miR‐200/375 control epithelial plasticity‐associated alternative splicing by repressing the RNA ‐binding protein Quaking
2018; Springer Nature; Volume: 37; Issue: 13 Linguagem: Inglês
10.15252/embj.201899016
ISSN1460-2075
AutoresKatherine A. Pillman, Caroline A. Phillips, Suraya Roslan, John Toubia, B. Kate Dredge, Andrew G. Bert, Rachael Lumb, Daniel Neumann, Xiaochun Li, Simon J. Conn, Dawei Liu, Cameron P. Bracken, David Lawrence, Nataly Stylianou, Andreas Schreiber, Wayne D. Tilley, Brett G. Hollier, Yeesim Khew‐Goodall, Luke A. Selth, Gregory J. Goodall, Philip A. Gregory,
Tópico(s)RNA modifications and cancer
ResumoArticle6 June 2018Open Access Source DataTransparent process miR-200/375 control epithelial plasticity-associated alternative splicing by repressing the RNA-binding protein Quaking Katherine A Pillman Katherine A Pillman orcid.org/0000-0002-5869-889X Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Search for more papers by this author Caroline A Phillips Caroline A Phillips Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Search for more papers by this author Suraya Roslan Suraya Roslan Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Search for more papers by this author John Toubia John Toubia Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Search for more papers by this author B Kate Dredge B Kate Dredge Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Search for more papers by this author Andrew G Bert Andrew G Bert Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Search for more papers by this author Rachael Lumb Rachael Lumb Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Search for more papers by this author Daniel P Neumann Daniel P Neumann Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Search for more papers by this author Xiaochun Li Xiaochun Li Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Search for more papers by this author Simon J Conn Simon J Conn orcid.org/0000-0002-1376-4515 Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Flinders Centre for Innovation in Cancer, College of Medicine & Public Health, Flinders University, Adelaide, SA, Australia Search for more papers by this author Dawei Liu Dawei Liu Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Search for more papers by this author Cameron P Bracken Cameron P Bracken Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Discipline of Medicine, The University of Adelaide, Adelaide, SA, Australia Search for more papers by this author David M Lawrence David M Lawrence Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Search for more papers by this author Nataly Stylianou Nataly Stylianou Institute of Health and Biomedical Innovation, Australian Prostate Cancer Research Centre - Queensland, Princess Alexandra Hospital, Queensland University of Technology, Brisbane, Qld, Australia Search for more papers by this author Andreas W Schreiber Andreas W Schreiber Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Search for more papers by this author Wayne D Tilley Wayne D Tilley orcid.org/0000-0003-1893-2626 Dame Roma Mitchell Cancer Research Laboratories, Adelaide Medical School, University of Adelaide, Adelaide, SA, Australia Freemasons Foundation Centre for Men's Health, Adelaide Medical School, University of Adelaide, Adelaide, SA, Australia Search for more papers by this author Brett G Hollier Brett G Hollier Institute of Health and Biomedical Innovation, Australian Prostate Cancer Research Centre - Queensland, Princess Alexandra Hospital, Queensland University of Technology, Brisbane, Qld, Australia Search for more papers by this author Yeesim Khew-Goodall Yeesim Khew-Goodall orcid.org/0000-0002-0473-5392 Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Discipline of Medicine, The University of Adelaide, Adelaide, SA, Australia School of Molecular and Biomedical Science, The University of Adelaide, Adelaide, SA, Australia Search for more papers by this author Luke A Selth Luke A Selth orcid.org/0000-0002-4686-1418 Dame Roma Mitchell Cancer Research Laboratories, Adelaide Medical School, University of Adelaide, Adelaide, SA, Australia Freemasons Foundation Centre for Men's Health, Adelaide Medical School, University of Adelaide, Adelaide, SA, Australia Search for more papers by this author Gregory J Goodall Corresponding Author Gregory J Goodall [email