title: Mass spectrometry-based metabolic profiling reveals different metabolite patterns in invasive ovarian carcinomas and ovarian borderline tumors.
abstract: Metabolites are the end products of cellular regulatory processes, and their levels can be regarded as the ultimate response of biological systems to genetic or environmental changes. We have used a metabolite profiling approach to test the hypothesis that quantitative signatures of primary metabolites can be used to characterize molecular changes in ovarian tumor tissues. Sixty-six invasive ovarian carcinomas and nine borderline tumors of the ovary were analyzed by gas chromatography/time-of-flight mass spectrometry (GC-TOF MS) using a novel contamination-free injector system. After automated mass spectral deconvolution, 291 metabolites were detected, of which 114 (39.1%) were annotated as known compounds. By t test statistics with P < 0.01, 51 metabolites were significantly different between borderline tumors and carcinomas, with a false discovery rate of 7.8%, estimated with repeated permutation analysis. Principal component analysis (PCA) revealed four principal components that were significantly different between both groups, with the highest significance found for the second component (P = 0.00000009). PCA as well as additional supervised predictive models allowed a separation of 88% of the borderline tumors from the carcinomas. Our study shows for the first time that large-scale metabolic profiling using GC-TOF MS is suitable for analysis of fresh frozen human tumor samples, and that there is a consistent and significant change in primary metabolism of ovarian tumors, which can be detected using multivariate statistical approaches. We conclude that metabolomics is a promising high-throughput, automated approach in addition to functional genomics and proteomics for analyses of molecular changes in malignant tumors.
authors.affiliation: Institute of Pathology and Department of Gynecology and Obstetrics, Charité University Hospital, Berlin, Germany. carsten.denkert@charite.de
authors.forename: Carsten
authors.initials: C
authors.lastname: Denkert
authors.forename: Jan
authors.initials: J
authors.lastname: Budczies
authors.forename: Tobias
authors.initials: T
authors.lastname: Kind
authors.forename: Wilko
authors.initials: W
authors.lastname: Weichert
authors.forename: Peter
authors.initials: P
authors.lastname: Tablack
authors.forename: Jalid
authors.initials: J
authors.lastname: Sehouli
authors.forename: Silvia
authors.initials: S
authors.lastname: Niesporek
authors.forename: Dominique
authors.initials: D
authors.lastname: Könsgen
authors.forename: Manfred
authors.initials: M
authors.lastname: Dietel
authors.forename: Oliver
authors.initials: O
authors.lastname: Fiehn
mesh_terms: D016000:Cluster Analysis; D005260:Female; D008401:Gas Chromatography-Mass Spectrometry / Q000379:methods; D006801:Humans; D009361:Neoplasm Invasiveness; D010051:Ovarian Neoplasms / Q000737:chemistry / Q000378:metabolism* / Q000473:pathology*; D025341:Principal Component Analysis