Exploring the therapeutic potential and in vitro validation of baicalin for the treatment of triple-negative breast cancer DOI Creative Commons
Yuan Ma, Ying Pan, Qiancheng Zhao

et al.

Frontiers in Pharmacology, Journal Year: 2025, Volume and Issue: 16

Published: April 28, 2025

Objective To explore the mechanism of action baicalin (BA) in treatment triple-negative breast cancer (TNBC) based on network pharmacology, molecular docking and dynamics simulations vitro validation. Methods The inhibitory effects different concentrations proliferation MDA-MB-231, 4T1, MCF-7, MCF-10A cell lines were evaluated by CCK8 assay with clone formation assay. Three compound target prediction platforms, Swiss Target Prediction, SEA Pharmmapper, used to predict baicalin-related targets, mapped cancer-related targets retrieved from GeneCards OMMI databases obtain potential for cancer; STRING database Cytoscape software construct protein interaction screen core targets; GO KEGG enrichment analyses performed binding key was verified simulation; expression relevant proteins verified. Results Baicalin showed more obvious antiproliferative at certain concentrations, had less effect normal cells. A total nine cancer, including AKT1, ESR1, TNF-α, SRC, EGFR, MMP9, JAK2, PPARG, GSK3B, identified through construction PPI interactions ‘Traditional Chinese Medicine-Component-Target-Disease’ network, a 252 related intersected analysis. analysis enriched 2,526 Biological process, 105 Cellular component 250 Molecular function intersecting 128 signaling pathways results studies found that able interact other breast, JAK2 proteins, significant changes levels proteins. Conclusion inhibits TNF-α their cancer.

Language: Английский

Exploring the therapeutic potential and in vitro validation of baicalin for the treatment of triple-negative breast cancer DOI Creative Commons
Yuan Ma, Ying Pan, Qiancheng Zhao

et al.

Frontiers in Pharmacology, Journal Year: 2025, Volume and Issue: 16

Published: April 28, 2025

Objective To explore the mechanism of action baicalin (BA) in treatment triple-negative breast cancer (TNBC) based on network pharmacology, molecular docking and dynamics simulations vitro validation. Methods The inhibitory effects different concentrations proliferation MDA-MB-231, 4T1, MCF-7, MCF-10A cell lines were evaluated by CCK8 assay with clone formation assay. Three compound target prediction platforms, Swiss Target Prediction, SEA Pharmmapper, used to predict baicalin-related targets, mapped cancer-related targets retrieved from GeneCards OMMI databases obtain potential for cancer; STRING database Cytoscape software construct protein interaction screen core targets; GO KEGG enrichment analyses performed binding key was verified simulation; expression relevant proteins verified. Results Baicalin showed more obvious antiproliferative at certain concentrations, had less effect normal cells. A total nine cancer, including AKT1, ESR1, TNF-α, SRC, EGFR, MMP9, JAK2, PPARG, GSK3B, identified through construction PPI interactions ‘Traditional Chinese Medicine-Component-Target-Disease’ network, a 252 related intersected analysis. analysis enriched 2,526 Biological process, 105 Cellular component 250 Molecular function intersecting 128 signaling pathways results studies found that able interact other breast, JAK2 proteins, significant changes levels proteins. Conclusion inhibits TNF-α their cancer.

Language: Английский

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