Department of Oncology, Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Shanghai University of Traditional Chinese Medicine, Shanghai, China.
PLoS One. 2021 Jun 14;16(6):e0252508. doi: 10.1371/journal.pone.0252508. eCollection 2021.
We aimed to predict the targets and signal pathways of Xiao-Chai-Hu-Tang (XCHT) in the treatment of colorectal cancer (CRC) based on network pharmacology, just as well as to further analyze its anti-CRC material basis and mechanism of action.
We adopted Traditional Chinese Medicine Systems Pharmacology Database (TCMSP) and Traditional Chinese Medicine Integrated Database (TCMID) databases to screen the active ingredients and potential targets of XCHT. CRC-related targets were retrieved by analyzing published microarray data (accession number GSE110224) from the Gene Expression Omnibus (GEO) database. The common targets were used to construct the "herb-active ingredient-target" network using the Cytoscape 3.8.0 software. Next, we constructed and analyzed protein-to-protein interaction (PPI) using BisoGenet and CytoNCA plug-in in Cytoscape. We then performed Gene Ontology (GO) functional and the Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analyses of target genes using the R package of clusterProfiler. Furthermore, we used the AutoDock Tools software to conduct molecular docking studies on the active ingredients and key targets to verify the network pharmacological analysis results.
We identified a total of 71 active XCHT ingredients and 20 potential anti-CRC targets. The network analysis revealed quercetin, stigmasterol, kaempferol, baicalein, and acacetin as potential key compounds, and PTGS2, NR3C2, CA2, and MMP1 as potential key targets. The active ingredients of XCHT interacted with most CRC disease targets. We showed that XCHT's therapeutic effect was attributed to its synergistic action (multi-compound, multi-target, and multi-pathway). Our GO enrichment analysis showed 46 GO entries, including 20 biological processes, 6 cellular components, and 20 molecular functions. We identified 11 KEGG signaling pathways, including the IL-17, TNF, Toll-like receptor, and NF-kappa B signaling pathways. Our results showed that XCHT could play a role in CRC treatment by regulating different signaling pathways. The molecular docking experiment confirmed the correlation between five core compounds (quercetin, stigmasterol, kaempferol, baicalein, and acacetin) just as well as PTGS2, NR3C2, CA2, and MMP1.
In this study, we described the potential active ingredients, possible targets, and key biological pathways responsible for the efficacy of XCHT in CRC treatment, providing a theoretical basis for further research.
我们旨在基于网络药理学预测小柴胡汤（XCHT）治疗结直肠癌（CRC）的靶点和信号通路，同时进一步分析其抗 CRC 的物质基础和作用机制。
我们采用中药系统药理学数据库（TCMSP）和中药整合数据库（TCMID）数据库筛选 XCHT 的活性成分和潜在靶点。通过分析来自基因表达综合数据库（GEO）数据库的已发表微阵列数据（注册号 GSE110224），检索与 CRC 相关的靶点。使用 Cytoscape 3.8.0 软件构建“草药-活性成分-靶标”网络，将共同靶标可视化。接下来，我们使用 BisoGenet 和 CytoNCA 插件在 Cytoscape 中构建和分析蛋白质-蛋白质相互作用（PPI）网络。然后，我们使用 R 包 clusterProfiler 对靶基因进行基因本体（GO）功能和京都基因与基因组百科全书（KEGG）通路富集分析。此外，我们使用 AutoDock Tools 软件对活性成分和关键靶标进行分子对接研究，以验证网络药理学分析结果。
我们共鉴定出 71 种 XCHT 的活性成分和 20 个潜在的抗 CRC 靶点。网络分析表明，槲皮素、豆甾醇、山奈酚、黄芩素和白杨素可能是潜在的关键化合物，PTGS2、NR3C2、CA2 和 MMP1 可能是潜在的关键靶点。XCHT 的活性成分与大多数 CRC 疾病靶点相互作用。我们表明，XCHT 的治疗效果归因于其协同作用（多化合物、多靶点、多途径）。GO 富集分析显示 46 个 GO 条目，包括 20 个生物过程、6 个细胞成分和 20 个分子功能。我们确定了 11 个 KEGG 信号通路，包括 IL-17、TNF、Toll 样受体和 NF-kappa B 信号通路。我们的研究结果表明，XCHT 可以通过调节不同的信号通路在 CRC 治疗中发挥作用。分子对接实验证实了 5 种核心化合物（槲皮素、豆甾醇、山奈酚、黄芩素和白杨素）与 PTGS2、NR3C2、CA2 和 MMP1 之间的相关性。
在这项研究中，我们描述了 XCHT 治疗 CRC 的潜在活性成分、可能的靶点和关键生物学途径，为进一步研究提供了理论基础。
Zotero 插件
