期刊
JOURNAL OF PROTEOME RESEARCH
卷 11, 期 10, 页码 5034-5045出版社
AMER CHEMICAL SOC
DOI: 10.1021/pr300606e
关键词
breast cancer; biomarkers; blood assay; proteomics; mass spectrometry; single-nucleotide polymorphism (SNP); HER2 triple negative; proximal fluid
资金
- California Breast Cancer Research Program [6JB-0013]
- Department of Defense [DAMD17-01-1-0179]
- National Institute of Health [1RO1CA93736]
- Gonda Foundation
- EIF-Women Cancer Research Fund
- Friends of the Breast Program at UCLA
We have begun an early phase of biomarker discovery in three clinically important types of breast cancer using a panel of human cell lines: HER2 positive, hormone receptor positive and HER2 negative, and triple negative (HER2-, ER-, PR-). We identified and characterized the most abundant secreted, sloughed, or leaked proteins released into serum free media from these breast cancer cell lines using a combination of protein fractionation methods before LC-MS/MS mass spectrometry analysis. A total of 249 proteins were detected in the proximal fluid of 7 breast cancer cell lines. The expression of a selected group of high abundance and/or breast cancer-specific potential biomarkers including thromobospondin 1, galectin-3 binding protein, cathepsin D, vimentin, zinc-alpha 2-glycoprotein, CD44, and EGFR from the breast cancer cell lines and in their culture media were further validated by Western blot analysis. Interestingly, mass spectrometry identified a cathepsin D protein single-nucleotide polymorphism (SNP) by alanine to valine replacement from the MCF-7 breast cancer cell line. Comparison of each cell line media proteome displayed unique and consistent biosignatures regardless of the individual group classifications, demonstrating the potential for stratification of breast cancer. On the basis of the cell line media proteome, predictive Tree software was able to categorize each cell line as HER2 positive, HER2 negative, and hormone receptor positive and triple negative based on only two proteins, muscle fructose 1,6-bisphosphate aldolase and keratin 19. In addition, the predictive Tree software clearly identified MCF-7 cell line overexpresing the HER2 receptor with the SNP cathepsin D biomarker.
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