ArticleChinese medicine2021
A network pharmacology approach to reveal the pharmacological targets and biological mechanism of compound kushen injection for treating pancreatic cancer based on WGCNA and in vitro experiment validation.
Article in Chinese medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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21 citing papers in PubMed, 1 synthesis or guideline pooled it, 38 citations in OpenAlex.
- Evaluation of efficacy and safety for compound kushen injection combined with intraperitoneal chemotherapy for patients with malignant ascites: A systematic review and meta-analysis.Frontiers in pharmacology · 2023Pooled it
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- Application of Network Pharmacology in the Treatment of Neurodegenerative Diseases with Traditional Chinese Medicine.Planta medica · 2025Review
- Jiawei Duhuo Jisheng Mixture Mitigates Osteoarthritis Progression in Rabbits by Inhibiting Inflammation: A Network Pharmacology and Experimental Approach.Combinatorial chemistry & high throughput screening · 2025Article
- PRIM2 promotes proliferation and metastasis of pancreatic ductal adenocarcinoma through interactions with FAM111B.Medical oncology (Northwood, London, England) · 2024Article
- Machine Learning Developed a MYC Expression Feature-Based Signature for Predicting Prognosis and Chemoresistance in Pancreatic Adenocarcinoma.Biochemical genetics · 2024Article
- Application of network pharmacology in synergistic action of Chinese herbal compounds.Theory in biosciences = Theorie in den Biowissenschaften · 2024Review
- Important role and underlying mechanism of non‑SMC condensin I complex subunit G in tumours (Review).Oncology reports · 2024Review
- Weighted gene co-expression network analysis for hub genes in colorectal cancer.Pharmacological reports : PR · 2024Article
- Machine Learning Algorithms Identify Target Genes and the Molecular Mechanism of Matrine against Diffuse Large B-cell Lymphoma.Current computer-aided drug design · 2024Article
- Exploring the mechanism of ellagic acid against gastric cancer based on bioinformatics analysis and network pharmacology.Journal of cellular and molecular medicine · 2023Article
- Chinese herbal injections in combination with radiotherapy for advanced pancreatic cancer: A systematic review and network meta-analysis.Integrative medicine research · 2023Review
- Exploring the therapeutic mechanisms of Gleditsiae Spina acting on pancreatic cancerRSC advances · 2023Article
- Analyzing the research landscape: Mapping frontiers and hot spots in anti-cancer research using bibliometric analysis and research network pharmacology.Frontiers in pharmacology · 2023Article
- Integrative analysis of metabolome, proteome, and transcriptome for identifying genes influencing total lignin content inFrontiers in plant science · 2023Article
- Exploring the molecular mechanism of Sishen Decoction in the treatment of rheumatoid arthritis.Annals of translational medicine · 2022Article
- Tea Ingredients Have Anti-coronavirus Disease 2019 (COVID-19) Targets Based on Bioinformatics Analyses and Pharmacological Effects on LPS-Stimulated Macrophages.Frontiers in nutrition · 2022Article
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Authors and funding
16 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundCompound kushen injection (CKI), a Chinese patent drug, is widely used in the treatment of various cancers, especially neoplasms of the digestive system. However, the underlying mechanism of CKI in pancreatic cancer (PC) treatment has not been totally elucidated.
methodsHere, to overcome the limitation of conventional network pharmacology methods with a weak combination with clinical information, this study proposes a network pharmacology approach of integrated bioinformatics that applies a weighted gene co-expression network analysis (WGCNA) to conventional network pharmacology, and then integrates molecular docking technology and biological experiments to verify the results of this network pharmacology analysis.
resultsThe WGCNA analysis revealed 2 gene modules closely associated with classification, staging and survival status of PC. Further CytoHubba analysis revealed 10 hub genes (NCAPG, BUB1, CDK1, TPX2, DLGAP5, INAVA, MST1R, TMPRSS4, TMEM92 and SFN) associated with the development of PC, and survival analysis found 5 genes (TSPOAP1, ADGRG6, GPR87, FAM111B and MMP28) associated with the prognosis and survival of PC. By integrating these results into the conventional network pharmacology study of CKI treating PC, we found that the mechanism of CKI for PC treatment was related to cell cycle, JAK-STAT, ErbB, PI3K-Akt and mTOR signalling pathways. Finally, we found that CDK1, JAK1, EGFR, MAPK1 and MAPK3 served as core genes regulated by CKI in PC treatment, and were further verified by molecular docking, cell proliferation assay, RT-qPCR and western blot analysis.
conclusionsOverall, this study suggests that the optimized network pharmacology approach is suitable to explore the molecular mechanism of CKI in the treatment of PC, which provides a reference for further investigating biomarkers for diagnosis and prognosis of PC and even the clinical rational application of CKI.
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