Abstract
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].
Highlights
The management of breast cancer patients is still guided based on a constellation of clinicopathological features, including prognostic markers derived from careful histopathological analysis of tumours, namely tumour size, histological grade, presence of lymph node metastasis and vascular invasion [1,2,3]
The question that remains germane is whether molecular profiling offers more than the information provided by clinicopathological parameters and a handful of immunohistochemical markers. This was in part addressed by Dunkler and colleagues [45], who re-analysed the data from the cohort employed to validate the 70-gene signature and demonstrated that the contribution of this signature to the prognostication of breast cancer patients above and beyond that offered by the clinicopathological parameters was minimal
Taken together, it would be fair to say that, currently, molecular profiling does provide additional prognostic and to some extent predictive information to the current clinicopathological features and immunohistochemical markers routinely used. This information benefits a limited number of patients, is restricted to patients with ER-positive cancers, and seems only to constitute a reproducible and quantitative analysis of tumour cell proliferation
Summary
The management of breast cancer patients is still guided based on a constellation of clinicopathological features, including prognostic markers derived from careful histopathological analysis of tumours, namely tumour size, histological grade, presence of lymph node metastasis and vascular invasion [1,2,3]. The first prognostic gene signatures (that is, the 70-gene signature known as Mammaprint® [13], and the 76-gene signature [31]) were developed to be applied to all breast cancer patients Their performance in the training and validation datasets demonstrated objectively that the prognostic information provided by these signatures is independent of the information provided by tumour size, presence of lymph node metastasis and histological grade [1,2,32]. The question that remains germane is whether molecular profiling offers more than the information provided by clinicopathological parameters and a handful of immunohistochemical markers This was in part addressed by Dunkler and colleagues [45], who re-analysed the data from the cohort employed to validate the 70-gene signature and demonstrated that the contribution of this signature to the prognostication of breast cancer patients above and beyond that offered by the clinicopathological parameters was minimal. A recent comparison of the prognostic information provided by OncotypeDxTM or four immunohistochemical markers (that is, ER, PR, HER2 and Ki67 - a proliferation marker) semi-quantitatively assessed in the material from the ATAC (Arimidex, Tamoxifen, Alone or in Combination) prospective trial demonstrated that these four markers would at least be equivalent to OncotypeDxTM [46]
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