Molecular Diagnostics for Breast Cancer

乳腺癌分子诊断

• 批准号: 6640605
• 负责人: PHILIP S BERNARD
• 金额: $ 48万
• 依托单位: UNIVERSITY OF UTAH
• 依托单位国家: 美国
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-08-02 至 2005-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6640605
• 关键词: breast neoplasm /cancer diagnosis; breast neoplasms; clinical research; complementary DNA; diagnosis design /evaluation; diagnostic tests; gene expression; human subject; immunocytochemistry; microarray technology; molecular oncology; molecular pathology; neoplasm /cancer classification /staging; p53 gene /protein; polymerase chain reaction; tissue /cell culture

DESCRIPTION (provided by applicant): Advances in the biological sciences and technology are providing molecular targets with clinical utility for diagnosing and treating breast cancer. Current classifications in pathology for the diagnosis of breast cancer are based primarily on histopathological features and anatomic staging (i.e., tumor-node-metastasis). These criteria have prognostic significance but provide little information for guiding therapy. The only accepted molecular markers that predict response to therapy in breast cancer are the hormonal receptors for estrogen (ER) and progesterone (PgR). Other markers, such as HER-2/neu (erbB-2) and p53, continue to be studied for their predictive value. Recently, cDNA microarrays have shown that invasive breast carcinomas can be stratified based upon gene expression patterns and that these molecular "profiles" determine outcome. This molecular taxonomy agrees with the rudimentary classifications already used in pathology (e.g., ER and HER-2 status) and may provide additional information that can account for the observed phenotypic variation in clinical behavior. Our goals are to develop and implement molecular diagnostic tests for breast cancer. The incorporation of molecular targets into medicine for clinical trials and routine testing requires the development of assays that are amenable to the clinical laboratory. These assays need to be robust, rapid and cost-effective. Factors that facilitate finding statistical significance with many new markers include reaching an adequate study size and standardizing sample preparation, reagents and scoring criteria. We will use reverse transcription coupled to PCR (RT-PCR) to recapitulate microarray classifications using a selected minimal gene set. In addition, sequence-based methods and immunohistochemistry (IHC) will be used to assess p53 mutation status. Finally, a prospective study on 350 patients with breast cancer will be conducted. Tumors will be compared by cDNA microarray, real-lime quantitative RT-PCR and p53 status. Patients will be given the standard of care for treatment and clinical parameters will be correlated to molecular data. Multivariate analyses will be used to show statistical significance of molecular classifications. This study should provide a framework for molecular diagnostic testing of solid tumors in the clinical laboratory.

描述（由申请人提供）： 生物科学和技术的进步正在提供分子生物学， 用于诊断和治疗乳腺癌的具有临床实用性的靶点。 目前诊断乳腺癌的病理学分类是 主要基于组织病理学特征和解剖分期（即， 肿瘤-淋巴结-转移）。这些标准具有预后意义， 为指导治疗提供的信息很少。唯一被接受的分子 预测乳腺癌治疗反应的标志物是激素， 雌激素受体（ER）和孕激素受体（PgR）。其他标记，如 HER-2/neu（erbB-2）和p53的预测价值仍在研究中。 最近，cDNA微阵列显示，浸润性乳腺癌可以是 根据基因表达模式分层，这些分子 “概况”决定结果。这种分子分类学与 已经用于病理学的基本分类（例如，ER和HER-2 状态），并可以提供可以说明 观察到临床行为的表型变异。我们的目标是发展 并实施乳腺癌的分子诊断测试。掺入 用于临床试验和常规测试 需要开发适用于临床的测定法， 实验室这些检测方法需要稳健、快速和具有成本效益。因素 这有助于发现许多新标记物的统计学意义，包括 达到足够的研究规模并使样品制备、试剂 和评分标准。我们将使用逆转录结合PCR （RT-PCR）使用选择的最小的 基因组此外，基于序列的方法和免疫组织化学（IHC） 将用于评估p53突变状态。最后，一项关于 将对350例乳腺癌患者进行研究。肿瘤将通过以下方式进行比较： cDNA微阵列、实时定量RT-PCR和p53状态。患者将 将给予标准治疗和临床参数 与分子数据相关联。多变量分析将用于显示 分子分类的统计学意义。这项研究应 为实体瘤的分子诊断测试提供了框架， 临床实验室