Wang Wenjie, Zhang Chen, Yu Qihong, Zheng Xichuan, Yin Chuanzheng, Yan Xueke, Liu Gang, Song Zifang
Department of Hepatobiliary Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1277 Jiefang Avenue, Wuhan, 430022, China.
Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan, 430030, China.
BMC Gastroenterol. 2021 Feb 12;21(1):68. doi: 10.1186/s12876-021-01638-3.
Liver cancer is one of the most common malignancies worldwide. HCC (hepatocellular carcinoma) is the predominant pathological type of liver cancer, accounting for approximately 75-85 % of all liver cancers. Lipid metabolic reprogramming has emerged as an important feature of HCC. However, the influence of lipid metabolism-related gene expression in HCC patient prognosis remains unknown. In this study, we performed a comprehensive analysis of HCC gene expression data from TCGA (The Cancer Genome Atlas) to acquire further insight into the role of lipid metabolism-related genes in HCC patient prognosis.
We analyzed the mRNA expression profiles of 424 HCC patients from the TCGA database. GSEA(Gene Set Enrichment Analysis) was performed to identify lipid metabolism-related gene sets associated with HCC. We performed univariate Cox regression and LASSO(least absolute shrinkage and selection operator) regression analyses to identify genes with prognostic value and develop a prognostic model, which was tested in a validation cohort. We performed Kaplan-Meier survival and ROC (receiver operating characteristic) analyses to evaluate the performance of the model.
We identified three lipid metabolism-related genes (ME1, MED10, MED22) with prognostic value in HCC and used them to calculate a risk score for each HCC patient. High-risk HCC patients exhibited a significantly lower survival rate than low-risk patients. Multivariate Cox regression analysis revealed that the 3-gene signature was an independent prognostic factor in HCC. Furthermore, the signature provided a highly accurate prediction of HCC patient prognosis.
We identified three lipid-metabolism-related genes that are upregulated in HCC tissues and established a 3-gene signature-based risk model that can accurately predict HCC patient prognosis. Our findings support the strong links between lipid metabolism and HCC and may facilitate the development of new metabolism-targeted treatment approaches for HCC.
肝癌是全球最常见的恶性肿瘤之一。肝细胞癌（HCC）是肝癌的主要病理类型，约占所有肝癌的75 - 85%。脂质代谢重编程已成为HCC的一个重要特征。然而，脂质代谢相关基因表达对HCC患者预后的影响仍不清楚。在本研究中，我们对来自癌症基因组图谱（TCGA）的HCC基因表达数据进行了全面分析，以进一步了解脂质代谢相关基因在HCC患者预后中的作用。
我们分析了来自TCGA数据库的424例HCC患者的mRNA表达谱。进行基因集富集分析（GSEA）以鉴定与HCC相关的脂质代谢相关基因集。我们进行了单变量Cox回归和LASSO（最小绝对收缩和选择算子）回归分析，以鉴定具有预后价值的基因并建立预后模型，并在验证队列中进行了测试。我们进行了Kaplan-Meier生存分析和ROC（受试者工作特征）分析以评估模型的性能。
我们鉴定出三个在HCC中具有预后价值的脂质代谢相关基因（ME1、MED10、MED22），并使用它们为每位HCC患者计算风险评分。高危HCC患者的生存率明显低于低危患者。多变量Cox回归分析显示，三基因特征是HCC的独立预后因素。此外，该特征对HCC患者的预后提供了高度准确的预测。
我们鉴定出三个在HCC组织中上调的脂质代谢相关基因，并建立了基于三基因特征的风险模型，该模型可以准确预测HCC患者的预后。我们的研究结果支持脂质代谢与HCC之间的紧密联系，并可能促进针对HCC的新的代谢靶向治疗方法的开发。
