Abstract 4634: Variants within super-enhancer regulatory elements associate with epithelial ovarian cancer risk

Background: Cell-type-specific super enhancers, or large clusters of mediator-rich enhancers, are highly transcribed regions of the genome with key functions in the maintenance of cell identity and control. These regulatory elements are easily perturbed and enriched for disease-associated sequence v...

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Veröffentlicht in:Cancer research (Chicago, Ill.) Ill.), 2015-08, Vol.75 (15_Supplement), p.4634-4634
Hauptverfasser: Reid, Brett M., Permuth-Wey, Jennifer, Chen, Y. Ann, Lin, Hui-Yi, Monteiro, Alvaro, Chen, Zhihua, Berchuck, Andrew, Chenevix-Trench, Georgia, Doherty, Jennifer, Gayther, Simon, Goode, Ellen L., Iversen, Edwin, Pearce, Leigh, Pharoah, Paul, Phelan, Catherine, Ramus, Susan, Rossing, Mary Anne, Schildkraut, Joellen, Sellers, Thomas
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Sprache:eng
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Zusammenfassung:Background: Cell-type-specific super enhancers, or large clusters of mediator-rich enhancers, are highly transcribed regions of the genome with key functions in the maintenance of cell identity and control. These regulatory elements are easily perturbed and enriched for disease-associated sequence variation. Identification of disease-associated super-enhancers and investigation of their sequence variants may help identify important, biologically relevant associations previously overlooked by genome-wide studies. Thus, we sought to identify variants within ovarian tissue specific super-enhancers and investigate their association with epithelial ovarian cancer (EOC) susceptibility. Methods: We utilized genotype data from a European population of ∼11,000 invasive EOC cases and 22,000 healthy controls from the Ovarian Cancer Association Consortium. A public catalog of 478 super-enhancers, identified by peak histone H3K27ac ChIP-seq signal in ovarian tissue, was used to identify 72,116 variants located within 344 super-enhancer regions. Unconditional logistic regression (log-additive model) was used to assess individual SNP-EOC risk associations. Additionally, we reviewed associations within 500 kb of super-enhancer regions to identify proximal associated variants. When LD structure indicated, we employed conditional analysis to determine independence of the super-enhancer signal. Gene-EOC risk associations were assessed with the Admixture Maximum Likelihood (AML) test and Sequence-Kernel Association Test (SKAT) for the combined effect of common and rare (MAF
ISSN:0008-5472
1538-7445
DOI:10.1158/1538-7445.AM2015-4634