¹H NMR metabolomics analysis of glioblastoma subtypes: correlation between metabolomics and gene expression characteristics

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DOIResolve DOI: http://doi.org/10.1074/jbc.M111.337196
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TypeArticle
Journal titleJournal of Biological Chemistry
ISSN0021-9258
1083-351X
Volume287
Issue24
Pages2016420175; # of pages: 12
Subjectbioinformatics; glioblastoma; metabolomics; transcriptomics; tumor metabolism
AbstractGlioblastoma multiforme (GBM) is the most common form of malignant glioma, characterized by unpredictable clinical behaviors that suggest distinct molecular subtypes. With the tumor metabolic phenotype being one of the hallmarks of cancer, we have set upon to investigate whether GBMs show differences in their metabolic profiles. ¹H NMR analysis was performed on metabolite extracts from a selection of nine glioblastoma cell lines. Analysis was performed directly on spectral data and on relative concentrations of metabolites obtained from spectra using a multivariate regression method developed in this work. Both qualitative and quantitative sample clustering have shown that cell lines can be divided into four groups for which the most significantly different metabolites have been determined. Analysis shows that some of the major cancer metabolic markers (such as choline, lactate, and glutamine) have significantly dissimilar concentrations in different GBM groups. The obtained lists of metabolic markers for subgroups were correlated with gene expression data for the same cell lines. Metabolic analysis generally agrees with gene expression measurements, and in several cases, we have shown in detail how the metabolic results can be correlated with the analysis of gene expression. Combined gene expression and metabolomics analysis have shown differential expression of transporters of metabolic markers in these cells as well as some of the major metabolic pathways leading to accumulation of metabolites. Obtained lists of marker metabolites can be leveraged for subtype determination in glioblastomas.
Publication date
PublisherAmerican Society for Biochemistry and Molecular Biology
LanguageEnglish
AffiliationInformation and Communication Technologies; National Research Council Canada
Peer reviewedYes
NPARC number21269082
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Record identifier84a6222c-b0f2-4dfa-8933-b33473b45622
Record created2013-12-05
Record modified2016-05-09
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