Breast Pre-Cancer Atlas Center

摘要 侵袭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，基本上是一种疾病， 通过在乳房X线摄影术上检测到异常乳房钙化而触发的筛查。前 在乳房X光检查出现后，DCIS是一种偶然的和相对罕见的发现。超过6万名妇女 在美国，每年都会出现这种诊断， 从积极监测到双侧乳房切除术的疾病管理指南。我们 建议编制多层面和多尺度的DCIS数据，以构建癌前病变图谱， 可以用来更好地了解疾病，也可以更好地分层疾病进展的风险。为此我们 已经组建了一个研究团队，具有深入和互补的临床，实验和 DCIS和乳腺癌的定量专业知识和经验。此外，我们进行这些研究 充分考虑肿瘤演变和生态学，因为它涉及癌前发展， 进展拟议的Atlas建设的具体方面包括： 将捕获空间和纵向信息的队列，包括前瞻性临床试验队列 2）旨在保持相关空间组织的分析， 基于3）放射学-组织学-细胞学- 分子配准方法，4）在多个尺度上的表征，包括整个肿瘤，单个肿瘤， 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、基因表达和微环境因素，包括炎症细胞， 数据区. 6)将乳腺癌内在亚型范例纳入分析阶段，以及7） 分层、空间和纵向数据可视化。总的来说，这项工作将提供一个全面的 平台，以指导下一代DCIS和其他癌前病变的研究。

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.