USING GENE EXPRESSION ANALYSIS TO GUIDE AND IDENTIFY TREATMENTS FOR BREAST CANCER PATIENTS

Abstract

<p>Based on breast cancer clinical trial data accumulated over the last several decades it is obvious that standard breast cancer therapeutics extend survival in breast cancer patients. However, only a minority of patients within these trials derive benefit from treatment. In a population of breast cancer patients treated with adjuvant therapy after surgery, many patients are over-treated, as they would never experience relapse even without receiving adjuvant therapies. Among the remaining patients, some achieve durable remission from therapy, whereas others relapse despite therapy. Hence, there is an obvious need to develop biomarkers that can serve to identify these three populations of patients, such that only patients who are likely to benefit from available therapies are treated with these therapies, as well as to develop new therapies for the treatment of patients who aren’t afforded durable remission by approved treatments. Here, we present the identification of biomarkers to identify low risk breast cancer patients who experience excellent long-term survival even without adjuvant therapy. Conversely, high risk patients represent those patients most likely to benefit from intervention with aggressive treatment regimens. We also report on the identification of biomarkers which can predict the likelihood of response to approved chemotherapy regimens, which could be used to further stratify high risk patients into responders and non-responders. Finally, for high risk patients unlikely to be afforded durable remission from available therapies, we report on the identification of agents that target breast tumor-initiating cells, and may be effective for the treatment of these patients.</p>