Integrated Biomarkers to Characterize Breast Cancer Risk

描述(由申请人提供)：本提案的目的是开发、验证和集成新的生物标记物，以表征患乳腺癌、患乳腺癌或进展为乳腺癌的风险。我们已经组建了一支由学术和行业研究人员组成的卓越的多学科团队，他们正在使用基于分子和细胞的技术来开发生物标记物。我们将使用强大的临床资源，包括独特的回顾和前瞻性数据集，进一步开发和评估它们，并将它们彼此集成(交叉验证)，并纳入临床决策(建模)的背景中。拟议的研究试图重新定义从传统的乳腺癌筛查到联合检测/生物学特征/风险预测的范式。我们的假设是：1)SNP(生殖系)和蛋白质组(血清)谱可以定义乳腺癌风险并检测早期癌症，并且可以组合用于分级筛查策略；2)有希望指示进展和转移风险的生物标记物，包括基于组织的表达谱和循环肿瘤细胞(CTCs)的检测，应该直接比较以及整合，以最大限度地提供有关表型和风险的信息；3)联合分析生物标记物不仅更有效，而且可能导致综合策略，以实现最佳临床应用。为了完成我们的工作，我们提出了4个项目：项目1：在可触及和乳房摄影异常的临床评估的背景下，开发基于SNP和血清蛋白质组学的癌症检测(初级和继发性)和风险描述；项目2：利用回顾数据集(盖伊医院：自然历史人群，25年随访，没有系统治疗；加州大学旧金山分校综合微转移/CTC数据集；UCSF孢子DCIS数据集)，开发基于石蜡切片的表达谱，以预测疾病进展的风险；项目3：开发和验证基于CTC的分析，包括CTC检测的领先方法；与基于组织的生物标记物交叉验证CTC数据；开发CTC的分子图谱方法；项目4：在一项前瞻性临床研究中评估有前景的生物标记物，以交叉验证化验，并纳入反映所检测癌症生物学特性的预测结果模型。

DESCRIPTION (provided by applicant): The purpose of this proposal is to develop, validate and integrate novel biomarkers to characterize the risk of getting, having, or progressing with breast cancer. We have assembled a superb multidisciplinary team of academic and industry investigators who are using molecular and cell based technologies for biomarker development. We will further develop and evaluate them using powerful clinical resources, including unique retrospective and prospective data sets, and will integrate them with each other (cross validation) and into the context of clinical decision (modeling). The proposed studies attempt to redefine the paradigm from conventional breast cancer screening to combined detection/biological characterization/risk projection. Our hypotheses are that: 1) SNP (germline) and proteomic (serum) profiles can define breast cancer risk and detect early cancer, and may be combined for a tiered screening strategy; 2) Promising biomarkers indicative of risk of progression and metastasis, including tissue-based expression profiling and detection of circulating tumor cells (CTCs), should be directly compared as well as integrated to maximize information about phenotypes and risk; and 3) Combined analysis of biomarkers is not only more efficient but may lead to integrated strategies for optimal clinical application. In order to accomplish our work we propose 4 projects: Project 1: Develop SNP- and serum proteomics-based profiles for cancer detection (primary and secondary) and risk profiling in the context of clinical evaluation of palpable and mammographic abnormalities; Project 2: Develop paraffin based expression profiles to predict risk of disease progression using retrospective datasets (Guy's Hospital: natural history population with 25 yr follow-up and no systemic therapy; UCSF comprehensive micrometastases/CTC data set; UCSF SPORE DCIS data set); Project 3: Develop and validate CTC-based assays, including leading approaches for CTC detection; cross-validate CTC data with tissue-based biomarkers; and develop methods for molecular profiling of CTCs; Project 4: Evaluate promising biomarkers in a prospective clinical study for cross validation of assays and integration into predictive outcome models that reflect the biological properties of the cancer detected.