癌的用药规律研究得出其核心组方包括党参、茯苓、白术、陈皮、浙贝母、黄芪、甘草,而其现代药理作用主要为抗癌细胞增殖、抗菌、免疫抑制等；在治疗肺癌的中药复方中,白术、茯苓、半夏、浙贝母尤为重要,可作为治疗肺癌的复方核心中药,核心中药治疗肺癌主要通过多成分、多靶点调控肿瘤坏死因子信号通路、铂耐药通路、IL-17信号通路等达到治疗肺癌的效果,综上为真实世界中药复方治疗肺癌的用药规律特点。对中医药治疗肺癌的临床研究有一定的指导意义。
Objective: Data mining, network pharmacology and molecular docking methods were used to explore the medication rule and core Chinese medicine of Chinese herbal compound in the treatment of lung cancer, and to provide effective prescription medication reference for clinical treatment of lung cancer. Methods: Excel2019 was used to collect and sort out commonly used Traditional Chinese medicine compounds for clinical treatment of lung cancer, and screen effective compounds. Through the traditional Chinese Medicine inheritance assistance platform (V2.5), SPSS Modeler 18.0, SPSS Statistics 25 and Cytoscape3.6, the distribution of syndrome type, drug frequency, core drug combination and drug association rules of patients were analyzed, and the core TCM was obtained. The effective components, drug targets and disease targets were collected by using TCMSP, Genecards, CTD and other databases of core TCM and the intersection was obtained. The network of "TCM - compound - target - disease" was constructed through Cytoscape3.9.0, the protein interaction network was constructed through String platform and visually-driven bioinformatics analysis website, and finally the gene ontology, GO) and The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, the molecular docking of important compounds and key targets was performed based on the above analysis results; Results: 407 effective prescriptions were screened, involving 324 traditional Chinese medicines. The highest frequency of drug use was glycyrrhiza glycyrrhiza, Poria cocos, Atractylodes atractylodes, Tangerine peel, Pinellia pinellia, Astragalus membranaceus, Codonopsis pilosula, Thunberg Fritillary bulb, Hedyotis willd and Coix seed. In the diagnosis of TCM syndromes of lung cancer, the combination of phlegm and blood stasis (45.99%), the main treatment methods (28.99%, 29.25%) were eliminating phlegm and disperding knot, detoxifying and anticancer drugs, and the main TCM drugs were deficiency tonic drugs (32.69%). The statistical results of taste and sex were temperature (41.39%). Bitter taste (45.5%), lung meridian (25.82%); Association rule showed that fuling - Pinellia, Poria cocos, Pinellia - Atractylodes atractylodes, Poria cocos, Thunberg fritillaria - Pinellia - Atractylodes atractylodes were the combinations with the highest support degree in the same group. The core drugs in the complex network were Codonopsis pilosula, Poria cocos, Atractylodes atractylodes, Tangerine peel, Fritillaria thunbergii, Astragalus membranaceus and glycyrrhiza. The core traditional Chinese medicines are Atractylodes macrocephala, Poria cohoe, Pinellia ternata and Fritillaria thunbergii. A total of 89 targets were obtained by network pharmacology. The main effective components of core Chinese medicines were 12-li photoacyl-8-trans atractylodes triol, 14-acetyl coryl-8-trans atractylodes triol, β -sitosterol, etc. The important targets were AKT1, EGFR, TP53, etc. The enrichment results of GO molecular function showed that it may be mainly related to RNA polymerase II transcriptional regulation, cell reaction to chemical pressure, and metal ion reaction. KEGG pathway enrichment analysis showed that the key pathways were enriched in TUMOR necrosis factor signaling pathway, platinum resistance pathway, and IL-17 signaling pathway. The docking energy between key targets and important compounds is less than 0kJ/mol, and the docking conformation is stable. Conclusion: Anti-lung cancer traditional Chinese medicine in the real world is mainly bitter in taste, warm in nature, flat, cold and tonic for deficiency. In view of the pathogenesis of lung cancer, qi deficiency, blood stasis, phlegm and evil poison enter, and achieve the therapeutic effect by supplementing qi, helping Yang, clearing heat, detoxifying and eliminating fire. Based on the data mining method to study the drug use rule of lung cancer treatment in the real world, the core prescription includes Codonopsis pilosula, Poria cocos, Atractylodes atractylodes, tangerine peel, Fritillaria thunbergii, Astragalus membranaceus, glycyrrhiza, and its modern pharmacological effects are mainly anti-cancer cell proliferation, antibacterial, immunosuppression, etc. In the treatment of lung cancer, atractylodes macrocephala, Poria cochus, Pinellia ternata and Fritillaria thunbergii are particularly important, which can be used as the core Chinese medicine in the treatment of lung cancer. In summary, this is the drug use law and characteristics of Chinese medicine compound in the real world in the treatment of lung cancer. Core Chinese medicine in the treatment of lung cancer mainly regulates tumor necrosis factor signaling pathway, platinum resistance pathway and IL-17 signaling pathway through multi-components and multi-targets, which has certain guiding significance for the clinical study of Chinese medicine in the treatment of lung cancer.
章新友,李秀云,张亚明,等. 基于数据挖掘、网络药理学和分子对接方法的肺癌用药规律及核心中药分析[J]. 科学技术与工程, , ():复制