Breast cancer is a complex genetic disease characterized by the accumulation of multiple molecular alterations. The resulting clinical heterogeneity makes current therapeutic strategies-based on clinicopathlogical factors-less than perfectly adapted to each patient. Today, DNA arrays, by allowing the simultaneous and quantitative analysis of the mRNA expression levels of thousands of genes in a single assay, provide novel tools to tackle this complexity. Potential applications are multiple in the cancer field and the first research results are promising. Using home-made DNA arrays in an approach easily compatible with academic research-nylon support and radioactive detection-we identified a predictor set of 23 genes whose expression patterns differentiated two groups of breast cancer patients with different survival after adjuvant chemotherapy. We then validated and further extended these results in a larger, independent and homogeneous series of poor prognosis primary breast cancers treated with adjuvant anthracyclin-based chemotherapy. We confirmed the prognostic classification provided by the 23-gene set predictor. We then improved the predictor set and refined the classification by sorting the tumors into three classes with significantly different long-term survival. These results show the potential of the technology with an accessible approach for academic research teams. We also showed that nylon DNA arrays with radioactive detection are associated with excellent sensitivity, an advantage in clinical situations where the amount of available material is limited.