African-American women are more likely found at advanced stage and therefore have a worse survival. While the poor outcome observed in African-American women with breast cancer may be multifactorial, the aggressiveness of their disease may have a biological base. A significant tumor shrinkage induced by preoperative chemotherapy may be used as a surrogate marker to predict patient's survival outcome. We hypothesize that: (1) the differentially expressed proteins of each breast cancer predict tumor response to the preoperative chemotherapy; and (2) the biomarkers characterizing resistance to the treatment are more common in African-American women with locally advanced cancer than Caucasian Americans. Accordingly, this study will search for novel specific proteins in breast cancer that predict tumor responses to preoperative chemotherapy. The chemical identities of these proteins will be determined by mass spectrometry/proteomics. In addition, whether the """"""""drug-resistant"""""""" biomarkers are more common in African-American women will be systematically compared with the Caucasian American women. Finally, the prognostic value of the biomarkers will be compared with the conventional parameters such as patients' demographic and tumor features in a multivariant analysis to determine their independent predicative value and interaction of various factors. ? ? A new technology, SELDI or Surface-Enhanced Laser Desorption/lonization mass spectrometry will be used to discover biomarkers that can predict response of breast cancer to preoperative chemotherapy. The identities of these biomarkers will be established by spectrometry/proteomic of fragments of biomarkers. By completion of this project, prognosticators characterizing tumor response to the preoperative chemotherapy will be identified to better classify locally advanced breast cancer. The aggressive nature of the disease in African-Americans reflected by the proteomic markers characterizing tumor response to drug treatment will be objectively compared to Caucasians with comparable stage of diseases and identical treatment.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA093736-02
Application #
6665104
Study Section
Clinical Oncology Study Section (CONC)
Program Officer
Xie, Heng
Project Start
2002-09-27
Project End
2005-08-31
Budget Start
2003-09-01
Budget End
2004-08-31
Support Year
2
Fiscal Year
2003
Total Cost
$493,533
Indirect Cost
Name
University of California Los Angeles
Department
Surgery
Type
Schools of Medicine
DUNS #
092530369
City
Los Angeles
State
CA
Country
United States
Zip Code
90095
Whelan, Stephen A; He, Jianbo; Lu, Ming et al. (2012) Mass spectrometry (LC-MS/MS) identified proteomic biosignatures of breast cancer in proximal fluid. J Proteome Res 11:5034-45
Chang, Helena R; Glaspy, John; Allison, Mary Ann et al. (2010) Differential response of triple-negative breast cancer to a docetaxel and carboplatin-based neoadjuvant treatment. Cancer 116:4227-37
Lu, Ming; Whitelegge, Julian P; Whelan, Stephen A et al. (2010) Hydrophobic Fractionation Enhances Novel Protein Detection by Mass Spectrometry in Triple Negative Breast Cancer. J Proteomics Bioinform 3:1-10
Whelan, Stephen A; Lu, Ming; He, Jianbo et al. (2009) Mass spectrometry (LC-MS/MS) site-mapping of N-glycosylated membrane proteins for breast cancer biomarkers. J Proteome Res 8:4151-60
He, Jianbo; Shen, Dejun; Chung, Debra U et al. (2009) Tumor proteomic profiling predicts the susceptibility of breast cancer to chemotherapy. Int J Oncol 35:683-92
Prati, Raquel; Minami, Christina A; Gornbein, Jeff A et al. (2009) Accuracy of clinical evaluation of locally advanced breast cancer in patients receiving neoadjuvant chemotherapy. Cancer 115:1194-202
He, Jianbo; Gornbein, Jeffrey; Shen, Dejun et al. (2007) Detection of breast cancer biomarkers in nipple aspirate fluid by SELDI-TOF and their identification by combined liquid chromatography-tandem mass spectrometry. Int J Oncol 30:145-54
Shen, Dejun; He, Jianbo; Chang, Helena R (2005) In silico identification of breast cancer genes by combined multiple high throughput analyses. Int J Mol Med 15:205-12
Shen, Dejun; Chang, Helena R; Chen, Zugen et al. (2005) Loss of annexin A1 expression in human breast cancer detected by multiple high-throughput analyses. Biochem Biophys Res Commun 326:218-27