Mass spectrometry-based metabolic profiling reveals different metabolite patterns in invasive ovarian carcinomas and ovarian borderline tumors

Carsten Denkert, Jan Budczies, Tobias Kind, Wilko Weichert, Peter Tablack, Jalid Sehouli, Silvia Niesporek, Dominique Könsgen, Manfred Dietel, Oliver Fiehn

Research output: Contribution to journalArticle

285 Citations (Scopus)

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.

Original languageEnglish (US)
Pages (from-to)10795-10804
Number of pages10
JournalCancer Research
Volume66
Issue number22
DOIs
StatePublished - Nov 15 2006

Fingerprint

Mass Spectrometry
Carcinoma
Neoplasms
Principal Component Analysis
Gas Chromatography
Metabolomics
Genomics
Proteomics
Ovary

ASJC Scopus subject areas

  • Cancer Research
  • Oncology

Cite this

Mass spectrometry-based metabolic profiling reveals different metabolite patterns in invasive ovarian carcinomas and ovarian borderline tumors. / Denkert, Carsten; Budczies, Jan; Kind, Tobias; Weichert, Wilko; Tablack, Peter; Sehouli, Jalid; Niesporek, Silvia; Könsgen, Dominique; Dietel, Manfred; Fiehn, Oliver.

In: Cancer Research, Vol. 66, No. 22, 15.11.2006, p. 10795-10804.

Research output: Contribution to journalArticle

Denkert, C, Budczies, J, Kind, T, Weichert, W, Tablack, P, Sehouli, J, Niesporek, S, Könsgen, D, Dietel, M & Fiehn, O 2006, 'Mass spectrometry-based metabolic profiling reveals different metabolite patterns in invasive ovarian carcinomas and ovarian borderline tumors', Cancer Research, vol. 66, no. 22, pp. 10795-10804. https://doi.org/10.1158/0008-5472.CAN-06-0755
Denkert, Carsten ; Budczies, Jan ; Kind, Tobias ; Weichert, Wilko ; Tablack, Peter ; Sehouli, Jalid ; Niesporek, Silvia ; Könsgen, Dominique ; Dietel, Manfred ; Fiehn, Oliver. / Mass spectrometry-based metabolic profiling reveals different metabolite patterns in invasive ovarian carcinomas and ovarian borderline tumors. In: Cancer Research. 2006 ; Vol. 66, No. 22. pp. 10795-10804.
@article{04c58efef5a3430ab11c279ab34fc955,
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.",
author = "Carsten Denkert and Jan Budczies and Tobias Kind and Wilko Weichert and Peter Tablack and Jalid Sehouli and Silvia Niesporek and Dominique K{\"o}nsgen and Manfred Dietel and Oliver Fiehn",
year = "2006",
month = "11",
day = "15",
doi = "10.1158/0008-5472.CAN-06-0755",
language = "English (US)",
volume = "66",
pages = "10795--10804",
journal = "Journal of Cancer Research",
issn = "0099-7013",
publisher = "American Association for Cancer Research Inc.",
number = "22",

}

TY - JOUR

T1 - Mass spectrometry-based metabolic profiling reveals different metabolite patterns in invasive ovarian carcinomas and ovarian borderline tumors

AU - Denkert, Carsten

AU - Budczies, Jan

AU - Kind, Tobias

AU - Weichert, Wilko

AU - Tablack, Peter

AU - Sehouli, Jalid

AU - Niesporek, Silvia

AU - Könsgen, Dominique

AU - Dietel, Manfred

AU - Fiehn, Oliver

PY - 2006/11/15

Y1 - 2006/11/15

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=33845314350&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33845314350&partnerID=8YFLogxK

U2 - 10.1158/0008-5472.CAN-06-0755

DO - 10.1158/0008-5472.CAN-06-0755

M3 - Article

C2 - 17108116

AN - SCOPUS:33845314350

VL - 66

SP - 10795

EP - 10804

JO - Journal of Cancer Research

JF - Journal of Cancer Research

SN - 0099-7013

IS - 22

ER -