Abstract

BackgroundBasal breast cancers (BCs) represent ~15% of BCs. Although overall poor, prognosis is heterogeneous. Identification of good- versus poor-prognosis patients is difficult or impossible using the standard histoclinical features and the recently defined prognostic gene expression signatures (GES). Kinases are often activated or overexpressed in cancers, and constitute targets for successful therapies. We sought to define a prognostic model of basal BCs based on kinome expression profiling.MethodsDNA microarray-based gene expression and histoclinical data of 2515 early BCs from thirteen datasets were collected. We searched for a kinome-based GES associated with disease-free survival (DFS) in basal BCs of the learning set using a metagene-based approach. The signature was then tested in basal tumors of the independent validation set.ResultsA total of 591 samples were basal. We identified a 28-kinase metagene associated with DFS in the learning set (N = 73). This metagene was associated with immune response and particularly cytotoxic T-cell response. On multivariate analysis, a metagene-based predictor outperformed the classical prognostic factors, both in the learning and the validation (N = 518) sets, independently of the lymphocyte infiltrate. In the validation set, patients whose tumors overexpressed the metagene had a 78% 5-year DFS versus 54% for other patients (p = 1.62E-4, log-rank test).ConclusionsBased on kinome expression, we identified a predictor that separated basal BCs into two subgroups of different prognosis. Tumors associated with higher activation of cytotoxic tumor-infiltrative lymphocytes harbored a better prognosis. Such classification should help tailor the treatment and develop new therapies based on immune response manipulation.

Highlights

  • Basal breast cancers (BCs) represent ~15% of Breast cancer (BC)

  • The 73 Institut Paoli-Calmettes (IPC) basal tumors were used as training set for identifying a prognostic kinase gene expression signatures (GES) from the 661-gene list

  • Supervised analysis identified 581 genes differentially expressed in basal versus at least one other subtype, including 360 genes overexpressed in basal tumors (Additional file 3, Table S2)

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Summary

Introduction

Basal breast cancers (BCs) represent ~15% of BCs. overall poor, prognosis is heterogeneous. Identification of good- versus poor-prognosis patients is difficult or impossible using the standard histoclinical features and the recently defined prognostic gene expression signatures (GES). Gene expression profiling has identified molecular subtypes with different biological features and different outcome [1,2,3,4,5], including basal BCs. Basal BCs, which represent ~15-20% of invasive BCs are high-grade tumors, frequently do not express hormone receptors (HR) and ERBB2, and have the worst prognosis overall [6,7]. Kinases, which constitute ~1.7% of human genes [9], are activated or overexpressed in cancers [10], and constitute current or future targets for successful therapies [11]. A similar approach was successfully applied to 44 estrogen receptor (ER)-negative BCs, including ERBB2-

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