ArticleFrontiers in neuroscience2016
Reconstructed Metabolic Network Models Predict Flux-Level Metabolic Reprogramming in Glioblastoma.
Article in Frontiers in neuroscience, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
22 citing papers in PubMed.
- Mathematical Modeling in Cancer Metabolism: Tools for Translational Applications in Metabolism-Based Therapy.Advances in experimental medicine and biology · 2026Review
- Integrative systems biology approaches for analyzing microbiome dysbiosis and species interactions.Briefings in bioinformatics · 2025Review
- Genome-scale models in human metabologenomics.Nature reviews. Genetics · 2025Review
- Exosomal miR-21-5p from glioma associated mesenchymal stem cells promotes the progression and glycolysis of glioblastoma via PDHA1.Scientific reports · 2025Article
- Unveiling the Molecular Mechanisms of Glioblastoma through an Integrated Network-Based Approach.Biomedicines · 2024Article
- FBA-PRCC. Partial Rank Correlation Coefficient (PRCC) Global Sensitivity Analysis (GSA) in Application to Constraint-Based Models.Biomolecules · 2023Article
- Identification of Therapeutic Targets for Medulloblastoma by Tissue-Specific Genome-Scale Metabolic Model.Molecules (Basel, Switzerland) · 2023Article
- Review of Current Human Genome-Scale Metabolic Models for Brain Cancer and Neurodegenerative Diseases.Cells · 2022Review
- Constraint-Based Reconstruction and Analyses of Metabolic Models: Open-Source Python Tools and Applications to Cancer.Frontiers in oncology · 2022Review
- Systems Biology Approaches to Decipher the Underlying Molecular Mechanisms of Glioblastoma Multiforme.International journal of molecular sciences · 2021Review
- The genotypic and phenotypic impact of hypoxia microenvironment on glioblastoma cell lines.BMC cancer · 2021Article
- Current Perspective on the Natural Compounds and Drug Delivery Techniques in Glioblastoma Multiforme.Cancers · 2021Review
- Metabolic Drivers of Invasion in Glioblastoma.Frontiers in cell and developmental biology · 2021Review
- Glioma Stem-Like Cells and Metabolism: Potential for Novel Therapeutic Strategies.Frontiers in oncology · 2021Review
- Towards the routine use of in silico screenings for drug discovery using metabolic modelling.Biochemical Society transactions · 2020Review
- Genome-Scale Metabolic Modeling of Glioblastoma Reveals Promising Targets for Drug Development.Frontiers in genetics · 2020Article
- Discovery of therapeutic agents for prostate cancer using genome-scale metabolic modeling and drug repositioning.EBioMedicine · 2019Article
- Human Systems Biology and Metabolic Modelling: A Review-From Disease Metabolism to Precision Medicine.BioMed research international · 2019Review
- Differential Metabolism of Medium-Chain Fatty Acids in Differentiated Human-Induced Pluripotent Stem Cell-Derived Astrocytes.Frontiers in physiology · 2019Article
- Mitochondrial energy metabolism and signalling in human glioblastoma cell lines with different PTEN gene status.Journal of bioenergetics and biomembranes · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
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 phenotypes predicted by the GBM-specific metabolic models reconstructed in this work reflect the general metabolic reprogramming of GBM, reported both in in-vitro and in-vivo experiments. The computed flux profiles quantitatively predict that major sources of the acetyl-CoA and oxaloacetic acid pool used in TCA cycle are pyruvate dehydrogenase from glycolysis and anaplerotic flux from glutaminolysis, respectively. Also, our results, in accordance with recent studies, predict a contribution of oxidative phosphorylation to ATP pool via a slightly active TCA cycle in addition to the major contributor aerobic glycolysis. We verified our results by using different computational methods that incorporate transcriptome data with genome-scale models and by using different transcriptome datasets. Correct predictions of flux distributions in glycolysis, glutaminolysis, TCA cycle and lipid precursor metabolism validate the reconstructed models for further use in future to simulate more specific metabolic patterns for GBM.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.