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Permanent link (DOI): https://doi.org/10.7939/R3MM2D

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Application of ROC curve analysis to metabolomics data sets for the detection of cancer in a mouse model Open Access

Descriptions

Other title
Subject/Keyword
Mouse model
Detection
ROC curve
Cancer
Metabolomics
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Moroz, Jennifer
Supervisor and department
Gino Fallone (Oncology)
Alasdair Syme (Oncology)
Examining committee member and department
Jack Tuszynski (Physics)
Nicola De Zanche (Oncology)
Keith Wachowicz (Oncology)
Department
Department of Physics
Specialization

Date accepted
2010-09-30T20:06:24Z
Graduation date
2010-11
Degree
Master of Science
Degree level
Master's
Abstract
The goal of this study was to show that quantifiable metabolic changes may be used to screen for cancer. NIH III nude mice (n=22) were injected with human GBM cells, with daily urine samples collected pre and post-injection. 14 mice were injected with saline to serve as controls. The measurement of metabolite concentrations took place on an 800 MHz NMR spectrometer. 34 metabolites were identified and quantified, through targeted profiling, with Chenomx Suite 5.1. Univariate statistical analysis showed that 3 metabolites (2-oxoglutarate, glucose and trimethylamine n-oxide) were significantly altered in the presence of tumour, while PCA and PLS-DA models found the maximum variance between the healthy and tumour-bearing groups. Receiver operating characteristic (ROC) curve analysis was applied to the data set to provide a measure of clinical utility. ROC statistics were as high as 0.85 for the analysis of individual metabolites, 0.939 for the analysis of metabolite pairs and 0.996 for PLS-DA models. These results show that metabolomics has potential as a screening tool for cancer.
Language
English
DOI
doi:10.7939/R3MM2D
Rights
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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