ArticleCancer genomics & proteomics
Identification of
Article in Cancer genomics & proteomics. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Transcriptomic Evidence Identifies Two TMBIM Subgroups with Opposing Prognostic Associations in Glioma.Biology · 2026Article
- Mapping kinase-dependent tumor immune adaptation with multiplexed single-cell CRISPR screens.bioRxiv : the preprint server for biology · 2026Article
- IL1B-Expressing Exhausted CD4Cancer genomics & proteomicsArticle
- ERP44 Is Associated With Poor Prognosis and Promotes Proliferation and Temozolomide Resistance in Lower-grade Glioma.Cancer genomics & proteomicsArticle
- SNRPD2-dependency Fuels an Oncogenic Alternative Splicing Repertoire Driving Disease Aggressiveness in Glioma.Cancer genomics & proteomicsArticle
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
BACKGROUND/
aimGlioblastoma multiforme (GBM) is a highly aggressive, treatment-resistant brain tumor with a dismal prognosis, and identifying key molecules involved in its therapeutic resistance is essential to improve patient outcomes. This study was undertaken to identify hub genes associated with the radioresistance and temozolomide (TMZ) resistance of GBM using bioinformatics analysis. MATERIALS AND
methodsRNA-seq and microarray datasets from the GEO database were analyzed to identify differentially expressed genes (DEGs). GO and KEGG pathway enrichment analyses were performed using Enrichr. A protein-protein interaction (PPI) network was constructed using STRING and visualized with Cytoscape, and hub genes were identified by MCODE analysis. Expression and survival analyses were conducted on TCGA and GTEx datasets using GEPIA2.
resultsTwenty-four DEGs were considered linked to radioresistance and 122 to TMZ resistance. Functional enrichment and PPI network analyses highlighted key therapeutic resistance pathways, including cytokine-mediated signaling and inflammatory response pathways. Notably,
conclusionThis study identifies
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.