Suppr超能文献

网络分析探索参麦注射液治疗粒细胞减少症的药理学机制及循证医学方法验证。

Network analysis to explore the pharmacological mechanism of Shenmai injection in treating granulocytopenia and evidence-based medicine approach validation.

机构信息

Department of Oncology, Fenghua Hospital of Traditional Chinese Medicine, Ningbo, China.

Department of Rehabilitation, Fenghua Hospital of Traditional Chinese Medicine, Ningbo, China.

出版信息

Medicine (Baltimore). 2023 May 19;102(20):e33825. doi: 10.1097/MD.0000000000033825.

Abstract

BACKGROUND

Shenmai injection is frequently utilized in China to clinically treat granulocytopenia in oncology patients following chemotherapy. Despite this, the drug's therapeutic benefits remain a topic of contention, and its active components and potential treatment targets have yet to be established. The present study utilizes a network pharmacology approach to investigate the drug's active ingredients and possible therapeutic targets, and to evaluate the effectiveness of Shenmai injection in treating granulocytopenia through meta-analysis.

METHODS

In our subject paper, we utilized the TCMID database to investigate the active ingredients present in red ginseng and ophiopogon japonicus. To further identify molecular targets, we employed SuperPred, as well as OMIM, Genecards, and DisGeNET databases. Our focus was on targets associated with granulocytopenia. The DAVID 6.8 database was utilized to perform gene ontology functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. Additionally, a protein-protein interaction network was established. The resulting "drug-key component-potential target-core pathway" network was used to predict the mechanism of action of Shenmai injection in the treatment of granulocytopenia. In order to evaluate the quality of the studies included in our analysis, we utilized the Cochrane Reviewers' Handbook. We then conducted a meta-analysis of the clinical curative effect of Shenmai injection for granulocytopenia, utilizing the Cochrane Collaboration's RevMan 5.3 software.

RESULTS

After conducting a thorough screening, the study identified 5 primary ingredients of Shenmai injection - ophiopogonoside a, β-patchoulene, ginsenoside rf, ginsenoside re, and ginsenoside rg1-that can potentially target 5 essential proteins: STAT3, TLR4, PIK3CA, PIK3R1, and GRB2. Additionally, Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that Shenmai injection can be beneficial in treating granulocytopenia by interacting with pathways such as HIF-1 signaling, T-cell receptor signaling, PI3K-Akt signaling, chemokine signaling, and FoxO signaling. The results of meta-analysis indicate that the treatment group exhibited superior performance in terms of both efficiency and post-treatment leukocyte count when compared to the control group.

CONCLUSION

In summary, studies in network pharmacology demonstrate that Shenmai injection exerts an impact on granulocytopenia via various components, targets, and mechanisms. Additionally, evidence-based studies provide strong support for the effectiveness of Shenmai injection in preventing and treating granulocytopenia.

摘要

背景

参麦注射液在中国常用于肿瘤化疗后粒细胞减少症的临床治疗。然而,该药物的治疗效果仍存在争议,其活性成分和潜在的治疗靶点尚未确定。本研究采用网络药理学方法探讨药物的活性成分和可能的治疗靶点,并通过荟萃分析评价参麦注射液治疗粒细胞减少症的疗效。

方法

在我们的研究中,我们利用中药系统药理学数据库与分析平台(TCMSP)数据库筛选红参和麦冬中的活性成分。进一步通过 SuperPred、OMIM、Genecards 和 DisGeNET 数据库预测其作用靶点。我们关注与粒细胞减少症相关的靶点。利用 DAVID 6.8 数据库进行基因本体(GO)功能富集分析和京都基因与基因组百科全书(KEGG)通路富集分析。同时构建蛋白质-蛋白质相互作用(PPI)网络。构建“药物-关键成分-潜在靶点-核心通路”网络图,预测参麦注射液治疗粒细胞减少症的作用机制。为了评估分析中纳入研究的质量,我们使用了 Cochrane 评价员手册。然后我们使用 Cochrane 协作网的 RevMan 5.3 软件进行参麦注射液治疗粒细胞减少症的临床疗效的荟萃分析。

结果

经过全面筛选,本研究确定了参麦注射液的 5 种主要成分-麦冬皂苷 A、β-石竹烯、人参皂苷 Rf、人参皂苷 Re 和人参皂苷 Rg1-它们可能作用于 5 种关键蛋白:STAT3、TLR4、PIK3CA、PIK3R1 和 GRB2。此外,KEGG 通路分析表明,参麦注射液通过与 HIF-1 信号通路、T 细胞受体信号通路、PI3K-Akt 信号通路、趋化因子信号通路和 FoxO 信号通路等相互作用,对粒细胞减少症具有治疗作用。荟萃分析结果表明,与对照组相比,治疗组在疗效和治疗后白细胞计数方面均表现出优势。

结论

综上所述,网络药理学研究表明,参麦注射液通过多种成分、靶点和机制对粒细胞减少症产生影响。此外,基于证据的研究为参麦注射液预防和治疗粒细胞减少症的有效性提供了有力支持。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a3b2/10194581/2887542894b6/medi-102-e33825-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验