Predicting endocrine therapy responsiveness in breast cancer

Endocrine therapy is one of the most effective treatment strategies for breast cancer. However, in the adjuvant setting, up to 40% to 50% of patients with estrogen receptor (ER)-positive breast cancers relapse despite these interventions. Although ER and HER2 analysis has increased our ability to predict which patients will benefit from endocrine therapy, further improvement is needed, most specifically for patients with ER-positive, HER2-negative disease. Recent advances in genomic technology have made it possible to classify breast cancers into risk categories with significant prognostic implications. However, the predictive value of these tests remains the subject of investigation. Long-term follow-up of neoadjuvant endocrine therapy studies suggests that the in vivo assessment of therapeutic efficacy provided by this treatment approach is also valuable in predicting outcome. Indeed, the Preoperative Endocrine Prognostic Index (PEPI), based on tumor pathoiogic staging and expression levels of ER and Ki67 following 3 to 4 months of neoadjuvant endocrine therapy, reproducibly predicts long-term outcomes of hormone receptor-positive breast cancer. This article reviews ongoing progress in the effort to identify predictors of endocrine therapy responsiveness for breast cancer and discusses the value of "pre-treatment" vs "on-treatment" tumor profiling for predicting outcomes.