Kim Da Jung, Cho Eun Ju, Yu Kyung-Sang, Jang In-Jin, Yoon Jung-Hwan, Park Taesung, Cho Joo-Youn
Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul 03080, Korea.
Department of Internal Medicine and Liver Research Institute, Seoul National University College of Medicine, Seoul 03080, Korea.
Cancers (Basel). 2019 Oct 6;11(10):1497. doi: 10.3390/cancers11101497.
The established biomarker for hepatocellular carcinoma (HCC), serum α-fetoprotein (AFP), has suboptimal performance in early disease stages. This study aimed to develop a metabolite panel to differentiate early-stage HCC from cirrhosis. Cross-sectional metabolomic analyses of serum samples were performed for 53 and 47 patients with early HCC and cirrhosis, respectively, and 50 matched healthy controls. Results were validated in 82 and 80 patients with early HCC and cirrhosis, respectively. To retain a broad spectrum of metabolites, technically distinct analyses (global metabolomic profiling using gas chromatography time-of-flight mass spectrometry and targeted analyses using liquid chromatography with tandem mass spectrometry) were employed. Multivariate analyses classified distinct metabolites; logistic regression was employed to construct a prediction model for HCC diagnosis. Five metabolites (methionine, proline, ornithine, pimelylcarnitine, and octanoylcarnitine) were selected in a panel. The panel distinguished HCC from cirrhosis and normal controls, with an area under the receiver operating curve (AUC) of 0.82; this was significantly better than that of AFP (AUC: 0.75). During validation, the panel demonstrated significantly better predictability (AUC: 0.94) than did AFP (AUC: 0.78). Defects in ammonia recycling, the urea cycle, and amino acid metabolism, demonstrated on enrichment pathway analysis, may reliably distinguish HCC from cirrhosis. Compared with AFP alone, the metabolite panel substantially improved early-stage HCC detection.
肝细胞癌(HCC)已确立的生物标志物血清甲胎蛋白(AFP)在疾病早期阶段的表现并不理想。本研究旨在开发一种代谢物组,以区分早期HCC和肝硬化。分别对53例早期HCC患者、47例肝硬化患者以及50例匹配的健康对照者的血清样本进行横断面代谢组学分析。结果在82例早期HCC患者和80例肝硬化患者中得到验证。为了保留广泛的代谢物,采用了技术上不同的分析方法(使用气相色谱飞行时间质谱进行全代谢组分析以及使用液相色谱串联质谱进行靶向分析)。多变量分析对不同的代谢物进行分类;采用逻辑回归构建HCC诊断预测模型。在一个代谢物组中选择了五种代谢物(蛋氨酸、脯氨酸、鸟氨酸、庚二酰肉碱和辛酰肉碱)。该代谢物组可区分HCC与肝硬化及正常对照,受试者操作特征曲线下面积(AUC)为0.