Zhang Lin, Li Ling, Kong Hairui, Zeng Fangyin
Laboratory Medicine Center, Southern Medical University, Nanfang Hospital, Guangzhou 510515, China.E-mail:
Nan Fang Yi Ke Da Xue Xue Bao. 2015 May;35(5):763-6.
To identify the biomarkers of renal cell cancer (RCC) through urine metabolic analysis.
Urine samples of 27 RCC patients, 26 patients with other urinary cancers and 26 healthy volunteers were examined with gas chromatography-mass spectrometry (GC-MS). SIMCA-P+12.0.1.0 software was used for principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) to screen for the differential metabolites.
PCA (R2X=0.846, Q2=0.575) and OPLS-DA (R2X=0.736, R2Y=0.974, Q2Y=0.897) model were established for the RCC patients and control subjects. Fourteen metabolites were selected as the characteristic metabolites, including pentanoic acid, malonic acid, glutaric acid, adipic acid, amino quinoline, quinoline, indole acetic acid, and tryptophan, whose levels in the urine were significantly higher in the RCC patients than in the normal subjects (P<0.01); the RCC patients showed significantly higher urine contents of pentanoic acid, phenylalanine, and 6-methoxy-nitro quinoline than those with other urinary tumors (P<0.01).
The urine metabolites identified based on GC-MS analysis can distinguish RCC patients from patients with other urinary cancers and healthy subjects, suggesting their potential as diagnostic markers for RCC.
通过尿液代谢分析鉴定肾细胞癌(RCC)的生物标志物。
采用气相色谱 - 质谱联用(GC-MS)技术检测27例RCC患者、26例其他泌尿系统癌症患者及26名健康志愿者的尿液样本。使用SIMCA-P + 12.0.1.0软件进行主成分分析(PCA)和正交偏最小二乘判别分析(OPLS-DA)以筛选差异代谢物。
为RCC患者和对照受试者建立了PCA(R2X = 0.846,Q2 = 0.575)和OPLS-DA(R2X = 0.736,R2Y = 0.974,Q2Y = 0.897)模型。选择了14种代谢物作为特征代谢物,包括戊酸、丙二酸、戊二酸、己二酸、氨基喹啉、喹啉、吲哚乙酸和色氨酸,RCC患者尿液中这些代谢物的水平显著高于正常受试者(P < 0.01);RCC患者尿液中戊酸、苯丙氨酸和6-甲氧基硝基喹啉的含量显著高于其他泌尿系统肿瘤患者(P < 0.01)。
基于GC-MS分析鉴定的尿液代谢物可区分RCC患者与其他泌尿系统癌症患者及健康受试者,提示其作为RCC诊断标志物的潜力。