Novel Rac1/Stat3 and Stat5 Pathway in Differentiation and Neoplastic Transformation of Breast Epithelial Cells: Potential Prognostic Markers

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Cass, Jamaica
Breast cancer , Clinical
Breast cancer is one of the leading causes of death of women in North America. Signal Transducer and Activator of Transcription (Stat)3 and Stat5 are transcription factors involved in normal breast development, and are hyperactivated in 30-50% of breast cancers. Stat5 is required for breast epithelial cell differentiation and is over-expressed in breast cancers with a more differentiated phenotype. Constitutive over-expression of Stat3 in breast cancer, on the other hand, can drive expression of genes involved in survival, migration and angiogenesis. Our group has previously elucidated a novel activation mechanism of Stat3 by cadherin engagement in densely growing cells. We hypothesize that Stat5 and Stat3 are regulators of the balance between differentiation and transformation of breast epithelial cells: Stat3 activation is modulated by a cadherin/Rac1 pathway, and this may be necessary for differentiation. Stat5 on the other hand may play a role in differentiation independent of cell density. Therefore, Stat3 and Stat5 may turn out to be independent prognostic markers for breast cancer. We show here, through pharmacological inhibition experiments, that Stat3 is required for differentiation of HC11 breast epithelial cells, measured by β-casein expression. On the other hand, we also show that constitutively active Rac, a molecule downstream of cadherin in the Stat3 activation pathway, blocks the differentiation of breast epithelial cells. Stat5 is upregulated by hydrocortisone, insulin and prolactin, but is unaffected by density. Stat5 is also required for differentiation; moreover we show that expression of activated Stat5 in HC11 breast epithelial cells promotes a more differentiated phenotype. As an initial approach to biomarker development, we have optimized a quantitative analysis method to assess protein expression profiles of clinically relevant robust biomarkers using a 63 tumour breast cancer cohort. Automated quantitative analysis of protein expression in human breast cancer specimens, including target genes of Stat3 and Stat5, cyclin D1 and p21, are statistically similar to manual scoring, and correlate with clinico-pathological parameters. These data provide a vital link between benchwork and clinical studies, and could lead to possible future predictive biomarkers.
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