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Series GSE9195 Query DataSets for GSE9195
Status Public on May 07, 2008
Title Predicting prognosis using molecular profiling in estrogen receptor-positive breast cancer treated with tamoxifen
Organism Homo sapiens
Experiment type Expression profiling by array
Summary Background: Estrogen receptor positive (ER+) breast cancers (BC) are heterogeneous with regard to their clinical behavior and response to therapies. The ER is currently the best predictor of response to the anti-estrogen agent tamoxifen, yet up to 30-40% of ER+BC will relapse despite tamoxifen treatment. New prognostic biomarkers and further biological understanding of tamoxifen resistance are required. We used gene expression profiling to develop an outcome-based predictor using a training set of 255 ER+ BC samples from women treated with adjuvant tamoxifen monotherapy. We used clusters of highly correlated genes to develop our predictor to facilitate both signature stability and biological interpretation. Independent validation was performed using 362 tamoxifen-treated ER+ BC samples obtained from multiple institutions and treated with tamoxifen only in the adjuvant and metastatic settings.

Results: We developed a gene classifier consisting of 181 genes belonging to 13 biological clusters. In the independent set of adjuvantly-treated samples, it was able to define two distinct prognostic groups (HR 2.01 95%CI: 1.29-3.13; p=0.002). Six of the 13 gene clusters represented pathways involved in cell cycle and proliferation. In 112 metastatic breast cancer patients treated with tamoxifen, one of the classifier components suggesting a cellular inflammatory mechanism was significantly predictive of response.

Conclusions: We have developed a gene classifier that can predict clinical outcome in tamoxifen-treated ER+ BC patients. Whilst our study emphasizes the important role of proliferation genes in prognosis, our approach proposes other genes and pathways that may elucidate further mechanisms that influence clinical outcome and prediction of response to tamoxifen.
Keywords: disease state analysis
 
Overall design dataset of microarray experiments from primary breast tumors of patients treated by Tamoxifen in adjuvant setting. No replicate, no reference sample.
 
Contributor(s) Loi S, Haibe-Kains B, Desmedt C, Wirapati P, Lallemand F, Tutt AM, Gilett C, Ellis P, Ryder K, Reid JF, Daidone MG, Pierotti MA, Berns E, Jansen M, Foekens JJ, Delorenzi M, Bontempi G, Piccart MJ, Sotiriou C
Citation(s) 18498629, 20479250
Submission date Sep 28, 2007
Last update date Mar 25, 2019
Contact name Benjamin Haibe-Kains
E-mail(s) benjamin.haibe.kains@utoronto.ca
Phone +14165818626
Organization name Princess Margaret Cancer Centre
Department Princess Margaret Research
Lab Bioinformatics and Computational Genomics
Street address 610 University Avenue
City Toronto
State/province Ontario
ZIP/Postal code M5G 2M9
Country Canada
 
Platforms (1)
GPL570 [HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2.0 Array
Samples (77)
GSM232194 GUYT2_50261
GSM232195 GUYT2_50262
GSM232196 GUYT2_50263
Relations
BioProject PRJNA102769

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE9195_RAW.tar 628.2 Mb (http)(custom) TAR (of CEL)
GSE9195_TAMVALIDATION.RData 56.5 Mb (ftp)(http) RDATA
GSE9195_TAMVALIDATION_README.txt 2.1 Kb (ftp)(http) TXT
GSE9195_TAMVALIDATION_annot_hgu133ab.txt 848.5 Kb (ftp)(http) TXT
GSE9195_TAMVALIDATION_annot_hgu133plus2.txt 4.4 Mb (ftp)(http) TXT
GSE9195_TAMVALIDATION_demo.txt 5.6 Kb (ftp)(http) TXT
Processed data included within Sample table

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