Mammographic breast density is a strong predictor of breast cancer risk. Women with radiodense areas? covering greater than 50% of the tissue area have a 3 to 5 fold increase in risk for breast cancer compared? with women with little or no radiodense area. It is estimated that almost 1/3 of breast cancer incidence is? due to biological variables (both genetic and environmental) that modulate breast density. Given this? strong correlation between breast density and risk for breast cancer, it is surprising that so little is known? about the character or origin of dense breast tissue.? We hypothesize that the molecular interactions between stroma and epithelium represent some of? the very first changes that occur within breast tissue allowing malignant transformation and may therefore? serve as a predictor of breast cancer in its earliest stages. We propose that features of increased stromal? remodeling noted in the extracellular matrix (ECM) and molecular markers in mammographically dense? breasts are indicative of an 'activated' stroma. Activated stroma (AS) is similar to stroma formed during? normal, non-pathological processes such as morphogenesis and wound healing, and can also be found in? pathological states such as desmoplasia. While normal stromal-epithelial interactions actively suppress? preneoplastic phenotypes, activated stroma can become an active participant in cancer progression. We? hypothesize that the mechanistic links between high breast density and increased breast cancer? risk lie in the signal transduction pathways that lead to increased breast density and? concomitantly promote malignant progression in initiated cells in the adjacent epithelium. This? proposal will examine several aspects of the phenotypic, molecular and functional differences of? mammary fibroblasts and epithelial cells isolated from individuals with high or low mammographic density? that have or have not developed breast cancer. Histologic and molecular evaluation of these tissues will? provide novel markers that define increased breast density and increased cancer risk. In Project 2, we will? 1) Determine the cellular and histological composition of human breast tissues with high and low? mammographic density. A three-dimensional reconstruction (3D) of the gland, linked to the BioSig? database, will integrate this morphologic data with molecular data. (2) Using cDNA microarrays, we will? compare expression profiles from tissues with high and low mammographic densities (a) to each other? and (b) to matched tissues from individuals that have developed cancer at a distant site. These markers? can be used in Project 3 to evaluate paraffin-preserved benign breast biopsy tissue by immunostains for? association of risk for breast cancer.
In Specific Aim 3 In vivo and in vitro recombinant experiments will? provide insights into the cell combinations that generate increased breast density and molecular markers? associated with increased breast cancer risk. (3) Finally we will determine the functional phenotype of? fibroblast cells obtained from human breast tissues with high and low mammographic density. We have? found that fibroblasts from tissue with high mammographic density retain differential expression of? biologically relevant pathways such as the IGF-axis. These fibroblasts have been demonstrated to? facilitate tumor progression when placed in a murine recombinant model. The proposed studies will? determine the molecular basis for fibroblast enhancement of tumorigenic phenotypes.
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