Data mining and experimental validation identify a core herb combination as a therapeutic agent for malignant...

Malignant lymphoma (ML) is a heterogeneous group of cancers originating from lymphocytes and lymphoid tissues. Despite advances in treatment, refractory and relapsed cases remain a significant challenge, leading to poor prognosis and highlighting the need for novel therapies. This study aimed to use data mining and experimental validation to identify potential traditional Chinese medicine (TCM) therapeutic agents for ML and explore the underlying mechanisms. A comprehensive search on TCM prescriptions for ML treatment was conducted across multiple databases. Association rule mining was applied to identify commonly used herb combinations. In vivo experiments were performed to evaluate the effects of the core combination on tumor growth in the ML xenograft tumor model. Network pharmacology was used to explore the involved mechanisms. Molecular docking was used to assess the binding affinity of the key active ingredients to core proteins. Western blot analysis was conducted to evaluate the expression of proteins associated with the involved pathway. A total of 118 eligible TCM prescriptions for ML treatment were identified across various databases, including 213 herbs. Association rule analysis identified "Glycyrrhiza uralensis, Prepared Rehmannia Root, and Astragalus membranaceus" as the core herb combination for ML treatment. In vivo experiments showed that the identified combination inhibited tumor formation in the ML model. Functional analysis showed significant enrichment in the PI3K-Akt signaling pathway. Molecular docking revealed strong binding affinities between the key ingredients and the core proteins of this pathway. Western blot analysis showed a significant reduction in the ratios of p-PI3K/PI3K and p-AKT/AKT in the herb-treated group compared to the control. This study used data mining to explore the herbal characteristics in the treatment of ML and identify a core herb combination. In vivo experiments showed that the combination inhibited tumor growth in ML, which was associated with the suppression of PI3K-Akt signaling pathway activation. These findings support the potential of TCM-based therapies for ML and lay a foundation for further research and clinical application for the disease.