Molecular Mechanisms and Signaling Pathways Underlying the Synergistic Effect of Metformin and Paclitaxel in Preclinical Cancer Models: A Systematic Review.

Paclitaxel is a standard chemotherapeutic agent for various malignancies, but drug resistance frequently limits its clinical efficacy. Metformin, a widely used antidiabetic drug, has demonstrated anticancer properties. This systematic review evaluates the molecular mechanisms and signaling pathways underlying the synergistic interaction between metformin and paclitaxel in preclinical cancer models. A systematic search of Embase, Scopus, PubMed, Web of Science, and Google Scholar was conducted up to February 2026 following PRISMA guidelines. English-language preclinical studies examining the combined use of metformin and paclitaxel in cancer cell lines and animal models were included. Thirty-six studies met the eligibility criteria, including 28 in vitro and 8 in vivo studies. The majority demonstrated synergistic effects across endometrial, melanoma, triple-negative breast, prostate, and ovarian cancer models. Metformin enhances paclitaxel activity through several defined mechanisms. These include the activation of AMPK with subsequent suppression of the PI3K/AKT/mTOR pathway, epigenetic silencing of the oncogenic lncRNA SNHG7, induction of reactive oxygen species and mitochondrial apoptosis, and inhibition of cancer stemness via FOXO3a regulation. Additionally, metformin increases intracellular paclitaxel accumulation through OCT3 transporters. In vivo studies confirmed that metformin reduces tumor volume when combined with paclitaxel, utilizing both AMPK-dependent and AMPK-independent mechanisms such as cyclin D1 downregulation and gut microbiota modulation. Preclinical evidence indicates that metformin acts as a chemosensitizer, potentiating paclitaxel efficacy through multiple molecular pathways. This combination allows for reduced effective paclitaxel doses and may help overcome drug resistance, particularly in endometrial cancer, melanoma, and triple-negative breast cancer. Future clinical studies should optimize dosing regimens and validate predictive biomarkers, such as OCT1 and OCT3 expression, to improve clinical translation.