MicroRNA profiling of triple negative breast cancer: predicting outcome and targets.

Abstract

Abstract Abstract #2040 Background: Breast tumors have been categorized on their molecular basis into ER- and/or PR positive, HER2 gene amplified and triple-negative tumors. Among these, triple-negative tumors represent the most aggressive subclass of breast tumors that are most prevalent in African American women. Currently, no effective targeted therapies or potential biomarkers have been identified to predict outcome within this group.
 MicroRNAs(miRNAs) are global regulatory RNAs misregulated in almost every cancer and may function as tumor suppressor genes or proto-oncogenes. Specific miRNAs are aberrantly expressed in breast tumor versus normal tissue. Although miRNA expression profiles for the ER positive and HER2 positive subtype have been reported, the triple negative subtype remains to be studied.
 Hypothesis: We hypothesize that identifying the miRNA signature of the triple negative tumors as a subclass as well as differences in this signature between triple negative patients with known outcome will lead to the identification of miRNAs predictive of outcome. For these studies we will use a large, well-annotated database of triple negative breast cancer patients with long-term follow-up. We will then test the identified miRNAs in a well-established cell-culture system to determine which miRNAs can act as potential therapeutic agents in triple negative breast tumors.
 Study Design: We have performed miRNA microarray analysis to identify miRNA expression patterns in over 40 triple negative breast cancers using both fresh frozen tumors and formalin-fixed paraffin embedded (FFPE) samples. We have used the Ambion miRNA Taqman Low Density Array for analysis of these samples. The potential of specific miRNAs to predict outcome is currently being determined using statistical analysis.
 Results: Our initial studies indicated that the triple negative subgroup has a significantly different miRNA signature than the HER2 positive subtype. We also additionally found unique miRNA expression patterns that may define triple negative cancers as a class. The triple negative tumors are known to have low levels of p53 and our microarray data showed that miR-34a which has been shown to be co-regulated by p53 and has similar expression levels as p53 in tissues, was significantly low in the triple negative compared to HER 2 positive breast cancer. We are currently evaluating the impact of altering mir-34 expression in these cell lines in vitro. Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 2040.