A Study on the Mechanism of Canna Root in Treating Breast Cancer Based on Network Pharmacology

Vollständiger Abstract

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Objective: The present study was designed to investigate the prospective genetic targets of Boehmeria nivea root constituents for oncological applications via network pharmacology and laboratory validation, thereby clarifying the medicinal pathways of this plant. Methods: Major bioactive molecules from Boehmeria nivea root were sourced from the TCMSP platform, utilizing filters for oral bioavailability (OB) ≥30% and drug-likeness (DL) ≥0.18. Following the acquisition of molecular structures from PubChem, Swiss Target Prediction was employed to forecast potential interacting proteins, with subsequent analysis through Disease Ontology (DO). Transcriptomic profiles encompassing 1,081 tumor samples and 99 healthy controls were retrieved from TCGA. We utilized both DGE and WGCNA to pinpoint cancer-specific markers. By determining the intersection of drug and disease targets, a protein-protein interaction (PPI) network was established via STRING and analyzed using Cytoscape 3.9.1. Functional annotation (GO and KEGG) of central genes was performed within the R Studio environment. Results: Our findings identified five core bioactive agents-quercetin, hederagenin, betulinic acid, catechin, and β-sitosterol-which were associated with 221 predictive targets, while 5,075 genes exhibited differential expression in malignant tissues. Analysis revealed 81 overlapping targets; notable hub genes included PPARA, NR3C1, ESR2, TERT, ABCG2, PARP1, MET, ABCB1, KDR, and MMP9. Data from DO indicated a robust link between compound targets and oncological pathologies. Furthermore, GO enrichment demonstrated that hub genes predominantly regulate the G2/M phase and mitotic cycles. KEGG mapping suggested the herb's anti-cancer efficacy is likely mediated via the VEGF, calcium, and PI3K-AKT signaling pathways, alongside cell cycle modulation. Conclusion: The integrated analysis of Boehmeria nivea root and cancer-related genes highlighted 81 shared nodes. A high-priority cluster involving genes like MMP9, KDR, ABCB1, MET, and PARP1 was isolated using the MCODE algorithm. Functional analysis of this module indicates that the root's active components exert their anti-tumor effects by interfering with the PI3K-AKT axis, controlling mitotic checkpoints at the G2/M transition, and regulating serine/threonine protein kinase activities to induce cell cycle arrest in malignant cells.