In sub-Project 2 we will conduct a series of in vitro, and in silico investigations to assign a gene function to each validated risk variant and examine whether loss or gain of function of these genes in breast epithelial or stromal cells alter phenotypes in vitro in a 3-D model of breast morphogenesis and oncogenesis. As an initial assessment of potential gene function, we will use the DASL assay to determine the level of 24,000 RNA transcripts in breast tumor and normal tissue, from women for whom we also have an lllumina 540 GWAS data available. This will enable us to conduct expression quantitative trait locus (eQTL) analyses of cis and trans associations between >2.5 million SNPs (genotyped and imputed) and the ievels of each transcript and transcription patterns (Aim 1). We will develop an online tool and make these data publicly available that breast cancer researchers will then be able to use to conduct their own analyses (Aim 1). Using computational techniques we will conduct Bayesian Network analyses, and Gene-set enrichment analyses to identify networks of genes in which alterations of expression can be linked to specific germline risk variants (Aim 2). For risk variants that are in intergenic regions and potential enhancers, we will use Chromosomal Conformation Capture (3C) assays to examine whether these risk loci physically interact with distant DNA loci across the genome (Aim 3). Finally, for the genes that are identified in Aims 1-3, we will explore whether overexpression or knockdown of these genes alters the phenotypes of breast epithelial and stromal cells in a 3-D model of breast cancer development (Aim 4). These approaches are all directed at elucidating the mechanisms by which germline risk variants alter risk of breast cancer, information that may then lead to development of pharmacologic approaches to breast cancer prevention and treatment.
In sub-Project 2 we will conduct a series of laboratory and computational investigations to assign a gene function to each validated genetic risk variant for breast cancer. We will also examine how loss or gain of function of these genes alter phenotypes in a 3-D model of breast morphogenesis and oncogenesis. Data generated by this proposal will be critical in translating GWAS data into clinical targets that can be utilized for early detection, risk stratification, and drug development for the prevention and treatment of breast cancer.
|Dite, Gillian S; MacInnis, Robert J; Bickerstaffe, Adrian et al. (2016) Breast Cancer Risk Prediction Using Clinical Models and 77 Independent Risk-Associated SNPs for Women Aged Under 50 Years: Australian Breast Cancer Family Registry. Cancer Epidemiol Biomarkers Prev 25:359-65|
|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|
|Painter, Jodie N; O'Mara, Tracy A; Marquart, Louise et al. (2016) Genetic Risk Score Mendelian Randomization Shows that Obesity Measured as Body Mass Index, but not Waist:Hip Ratio, Is Causal for Endometrial Cancer. Cancer Epidemiol Biomarkers Prev 25:1503-1510|
|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|
|Bonilla, Carolina; Lewis, Sarah J; Martin, Richard M et al. (2016) Pubertal development and prostate cancer risk: Mendelian randomization study in a population-based cohort. BMC Med 14:66|
|(2016) PALB2, CHEK2 and ATM rare variants and cancer risk: data from COGS. J Med Genet 53:800-811|
|Karami, Sara; Han, Younghun; Pande, Mala et al. (2016) Telomere structure and maintenance gene variants and risk of five cancer types. Int J Cancer 139:2655-2670|
|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|
|Silvestri, Valentina; Barrowdale, Daniel; Mulligan, Anna Marie et al. (2016) Male breast cancer in BRCA1 and BRCA2 mutation carriers: pathology data from the Consortium of Investigators of Modifiers of BRCA1/2. Breast Cancer Res 18:15|
Showing the most recent 10 out of 123 publications