ArticleOncology letters2019
Identification of core differentially methylated genes in glioma.
Article in Oncology letters, 2019. 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
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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.
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Who cites it
6 citing papers in PubMed, 7 citations in OpenAlex.
- Long-read sequencing-based transcriptomic landscape in longissimus dorsi and transcriptome-wide association studies for growth traits of meat rabbits.Frontiers in veterinary science · 2024Article
- Article
- Screening and identification of differentially expressed microRNAs in diffuse large B-cell lymphoma based on microRNA microarray.Oncology letters · 2021Article
- Identification and Validation of a Seizure-Free-Related Gene Signature for Predicting Poor Prognosis in Lower-Grade Gliomas.International journal of general medicine · 2021Article
- Correlation amongTranslational cancer research · 2020Article
- Integrative Analysis of DNA Methylation Identified 12 Signature Genes Specific to Metastatic ccRCC.Frontiers in oncology · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Differentially methylated genes (DMGs) serve a crucial role in the pathogenesis of glioma via the regulation of the cell cycle, proliferation, apoptosis, migration, infiltration, DNA repair and signaling pathways. This study aimed to identify aberrant DMGs and pathways by comprehensive bioinformatics analysis. The gene expression profile of GSE28094 was downloaded from the Gene Expression Omnibus (GEO) database, and the GEO2R online tool was used to find DMGs. Gene Ontology (GO) functional analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis of the DMGs were performed by using the Database for Annotation Visualization and Integrated Discovery. A protein-protein interaction (PPI) network was constructed with Search Tool for the Retrieval of Interacting Genes. Analysis of modules in the PPI networks was performed by Molecular Complex Detection in Cytoscape software, and four modules were performed. The hub genes with a high degree of connectivity were verified by The Cancer Genome Atlas database. A total of 349 DMGs, including 167 hypermethylation genes, were enriched in biological processes of negative and positive regulation of cell proliferation and positive regulation of transcription from RNA polymerase II promoter. Pathway analysis enrichment revealed that cancer regulated the pluripotency of stem cells and the PI3K-AKT signaling pathway, whereas 182 hypomethylated genes were enriched in biological processes of immune response, cellular response to lipopolysaccharide and peptidyl-tyrosine phosphorylation. Pathway enrichment analysis revealed cytokine-cytokine receptor interaction, type I diabetes mellitus and TNF signaling pathway. A total of 20 hub genes were identified, of which eight genes were associated with survival, including notch receptor 1 (
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Registered trials
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