, 14:6 | Cite as

Metabolomic prediction of endometrial cancer

  • Ray O. Bahado-SinghEmail author
  • Amit Lugade
  • Jayson Field
  • Zaid Al-Wahab
  • BeomSoo Han
  • Rupasri Mandal
  • Trent C. Bjorndahl
  • Onur Turkoglu
  • Stewart F. Graham
  • David Wishart
  • Kunle Odunsi
Original Article



Endometrial cancer (EC) is associated with metabolic disturbances including obesity, diabetes and metabolic syndrome. Identifying metabolite biomarkers for EC detection has a crucial role in reducing morbidity and mortality.


To determine whether metabolomic based biomarkers can detect EC overall and early-stage EC.


We performed NMR and mass spectrometry based metabolomic analyses of serum in EC cases versus controls. A total of 46 early-stage (FIGO stages I–II) and 10 late-stage (FIGO stages III–IV) EC cases constituted the study group. A total of 60 unaffected control samples were used. Patients and controls were divided randomly into a discovery group (n = 69) and an independent validation group (n = 47). Predictive algorithms based on biomarkers and demographic characteristics were generated using logistic regression analysis.


A total of 181 metabolites were evaluated. Extensive changes in metabolite levels were noted in the EC versus the control group. The combination of C14:2, phosphatidylcholine with acyl-alkyl residue sum C38:1 (PCae C38:1) and 3-hydroxybutyric acid had an area under the receiver operating characteristics curve (AUC) (95% CI) = 0.826 (0.706–0.946) and a sensitivity = 82.6%, and specificity = 70.8% for EC overall. For early EC prediction: BMI, C14:2 and PC ae C40:1 had an AUC (95% CI) = 0.819 (0.689–0.95) and a sensitivity = 72.2% and specificity = 79.2% in the validation group.


EC is characterized by significant perturbations in important cellular metabolites. Metabolites accurately detected early-stage EC cases and EC overall which could lead to the development of non-invasive biomarkers for earlier detection of EC and for monitoring disease recurrence.


Endometrial cancer Metabolomics Biomarker Nuclear magnetic resonance Mass spectrometry 


Compliance with ethical standards

Conflict of interest

The authors declare no potential conflicts of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The study protocol was approved by the IRB - I 03103 “RPCI Data Bank and BioRepository (DBBR)”. Samples and de-identified clinical data was distributed for analysis under RPCI IRB-approved protocol BDR 048414 “Metabolomic analysis of gynecologic and non-gynecologic cancers: a pilot study”.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Supplementary material

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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  • Ray O. Bahado-Singh
    • 1
    Email author
  • Amit Lugade
    • 2
  • Jayson Field
    • 3
  • Zaid Al-Wahab
    • 3
  • BeomSoo Han
    • 4
  • Rupasri Mandal
    • 4
  • Trent C. Bjorndahl
    • 4
  • Onur Turkoglu
    • 1
  • Stewart F. Graham
    • 1
  • David Wishart
    • 4
    • 5
  • Kunle Odunsi
    • 2
    • 6
  1. 1.Department of Obstetrics and GynecologyWilliam Beaumont HealthRoyal OakUSA
  2. 2.Center for ImmunotherapyRoswell Park Cancer InstituteBuffaloUSA
  3. 3.Department of Gynecologic OncologyWilliam Beaumont HealthRoyal OakUSA
  4. 4.Departments of Biological SciencesUniversity of AlbertaEdmontonCanada
  5. 5.Department of Computing SciencesUniversity of AlbertaEdmontonCanada
  6. 6.Department of Gynecologic OncologyRoswell Park Cancer InstituteBuffaloUSA

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