Literature DB >> 22736106

Revealing the metabonomic variation of EC using ¹H-NMR spectroscopy and its association with the clinicopathological characteristics.

Ayshamgul Hasim1, Hong Ma, Batur Mamtimin, Abulizi Abudula, Madiniyet Niyaz, Li-Wei Zhang, Juret Anwer, Ilyar Sheyhidin.   

Abstract

In this study, (1)H NMR-based metabonomics has been applied to investigate esophageal cancer metabolic signatures in plasma and urine, purpose of assessing the diagnostic potential of this approach and gaining novel insights into esophageal cancer metabolism and systemic effects. Plasma and urine samples from esophageal cancer patients (n = 108) and a control healthy group (n = 40) were analyzed by Nuclear Magnetic Resonance (NMR) spectroscopy (600 MHz), and their spectral profiles subjected to Orthogonal Projections to Latent Structures (OPLS-DA) for multivariate statistics. Potential metabolic biomarkers were identified using data base comparisons used for examining the significance of metabolites. Compared to healthy controls, esophageal cancer plasma had higher levels of dimethylamine, α-glucose, β-glucose, citric acid, together with lower levels of Leucine, alanine, isoleucine, valine, glycoprotein, lactate, acetone, acetate, choline, isobutyrate, unsaturated lipid, VLDL, LDL, 1-methylhistidine; Compared to healthy controls, esophageal cancer urine had higher levels of Mannitol, glutamate, γ-propalanine, phenylalanine, acetate, allantoin, pyruvate, tyrosine, β-glucose and guinolinate, together with lower levels of N-acetylcysteine, valine, dihydrothymine, hippurate, methylguanidine, 1-methylnicotin- amide and Citric acid; Very good discrimination between cancer and control groups was achieved by multivariate modeling of plasma and urinary profiles. (1)H NMR-based metabolite profiling analysis was shown to be an effective approach to differentiating between patients with EC and healthy subjects. Good sensitivity and selectivity were shown by using the metabolite markers discovered to predict the classification of samples from the healthy control group and the patients with the disease. Plasma and urine metabolic profiling may have potential for early diagnosis of EC and may enhance our understanding of its mechanisms.

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Year:  2012        PMID: 22736106     DOI: 10.1007/s11033-012-1764-z

Source DB:  PubMed          Journal:  Mol Biol Rep        ISSN: 0301-4851            Impact factor:   2.316


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