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Background: A microarray-based 70-gene prognosis signature might improve the selection of patients with node-negative breast cancer for adjuvant systemic treatment. The main aims of this MicroarRAy PrognoSTics in Breast CancER (RASTER) study were to assess prospectively the feasibility of implementation of the 70-gene prognosis signature in community-based settings and its effect on adjuvant systemic treatment decisions when considered with treatment advice formulated from the Dutch Institute for Healthcare Improvement (CBO) and other guidelines., Methods: Between January, 2004 and December, 2006, 812 women aged under 61 years with primary breast carcinoma (clinical T1-4N0M0) were enrolled. Fresh tumour samples were collected in 16 hospitals in the Netherlands within 1 h after surgery. Clinicopathological factors were collected and microarray analysis was done with a custom-designed array chip that assessed the mRNA expression index of the 70 genes previously identified for the prognostic signature. Patients with a "good" signature were deemed to have a good prognosis and, therefore, could be spared adjuvant systemic treatment with its associated adverse effects, whereas patients with a "poor" signature were judged to have a poor prognosis and should be considered for adjuvant systemic treatment. Concordance between risk predicted by the prognosis signature and risk predicted by commonly used clinicopathological guidelines (ie, St Gallen guidelines, Nottingham Prognostic Index, and Adjuvant! Online) was assessed., Findings: Of 585 eligible patients, 158 patients were excluded because of sampling failure (n=128) and incorrect procedure (n=30). Prognosis signatures were assessed in 427 patients. The 70-gene prognosis signature identified 219 (51%) patients with good prognosis and 208 (49%) patients with poor prognosis. The Dutch CBO guidelines identified 184 patients (43%) with poor prognosis, which was discordant with those findings obtained with the prognosis signature in 128 (30%) patients. Oncologists recommended adjuvant treatment in 203 (48%) patients based on Dutch CBO guidelines, in 265 (62%) patients if the guidelines were used with the prognosis signature, and in 259 (61%) patients if Dutch CBO guidelines, prognosis signature, and patients' preferences for treatment were all taken into account. Adjuvant! Online guidelines identified more patients with poor prognosis than did the signature alone (294 [69%]), and discordance with the signature occurred in 160 (37%) patients. St Gallen guidelines identified 353 (83%) patients with poor prognosis with the signature and discordance in 168 (39%) patients. Nottingham Prognostic Index recorded 179 (42%) patients with poor prognosis with the signature and discordance in 117 (27%) patients., Interpretation: Use of the prognosis signature is feasible in Dutch community hospitals. Adjuvant systemic treatment was advised less often when the more restrictive Dutch CBO guidelines were used compared with that finally given after use of the prognosis signature. For the other guidelines assessed, less adjuvant chemotherapy would be given when the data based on prognosis signature alone are used, which might spare patients from adverse effects and confirms previous findings. Future studies should assess whether use of the prognosis signature could improve survival or equal survival while avoiding unnecessary adjuvant systemic treatment without affecting patients' survival, and further assess the factors that physicians use to recommend adjuvant systemic treatment.

Scientific advances in the field of genetics and gene-expression profiling have revolutionized the concept of patient-tailored treatment. Analysis of differential gene-expression patterns across thousands of biological samples in a single experiment (as opposed to hundreds to thousands of experiments measuring the expression of one gene at a time), and extrapolation of these data to answer clinically pertinent questions such as those relating to tumor metastatic potential, can help define the best therapeutic regimens for particular patient subgroups. The use of microarrays provides a powerful technology, allowing in-depth analysis of gene-expression profiles. Currently, microarray technology is in a transition phase whereby scientific information is beginning to guide clinical practice decisions. Before microarrays qualify as a useful clinical tool, however, they must demonstrate reliability and reproducibility. The high-throughput nature of microarray experiments imposes numerous limitations, which apply to simple issues such as sample acquisition and data mining, to more controversial issues that relate to the methods of biostatistical analysis required to analyze the enormous quantities of data obtained. Methods for validating proposed gene-expression profiles and those for improving trial designs represent some of the recommendations that have been suggested. This Review focuses on the limitations of microarray analysis that are continuously being recognized, and discusses how these limitations are being addressed.