ArticleJournal of Korean Neurosurgical Society2025
Comparative Analysis of Transcription Factors TWIST2, GATA3, and HES5 in Glioblastoma Multiforme : Evaluating Biomarker Potential and Therapeutic Targets Using in Silico Methods.
Article in Journal of Korean Neurosurgical Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Improved prognostic survival models for pediatric medulloblastoma using high dimensional gene expression data.BMC medical genomics · 2026Article
- A transcriptional network underlying migratory cellular states and reduced 5-ALA-based photodynamic detectability in glioblastoma.Molecular and clinical oncology · 2026Article
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Authors and funding
2 authors.
Funding
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Abstract
objectiveGlioblastoma multiforme (GBM) is characterized by substantial heterogeneity and limited therapeutic options. As molecular approaches to central nervous system tumors have gained prominence, this study examined the roles of three genes, TWIST2, GATA3, and HES5, known to be involved in oncogenesis, developmental processes, and maintenance of cancer stem cell properties, which have not yet been extensively studied in GBM. This study is the first to present gene expression data for TWIST2, GATA3, and HES5 specifically within the context of GBM patient survival.
methodsGene expression data for TWIST2, GATA3, and HES5 were collected from GBM and normal brain tissues using datasets from The Cancer Genome Atlas via the Genomic Data Commons portal and the Genotype-Tissue Expression database. These data were rigorously analyzed using in silico methods.
resultsAll three genes were significantly more expressed in GBM tissues than in normal tissues. TWIST2 and GATA3 were linked to lower survival rates in GBM patients. Interestingly, higher HES5 levels were associated with better survival rates, suggesting a complex role that needs more investigation.
conclusionThis study shows that TWIST2, GATA3, and HES5 could help predict outcomes in GBM patients. Our multigene model offers a better understanding of GBM and points to new treatment options, bringing hope for improved therapies and patient outcomes. This research advances our knowledge of GBM and highlights the potential of molecular diagnostics in oncology.
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