Academic Journal
Total saponins from Paris polyphylla against breast cancer: an integrative pharmacological study combining chemical profiling, network pharmacology, machine learning, and in vitro validation.
| Τίτλος: | Total saponins from Paris polyphylla against breast cancer: an integrative pharmacological study combining chemical profiling, network pharmacology, machine learning, and in vitro validation. |
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| Συγγραφείς: | Huang HT; School of Chinese Material Medica, Beijing University of Chinese Medicine, Beijing, 102488, China., Zhou LP; School of Chinese Material Medica, Beijing University of Chinese Medicine, Beijing, 102488, China., Chen Q; School of Chinese Material Medica, Beijing University of Chinese Medicine, Beijing, 102488, China., Wang WQ; School of Chinese Material Medica, Beijing University of Chinese Medicine, Beijing, 102488, China., Yao SC; School of Chinese Material Medica, Beijing University of Chinese Medicine, Beijing, 102488, China., Zhang HJ; School of Chinese Material Medica, Beijing University of Chinese Medicine, Beijing, 102488, China., Li YX; School of Chinese Material Medica, Beijing University of Chinese Medicine, Beijing, 102488, China., Qu CH; School of Chinese Material Medica, Beijing University of Chinese Medicine, Beijing, 102488, China., Yin XB; School of Chinese Material Medica, Beijing University of Chinese Medicine, Beijing, 102488, China., Ni J; School of Chinese Material Medica, Beijing University of Chinese Medicine, Beijing, 102488, China. Electronic address: 602054@bucm.edu.cn., Dong XX; School of Chinese Material Medica, Beijing University of Chinese Medicine, Beijing, 102488, China. Electronic address: dxiaoxv@163.com. |
| Πηγή: | Journal of ethnopharmacology [J Ethnopharmacol] 2026 Sep 29; Vol. 374 (Pt 2), pp. 122453. Date of Electronic Publication: 2026 Sep 29. |
| Publication Model: | Ahead of Print |
| Τύπος έκδοσης: | Journal Article |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Elsevier Sequoia Country of Publication: Ireland NLM ID: 7903310 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1872-7573 (Electronic) Linking ISSN: 03788741 NLM ISO Abbreviation: J Ethnopharmacol Subsets: MEDLINE |
| Imprint Name(s): | Publication: Limerick : Elsevier Sequoia Original Publication: Lausanne, Elsevier Sequoia. |
| Περίληψη: | Ethnopharmacological Relevance: Paris polyphylla Smith var. yunnanensis (Franch.) Hand.-Mazz., a traditional heat-clearing and detoxifying Chinese herb, has been extensively used in cancer therapy as a key constituent of Chinese patent medicines. Although the antitumor activities of individual steroidal saponin monomers have been extensively investigated, the therapeutic potential and molecular targets of the total saponins from Paris polyphylla var. yunnanensis (TPP) in breast cancer have not yet been reported. Aim of the Study: This study aimed to elucidate the anti-breast cancer efficacy and underlying mechanisms of TPP by integrating chemical profiling, network pharmacology, bioinformatics, machine learning, molecular docking, and in vitro experimental validation. Materials and Methods: The chemical composition of TPP was analyzed by UPLC-Q-TOF-MS and HPLC. Potential targets of TPP against breast cancer were predicted through network pharmacology and bioinformatics analyses, and further refined using protein-protein interaction network analysis combined with machine learning. The candidate targets were subsequently evaluated by ROC curve analysis, immune cell infiltration assessment, and molecular docking. Finally, the findings were validated through in vitro pharmacological assays, RT-qPCR, Western blotting and RNA transcriptomic sequencing (RNA-seq). Results: Seventeen compounds were identified in TPP, with polyphyllin I, II, and VII constituting over 85% of the total active components. Through intersection analysis of TPP targets, WGCNA module genes, and DEGs, 111 potential therapeutic targets were identified. Subsequent protein-protein interaction network analysis and machinelearning prioritized four hub genes-LIPE, PPARG, FABP4, and IGF1-which were significantly downregulated in breast cancer tissues and validated with high diagnostic accuracy (AUC > 0.90). These genes were closely associated with tumor immune cell infiltration. Molecular docking predicted strong binding between the major saponins and key targets, and RT-qPCR and Western blotting further validated the reversal of their expression at both mRNA and protein levels. In vitro assays demonstrated that TPP significantly suppressed 4T1 cells proliferation, colony formation, and migration, while concurrently inducing apoptosis and pyroptosis. RNA-seq analysis further substantiated that TPP exerts its anti-breast cancer effects through modulation of lipid metabolic pathways. Conclusions: This study demonstrates that TPP exert anti-breast cancer effects by targeting the LIPE/PPARG/FABP4/IGF1 axis and triggering apoptosis and pyroptosis. These findings offer a foundation for ethnopharmacological application of TPP in breast cancer therapy and demonstrate the potential of integrative pharmacological strategies in developing targeted breast cancer treatment. (Copyright © 2026 Elsevier B.V. All rights reserved.) |
| Competing Interests: | Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. |
| Contributed Indexing: | Keywords: Anti-breast cancer; Network pharmacology; Paridis rhizoma; Pyroptosis; machine learning |
| Entry Date(s): | Date Created: 20260929 Latest Revision: 20261005 |
| Update Code: | 20261006 |
| DOI: | 10.1016/j.jep.2026.122453 |
| PMID: | 42810458 |
| Βάση Δεδομένων: | MEDLINE |
| ISSN: | 1872-7573 |
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| DOI: | 10.1016/j.jep.2026.122453 |