A gene expression signature that can predict the recurrence of tamoxifen-treated primary breast cancer - PubMed (original) (raw)

A gene expression signature that can predict the recurrence of tamoxifen-treated primary breast cancer

Maïa Chanrion et al. Clin Cancer Res. 2008.

Abstract

Purpose: The identification of a molecular signature predicting the relapse of tamoxifen-treated primary breast cancers should help the therapeutic management of estrogen receptor-positive cancers.

Experimental design: A series of 132 primary tumors from patients who received adjuvant tamoxifen were analyzed for expression profiles at the whole-genome level by 70-mer oligonucleotide microarrays. A supervised analysis was done to identify an expression signature.

Results: We defined a 36-gene signature that correctly classified 78% of patients with relapse and 80% of relapse-free patients (79% accuracy). Using 23 independent tumors, we confirmed the accuracy of the signature (78%) whose relevance was further shown by using published microarray data from 60 tamoxifen-treated patients (63% accuracy). Univariate analysis using the validation set of 83 tumors showed that the 36-gene classifier is more efficient in predicting disease-free survival than the traditional histopathologic prognostic factors and is as effective as the Nottingham Prognostic Index or the "Adjuvant!" software. Multivariate analysis showed that the molecular signature is the only independent prognostic factor. A comparison with several already published signatures demonstrated that the 36-gene signature is among the best to classify tumors from both training and validation sets. Kaplan-Meier analyses emphasized its prognostic power both on the whole cohort of patients and on a subgroup with an intermediate risk of recurrence as defined by the St. Gallen criteria.

Conclusion: This study identifies a molecular signature specifying a subgroup of patients who do not gain benefits from tamoxifen treatment. These patients may therefore be eligible for alternative endocrine therapies and/or chemotherapy.

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Figures

Figure 1

Figure 1. Hierarchical clustering analysis of the 132 tumors from the training set using the 36-gene predictive signature

The 132 tumors from 86 relapse-free (RF) and 46 patients with relapse (R), as indicated on the top of the figure, were divided into two main clusters, corresponding to the two branches of the dendrogram: the R and RF clusters. The 36 genes from the predictive signature are indicated on the right.

Figure 2

Figure 2. Kaplan-Meier survival curves for time to recurrence according to the 36-gene classifier

Kaplan-Meier disease-free survival curves based on the 36-gene signature: A, for the cohort of 83 patients from the validation set; B, for the 60 out of these 83 tumors who belong to the St Gallen intermediate-risk group. The _p_-values were calculated by using the log-rank test.

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