The role of microRNA-128a in regulating TGFbeta signaling in letrozole-resistant breast cancer cells

Abstract

Resistance to endocrine therapy agents has presented a clinical obstacle in the treatment of hormone-dependent breast cancer. Our laboratory has initiated a study of microRNA regulation of signaling pathways that may result in breast cancer progression on aromatase inhibitors (AI). Microarray analysis of hormone refractory cell lines identified 115 differentially regulated microRNAs, of which 49 microRNAs were believed to be hormone-responsive. A group of microRNAs were inversely expressed in the AI-resistant lines versus LTEDaro and tamoxifen-resistant. We focused our work on hsa-miR-128a which was hormone-responsive and selectively up-regulated in the letrozole-resistant cell lines. Human miR-128a was predicted to target the TGFβ signaling pathway and indeed sensitivity to TGFβ was compromised in the letrozole-resistant cells, as compared to parental MCF-7aro. Human miR-128a was shown to negatively target TGFβRI protein expression by binding to the 3'UTR region of the gene. Inhibition of endogenous miR-128a resulted in resensitization of the letrozole-resistant lines to TGFβ growth inhibitory effects. These data suggest that the hormone-responsive miR-128a can modulate TGFβ signaling and survival of the letrozole-resistant cell lines. To our knowledge, this is the first study to address the role of microRNA regulation as well as TGFβ signaling in AI-resistant breast cancer cell lines. We believe that in addition to estrogen-modulation of gene expression, hormone-regulated microRNAs may provide an additional level of post-transcriptional regulation of signaling pathways critically involved in breast cancer progression and AI-resistance.

Figure 1. microRNA microarray analysis of the AI, LTEDaro and tamoxifen-resistant cell lines

A) Partek Genomics Suite was used to generate the similarity matrix plot that compared expression of 342 RMA normalized microRNAs. Correlation coefficients were calculated using a linear Pearson correlation algorithm and visualized with red and green indicating high (0.9) and low (0.3) correlation, respectively. Unique clusters of microRNAs that share similar expression patterns are labeled A, B, C and D. B) Hierarchical clustering (Pearson’s dissimilarity algorithm) and heat map analysis of 115 significant microRNAs was based on 1-way ANOVA analysis, in comparison to the parental MCF-7aro cells. The false discovery rate (FDR) was set to 1%, with a corresponding p-value of 0.003. Clusters A, B and C corresponded with microRNA clusters visualized with the similarity matrix (Figure 1A), as labeled on the top dendrogram. Biological replicates were shown horizontally and individual microRNAs were clustered vertically, with red indicating up-regulation and green representing down-regulated microRNA expression, according to the color legend.

Figure 2. Hormone-regulated microRNAs

A) Hierarchical clustering of hormone-responsive microRNAs. Based on the 115 significant microRNAs (p-value of 0.003) identified in Figure 1B, average fold-change criteria of 1.2 was used to select microRNAs up-regulated in the T-only lines and inversely regulated in the parental MCF-7aro cells and hormone-deprived LTEDaro lines. B) Hormone-responsive microRNAs were validated by quantitative real-time PCR with miR-17-3p representatively shown. For internal control purposes, microRNA expression was normalized to U6 small RNA expression in the MCF-7aro, T-only and hormone-free LTEDaro cells. C) Expression of hormone-responsive microRNAs was also validated in the parental MCF-7aro cells, with miR-17-3p shown. Treatment conditions compared DMSO vehicle control to hormone (T and E2) and T+letrozole treatment. For statistical analysis, Student’s t-test compared samples to MCF-7aro and DMSO treated controls in 2B and 2C, with * indicating statistical significance at a p-value < 0.05.

Figure 3. Letrozole-resistant microRNAs

A) Hierarchical clustering and heat map of microRNAs specifically identified in the T+LET R lines. Based on the 115 significant microRNAs (p-value of 0.003) identified in Figure 1B, average fold-change criteria of 1.2 was used to select microRNAs up-regulated in the T+LET R lines. B) Expression of miR-128a was validated using quantitative real- time PCR in the parental MCF-7aro cells, T-only, T+LET R and LTEDaro lines. U6 RNA was used for internal control normalization within samples. For statistical analysis, Student’s t-test compared samples to MCF-7aro control cells, with * indicating statistical significance at a p-value < 0.05.

Figure 4. Loss of sensitivity to the growth inhibitory effects of TGFβ in the T+LET R lines

Dose response proliferation studies with TGFβ1 in the parental MCF-7aro (A) and T+LET R lines (B). For statistical analysis, Student’s t-test compared treatment conditions to media control, with * indicating statistical significance at a p-value < 0.05. C) Luciferase assays were performed using a SMAD 2/3 luciferase reporter, containing the CAGA consensus SMAD binding site, co-transfected with a control pRL-CMV renilla reporter. For statistical analysis, Student’s t-test compared treatment conditions to media control, with ** indicating statistical significance at a p-value < 0.01. D) Western analysis was carried out to determine total protein expression of TGFβR1, in comparison to β-actin protein expression in the MCF-7aro and T+LET R lines. E) Activation of SMAD2 by phosphorylation of serine residues 465/467 was detected by western analysis. Levels of phospho-SMAD2 were compared to total SMAD2 and β-actin.

Figure 5. Human miR-128a targets TGFβR1 at the 3’UTR

A) Expression of miR-128a was detected by real-time PCR, relative to U6 RNA expression, after pre-miR-128a mimic or negative control (NC) transfection. Student’s t-test compared NC and pre-miR-128a transfected cells, with ** indicating statistical significance at a p-value < 0.01. B) Post NC or pre-miR-128a transient transfection, TGFβR1 mRNA expression was detected by real-time PCR analysis, relative to the β-actin housekeeping gene. C) Transfection of the NC or pre-miR-128a mimic was performed and T+LET R cells were harvested for western analysis to detect total TGFβR1 and total SMAD2 expression levels. Quantified western blots of three independent experiments are shown, with * indicating statistical significance using Student’s t-test at a p-value < 0.05. D-E) WT and MT luciferase constructs containing the putative miR-128a target binding site within the 3’UTR of the TGFβR1 were co-transfected with the NC or pre-miR-128a mimic into MCF-7aro (D) and T+LET R (E) cells. For statistical analysis, Student’s t-test compared pre-miR-128a with NC transfected cells in 5D and 5E, with ** indicating statistical significance at a p-value < 0.01.

Figure 6. Anti-miR-128a transfection sensitizes T+LET R lines to the growth inhibitory effects of TGFβ

A) Transient transfection of anti-miR-128a inhibitor versus NC was performed to determine expression of miR-128a by real-time PCR, relative to U6 expression. Student’s t-test compared NC and anti-miR-128a transfected cells, with ** indicating statistical significance at a p-value < 0.01. B) Expression of TGFβR1 was quantified using real-time PCR, after transient transfection of NC or anti-miR-128a inhibitor. C) Transient transfection of NC or anti-miR-128a inhibitor was performed at concentrations of 10, 30 and 50nM and all conditions were treated with 1ng/ml TGFβ1 for 5 days. MTT assays for cell viability were performed in the MCF-7aro and T+LET R lines. For statistical analysis, Student’s t-test compared anti-miR-128a with NC transfected cells in 6C, with * indicating statistical significance at a p-value < 0.05.