ArticleComputational and structural biotechnology journal2024
Analysis of transcription profiles for the identification of master regulators as the key players in glioblastoma.
Article in Computational and structural biotechnology journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- A Pathogenic ROCK-Signaling Network Involving a Lysine Deletion in Myh11 Renders Carriers Susceptible to Aortic Dissection.International journal of molecular sciences · 2026Article
- Glioblastoma Stem Cells and Tumour Microenvironment: Interactions Across Hypoxia, Vasculature and Immune Modulation.International journal of molecular sciences · 2026Review
- Analysis of Genomic and Transcriptomic Data Revealed Key Genes and Processes in the Development of Major Depressive Disorder.International journal of molecular sciences · 2025Article
- CirRFKB: A knowledgebase of circadian-related risk factors for cancer pathogenesis and personalized medicine.Computational and structural biotechnology journal · 2025Article
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Authors and funding
3 authors.
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Abstract
Glioblastoma (GBM) is the most common malignant brain tumor with poor overall survival. Current treatment management for GBM has low efficacy, mainly due to high inter-patient heterogeneity. The transcription profiles in GBM define cell properties essential for tumor progression. We have developed an approach for the identification of master regulators (MRs) that are responsible for the gene expression changes in GBM. The approach is based on transcription factor enrichment analysis with subsequent "upstream" analysis in the signaling network. The main feature of the approach is that all calculations are performed for transcription profiles from individual samples, which allows taking into account GBM transcription heterogeneity. We identified 451 MRs that were up-regulated or down-regulated and, thus, were important parts of positive feedback loops. The number of MRs in the samples correlated with the degree of tumor immune infiltration, while the differences in MR profiles were generally consistent with the known GBM subtypes: mesenchymal, classical, and proneural. MRs densely interact with each other in the signaling network that may be associated with the robustness to pharmacological intervention. We identified 102 receptors among MRs, which is coherent with the importance of cell-cell interactions for GBM progression. The role of some of them in GBM is not currently investigated: lysophosphatidic acid receptors 5 and 6, sphingosine-1-phosphate receptor 4, lysophosphatidylserine receptors GPR34 and GPR174, and G protein-coupled receptors 84 and 132 for fatty acids. Information on the revealed MRs can be used to search for novel therapeutic strategies to treat GBM.
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