High gene expression levels of VEGFA and CXCL8 in the peritumoral brain zone are associated with the recurrence of glioblastoma: A bioinformatics analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:31788092", "kind": "science-record", "revision": 4, "content_hash": "sha256:96bca341c8e8d4e7735572798858bdadbb8c515a5a074c680353365565087a09", "created_at": "2026-11-01T15:40:52Z", "updated_at": "2026-11-01T22:01:03Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "High gene expression levels of VEGFA and CXCL8 in the peritumoral brain zone are associated with the recurrence of glioblastoma: A bioinformatics analysis.", "doi": "10.3892/ol.2019.10988", "pmid": "31788092", "authors": ["Xiaobin Luo", "Shangyi Xu", "Yali Zhong", "Tianqi Tu", "Youlin Xu", "Xianglong Li", "Bin Wang", "Fubing Yang"], "journal": "Oncology letters", "year": 2019, "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.", "claims": [{"id": "claim-method", "statement": "The GBM sample was selected as the dataset and the hazard ratio (HR) was calculated based on the Cox Proportional-Hazards Model.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:31788092", "locator": "sections[8] \"Survival analysis\" paragraph 2", "quote": "The GBM sample was selected as the dataset and the hazard ratio (HR) was calculated based on the Cox Proportional-Hazards Model."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets generated and/or analyzed during the current study are available in the GEO repository (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13276) and (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE116520).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:31788092", "locator": "sections[19] \"Availability of data and materials\" paragraph 2", "quote": "The datasets generated and/or analyzed during the current study are available in the GEO repository (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13276) and (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE116520)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": null, "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:31788092"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "blocked", "blocked_on": "data:accession_absent", "description": "The GEO series accession resolves and its sample accessions are listed. 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