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ZENODO
Dataset . 2008
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2008
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2008
License: CC BY
Data sources: Datacite
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GSE9195 Expression Data

Authors: Loi, Sherene; Haibe-Kains, Benjamin; Desmedt, Christine; Wirapati, Pratyaksha; Lallemand, Françoise; Tutt, Andrew M; Gillet, Cheryl; +17 Authors

GSE9195 Expression Data

Abstract

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.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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Cancer Research