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Advances in Brief |
Genzyme Molecular Oncology, Framingham, Massachusetts 01701 [M. N., W. Z., J. M. P., B. P. C., Y. H. G., G. C., G. M. L., S. L. M.]; Department of Oncology, Novartis Institute for Biomedical Research, Summit, New Jersey 07901 [S. M.]; Lion Bioscience, Cambridge, Massachusetts 02141 [D. R.]; and Breast Cancer Program, Johns Hopkins Oncology Center, Baltimore, Maryland 21205 [A. T. F., S. S.]
Several methods have been used recently to determine gene expression profiles of cell populations. Here we demonstrate the strength of combining two approaches, serial analysis of gene expression (SAGE) and DNA arrays, to help elucidate pathways in breast cancer progression by finding genes consistently expressed at different levels in primary breast cancers, metastatic breast cancers, and normal mammary epithelial cells. SAGE profiles of 21PT and 21MT, two well-characterized breast tumor cell lines, were compared with SAGE profiles of normal breast epithelial cells to identify differentially expressed genes. A subset of these candidates was then placed on an array and screened with clinical breast tumor samples to find genes and expressed sequence tags that are consistently expressed at different levels in diseased and normal tissues. In addition to finding the predicted overexpression of known breast cancer markers HER-2/neu and MUC-1, the powerful coupling of SAGE and DNA arrays resulted in the identification of genes and potential pathways not implicated previously in breast cancer. Moreover, these techniques also generated information about the differences and similarities of expression profiles in primary and metastatic breast tumors. Thus, combining SAGE and custom array technology allowed for the rapid identification and validation of the clinical relevance of many genes potentially involved in breast cancer progression. These differentially expressed genes may be useful as tumor markers and prognostic indicators and may be suitable targets for various forms of therapeutic intervention.
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C. D. Hough, C. A. Sherman-Baust, E. S. Pizer, F. J. Montz, D. D. Im, N. B. Rosenshein, K. R. Cho, G. J. Riggins, and P. J. Morin Large-Scale Serial Analysis of Gene Expression Reveals Genes Differentially Expressed in Ovarian Cancer Cancer Res., November 1, 2000; 60(22): 6281 - 6287. [Abstract] [Full Text]
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K. Ono, T. Tanaka, T. Tsunoda, O. Kitahara, C. Kihara, A. Okamoto, K. Ochiai, T. Takagi, and Y. Nakamura Identification by cDNA Microarray of Genes Involved in Ovarian Carcinogenesis Cancer Res., September 1, 2000; 60(18): 5007 - 5011. [Abstract] [Full Text]
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D. Scheurle, M. P. DeYoung, D. M. Binninger, H. Page, M. Jahanzeb, and R. Narayanan Cancer Gene Discovery Using Digital Differential Display Cancer Res., August 1, 2000; 60(15): 4037 - 4043. [Abstract] [Full Text]
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 A. T. Ferguson, E. Evron, C. B. Umbricht, T. K. Pandita, T. A. Chan, H. Hermeking, J. R. Marks, A. R. Lambers, P. A. Futreal, M. R. Stampfer, et al. High frequency of hypermethylation at the 14-3-3 sigma locus leads to gene silencing in breast cancer PNAS, May 23, 2000; 97(11): 6049 - 6054. [Abstract] [Full Text] [PDF]
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