Subregional Breast Density and Cancer Risk

次区域乳房密度和癌症风险

• 批准号: 8436160
• 负责人: JOHN Alan SHEPHERD
• 金额: $ 15.72万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-03-01 至 2015-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8436160
• 关键词: Adipose tissue; Affect; Age; Automobile Driving; Behavior; Biological; Biological Markers; Biopsy; Breast; Breast Cancer Risk Factor; Caliber; Clinical; Collaborations; Data; Data Set; Development; Dimensions; Drug or chemical Tissue Distribution; Epithelial; Ethnic Origin; Exclusion; Fractals; Frequencies; Future; Goals; Health; High Risk Woman; Image; Individual; Lesion; Localized Malignant Neoplasm; Malignant Neoplasms; Mammary Gland Parenchyma; Mammographic Density; Mammography; Masks; Measurement; Measures; Mission; Morphology; Noninfiltrating Intraductal Carcinoma; Outcome; PTGS2 gene; Peripheral; Population; Proteins; Public Health; Questionnaires; Research; Risk; Risk Assessment; Risk Factors; Risk Marker; Risk Reduction; Roentgen Rays; Serum; Serum Markers; Severities; Smooth Muscle Actin Staining Method; Spatial Distribution; Structure; Testing; Texture; Thick; Tissues; Universities; Vermont; Woman; Women' s Health; Work; breast density; cancer risk; cancer site; cancer type; clinical risk; cohort; density; improved; in vivo; malignant breast neoplasm; morphometry; mortality; novel; screening; stromelysin 3

DESCRIPTION (provided by applicant): Identifying women at risk for breast cancer is not part of the current clinical paradigm for women's health even though strong risk factors, such as breast density, have been identified. A high percentage of dense parenchyma on mammograms appears to give a 4-6 fold risk to develop breast cancer. The biological cause for the association is unclear even after 20 years of study. The long-term goal of this proposed research is to determine the best global or local measure of breast density for risk assessment of high-mortality cancers. The objective of this application is to describe the relationship of specific local measures of volume breast density and density morphology to cancer risk for invasive cancers as well as DCIS cases, and to discover what serum, tissue, or clinical biomarkers act as a determinant of the macro distribution of dense breast tissue. The central hypothesis is that subregional measurements of the percent fibroglandular volume density are more strongly associated with local and global breast cancer risk. Very little is known of the distribution of dense tissue within breast tissue in women with cancer versus those without because an in vivo description of dense tissue distribution has not been available. Our secondary hypothesis is that specific biomarkers of breast density act as morphostats for density macro structure. Our approach is unique in that we will be using a novel pixel-by-pixel measure of volumetric breast density called Single X-ray Absorptiometry (SXA). Our first specific aim is to identify subregions of dense breast volume associated with subsequent breast cancer in women undergoing mammography. The working hypothesis for this aim is that subregions of the breast may be stronger risk predictor of local cancer in that region than global breast density. In addition, subregional density may be a stronger risk predictor of a woman's risk of breast cancer than global breast density due to the exclusion of peripheral adipose that envelopes the parenchyma. Our second specific aim is to Identify the association of breast morphology to risk and to key tissue, serum, and clinical correlates to test the morphostatic behavior of breast density. The coarse distribution of density is known to show morphostatic qualities between women as well as between a woman's two breasts. Our working hypothesis is that there may be a particular spatial distribution, or morphology, of dense tissue that is associated with cancer risk independent of the magnitude of the density. Our expected outcome will include: development of new regions of local breast density that will be made available for future studies using our large cohort, confirmation of breast density as either a local or global risk factor, and the identification of the most likely biomarker candidates driving breast density morphometry. Our findings will reduce the risks of harms for women undergoing mammography by providing a cancer risk marker to intelligently reduce the screening frequency of very low risk women. It will aid in the decreased mortality of high risk women by their more accurate identification and targeting for use of more sensitive imaging and risk reduction strategies.

描述（由申请人提供）：尽管已经确定了诸如乳腺密度等强风险因素，但确定有乳腺癌风险的女性并不是当前女性健康临床范例的一部分。乳房X光照片上高比例的致密实质组织似乎使患乳腺癌的风险增加了4-6倍。即使经过 20 年的研究，这种关联的生物学原因仍不清楚。这项拟议研究的长期目标是确定乳腺密度的最佳全球或局部测量方法，以评估高死亡率癌症的风险。本申请的目的是描述乳腺体积密度和密度形态的特定局部测量与浸润性癌症以及导管原位癌病例的癌症风险之间的关系，并发现哪些血清、组织或临床生物标志物充当乳腺体积密度和密度形态的决定因素。致密乳腺组织的宏观分布。核心假设是，纤维腺体体积密度百分比的次区域测量与局部和全球乳腺癌风险更密切相关。对于患有癌症的女性与未患有癌症的女性的乳腺组织内致密组织的分布知之甚少，因为尚未获得致密组织分布的体内描述。我们的第二个假设是乳腺密度的特定生物标志物充当密度宏观结构的形态调节剂。我们的方法的独特之处在于，我们将使用一种新颖的逐像素测量乳房体积密度的方法，称为单 X 射线吸收测定法 (SXA)。我们的第一个具体目标是确定接受乳房X光检查的女性中与后续乳腺癌相关的致密乳腺体积子区域。该目标的工作假设是，与整体乳房密度相比，乳房的子区域可能是该区域局部癌症的更强的风险预测因子。此外，由于排除了包裹实质的外周脂肪，次区域密度可能比整体乳腺密度更能预测女性患乳腺癌的风险。我们的第二个具体目标是确定乳房形态与风险以及关键组织、血清和临床相关因素的关联，以测试乳房密度的形态静态行为。已知密度的粗略分布显示了女性之间以及女性两个乳房之间的形态静态特性。我们的工作假设是，致密组织可能存在特定的空间分布或形态，与癌症风险相关，而与密度的大小无关。我们的预期成果将包括：开发局部乳腺密度的新区域，以便使用我们的大型队列进行未来的研究，确认乳腺密度作为局部或全球风险因素，以及识别最有可能的生物标记候选物乳腺密度形态测量。我们的研究结果将通过提供癌症风险标记来智能地降低极低风险女性的筛查频率，从而降低接受乳房X光检查的女性受到伤害的风险。它将通过更准确的识别和针对使用更灵敏的成像和降低风险策略的目标，帮助降低高危女性的死亡率。