A comprehensive analysis of prognostic signatures reveals the high predictive capacity of Proliferation, Immune response and RNA splicing modules in breast cancer

Fabien Reyal, Martin H. van Vliet, Nicola J. Armstrong, Hugo M. Horlings, Karin E. de Visser, Marlen Kok, Andrew E. Teschendorff, Stella Mook, Laura van 't Veer, Carlos Caldas, Remy J. Salmon, Marc J. van de Vijver, Lodewyk F. A. Wessels

Research output: Contribution to journalArticle*Academicpeer-review

Abstract

ABSTRACT: INTRODUCTION: Several gene expression signatures have been proposed which have been demonstrated to be predictive of outcome in breast cancer. Here we address the following issues: 1) Do these signatures perform similarly? 2) Are there (common) molecular processes reported by these signatures? 3) Can better prognostic predictors be constructed based on these identified molecular processes? METHODS: We performed a comprehensive analysis of the performance of nine gene expression signatures on seven different breast cancer datasets. To better characterize the functional processes associated with these signatures, we enlarged each signature by including all probes with a significant correlation to at least one of the genes in the original signature. The enrichment of functional groups was assessed using four ontology databases. RESULTS: The classification performance of the nine gene expression signatures is very similar in terms of assigning a sample to either a 'poor' or 'good' outcome group. Nevertheless the concordance in classification at the sample level is low, with only 50% of the breast cancer samples classified in the same outcome group by all classifiers. The predictive accuracy decreases with the number of 'poor' outcome assignments given to a sample. The best classification performance was obtained for the group of patients with only 'good' outcome assignments. Enrichment analysis of the enlarged signatures revealed 11 functional modules with prognostic ability. The combination of the RNA-splicing and Immune modules resulted in a classifier with high prognostic performance on an independent validation set. CONCLUSIONS: This study revealed that the nine signatures perform similarly but exhibit a large degree of discordance in prognostic group assignment. Functional analyses indicate that proliferation is a common cellular process, but that other functional categories are also enriched and show independent prognostic ability. We provide new evidence of the potentially promising prognostic impact of Immunity and RNA-splicing processes in breast cancer
Original languageEnglish
Pages (from-to)R93
JournalBreast cancer research
Volume10
Issue number6
DOIs
Publication statusPublished - 2008

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