Xu Lei, Xiao Ting, Chao Tengfei, Xiong Huihua, Yao Wei
Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China.
Department of Ultrasonography, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China.
BMC Cancer. 2025 May 19;25(1):895. doi: 10.1186/s12885-025-14306-6.
Hepatocellular Carcinoma (HCC) is related to dysregulated lipid metabolism and immunosuppressive microenvironment. This study developed a genetic risk model using lipid metabolism-related genes to predict survival and immune patterns in HCC patients.
Differentially expressed genes (DEGs) related to lipid metabolism were identified in HCC via the TCGA-LIHC dataset. A risk model for survival prediction was constructed via DEGs related to survival. The immune signature associated with the risk model was also evaluated by the CIBERSORT algorithm, tumor immune dysfunction and exclusion algorithm, and single sample gene set enrichment analysis.
This study identified six lipid metabolism-related genes, ADH4, LCAT, CYP2C9, CYP17A1, LPCAT1, and ACACA, to construct a lipid metabolism-related gene risk model that can divide HCC patients into low- and high-risk groups. Internal and external validation verified that the risk model could be a signature that could effectively predict HCC patient prognosis. High-risk patients showed disrupted immune cell profiles, reduced tumor-killing capacity, and increased expression of immune checkpoint genes. However, they responded more favorably to immune checkpoint inhibitor (ICB) therapy. The top ten hub genes related to the risk model were associated with tumor progression and deteriorating prognosis. In vitro experiments verified that the downregulation of the top 1 hub gene CDK1 was correlated to the HCC cell proliferation.
The risk model constructed using lipid metabolism-related genes could effectively predict prognosis and was related to the immunosuppressive microenvironment and ICB immunotherapy. The hub genes related to the risk model were potential therapeutic targets.
肝细胞癌（HCC）与脂质代谢失调和免疫抑制微环境有关。本研究利用脂质代谢相关基因建立了一个遗传风险模型，以预测HCC患者的生存情况和免疫模式。
通过TCGA-LIHC数据集在HCC中鉴定出与脂质代谢相关的差异表达基因（DEGs）。通过与生存相关的DEGs构建生存预测风险模型。还通过CIBERSORT算法、肿瘤免疫功能障碍和排除算法以及单样本基因集富集分析评估了与风险模型相关的免疫特征。
本研究鉴定出六个与脂质代谢相关的基因，即ADH4、LCAT、CYP2C9、CYP17A1、LPCAT1和ACACA，构建了一个脂质代谢相关基因风险模型，该模型可将HCC患者分为低风险组和高风险组。内部和外部验证证实，该风险模型可以作为一个有效预测HCC患者预后的标志物。高风险患者表现出免疫细胞谱紊乱、肿瘤杀伤能力降低以及免疫检查点基因表达增加。然而，他们对免疫检查点抑制剂（ICB）治疗的反应更有利。与风险模型相关的前十个枢纽基因与肿瘤进展和预后恶化有关。体外实验证实，头号枢纽基因CDK1的下调与HCC细胞增殖相关。
利用脂质代谢相关基因构建的风险模型可以有效预测预后，并且与免疫抑制微环境和ICB免疫治疗有关。与风险模型相关的枢纽基因是潜在的治疗靶点。
