PDF(Sci-hub)
Abstract：
OBJECTIVE: Colon cancer is occurring at an increasing rate and ginger (Zingiber officinale), as a commonly used herbal medicine, has been suggested as a potential agent for colon cancer. This study was aimed to identify the bioactive components and potential mechanisms of ginger for colon cancer prevention by an integrated network pharmacology approach.
METHODS: The putative ingredients of ginger and its related targets were discerned from the TCMSP and Swiss target prediction database. After that, the targets interacting with colon cancer were collected using Genecards, OMIM, and Drugbank databases. KEGG pathway and GO enrichment analysis were performed to explore the signaling pathways related to ginger for colon cancer treatments. The PPI and compound-target-disease networks were constructed using Cytoscape 3.8.1. Finally, Discovery studio software was employed to confirm the key genes and active components from ginger.
RESULTS: Six potential active compounds, 285 interacting targets in addition to 1356 disease-related targets were collected, of which 118 intersection targets were obtained. A total of 34 key targets including PIK3CA, SRC, and TP53 were identified through PPI network analysis. These targets were mainly focused on the biological processes of phosphatidylinositol 3-kinase signaling, cellular response to oxidative stress, and cellular response to peptide hormone stimulus. The KEGG enrichment manifested that three signaling pathways were closely related to colon cancer prevention of ginger, cancer, endocrine resistance, and hepatitis B pathways. TP53, HSP90AA1, and JAK2 were viewed as the most important genes, which were validated by molecular docking simulation.
CONCLUSIONS: This study demonstrated that ginger produced preventive effects against colon cancer by regulating multi-targets and multi-pathways with multi-components. And, the combined data provide novel insight for ginger compounds developed as new drug for anti-colon cancer.
METHODS: The putative ingredients of ginger and its related targets were discerned from the TCMSP and Swiss target prediction database. After that, the targets interacting with colon cancer were collected using Genecards, OMIM, and Drugbank databases. KEGG pathway and GO enrichment analysis were performed to explore the signaling pathways related to ginger for colon cancer treatments. The PPI and compound-target-disease networks were constructed using Cytoscape 3.8.1. Finally, Discovery studio software was employed to confirm the key genes and active components from ginger.
RESULTS: Six potential active compounds, 285 interacting targets in addition to 1356 disease-related targets were collected, of which 118 intersection targets were obtained. A total of 34 key targets including PIK3CA, SRC, and TP53 were identified through PPI network analysis. These targets were mainly focused on the biological processes of phosphatidylinositol 3-kinase signaling, cellular response to oxidative stress, and cellular response to peptide hormone stimulus. The KEGG enrichment manifested that three signaling pathways were closely related to colon cancer prevention of ginger, cancer, endocrine resistance, and hepatitis B pathways. TP53, HSP90AA1, and JAK2 were viewed as the most important genes, which were validated by molecular docking simulation.
CONCLUSIONS: This study demonstrated that ginger produced preventive effects against colon cancer by regulating multi-targets and multi-pathways with multi-components. And, the combined data provide novel insight for ginger compounds developed as new drug for anti-colon cancer.
摘要：
目的：结肠癌的发病率在上升，生姜（生姜），作为一种常用的草药，已被认为是结肠癌的潜在药物。本研究旨在通过综合网络药理学方法确定生姜预防结肠癌的生物活性成分和潜在机制。
方法：从TCMSP和瑞士目标预测数据库中识别了姜的推定成分及其相关目标。之后,使用基因卡收集与结肠癌相互作用的靶标，OMIM,和Drugbank数据库。进行KEGG通路和GO富集分析以探索与生姜相关的信号通路用于结肠癌治疗。使用Cytoscape3.8.1构建PPI和复合靶疾病网络。最后,使用Discoverystudio软件来确认生姜的关键基因和活性成分。
结果：六种潜在的活性化合物，除了1356个疾病相关靶标外，还收集了285个相互作用的靶标，其中获得了118个相交目标。共有34个关键目标，包括PIK3CA，SRC,通过PPI网络分析确定TP53。这些靶点主要集中在磷脂酰肌醇3-激酶信号的生物学过程，细胞对氧化应激的反应，和细胞对肽激素刺激的反应。KEGG富集表明,三种信号通路与生姜预防结肠癌密切相关,癌症,内分泌抵抗，和乙型肝炎途径。TP53，HSP90AA1和JAK2被认为是最重要的基因，通过分子对接模拟进行了验证。
结论：这项研究表明，生姜通过调节多靶点和多途径的多组分产生预防结肠癌的作用。And,这些综合数据为生姜化合物作为抗结肠癌新药的开发提供了新的见解。
方法：从TCMSP和瑞士目标预测数据库中识别了姜的推定成分及其相关目标。之后,使用基因卡收集与结肠癌相互作用的靶标，OMIM,和Drugbank数据库。进行KEGG通路和GO富集分析以探索与生姜相关的信号通路用于结肠癌治疗。使用Cytoscape3.8.1构建PPI和复合靶疾病网络。最后,使用Discoverystudio软件来确认生姜的关键基因和活性成分。
结果：六种潜在的活性化合物，除了1356个疾病相关靶标外，还收集了285个相互作用的靶标，其中获得了118个相交目标。共有34个关键目标，包括PIK3CA，SRC,通过PPI网络分析确定TP53。这些靶点主要集中在磷脂酰肌醇3-激酶信号的生物学过程，细胞对氧化应激的反应，和细胞对肽激素刺激的反应。KEGG富集表明,三种信号通路与生姜预防结肠癌密切相关,癌症,内分泌抵抗，和乙型肝炎途径。TP53，HSP90AA1和JAK2被认为是最重要的基因，通过分子对接模拟进行了验证。
结论：这项研究表明，生姜通过调节多靶点和多途径的多组分产生预防结肠癌的作用。And,这些综合数据为生姜化合物作为抗结肠癌新药的开发提供了新的见解。
