Differential expression of microRNAs as predictors of glioblastoma phenotypes

BMC Bioinformatics

Barrie S Bradley³  Joseph C Loftus¹  Clinton J Mielke²  Valentin Dinu³ 

[1] Biochemistry and Molecular Biology, Mayo Clinic Arizona, 13400 E. Shea Boulevard, Scottsdale, AZ 85259, USA

[2] The Biodesign Institute, Arizona State University, 1001 S. McAllister Ave, Tempe, AZ 85287, USA

[3] Department of Biomedical Informatics, Arizona State University, 13212 East Shea Boulevard, Scottsdale, AZ 85259, USA

关键词: Pathway analysis;    Target prediction;    Gene expression;    Cell migration;    Glioblastoma;    miR;    MicroRNA;   

Others  :  1087646
DOI  :  10.1186/1471-2105-15-21

 received in 2013-03-02, accepted in 2014-01-17,  发布年份 2014

【 摘 要 】

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.

【 授权许可】

   
2014 Bradley et al.; licensee BioMed Central Ltd.

【 图 表 】

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