Biological Basis of Breast Density and Cancer Risk

描述（由申请人提供）： 虽然通过乳房X光检查测量的高乳腺密度是乳腺癌风险最强的预测因素之一，但我们对乳腺密度的生物学基础以及它与癌症风险增加的原因或方式知之甚少。为了解决这个问题，我们需要一种结合临床/基础科学的方法来获得更准确和信息量更大的技术来测量乳腺摄影密度，更全面地了解产生乳腺密度的生物学，最重要的是，找到一种方法来确定这种生物学的特定方面，这些方面有助于增加人类乳腺癌的风险。我们的多学科研究将首先检查人体组织，以解决乳腺密度的组织学和病理生理学基础。为了扩展这些研究，我们将使用动物模型来测试通过分析人体组织产生的预测，因为小鼠模型提供了一种更容易操作的体内环境。我们将使用（并开发）高分辨率的体积生物成像，以空间配准乳腺密度的临床X射线图像的组织学和组织成分，乳腺密度的基础。这些信息将指导我们对同一组织进行分子分析，以产生乳腺密度的全面分子和细胞画像。使用人体组织的体内和体外结构，遗传，分子和功能分析的强大组合，我们将确定将高乳腺密度与乳腺癌风险增加联系起来的候选标志物。我们将使用大型，明确定义和独特的基于人群的队列来测试我们的假设和验证标志物，这些标志物将提高临床医生识别乳腺癌风险显著增加的女性的能力。我们假设乳腺密度增加可能是生物过程的最终结果，导致细胞-细胞和/或细胞-细胞外基质（ECM）相互作用的改变，这些都是乳腺癌风险增加的原因。这些改变的相互作用受到遗传、生理和环境因素的影响，并产生高乳腺密度特征性的组织表型（过量胶原蛋白、组织重塑等）。这些表型特征已在对组织重塑或损伤的反应发生的情况下观察到，例如在乳腺发育（分支形态发生）、伤口愈合或恶性肿瘤的促纤维增生反应中。在这些过程中，“活化的基质”导致胶原蛋白和腱生蛋白的水平增加、基质重塑和对位于其中的细胞组分的改变的细胞周期控制。我们的两名研究人员（Tlsty和Alcohos-Hoff）先前的工作表明，这种基质可以显著影响人类和小鼠模型中的肿瘤发生。适当的基质-上皮相互作用实际上可以抑制上皮细胞中癌前表型的表达，相反，改变的基质-上皮相互作用可以促进癌前病变进展为恶性肿瘤的可能性。来自项目1中的新型成像、项目2和4中的细胞、分子和功能分析以及项目3中的分子标志物的流行病学评估的信息的组合有可能创建几种新的和临床上有用的乳腺密度的放射学和/或分子测量，其比乳腺X线摄影密度更特异性地用于估计癌症风险。

DESCRIPTION (provided by applicant): While high breast density, as measured by mammography, is one of the strongest predictors of breast cancer risk, we know little about the biological basis of breast density or why or how it is associated with increased cancer risk. To address this problem we need a combined clinical/ basic science approach to obtain more accurate and informative techniques to measure mammographic density in the clinic, a fuller understanding of the biology that generates breast density and, most importantly, a way to identify specific aspects of this biology that contribute to increased risk for human breast cancer. Our multidisciplinary investigation will first and foremost examine human tissue to address the histologic and pathophysiologic basis of breast density. To extend these studies, we will use animal models to test predictions generated by the analysis of human tissues since murine models provide an in vivo setting that can be more easily manipulated. We will use (and develop) high-resolution, volumetric bio-imaging to spatially co-register clinical X-ray images of breast density to the histology and tissue composition that underlies breast density. This information will guide our molecular analysis of the same tissue to produce a comprehensive molecular and cellular portrait of breast density. Using a powerful combination of in vivo and in vitro structural, genetic, molecular and functional analyses of human tissue, we will identify candidate markers that link high breast density with an increased risk for breast cancer. We will use large, well-defined and unique population-based cohorts to test our hypotheses and validate markers that would enhance a clinician's ability to identify those women at significantly increased risk for breast cancer. We hypothesize that increased breast density may be the end result of biologic processes that result in altered cell-cell and/or cell-extracelluar matrix (ECM) interactions and that these are causal for increased breast cancer risk. These altered interactions are influenced by genetic, physiologic and environmental factors and generate the tissue phenotypes that are characteristic of high breast density (excess collagen, tissue remodeling, etc.). These phenotypic characteristics have been observed in conditions where response to tissue remodeling or damage is occurring such as in mammary gland development (branching morphogenesis), wound healing or the desmoplastic reaction of malignancies. In these processes, "activated stroma" results in increased levels of collagen and tenascin, stromal remodeling and altered cell cycle control for cellular components located within. Prior work from two of our Investigators (Tlsty and Barcellos-Hoff) has shown that such stroma can dramatically influence tumorigenesis in both human and murine models. Proper stromal-epithelial interactions can actually suppress the expression of preneoplastic phenotypes in epithelial cells and conversely, altered stromal-epithelial interactions can promote the probability that preneoplastic lesions progress to malignancy. The combination of information from the novel imaging in Project 1, the cellular, molecular and functional analyses in Projects 2 and 4 and the epidemiological assessment of molecular markers in Project 3 has the potential to create several new and clinically useful, radiographic and/or molecular measures of breast density that are more specific than mammographic density for estimating cancer risk.