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Metabolomic prediction of endometrial cancer

To access, purchase, authenticate, or subscribe to the full-text of this article, please visit this link: http://dx.doi.org/10.1007/s11306-017-1290-z Byline: Ray O. Bahado-Singh (1), Amit Lugade (2), Jayson Field (3), Zaid Al-Wahab (3), BeomSoo Han (4), Rupasri Mandal (4), Trent C. Bjorndahl (4), On... Full description

Journal Title: Metabolomics 2018, Vol.14(1), pp.1-9
Main Author: Bahado-Singh, Ray
Other Authors: Lugade, Amit , Field, Jayson , Al-Wahab, Zaid , Han, BeomSoo , Mandal, Rupasri , Bjorndahl, Trent , Turkoglu, Onur , Graham, Stewart , Wishart, David , Odunsi, Kunle
Format: Electronic Article Electronic Article
Language: English
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ID: ISSN: 1573-3882 ; E-ISSN: 1573-3890 ; DOI: 10.1007/s11306-017-1290-z
Link: http://dx.doi.org/10.1007/s11306-017-1290-z
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recordid: springer_jour10.1007/s11306-017-1290-z
title: Metabolomic prediction of endometrial cancer
format: Article
creator:
  • Bahado-Singh, Ray
  • Lugade, Amit
  • Field, Jayson
  • Al-Wahab, Zaid
  • Han, BeomSoo
  • Mandal, Rupasri
  • Bjorndahl, Trent
  • Turkoglu, Onur
  • Graham, Stewart
  • Wishart, David
  • Odunsi, Kunle
subjects:
  • Endometrial cancer
  • Metabolomics
  • Biomarker
  • Nuclear magnetic resonance
  • Mass spectrometry
ispartof: Metabolomics, 2018, Vol.14(1), pp.1-9
description: To access, purchase, authenticate, or subscribe to the full-text of this article, please visit this link: http://dx.doi.org/10.1007/s11306-017-1290-z Byline: Ray O. Bahado-Singh (1), 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) Keywords: Endometrial cancer; Metabolomics; Biomarker; Nuclear magnetic resonance; Mass spectrometry Abstract: Introduction 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. Objective To determine whether metabolomic based biomarkers can detect EC overall and early-stage EC. Methods 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. Results 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. Conclusions 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. Author Affiliation: (1) Department of Obstetrics and Gynecology, William Beaumont Health, Royal Oak, MI, 48073, USA (2) Center for Immunotherapy, Roswell Park Cancer Institute, Buffalo, NY, USA (3) Department of Gynecologic Oncology, William Beaumont Health, Roya
language: eng
source:
identifier: ISSN: 1573-3882 ; E-ISSN: 1573-3890 ; DOI: 10.1007/s11306-017-1290-z
fulltext: fulltext
issn:
  • 1573-3890
  • 15733890
  • 1573-3882
  • 15733882
url: Link


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titleMetabolomic prediction of endometrial cancer
creatorBahado-Singh, Ray ; Lugade, Amit ; Field, Jayson ; Al-Wahab, Zaid ; Han, BeomSoo ; Mandal, Rupasri ; Bjorndahl, Trent ; Turkoglu, Onur ; Graham, Stewart ; Wishart, David ; Odunsi, Kunle
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descriptionTo access, purchase, authenticate, or subscribe to the full-text of this article, please visit this link: http://dx.doi.org/10.1007/s11306-017-1290-z Byline: Ray O. Bahado-Singh (1), 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) Keywords: Endometrial cancer; Metabolomics; Biomarker; Nuclear magnetic resonance; Mass spectrometry Abstract: Introduction 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. Objective To determine whether metabolomic based biomarkers can detect EC overall and early-stage EC. Methods 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. Results 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. Conclusions 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. Author Affiliation: (1) Department of Obstetrics and Gynecology, William Beaumont Health, Royal Oak, MI, 48073, USA (2) Center for Immunotherapy, Roswell Park Cancer Institute, Buffalo, NY, USA (3) Department of Gynecologic Oncology, William Beaumont Health, Royal Oak, MI, USA (4) Departments of Biological Sciences, University of Alberta, Edmonton, AB, T6G 2E8, Canada (5) Department of Computing Sciences, University of Alberta, Edmonton, AB, T6G 2E8, Canada (6) Department of Gynecologic Oncology, Roswell Park Cancer Institute, Buffalo, NY, USA Article History: Registration Date: 25/10/2017 Received Date: 13/06/2017 Accepted Date: 25/10/2017 Online Date: 01/12/2017 Article note: Electronic supplementary material The online version of this article ( https://doi.org/10.1007/s11306-017-1290-z) contains supplementary material, which is available to authorized users.
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