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      Research on the Potential Mechanism of Gentiopicroside Against Gastric Cancer Based on Network Pharmacology

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          Abstract

          Background

          Gastric cancer was still one of the commonly diagnosed cancer types and the third-most common cause of cancer-related death in the world. Gentiopicroside, which is extracted from the Gentianella acuta, is commonly used in both traditional treatment and modern clinical care; therefore, its anticancer effects have been attracted more attention. However, the systematic analysis of action mechanism of Gentiopicroside on gastric cancer (GC) has not yet been carried out.

          Aim

          A network pharmacology-based strategy combined with molecular docking studies and in vitro validation was employed to investigate potential targets and molecular mechanism of Gentiopicroside against GC.

          Materials and Methods

          Potential targets of Gentiopicroside, as well as related genes of GC, were acquired from public databases. Potential targets, and signaling pathways were determined through bioinformatic analysis, including protein–protein interaction (PPI), the Gene Ontology (GO), and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Subsequently, molecular docking and cell experiments were performed to further verify the above findings.

          Results

          Our findings revealed that the anticancer activity of Gentiopicroside potentially involves 53 putative identified target genes. In addition, GO, KEGG, and network analyses revealed that these targets were associated with cell proliferation, metabolic process, and other physiological processes. Furthermore, we have proved that critical compound affected the expression of CCND1, CCNE1, p-AKT and p-P38 at protein levels. These findings provide an overview of the anticancer action of Gentiopicroside from a network perspective; meanwhile, it might also set an example for future studies of other materials used in traditional Chinese medicine (TCM).

          Conclusion

          This study comprehensively illuminated the potential targets and molecular mechanism of Gentiopicroside against GC. It also provided a promising approach to uncover the scientific basis and therapeutic mechanism of TCM treating for disease.

          Most cited references33

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          Global Cancer Statistics 2018: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries

          This article provides a status report on the global burden of cancer worldwide using the GLOBOCAN 2018 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer, with a focus on geographic variability across 20 world regions. There will be an estimated 18.1 million new cancer cases (17.0 million excluding nonmelanoma skin cancer) and 9.6 million cancer deaths (9.5 million excluding nonmelanoma skin cancer) in 2018. In both sexes combined, lung cancer is the most commonly diagnosed cancer (11.6% of the total cases) and the leading cause of cancer death (18.4% of the total cancer deaths), closely followed by female breast cancer (11.6%), prostate cancer (7.1%), and colorectal cancer (6.1%) for incidence and colorectal cancer (9.2%), stomach cancer (8.2%), and liver cancer (8.2%) for mortality. Lung cancer is the most frequent cancer and the leading cause of cancer death among males, followed by prostate and colorectal cancer (for incidence) and liver and stomach cancer (for mortality). Among females, breast cancer is the most commonly diagnosed cancer and the leading cause of cancer death, followed by colorectal and lung cancer (for incidence), and vice versa (for mortality); cervical cancer ranks fourth for both incidence and mortality. The most frequently diagnosed cancer and the leading cause of cancer death, however, substantially vary across countries and within each country depending on the degree of economic development and associated social and life style factors. It is noteworthy that high-quality cancer registry data, the basis for planning and implementing evidence-based cancer control programs, are not available in most low- and middle-income countries. The Global Initiative for Cancer Registry Development is an international partnership that supports better estimation, as well as the collection and use of local data, to prioritize and evaluate national cancer control efforts. CA: A Cancer Journal for Clinicians 2018;0:1-31. © 2018 American Cancer Society.
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            Cytoscape: a software environment for integrated models of biomolecular interaction networks.

            Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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              AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading.

              AutoDock Vina, a new program for molecular docking and virtual screening, is presented. AutoDock Vina achieves an approximately two orders of magnitude speed-up compared with the molecular docking software previously developed in our lab (AutoDock 4), while also significantly improving the accuracy of the binding mode predictions, judging by our tests on the training set used in AutoDock 4 development. Further speed-up is achieved from parallelism, by using multithreading on multicore machines. AutoDock Vina automatically calculates the grid maps and clusters the results in a way transparent to the user. Copyright 2009 Wiley Periodicals, Inc.
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                Author and article information

                Journal
                Drug Des Devel Ther
                Drug Des Devel Ther
                dddt
                dddt
                Drug Design, Development and Therapy
                Dove
                1177-8881
                23 November 2020
                2020
                : 14
                : 5109-5118
                Affiliations
                [1 ]Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University , Guangzhou, People's Republic of China
                [2 ]Department of Traditional Chinese Medicine, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University , Guangzhou, People’s Republic of China
                [3 ]Department of Thoracic Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University , Guangzhou, People's Republic of China
                [4 ]Department of Hepatobiliary Surgery, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University , Guangzhou, People’s Republic of China
                [5 ]Sun Yat-Sen University Zhongshan School of Medicine , Guangzhou, People’s Republic of China
                Author notes
                Correspondence: Jie WangDepartment of Hepatobiliary Surgery, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University , Yanjiang West Road 107#, Guangzhou510120, People’s Republic of China Email jiewsysu@163.com
                Qihui HuangDepartment of Traditional Chinese Medicine, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University , Yanjiang West Road 107#, Guangzhou510120, People’s Republic of China Email hqhui84181833@sina.com
                [*]

                These authors contributed equally to this work

                Author information
                http://orcid.org/0000-0003-0778-0057
                http://orcid.org/0000-0003-1215-2733
                Article
                270757
                10.2147/DDDT.S270757
                7700081
                33262572
                8fb19aab-e243-43b2-a62e-1c29836507f7
                © 2020 Huang et al.

                This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms ( https://www.dovepress.com/terms.php).

                History
                : 04 July 2020
                : 24 September 2020
                Page count
                Figures: 9, References: 33, Pages: 10
                Categories
                Original Research

                Pharmacology & Pharmaceutical medicine
                gentiopicroside,gastric cancer,mechanism,network pharmacology,molecular docking

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