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. 2021 Dec 4;21(1):1296.
doi: 10.1186/s12885-021-08955-6.

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

Chiara Giacomelli  1   2 , Janine Jung #  3 , Astrid Wachter #  4 , Susanne Ibing  5 , Rainer Will  6 , Stefan Uhlmann  3 , Heiko Mannsperger  3 , Özgür Sahin  3   7 , Yosef Yarden  8 , Tim Beißbarth  4 , Ulrike Korf  3 , Cindy Körner  3 , Stefan Wiemann  9
Affiliations

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

Chiara Giacomelli et al. BMC Cancer. .

Abstract

Background: Triple negative breast cancer (TNBC) is the most aggressive subtype of breast cancer (BC). Treatment options for TNBC patients are limited and further insights into disease aetiology are needed to develop better therapeutic approaches. microRNAs' ability to regulate multiple targets could hold a promising discovery approach to pathways relevant for TNBC aggressiveness. Thus, we address the role of miRNAs in controlling three signalling pathways relevant to the biology of TNBC, and their downstream phenotypes.

Methods: To identify miRNAs regulating WNT/β-catenin, c-Met, and integrin signalling pathways, we performed a high-throughput targeted proteomic approach, investigating the effect of 800 miRNAs on the expression of 62 proteins in the MDA-MB-231 TNBC cell line. We then developed a novel network analysis, Pathway Coregulatory (PC) score, to detect miRNAs regulating these three pathways. Using in vitro assays for cell growth, migration, apoptosis, and stem-cell content, we validated the function of candidate miRNAs. Bioinformatic analyses using BC patients' datasets were employed to assess expression of miRNAs as well as their pathological relevance in TNBC patients.

Results: We identified six candidate miRNAs coordinately regulating the three signalling pathways. Quantifying cell growth of three TNBC cell lines upon miRNA gain-of-function experiments, we characterised miR-193b as a strong and consistent repressor of proliferation. Importantly, the effects of miR-193b were stronger than chemical inhibition of the individual pathways. We further demonstrated that miR-193b induced apoptosis, repressed migration, and regulated stem-cell markers in MDA-MB-231 cells. Furthermore, miR-193b expression was the lowest in patients classified as TNBC or Basal compared to other subtypes. Gene Set Enrichment Analysis showed that miR-193b expression was significantly associated with reduced activity of WNT/β-catenin and c-Met signalling pathways in TNBC patients.

Conclusions: Integrating miRNA-mediated effects and protein functions on networks, we show that miRNAs predominantly act in a coordinated fashion to activate or repress connected signalling pathways responsible for metastatic traits in TNBC. We further demonstrate that our top candidate, miR-193b, regulates these phenotypes to an extent stronger than individual pathway inhibition, thus emphasizing that its effect on TNBC aggressiveness is mediated by the coordinated repression of these functionally interconnected pathways.

Keywords: Integrin signalling; Triple negative breast cancer; WNT/β-catenin; c-Met signalling; microRNAs.

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Conflict of interest statement

