Project 4: Genetic Predictors of Progression of Premalignant Breast Disease
Normal breast epithelial growth and differentiation is under the control of two well-studied molecular signaling pathways mediated by the epidermal growth factor (ERBB) and transforming growth factor (TGFβ) receptor families. These pathways are also closely intertwined in the etiology of benign proliferative breast disease and breast cancer. The overall objective of this study is to identify predictors of breast cancer by investigating how genetic variation within the well-defined ERBB and TGFβ signaling pathways interacts with histologically defined breast lesions to affect breast cancer risk. We will approach this objective with a study of a unique cohort of 7963 women who underwent biopsy for benign breast disease, 535 of whom have developed invasive breast cancer or ductal carcinoma in situ during follow-up. Cohort projections indicate that the number affected by breast cancer will expand to 908 over the next five years. The cohort is separately funded as the Nashville Breast Cohort, with a productive 30-year history of breast cancer investigation. The cohort is accompanied by epidemiological data of established breast cancer risk factors, paraffin-embedded tissue blocks of the initial benign breast disease biopsy, and rigorous histologic detail of both the initial biopsy and subsequent tumor. Our investigation will be conducted as a nested case-control study of these patients. Our aims build upon the high quality of this cohort, and bring together multidisciplinary expertise in epidemiology, genetics, and pathology.
Specific Aim 1. To evaluate the role of genes central to the ERBB signaling pathway system in breast cancer risk by linkage disequilibrium mapping. We hypothesize that common polymorphisms of the genes encoding key nodes of this signaling pathway affect the risk for breast cancer. We will address the hypothesis by selecting single nucleotide polymorphisms (SNPs) that efficiently capture genetic diversity at each gene by virtue of previously characterized patterns of linkage disequilibrium (LD). These tagging SNPs are selected using data from the International HapMap1 for 95 genes that encode core components of the ERBB pathway, including 28 genes that encode key nodes of cross-talk between the ERBB, phosphatidylinositol 3 kinase (PI3K), and protein kinase C (PKC) signaling pathways. The study will be conducted among 908 cases and 1816 matched controls from the Nashville Breast Cohort. Single allele- and haplotype-based analytic approaches will be applied to systematically address the hypothesis, without assumption of variant function.
Specific Aim 2. To evaluate the role of genes central to the TGFβ signaling pathway system in breast cancer risk by linkage disequilibrium mapping. The TGFβ and ERBB pathways form a complex signaling network that is strongly implicated in the development of breast cancer. The approach of Aim 2 mirrors that of Aim 1. We will fully capture the genetic diversity of 18 genes that encode core components of the TGFβ pathway for tests of association in the nested case-control study.
Specific Aim 3. To identify candidate etiologic variants of haplotypes that are significantly associated with breast cancer risk in Aims 1 and 2. We will re-sequence individuals carrying associated haplotypes to systematically discover all genetic variation in full linkage disequilibrium and marking the haplotypes. The narrow subset of these variants will most efficiently detect the risk haplotypes and may be subsequently evaluated for biological function. These may also suggest novel therapeutic targets for future interventions in breast cancer.
Specific Aim 4. To assess how genetic variation of the ERBB and TGFβ signaling network interacts with proliferative breast disease to affect breast cancer risk. Proliferative breast lesions are associated with a mild elevation in breast cancer risk and are thought to be the first step in a non-obligate process that can result in breast cancer. We will test the hypothesis that proliferative breast disease interacts synergistically with genetic variants of the signaling network to significantly elevate breast cancer risk.