Dataset Information

Esophageal cancer metabolite biomarkers detected by LC-MS and NMR methods.

ABSTRACT:

Background

Esophageal adenocarcinoma (EAC) is a rarely curable disease and is rapidly rising worldwide in incidence. Barret's esophagus (BE) and high-grade dysplasia (HGD) are considered major risk factors for invasive adenocarcinoma. In the current study, unbiased global metabolic profiling methods were applied to serum samples from patients with EAC, BE and HGD, and healthy individuals, in order to identify metabolite based biomarkers associated with the early stages of EAC with the goal of improving prognostication.

Methodology/principal findings

Serum metabolite profiles from patients with EAC (n?=?67), BE (n?=?3), HGD (n?=?9) and healthy volunteers (n?=?34) were obtained using high performance liquid chromatography-mass spectrometry (LC-MS) methods. Twelve metabolites differed significantly (p<0.05) between EAC patients and healthy controls. A partial least-squares discriminant analysis (PLS-DA) model had good accuracy with the area under the receiver operative characteristic curve (AUROC) of 0.82. However, when the results of LC-MS were combined with 8 metabolites detected by nuclear magnetic resonance (NMR) in a previous study, the combination of NMR and MS detected metabolites provided a much superior performance, with AUROC?=?0.95. Further, mean values of 12 of these metabolites varied consistently from healthy controls to the high-risk individuals (BE and HGD patients) and EAC subjects. Altered metabolic pathways including a number of amino acid pathways and energy metabolism were identified based on altered levels of numerous metabolites.

Conclusions/significance

Metabolic profiles derived from the combination of LC-MS and NMR methods readily distinguish EAC patients and potentially promise important routes to understanding the carcinogenesis and detecting the cancer. Differences in the metabolic profiles between high-risk individuals and the EAC indicate the possibility of identifying the patients at risk much earlier to the development of the cancer.

SUBMITTER: Zhang J

PROVIDER: S-EPMC3264576 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Publications

Esophageal cancer metabolite biomarkers detected by LC-MS and NMR methods.

Zhang Jian J Bowers Jeremiah J Liu Lingyan L Wei Siwei S Gowda G A Nagana GA Hammoud Zane Z Raftery Daniel D

PloS one 20120123 1

<h4>Background</h4>Esophageal adenocarcinoma (EAC) is a rarely curable disease and is rapidly rising worldwide in incidence. Barret's esophagus (BE) and high-grade dysplasia (HGD) are considered major risk factors for invasive adenocarcinoma. In the current study, unbiased global metabolic profiling methods were applied to serum samples from patients with EAC, BE and HGD, and healthy individuals, in order to identify metabolite based biomarkers associated with the early stages of EAC with the go ...[more]

PMID: 22291914

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Dataset Information

Esophageal cancer metabolite biomarkers detected by LC-MS and NMR methods.

Background

Methodology/principal findings

Conclusions/significance

Publications

Esophageal cancer metabolite biomarkers detected by LC-MS and NMR methods.

Similar Datasets

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