All the authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
miRNAs coordinately regulate signalling pathways despite mildly regulating individual targets. A and B – MDA-MB-231 cells were transfected with individual miRNAs from a library of 800 representing the global miRNome. 48 h post-transfection, total protein lysates were harvested and the expression of 62 target proteins was assessed by Reverse Phase Protein Assay (RPPA). After normalization for total protein content, the effect of miRNAs on target proteins was quantified by limma test. P-values were corrected for multiple testing with Benjamini-Hochberg method. Tabular results are available in Supplementary Table 2. A. Effects of miRNAs on the 62 probed targets are represented with a heatmap of all fold changes compared to negative controls in log2 scale (log2FC). Only miRNAs which caused at least one statistically significant interaction across the entire dataset were plotted, leading to 722 rows. The upper rug represents the prevalence of miRNA regulation for each target, weighted for the library size, separating the number of miRNAs significantly positively (+ve) or negatively (−ve) regulate each target. The second rug represents the average of statistically significant (q-value ≤0.001) regulation of each target, separating positive and negative regulations. The lower rugs represent from which pathway(s) of origin the targets derived from, as well as the putative effect of the target on the pathway. B. The regulatory activity of miRNAs is summarised in a violin plot containing all statistically significant (q ≤ 0.001) log2FC in protein expression. Full and dotted lines in the violins respectively represent the medians and the quartiles of the distributions. The horizontal lines in the plot represent the averages. C. Principles of PC score computation to transform the effect of a miRNA on a single target protein into a Pathway Coregulatory (PC) effect, integrating the function of the assayed protein on the signalling pathway. miRNA negatively or positively regulate (dark purple and green, respectively) the expression of a target with repressive or activating function (lilac and yellow, respectively). The combination of these two factors identifies the effect on the pathway as positive or negative (bright green or red, respectively). The cumulative effect of a miRNA is then summarized in a PC score classifying each miRNA as activator or repressor of a pathway. D. The distributions of computed PC scores for WNT/β-catenin (left), c-Met (middle), and integrin signalling (right). In each graph, numbers indicate the number of putative repressing or activating proteins probed associated to the pathway. E. Principles of bootstrapping for statistical testing. The miR-N matrix used to calculate the PC scores was randomized 10,000 times, for each a miRNA-specific random PC score was computed. Then, the experimental PC score was tested against the randomly generated ones. An experimental PC score was considered significant with a 5% alpha level. F. Venn diagrams display the number of miRNAs repressing (left) or activating (right) the signalling pathways with a significant effect after randomization test
Fig. 2
Fig. 2
Candidate miRNAs repress pathway activity and pathway-dependent growth. A. Stable isogenic Recombinant (SiR) MDA-MB-231 cells were transfected with miRNA mimics or treated with iCRT-14. 30 h later cells were stimulated with recombinant WNT3a. 18 h later, FLuc and RLuc activities were assayed. The effect of miRNAs and iCRT-14 are shown on normalized luciferase activity relative to respective negative controls. Significance was calculated by one-sample, two-tailed t-test on three independent SiR clones. P-values *** ≤ 0.0001, *** ≤ 0.001. B. 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. Growth reduction is represented in red and growth induction in green. Corresponding full bar charts are shown in Supplementary Fig. 3 with statistics. 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 cell growth was evaluated by nuclei counts. For every condition, the effect of treatments was compared to relative vehicle (DMSO for iCRT-14 and Capmatinib, PBS for Erlotinib; BSA as vehicle control for all stimulations). 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 ** ≤ 0.01, * ≤ 0.05. non-significant are not marked
Fig. 3
Fig. 3
miR-193b regulates apoptosis, migration, and stemness in TNBC cell lines. A and B – MDA-MB-231 cells were treated and 72 h later apoptosis was evaluated by Propodium Iodide positive nuclei. For each condition, the effect of treatments was quantified relative to respective controls. Unstimulated conditions represent BSA-containing media to the same final concentration present in stimulation conditions, where it was used as carrier protein. AThe effect of miR-193b was compared to two negative miRNA mimics. B The effect of inhibitors was compared to the respective vehicle controls. Each experiment was repeated in biological triplicate, with six technical replicates each. Significance was calculated by two-tailed t-tests (one-sample for chemical inhibitors, unpaired for miRNA OE). P-values *** ≤ 0.001, ** ≤ 0.01, * ≤ 0.05. non-significant are not marked. C. Serum-starved MDA-MB-231 cells overexpressing miR-193b or treated with iCRT-14 were seeded in the upper compartment of a transwell system, with serum in the lower chamber as chemoattractant. 20 h later, migration relative to controls was evaluated by nuclei counts. The effect of miR-193b was tested against miRNA mimic negative control #2 (top), and the effect of iCRT-14 against its vehicle, DMSO (bottom). The experiment was repeated in biological triplicate with three technical replicates each. Significance was calculated by one-sample, two-tailed t-test. P-values **** ≤ 0.0001. D and E – FACS analysis of CD24 and CD44 surface marker expression in MDA-MB-231 cells 96 h post-transfection with miR-193b or iCRT-14 treatment, compared to respective controls. The experiment was repeated in six biological replicates, with two technical replicates each. Significance was calculated by paired, two-tailed t-test. P-values indicated on each graph. P-values *** ≤ 0.001, ** ≤ 0.01, * ≤ 0.05. non-significant are not marked. D For each condition, the percentage of cells gated as CD44 positive and CD24 negative (stem-like population) is plotted. E For each condition, the percentage of cells gated as CD44 negative (left bars) or CD24 positive (right bars) are plotted
Fig. 4
Fig. 4
miR-193b expression in BRCA patients is associated with aggressiveness and gene sets of signalling pathways of interest. A and B – Violin plots of miR-193b expression in two BRCA datasets. Dashed and dotted lines within violins represent the median and quartiles of the distributions. Within each dataset, the number of patients belonging to the TNBC or non-TNBC classification are written in parentheses at the x-axes. Statistical significance was calculated using two-tailed, unpaired t-test. Statistical significance is indicated above comparisons: p-values by asterisks **** ≤ 0.0001, *** ≤ 0.001, ** ≤ 0.01, * ≤ 0.05, ns = not significant. A miR-193b expression stratifying patients by receptor expression status in TCGA (left) and METABRIC (right) datasets. B miR-193b expression in two BRCA datasets stratifying patients by PAM50 classification into Basal, Her2, Luminal A (LumA), and Luminal B (LumB). C. Gene Set Enrichment Analysis of gene lists for positive and negative regulators of WNT signalling (blue box), c-Met signalling (purple box), and integrin signalling (orange box). Normalized enrichment scores (NES) and statistical significance by false discovery rates (FDR) are indicated below every signature. D Effect of miR-193b on the three signalling pathways, integrated according to their KEGG maps with downstream phenotypes. Target proteins probed in the HTS are shaded in lilac or pale yellow when they are repressors or activators of the pathways, respectively. miR-193b repressive or activating effect on the pathways is represented by a box around the proteins significantly regulated, of red or green colour, respectively. The chemical inhibitors’ activities are highlighted in blue (iCRT-14), purple (Capmatinib), and green (Erlotinib)
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