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. ? ?

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project--Cooperative Agreements (U01)
Project #
1U01CA117378-01
Application #
7002571
Study Section
Special Emphasis Panel (ZCA1-SRRB-Y (M2))
Program Officer
Kagan, Jacob
Project Start
2005-09-26
Project End
2010-07-31
Budget Start
2005-09-26
Budget End
2006-07-31
Support Year
1
Fiscal Year
2005
Total Cost
$322,249
Indirect Cost
Name
Battelle Pacific Northwest Laboratories
Department
Type
DUNS #
032987476
City
Richland
State
WA
Country
United States
Zip Code
99352
Wolf, Omer; Weissman, Oren; Harats, Moti et al. (2013) Birth wind and fire: raising awareness to operating room fires during delivery. J Matern Fetal Neonatal Med 26:1303-5
Jin, Hongjun; Daly, Don S; Marks, Jeffrey R et al. (2013) Oxidatively modified proteins as plasma biomarkers in breast cancer. Cancer Biomark 13:193-200
Zangar, Richard C; Bollinger, Nikki; Weber, Thomas J et al. (2011) Reactive oxygen species alter autocrine and paracrine signaling. Free Radic Biol Med 51:2041-7
Zhang, Yi; Gonzalez, Rachel M; Zangar, Richard C (2011) Protein secretion in human mammary epithelial cells following HER1 receptor activation: influence of HER2 and HER3 expression. BMC Cancer 11:69
White, Amanda M; Daly, Don S; Zangar, Richard C (2011) Analysis of high-throughput ELISA microarray data. Methods Mol Biol 694:191-211
Varnum, Susan M; Webb-Robertson, Bobbie-Jo M; Hessol, Nancy A et al. (2011) Plasma biomarkers for detecting Hodgkin's lymphoma in HIV patients. PLoS One 6:e29263
Gonzalez, Rachel M; Daly, Don S; Tan, Ruimin et al. (2011) Plasma biomarker profiles differ depending on breast cancer subtype but RANTES is consistently increased. Cancer Epidemiol Biomarkers Prev 20:1543-51
Daly, Don Simone; Anderson, Kevin K; Seurynck-Servoss, Shannon L et al. (2010) An internal calibration method for protein-array studies. Stat Appl Genet Mol Biol 9:Article 14
Jin, Hongjun; Zangar, Richard C (2010) Antibody microarrays for high-throughput, multianalyte analysis. Cancer Biomark 6:281-90
Zangar, R C; Daly, D S; White, A M et al. (2009) ProMAT calibrator: A tool for reducing experimental bias in antibody microarrays. J Proteome Res 8:3937-43

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