论著
ENGLISH ABSTRACT
西黄丸治疗胃癌作用机制的网络药理学和机器学习探讨
王励之
陈泓西
朱康莲
作者及单位信息
·
DOI: 10.3760/cma.j.issn.1007-1245.2024.23.012
Exploring mechanism of Xihuang pills in treatment of gastric cancer based on network pharmacology and machine learning
Wang Lizhi
Chen Hongxi
Zhu Kanglian
Authors Info & Affiliations
Wang Lizhi
Department of Gastrointestinal Surgery, Hunan Provincial People's Hospital, First Hospital, Hunan Normal University, Changsha410005, China
Chen Hongxi
Department of Gastrointestinal Surgery, Hunan Provincial People's Hospital, First Hospital, Hunan Normal University, Changsha410005, China
Zhu Kanglian
First Department of Ophthalmology and Stomatology, Hunan Provincial People's Hospital, First Hospital, Hunan Normal University, Changsha410005, China
·
DOI: 10.3760/cma.j.issn.1007-1245.2024.23.012
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摘要

目的通过网络药理学和机器学习探讨西黄丸治疗胃癌的作用机制。

方法所有数据采集和分析于2023年11月至2024年8月期间进行,研究的各阶段包括数据收集、基因靶点预测、网络模型构建及数据统计分析。利用中药系统药理学数据库(TCMSP)查询并提取西黄丸的化学成分数据,利用Swiss Target Prediction和HERB数据库预测活性成分靶点。使用Genecard收集疾病相关靶点,并筛选差异靶点。通过机器学习算法中的支持向量机进一步筛选疾病靶点基因。西黄丸治疗胃癌的潜在作用靶点是疾病靶点与活性成分靶点的交集。利用ClusterProfiler包进行潜在靶点的基因本体(GO)功能富集分析及京都基因与基因组百科全书(KEGG)通路富集分析。将活性成分与潜在作用靶点导入Cytoscape 3.10.0软件,构建“药物-活性成分-靶点”网络。拓扑分析获取西黄丸治疗胃癌的核心成分。利用LASSO回归筛选西黄丸治疗胃癌的核心靶点,Cibersort算法对核心靶点进行免疫浸润分析。数据通过R 4.2.1软件进行处理,采用 t检验和单因素方差分析进行统计学检验。

结果共选出有效活性成分41个,相关靶点182个,胃癌相关基因2 410个,交集基因119个。通过GO富集分析,共识别出2 049个GO条目( P<0.05);而信号通路富集分析则揭示了177条KEGG信号通路( P<0.05)。“药物-活性成分-靶点”网络分析发现,槲皮素是西黄丸治疗胃癌的核心成分。LASSO回归筛选出CD36、GJA1、SERPINE1基因可能是西黄丸治疗胃癌的核心作用靶点。数据分析结果显示,相较于正常样本,胃癌患者中GJA1和SERPINE1基因展现出较高的表达水平(均 P<0.01),而CD36呈现低表达趋势( P<0.001),且均具有良好的诊断效能。预后分析结果表明,胃癌患者预后状况与核心靶点的表达水平呈负相关,即核心靶点表达水平越高,预后越不良。免疫浸润分析结果表明,胃癌的发生发展与多种免疫细胞失调相关,核心靶点CD36、GJA1、SERPINE1可通过调控多种免疫细胞浸润缓解胃癌进程。

结论西黄丸可通过抗炎、调节免疫细胞功能等多方面发挥对胃癌的治疗作用。

西黄丸;胃癌;机器学习;网络药理学;免疫浸润
ABSTRACT

ObjectiveTo explore the potential mechanism of Xihuang pills in the treatment of gastric cancer (GC) based on network pharmacology and machine learning.

MethodsAll the data collection and analysis were conducted between November 2023 and August 2024. The study involved various stages, including data collection, gene target prediction, network model construction, and statistical analysis. The chemical composition data of Xihuang pills were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). The active ingredient targets were predicted using the Swiss Target Prediction and HERB databases. The disease-related targets were collected from GeneCard, and differential targets were filtered. The disease target genes were further filtered using the support vector machine (SVM) machine learning algorithm. The potential targets of Xihuang pills for gastric cancer were identified as the intersection of disease targets and active ingredient targets. Gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the potential targets were performed using the clusterProfiler package. The active ingredients and potential targets were imported into the Cytoscape 3.10.0 software to construct a "drug-active ingredient-target" network. The topological analysis was performed to identify the core components of Xihuang pills in the treatment of gastric cancer. The LASSO regression was used to screen the core targets of Xihuang pills for gastric cancer. The Cibersort algorithm was employed for immune infiltration analysis of the core targets. The data were processed using the R 4.2.1 software, and statistical tests were conducted using t test and one-way analysis of variance.

