Identification of differentially expressed genes regulated by transcription factors in glioblastomas by bioinformatics analysis

Mol Med Rep. 2015 Apr;11(4):2548-54. doi: 10.3892/mmr.2014.3094. Epub 2014 Dec 15.

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.

MeSH terms

  • Algorithms
  • Computational Biology* / methods
  • Databases, Genetic
  • Gene Expression Regulation, Neoplastic*
  • Gene Regulatory Networks
  • Glioblastoma / genetics*
  • Glioblastoma / metabolism*
  • Glioblastoma / pathology
  • Humans
  • Neoplasm Grading
  • Transcription Factors / metabolism*

Substances

  • Transcription Factors