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.
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