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Figure 5 | Breast Cancer Research

Figure 5

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

Figure 5

Enrichment analysis for the seven enlarged signatures and Kaplan–Meier analysis of distant metastasis-free survival. (a) Enrichment analysis for the seven enlarged signatures on a collection of 1,889 gene sets from the Reactome, Kyoto Encyclopedia of Genes and Genomes (KEGG), Molecular Signatures Database, and Gene Ontology databases. Significance of the P values was computed with the hypergeometric test. All P values were adjusted for multiple testing using the Benjamini–Hochberg method. Each cell in the matrix represents the adjusted P value for a given enlarged signature and a gene set. The ontology modules to which a particular gene set belongs are indicated at the top. See (b) for the link between the color coding and the module identity. (b) Kaplan–Meier analysis of distant metastasis-free survival (DMFS) on the Chin–Loi training set for each of the 11 ontology modules. The Kaplan–Meier analysis is based on the output of a nearest mean classifier trained on the genes in each of the ontology modules. (c) Kaplan–Meier analysis of DMFS on van Vijver and colleagues' breast cancer series as stratified by the Immune and RNA splicing module classifier, for both endpoints. Blue curve, low-risk group where both classifiers assign a patient to the good outcome group; grey curve, intermediate-risk category where the classifiers are discordant; red curve, high-risk category where both classifiers assign a patient to the poor outcome group. For comparison, the same dataset as stratified by the Netherlands Cancer Institute (NKI) 70-gene classifier for both endpoints is also presented.

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