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

利用网络药理学探索五味丸治疗胰腺肿瘤的潜在机制

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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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