Breast Pre-Cancer Atlas Center

摘要 浸润性乳腺癌的发展可能经常通过一种称为 导管原位癌(DCIS)。DCIS是一种常见的临床诊断，本质上是一种疾病 在乳房X光检查中发现异常的乳房钙化而触发的筛查。在此之前 乳房X光检查的出现，DCIS是一个偶然且相对不常见的发现。超过6万名女性 在美国，每年都会出现这种诊断，证据相对薄弱 指导疾病管理，从积极监测到双侧乳房切除术。我们 建议汇编DCIS的多维和多尺度数据，以构建一份癌症前地图集，该地图集 可以用来更好地了解疾病，也可以更好地对进展风险进行分层。为了做到这一点，我们 已经组建了一支研究团队，具有深入和互补的临床、实验和 在DCIS和乳腺癌方面的量化专业知识和经验。此外，我们还进行了这些研究 充分考虑肿瘤的进化和生态学，因为它与癌症前发展和 进步。拟议的Atlas建设的具体方面包括：1)几种类型的DCIS 将捕获空间和纵向信息的队列，包括预期临床试验队列 正在进行主动监视，2)旨在保持相关空间组织的分析 基于放射学-组织学-细胞学的进化和图谱构建考虑的疾病 分子配准方法，4)包括整个肿瘤、单个肿瘤在内的多尺度表征 导管和单细胞水平，5)相关参数的表征，包括突变、拷贝数 改变、甲基化、基因表达和包括炎症细胞在内的微环境因素 配置文件。6)将乳腺癌固有亚型范式纳入分析阶段，以及7) 分层、空间和纵向数据可视化。总体而言，这项工作将提供全面的 指导下一代对DCIS和其他癌前病变的研究的平台。

ABSTRACT Development of invasive breast cancer may frequently progress through a preinvasive precursor called ductal carcinoma in situ (DCIS). DCIS is a common clinical diagnosis that is essentially a disease of screening triggered by the detection of abnormal breast calcifications on mammography. Before the advent of mammography, DCIS was an incidental and relatively uncommon finding. Over 60,000 women in the United States will be presented with this diagnosis each year with relatively weak evidence-based guidance for disease management which ranges from active surveillance to bilateral mastectomy. We propose to compile multi-dimensional and multi-scale data on DCIS to construct a Pre-Cancer Atlas that can be used to better understand the disease but also to better stratify risk of progression. To do this, we have assembled a team of investigators with deep and complementary clinical, experimental, and quantitative expertise and experience with DCIS and breast cancer. Further, we conduct these studies with full consideration of tumor evolution and ecology as it pertains to precancer development and progression. Specific aspects of the proposed Atlas construction include: 1) Several types of DCIS cohorts that will capture spatial and longitudinal information including a prospective clinical trial cohort undergoing active surveillance, 2) Analyses designed to maintain relevant spatial organization of the disease for evolutionary and Atlas building considerations based on 3) Radiologic-histologic-cellular- molecular registration approaches, 4) Characterization at multiple scales including whole tumor, single duct and single cell levels, 5) Characterization of relevant parameters including mutations, copy number changes, methylation, gene expression, and microenvironmental elements including inflammatory cell profiles. 6) Incorporation of the breast cancer intrinsic subtype paradigm into the analytic phase, and 7) Layered, spatial, and longitudinal data visualization. Overall, this work will provide a comprehensive platform to guide the next generation of studies on DCIS and other precancers.