Genome wide association analyses have recently discovered several low penetrant breast cancer susceptibility genes, however, vast majority of genetic predisposition to breast cancer is yet to be characterized. Considering methylation alterations in breast cancer tumors, it can be suggested that aberrant or compromised epigenome regulation may serve as a mechanism underlying predisposition to breast cancer. In this study we propose to integrate publically available data from recent GWAS and an independent candidate pathway haplotype tagging (ht) approach to identify DNA variation in epigenetic regulatory (ERG) genes that confers elevated risk to breast cancer. The panel of 989 tagging SNPs (tSNPs) capturing common genetic variation in 102 candidate epigenetic regulatory genes, will be tested in case/control association analysis separately for single effects as well as epistatic gene-gene interactions as low- penetrance breast cancer susceptibility alleles. The project will employ a two-step approach to maximize statistical power;including a cohort of cases with strong family history of breast cancer (N=500) as well as large cohorts of unselected breast cancer cases (N=2000) and healthy controls (N=2000). Cases and controls will be drawn from two populations, isolated population of Ashkenazi Jewish ancestry (AJ)(1300 case, 1000 controls) and sample population of predominantly non-AJ European ancestry (1200 cases, 1000 controls). Finally, the replication of the most significant associations will be performed on ~10,000 breast cancer cases and ~10,000 controls within Breast Cancer Association Consortium (BCAC). The proposed project will provide a first genomic approach to date utilizing systematic analysis of epigentic regulatory pathways to identify complex effects on genetic susceptibility to breast cancer. The results of this study will extend the observations from prior GWAS and may in turn provide further biological evidence elucidating a role of aberrant epigenome in breast cancer tumorigenesis.

Public Health Relevance

Recent biotechnological advances in post-genomic era have yielded the strategies to identify genes that predispose human breast cancer. However, despite this enormous effort, for more than 70% of all hereditary breast cancers the genetic defects are yet to be identified. Human genetic information is in large extent regulated by """"""""non-DNA"""""""" events, called epigenome. It was described that epigenome regulation is defected in many cancers, including breast tumors. We believe that in some breast cancer families there are inherited defect in genes that regulate epigenome response what in turn confers elevated risk to breast cancer. These defects in epigenome regulating genes are a result of DNA variation among individuals caused by single nucleotide polymorphisms (SNPs) what alters epigenome processes among individuals. In this proposal we will use DNA from 500 breast cancer families with more than one case of breast cancer. Second, we will look at 2000 breast cancer patients versus 2000 healthy individuals. By comparing the differences in genetic variation of epigenome regulatory genes between the two groups we will be able to determine an individual genetic predisposition for a development of breast cancer. The results of this study will significantly contribute to the early diagnosis, prevention and treatment of the disease and the methods used in this proposal can be applied to identification of gene mutations predisposing to other cancers, where complex genetic susceptibility remains unknown.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Exploratory/Developmental Grants (R21)
Project #
7R21CA139396-03
Application #
8316539
Study Section
Cancer Genetics Study Section (CG)
Program Officer
Verma, Mukesh
Project Start
2010-01-01
Project End
2012-12-31
Budget Start
2011-03-16
Budget End
2012-12-31
Support Year
3
Fiscal Year
2011
Total Cost
$164,598
Indirect Cost
Name
New York University
Department
Public Health & Prev Medicine
Type
Schools of Medicine
DUNS #
121911077
City
New York
State
NY
Country
United States
Zip Code
10016
Hart, Steven N; Maxwell, Kara N; Thomas, Tinu et al. (2016) Collaborative science in the next-generation sequencing era: a viewpoint on how to combine exome sequencing data across sites to identify novel disease susceptibility genes. Brief Bioinform 17:672-7
Vijai, Joseph; Topka, Sabine; Villano, Danylo et al. (2016) A Recurrent ERCC3 Truncating Mutation Confers Moderate Risk for Breast Cancer. Cancer Discov 6:1267-1275