A comprehensive analysis of prognostic signatures reveals the high predictive capacity of the proliferation, immune response and RNA splicing modules in breast cancer.
BACKGROUND
Several gene expression signatures have been proposed and demonstrated to be predictive of outcome in breast cancer. In the present article we address the following issues: Do these signatures perform similarly? Are there (common) molecular processes reported by these signatures? 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 outcome group or a 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
The 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.
Reyal
Fabien
F
Department of Pathology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands.
van Vliet
Martin H
MH
Armstrong
Nicola J
NJ
Horlings
Hugo M
HM
de Visser
Karin E
KE
Kok
Marlen
M
Teschendorff
Andrew E
AE
Mook
Stella
S
van 't Veer
Laura
L
Caldas
Carlos
C
Salmon
Remy J
RJ
van de Vijver
Marc J
MJ
Wessels
Lodewyk F A
LF
D001943:Breast Neoplasms / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D049109:Cell Proliferation; D019295:Computational Biology; D030541:Databases, Genetic; D005260:Female; D020869:Gene Expression Profiling; D006801:Humans; D055633:Immune System Phenomena / Q000502:physiology*; D011379:Prognosis; D012326:RNA Splicing / Q000502:physiology*; D015996:Survival Rate