Breast cancer is a heterogeneous disease made of various molecular subtypes with different prognosis. However, evolution remains difficult to predict within some subtypes, such as luminal A, and treatment is not as adapted as it should be. Refinement of prognostic classification and identification of new therapeutic targets are needed. Using oligonucleotide microarrays, we profiled 227 breast cancers. We focused our analysis on two major breast cancer subtypes with opposite prognosis, luminal A (n = 80) and basal (n = 58), and on genes encoding protein kinases. Whole-kinome expression separated luminal A and basal tumors. The expression (measured by a kinase score) of 16 genes encoding serine/threonine kinases involved in mitosis distinguished two subgroups of luminal A tumors: Aa, of good prognosis and Ab, of poor prognosis. This classification and its prognostic effect were validated in 276 luminal A cases from three independent series profiled across different microarray platforms. The classification outperformed the current prognostic factors in univariate and multivariate analyses in both training and validation sets. The luminal Ab subgroup, characterized by high mitotic activity compared with luminal Aa tumors, displayed clinical characteristics and a kinase score intermediate between the luminal Aa subgroup and the luminal B subtype, suggesting a continuum in luminal tumors. Some of the mitotic kinases of the signature represent therapeutic targets under investigation. The identification of luminal A cases of poor prognosis should help select appropriate treatment, whereas the identification of a relevant kinase set provides potential targets.

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http://dx.doi.org/10.1158/0008-5472.CAN-07-5516DOI Listing

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