| Summary: | Background: Li-Ru-Kang (LRK) has been used in the treatment of hyperplasia of mammary glands (HMG) for several decades and can effectively improve clinical symptoms. This study aims to investigate the mechanism by which LRK intervenes in HMG based on an integrated approach that combines metabolomics and network pharmacology analyses.Methods: The effects of LRK on HMG induced by estrogen-progesterone in rats were evaluated by analyzing the morphological and pathological characteristics of breast tissues. Moreover, UPLC-QTOF/MS was performed to explore specific metabolites potentially affecting the pathological process of HMG and the effects of LRK. Pathway analysis was conducted with a combination of metabolomics and network pharmacology analyses to illustrate the pathways and network of LRK-treated HMG.Results: Li-Ru-Kang significantly improved the morphological and pathological characteristics of breast tissues. Metabolomics analyses showed that the therapeutic effect of LRK was mainly associated with the regulation of 10 metabolites, including prostaglandin E2, phosphatidylcholine, leukotriene B4, and phosphatidylserine. Pathway analysis indicated that the metabolites were related to arachidonic acid metabolism, glycerophospholipid metabolism and linoleic acid metabolism. Moreover, principal component analysis showed that the metabolites in the model group were clearly classified, whereas the metabolites in the LRK group were between those in the normal and model groups but closer to those in the normal group. This finding indicated that these metabolites may be responsible for the effects of LRK. The therapeutic effect of LRK on HMG was possibly related to the regulation of 10 specific metabolites. In addition, we further verified the expression of protein kinase C alpha (PKCα), a key target predicted by network pharmacology analysis, and showed that LRK could significantly improve the expression of PKCα.Conclusion: Our study successfully explained the modulatory properties of LRK treatment on HMG using metabolomics and network pharmacology analyses. This systematic method can provide methodological support for further understanding the complex mechanism underlying HMG and possible traditional Chinese medicine (TCM) active ingredients for the treatment of HMG.
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