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BMC Complementary Medicine and Therapies
Published in: BMC Complementary Medicine and Therapies 1/2019

Open Access 01-12-2019 | Active Ingredients | Research article

Utilising network pharmacology to explore the underlying mechanism of Wumei Pill in treating pancreatic neoplasms

Authors: Yuxiang Wan, Lin Xu, Zeyu Liu, Ming Yang, Xin Jiang, Qiaoli Zhang, Jinchang Huang

Published in: BMC Complementary Medicine and Therapies | Issue 1/2019

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Abstract

Background

Wumei Pill (WMP), a famous herbal formula, has been widely used to treat digestive system diseases in clinical practice in China for centuries. We have found a correlation between the indications of WMP and the typical symptoms of pancreatic neoplasms. However, the pharmacological mechanisms of WMP still remain unknown.

Methods

In the present work, we used a network pharmacological method to predict its underlying complex mechanism of treating pancreatic neoplasms. Firstly, we obtained relative compounds of WMP based on TCMSP database, TCM database@Taiwan and TCMID database and collected potential targets of these compounds by target fishing. Then we built the pancreatic neoplasms target database by CTD, TTD, PharmGKB. Based on the matching results between WMP potential targets and pancreatic neoplasms targets, we built a PPI network to analyze the interactions among these targets and screen the hub targets by topology. Furthermore, DAVID bioinformatics resources were utilized for the enrichment analysis on GO_BP and KEGG.

Results

A total of 80 active ingredients and 77 targets of WMP were picked out. The results of DAVID enrichment analysis indicated that 58 cellular biological processes (FDR < 0.01) and 17 pathways (FDR < 0.01) of WMP mostly participated in the complex treating effects associated with proliferation, apoptosis, inflammatory response and angiogenesis. Moreover, 17 hub nodes of WMP (PTGS2, BCL2, TP53, IL6, MAPK1, EGFR, EGF, CASP3, JUN, MAPK8, MMP9, VEGFA, TNF, MYC, AKT1, FOS and TGFB1) were recognized as potential targets of treatments, implying the underlying mechanisms of WMP acting on pancreatic neoplasms.

