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BMC Cancer ; 10: 336, 2010 Jun 28.
Article in English | MEDLINE | ID: mdl-20584321

ABSTRACT

BACKGROUND: Gene expression profiling may improve prognostic accuracy in patients with early breast cancer. Our objective was to demonstrate that it is possible to develop a simple molecular signature to predict distant relapse. METHODS: We included 153 patients with stage I-II hormonal receptor-positive breast cancer. RNA was isolated from formalin-fixed paraffin-embedded samples and qRT-PCR amplification of 83 genes was performed with gene expression assays. The genes we analyzed were those included in the 70-Gene Signature, the Recurrence Score and the Two-Gene Index. The association among gene expression, clinical variables and distant metastasis-free survival was analyzed using Cox regression models. RESULTS: An 8-gene prognostic score was defined. Distant metastasis-free survival at 5 years was 97% for patients defined as low-risk by the prognostic score versus 60% for patients defined as high-risk. The 8-gene score remained a significant factor in multivariate analysis and its performance was similar to that of two validated gene profiles: the 70-Gene Signature and the Recurrence Score. The validity of the signature was verified in independent cohorts obtained from the GEO database. CONCLUSIONS: This study identifies a simple gene expression score that complements histopathological prognostic factors in breast cancer, and can be determined in paraffin-embedded samples.


Subject(s)
Breast Neoplasms/genetics , Gene Expression Profiling/methods , Gene Expression Regulation, Neoplastic , Genetic Testing/methods , Polymerase Chain Reaction , Breast Neoplasms/diagnosis , Breast Neoplasms/mortality , Breast Neoplasms/secondary , Breast Neoplasms/therapy , Databases, Genetic , Female , Genetic Predisposition to Disease , Humans , Kaplan-Meier Estimate , Middle Aged , Neoplasm Staging , Paraffin Embedding , Predictive Value of Tests , Prognosis , Proportional Hazards Models , Reproducibility of Results , Retrospective Studies , Risk Assessment , Risk Factors , Time Factors
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