Challenges in the stratification of breast tumors for tailored therapies

Studying the molecular stratification of breast carcinoma is a real challenge considering the extreme heterogeneity of these tumors. Many patients are now treated following recommendation established at several NIH and St Gallen consensus conferences. However a significant fraction of these breast cancer patients do not need adjuvant chemotherapies while other patients receive inefficacious therapies. High density gene expression arrays have been designed to attempt to establish expression profiles that could be used as prognostic indicators or as predictive markers for response to treatment. This review is intended to discuss the potential value of these new indicators, but also the current weaknesses of these new genomic and bioinformatic approaches. The combined analysis of transcriptomic and genomic alteration data from relatively large numbers of well annotated tumor specimens may offer an opportunity to overcome the current difficulties in validating recently published non overlapping gene lists as prognostic or therapeutic indicators. There is also hope for identifying and deciphering signal transduction pathways driving tumor progression with newly developed algorithms and semi quantitative parameters obtained in simplified in vitro or in vivo models for specific transduction pathways.