Abstract
BACKGROUND: Angelica-based formulas can improve quality of life in patients with endometrial cancer. However, the results remain controversial, and their mechanisms of action are unclear. In this study, we systematically explored the effects and mechanism of action of Angelica sinensis (AS) in endometrial cancer (EC) using network pharmacology and molecular docking. METHODS: We systematically searched PubMed, Embase, Cochrane Library, Web of Science, Chinese Science and Technology Journals (CQVIP), China Academic Journals (CNKI), Wanfang, and Chinese Biomedical Literature database (SinoMed). Nine randomized controlled trials were enrolled in the study. In network pharmacology, ingredients of Angelica sinensis were screened, endometrial cancer related genes were then identified and the 'Herb-Ingredient-Target-Disease' network constructed. Molecular docking was finally employed for in silico simulation matching between representative Angelica sinensis ingredients and their target genes. RESULTS: The meta-analysis of this research provides evidence to support the efficacy of angelica-based formulas in the treatment of endometrial cancer. Network pharmacology demonstrated that EGFR, TP53, CTNNB1, CCND1, and HRAS are the core targets of endometrial cancer, and ferulic acid and caffeic acid are the major bioactive ingredients of Angelica sinensis. Molecular docking showed that ferulic acid and caffeic acid can closely bind core targets. CONCLUSIONS: Our study is the first to systematically apply bioinformatics methods-including meta-analysis, network pharmacology, and molecular docking-to explore the pharmacological and molecular mechanisms of Angelica sinensis in endometrial cancer treatment. Results of our study provide valuable scientific insights into the underlying mechanisms of Angelica sinensis in the treatment of endometrial cancer, serving as a crucial foundation for future research in this area.