ArticleFrontiers in genetics2020
Genome-Scale Metabolic Modeling of Glioblastoma Reveals Promising Targets for Drug Development.
Article in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed, 38 citations in OpenAlex.
- Higher order synthetic lethals are keys to minimize cancer treatment effects on non-tumor cells.PloS one · 2026Article
- hiPSCGEM01: A Genome-Scale Metabolic Model for Fibroblast-Derived Human iPSCs.Bioengineering (Basel, Switzerland) · 2025Article
- Genome-scale metabolic modeling and machine learning unravel metabolic reprogramming and mast cell role in lung cancer: a multi-level analysis.Translational lung cancer research · 2025Article
- Genome-Scale Metabolic Modeling Identifies Synergistic Metabolites that Enhance 5-Fluorouracil Efficacy in Colon Cancer.Iranian biomedical journal · 2025Article
- Article
- Bypassing Blood-Brain Barrier and Glucose Dependency of Anti-Glioblastoma Drug Candidates Targeting Mitochondrial Respiration.Journal of cellular physiology · 2025Article
- From Data to Cure: A Comprehensive Exploration of Multi-omics Data Analysis for Targeted Therapies.Molecular biotechnology · 2025Review
- Boric acid impedes glioblastoma growth in a rat model: insights from multi-approach analysis.Medical oncology (Northwood, London, England) · 2025Article
- Identifying Hub Genes and Metabolic Pathways in Collagen VI-Related Dystrophies: A Roadmap to Therapeutic Intervention.Biomolecules · 2024Article
- Review
- Unveiling the Molecular Mechanisms of Glioblastoma through an Integrated Network-Based Approach.Biomedicines · 2024Article
- Article
- Novel sights on therapeutic, prognostic, and diagnostics aspects of non-coding RNAs in glioblastoma multiforme.Metabolic brain disease · 2023Review
- Genome-scale metabolic modeling of Aspergillus fumigatus strains reveals growth dependencies on the lung microbiome.Nature communications · 2023Article
- Whole-cell energy modeling reveals quantitative changes of predicted energy flows in RAS mutant cancer cell lines.iScience · 2023Article
- Identification of Therapeutic Targets for Medulloblastoma by Tissue-Specific Genome-Scale Metabolic Model.Molecules (Basel, Switzerland) · 2023Article
- A Risk Signature Consisting of Eight mCellular and molecular neurobiology · 2022Article
- Review of Current Human Genome-Scale Metabolic Models for Brain Cancer and Neurodegenerative Diseases.Cells · 2022Review
- Metabolic modeling-based drug repurposing in Glioblastoma.Scientific reports · 2022Article
- System-level metabolic modeling facilitates unveiling metabolic signature in exceptional longevity.Aging cell · 2022Article
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Glioblastoma (GBM) is an aggressive type of brain cancer with a poor prognosis for affected patients. The current line of treatment only gives the patients a survival time of on average 15 months. In this work, we use genome-scale metabolic models (GEMs) together with other systems biology tools to examine the global transcriptomics-data of GBM-patients obtained from The Cancer Genome Atlas (TCGA). We reveal the molecular mechanisms underlying GBM and identify potential therapeutic targets for effective treatment of patients. The work presented consists of two main parts. The first part stratifies the patients into two groups, high and low survival, and compares their gene expression. The second part uses GBM and healthy brain tissue GEMs to simulate gene knockout in a GBM cell model to find potential therapeutic targets and predict their side effect in healthy brain tissue. We (1) find that genes upregulated in the patients with low survival are linked to various stages of the glioma invasion process, and (2) identify five essential genes for GBM, whose inhibition is non-toxic to healthy brain tissue, therefore promising to investigate further as therapeutic targets.
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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.