ReviewOncology letters2025
Key genes altered in glioblastoma based on bioinformatics (Review).
Review in Oncology letters, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- Identification of shared hub genes CTNNB1, TJP1, PTK2, and TP53 associated with endothelial proliferation in infantile hemangioma and glioblastoma.Mammalian genome : official journal of the International Mammalian Genome Society · 2026Article
- Article
- From Data to Decision: Integrating Bioinformatics into Glioma Patient Stratification and Immunotherapy Selection.International journal of molecular sciences · 2026Review
- Antibody therapies in glioblastoma: Overcoming micro-environmental barriers.Iranian journal of basic medical sciences · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Glioblastoma multiforme (GBM) is an aggressive brain tumor with poor prognosis. Recent advancements in bioinformatics have contributed to uncovering the genetic alterations that underlie the development and progression of GBM. Analysis of extensive genomic data led to the identification of significant pathways involved in GBM, such as the PI3K/AKT/mTOR and Ras/Raf/MEK/ERK signaling pathways, alongside key genes such as EGFR, TP53 and TERT. These findings have enhanced our understanding of GBM biology and led to the identification of new therapeutic targets. Bioinformatics has become an indispensable tool in pinpointing the genetic modifications that drive GBM, paving the way for innovative treatment strategies. This approach not only aids in comprehending the complexities of GBM but also holds promise for improving outcomes in patients suffering from this devastating disease. The ongoing integration of bioinformatics in GBM research continues to be vital for advancing therapeutic options.
Indexed as
Identifiers
What Socratic 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 Socratic graph.