Molecular Predictors of Response to Therapy for Breast Cancer

Abstract

For several decades, measurements from tumor tissue biomarkers have been used to identify subsets of breast cancer patients that may benefit from specific therapies. Since the 1980s, estrogen receptor testing has been routinely performed on breast carcinoma samples to determine whether hormonal therapy is indicated. Today, estrogen receptor, progesterone receptor, and human epidermal growth factor receptor type 2 testing to guide treatment decisions are standard of care. In recent years, multigene assays have been introduced to predict breast tumor behavior. In particular, the OncotypeDx and MammaPrint assays have been commercialized and are used in North America and Europe to guide clinical decisions. Others, including the Breast Cancer Index (BCI; bioTheranostics) and PAM50 (Expression Analysis, Inc), are gaining acceptance as validated assays with associated clinical outcomes. In addition, certain germ line genetic tests are now reported to predict response to specific treatments (e.g., BRCA1, 2, CYP2D6). The optimal use of these novel molecular assays is a challenge to the practicing oncologist. In this review, we will focus on the role of biomarkers that predict response to treatment of breast cancer patients and provide a framework for oncologists to understand and evaluate these tools for use in clinical practice.