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Abstract Details
Activity Number:
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668
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Type:
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Contributed
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Date/Time:
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Thursday, August 2, 2012 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistics in Epidemiology
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Abstract - #304736 |
Title:
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DNA Methylation in Blood Is Associated with Breast Cancer: A Study in Prospective Samples from the Sister Study
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Author(s):
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Zongli Xu*+ and Sophia C.E. Bolick and Lisa A. DeRoo and Dale P. Sandler and Clarice Weinberg and Jack A. Taylor
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Companies:
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National Institute of Environmental Health Sciences and National Institute of Environmental Health Sciences and National Institute of Environmental Health Sciences and National Institute of Environmental Health Sciences and National Institute of Environmental Health Sciences and National Institute of Environmental Health Sciences
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Address:
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111 TW Alexander Drive, Durham, NC, 27709, United States
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Keywords:
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DNA methylation ;
breast cancer ;
risk prediction ;
EWAS ;
epigenetic
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Abstract:
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DNA methylation in blood is a potential epigenetic marker of cancer risk, but has not been evaluated on a genome-wide scale in prospective studies. We measured DNA methylation at 27,578 CpGs in blood samples from 298 women who developed breast cancer 0-5 years after enrollment in the Sister Study cohort and compared them to a random sample of 612 cohort women who remained cancer free. We identified 250 CpGs that were differentially methylated (dmCpGs) between cases and non-cases. Women diagnosed < 1 year of blood draw had small, but consistently greater divergence from non-cases than did women diagnosed >1 year. 75% of these differentially methylated CpGs (dmCpGs) were hypo-methylated in cases relative to non-cases and there were high concordance between case-blood and breast tumor DNA for the direction of methylation change relative to non-cases. Gene set enrichment analysis identified 18 significant pathways including 6 cancer pathways. Receiver operating characteristic analysis had case prediction accuracy of 65% (95%CI:62%-69%) in test sets. Methylation profiling of blood holds promise for breast cancer detection and risk prediction.
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Authors who are presenting talks have a * after their name.
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