基于数据挖掘和网络药理学的中药治疗胃癌前病变的分子生物学机制研究。

Study on molecular biological mechanism of Chinese herbal medicines for the treatment of gastric precancerous lesions based on data mining and network pharmacology.

机构信息

1. Graduate School, Beijing University of Traditional Chinese Medicine, Beijing 100029, China.

2. Department of Spleen and Stomach Diseases, Xiyuan Hospital of China Academy of Chinese Medical Sciences, Beijing 100091, China.

出版信息

Zhejiang Da Xue Xue Bao Yi Xue Ban. 2022 Nov 25;51(5):573-584. doi: 10.3724/zdxbyxb-2022-0278.

Abstract

OBJECTIVE

To explore the molecular biological mechanisms of Chinese herbal medicines for the treatment of gastric precancerous lesions by data mining and network pharmacology.

METHODS

The keywords "gastric precancerous lesions""gastric precancerous disease""gastric mucosal intraepithelial neoplasia""gastric mucosal heterogeneous hyperplasia""gastric precancerous state""chronic gastritis, atrophic""combined Chinese and Western medicine""Chinese medicine therapy""efficacy evaluation" "randomized controlled trial"were searched in China Journal Full-text Database, Wanfang Data, VIP database, PubMed and Embase from 2001 to 2021. The information was extracted from the literature which met the inclusion and exclusion criteria, and the database was constructed to identify the high-frequency herbal medicines. The top six Chinese herbal medicines were analyzed by the network pharmacology methods, including the acquisition of herbs compounds and gastric precancerous lesions targets using Pharmacology Database and Analysis Platform and GeneCards databases, construction of protein-protein interaction network, and screening of core targets, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of core targets through Metascape platform, etc., to elucidate their active components, targets and pathways.

RESULTS

A total of 482 compound prescriptions with 603 herbal medicines were included, and the top 6 herbal medicines with higher application frequency were (63.35%), (58.54%), (54.06%), (49.92%), (46.43%), and (45.44%). The results of the network pharmacological analysis showed that the active ingredients were 4 types from , 3 from , 9 from , 13 from , 7 from , and 9 from ; 77 predicted targets were in , 11 in , 33 in , 58 in , 65 in and 89 in ; and 98 crossover genes were obtained after these targets were compared with the disease genes, among which HSP90AA1, AKT1, TP53, STAT3, MAPK1 and TNF had higher relevance to the treatment of gastric precancerous lesions. The results of the GO enrichment analysis showed that the active ingredients of high frequency Chinese medicine mostly acted through biological processes such as response to inorganic substance, response to hormone, gland development, positive regulation of cell migration, positive regulation of cell motility, etc. The targets include cellular components such as vesicle lumen, secretory granule lumen, cytoplasmic vesicle lumen, transcription regulator complex, and with molecular functions such as kinase binding, protein kinase binding and DNA-binding transcription factor binding. The results of the KEGG pathway enrichment analysis showed that , , and mainly act through the cancer pathway and PI3K-AKT pathway; and mainly act through the cancer pathway and proteoglycans in cancer, and all six herbs were involved in the cancer pathway and five herbs are involved in the PI3K-AKT pathway.

CONCLUSION

In this study, we obtained the top 6 high-frequency Chinese herbal medicines in the treatment of gastric precancerous lesions by data mining method, and revealed that their mechanisms are involved in cell proliferation, differentiation, immunity, inflammation and other processes mainly through cancer pathway, PI3K-AKT signaling pathway, proteoglycans in cancer.

摘要

目的

通过数据挖掘和网络药理学探讨中药治疗胃癌前病变的分子生物学机制。

方法

在中国期刊全文数据库、万方数据、维普数据库、PubMed 和 Embase 中检索 2001 年至 2021 年的“胃前病变”“胃前疾病”“胃黏膜上皮内瘤变”“胃黏膜异型增生”“胃前状态”“萎缩性胃炎,慢性”“中西医结合”“中药疗法”“疗效评价”“随机对照试验”的关键词。从符合纳入和排除标准的文献中提取信息,构建数据库以识别高频草药。使用药理学数据库和分析平台以及基因卡片数据库,对前六种中草药进行网络药理学分析,包括获取草药化合物和胃癌前病变靶点、构建蛋白质-蛋白质相互作用网络、筛选核心靶点、通过 Metascape 平台进行基因本体(GO)和京都基因与基因组百科全书(KEGG)富集分析等,以阐明其活性成分、靶点和途径。

结果

共纳入 482 个复方处方,涉及 603 种草药,应用频率较高的前 6 种草药分别为(63.35%)、(58.54%)、(54.06%)、(49.92%)、(46.43%)和(45.44%)。网络药理学分析结果表明,活性成分有 4 种来自 ,3 种来自 ,9 种来自 ,13 种来自 ,7 种来自 ,9 种来自 ;预测靶点有 77 个在 ,11 个在 ,33 个在 ,58 个在 ,65 个在 ,89 个在 ;将这些靶点与疾病基因进行比较后,获得了 98 个交叉基因,其中 HSP90AA1、AKT1、TP53、STAT3、MAPK1 和 TNF 与胃癌前病变的治疗相关性较高。GO 富集分析结果表明,高频中药的活性成分主要通过无机物质反应、激素反应、腺体发育、细胞迁移的正调节、细胞运动的正调节等生物学过程发挥作用。靶点包括囊泡腔、分泌颗粒腔、细胞质囊泡腔、转录调节复合物等细胞成分,以及具有激酶结合、蛋白激酶结合和 DNA 结合转录因子结合等分子功能。KEGG 通路富集分析结果表明, 、 、 和 主要通过癌症途径和 PI3K-AKT 通路发挥作用; 和 主要通过癌症途径和癌症中的蛋白聚糖发挥作用,这 6 种草药都参与了癌症途径,5 种草药都参与了 PI3K-AKT 通路。

结论

本研究通过数据挖掘方法获得了治疗胃癌前病变的前 6 种高频中药,并揭示其机制主要通过癌症途径、PI3K-AKT 信号通路、癌症中的蛋白聚糖参与细胞增殖、分化、免疫、炎症等过程。

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