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Journal of Oncology
Volume 2011 (2011), Article ID 174019, 9 pages
http://dx.doi.org/10.1155/2011/174019
Research Article

Metabolomic Characterization of Ovarian Epithelial Carcinomas by HRMAS-NMR Spectroscopy

1Biophysics and Nuclear Medicine Department, University Hospitals of Strasbourg, 67098 Strasbourg, France
2University of Strasbourg, CNRS LINC UMR 7237, 67081 Strasbourg, France
3University of Strasbourg, Institute of Chemistry, CNRS UMR 7177, 67081 Strasbourg, France
4Pathology Department, University Hospitals of Strasbourg, 67098, France
5Bruker BioSpin, 67160 Wissembourg, France

Received 10 November 2010; Revised 3 February 2011; Accepted 28 February 2011

Academic Editor: Nelson N. H. Teng

Copyright © 2011 D. Ben Sellem et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Objectives. The objectives of the present study are to determine if a metabolomic study by HRMAS-NMR can (i) discriminate between different histological types of epithelial ovarian carcinomas and healthy ovarian tissue, (ii) generate statistical models capable of classifying borderline tumors and (iii) establish a potential relationship with patient's survival or response to chemotherapy. Methods. 36 human epithelial ovarian tumor biopsies and 3 healthy ovarian tissues were studied using 1H HRMAS NMR spectroscopy and multivariate statistical analysis. Results. The results presented in this study demonstrate that the three histological types of epithelial ovarian carcinomas present an effective metabolic pattern difference. Furthermore, a metabolic signature specific of serous (N-acetyl-aspartate) and mucinous (N-acetyl-lysine) carcinomas was found. The statistical models generated in this study are able to predict borderline tumors characterized by an intermediate metabolic pattern similar to the normal ovarian tissue. Finally and importantly, the statistical model of serous carcinomas provided good predictions of both patient's survival rates and the patient's response to chemotherapy. Conclusions. Despite the small number of samples used in this study, the results indicate that metabolomic analysis of intact tissues by HRMAS-NMR is a promising technique which might be applicable to the therapeutic management of patients.