ArticleOncology letters2019
High gene expression levels of VEGFA and CXCL8 in the peritumoral brain zone are associated with the recurrence of glioblastoma: A bioinformatics analysis.
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 22 papers, 1 of them a synthesis that pooled it.
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
22 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
- The Invasive Margin of Glioblastoma as a Molecular Ecosystem: Spatial Heterogeneity, Tumor-Host Interactions, and Therapeutic Opportunities.International journal of molecular sciences · 2026Review
- Explainable Machine Learning Models for Glioma Subtype Classification and Survival Prediction.Cancers · 2025Article
- Towards Optical Biopsy in Glioma Surgery.International journal of molecular sciences · 2025Review
- Malignant Cells Beyond the Tumor Core: The Non-Negligible Factor to Overcome the Refractory of Glioblastoma.CNS neuroscience & therapeutics · 2025Review
- The Original Mouse Models of Glioblastoma: Analysis of Pathophysiological Characteristics of Transplanted Tumor Tissue.Sovremennye tekhnologii v meditsine · 2025Article
- Discovery of key molecular signatures for diagnosis and therapies of glioblastoma by combining supervised and unsupervised learning approaches.Scientific reports · 2024Article
- Article
- Article
- Peritumoral brain zone in glioblastoma: biological, clinical and mechanical features.Frontiers in immunology · 2024Review
- Exploring potential therapeutic targets for small cell lung cancer based on transcriptomics combined with Mendelian randomization analysis.Frontiers in immunology · 2024Article
- Peritumoral Brain Zone in Astrocytoma: Morphology, Molecular Aspects, and Clinical Manifestations (Review).Sovremennye tekhnologii v meditsine · 2024Review
- Inhalant Cannabidiol Inhibits Glioblastoma Progression Through Regulation of Tumor Microenvironment.Cannabis and cannabinoid research · 2023Article
- Article
- Novel Roles of RNA m6A Methylation Regulators in the Occurrence of Alzheimer's Disease and the Subtype Classification.International journal of molecular sciences · 2022Article
- Hijacking Sexual Immuno-Privilege in GBM-An Immuno-Evasion Strategy.International journal of molecular sciences · 2021Article
- Analysis of Circulating miRNA Profile in Plasma Samples of Glioblastoma Patients.International journal of molecular sciences · 2021Article
- Identification of Hub Genes and Key Pathways Associated with Anti-Biomolecules · 2021Article
- Research Supporting a Pilot Study of Metronomic Dapsone during Glioblastoma Chemoirradiation.Medical sciences (Basel, Switzerland) · 2021Article
- AKIP1 promotes glioblastoma viability, mobility and chemoradiation resistance via regulating CXCL1 and CXCL8 mediated NF-κB and AKT pathways.American journal of cancer 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
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The present study aimed to identify differentially regulated genes between the peritumoral brain zone (PBZ) and tumor core (TC) of glioblastoma (GBM), to elucidate the underlying molecular mechanisms and provide a target for the treatment of tumors. The GSE13276 and GSE116520 datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) for the PBZ and TC were obtained using the GEO2R tool. The bioinformatics and evolutionary genomics online tool Venn was used to identify common DEGs between the two datasets. The Database for Annotation, Visualization, and Integrated Discovery online tool was used to analyze enriched pathways of the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. The Search Tool for the Retrieval of Interacting Genes/Proteins online tool was used to construct a protein-protein interaction (PPI) network of DEGs. Hub genes were identified using Cytohubba, a plug-in for Cytoscape. The Gene Expression Profiling Interactive Analysis (GEPIA) database was utilized to perform survival analysis. In total, 75 DEGs, including 12 upregulated and 63 downregulated genes, were identified. In the GO term analysis, these DEGs were mainly enriched in 'regulation of angiogenesis' and 'central nervous system development'. Furthermore, in the KEGG pathway analysis, the DEGs were mainly enriched in 'bladder cancer' and 'endocytosis'. When filtering the results of the PPI network analysis using Cytohubba, a total of 10 hub genes, including proteolipid protein 1, myelin associated oligodendrocyte basic protein, contactin 2, myelin oligodendrocyte glycoprotein, myelin basic protein, myelin associated glycoprotein, SRY-box transcription factor 10, C-X-C motif chemokine ligand 8 (CXCL8), vascular endothelial growth factor A (VEGFA) and plasmolipin, were identified. These hub genes were further subjected to GO term and KEGG pathway analysis, and were revealed to be enriched in 'central nervous system development', 'bladder cancer' and 'rheumatoid arthritis'. These hub genes were used to perform survival analysis using the GEPIA database, and it was determined that VEGFA and CXCL8 were significantly associated with a reduction in the overall survival of patients with GBM. In conclusion, the results suggest that the recurrence of GBM is associated with high gene expression levels VEGFA and CXCL8, and the development of the central nervous system.
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.