Predicting Anticancer Targets of Mebendazole Through Network Pharmacology: An Integrated Analysis of Molecular Targets, Signalling Pathways, and Clinical Trial Evidence

Mebendazole (MBZ), a broad-spectrum anthelmintic benzimidazole with an established safety profile, has attracted significant interest as a candidate for oncological drug repurposing. Despite growing preclinical and early clinical evidence, a systematic characterisation of MBZ's multi-target anticancer mechanisms has not been comprehensively performed. Here, we employed a network pharmacology approach to predict and validate the principal anticancer targets of MBZ. Using reverse pharmacophore mapping (SwissTargetPrediction, PharmMapper) and disease-target databases (GeneCards, OMIM), we identified 14 high-confidence anticancer targets. Protein–protein interaction (PPI) networks were constructed in STRING v12.0 and analysed in Cytoscape v3.10; pathway enrichment was performed using KEGG and Gene Ontology (GO) analyses (Enrichr/DAVID). Key predicted targets include β-tubulin (TUBB), vascular endothelial growth factor receptor 2 (VEGFR2/KDR), BRAF kinase, TRAF2- and Nck-interacting kinase (TNIK), BCL-2 family proteins, MEK1/2-ERK1/2 (MAPK pathway), and TP53. KEGG enrichment identified the MAPK signalling pathway, PI3K-AKT signalling, cell cycle regulation, apoptosis, and Wnt signalling as the top five enriched oncological pathways (all FDR < 0.05). These findings were cross-referenced with publicly registered clinical trials (NCT01729260, NCT03925662) and published pharmacological data, substantiating the in silico predictions. Our data collectively support the multi-target pharmacological basis of MBZ's anticancer activity and provide a rationale for prioritised biomarker-stratified clinical trials in glioblastoma multiforme, colorectal cancer, and non-small cell lung cancer.