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Talk Title :
The Breast Cancer Tumor Microenvironment
Date / Time / Location:
Thursday November 13th, 2008 – 6:00 pm
Room S1-151 at IRIC
McGill Center for Bioinformatics
It is increasingly evident that breast cancer outcome is strongly influenced by signals emanating from tumor-associated stroma. However, little is known about how gene expression changes in this tissue affect tumor progression. In this talk, we compare gene expression profiles from laser capture-microdissected tumor-associated versus matched normal stroma, and derive transcriptional profiles strongly associated with clinical outcome. We present a stroma-derived predictor that generates new information to stratify disease endpoint, independent of standard clinical prognostic factors and previously published predictors.
Genes represented in the stroma-derived predictor reveal the strong prognostic capacity of differential immune responses as well as angiogenic and hypoxic responses. The computational and statistical aspects underpinning this work are built upon a new approach to analyzing gene expression data that in some sense is “orthologonal” to traditional clustering based tools, and is general in the sense that a wide range of data types can be easily integrated into the system.We show how this tool stratifies patients in an interesting and clinically relevant way.