protected] orcid.org/0000-0003-1294-0692 Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Discipline of Medicine, The University of Adelaide, Adelaide, SA, Australia School of Molecular and Biomedical Science, The University of Adelaide, Adelaide, SA, Australia Search for more papers by this author Philip A Gregory Corresponding Author Philip A Gregory [email protected] orcid.org/0000-0002-0999-0632 Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Discipline of Medicine, The University of Adelaide, Adelaide, SA, Australia Search for more papers by this author Katherine A Pillman Katherine A Pillman orcid.org/0000-0002-5869-889X Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Search for more papers by this author Caroline A Phillips Caroline A Phillips Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Search for more papers by this author Suraya Roslan Suraya Roslan Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Search for more papers by this author John Toubia John Toubia Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Search for more papers by this author B Kate Dredge B Kate Dredge Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Search for more papers by this author Andrew G Bert Andrew G Bert Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Search for more papers by this author Rachael Lumb Rachael Lumb Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Search for more papers by this author Daniel P Neumann Daniel P Neumann Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Search for more papers by this author Xiaochun Li Xiaochun Li Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Search for more papers by this author Simon J Conn Simon J Conn orcid.org/0000-0002-1376-4515 Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Flinders Centre for Innovation in Cancer, College of Medicine & Public Health, Flinders University, Adelaide, SA, Australia Search for more papers by this author Dawei Liu Dawei Liu Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Search for more papers by this author Cameron P Bracken Cameron P Bracken Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Discipline of Medicine, The University of Adelaide, Adelaide, SA, Australia Search for more papers by this author David M Lawrence David M Lawrence Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Search for more papers by this author Nataly Stylianou Nataly Stylianou Institute of Health and Biomedical Innovation, Australian Prostate Cancer Research Centre - Queensland, Princess Alexandra Hospital, Queensland University of Technology, Brisbane, Qld, Australia Search for more papers by this author Andreas W Schreiber Andreas W Schreiber Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Search for more papers by this author Wayne D Tilley Wayne D Tilley orcid.org/0000-0003-1893-2626 Dame Roma Mitchell Cancer Research Laboratories, Adelaide Medical School, University of Adelaide, Adelaide, SA, Australia Freemasons Foundation Centre for Men's Health, Adelaide Medical School, University of Adelaide, Adelaide, SA, Australia Search for more papers by this author Brett G Hollier Brett G Hollier Institute of Health and Biomedical Innovation, Australian Prostate Cancer Research Centre - Queensland, Princess Alexandra Hospital, Queensland University of Technology, Brisbane, Qld, Australia Search for more papers by this author Yeesim Khew-Goodall Yeesim Khew-Goodall orcid.org/0000-0002-0473-5392 Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Discipline of Medicine, The University of Adelaide, Adelaide, SA, Australia School of Molecular and Biomedical Science, The University of Adelaide, Adelaide, SA, Australia Search for more papers by this author Luke A Selth Luke A Selth orcid.org/0000-0002-4686-1418 Dame Roma Mitchell Cancer Research Laboratories, Adelaide Medical School, University of Adelaide, Adelaide, SA, Australia Freemasons Foundation Centre for Men's Health, Adelaide Medical School, University of Adelaide, Adelaide, SA, Australia Search for more papers by this author Gregory J Goodall Corresponding Author Gregory J Goodall [email protected] orcid.org/0000-0003-1294-0692 Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Discipline of Medicine, The University of Adelaide, Adelaide, SA, Australia School of Molecular and Biomedical Science, The University of