Kind T, Tolstikov V, Fiehn O, Weiss RHA comprehensive urinary metabolomic approach for identifying kidney cancer. Anal Biochem 363: 185-195

Department of Internal Medicine, University of California, Davis, Davis, California, United States
Analytical Biochemistry (Impact Factor: 2.22). 05/2007; 363(2):185-95. DOI: 10.1016/j.ab.2007.01.028
Source: PubMed


The diagnosis of cancer by examination of the urine has the potential to improve patient outcomes by means of earlier detection. Due to the fact that the urine contains metabolic signatures of many biochemical pathways, this biofluid is ideally suited for metabolomic analysis, especially involving diseases of the kidney and urinary system. In this pilot study, we test three independent analytical techniques for suitability for detection of renal cell carcinoma (RCC) in urine of affected patients. Hydrophilic interaction chromatography (HILIC-LC-MS), reversed-phase ultra performance liquid chromatography (RP-UPLC-MS), and gas chromatography time-of-flight mass spectrometry (GC-TOF-MS) all were used as complementary separation techniques. The combination of these techniques is best suited to cover a very large part of the urine metabolome by enabling the detection of both lipophilic and hydrophilic metabolites present therein. In this study, it is demonstrated that sample pretreatment with urease dramatically alters the metabolome composition apart from removal of urea. Two new freely available peak alignment methods, MZmine and XCMS, are used for peak detection and retention time alignment. The results are analyzed by a feature selection algorithm with subsequent univariate analysis of variance (ANOVA) and a multivariate partial least squares (PLS) approach. From more than 2000 mass spectral features detected in the urine, we identify several significant components that lead to discrimination between RCC patients and controls despite the relatively small sample size. A feature selection process condensed the significant features to less than 30 components in each of the data sets. In future work, these potential biomarkers will be further validated with a larger patient cohort. Such investigation will likely lead to clinically applicable assays for earlier diagnosis of RCC, as well as other malignancies, and thereby improved patient prognosis.

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Available from: Vladimir V Tolstikov, Jan 18, 2014
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    • "Perturbation in the levels of bile acids, histidine and inosine were found in gas chromatography–mass spectrometry (GC–MS) and liquid chromatography– mass spectrometry (LC–MS)-based studies of hepatocellular cancer [8]. Altered levels of metabolites such as acylcarnitines, quinolinate, 4 hydroxybenzoate, and gentisate have been reported in kidney cancer [12] [13] [14]. Several potential biomarkers have been reported in ESCC by carrying out serum metabolomics [15]. "
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    • "In fact, the use of urease pretreatment is a common approach prior to chromatography techniques due to the risk of column overloading, peak distortions, and ion suppression, among other matrix effects, that may occur due to the high concentrations of urea in urine samples. However, after urease treatment a dramatic alteration in the urinary metabolomes was seen, thus, other processes may be selected to avoid the interference of urea in the chromatographic separation like the use of adequate elution gradients instead of urease (Kind et al. 2007). Later, Kim et al. (2009) using a larger sample cohort confirmed the interest of urine matrix for metabolomics purposes using an HILIC approach as Kind et al. (Table 1). "
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