Accurate Prediction and Validation of Response to Endocrine Therapy in Breast Cancer.

Abstract

Aromatase inhibitors (AIs) have an established role in the treatment of breast cancer. Response rates are only 50% to 70% in the neoadjuvant setting and lower in advanced disease. Accurate biomarkers are urgently needed to predict response in these settings and to determine which individuals will benefit from adjuvant AI therapy. Pretreatment and on-treatment (after 2 weeks and 3 months) biopsies were obtained from 89 postmenopausal women who had estrogen receptor-alpha positive breast cancer and were receiving neoadjuvant letrozole for transcript profiling. Dynamic clinical response was assessed with use of three-dimensional ultrasound measurements. The molecular response to letrozole was characterized and a four-gene classifier of clinical response was established (accuracy of 96%) on the basis of the level of two genes before treatment (one gene [IL6ST] was associated with immune signaling, and the other [NGFRAP1] was associated with apoptosis) and the level of two proliferation genes (ASPM, MCM4) after 2 weeks of therapy. The four-gene signature was found to be 91% accurate in a blinded, completely independent validation data set of patients treated with anastrozole. Matched 2-week on-treatment biopsies were associated with improved predictive power as compared with pretreatment biopsies alone. This signature also significantly predicted recurrence-free survival (P = .029) and breast cancer -specific survival (P = .009). We demonstrate that the test can also be performed with use of quantitative polymerase chain reaction or immunohistochemistry. A four-gene predictive model of clinical response to AIs by 2 weeks has been generated and validated. Deregulated immune and apoptotic responses before treatment and cell proliferation that is not reduced 2 weeks after initiation of treatment are functional characteristics of breast tumors that do not respond to AIs.