Differential expression of microRNAs as predictors of glioblastoma phenotypes

Barrie S. Bradley, Joseph C. Loftus, Clinton J. Mielke, Valentin Dinu

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Background: Glioblastoma is the most aggressive primary central nervous tumor and carries a very poor prognosis. Invasion precludes effective treatment and virtually assures tumor recurrence. In the current study, we applied analytical and bioinformatics approaches to identify a set of microRNAs (miRs) from several different human glioblastoma cell lines that exhibit significant differential expression between migratory (edge) and migration-restricted (core) cell populations. The hypothesis of the study is that differential expression of miRs provides an epigenetic mechanism to drive cell migration and invasion. Results: Our research data comprise gene expression values for a set of 805 human miRs collected from matched pairs of migratory and migration-restricted cell populations from seven different glioblastoma cell lines. We identified 62 down-regulated and 2 up-regulated miRs that exhibit significant differential expression in the migratory (edge) cell population compared to matched migration-restricted (core) cells. We then conducted target prediction and pathway enrichment analysis with these miRs to investigate potential associated gene and pathway targets. Several miRs in the list appear to directly target apoptosis related genes. The analysis identifies a set of genes that are predicted by 3 different algorithms, further emphasizing the potential validity of these miRs to promote glioblastoma.Conclusions: The results of this study identify a set of miRs with potential for decreased expression in invasive glioblastoma cells. The verification of these miRs and their associated targeted proteins provides new insights for further investigation into therapeutic interventions. The methodological approaches employed here could be applied to the study of other diseases to provide biomedical researchers and clinicians with increased opportunities for therapeutic interventions.

Original languageEnglish (US)
Article number21
JournalBMC Bioinformatics
Volume15
Issue number1
DOIs
StatePublished - Jan 18 2014

Fingerprint

MicroRNA
Differential Expression
Glioblastoma
MicroRNAs
Phenotype
Predictors
Cells
Genes
Cell Population
Tumors
Migration
Cell
Invasion
Gene
Cell death
Bioinformatics
Target
Cell Movement
Gene expression
Tumor

Keywords

  • Cell migration
  • Gene expression
  • Glioblastoma
  • MicroRNA
  • miR
  • Pathway analysis
  • Target prediction

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Applied Mathematics
  • Structural Biology

Cite this

Differential expression of microRNAs as predictors of glioblastoma phenotypes. / Bradley, Barrie S.; Loftus, Joseph C.; Mielke, Clinton J.; Dinu, Valentin.

In: BMC Bioinformatics, Vol. 15, No. 1, 21, 18.01.2014.

Research output: Contribution to journalArticle

Bradley, Barrie S. ; Loftus, Joseph C. ; Mielke, Clinton J. ; Dinu, Valentin. / Differential expression of microRNAs as predictors of glioblastoma phenotypes. In: BMC Bioinformatics. 2014 ; Vol. 15, No. 1.
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