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Metabolomics

, 14:154 | Cite as

Targeted metabolomic profiling of low and high grade serous epithelial ovarian cancer tissues: a pilot study

  • Gunjal Garg
  • Ali YilmazEmail author
  • Praveen Kumar
  • Onur Turkoglu
  • David G. Mutch
  • Matthew A. Powell
  • Barry Rosen
  • Ray O. Bahado-Singh
  • Stewart F. Graham
Original Article

Abstract

Introduction

Epithelial ovarian cancer (EOC) remains the leading cause of death from gynecologic malignancies and has an alarming global fatality rate. Besides the differences in underlying pathogenesis, distinguishing between high grade (HG) and low grade (LG) EOC is imperative for the prediction of disease progression and responsiveness to chemotherapy.

Objectives

The aim of this study was to investigate, the tissue metabolome associated with HG and LG serous epithelial ovarian cancer.

Methods

A combination of one dimensional proton nuclear magnetic resonance (1D H NMR) spectroscopy and targeted mass spectrometry (MS) was employed to profile the tissue metabolome of HG, LG serous EOCs, and controls.

Results

Using partial least squares-discriminant analysis, we observed significant separation between all groups (p < 0.05) following cross validation. We identified which metabolites were significantly perturbed in each EOC grade as compared with controls and report the biochemical pathways which were perturbed due to the disease. Among these metabolic pathways, ascorbate and aldarate metabolism was identified, for the first time, as being significantly altered in both LG and HG serous cancers. Further, we have identified potential biomarkers of EOC and generated predictive algorithms with AUC (CI) = 0.940 and 0.929 for HG and LG, respectively.

Conclusion

These previously unreported biochemical changes provide a framework for future metabolomic studies for the development of EOC biomarkers. Finally, pharmacologic targeting of the key metabolic pathways identified herein could lead to novel and effective treatments of EOC.

Keywords

Serous ovarian cancer 1H NMR Targeted mass spectrometry Metabolomics Multivariate data analysis 

Notes

Acknowledgements

This research was supported by seed grant funding from the Cancer Research Seed Grant Award at Beaumont Health.

Author contributions

RBS supervised and designed the experiment, SFG and GG supervised all experimental procedures, AY and PK collected the metabolomics data, AY wrote the manuscript, AY performed statistical data analysis and bioinformatics, all authors read and reviewed the manuscript.

Compliance with ethical standards

Conflict of interest

The authors report no conflict of interest.

Supplementary material

11306_2018_1448_MOESM1_ESM.docx (481 kb)
Supplementary material 1 (DOCX 480 KB)

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Gunjal Garg
    • 1
  • Ali Yilmaz
    • 2
    Email author return OK on get
  • Praveen Kumar
    • 2
  • Onur Turkoglu
    • 2
  • David G. Mutch
    • 3
  • Matthew A. Powell
    • 3
  • Barry Rosen
    • 2
  • Ray O. Bahado-Singh
    • 2
  • Stewart F. Graham
    • 2
  1. 1.Karmanos Cancer Institute Mclaren FlintFlintUSA
  2. 2.Department of Obstetrics and GynecologyWilliam Beaumont HealthRoyal OakUSA
  3. 3.Department of Obstetrics and GynecologyWashington University School of MedicineSt. LouisUSA

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