肝细胞癌（HCC）是全世界癌症相关死亡的主要原因。中药（TCM）被广泛用作辅助疗法，可提高患者的生存率和生活质量。中医将肝癌分为五种不同的综合征，每种都用特定的草药配方治疗。然而，这些治疗的分子机制仍不清楚。我们采用网络医学的方法来探索中医治疗肝癌的机制。通过构建蛋白质-蛋白质相互作用（PPI）网络，我们整合了与中医证候及其相应草药配方相关的基因。这使得能够对中医证候、肝癌和治疗具体方剂之间的拓扑和功能关系进行定量分析。我们的研究结果表明，与五种中医证候相关的基因与 PPI 网络内的肝癌相关基因密切相关。五个中药方剂对应的基因组与肝癌及其相关证候显着接近，提示了中医辨证治疗的功效。此外，通过应用于异构网络的随机游走算法，我们优先考虑活性草药成分，结果得到文献证实。这些关键化合物的鉴定强调了网络医学揭示中药复杂药理作用的潜力。这项研究为中医治疗 HCC 的策略提供了分子基础，并强调了特定草药成分作为药物开发和精准医学的潜在先导。版权所有 © 2024 高、曹、何、刘、郭、董、宋、吴和赵。

Hepatocellular carcinoma (HCC) is a major cause of cancer-related mortality worldwide. Traditional Chinese Medicine (TCM) is widely utilized as an adjunct therapy, improving patient survival and quality of life. TCM categorizes HCC into five distinct syndromes, each treated with specific herbal formulae. However, the molecular mechanisms underlying these treatments remain unclear.We employed a network medicine approach to explore the therapeutic mechanisms of TCM in HCC. By constructing a protein-protein interaction (PPI) network, we integrated genes associated with TCM syndromes and their corresponding herbal formulae. This allowed for a quantitative analysis of the topological and functional relationships between TCM syndromes, HCC, and the specific formulae used for treatment.Our findings revealed that genes related to the five TCM syndromes were closely associated with HCC-related genes within the PPI network. The gene sets corresponding to the five TCM formulae exhibited significant proximity to HCC and its related syndromes, suggesting the efficacy of TCM syndrome differentiation and treatment. Additionally, through a random walk algorithm applied to a heterogeneous network, we prioritized active herbal ingredients, with results confirmed by literature.The identification of these key compounds underscores the potential of network medicine to unravel the complex pharmacological actions of TCM. This study provides a molecular basis for TCM's therapeutic strategies in HCC and highlights specific herbal ingredients as potential leads for drug development and precision medicine.Copyright © 2024 Gao, Cao, He, Liu, Guo, Dong, Song, Wu and Zhao.