Selection of endocrine therapy for breast cancer is becoming increasingly complex with a greater choice of endocrine therapeutic agents becoming available that can be used either individually or sequentially, but also with a wider cost range between generic tamoxifen and aromatase inhibitors that can effect treatment decisions. The current challenges for treatment selection in estrogen receptor (ER)-positive breast cancer include the ability to predict benefit from endocrine therapy and/or chemotherapy, select among endocrine agents, and define the duration and sequence of endocrine treatments. In addition, many more women now develop metastases having already received prior adjuvant tamoxifen therapy and only 20% - 50% of women with breast cancer that is ER-positive by immunohistochemistry (IHC) will respond to first-line endocrine therapies. Gene expression profiles may be able to provide a more predictive test of endocrine sensitivity. In collaboration with the University of Texas MD Anderson Cancer Center, we have proposed development of an index of Sensitivity to Endocrine Therapy (SET). A continuous index of endocrine sensitivity can potentially improve first-line therapy response prediction but can also help to select unresponsive ER- positive patients who might benefit from a combined endocrine and chemotherapy treatment. We aim to develop a more specific assay of ER pathway activity and apply it to predict endocrine sensitivity in women with breast cancer. We propose a "proof of concept" analysis of genomic measurement of ESR1 (ER receptor status) and SET index (independently and combined), in women with ER-positive breast cancer for prediction of response to adjuvant tamoxifen therapy compared to standard markers such as ER and the progesterone receptor (PGR). Our specific aims are to (i) analyze about 280 transcriptional profiles of ER-positive breast cancer treated with adjuvant tamoxifen to establish clinically significant and meaningful classes of endocrine response based on the SET index, and (ii) to validate the SET classes using about 250 independent samples from ER-positive patients that were treated with tamoxifen. Breast cancer is a leading cause of mortality and suffering in women despite advances in early detection techniques. Selection of treatment is a crucial decision that will affect the long-term survival of a patient upon breast cancer diagnosis. Endocrine treatment is considered standard for patients with estrogen-receptor positive tumors; however, treatment decisions based on receptor status and other pathologic parameters has led to high observed relapse rates. An improved validated predictor of treatment response based on gene expression profiling promises to make a significant impact on selection of patients for appropriate treatments and treatment combinations
