High-Throughput Evaluation of Breast Cancer Markers

描述（由申请人提供）：乳腺癌是美国最常见的癌症之一，每年导致约43，000名女性死亡。 目前用于早期检测的方法（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，并且是不可靠的。 由于许多血液蛋白质已被报道在乳腺癌患者中发生改变，因此通过分析这些蛋白质可能会获得更有用和更准确的乳腺癌评估。 由于乳腺癌是一种多方面的疾病，因此可能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会受到年龄、生育史、绝经状态等流行病学因素的影响。 因此，我们假设，这将是必要的，以准确地检测乳腺癌的标志物的配置文件，这一配置文件的准确性将提高占流行病学因素的可预测的影响。 为了验证这一假设，我们将采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1阶段”生物标志物发现分析。 基于第一次研究的结果和其他信息，我们将采用ELISA微阵列技术对约1000份血浆样本中的50种蛋白质进行“第2阶段”分析。 最后，我们将进行一项广泛的“3期”回顾性研究，目的是确定在通过常规方法检测乳腺癌之前，是否可以使用选定的血浆标志物子集来预测高危女性人群中乳腺癌的存在。 因此，拟议的研究将有效利用新技术，大大加快生物标志物研究的步伐。 这些分析的最终结果将是对整个蛋白水平谱的广泛表征。 我们将使用足够数量的样本得出关于该生物标志物谱检测早期疾病存在的能力以及纳入流行病学因素是否可以提高该分析准确性的统计学有效结论。

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.