Accurate biomarkers are needed to predict response to aromatase inhibitors in patients with breast cancer. Using current therapies, response rates are 50% to 70% in the neoadjuvant setting and lower in patients with advanced disease. To address this issue, researchers in the United Kingdom have developed a predictive model of clinical response to aromatase inhibitors­­­­­­­­­­­–specifically letrozole (Femara).

Arran K. Turnbull, PhD, MSc, of the University of Edinburgh Cancer Research UK Centre, Edinburgh, and his research team obtained biopsies from 89 postmenopausal women diagnosed with estrogen receptor alpha-positive breast cancer who were prescribed neoadjuvant letrozole prior to and during treatment (after 2 weeks and 3 months). They measured clinical response using 3D ultrasound imaging.

The results, first published in the Journal of Clinical Oncology, showed with 96% accuracy of clinical response using a four-gene classifier. This was based on the level of two genes prior to treatment. One gene, IL6ST, was associated with immune signaling, and the other gene, NGFRAP1, was associated with cell death and the level of two proliferation genes (ASPM, MCM4) after 2 weeks of therapy.¹

Researchers concluded that the four-gene predictive model of clinical response to aromatase inhibitors by 2 weeks has been validated. They also determined that deregulated immune and apoptotic responses before treatment and cell proliferation that is not reduced 2 weeks after initiation of treatment demonstrated that these breast tumors that do not respond to aromatase inhibitors, and therefore would not benefit from their use.

These findings may provide more opportunities for patients with breast cancer to experience the most predictive methods to determine which therapies may or may not benefit them. Further studies with other types of aromatase inhibitors may show efficacy in the patients for whom letrozole did not demonstrate clinical benefit.

References:

• Turnbull AK, Arthur LM, Renshaw L, et al. (2015). Accurate Prediction and Validation of Response to Endocrine Therapy in Breast Cancer. Journal of Clinical Oncology.