ArticleMolecular medicine reports2015
Identification of differentially expressed genes regulated by transcription factors in glioblastomas by bioinformatics analysis.
Article in Molecular medicine reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.
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Who cites it
28 citing papers in PubMed, 1 synthesis or guideline pooled it, 38 citations in OpenAlex.
- Identification of Paxillin as a Prognostic Factor for Glioblastoma via Integrated Bioinformatics Analysis.BioMed research international · 2022Pooled it
- Akt/FoxM1 signaling pathway-mediated upregulation of MYBL2 promotes progression of human glioma.Journal of experimental & clinical cancer research : CR · 2017Trial
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- SPI1 activates TGF-β1/PI3K/Akt signaling through transcriptional upregulation of FKBP12 to support the mesenchymal phenotype of glioma stem cells.Brain pathology (Zurich, Switzerland) · 2024Article
- Development and validation of a novel mitophagy-related gene prognostic signature for glioblastoma multiforme.BMC cancer · 2022Article
- A Novel Immune-Related lncRNA-Based Model for Survival Prediction in Clear Cell Renal Cell Carcinoma.Journal of immunology research · 2021Article
- Bioinformatic analysis of the potential molecular mechanism of PAK7 expression in glioblastoma.Molecular medicine reports · 2020Article
- An eight-mRNA signature outperforms the lncRNA-based signature in predicting prognosis of patients with glioblastoma.BMC medical genetics · 2020Article
- Identification and Validation of an Immunological Expression-Based Prognostic Signature in Breast Cancer.Frontiers in genetics · 2020Article
- Dynamic TF-lncRNA Regulatory Networks Revealed Prognostic Signatures in the Development of Ovarian Cancer.Frontiers in bioengineering and biotechnology · 2020Article
- Identification of key candidate genes and pathways in glioblastoma by integrated bioinformatical analysis.Experimental and therapeutic medicine · 2019Article
- Identification of differentially expressed genes and fusion genes associated with malignant progression of spinal cord gliomas by transcriptome analysis.Scientific reports · 2019Article
- Meta-Analysis of Salt Stress Transcriptome Responses in Different Rice Genotypes at the Seedling Stage.Plants (Basel, Switzerland) · 2019Article
- Identification of potential prognostic TF-associated lncRNAs for predicting survival in ovarian cancer.Journal of cellular and molecular medicine · 2019Article
- Identification of hub genes and pathways in glioblastoma by bioinformatics analysis.Oncology letters · 2019Article
- Characterization of Transcriptome Transition Associates Long Noncoding RNAs with Glioma Progression.Molecular therapy. Nucleic acids · 2018Article
- Genome-wide expression profiling of glioblastoma using a large combined cohort.Scientific reports · 2018Article
- Article
- Minority stress and leukocyte gene expression in sexual minority men living with treated HIV infection.Brain, behavior, and immunity · 2018Article
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The present study aimed to identify differentially expressed genes (DEGs) regulated by transcription factors (TFs) in glioblastoma, by conducting a bioinformatics analysis. The results of the present study may provide potential therapeutic targets that are involved in the development of glioblastoma. The GSE4290 raw data set was downloaded from the Gene Expression Omnibus database, and consisted of 23 non‑tumor samples and 77 glioblastoma (grade 4) tumor samples. Robust Multichip Averaging was used to identify DEGs between the glioblastoma and non‑tumor samples. Functional enrichment analysis of the DEGs was also performed. Based on the TRANSFAC® database, TFs associated with the glioblastoma gene expression profile were used to construct a regulatory network. Furthermore, trimmed subnets were identified according to calculated Z‑scores. A total of 676 DEGs were identified, of which 190 were upregulated and 496 were downregulated. Gene Ontology analysis demonstrated that the majority of these DEGs were functionally enriched in synaptic transmission, regulation of vesicle‑mediated transport and ion‑gated channel activity. In addition, the enriched Kyoto Encyclopedia of Genes and Genomes pathway included neuroactive ligand‑receptor interaction, calcium signaling pathway, p53 signaling pathway and cell cycle. Based on the TRANSFAC® database, transcriptional regulatory networks with 2,246 nodes and 4,515 regulatory pairs were constructed. According to the Z‑scores, the following candidate TFs were identified: TP53, SP1, JUN, STAT3 and SPI1; alongside their downstream DEGs. TP53 was the only differentially expressed TF. These candidate TFs and their downstream DEGs may have important roles in the progression of glioblastoma, and could be potential biomarkers for clinical treatment.
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