Liver Unit, Department of Medicine, Imperial College London, QEQM Building, St. Mary's Hospital Campus, South Wharf Road, London W2 1NY, United Kingdom.
J Proteome Res. 2010 Feb 5;9(2):1096-103. doi: 10.1021/pr901058t.
Hepatocellular carcinoma (HCC) is the commonest primary hepatic malignancy worldwide. Current serum diagnostic biomarkers, such as alpha-fetoprotein, are expensive and insensitive in early tumor diagnosis. Urinary biomarkers differentiating HCC from chronic liver disease would be practical and widely applicable. Using an 11.7T nuclear magnetic resonance system, urine was analyzed from three well-matched subject groups, collected at Jos University Teaching Hospital (JUTH), Nigeria. Multivariate factor analyses were performed using principal components analysis (PCA) and partial least-squares discriminant analysis (PLS-DA). All patients were of Nigerian descent: 18 hepatitis B surface antigen (HBsAg)-positive patients with HCC, 10 HBsAg positive patients with cirrhosis, and 15 HBsAg negative healthy Nigerian controls. HCC patients were distinguished from healthy controls, and from the cirrhosis cohort, with sensitivity/specificity of 100%/93% and 89.5%/88.9%, respectively. Metabolites that most strongly contributed to the multivariate models were creatinine, carnitine, creatine and acetone. Urinary (1)H MRS with multivariate statistical analysis was able to differentiate patients with HCC from normal subjects and patients with cirrhosis. Creatinine, carnitine, creatine and acetone were identified as the most influential metabolites. These findings have identified candidate urinary HCC biomarkers which have potential to be developed as simple urinary screening tests for the clinic.
肝细胞癌 (HCC) 是全球最常见的原发性肝脏恶性肿瘤。目前的血清诊断生物标志物,如甲胎蛋白,在早期肿瘤诊断中既昂贵又不敏感。区分 HCC 与慢性肝病的尿生物标志物将具有实际意义且适用范围广泛。使用 11.7T 核磁共振系统,从三个匹配良好的受试者组(在尼日利亚的乔斯大学教学医院 (JUTH) 采集的尿液)中进行了分析。使用主成分分析 (PCA) 和偏最小二乘判别分析 (PLS-DA) 进行多变量因子分析。所有患者均为尼日利亚血统:18 名乙型肝炎表面抗原 (HBsAg) 阳性 HCC 患者、10 名 HBsAg 阳性肝硬化患者和 15 名 HBsAg 阴性健康尼日利亚对照者。HCC 患者与健康对照组和肝硬化组的区别在于,敏感性/特异性分别为 100%/93%和 89.5%/88.9%。对多元模型贡献最大的代谢物是肌酐、肉碱、肌酸和丙酮。使用多元统计分析的尿 (1)H MRS 能够区分 HCC 患者与正常受试者和肝硬化患者。鉴定出肌酐、肉碱、肌酸和丙酮是最具影响力的代谢物。这些发现确定了候选尿 HCC 生物标志物,它们有可能作为临床的简单尿筛选试验得到开发。