Fig. 3

Integrative analysis of DNA methylation and gene expression data identifies a 14-gene signature of MG stress with clinical relevance.A Workflow showing the integration of differential gene expression, methylation and their corresponding GSEA pathway enrichment under MG stress condition. This integration led to the selection of 60 potential candidates that represented genes repressed under MG stress. These 60 genes were validated in xenografts and refined further using pathway correlation approach (detailed in Material and Methods) using TNBC patient data from METABRIC cohort. This resulted in a final 14-gene based signature of MG stress. Next, MG score was derived from this MG signature and was evaluated for its clinical relevance in TNBC patients. The numbers in the yellow boxes correspond to the genes resulting from the indicated analysis. The numbers in the green boxes represent GSEA pro-oncogenic pathways with their respective total number of genes specified between brackets. B Signature optimization data are represented in a heatmap showing correlation between the six MG stress-affected pathways (rows) and 60 integration genes (columns) using METABRIC TNBC patient cohort. Genes with statistically significant correlation greater than 0.25 with at least one of the pathways were selected for composing the final MG signature. The outcome of this optimization step is 14 genes highlighted in bold in the columns and composing MG signature (detailed in Material and Methods). Positive and negative correlations are shown in red and cyan colors, respectively. Insignificant correlation values (p-value > 0.05 or correlation coefficient = 0) are shown as white boxes. C Top panel represents a heatmap of the 14-gene MG signature in METABRIC TNBC patients (n = 277). Middle panel shows the waterfall plot representing TNBCs distribution from low to high MG score (Y-axis). Bottom panel represents signature status of hypermethylator phenotype [27], metabolic glycolysis and hypoxia signatures based on Reactome gene lists, LDHB gene expression, and metabolic-pathway-based subtypes (MPS1, MPS2, MPS3) [53]. All these signature scores are represented as low (green), mid (yellow) and high (red) level and their respective Spearman correlation (R) with p-values is given when compared to MG signature score. D Kaplan–Meier curves showing significant differences (p = 0.015) in disease specific survival between low (n = 93) and high (n = 93) MG score TNBC tumors from METABRIC cohort. E Kaplan–Meier curves showing significant differences of disease specific survival across Lehmann subtypes using METABRIC TNBC cohort with respective MG score status highlighted in the pie plots shown beside. As MG score increases the survival probability decreases, with patients bearing BL1 and UNS tumor subtypes being among the worst survivors. Respective number of patients for each TNBC subtype are mentioned in parentheses