Adelaide, Adelaide, SA, Australia Search for more papers by this author Philip A Gregory Corresponding Author Philip A Gregory [email protected] orcid.org/0000-0002-0999-0632 Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia Discipline of Medicine, The University of Adelaide, Adelaide, SA, Australia Search for more papers by this author Author Information Katherine A Pillman1,‡, Caroline A Phillips1,‡, Suraya Roslan1,‡, John Toubia1,‡, B Kate Dredge1, Andrew G Bert1, Rachael Lumb1, Daniel P Neumann1, Xiaochun Li1, Simon J Conn1,2, Dawei Liu1, Cameron P Bracken1,3, David M Lawrence1, Nataly Stylianou4, Andreas W Schreiber1, Wayne D Tilley5,6, Brett G Hollier4, Yeesim Khew-Goodall1,3,7, Luke A Selth5,6, Gregory J Goodall *,1,3,7 and Philip A Gregory *,1,3 1Centre for Cancer Biology, University of South Australia and SA Pathology, Adelaide, SA, Australia 2Flinders Centre for Innovation in Cancer, College of Medicine & Public Health, Flinders University, Adelaide, SA, Australia 3Discipline of Medicine, The University of Adelaide, Adelaide, SA, Australia 4Institute of Health and Biomedical Innovation, Australian Prostate Cancer Research Centre - Queensland, Princess Alexandra Hospital, Queensland University of Technology, Brisbane, Qld, Australia 5Dame Roma Mitchell Cancer Research Laboratories, Adelaide Medical School, University of Adelaide, Adelaide, SA, Australia 6Freemasons Foundation Centre for Men's Health, Adelaide Medical School, University of Adelaide, Adelaide, SA, Australia 7School of Molecular and Biomedical Science, The University of Adelaide, Adelaide, SA, Australia ‡These authors contributed equally to this work *Corresponding author. Tel: +61 8 8302 7751; E-mail: [email protected] *Corresponding author. Tel: +61 8 8302 7829; E-mail: [email protected] The EMBO Journal (2018)37:e99016https://doi.org/10.15252/embj.201899016 PDFDownload PDF of article text and main figures. Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info Abstract Members of the miR-200 family are critical gatekeepers of the epithelial state, restraining expression of pro-mesenchymal genes that drive epithelial–mesenchymal transition (EMT) and contribute to metastatic cancer progression. Here, we show that miR-200c and another epithelial-enriched miRNA, miR-375, exert widespread control of alternative splicing in cancer cells by suppressing the RNA-binding protein Quaking (QKI). During EMT, QKI-5 directly binds to and regulates hundreds of alternative splicing targets and exerts pleiotropic effects, such as increasing cell migration and invasion and restraining tumour growth, without appreciably affecting mRNA levels. QKI-5 is both necessary and sufficient to direct EMT-associated alternative splicing changes, and this splicing signature is broadly conserved across many epithelial-derived cancer types. Importantly, several actin cytoskeleton-associated genes are directly targeted by both QKI and miR-200c, revealing coordinated control of alternative splicing and mRNA abundance during EMT. These findings demonstrate the existence of a miR-200/miR-375/QKI axis that impacts cancer-associated epithelial cell plasticity through widespread control of alternative splicing. Synopsis miR-200 and miR-375 regulate the level of the RNA-binding protein, Quaking (QKI), which orchestrates widespread control of alternative splicing during epithelial-mesenchymal transition (EMT), thereby affecting multiple facets of cancer-associated epithelial cell plasticity. miR-200c and miR-375 control EMT-associated alternative splicing by suppressing QKI. QKI-5 influences cell plasticity, invasion and tumour growth by modulating alternative splicing. Actin cytoskeleton-associated genes are targeted both by QKI and miR-200c, revealing coordinated control of alternative splicing and mRNA abundance during EMT. Introduction The ability of cells to reversibly transition between epithelial and mesenchymal states (epithelial-to-mesenchymal transition, EMT) is exploited by tumours to drive malignant progression. EMT is governed by networks of transcriptional and post-transcriptional mechanisms. A reciprocal feedback loop between the miR-200 family and ZEB1/2 transcription factors plays a central role in epithelial cell plasticity (Bracken et al, 2008; Burk et al, 2008; Gregory et al, 2011), and by virtue of its potency functions