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. 2018 Nov 12;9:4746. doi: 10.1038/s41467-018-07021-3

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© The Author(s) 2018

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 2 — Proliferation and immuno subnetworks. a Heatmap of correlation (Spearman) and cluster analysis of patient’s risk scores of proliferation modules in breast cancer, alongside mRNA abundance of a proliferation marker MKI67. Ward’s method was used for hierarchical clustering. Data shown for validation cohorts. b Kaplan–Meier analysis of predicted proliferation scores (validation cohorts) using SIMMS-derived proliferation biomarker. Groups (Q1-Q4) were established using quartiles derived from the training set. Groups Q2-Q4 were compared to Q1 using Cox proportional hazards model. P value was estimated using Log-rank test assessing heterogeneity across the four groups. c Kaplan–Meier analysis of tumor immune microenvironment driver subnetwork (BioCarta pathway: T cell receptor signaling) in Affymetrix based validation cohorts. Quartile based risk groups (thresholds derived from training set), demonstrating linear increase in the likelihood of recurrence/event. Test statistics same as in b. d Kaplan–Meier analysis of tumor immune microenvironment driver subnetwork (BioCarta pathway: T cell receptor signaling) in Metabric breast cancer cohort (Illumina platform). e Assessment of computationally inferred immune system infiltration and stromal estimates against SIMMS predicted risk groups (Q1-Q4 i.e., low to high) in Affymetrix validation cohorts (test statistic: ANOVA P value). Color of dots represent respective validation cohort (Supplementary Table 2). f Same as e using Metabric cohort (Illumina platform)