A consensus prognostic gene expression classifier for ER positive breast cancer.

Abstract:: BACKGROUND: A consensus prognostic gene expression classifier is still elusive in heterogeneous diseases such as breast cancer. RESULTS: Here we perform a combined analysis of three major breast cancer microarray data sets to hone in on a universally valid prognostic molecular classifier in estrogen receptor (ER) positive tumors. Using a recently developed robust measure of prognostic separation, we further validate the prognostic classifier in three external independent cohorts, confirming the validity of our molecular classifier in a total of 877 ER positive samples. Furthermore, we find that molecular classifiers may not outperform classical prognostic indices but that they can be used in hybrid molecular-pathological classification schemes to improve prognostic separation. CONCLUSION: The prognostic molecular classifier presented here is the first to be valid in over 877 ER positive breast cancer samples and across three different microarray platforms. Larger multi-institutional studies will be needed to fully determine the added prognostic value of molecular classifiers when combined with standard prognostic factors.

Authors:: AE Teschendorff, A Naderi, NL Barbosa-Morais, SE Pinder, IO Ellis, S Aparicio, JD Brenton, C Caldas

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