Vermont Breast Cancer Molecular Characterization Laboratory

 描述（由申请人提供）：在过去的30年里，乳腺癌筛查和治疗的进展降低了美国乳腺癌的死亡率。然而，随着筛查性乳房X光检查的广泛采用，早期乳腺癌诊断率急剧增加，但这并没有被晚期疾病的下降所抵消。越来越多的证据表明，如果不是通过筛查发现，那么很大一部分筛查发现的乳腺癌在临床上永远不会出现。虽然关于过度诊断的程度存在广泛的争论，但人们普遍认为，迫切需要新的方法来区分惰性筛查发现的病例与可能危及生命的病例。肿瘤微环境在乳腺癌进展中的作用越来越被认识到。一些证据表明，乳腺肿瘤的发生受到恶性乳腺上皮细胞和肿瘤微环境的非肿瘤细胞之间的活性信号传导的严重影响。我们提案的目标是通过微创方法识别肿瘤微环境特征，预测早期筛查检测的乳腺癌的侵袭性。我们将利用和完善最先进的技术来表征基于细胞组成和特定细胞群的基因表达的侵袭性特征，这些细胞群在间隔和间歇检测的浸润性乳腺癌的肿瘤微环境中。然后，我们将确定这些侵袭性肿瘤微环境特征在早期筛查检测的乳腺癌中的存在是否与进展相关。我们将从佛蒙特州乳腺癌监测系统（VBCSS）获得800份福尔马林固定、石蜡包埋标本的回顾性数据，以供分析，该系统收集了自1996年以来佛蒙特州所有接受乳腺成像的女性的综合患者、放射学、病理学、治疗和结局数据。VBCSS拥有超过1，200个中央审查DCIS标本的大型现有储存库，并可访问佛蒙特州诊断病例的10，000多个浸润性乳腺癌标本。我们还将通过佛蒙特州癌症中心组织生物库进行新鲜标本的前瞻性收集，该组织生物库也与VBCSS的综合数据相关联。对侵袭性和惰性肿瘤微环境特征的识别将促进为具有良好预后的女性子集开发更保守的治疗策略，并为预后不良的病例提供治疗干预的新靶点。我们已经组建了一个多学科的研究团队，在细胞和分子癌症生物学，病理学，癌症筛查和流行病学方面拥有国家认可的专业知识，以及长期的基于生产联盟的合作研究记录。佛蒙特州乳腺癌分子表征实验室将为联盟提供科学领导，技术资源，并访问与VBCSS丰富数据相关的回顾性和前瞻性收集的乳腺标本的大型存储库。

 DESCRIPTION (provided by applicant): Advances in breast cancer screening and treatment have reduced breast cancer mortality in the US over the past 30 years. However, the widespread adoption of screening mammography has been accompanied by dramatic increases in early stage breast cancer diagnoses that have not been offset by declines in advanced stage disease. Accumulating evidence suggests that a substantial fraction of screen-detected breast cancers would never have emerged clinically if not detected through screening. While there is extensive debate regarding the magnitude of overdiagnosis, there is widespread consensus that new approaches are urgently needed to distinguish indolent screen-detected cases from those that may be life threatening. The role of the tumor microenvironment in breast cancer progression has been increasingly recognized. Several lines of evidence indicate that breast tumorigenesis is critically influenced by active signaling between malignant breast epithelial cells and non-neoplastic cells of the tumor microenvironment. The goal of our proposal is to identify tumor microenvironment signatures that predict the aggressiveness of early stage, screen-detected breast cancers by minimally invasive methods. We will leverage and refine state-of-the-art technologies to characterize aggressive signatures based on the cellular composition and gene expression of specific cell populations within the tumor microenvironment of interval- and symptom-detected invasive breast cancers. We will then determine whether the presence of these aggressive tumor microenvironment signatures in early stage, screen-detected breast cancer is associated with progression. We will obtain retrospective data on 800 formalin-fixed, paraffin-embedded specimens for analysis from the Vermont Breast Cancer Surveillance System (VBCSS), which has collected integrated patient, radiology, pathology, treatment, and outcomes data on all women undergoing breast imaging in the state of Vermont since 1996. The VBCSS has a large existing repository of over 1,200 centrally-reviewed DCIS specimens and access to over 10,000 invasive breast cancer specimens for cases diagnosed in the state of Vermont. We will also engage in prospective collection of fresh specimens via the Vermont Cancer Center Tissue Biobank, which is also linked to the integrated data of the VBCSS. The identification of aggressive and indolent tumor microenvironment signatures will promote the development of more conservative treatment strategies for the subset of women with favorable prognosis and suggest novel targets for therapeutic intervention in cases with unfavorable prognosis. We have assembled a multidisciplinary research team with nationally recognized expertise in cellular and molecular cancer biology, pathology, cancer screening, and epidemiology, as well as a long track record of productive consortium-based collaborative research. The Vermont Breast Cancer Molecular Characterization Laboratory will provide the consortium with scientific leadership, technical resources, and access to a large repository of retrospective and prospectively collected breast specimens linked to the rich data of the VBCSS.