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Bladder Cancer Determination Via Two Urinary Metabolites: A Biomarker Pattern Approach

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Bladder Cancer Determination Via Two Urinary Metabolites A Biomarker Pattern Approach.htm (403bytes)
Date
2011-07-28
Author
Huang, Zhenzhen
Lin, Lin
Gao, Yao
Chen, Yongjing
Yan, Xiaomei
颜晓梅
Xing, Jinchun(Xiamen First Hosp, Dept Urol)
Hang, Wei
杭纬
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  • 化学化工-已发表论文 [14469]
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Abstract
The purpose of this study was to use metabonomic profiling to identify a potential specific biomarker pattern in urine as a noninvasive bladder cancer (BC) detection strategy. A liquid chromatography-mass spectrometry based method, which utilized both reversed phase liquid chromatography and hydrophilic interaction chromatography separations, was performed, followed by multivariate data analysis to discriminate the global urine profiles of 27 BC patients and 32 healthy controls. Data from both columns were combined, and this combination proved to be effective and reliable for partial least squares-discriminant analysis. Following a critical selection criterion, several metabolites showing significant differences in expression levels were detected. Receiver operating characteristic analysis was used for the evaluation of potential biomarkers. Carnitine C9:1 and component I, were combined as a biomarker pattern, with a sensitivity and specificity up to 92.6% and 96.9%, respectively, for all patients and 90.5% and 96.9%, respectively for low-grade BC patients. Metabolic pathways of component I and carnitine C9: 1 are discussed. These results indicate that metabonomics is a practicable tool for BC diagnosis given its high efficacy and economization. The combined biomarker pattern showed better performance than single metabolite in discriminating bladder cancer patients, especially low-grade BC patients, from healthy controls. Molecular & Cellular Proteomics 10: 10.1074/mcp.M111.007922, 1-10, 2011.
Citation
MOLECULAR & CELLULAR PROTEOMICS,2011,10(10):
URI
http://dx.doi.org/doi:10.1074/mcp.M111.007922
https://dspace.xmu.edu.cn/handle/2288/11505
WOS:000295773800021

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