Dataset Information

GC-MS metabolomics-based approach for the identification of a potential VOC-biomarker panel in the urine of renal cell carcinoma patients.

ABSTRACT: The analysis of volatile organic compounds (VOCs) emanating from biological samples appears as one of the most promising approaches in metabolomics for the study of diseases, namely cancer. In fact, it offers advantages, such as non-invasiveness and robustness for high-throughput applications. The purpose of this work was to study the urinary volatile metabolic profile of patients with renal cell carcinoma (RCC) (n = 30) and controls (n = 37) with the aim of identifying a potential specific urinary volatile pattern as a non-invasive strategy to detect RCC. Moreover, the effect of some confounding factors such as age, gender, smoking habits and body mass index was evaluated as well as the ability of urinary VOCs to discriminate RCC subtypes and stages. A headspace solid-phase microextraction/gas chromatography-mass spectrometry-based method was performed, followed by multivariate data analysis. A variable selection method was applied to reduce the impact of potential redundant and noisy chromatographic variables, and all models were validated by Monte Carlo cross-validation and permutation tests. Regarding the effect of RCC on the urine VOCs composition, a panel of 21 VOCs descriptive of RCC was defined, capable of discriminating RCC patients from controls in principal component analysis. Discriminant VOCs were further individually validated in two independent samples sets (nine RCC patients and 12 controls, seven RCC patients with diabetes mellitus type 2) by univariate statistical analysis. Two VOCs were found consistently and significantly altered between RCC and controls (2-oxopropanal and, according to identification using NIST14, 2,5,8-trimethyl-1,2,3,4-tetrahydronaphthalene-1-ol), strongly suggesting enhanced potential as RCC biomarkers. Gender, smoking habits and body mass index showed negligible and age-only minimal effects on the urinary VOCs, compared to the deviations resultant from the disease. Moreover, in this cohort, the urinary volatilome did not show ability to discriminate RCC stages and histological subtypes. The results validated the value of urinary volatilome for the detection of RCC and advanced with the identification of potential RCC urinary biomarkers.

SUBMITTER: Monteiro M

PROVIDER: S-EPMC5571542 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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GC-MS metabolomics-based approach for the identification of a potential VOC-biomarker panel in the urine of renal cell carcinoma patients.

Monteiro Márcia M Moreira Nathalie N Pinto Joana J Pires-Luís Ana S AS Henrique Rui R Jerónimo Carmen C Bastos Maria de Lourdes ML Gil Ana M AM Carvalho Márcia M Guedes de Pinho Paula P

Journal of cellular and molecular medicine 20170404 9

The analysis of volatile organic compounds (VOCs) emanating from biological samples appears as one of the most promising approaches in metabolomics for the study of diseases, namely cancer. In fact, it offers advantages, such as non-invasiveness and robustness for high-throughput applications. The purpose of this work was to study the urinary volatile metabolic profile of patients with renal cell carcinoma (RCC) (n = 30) and controls (n = 37) with the aim of identifying a potential specific urin ...[more]

PMID: 28378454

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Project description:(1) Background: The ability to determine the age of ginseng is very important because the price of ginseng depends on the cultivation period. Since morphological observation is subjective, a new scientific and systematic method for determining the age of ginseng is required. (2) Methods: Three techniques were used for a metabolomics approach. High-resolution magic-angle-spinning nuclear magnetic resonance (HR-MAS NMR) spectroscopy was used to analyze powdered ginseng samples without extraction. Ultrahigh-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-QTOF/MS) and gas chromatography quadrupole time-of-fight mass spectrometry (GC-TOF/MS) were used to analyze the extracts of 4-, 5-, and 6-year-old ginseng. (3) Results: A metabolomics approach has the potential to discriminate the age of ginseng. Among the primary metabolites detected from NMR spectroscopy, the levels of fumarate and choline showed moderate prediction with an area under the curve (AUC) value of more than 0.7. As a result of UPLC-QTOF/MS-based profiling, 61 metabolites referring to the VIP (variable importance in the projection) score contributed to discriminating the age of ginseng. The results of GC×GC-TOF/MS showed clear discrimination of 4-, 5-, and 6-year-old ginseng using orthogonal partial least-squares discriminant analysis (OPLS-DA) to 100% of the discrimination rate. The results of receiver operating characteristic (ROC) analysis, 16 metabolites between 4- and 5-year-old ginseng, and 18 metabolites between 5- and 6-year-old ginseng contributed to age discrimination in all regions. (4) Conclusions: These results showed that metabolic profiling and multivariate statistical analyses can distinguish the age of ginseng. Especially, it is meaningful that ginseng samples from different areas had the same metabolites for age discrimination. In future studies, it will be necessary to identify the unknown variables and to collaboratively study with other fields the biochemistry of aging in ginseng.

Project description:BackgroundMulberry (Morus multicaulis) branch bark powder have showed effective hypoglycemic activity in our previous research. This study aims to explore the mechanism of protect effect on diabetes mice of mulberry branch bark as food supplement based on non-targeted GC-MS metabolomics' platform.MethodsAnimal model of double diabetes was established with high fat diet and Streptozotocin injection. Mice were fed with mulberry branch bark powder (MBBP) for five weeks to study its therapeutic effect. The metabolite feature of diabetes model and treatment group mice were characterized using a gas chromatography-mass spectrometry-based metabolomics, complemented with the biochemical evaluation, histological inspection, immunohistochemistry observations and enzyme protein detection.ResultsA panel of endogenous metabolites were revealed that are relevant to disturbed metabolic processes among groups. The serum metabolic profiles were significantly different between the model group and treatment group. The manner of MBBP treatment showed to be significantly dose dependent and 20% MBBP treatment gain a relatively greater benefit than others. The metabolic disorders in model group include enhanced activation of the sorbitol pathway and galactose metabolite, increased activities of gluconeogenesis, fatty acid oxidation, proteins catabolism and attenuated activities of pentose phosphate pathway, glycolysis and aerobic oxidation pathways, internal synthesis of cholesterol, inositol production. MBBP treatment ameliorate these abnormal metabolize as revealed by differential metabolites comparing with that of model mice, such as decreasing the accumulation of ketone body, enhancing NADPH biosynthesis, partially reversing oxidative stress and energy metabolism disturbance.ConclusionsMulberry branch bark had a re-balancing effect on the disturbed metabolic pathways in the diabetic mice. Based on the metabolic pathways network, oral administration of MBBP could ameliorate the hyperglycemia and hyperlipidemia symptoms in a global scale and restore the abnormal metabolic state to a near normal level in a dose dependent pattern.

Dataset Information

GC-MS metabolomics-based approach for the identification of a potential VOC-biomarker panel in the urine of renal cell carcinoma patients.

Publications

GC-MS metabolomics-based approach for the identification of a potential VOC-biomarker panel in the urine of renal cell carcinoma patients.

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