ArticleCancer genomics & proteomics
FN1 and VEGFA Are Potential Therapeutic Targets in Glioblastoma as Determined by Bioinformatics Analysis.
Article in Cancer genomics & proteomics. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Long non-coding RNAs in the exosomal network: dual roles and clinical implications in cancer.Animal cells and systems · 2026Review
- MAGNET: Multi-view graph autoencoder with cell-gene attention for cell interaction network reconstruction from spatial transcriptomics.PLoS computational biology · 2025Article
- Spatial transcriptomics of glioblastoma defines biologically and clinically significant reprogramming patterns across unique spatial microenvironments.bioRxiv : the preprint server for biology · 2025Article
- Molecular Docking and Simulation Analysis of Glioblastoma Cell Surface Receptors and Their Ligands: Identification of Inhibitory Drugs Targeting Fibronectin Ligand to Potentially Halt Glioblastoma Pathogenesis.International journal of molecular sciences · 2025Article
- LncRNA H19 acts as a ceRNA to promote glioblastoma malignancy by sponging miR-19b-3p and upregulating SERPINE1.Cancer cell international · 2025Article
- SNRPD2-dependency Fuels an Oncogenic Alternative Splicing Repertoire Driving Disease Aggressiveness in Glioma.Cancer genomics & proteomicsArticle
- Identification ofCancer genomics & proteomicsArticle
- IL1B-Expressing Exhausted CD4Cancer genomics & proteomicsArticle
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND/
aimGlioblastoma is the most malignant brain tumor, and despite advances in treatment, survival rates are still dismal. Therefore, a comprehensive understanding of the underlying molecular mechanisms of glioblastoma is needed. This study suggests potential therapeutic targets in glioblastoma that may provide new therapeutic insights. MATERIALS AND
methodsTo identify hub genes in glioblastoma, three datasets were selected from the GEO database. After screening DEGs using GEO2R, GO and KEGG analyses were performed using DAVID. The PPI network was visualized using Cytoscape and 7 hub genes were extracted. The prognostic potential of 7 hub genes was investigated using the Gliovis and GEPIA2 databases.
resultsIn total, 176 up-regulated and 263 down-regulated genes were identified. From the PPI network, 7 hub genes were identified including CAMK2A, DLG4, SNAP25, SYT1, MYC, FN1, and VEGFA. Out of the 7 hub genes identified, FN1 and VEGFA have been associated with a poor prognosis in glioblastoma based on the survival analysis.
conclusionThis study suggests that high levels of FN1 and VEGFA expression are associated with a poor prognosis in glioblastoma and that both genes are promising targets for glioblastoma therapy. Bioinformatics analysis of DEGs revealed putative targets that might reveal the molecular mechanisms underlying glioblastoma.
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