Extended Data Fig. 6: Data related to Fig. 3.
From: AKT and EZH2 inhibitors kill TNBCs by hijacking mechanisms of involution
a, gene set enrichment analysis of open peaks enriched in sensitive and resistant TNBC cell lines at baseline as assessed by ATAC-seq. Adjusted p values are FDR calculated using the Benjamini Hochberg method within the GSEA software. b-c, leading edge plot of gene set enrichment analysis of CHARAFE BREAST CANCER BASAL VS MESENCHYMAL DOWN (mesenchymal genes, (b)) and CHARAFE BREAST CANCER BASAL VS MESENCHYMAL UP (basal genes, (c)) in sensitive and resistant cell lines at baseline as measured by RNA-seq. Adjusted p values are FDR calculated using the Benjamini Hochberg method within the GSEA software. d, heatmap of correlation coefficients of differentially expressed genes in TNBC cell lines generated in this study as DMSO treated samples or sourced from the CCLE dataset. e, relative cell counts of five additional TNBC cell lines predicted to be sensitive or resistant by machine learning models. Data are mean ± s.d. of biological independent samples. n = 3. f, performance metrics for machine learning models. g, oncoprint of TNBC tumours from TCGA firehose dataset with alterations for AKT3, PTEN, INPP4B, and PIK3CA denoted.