Conclusion

WMP could alleviate the symptoms of pancreatic neoplasms through the molecular mechanisms predicted by network pharmacology. This study proposes a strategy to elucidate the mechanisms of Traditional Chinese Medicine (TCM) at the level of network pharmacology.
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Literature
1.
2.
Rahib L, Smith BD, Aizenberg R, et al. Projecting cancer incidence and deaths to 2030: the unexpected burden of thyroid, liver, and pancreas cancers in the United States. Cancer Res. 2014;74(14):2913–21.PubMedCrossRef
3.
Smith RA, Brooks D, Cokkinides V, et al. Cancer screening in the United States, 2013: a review of current American Cancer Society guidelines, current issues in cancer screening, and new guidance on cervical cancer screening and lung cancer screening. CA Cancer J Clin. 2013;63(2):88–105.PubMedCrossRef
4.
Sonja G, Tibor S, Christian MZB, et al. Preoperative/neoadjuvant therapy in pancreatic Cancer: a systematic review and meta-analysis of response and resection percentages. PLoS Med. 2010;7(4):e1000267.CrossRef
5.
Bailey P, Chang DK, Nones K, et al. Genomic analyses identify molecular subtypes of pancreatic cancer. Nature. 2016;531(7592):47–52.PubMedCrossRef
6.
Liang C, Qin Y, Zhang B, et al. Energy sources identify metabolic phenotypes in pancreatic cancer. Acta Biochim Biophys Sin. 2016;48(11):969–79.PubMedCrossRef
7.
Guohua Y, Wubin W, Xu W, et al. Network pharmacology-based strategy to investigate pharmacological mechanisms of Zuojinwan for treatment of gastritis. BMC Complement Altern Med. 2018;18:292.CrossRef
8.
Li M, Wang MM, Guo XW, et al. Different survival benefits of Chinese medicine for pancreatic cancer: how to choose? Chin J Integr Med. 2018;24(4):178–84.PubMedCrossRef
9.
Kuo YT, Liao HH, Chiang JH, et al. Complementary Chinese herbal medicine therapy improves survival of patients with pancreatic Cancer in Taiwan: a Nationwide population-based cohort study. Integr Cancer Ther. 2018;17(2):411–22.PubMedCrossRef
10.
Mei T, Wang X, Wang A, et al. Effect of Jiaweiwumei decoction on regulatory T cells and interleukin-10 in a rat model of ulcerative colitis. J Tradit Chin Med. 2015;35(3):312–5.CrossRef
11.
Ma NX, Sun W, Liu SL, et al. Compound Wumei powder inhibits the invasion and metastasis of gastric Cancer via Cox-2/PGE2-PI3K/AKT/GSK3β/β-catenin signaling pathway. Evid Based Complement Alternat Med. 2017;(2017):3039450. https://​doi.​org/​10.​1155/​2017/​3039450.
12.
13.
Jinchang H, Lin X. Clinical observation on 21 cases of pancreatic cancer treated with modified Wumei pills. Chin J Clin. 2012;40(11):52–5.
14.
Hopkins AL. Network pharmacology: the next paradigm in drug discovery. Nat Chem Biol. 2008;4(11):682–90.PubMedCrossRef
15.
Zhang B, Wang X, Li S. An integrative platform of TCM network pharmacology and its application on a herbal formula, Qing-Luo-Yin. Evid Based Complement Alternat Med. 2013;2013:456747.PubMedPubMedCentral
16.
Zhang Y, Bai M, Zhang B, et al. Uncovering pharmacological mechanisms of Wu-tou decoction acting on rheumatoid arthritis through systems approaches: drug-target prediction, network analysis and experimental validation. Sci Rep. 2015;5:9463.PubMedPubMedCentralCrossRef
17.
Li H, Zhao L, Zhang B, et al. A network pharmacology approach to determine active compounds and action mechanisms of ge-gen-qin-lian decoction for treatment of type 2 diabetes. Evid Based Complement Alternat Med. 2014;2014:495840.PubMedPubMedCentral
18.
Ru J, Li P, Wang J, et al. TCMSP: a database of systems pharmacology for drug discovery from herbal medicines. J Cheminf. 2014;6(1):13.CrossRef
19.
20.
Xue R, Fang Z, Zhang M, et al. TCMID: traditional Chinese medicine integrative database for herb molecular mechanism analysis. Nucleic Acids Res. 2013;41(Database issue):D1089–95.PubMed
21.
22.
Willett P, Barnard JM, Downs GM. Chemical similarity searching. J Chem Inf Comput Sci. 1998;38(6):983–96.CrossRef
23.
Tao W, Xu X, Wang X, et al. Network pharmacology-based prediction of the active ingredients and potential targets of Chinese herbal Radix Curcumae formula for application to cardiovascular disease. J Ethnopharmacol. 2013;145(1):1–10.PubMedCrossRef
24.
Pang KS. Modeling of intestinal drug absorption: roles of transporters and metabolic enzymes (for the gillette review series). Drug Metab Dispos. 2003;31(12):1507–19.PubMedCrossRef
25.
Guxiang H, Changhui Z, Wenna Z, et al. QSPR study on the permeability of drugs across Caco-2 monolayer. J Zheijang Univ. 2009;3:304–8.
26.
Keiser MJ, Roth BL, Armbruster BN, et al. Relating protein pharmacology by ligand chemistry. Nat Biotechnol. 2007;25(2):197–206.PubMedCrossRef
27.
Gfeller D, Michielin O, Zoete V. Shaping the interaction landscape of bioactive molecules. Bioinformatics. 2013;29(23):3073.PubMedCrossRef
28.
29.
Grondin CJ, Davis AP, Wiegers TC, et al. Accessing an expanded exposure science module at the comparative Toxicogenomics database. Environ Health Perspect. 2018;126(1):014501.PubMedPubMedCentralCrossRef
