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Open Access Research article

Genome-wide associations of signaling pathways in glioblastoma multiforme

Stefan Wuchty1*, Alexei Vazquez2, Serdar Bozdag3 and Peter O Bauer45

Author Affiliations

1 National Center of Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA

2 Department of Radiation Oncology, The Cancer Institute of New Jersey and University of Medicine and Dentistry of New Jersey, Robert Wood Johnson Medical School, New Brunswick, NJ, 08901, USA

3 Dept. of Mathematics, Statistics and Comp. Science, Marquette University, Milwaukee, WI, 52333, USA

4 National Cancer Institute, National Institutes of Neurological Disorder and Stroke, National Institutes of Health, Bethesda, MD, 20892, USA

5 Present address: Dept. of Neuroscience, Mayo Clinic, Jacksonville, FL, 32224, USA

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BMC Medical Genomics 2013, 6:11  doi:10.1186/1755-8794-6-11

Published: 28 March 2013

Abstract

Background

eQTL analysis is a powerful method that allows the identification of causal genomic alterations, providing an explanation of expression changes of single genes. However, genes mediate their biological roles in groups rather than in isolation, prompting us to extend the concept of eQTLs to whole gene pathways.

Methods

We combined matched genomic alteration and gene expression data of glioblastoma patients and determined associations between the expression of signaling pathways and genomic copy number alterations with a non-linear machine learning approach.

Results

Expectedly, over-expressed pathways were largely associated to tag-loci on chromosomes with signature alterations. Surprisingly, tag-loci that were associated to under-expressed pathways were largely placed on other chromosomes, an observation that held for composite effects between chromosomes as well. Indicating their biological relevance, identified genomic regions were highly enriched with genes having a reported driving role in gliomas. Furthermore, we found pathways that were significantly enriched with such driver genes.

Conclusions

Driver genes and their associated pathways may represent a functional core that drive the tumor emergence and govern the signaling apparatus in GBMs. In addition, such associations may be indicative of drug combinations for the treatment of brain tumors that follow similar patterns of common and diverging alterations.