The management of breast cancer patients is still guided based on a constellation of clinicopathological features, including prognostic markers derived from careful histo-pathological analysis of tumours, namely tumour size, histological grade, presence of lymph node metastasis and vascular invasion [1-3]. Despite the huge amount of resources allocated to translational research endeavours, only three predictive markers are utilised to define the therapy of breast cancer patients: oestrogen receptor (ER) and progesterone receptor (PR), the predictive markers of response to endocrine therapy, and human epidermal growth factor receptor 2 (HER2), the molecular target of trastuzumab and lapatinib. These parameters are then used in conjunction either in the form of guidelines (for example, St Gallen's consensus criteria) or included in multivariable algorithms (for example, Adjuvant!Online) for clinical decision making [1-3]. Albeit seemingly simplistic, this approach has been shown to be clinically relevant, given that predictions made with Adjuvant!Online do correlate with the actual outcome of breast cancer patients [4], and, most importantly, the use of this framework to define the systemic therapy of breast cancer patients has contributed to the steady decline in the mortality of breast cancer patients [5]. Although eective, this approach is not sucient for the potential of individualised therapy to be realised. The promise of high throughput technologies, and in particular of gene expression profiling with microarrays, has been of apocalyptic dimensions [6-9]. The objectivity of the methodology coupled with the elaborate, if not mind boggling [10], bioinformatic approaches to answer clinically relevant questions have led some of the proponents of this technology to compare histopathology with some rituals practiced by ancient tribes [7], and some experts in the field predicted back in 2000 that microarrays would make conventional diagnostic techniques obsolete [6]. Microarrays and their derivatives have undoubtedly contributed to our understanding of breast cancer (for reviews, see [1,2]). They have provided direct evidence to demonstrate that breast cancer is a heterogeneous disease at the molecular level [11], that ER-positive and -negative diseases are fundamentally different [11-14], that molecular subtypes of breast cancer do exist [11,15-18], and that some special histological types of breast cancer are distinct entities at the molecular level [19-22]. Furthermore, they have led to the development of a molecular taxonomy that is currently being tested in clinical trials [16], and of prognostic 'gene signatures', some of which have already been approved by the US Food and Drug Administration [1,2,13,23].