ArticleJournal of immunology research2017
The Identification of Key Genes and Pathways in Glioma by Bioinformatics Analysis.
Article in Journal of immunology research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 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
34 citing papers in PubMed, 50 citations in OpenAlex.
- RPL5 deficiency-induced ribosomal stress targets a select subset of proteins and inhibits the PI3K-Akt-mTOR signaling pathway to eradicate leukemia stem cells.Cell death & disease · 2025Article
- Prognostic Significance ofBiology · 2025Article
- Explainable Machine Learning Models for Glioma Subtype Classification and Survival Prediction.Cancers · 2025Article
- Integrative bioinformatic analysis to identify potential phytochemical candidates for glioblastoma.Heliyon · 2024Article
- Insights into the structural and functional activities of forgotten Kinases: PCTAIREs CDKs.Molecular cancer · 2024Review
- Article
- Identification of New Key Genes and Their Association with Breast Cancer Occurrence and Poor Survival Using In Silico and In Vitro Methods.Biomedicines · 2023Article
- Discovery of 3-Amino-1International journal of molecular sciences · 2022Article
- Metabolic collateral lethal target identification reveals MTHFD2 paralogue dependency in ovarian cancer.Nature metabolism · 2022Article
- Identification of hub genes and biological pathways in glioma via integrated bioinformatics analysis.The Journal of international medical research · 2022Article
- Identification of Candidate lncRNA and Pseudogene Biomarkers Associated with Carbon-Nanotube-Induced Malignant Transformation of Lung Cells and Prediction of Potential Preventive Drugs.International journal of environmental research and public health · 2022Article
- ATF4/MYC Regulates MTHFD2 to Promote NSCLC Progression by Mediating Redox Homeostasis.Disease markers · 2022Article
- LASSO-based screening for potential prognostic biomarkers associated with glioblastoma.Frontiers in oncology · 2022Article
- Overexpression of CDCA8 Predicts Poor Prognosis and Promotes Tumor Cell Growth in Prostate Cancer.Frontiers in oncology · 2022Article
- Scouting for common genes in the heterogenous hypoxic tumor microenvironment and their validation in glioblastoma.3 Biotech · 2021Article
- Prediction and analysis of hub genes between glioblastoma and low-grade glioma using bioinformatics analysis.Medicine · 2021Article
- Article
- Establishment of an Immune-Related Gene Signature for Risk Stratification for Patients with Glioma.Computational and mathematical methods in medicine · 2021Article
- Expression and Prognostic Value Identification of Methylenetetrahydrofolate Dehydrogenase 2 (MTHFD2) in Brain Low-Grade Glioma.International journal of general medicine · 2021Article
- Overexpressed GNA13 induces temozolomide sensitization via down-regulating MGMT and p-RELA in glioma.American journal of translational research · 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
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Glioma is the most common malignant tumor in the central nervous system. This study aims to explore the potential mechanism and identify gene signatures of glioma. The glioma gene expression profile GSE4290 was analyzed for differentially expressed genes (DEGs). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were applied for the enriched pathways. A protein-protein interaction (PPI) network was constructed to find the hub genes. Survival analysis was conducted to screen and validate critical genes. In this study, 775 downregulated DEGs were identified. GO analysis demonstrated that the DEGs were enriched in cellular protein modification, regulation of cell communication, and regulation of signaling. KEGG analysis indicated that the DEGs were enriched in the MAPK signaling pathway, endocytosis, oxytocin signaling, and calcium signaling. PPI network and module analysis found 12 hub genes, which were enriched in synaptic vesicle cycling rheumatoid arthritis and collecting duct acid secretion. The four key genes CDK17, GNA13, PHF21A, and MTHFD2 were identified in both generation (GSE4412) and validation (GSE4271) dataset, respectively. Regression analysis showed that CDK13, PHF21A, and MTHFD2 were independent predictors. The results suggested that CDK17, GNA13, PHF21A, and MTHFD2 might play important roles and potentially be valuable in the prognosis and treatment of glioma.
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.