Abstract

Oncologists use tumor size, appearance and lymph node status and routine markers such as estrogen/progesterone receptors or proliferative rate, to assess likely disease outcome in breast cancer patients. Although a majority of women with node-negative breast cancer have a good prognosis, 30% experience recurrence and death from metastatic disease. As a result, systemic therapies are routinely administered to nearly all of these node-negative patients. Markers that better predict recurrence risk could be used to effectively target adjuvant therapies to those patients most likely to benefit from them. Our aim is to characterize the genetic markers that 1) are differentially expressed in good versus bad outcome node-negative breast cancers, 2) help dichotomize node-negative patients into high and low-risk categories so that adjuvant treatment could be more effectively utilized, and 3) delineate the genetic pathways associated with metastatic phenotype. Using cDNA arrays (Clontech Inc), we analyzed 30 untreated, primary tumors from node-negative breast cancer patients who were either cured by their surgery alone, or who experienced metastatic recurrence. In this blinded study, the tumor samples were matched for age, menopausal status, tumor size and grade, and ER/PR status. At the p = 0.05 level of significance, 137 genes involved in cell cylcle, apoptosis, cell adhesion, cytoskeleton, signal transduction etc were found to be differentially expressed between the 2 types of tumor samples. Clustering and Tree-View analyses generated dendrograms showed that the 2 categories of tumors mostly but not completely formed outcome-related clusters. We have validated some of these genes by semiquantitative RT-PCR. We are attempting to use Immunohistochemistry on Tumor Tissue Arrays to assess the prognostic significance of some of the candidate metastatic markers. Clinicians could use these gene expression patterns to select the appropriate adjuvant therapy regimen to node-negative breast cancer patients.

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