Integration of Meta-Analysis and Network Pharmacology to Investigate the Pharmacological Mechanisms of Quercetin on Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is as the most frequently observed histological subtype among primary liver malignancies. While quercetin (QT) shows potential antitumor activity, its preclinical anti-HCC effects and safety (especially in animals) remain unclear. Most existing studies use single methods (e.g., individual animal or in vitro assays), which compromises the reliability of the conclusions. This study's novelty lies in its use of a combined approach-integrating meta-analysis to quantify efficacy and network pharmacology to explore mechanisms, with experimental validation-to address this research gap. This work explores QT's preclinical anti-HCC effects and adverse effects using this integrated approach.

We collected literature on the treatment of HCC with QT from January 2000 to August 2024. Nine articles meeting the requirements were included in the current study. Subsequent to this, a meta-analysis was conducted, with further validation via network pharmacology approaches and experimental assays.

A meta-analysis found that QT significantly inhibited HCC growth (reduced tumor volume/weight) and reduced mortality in tumor-bearing mice, with no significant effect on body weight. Network pharmacology identified protein kinase B alpha (AKT1) and the phosphoinositide 3-kinase (PI3K)/AKT pathway as potential therapeutic targets. Finally, the aforementioned conclusions were further verified through experimental validation.

Preclinically, QT effectively inhibited HCC growth and reduced mortality in tumor-bearing mice without affecting body weight, likely via the PI3K/AKT pathway (targeting AKT1). Our study results furnish preliminary evidence for QT as a promising candidate for HCC adjuvant treatment, supporting its further evaluation in clinical trials. Limitations include reliance on preclinical data; thus, the translational value needs clinical validation, and the underlying mechanisms require more in-depth investigation.
Cancer
Care/Management

Authors

Tan Tan, Chen Chen, Peng Peng, Tang Tang, Sun Sun, Zhou Zhou, Zhou Zhou, Li Li, Peng Peng, Chen Chen
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