Mass Spectrometry Letters

Korean Society for Mass Spectrometry (한국질량분석학회)
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Discovery of Urinary Biomarkers in Patients with Breast Cancer Based on Metabolomics

  • Lee, Jeongae (Molecular Recognition Research Center, Korea Institute of Science and Technology) ;
  • Woo, Han Min (Clean Energy Research Center, Korea Institute of Science and Technology) ;
  • Kong, Gu (Department of Pathology, School of Medicine, Hanyang University) ;
  • Nam, Seok Jin (Division of Breast-Endocrine Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine) ;
  • Chung, Bong Chul (Molecular Recognition Research Center, Korea Institute of Science and Technology)
  • Received : 2013.11.29
  • Accepted : 2013.12.10
  • Published : 2013.12.30
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Abstract

A metabolomics study was conducted to identify urinary biomarkers for breast cancer, using gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS), analyzed by principal components analysis (PCA) as well as a partial least squares-discriminant analysis (PLS-DA) for a metabolic pattern analysis. To find potential biomarkers, urine samples were collected from before- and after-mastectomy of breast cancer patients and healthy controls. Androgens, corticoids, estrogens, nucleosides, and polyols were quantitatively measured and urinary metabolic profiles were constructed through PCA and PLS-DA. The possible biomarkers were discriminated from quantified targeted metabolites with a metabolic pattern analysis and subsequent screening. We identified two biomarkers for breast cancer in urine, ${\beta}$-cortol and 5-methyl-2-deoxycytidine, which were categorized at significant levels in a student t-test (p-value < 0.05). The concentrations of these metabolites in breast cancer patients significantly increased relative to those of controls and patients after mastectomy. Biomarkers identified in this study were highly related to metabolites causing oxidative DNA damage in the endogenous metabolism. These biomarkers are not only useful for diagnostics and patient stratification but can be mapped on a biochemical chart to identify the corresponding enzyme for target identification via metabolomics.

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