Elsevier

Neoplasia

Volume 10, Issue 1, January 2008, Pages 79-88, IN30-IN34
Neoplasia

A Transcriptional Fingerprint of Estrogen in Human Breast Cancer Predicts Patient Survival

https://doi.org/10.1593/neo.07859Get rights and content
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Estrogen signaling plays an essential role in breast cancer progression, and estrogen receptor (ER) status has long been a marker of hormone responsiveness. However, ER status alone has been an incomplete predictor of endocrine therapy, as some ER+ tumors, nevertheless, have poor prognosis. Here we sought to use expression profiling of ER+ breast cancer cells to screen for a robust estrogen-regulated gene signature that may serve as a better indicator of cancer outcome. We identified 532 estrogen-induced genes and further developed a 73-gene signature that best separated a training set of 286 primary breast carcinomas into prognostic subtypes by stepwise cross-validation. Notably, this signature predicts clinical outcome in over 10 patient cohorts as well as their respective ER+ subcohorts. Further, this signature separates patients who have received endocrine therapy into two prognostic subgroups, suggesting its specificity as a measure of estrogen signaling, and thus hormone sensitivity. The 73-gene signature also provides additional predictive value for patient survival, independent of other clinical parameters, and outperforms other previously reported molecular outcome signatures. Taken together, these data demonstrate the power of using cell culture systems to screen for robust gene signatures of clinical relevance.

Abbreviations

ER
estrogen receptor
FDR
false discovery rate
KM
Kaplan-Meier
MCM
molecular concept map
OS
overall survival
SAM
significance analysis of microarrays

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This research was supported in part by the National Institutes of Health (R01 CA97063 to A. M. C. and D. G., U54 DA021519-01A1 to A. M. C.), the Early Detection Research Network (UO1 CA111275 to A. M. C. and D. G.), the National Institutes of General Medical Sciences (GM 72007 to D. G.), the Department of Defense (W81XWH-06-1-0224 to A. M. C. and PC060266 to J. Y.), and the Cancer Center Bioinformatics Core (support grant 5P30 CA46592 to A. M. C.). A. M. C. is supported by a Clinical Translational Research Award from the Burroughs Welcome Foundation. K. E. C., M. E. L., and J. M. R. are supported by the Breast Cancer Research Foundation N003173. This article refers to supplementary material, which are designated by Tables W1, W2, W3, and W4 and Figure W1 and are available online at www.neoplasia.com.

3

These authors contributed equally to this manuscript.

4

These authors share senior authorship.