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.


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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    ABSTRACT: Esophageal squamous cell carcinoma (ESCC) is one of the most aggressive cancers with poor prognosis. Here, we carried out liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-Q-TOF-MS)-based untargeted metabolomic analysis of ESCC serum samples. Statistical analysis resulted in the identification of 652 significantly dysregulated molecular features in serum from ESCC patients as compared to the healthy subjects. We identified several metabolites associated with glycerophospholipid metabolic pathway. Phosphatidylcholines were identified as a major class of dysregulated metabolites in this study suggesting potential perturbation of phosphocholine metabolism in ESCC. By using a targeted MS/MS approach both in positive and negative mode, we were able to characterize and confirm the structure of seven metabolites. Our study describes a quantitative LC-MS approach for characterizing dysregulated lipid metabolism in ESCC. Altered metabolism is a hallmark of cancer. We carried out (LC-MS)-based untargeted metabolomic profiling of serum from esophageal squamous cell carcinoma (ESCC) patients to characterize dysregulated metabolites. Phosphatidylcholine metabolism was found to be significantly altered in ESCC. Our study illustrates the use of mass spectrometry-based metabolomic analysis to characterize molecular alterations associated with ESCC. This article is part of a Special Issue entitled: Proteomics in India. Copyright © 2015. Published by Elsevier B.V.
    Journal of proteomics 05/2015; 127. DOI:10.1016/j.jprot.2015.05.013 · 3.89 Impact Factor
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    • "Blood (and its derivatives like serum) and urine are the most commonly used specimens for biomarker studies because of easy repetitive access and high yield. Moreover, saliva, breath condensate, bronchial washes, pancreatic juices, prostatic secretions, faeces, and other types of physiological liquids or surrogate tissues can be also used for metabolomics studies [12]. For different biofluids, the standard sample volume required for most types of analyses is within the range of 0.1 to 0.5 mL. "
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    ABSTRACT: Thyroid cancer is the most common endocrine malignancy with four major types distinguished on the basis of histopathological features: papillary, follicular, medullary, and anaplastic. Classification of thyroid cancer is the primary step in the assessment of prognosis and selection of the treatment. However, in some cases, cytological and histological patterns are inconclusive; hence, classification based on histopathology could be supported by molecular biomarkers, including markers identified with the use of high-throughput “omics” techniques. Beside genomics, transcriptomics, and proteomics, metabolomic approach emerges as the most downstream attitude reflecting phenotypic changes and alterations in pathophysiological states of biological systems. Metabolomics using mass spectrometry and magnetic resonance spectroscopy techniques allows qualitative and quantitative profiling of small molecules present in biological systems. This approach can be applied to reveal metabolic differences between different types of thyroid cancer and to identify new potential candidates for molecular biomarkers. In this review, we consider current results concerning application of metabolomics in the field of thyroid cancer research. Recent studies show that metabolomics can provide significant information about the discrimination between different types of thyroid lesions. In the near future, one could expect a further progress in thyroid cancer metabolomics leading to development of molecular markers and improvement of the tumor types classification and diagnosis.
    International Journal of Endocrinology 03/2015; 2015. DOI:10.1155/2015/258763 · 1.95 Impact Factor
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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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    ABSTRACT: Since Otto Warburg, many studies have explored the unique metabolic phenotype of cancer cells highlighting the value and applicability of metabolomics in the oncology field, particularly in the development of cancer biomarkers. With respect to renal cell carcinoma (RCC), a metabolomics approach would own a great potential since urinary system is intimately connected with urine and, this biofluid, offers some advantages allowing the development of an assay suitable for use in clinical practice. Moreover, the assessment of metabolic derangements characteristics of RCC might provide a complete health assessment of this pathology, enabling the development of novel targeted therapies and even the stratification of responsive patients to specific therapeutic options improving the effectiveness of therapy. Metabolomic studies performed so far showed that the RCC metabolic signature is characterized by alterations in metabolites related to energy metabolic pathways, particularly glycolysis, amino acid and fatty acid catabolism, known to be crucial to cell proliferation. Despite some of those alterations are common to carcinogenesis, the potential role of acylcarnitines, gentisate, α-ketoglutarate and quinolinate in RCC pathophysiology has been proposed recently. The ability of metabolomics to discriminate between RCC and normal samples shows convincing evidence of its applicability in RCC management. Furthermore, the studies already carried out have not only tried to unveil the metabolic profile of RCC but also to evaluate the impact of some factors, namely technical, in RCC-metabolomics research. This type of study is pivotal in the design of metabolomics studies, helping to increase the reliability of the results. The present review updates the current knowledge on the metabolic alterations recognized in the RCC, and provides insight to the characteristics, strengths, limitations, and recent advances in RCC-metabolomics studies, always keeping in mind its potential application in clinical/health areas as a biomarker discovery tool.
    Metabolomics 12/2014; 10(6). DOI:10.1007/s11306-014-0659-5 · 3.86 Impact Factor
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