AUTHOR=Gao Kai , Cao WanChen , He ZiHao , Liu Liu , Guo JinCheng , Dong Lei , Song Jini , Wu Yang , Zhao Yi 

TITLE=Network medicine analysis for dissecting the therapeutic mechanism of consensus TCM formulae in treating hepatocellular carcinoma with different TCM syndromes

JOURNAL=Frontiers in Endocrinology

VOLUME=Volume 15 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2024.1373054

DOI=10.3389/fendo.2024.1373054

ISSN=1664-2392

ABSTRACT=Traditional Chinese medicine (TCM) has long been used as a complementary therapy for hepatocellular carcinoma (HCC) in clinical practice, and has significantly improved the patients' survival time and quality of life. According to the national therapeutic guidelines, TCM summarized 5 detailed subtypes, called TCM syndromes of the HCC disease using stringent diagnostic criteria, and assigned 5 consensus formulae for treating each of them respectively. To dissect the therapeutic mechanisms underlying this syndrome differentiation and treatment, we assembled a protein-protein interaction (PPI) network and performed network medicine analysis of the HCC disease, its TCM syndromes and formulae. Firstly, we showed that the five TCM syndrome types-related genes are topologically and functionally close to the HCC disease-related genes in the PPI network. Then we demonstrated that the gene sets for 5 TCM formulae were significantly adjacent to that for HCC and its related TCM syndromes, giving quantitative measures and functional interpretation about the efficiency of TCM syndrome differentiation as well as their corresponding treatment modalities. Finally, we ranked the importance of active herbal ingredients that constitute TCM herbs by the random walk algorithm through a newly assembled heterogeneous network. We showed that the prioritization results can be further confirmed by literature, demonstrating the power of network medicine analysis for decoding the medicinal knowledge from TCM.