A meta-analysis of gene expression-based biomarkers predicting outcome after tamoxifen treatment in breast cancer

To date, three molecular markers (ER, PR, and CYP2D6) have been used in clinical setting to predict the benefit of the anti-estrogen tamoxifen therapy. Our aim was to validate new biomarker candidates predicting response to tamoxifen treatment in breast cancer by evaluating these in a meta-analysis...

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Bibliographic Details
Published in:Breast cancer research and treatment 2013-07, Vol.140 (2), p.219-232
Main Authors: Mihály, Zsuzsanna, Kormos, Máté, Lánczky, András, Dank, Magdolna, Budczies, Jan, Szász, Marcell A, Győrffy, Balázs
Format: Article
Language:English
Subjects:
Analysis
Antineoplastic Agents, Hormonal - administration & dosage
Biological and medical sciences
Biomarkers
Biomarkers, Tumor - biosynthesis
Breast cancer
Breast Neoplasms - drug therapy
Breast Neoplasms - genetics
Breast Neoplasms - pathology
BTG2 protein
Cancer
Cancer research
Cancer therapies
Care and treatment
Clinical outcomes
Cytochrome P-450
Disease-Free Survival
Drug therapy
Estrogen
Female
Gene expression
Gene Expression Regulation, Neoplastic
Genetic aspects
Gynecology. Andrology. Obstetrics
Humans
Kaplan-Meier Estimate
Large Neutral Amino Acid-Transporter 1 - metabolism
Mammary gland diseases
Medical sciences
Medicine
Medicine & Public Health
Multiple tumors. Solid tumors. Tumors in childhood (general aspects)
Neoplasm Recurrence, Local - drug therapy
Neoplasm Recurrence, Local - genetics
Oncology
Prognosis
Pyridines - metabolism
Review
Tamoxifen
Tamoxifen - administration & dosage
tau Proteins - metabolism
Treatment Outcome
Tumors
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Summary:To date, three molecular markers (ER, PR, and CYP2D6) have been used in clinical setting to predict the benefit of the anti-estrogen tamoxifen therapy. Our aim was to validate new biomarker candidates predicting response to tamoxifen treatment in breast cancer by evaluating these in a meta-analysis of available transcriptomic datasets with known treatment and follow-up. Biomarker candidates were identified in Pubmed and in the 2007–2012 ASCO and 2011–2012 SABCS abstracts. Breast cancer microarray datasets of endocrine therapy-treated patients were downloaded from GEO and EGA and RNAseq datasets from TCGA. Of the biomarker candidates, only those identified or already validated in a clinical cohort were included. Relapse-free survival (RFS) up to 5 years was used as endpoint in a ROC analysis in the GEO and RNAseq datasets. In the EGA dataset, Kaplan–Meier analysis was performed for overall survival. Statistical significance was set at p  
ISSN:0167-6806
1573-7217
DOI:10.1007/s10549-013-2622-y