Molecular biology in breast cancer: Should molecular classifiers be assessed by conventional tools or by gene expression arrays?

Breast cancer is a complex disease, with heterogeneous presentations and clinical courses. Standard clinico-pathological parameters, relying on single gene or protein characterization determined with sometimes poorly-reproducible technologies, have shown limitations in the classification of the disease and in the prediction of individual patient outcomes and responses to therapy. Gene-expression profiling has revealed great potential to accurately classify breast cancer and define patient prognosis and prediction to anti-cancer therapy. Nevertheless, the performance of molecular classifiers remains sub-optimal, and both technical and conceptual improvements are needed. It is likely that determining the ideal strategy for tailoring treatment of breast cancer will require a more systematic, structured and multi-dimensional approach than in the past. Besides implementing cutting-edge technologies to detect genetic and epigenetic cancer alterations, the future of breast cancer research will in all probability rely on the innovative and multilevel integration of molecular profiles with clinical parameters of the disease and patient-related factors.