Gene expression predictors in breast cancer: current status, limitations and perspectives

Abstract

Breast cancer is characterised by a wide heterogeneity regarding outcome and drug sensitivity. A better prediction of these two parameters at the individual level should improve patient management and therefore also improve both the quality of life and the overall survival of the patient. Several molecular predictors for prognosis (MammaPrint or Oncotype DX) and drug prediction (DLD30, SET index) have been generated using DNA-based arrays or RT-PCR, some of these being tested in phase III trials. Although they exhibit good metric performance and should improve the quality of care in the next decade, these predictors are considered suboptimal regarding the potential of the technology. New study design and arrays should generate more powerful second generation gene signatures.