Gene expression profiling in breast cancer: classification, prognostication, and prediction

Abstract

Microarray-based gene expression profiling has had a major effect on our understanding of breast cancer. Breast cancer is now perceived as a heterogeneous group of different diseases characterised by distinct molecular aberrations, rather than one disease with varying histological features and clinical behaviour. Gene expression profiling studies have shown that oestrogen-receptor (ER)-positive and ER-negative breast cancers are distinct diseases at the transcriptomic level, that additional molecular subtypes might exist within these groups, and that the prognosis of patients with ER-positive disease is largely determined by the expression of proliferation-related genes. On the basis of these principles, a molecular classification system and prognostic multigene classifiers based on microarrays or derivative technologies have been developed and are being tested in randomised clinical trials and incorporated into clinical practice. In this review, we focus on the conceptual effect and potential clinical use of the molecular classification of breast cancer, and discuss prognostic and predictive multigene predictors.