High-Throughput Evaluation of Breast Cancer Markers

描述(申请人提供)：乳腺癌是美国最常见的癌症之一，每年导致约43,000名妇女死亡。目前早期发现这种疾病的方法(例如，乳房X光检查和乳房检查)依赖于物理手段来检测肿瘤，而且不可靠。由于有报道称，乳腺癌患者的血液中有许多蛋白质发生了改变，因此对这些蛋白质的分析可能会对乳腺癌做出更有用和更准确的评估。由于乳腺癌是一种多方面的疾病，似乎需要分析一种以上的蛋白质来检测这种疾病的所有形式。此外，许多癌症标志物的正常水平还会受到年龄、生育史、绝经状况等流行病学因素的影响。因此，我们假设，为了准确检测乳腺癌，有必要使用标记物的图谱，并且通过考虑流行病学因素的可预测影响，该图谱的准确性将得到改善。为了验证这一假设，我们将使用复杂的蛋白质组学方法并利用几项独立资助的研究结果，进行“第一阶段”生物标记物发现分析。基于第一项研究的结果和其他信息，我们将利用ELISA微阵列技术对约1000个血浆样本中的50个蛋白质进行“第二阶段”分析。最后，我们将进行一项广泛的“第三阶段”回顾研究，目的是确定选定的血浆标志物子集是否可以在通过传统方法检测到乳腺癌之前，用于预测高危女性人群中乳腺癌的存在。因此，建议的研究将有效地利用新技术来显著加快生物标记物研究的步伐。这些分析的最终结果将是对整个蛋白质水平的广泛表征。我们将使用足够数量的样本来得出统计上有效的结论，以确定这种生物标志物配置文件检测早期疾病的能力，以及纳入流行病学因素是否可以提高这一分析的准确性。

DESCRIPTION (provided by applicant): Breast cancer is one of the most prevalent cancer in the United States, resulting in the death of ~43,000 women per year. Current methods for early detection (e.g., mammography and breast exam) of this disease rely on physical means to detect a tumor and are unreliable. Since a number of blood proteins have been reported to be altered in women with breast cancer, a more useful and accurate evaluation of breast cancer could potentially be obtained by an analysis of these proteins. Since breast cancer is a multifaceted disease, it seems likely that analysis of more than one protein will be needed to detect all forms of this disease. In addition, the normal levels of many cancer markers will be affected by age, reproductive history, menopausal status and other epidemiological factors. Therefore, we hypothesize that it will be necessary to use a profile of markers in order to accurately detect breast cancer and that the accuracy of this profile will be improved by accounting for predictable effects of epidemiological factors. In order to test this hypothesis, we will undertake a "phase 1" biomarker discovery analysis using sophisticated proteomics methodologies and leveraging the results from several independently funded studies. Based on results of this first study and other information, we will undertake a "phase 2" analysis of 50 proteins in ~1000 plasma samples using ELISA microarray technology. Finally, we will undertaken an extensive "phase 3" retrospective study with the goal of determining whether a selected subset of plasma markers can be used to predict the presence of breast cancer in a population of high-risk women prior to detection of that disease by conventional methods. Therefore, the proposed research will effectively utilize new technologies to significantly accelerate the pace of biomarker research. The final result of these analyses will be an extensive characterization of a whole profile of protein levels. We will use sufficient numbers of samples to draw statistically valid conclusions about the ability of this biomarker profile to detect the presence of early disease and whether incorporation of epidemiological factors can improve the accuracy of this analysis.