GSE9195 Expression Data
Authors/Creators
- Loi, Sherene (Data collector)1
- Haibe-Kains, Benjamin (Data collector)1
- Desmedt, Christine (Data collector)1
- Wirapati, Pratyaksha (Data collector)1
- Lallemand, Françoise (Data collector)1
- Tutt, Andrew M (Data collector)1
- Gillet, Cheryl (Data collector)1
- Ellis, Paul (Data collector)1
- Ryder, Kenneth (Data collector)1
- Reid, James F (Data collector)1
- Daidone, Maria G (Data collector)1
- Pierotti, Marco A (Data collector)1
- Berns, Els Mjj (Data collector)1
- Jansen, Maurice Phm (Data collector)1
- Foekens, John A (Data collector)1
- Delorenzi, Mauro (Data collector)1
- Bontempi, Gianluca (Data collector)1
- Piccart, Martine J (Data collector)1
- Sotiriou, Christos (Data collector)1
- Piccolo, Stephen (Data curator)2
- Nwosu, Ifeanyichukwu (Data curator)2
- Tabler, Daniel (Data curator)2
- Lo, Shu-Fei (Project member)2
- Steadman, Heidi (Project member)2
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1.
Institut Jules Bordet
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2.
Brigham Young University
Description
Predicting prognosis using molecular profiling in estrogen receptor-positive breast cancer treated with tamoxifen.
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.
Files
Files
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