2016
DOI: 10.3389/fnins.2016.00156
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Reconstructed Metabolic Network Models Predict Flux-Level Metabolic Reprogramming in Glioblastoma

Abstract: Developments in genome scale metabolic modeling techniques and omics technologies have enabled the reconstruction of context-specific metabolic models. In this study, glioblastoma multiforme (GBM), one of the most common and aggressive malignant brain tumors, is investigated by mapping GBM gene expression data on the growth-implemented brain specific genome-scale metabolic network, and GBM-specific models are generated. The models are used to calculate metabolic flux distributions in the tumor cells. Metabolic… Show more

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Cited by 32 publications
(29 citation statements)
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References 69 publications
(122 reference statements)
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“…The second step was the refinement of the transformations identified in step one based on genome scale metabolic models (i.e., astrocyte specificity) (Schultz and Cutub, 2016). In this regard, we used the astrocyte-neuronal metabolic model published by Özcan and Çakır (2016). The model provided curated astrocyte-specific metabolic information for 276 metabolites interacting across 375 reactions.…”
Section: Methodsmentioning
confidence: 99%
“…The second step was the refinement of the transformations identified in step one based on genome scale metabolic models (i.e., astrocyte specificity) (Schultz and Cutub, 2016). In this regard, we used the astrocyte-neuronal metabolic model published by Özcan and Çakır (2016). The model provided curated astrocyte-specific metabolic information for 276 metabolites interacting across 375 reactions.…”
Section: Methodsmentioning
confidence: 99%
“…Many of the cell's systems undergo major reprogramming as part of the tumorigenesis of GBM, some of the most significant alterations can be observed in the metabolic system (Agnihotri and Zadeh, 2016;Ozcan and Cakir, 2016). Metabolism is the collective name for the many integrated biochemical reactions in the body that are responsible for the uptake and conversion of nutrients to energy and building blocks for the cell as well as elimination of cellular waste.…”
Section: Introductionmentioning
confidence: 99%
“…System approaches integrates mathematical model formulations with computational modellings, that could represent the biochemical knowledge used to strengthen experimental results (Palsson, 2009 ; Hyduke et al, 2013 ). The expression of biological phenomena using mathematical models has been used to understand how information, energy and matter behaves in the cell and to get an efficient statistical inference in experimental research by studying the dynamical behavior of cell (Najafi et al, 2014 ; Vanlier et al, 2014 ; Özcan and Çakır, 2016 ; Rajkumar et al, 2016 ).…”
Section: Introductionmentioning
confidence: 99%