ResultsA total of 41 active ingredients and 182 related targets were identified, with 2 410 gastric cancer-related genes and 119 intersecting genes. The GO enrichment analysis identified 2 049 GO terms ( P<0.05); the KEGG pathway enrichment analysis revealed 177 KEGG signaling pathways ( P<0.05). The network analysis of the "drug-active ingredient-target" revealed that quercetin might be a potential core component of Xihuang pills for gastric cancer. The LASSO regression identified CD36, GJA1, and SERPINE1 as potential core targets for Xihuang pills in the treatment of gastric cancer. The data analysis revealed that compared to normal samples, GJA1 and SERPINE1 genes were highly expressed in patients with gastric cancer (both P<0.01), while CD36 showed a trend of low expression ( P<0.001); all the three had good diagnostic efficacy. The prognostic analysis indicated that higher expression levels of core targets were negatively correlated with patients' prognosis, meaning that the higher the expression levels of the core targets, the worse the prognosis. The immune infiltration analysis suggested that the development of gastric cancer is associated with the dysregulation of multiple immune cells. The core targets, CD36, GJA1, and SERPINE1, may alleviate the progression of gastric cancer regulating the infiltration of various immune cells.

ConclusionXihuang Pills may exert therapeutic effects on gastric cancer through anti-inflammatory mechanisms and by regulating immune cell functions.

Xihuang pills;Gastric cancer;Machine learning;Network pharmacology;Immune infiltration
Zhu Kanglian, Email: mocdef.qabq071391062
引用本文

王励之,陈泓西,朱康莲. 西黄丸治疗胃癌作用机制的网络药理学和机器学习探讨[J]. 国际医药卫生导报,2024,30(23):3937-3946.

DOI:10.3760/cma.j.issn.1007-1245.2024.23.012

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胃癌作为消化系统中最常见的恶性肿瘤,其发病率和病死率在全球范围内分别位列第五和第四,给社会带来了严重危害 1 , 2。胃癌治疗主要依赖于化疗和放疗,然而肿瘤细胞的耐药性及化疗的毒副作用会对治疗效果产生显著影响,降低患者生活质量 3。中医药在肿瘤防治领域拥有悠久历史,随着中药治疗肿瘤研究的不断深入,已发现将中药与西医治疗相结合在肿瘤防治方面能够发挥积极效果,尤其在提升患者免疫功能、增强体质耐受力、减轻化疗不良反应及提高疗效等方面 4 , 5。此外,相较于西医治疗,中医治疗费用更为经济,有助于减轻医疗负担,改善患者生活质量。在癌症治疗中,调气解毒法具有重要临床价值,尤其在胃癌患者常见的气滞血瘀和癌毒积聚现象中表现突出。根据中医学理论,气机不畅会导致血液循环障碍,而气滞血瘀状态会加重肿瘤进展。因此,临床上常采用调和气血、解毒散结治疗策略,改善患者全身气血运行和毒素代谢。西黄丸是这一疗法的经典方剂,其组方来源于《外科证治全生集》,主要包括牛黄、麝香、乳香、没药四味中药,各药物成分在方剂中发挥特定作用。麝香具有活血化瘀效果,有助于改善局部微循环;牛黄具备清热解毒作用,可缓解炎症和毒性反应;乳香和没药则具有活血行气、消肿止痛功能。西黄丸通过其综合作用,能够有效调节癌症患者气血运行,改善瘀血积聚和癌毒内蕴状况,对肿瘤进展及患者症状有一定缓解作用。郭秋均 6研究表明,西黄丸能够通过调节乏氧微环境来抑制胃癌细胞生长和转移。
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备注信息
A
朱康莲,Email: mocdef.qabq071391062
B

王励之、陈泓西:研究构思和设计,文章撰写,对文章的知识性内容作批评性审阅;朱康莲:研究构思和设计,课题设计和指导,对文章的知识性内容作批评性审阅

C
王励之, 陈泓西, 朱康莲. 西黄丸治疗胃癌作用机制的网络药理学和机器学习探讨[J]. 国际医药卫生导报, 2024, 30(23): 3937-3946. DOI: 10.3760/cma.j.issn.1007-1245.2024.23.012.
D
所有作者均声明不存在利益冲突
E
湖南省卫健委科研项目 (B20230401652)
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