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Epigenetics. 2014 Jun;9(6):873-83. doi: 10.4161/epi.28571. Epub 2014 Mar 26.

A novel approach to the discovery of survival biomarkers in glioblastoma using a joint analysis of DNA methylation and gene expression.

Author information

1
Department of Pathology and Laboratory Medicine; Brown University; Providence, RI USA.
2
Department of Epidemiology; Brown University; Providence, RI USA.
3
Department of Public Health; Oregon State University; Corvallis, OR USA.
4
Department of Pharmacology and Toxicology; Geisel School of Medicine at Dartmouth; Hanover, NH USA; Department of Community and Family Medicine and Section of Biostatistics and Epidemiology; Geisel School of Medicine at Dartmouth; Dartmouth, NH USA.
5
Department of Neurological Surgery; University of California at San Francisco; San Francisco, CA USA.
6
Department of Pathology and Laboratory Medicine; Brown University; Providence, RI USA; Department of Epidemiology; Brown University; Providence, RI USA.

Abstract

Glioblastoma multiforme (GBM) is the most aggressive of all brain tumors, with a median survival of less than 1.5 years. Recently, epigenetic alterations were found to play key roles in both glioma genesis and clinical outcome, demonstrating the need to integrate genetic and epigenetic data in predictive models. To enhance current models through discovery of novel predictive biomarkers, we employed a genome-wide, agnostic strategy to specifically capture both methylation-directed changes in gene expression and alternative associations of DNA methylation with disease survival in glioma. Human GBM-associated DNA methylation, gene expression, IDH1 mutation status, and survival data were obtained from The Cancer Genome Atlas. DNA methylation loci and expression probes were paired by gene, and their subsequent association with survival was determined by applying an accelerated failure time model to previously published alternative and expression-based association equations. Significant associations were seen in 27 unique methylation/expression pairs with expression-based, alternative, and combinatorial associations observed (10, 13, and 4 pairs, respectively). The majority of the predictive DNA methylation loci were located within CpG islands, and all but three of the locus pairs were negatively correlated with survival. This finding suggests that for most loci, methylation/expression pairs are inversely related, consistent with methylation-associated gene regulatory action. Our results indicate that changes in DNA methylation are associated with altered survival outcome through both coordinated changes in gene expression and alternative mechanisms. Furthermore, our approach offers an alternative method of biomarker discovery using a priori gene pairing and precise targeting to identify novel sites for locus-specific therapeutic intervention.

KEYWORDS:

DNA methylation; biomarker; gene expression; glioma; mediation analysis

PMID:
24670968
PMCID:
PMC4065185
DOI:
10.4161/epi.28571
[Indexed for MEDLINE]
Free PMC Article

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