Combining serial analysis of gene expression and array technologies to identify genes differentially expressed in breast cancer

Mariana Nacht, Anne T. Ferguson, Wen Zhang, Joseph M. Petroziello, Brian P. Cook, Yu Hong Gao, Sharon Maguire, Deborah Riley, George Coppola, Gregory M. Landes, Stephen L. Madden, Saraswati Sukumar

Research output: Contribution to journalArticlepeer-review

228 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)5464-5470
Number of pages7
JournalCancer Research
Volume59
Issue number21
StatePublished - Nov 1 1999

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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