30.
Li YH, Yu CY, Li XX, et al. Therapeutic target database update 2018: enriched resource for facilitating bench-to-clinic research of targeted therapeutics. Nucleic Acids Res. 2018;46(D1):D1121–7.PubMed
31.
Whirl-Carrillo M, Mcdonagh EM, Hebert JM, et al. Pharmacogenomics knowledge for personalized medicine. Clin Pharmacol Ther. 2012;92(4):414–7.PubMedCrossRef
32.
Szklarczyk D, Morris JH, Cook H, et al. The STRING database in 2017: quality-controlled protein–protein association networks, made broadly accessible. Nucleic Acids Res. 2017, 45(Database issue):D362–8.PubMedPubMedCentralCrossRef
33.
Shannon P, Markiel A, Ozier O, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13(11):2498–504.PubMedPubMedCentralCrossRef
34.
35.
Raman K, Damaraju N, Joshi GK. The organisational structure of protein networks: revisiting the centrality-lethality hypothesis. Syst Synth Biol. 2014;8(1):73–81.PubMedCrossRef
36.
Tang Y, Li M, Wang J, et al. CytoNCA: a cytoscape plugin for centrality analysis and evaluation of protein interaction networks. Biosystems. 2015;127:67–72.PubMedCrossRef
37.
Huang DW, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 2008;4(1):44.CrossRef
38.
Chen L, Zhang YH, Wang S, et al. Prediction and analysis of essential genes using the enrichments of gene ontology and KEGG pathways. PLoS One. 2017;12(9):e0184129.PubMedPubMedCentralCrossRef
39.
Cao ZQ, Wang XX, Lu L, et al. β-Sitosterol and gemcitabine exhibit synergistic anti-pancreatic Cancer activity by modulating apoptosis and inhibiting epithelial–mesenchymal transition by deactivating Akt/GSK-3β signaling. Front Pharmacol. 2019;9:1525.PubMedPubMedCentralCrossRef
40.
Lee J, Kim JH. Kaempferol inhibits pancreatic Cancer cell growth and migration through the blockade of EGFR-related pathway in vitro. PLoS One. 2016;11(5):e0155264.PubMedPubMedCentralCrossRef
41.
Daisuke Hirayama M, Takahiro Fujimori M, Kazuhiro Satonaka M, et al. Immunohisto-chemical study of epidermal growth factor and transforming growth factor-β in the penetrating type of early gastric cancer. Hum Pathol. 1992;23(6):681–5.CrossRef
42.
Rimawi MF, Shetty PB, Weiss HL, et al. Epidermal growth factor receptor expression in breast cancer association with biologic phenotype and clinical outcomes. Cancer. 2010;116(5):1234–42.PubMedCrossRef
43.
Engelman JA, Ji L, Cantley LC. The evolution of phosphatidylinositol 3-kinases as regulators of growth and metabolism. Nat Rev Genet. 2006;7(8):606–19.PubMedCrossRef
44.
45.
46.
Fesik SW. Promoting apoptosis as a strategy for cancer drug discovery. Nat Rev Cancer. 2005;5(11):876–85.PubMedCrossRef
47.
Zhao A, Zeng Q, Xie X, et al. MicroRNA-125b induces cancer cell apoptosis through suppression of Bcl-2 expression. J Genet Genomics. 2012;39(1):29–35.PubMedCrossRef
48.
Duronio V. The life of a cell: apoptosis regulation by the PI3K/PKB pathway. Biochem J. 2008;415(3):333–44.PubMedCrossRef
49.
Wang W, Zeng C, Feng Y, et al. The size-dependent effects of silica nanoparticles on endothelial cell apoptosis through activating the p53-caspase pathway. Environ Pollut. 2018;233:218–25.PubMedCrossRef
50.
Murthy KNC, Jayaprakasha GK, Patil BS. Apoptosis mediated cytotoxicity of citrus obacunone in human pancreatic cancer cells. Toxicol in Vitro. 2011;25(4):0–867.
51.
Mantovani A, Allavena P, Sica A, et al. Cancer-related inflammation. Nature. 2008;454(7203):436–44.PubMedCrossRef
52.
Sethi G, Sung B, Aggarwal BB. TNF: a master switch for inflammation to cancer. Front Biosci 2008, 13:5094–5107.CrossRef
53.
54.
Granado-Serrano AB, Martín MA, Bravo L, et al. Quercetin modulates NF-κ B and AP-1/JNK pathways to induce cell death in human hepatoma cells. Nutr Cancer. 2010;62(3):390–401.PubMedCrossRef
55.
Sabino MC, Ghilardi JR, Feia KJ, et al. The involvement of prostaglandins in tumorigenesis, tumor-induced osteolysis and bone cancer pain. J Musculoskelet Neuronal Interact. 2002;2(6):561–2.PubMed
56.
Khorana AA, Ahrendt SA, Ryan CK, et al. Tissue factor expression, angiogenesis, and thrombosis in pancreatic Cancer. Clin Cancer Res. 2007;13(10):2870.PubMedCrossRef
57.
Liao D, Johnson RS. Hypoxia: a key regulator of angiogenesis in cancer. Cancer Metastasis Rev. 2007;26(2):281–90.PubMedCrossRef
58.
Kim D, Sung B, Kim JA, et al. HS-1793, a resveratrol analogue, downregulates the expression of hypoxia-induced HIF-1 and VEGF and inhibits tumor growth of human breast cancer cells in a nude mouse xenograft model. Int J Oncol. 2017;51(2):715–23.PubMedCrossRef
Metadata
Title
Utilising network pharmacology to explore the underlying mechanism of Wumei Pill in treating pancreatic neoplasms
Authors
Yuxiang Wan
Lin Xu
Zeyu Liu
Ming Yang
Xin Jiang
Qiaoli Zhang
Jinchang Huang
Publication date
01-12-2019
Publisher
BioMed Central
Published in
BMC Complementary Medicine and Therapies / Issue 1/2019
Electronic ISSN: 2662-7671
DOI
https://doi.org/10.1186/s12906-019-2580-y

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