Abstract
A consensus prognostic classifier for estrogen receptor positive breast tumors has been developed and shown to be valid in nearly 900 samples across different microarray platforms.
Highlights
A consensus prognostic gene expression classifier is still elusive in heterogeneous diseases such as breast cancer
In this work we present a combined analysis of estrogen receptor (ER)+ breast cancer that uses a recently proposed framework [16] for objectively evaluating prognostic separation of a molecular classifier across independent data sets and platforms
This choice was motivated by our previous work [12], where a prognostic signature, derived from the NCH cohort, was http://genomebiology.com/2006/7/10/R101
Summary
A consensus prognostic gene expression classifier is still elusive in heterogeneous diseases such as breast cancer. There have been reports of molecular prognostic and predictive signatures that were valid in external independent cohorts [2,3,4,5,6,7] One of these studies derived the prognostic signature from genes correlating with histological grade [4], while in [5] it was derived directly from correlations with clinical outcome data and was validated in Genome Biology 2006, 7:R101. Another study validated a predictive score, based on 21 genes, for ER+LN-tamoxifen treated breast cancer [2] These results are encouraging, yet, as explained recently in [8,9], much larger cohort sizes may be needed before a consensus prognostic signature emerges. These problems have raised questions about the clinical utility of molecular signatures as currently developed [13]
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