Additional file 2 of Coordinated regulation of WNT/β-catenin, c-Met, and integrin signalling pathways by miR-193b controls triple negative breast cancer metastatic traits

Additional file 2 Supplementary Fig. 1. Quantifying effects of miRNAs library overexpression on individual targets. Violin plots of all significant (q ≤ 0.001) positive or negative log2FCs computed by limma testing, for each individual protein assayed. Proteins are ranked by average negative log2FC. p21-Rac, and SHP-2 are displayed at the end of the distribution since they are not significantly upregulated by any miRNA. Within each violin, dashed lines represent the medians and dotted lines represent the quartiles of the distributions. Horizontal red and blue lines represent the averages and medians, respectively, computed from the whole HTS. Supplementary Fig. 2. Addressing biological features of transcript regulating protein expression patterns. A. Effect of miRNAs on selected targets is represented in three volcano plots. The log2 fold change of protein expression compared to control miRNA mimics is plotted on the x-axes, q-values (in log10) are plotted on the y-axes. Red horizontal lines identify the q-value cutoff used for the downstream analyses (q ≤ 0.001), vertical dotted lines represent for each target the minimum log2FC at which the cutoff was passed. Statistically significant interactions are in purple (downregulations) or green (upregulations). The three targets displayed are Low-density lipoprotein receptor-related protein 6 (LRP6) (left panel), EGF receptor (EGFR) (middle), and p27/Kip (right). B. Effect of mRNA 3’UTR sizes on miRNA-mediated regulation. For each target assayed, the length of the 3’UTR of the cognate mRNAs is extracted from MDA-MB-231 sequencing data. Sizes of 3’UTRs on the x-axes (in nucleotides – nt.) are then plotted against the number of miRNAs significantly downregulating (left panel) or upregulating (right panel) the expression of the target proteins by at least an absolute value of 0.5 log2FC. For each distribution, Pearson r is computed and in both cases the p-value does not indicate a significant correlation. Supplementary Fig. 3. Candidate miRNAs effect on cell growth. Data represented in main Fig. 2B is represented here as a bar chart to allow for individual value and statistically significance inspection. MDA-MB-231, SUM-159, and HCC-1806 cells were transfected with miRNA mimics, 5 hours later medium was changed and, where marked, pathways were stimulated. 72 h post-transfection cells growth was evaluated by nuclei counts. The effect of miRNAs was compared to two negative miRNA mimics. Each experiment was repeated in biological triplicate, with six technical replicates each. Significance was calculated by one-sample, two-tailed t-test. P-values **** ≤ 0.0001, *** ≤ 0.001, ** ≤ 0.01, * ≤ 0.05. non-significant are not marked. Supplementary Fig. 4. Chemical inhibition of the pathway with reciprocal stimulations. A – C – MDA-MB-231, SUM-159, and HCC-1806 cells were treated with compounds or vehicle controls in combination with pathway stimulations, where marked. 72 h later cells growth was evaluated by nuclei counts. For each condition, the effect of treatments was quantified relative to respective controls. The effect of treatments is compared to relative vehicle (DMSO for Capmatinib, PBS for Erlotinib; BSA as stimulation control). Being a relative growth, a single control bar is shown in plots. Each experiment was repeated in biological triplicate, with six technical replicates each. Significance was calculated by one-sample, two-tailed t-test. P-values * ≤ 0.05. non-significant are not marked.