The integrative metabolomic-transcriptomic landscape of glioblastome multiforme
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Dieter Henrik Heiland1,5, Jakob Wörner2, Jan Gerrit Haaker1,5, Daniel Delev1,5, Nils Pompe2, Bianca Mercas1,5, Pamela Franco1,5, Annette Gäbelein1,5, Sabrina Heynckes1,5, Dietmar Pfeifer3,5, Stefan Weber2, Irina Mader4,5 and Oliver Schnell1,5
1Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg, Germany
2Institute of Physical Chemistry, Faculty of Chemistry and Pharmacy, University of Freiburg, Freiburg, Germany
3Department of Hematology, Oncology and Stem Cell Transplantation, Medical Center, University of Freiburg, Freiburg, Germany
4Department of Neuroradiology, Medical Center, University of Freiburg, Freiburg, Germany
5Faculty of Medicine, University of Freiburg, Freiburg, Germany
Dieter Henrik Heiland, email: email@example.com
Keywords: metabolomics, transcriptomics, network analysis, glioblastoma multiforme, WGCNA
Received: January 02, 2017 Accepted: February 23, 2017 Published: March 24, 2017
The purpose of this study was to map the landscape of metabolic-transcriptional alterations in glioblastoma multiforme. Omic-datasets were acquired by metabolic profiling (1D-NMR spectroscopy n=33 Patient) and transcriptomic profiling (n=48 Patients). Both datasets were analyzed by integrative network modeling. The computed model concluded in four different metabolic-transcriptomic signatures containing: oligodendrocytic differentiation, cell-cycle functions, immune response and hypoxia. These clusters were found being distinguished by individual metabolism and distinct transcriptional programs. The study highlighted the association between metabolism and hallmarks of oncogenic signaling such as cell-cycle alterations, immune escape mechanism and other cancer pathway alterations. In conclusion, this study showed the strong influence of metabolic alterations in the wide scope of oncogenic transcriptional alterations.
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