SRC Is a Potential Target of Arctigenin in Treating Triple-Negative Breast Cancer: Based on Machine Learning Algorithms, Molecular Modeling and in Vitro Test

Tianping Li^1,2*Yuezhou Huang^1,2Qing Luo³Linfeng Li⁴

• ¹Sichuan University, Chengdu, China
• ²Sichuan University West China Hospital Department of Clinical Pharmacy, Chengdu, China
• ³Macao Polytechnic University, Macau, Macao, SAR China
• ⁴Sichuan Kelun Biotech Biopharmaceutical Co Ltd, Chengdu, China

This research explores the effects of Arctigenin (AG) on triple negative breast cancer (TNBC) and examines its underlying mechanisms. Potential AG targets and the TNBC-related targets were determined using public databases. By analyzing the overlap between drug-specific and disease-related targets, we focused on key genes to uncover differentially expressed genes and conducted a Weighted Gene Co-expression Network Analysis (WGCNA). Then, pathway enrichment analysis was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Subsequently, utilized machine learning techniques to pinpoint hub genes, validated their significance in TNBC treatment through molecular docking studies, and evaluated their diagnostic capabilities via differential gene expression and Receiver Operating Characteristic (ROC) curves. Our analysis identified AG with 183 correlated targets, 5193 differentially expressed genes, and 6173 co-expression module genes related to TNBC. A total of 4 hub genes were identified among the 28 intersecting genes using machine learning algorithms. Molecular docking, Molecular dynamics (MD) and surface plasmon resonance (SPR) indicated a moderately strong interaction between AG and SRC kinase, where the oxygen atom of AG forms hydrogen bonds with the oxygen atom in M341 and the nitrogen atom in G344 of SRC. In vitro assays confirmed that AG reduced the viability of MDA-MB-453 and MDA-MB-231 cells in a concentration-and time-dependent manner, leading S phase arrest and apoptosis. Western blotting indicated that AG significantly reduced the levels of Bcl-2, caspase-3, and caspase-9, as well as decreased SRC, p-PI3K-p85, p-AKT1, p-MEK1/2, and p-ERK1/2 expression in TNBC cells in a concentration-dependent manner. AG effectively suppresses the proliferation of TBNC cells by directly binding to SRC kinase, which simultaneously suppresses the PI3K/AKT and MEK/ERK signaling pathways, ultimately causing cell cycle arrest and apoptosis. Our findings highlight the anti-TNBC efficacy of AG and elucidate its mechanism of action, offering new perspectives on multitarget therapies for TNBC.