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

Abstract

Introduction 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.

The contribution of gene expression profiling to breast cancer classification, prognostication and prediction: a retrospective of the last decade

“…Contrary to previous 'cancer stem cell' signatures, patients with ER-positive tumours expressing a 'mammosphere-derived' gene set had a significantly longer overall survival, independent of age, size, histological grade, lymph node status, ER, PR and HER2. This is not surprising, as outcome of patients with ER-positive disease has been shown to be largely determined by the expression levels of proliferation genes [31,104,111]. Furthermore, the 'mammospherederived' gene set did not show any discriminatory power in ER-negative breast cancers [110].…”

“…The 'wound-response signature' (ie CSR) was shown to be an independent predictor of metastasis and outcome in the NKI295 dataset, improved risk stratification based on the NIH or St. Gallen consensus criteria and identified patients with 'low risk' in the group of 'high-risk' patients stratified according to the NIH or St. Gallen guidelines [115]. Despite the alleged removal of cell cycle-related genes from the CSR, the wound-response signature was still found to be significantly enriched for proliferation genes [31,111].…”

Gene expression profiling integrated into network modelling reveals heterogeneity in the mechanisms of BRCA1 tumorigenesis

“…The expression level of immune response genes has recently been shown to provide prognostic value for sporadic ER-negative breast tumours (Teschendorff et al, 2007) and this biological process seems to be commonly present in breast cancer prognosis signatures (Reyal et al, 2008). Examination of gene-set #2 and the signature of Teschendorff et al (2007) identified 18 genes in common, which is higher than the number expected by chance (P-value o10 À7 ).…”

Basal-like and triple-negative breast cancers: a critical review with an emphasis on the implications for pathologists and oncologists

“…Recently, several groups have identified a subgroup of good prognosis ERÀ cancers, encompassing a subgroup of triple-negative and basal-like tumors, which is characterized by the expression of an immune response module. [125][126][127][128] This transcriptomic profile may prove helpful for the identification of patients with triple-negative and basal-like cancers that have a better outcome. In this context, the finding of higher expression of CT-X antigens (in particular MAGE and NY-ESO) in this subgroup opens up another potential avenue for therapy as vaccines against these antigens are already in clinical trial for lung cancer.…”