Breast cancer is the most common malignancy among women in the United States and many other parts of the world. It is believed that most breast cancers are caused by genetic factors and gene-environment interactions. Over the past 10 years many genetic polymorphisms have been investigated in relation to breast cancer risk, yet few of the associations found have been confirmed. As part of this renewal application for the Shanghai Breast Cancer Study (SBCS R01CA64277), a large population-based case-control study of breast cancer funded by NCI since 1996, we propose several novel approaches to circumvent the limitations of the methodologies currently used for studying low-penetrance genetic variants for the risk of complex, multifactorial diseases. First, in addition to studying common genetic variants using haplotype tagging SNPs (htSNP), we propose to test the hypothesis that a large part of breast cancer susceptibility may be due to the summation of the effect from multiple low-frequency genetic variants. We also propose to use resequencing data to enhance htSNP selection and reduce misclassification errors and use quantitative functional data to define risk groups. With these new approaches, we will comprehensively evaluate genetic polymorphisms in the TGF2 signaling pathway in a two-phase study including approximately 6200 cases and controls. Genetic variants in major TGF2 pathway genes will be screened in Phase I, and promising associations will be validated in Phase II along with a series of in vitro functional assays. Breast cancer patients are being followed for cancer recurrence, relapse, and death, and the association of TGF2 pathway gene variants with breast cancer survival will be evaluated in a two-phase study. Numerous in vitro and animal studies have clearly demonstrated that the TGF2 signaling pathway plays a pivotal role in the development and progression of breast cancer. It remains unclear, however, whether these laboratory findings can be translated into cancer prevention strategies and clinical practice. The proposed study, with its strong methodology and novel approaches, has outstanding potential for discovering genetic markers that will be valuable in identifying high- risk women for cost-efficient breast cancer prevention and personalized treatment and follow-up care after cancer diagnosis. The proposed novel approaches will not only facilitate the evaluation of the study hypotheses, but also provide significant data to expand and guide future studies of low-penetrance genetic factors for breast cancer and other complex, multifactorial diseases.
It is believed that most breast cancers are caused by genetic factors and gene- environment interactions. Herein, we propose a large epidemiologic study to comprehensively evaluate genetic markers in relation to breast cancer risk and survival. The results from this study will be valuable in identifying high-risk women for cost- efficient breast cancer prevention and personalized treatment and follow-up care after cancer diagnosis.
|Shi, Jiajun; Zhang, Yanfeng; Zheng, Wei et al. (2016) Fine-scale mapping of 8q24 locus identifies multiple independent risk variants for breast cancer. Int J Cancer 139:1303-17|
|Luu, Hung N; Long, Jirong; Wen, Wanqing et al. (2016) Association between genetic risk score for telomere length and risk of breast cancer. Cancer Causes Control 27:1219-28|
|Easton, Douglas F; Lesueur, Fabienne; Decker, Brennan et al. (2016) No evidence that protein truncating variants in BRIP1 are associated with breast cancer risk: implications for gene panel testing. J Med Genet 53:298-309|
|Wen, Wanqing; Shu, Xiao-Ou; Guo, Xingyi et al. (2016) Prediction of breast cancer risk based on common genetic variants in women of East Asian ancestry. Breast Cancer Res 18:124|
|Darabi, Hatef; Beesley, Jonathan; Droit, Arnaud et al. (2016) Fine scale mapping of the 17q22 breast cancer locus using dense SNPs, genotyped within the Collaborative Oncological Gene-Environment Study (COGs). Sci Rep 6:32512|
|(2016) PALB2, CHEK2 and ATM rare variants and cancer risk: data from COGS. J Med Genet 53:800-811|
|Wen, Wanqing; Kato, Norihiro; Hwang, Joo-Yeon et al. (2016) Genome-wide association studies in East Asians identify new loci for waist-hip ratio and waist circumference. Sci Rep 6:17958|
|Han, Mi-Ryung; Long, Jirong; Choi, Ji-Yeob et al. (2016) Genome-wide association study in East Asians identifies two novel breast cancer susceptibility loci. Hum Mol Genet 25:3361-3371|
|(2016) Functional mechanisms underlying pleiotropic risk alleles at the 19p13.1 breast-ovarian cancer susceptibility locus. Nat Commun 7:12675|
|Samuels, David C; Wang, Jing; Ye, Fei et al. (2016) Heterozygosity Ratio, a Robust Global Genomic Measure of Autozygosity and Its Association with Height and Disease Risk. Genetics :|
Showing the most recent 10 out of 206 publications