Additional file 1: of A subgroup of microRNAs defines PTEN-deficient, triple-negative breast cancer patients with poorest prognosis and alterations in RB1, MYC, and Wnt signaling

Figure S1. Overview of breast cancer (BC) datasets, cohorts and groups used in this project, and subgrouping analysis. (A) The 1302 BC dataset, which includes 205 triple-negative breast cancers (TNBC) with matched mRNA and miRNA data from EGAS00000000122, was used as training cohort. Six subgroups of all BC or TNBC were randomly divided to correlate expression of PTEN and miRNAs. The 207 BC dataset, which contained 44 TNBC with matched mRNA and miRNA data from GSE22220, was used as validation cohort. 205 related TNBC with copy number alteration (CNA) data and 185 related TNBC with gene mutation data from EGAS00001001753 were used to confirm genomic changes of PTEN-miRNA co-expression profile. (B) Kaplan-Meier survival analysis on PAM50 classification of all 1302 breast cancers (BC), and examples of subgroups 2A-651 BC and 2B-651 BC. (C) Heatmap of correlation coefficient (r) between PTEN and miRNAs for most positive or negative correlation in BC (left) or TNBC (right). Figure S2. DNA sequence variations in TNBC subgroups. (A) Heatmaps of Copy Number Alteration (CNA) of 93 protein-coding cancer genes among the different subgroups in 31 PTEN(-) TNBC. (B) Mutational landscape of 74 genes that have at least one mutated gene among the TNBC subgroups in 28 PTEN(-) TNBC.. Figure S3. Significant changes in copy number alterations (CNA) in protein-coding cancer genes among TNBC subgroups. CNA of total gain (1 + 2) and loss (-1 + -2) in TNBC subgroups and CNA changes of CUX1, DNMT3A, GATA3, MMLLT4, MYC, PBRM1, PTEN and ZNF217. Figure S4. Low EGFR pathway activity in PTEN-deficient TNBC including subgroup ‘a’ as compared to PTEN+ tumors. Figure S5. mRNA expression and CNA of Wnt/β-catenin signaling related genes in PTEN-low/miRs-low (subgroup ‘a’) TNBC versus other TNBC. Figure S6. mRNA expression and CNA of Wnt/β-catenin signaling related genes in PTEN(-)/β-catenin(+) TNBC versus other TNBC. Figure S7. Mutation in PTEN/β-catenin(+) TNBC versus other TNBC. 173 gene mutation data were compared and 135 genes with at least one mutation are shown in order of the number of mutated genes. Figure S8. CRNDE mRNA expression level and distribution in 1292 BC in EGAS00000000083. (A) Expression level of CRNDE mRNA in high (> 1), medium (1 to 0) and low (< 0) was tested by Log-rank test and revealed no significant difference. CRNDE distribution of mRNA expression was compared in TNBC subgroups (B) and PAM50 subtypes (C) by ANOVA and t-test. Figure S9. Correlation between CRNDE expression and target miRNAs in TNBC subgroups and PAM50 subtypes. Pearson correlation was preformed between CRNDE and its target miRNAs miR-136 and miR-451 in TNBC subgroups and PAM50 subtypes. CRNDE targets miRNAs miR-384 and miR-181a-5p are not available in EGAD00010000438 miRNA dataset; four miR-181a-related miRNAs were tested here. Figure S10. Target miRNAs are predicted to regulate MYC, β-Catenin and PI3K signalling pathways. (A) Predicted target genes and overlap between the five identified miRNAs using miRWalk3 miRNAs target mining tool. (B) Detected target genes overlap with MYC, β-Catenin 3 and PI3K pathway activity genes. (C) mRNA expression of top 20 detected target genes on the MYC, β-Catenin and PI3K pathways that are regulated by the five identified miRNAs. (D) mRNA expression of six detected targets of the five miRNAs and/or MYC, β-Catenin and PI3K pathway training genes that appear more than once in panel C. Figure S11. Connectivity map by GWC identifies PI3K and other drugs for PTEN-low/miRs-low subgroup of TNBC. Connectivity scores (CS) of drug hits generated using the GSEA method and different sizes of the PTEN-low/miRs-low TNBC (group ‘a’; 4 signature sizes). Each dot represents the connectivity score of a specific drug, and colors reflect gene signature size used in the connectivity map analysis. Dots plotted represent drug hits that have a negative CS < (-0.3) across all signature sizes. Dots above the CS line of -0.5, indicate drugs that have a better ability to reverse the TNBC group ‘a’ signature in the connectivity map analysis. No drugs had score <-0.5 across all 4 runs. Thus, for this analysis, the stringency cut-off was set at <-0.45). Figure S12. Overlap between drug hits using GSEA and GWC connectivity scoring metrics. The number of drug hits is based on group ‘a’ TNBC gene signature size tested, with CS <-0.5. Common drugs identified by both methods in each analysis are highlighted. For 200 gene size, see Fig. 6c. (PPTX 2216 kb