ArticleJournal of neuro-oncology2018
Bioinformatic analysis of gene expression and methylation regulation in glioblastoma.
Article in Journal of neuro-oncology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.
What it found
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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
33 citing papers in PubMed, 1 synthesis or guideline pooled it.
- mRNA markers for survival prediction in glioblastoma multiforme patients: a systematic review with bioinformatic analyses.BMC cancer · 2024Pooled it
- Midkine and pleiotrophin in glioma: From mechanistic insights to therapeutic potential.Neoplasia (New York, N.Y.) · 2026Review
- SGSM1 as a pan-cancer biomarker: multi-omics insights into immune regulation, prognostic value, and therapeutic implications.Discover oncology · 2025Article
- Identifying the HIV-Resistance-Related Factors and Regulatory Network via Multi-Omics Analyses.International journal of molecular sciences · 2024Article
- Article
- ImaGene: a web-based software platform for tumor radiogenomic evaluation and reporting.Bioinformatics advances · 2022Article
- Article
- Identification of 9 Gene Signatures by WGCNA to Predict Prognosis for Colon Adenocarcinoma.Computational intelligence and neuroscience · 2022Article
- Identification of key genes involved in the recurrence of glioblastoma multiforme using weighted gene co-expression network analysis and differential expression analysis.Bioengineered · 2021Article
- Article
- PTRF/cavin-1 remodels phospholipid metabolism to promote tumor proliferation and suppress immune responses in glioblastoma by stabilizing cPLA2.Neuro-oncology · 2021Article
- Continuous MYD88 Activation Is Associated With Expansion and Then Transformation of IgM Differentiating Plasma Cells.Frontiers in immunology · 2021Article
- DNA Methylation-Driven Genes for Developing Survival Nomogram for Low-Grade Glioma.Frontiers in oncology · 2021Article
- Construction of Novel Methylation-Driven Gene Model and Investigation of PARVB Function in Glioblastoma.Frontiers in oncology · 2021Article
- Promoting Prognostic Model Application: A Review Based on Gliomas.Journal of oncology · 2021Review
- Abnormal expression ofPeerJ · 2021Article
- MYD88 Is a Potential Prognostic Gene and Immune Signature of Tumor Microenvironment for Gliomas.Frontiers in oncology · 2021Article
- Analysis of the EGFR Amplification and CDKN2A Deletion Regulated Transcriptomic Signatures Reveals the Prognostic Significance ofFrontiers in oncology · 2021Article
- A novel methylation signature predicts radiotherapy sensitivity in glioma.Scientific reports · 2020Article
- Methylation of MGMT promoter does not predict response to temozolomide in patients with glioblastoma in Donostia Hospital.Scientific reports · 2020Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Different gene expression and methylation profiles are identified in glioblastoma (GBM). To screen the differentially expressed genes affected by DNA methylation modification and further investigate their prognostic values for GBMs. We included The Cancer Genome Atlas (TCGA) RNA sequencing (676) and DNA methylation (Illumina Human Methylation 450K; 657) databases to detect the gene expression and methylation profiles. Chinese Glioma Genome Atlas (CGGA) RNA sequencing database and TCGA DNA methylation (Illumina Human Methylation 27K; 283) was included for validation. Gene expression and DNA methylation statues were identified using principal components analysis (PCA). A total of 3365 differentially expressed genes were identified. Among them, 2940 genes showed low methylation and high expression, while 425 genes showed high methylation and low expression in GBMs. An eight-gene (C9orf64, OSMR, MDK, MARVELD1, PTRF, MYD88, BIRC3, RPP25) signature was established to divide GBM patients into two groups based on the cut-off point (27.24). The high risk group had shorter overall survival (OS) than low risk group (median OS 15.77 vs. 10.61 months; P = 0.0002). Moreover, the different clinical and molecular features were shown between two groups. These findings could be validated in additional datasets. The differentially expressed genes affected by DNA methylation modification were detected. Our results showed that the eight-gene signature has independently prognostic value for GBM patients.
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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.