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Gene expression signatures that predict outcome of tamoxifen-treated estrogen receptor-positive, high-risk, primary breast cancer patients: a DBCG study.

ABSTRACT: BACKGROUND: Tamoxifen significantly improves outcome for estrogen receptor-positive (ER+) breast cancer, but the 15-year recurrence rate remains 30%. The aim of this study was to identify gene profiles that accurately predicted the outcome of ER+ breast cancer patients who received adjuvant Tamoxifen mono-therapy. METHODOLOGY/PRINCIPAL FINDINGS: Post-menopausal breast cancer patients diagnosed no later than 2002, being ER+ as defined by >1% IHC staining and having a frozen tumor sample with >50% tumor content were included. Tumor samples from 108 patients treated with adjuvant Tamoxifen were analyzed for the expression of 59 genes using quantitative-PCR. End-point was clinically verified recurrence to distant organs or ipsilateral breast. Gene profiles were identified using a model building procedure based on conditional logistic regression and leave-one-out cross-validation, followed by a non-parametric bootstrap (1000x re-sampling). The optimal profiles were further examined in 5 previously-reported datasets containing similar patient populations that were either treated with Tamoxifen or left untreated (n?=?623). Three gene signatures were identified, the strongest being a 2-gene combination of BCL2-CDKN1A, exhibiting an accuracy of 75% for prediction of outcome. Independent examination using 4 previously-reported microarray datasets of Tamoxifen-treated patient samples (n?=?503) confirmed the potential of BCL2-CDKN1A. The predictive value was further determined by comparing the ability of the genes to predict recurrence in an additional, previously-published, cohort consisting of Tamoxifen-treated (n?=?58, p?=?0.015) and untreated patients (n?=?62, p?=?0.25). CONCLUSIONS/SIGNIFICANCE: A novel gene expression signature predictive of outcome of Tamoxifen-treated patients was identified. The validation suggests that BCL2-CDKN1A exhibit promising predictive potential.

SUBMITTER: Lyng MB

PROVIDER: S-EPMC3546921 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Gene expression signatures that predict outcome of tamoxifen-treated estrogen receptor-positive, high-risk, primary breast cancer patients: a DBCG study.

Lyng Maria B MB Lænkholm Anne-Vibeke AV Tan Qihua Q Vach Werner W Gravgaard Karina H KH Knoop Ann A Ditzel Henrik J HJ

PloS one 20130116 1

<h4>Background</h4>Tamoxifen significantly improves outcome for estrogen receptor-positive (ER+) breast cancer, but the 15-year recurrence rate remains 30%. The aim of this study was to identify gene profiles that accurately predicted the outcome of ER+ breast cancer patients who received adjuvant Tamoxifen mono-therapy.<h4>Methodology/principal findings</h4>Post-menopausal breast cancer patients diagnosed no later than 2002, being ER+ as defined by >1% IHC staining and having a frozen tumor sam ...[more]

PMID: 23342080

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Project description:PurposeRecent data have shown that the expression levels of long noncoding RNAs (lncRNAs) are associated with tamoxifen sensitivity in estrogen receptor (ER)-positive breast cancer. Herein, we constructed an lncRNA-based model to predict disease outcomes of ER-positive breast cancer patients treated with tamoxifen.MethodsLncRNA expression information was acquired from Gene Expression Omnibus by re-mapping pre-existing microarrays of patients with ER-positive breast cancer treated with tamoxifen. The distant metastasis-free survival (DMFS) predictive signature was subsequently built based on a Cox proportional hazard regression model in discover cohort patients, which was further evaluated in another independent validation dataset.ResultsSix lncRNAs were found to be associated with DMFS in the discover cohort, which were used to construct a tamoxifen efficacy-related lncRNA signature (TLS). There were 133 and 362 patients with TLS high- and low-risk signatures in the discover cohort. Both univariate and multivariate analysis demonstrated that TLS was associated with DMFS. TLS high-risk patients had worse outcomes than low-risk patients, with a hazard ratio of 4.04 (95% confidence interval, 2.83-5.77; p<0.001). Both subgroup analysis and receiver operating characteristic analysis indicated that TLS performed better in lymph node-negative, luminal B, 21-gene recurrence score high-risk, and 70-gene prognosis signature high-risk patients. Moreover, in a comparison of the 21-gene recurrence score and 70-gene prognosis signature, TLS showed a similar area under receiver operating characteristic curve in all patients. Gene Set Enrichment Analysis indicated that TLS high-risk patients showed different gene expression patterns related to the cell cycle and nucleotide metabolism from those of low-risk patients.ConclusionThis six-lncRNA signature was associated with disease outcome in ER-positive breast cancer patients treated with tamoxifen, which is comparable to previous messenger RNA signatures and requires further clinical evaluation.

Dataset Information

Gene expression signatures that predict outcome of tamoxifen-treated estrogen receptor-positive, high-risk, primary breast cancer patients: a DBCG study.

Publications

Gene expression signatures that predict outcome of tamoxifen-treated estrogen receptor-positive, high-risk, primary breast cancer patients: a DBCG study.

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