ArticleOncology letters2020
Identification of glioblastoma-specific prognostic biomarkers via an integrative analysis of DNA methylation and gene expression.
Article in Oncology letters, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed, 6 citations in OpenAlex.
- TRIM47 promotes cell viability, cell cycle progression, metabolic reprogramming, and inhibits apoptosis of glioma via the NF-κB signaling pathway.Translational cancer research · 2026Article
- In vitro assessment of siRNA-mediated LRP5 silencing and temozolomide treatment in glioblastoma and brain cancer stem cells.Molecular genetics and genomics : MGG · 2026Article
- A novel prognostic model based on Golgi apparatus-related genes predicts patient survival in glioblastoma.Open medicine (Warsaw, Poland) · 2026Article
- Key genes altered in glioblastoma based on bioinformatics (Review).Oncology letters · 2025Review
- Size matters: Biomolecular compositions of small and large extracellular vesicles in the urine of glioblastoma patients.Journal of extracellular biology · 2024Article
- Integrative analysis of somatic mutations and differential expression profiles in glioblastoma based on aging acceleration.International journal of clinical and experimental pathology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Glioblastoma (GBM) is the most aggressive and lethal tumor of the central nervous system. The present study set out to identify reliable prognostic and predictive biomarkers for patients with GBM. RNA-sequencing data were obtained from The Cancer Genome Atlas database and DNA methylation data were downloaded using the University of California Santa Cruz-Xena database. The expression and methylation differences between patients with GBM, and survival times <1 and ≥1 year were investigated. A protein-protein interaction network was constructed and functional enrichment analyses of differentially expressed and methylated genes were performed. Hub genes were identified using the Cytoscape plug-in cytoHubba software. Survival analysis was performed using the survminer package, in order to determine the prognostic values of the hub genes. The present study identified 71 genes that were hypomethylated and expressed at high levels, and four genes that were hypermethylated and expressed at low levels in GBM. These genes were predominantly enriched in the 'JAK-STAT signaling pathway', 'transcriptional misregulation in cancer' and the 'ECM-receptor interaction', which are associated with GBM development. Among the 24 hub genes identified, 15 possessed potential prognostic value. An integrative analysis approach was implemented in order to analyze the association of DNA methylation with changes in gene expression and to assess the association of gene expression changes with GBM survival time. The results of the present study suggest that these 15 CpG-based genes may be useful and practical tools in predicting the prognosis of patients with GBM. However, future research on gene methylation and/or expression is required in order to develop personalized treatments for patients with GBM.
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.