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  • Berberine Targets Kinase-Dense Regulatory Hubs in Pancreatic Ductal Adenocarcinoma: Insights from Network Pharmacology

  • Elina Khanehzar,1 Fatemeh Shams,2 Amir Sajad Jafari,3,*
    1. Student Research Committee, Shiraz University of Medical Sciences, Shiraz, Iran / Medicinal and Natural Products Chemistry Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
    2. Student Research Committee, Shiraz University of Medical Sciences, Shiraz, Iran / Medicinal and Natural Products Chemistry Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
    3. Department of Basic Sciences, School of Veterinary Medicine, Shiraz University, Shiraz, Iran / Medicinal and Natural Products Chemistry Research Center, Shiraz University of Medical Sciences, Shiraz, Iran


  • Introduction: Pancreatic ductal adenocarcinoma (PDAC) is an exceptionally lethal malignancy, with a five-year survival rate of less than 12% despite advances in therapy. Its poor prognosis stems from a combination of late diagnosis, dense desmoplastic stroma, and highly adaptive oncogenic signaling networks that enable rapid drug resistance. Current therapeutic strategies mostly follow a single-target paradigm, which has proven inadequate for a cancer as genetically and phenotypically complex as PDAC. Natural compounds with multi-target activity have drawn growing interest as potential therapeutic leads. Berberine, a plant-derived isoquinoline alkaloid, is known to possess anti-inflammatory and antitumor properties and has shown inhibitory effects in various malignancies. However, its mechanisms of action in PDAC remain poorly understood. Given PDAC’s intricate signaling network, we hypothesized that berberine acts on multiple targets simultaneously. To explore this, we employed a network pharmacology framework to map berberine’s potential molecular targets in PDAC and to identify the key pathways and biological processes they converge upon. Understanding the systems-level mechanism of a compound with broad activity could offer a valuable foundation for developing multi-target strategies against this otherwise treatment-refractory cancer.
  • Methods: Human targets of berberine were predicted using SwissTargetPrediction, and PDAC-associated genes were retrieved from the Open Targets Platform. Overlapping genes were identified using Venny version 2.2.0, which revealed 61 shared targets between the two datasets (from 4940 berberine targets and 101 PDAC genes). These overlapping targets were used to construct a protein–protein interaction (PPI) network in STRING at high confidence (interaction score >0.7) and limited to Homo sapiens. The resulting network, containing 61 nodes, was imported into Cytoscape for topological analysis. Degree centrality, betweenness centrality, and clustering coefficient were calculated, and nodes with high degree values were considered as potential hub proteins. Functional enrichment analysis was performed in STRING across the Gene Ontology (GO) categories of Biological Process (BP), Molecular Function (MF), and Cellular Component (CC). Significance was assessed using false discovery rate (FDR) correction, and FDR <0.05 was considered statistically significant. All analyses were performed with default parameters unless otherwise specified.
  • Results: The PPI network of 61 overlapping genes formed a dense, highly connected cluster. Topological analysis identified SRC, CDC42, CDK4, PTGS2, ABL1, CDK2, KIT, PIK3CB, MAPK14, and CHEK1 among the most connected nodes. GO enrichment showed strong convergence on kinase-related signaling. MF terms were dominated by protein kinase activity (FDR = 1.0 × 10⁻²⁸), protein serine/threonine kinase activity, and ATP binding. BP terms highlighted protein autophosphorylation (FDR = 1.0 × 10⁻²⁶), peptidyl-serine phosphorylation (FDR = 1.0 × 10⁻²²), and positive regulation of intracellular signal transduction. CC terms localized these targets to the phosphatidylinositol 3-kinase complex, protein kinase complexes, and membrane-associated compartments, suggesting that berberine may act by perturbing central phosphorylation-driven signaling nodes in PDAC.
  • Conclusion: This network pharmacology analysis indicates that berberine targets a network of proteins central to kinase-mediated signaling in PDAC. The identification of key hub proteins and their functional convergence on phosphorylation-driven pathways provides a mechanistic rationale for berberine’s anticancer activity. By uncovering a kinase-centered network potentially susceptible to modulation by berberine, this study offers a conceptual framework for repurposing natural compounds as multi-target therapeutics in PDAC, an area with an urgent need for novel strategies. Experimental validation of these hub targets through molecular docking, expression profiling, and functional assays will be an essential next step to translate these computational predictions into therapeutic insights.
  • Keywords: Berberine; Pancreatic ductal adenocarcinoma; Network pharmacology; Protein–protein interaction; Gene

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