Objective  To predict the core therapeutic targets and signaling pathways of lotusine in pancreatic cancer treatment using network pharmacology.

Methods  Potential targets of lotusine were retrieved from TCMSP and SwissTargetPrediction database. Pancreatic cancer-related targets were collected from GeneCards, OMIM, and DisGeNET databases. The intersection targets were identified using Venny 2.1.0. A protein-protein interaction (PPI) network was constructed via the STRING database, and visualized and analyzed using Cytoscape 3.10.4 to screen core targets. Gene ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the DAVID database. Molecular docking was conducted to validate the binding of lotusine to core targets. Molecular docking experiments were used to validate binding affinity, and animal experiments were conducted to verify the drug efficacy.

Results  A total of 112 potential targets of lotusine, 2,187 pancreatic cancer-related targets were identified, yielding 37 intersection targets. PPI network analysis showed that JUN, PIK3CA, HSP90AA1, ESR1, and SRC were core targets. GO functional enrichment analysis indicated involvement in regulation of cell proliferation, apoptotic process, inflammatory response, and angiogenesis. KEGG pathway analysis showed significant enrichment in PI3K-AKT signaling pathway and other cancer-related pathways. Molecular docking demonstrated strong binding affinities between lotusine and ESR1 (-7.8 kcal/mol), SRC (-8.2 kcal/mol) and HSP90AA1 (-8.7 kcal/mol). In vivo experiments showed that lotusine (20 mg/kg) significantly inhibited tumor growth by 34% (P<0.05) without significant body weight loss.

Conclusion  Lotusine exhibited inhibitory activity against pancreatic cancer xenograft growth in vivo, potentially through modulation of multiple targets and pathways including PI3K-AKT.

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