We plan to conduct a genome-wide association study of young (<50 years) invasive female breast cancer to identify new genes responsible for young cases who are negative for BRCA1 and BRCA2 gene mutations. This collaborative study will exploit the availability of biological samples and epidemiological data from 2,330 population-based, individually matched case-control pairs ascertained by large breast cancer study resources in Australia, Canada, the US and Germany. We will focus on early-onset BRCA1- and BRCA2-negative invasive cases because this group has high public health importance and high likelihood of harboring unidentified breast cancer genes. To enhance cost-efficiency and validity, the study will proceed in two phases. Phase I will genotype and analyze population-based samples of 1,500 non-Hispanic Caucasian matched case-control pairs. We will perform Phase I in two stages. In Stage 1, we will genotype and analyze 1,000 case-control pairs, using the Affymetrix 500k SNP array augmented by the ParAllele non-synonymous 20k cSNP panel. In Stage 2, we will genotype the remaining 500 case-control pairs only for the SNPs identified as promising in Stage 1. We will then analyze these SNPs using all 1,500 case-control pairs, adjusting for established breast cancer risk factors. Phase II will genotype and analyze an independent set of 830 population-based sister case-control pairs for all promising SNPs from Phase I and also the surrounding haplotype-tagging and functional SNPs in the haplotypes containing these SNPs. Phase II provides robustness against false positives due either to confounding by population structure or to multiple comparisons in Phase I analyses. This genome-wide association study offers several strengths, including the availability of large numbers of population-based, well-matched young cases and controls, the ability to control confounding by population structure using a robust sister-pair design, and the extended genomic coverage provided by the combined Affymetrix and ParAllele high-density SNP panels. In conclusion, this research aims to identify new genes for early-onset breast cancer, which is a major source of morbidity, mortality and loss of life expectancy throughout the world. ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project--Cooperative Agreements (U01)
Project #
1U01CA122171-01
Application #
7131498
Study Section
Special Emphasis Panel (ZRG1-HOP-N (02))
Program Officer
Seminara, Daniela
Project Start
2006-09-28
Project End
2006-11-30
Budget Start
2006-09-28
Budget End
2006-11-30
Support Year
1
Fiscal Year
2006
Total Cost
$2,180,106
Indirect Cost
Name
Columbia University (N.Y.)
Department
Public Health & Prev Medicine
Type
Schools of Public Health
DUNS #
621889815
City
New York
State
NY
Country
United States
Zip Code
10032
Scannell Bryan, Molly; Argos, Maria; Andrulis, Irene L et al. (2018) Germline Variation and Breast Cancer Incidence: A Gene-Based Association Study and Whole-Genome Prediction of Early-Onset Breast Cancer. Cancer Epidemiol Biomarkers Prev 27:1057-1064
Kibriya, Muhammad G; Jasmine, Farzana; Parvez, Faruque et al. (2017) Association between genome-wide copy number variation and arsenic-induced skin lesions: a prospective study. Environ Health 16:75
Scannell Bryan, Molly; Argos, Maria; Andrulis, Irene L et al. (2017) Limited influence of germline genetic variation on all-cause mortality in women with early onset breast cancer: evidence from gene-based tests, single-marker regression, and whole-genome prediction. Breast Cancer Res Treat 164:707-717
Michailidou, Kyriaki (see original citation for additional authors) (2017) Association analysis identifies 65 new breast cancer risk loci. Nature 551:92-94
Southey, Melissa C (see original citation for additional authors) (2016) PALB2, CHEK2 and ATM rare variants and cancer risk: data from COGS. J Med Genet 53:800-811
Ahsan, Habibul; Halpern, Jerry; Kibriya, Muhammad G et al. (2014) A genome-wide association study of early-onset breast cancer identifies PFKM as a novel breast cancer gene and supports a common genetic spectrum for breast cancer at any age. Cancer Epidemiol Biomarkers Prev 23:658-69
Rundle, Andrew; Ahsan, Habibul; Vineis, Paolo (2012) Better cancer biomarker discovery through better study design. Eur J Clin Invest 42:1350-9
Pierce, Brandon L; Tong, Lin; Kraft, Peter et al. (2012) Unidentified genetic variants influence pancreatic cancer risk: an analysis of polygenic susceptibility in the PanScan study. Genet Epidemiol 36:517-24
Jasmine, Farzana; Rahaman, Ronald; Dodsworth, Charlotte et al. (2012) A genome-wide study of cytogenetic changes in colorectal cancer using SNP microarrays: opportunities for future personalized treatment. PLoS One 7:e31968
Jasmine, Farzana; Rahaman, Ronald; Roy, Shantanu et al. (2012) Interpretation of genome-wide infinium methylation data from ligated DNA in formalin-fixed, paraffin-embedded paired tumor and normal tissue. BMC Res Notes 5:117

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