widely in controlling cell invasiveness, stemness and tumour metastasis (Gibbons et al, 2009; Wellner et al, 2009; Brabletz & Brabletz, 2010). However, in addition to ZEB1/2, miR-200 can regulate many other target genes that contribute to these functions (Bracken et al, 2014, 2016; Perdigao-Henriques et al, 2016), although for most of these interactions the implications for cancer progression are not well understood. Alternative splicing is an additional layer of post-transcriptional control that exhibits widespread changes during EMT and has causal effects on epithelial cell function (Warzecha et al, 2010; Shapiro et al, 2011). The epithelial spliced regulatory proteins (ESRP1 and ESRP2) play prominent roles in maintaining epithelial alternative splicing patterns, and loss of ESRP expression in the mesenchymal state results in alterations to the these patterns (Warzecha et al, 2009; Brown et al, 2011). Several other RNA-binding proteins including RBFOX2, MBNL1/2, RBM47 and Quaking (QKI) have also been reported to directly influence mesenchymal associated alternative splicing (Shapiro et al, 2011; Venables et al, 2013a,b; Braeutigam et al, 2014; Yang et al, 2016); however, the direct contribution of these factors to alternative splicing and the mechanisms controlling their expression during EMT remain largely uncharacterised. We find here that miR-200 exerts a widespread influence on alternative splicing during EMT, through its strong regulation of QKI. QKI is a member of the STAR family of RBPs and has been reported to have diverse functions in mRNA stability (Larocque et al, 2005; Zhao et al, 2006) and translation (Saccomanno et al, 1999; de Bruin et al, 2016b), miRNA processing (Wang et al, 2013, 2017) and alternative splicing (Hall et al, 2013; van der Veer et al, 2013; Zong et al, 2014; de Bruin et al, 2016a; Darbelli et al, 2017; Fagg et al, 2017; Hayakawa-Yano et al, 2017). We have recently shown that QKI can promote circular RNA formation during EMT (Conn et al, 2015), although the functional consequences of QKI in EMT remain unclear. While seeking to identify the miR-200 targets most biologically relevant to cancer progression, we surprisingly found that QKI is one of the most consistent clinical correlates of miR-200 activity. QKI is strongly regulated by miR-200 and miR-375, directly binds to and mediates hundreds of alternative splicing events, and regulates multiple facets of mesenchymal cell plasticity without significantly perturbing gene expression. Our findings implicate alternative splicing as an important regulator of cell plasticity and broaden the network of post-transcriptional changes orchestrated by miR-200. Given the important roles of miR-200, miR-375 and QKI in cell differentiation, we propose this pathway may define transcript selection in a broad range of biological contexts. Results QKI is inversely correlated with miR-200c in cancer To identify miR-200c targets that may be especially relevant to cancer progression, we created a ranking method that merges microRNA–mRNA correlations from cancer and cell line data sets, EMT data sets and Ago-HITS-CLIP data (Figs 1A and EV1A). The first and third highest ranked genes were ZEB1 and ZEB2, but surprisingly, the second highest ranked gene was the RNA-binding protein QKI (Fig 1B), which has not been described to be a target of miR-200, but was recently shown to regulate circRNA production in human mammary epithelial cells (HMLE) that have undergone EMT (Conn et al, 2015). To assess whether the negative correlation holds at the protein level, we measured QKI protein in a panel of breast cancer cell lines, which showed an even stronger negative correlation with miR-200c (Fig 1C). Figure 1. Quaking is a direct target and inversely correlates with miR-200c and miR-375 in cancer A. Flow chart of pipeline used to discover miR-200c targets relevant to cancer. B. Comparison of the top 20 miR-200c targets in listed experimental and clinical data sets ranked in order of consistency. An "X" in experimental data sets indicates evidence of miR-200 targeting. For clinical data sets (Liu et al, 2010; Taylor et al, 2010; Enerly et al, 2011), Pearson correlation coefficients between miR-200c and target genes are shown with significant values indicated in red. C. Relative expression of QKI, E-cadherin and miRNAs in a human breast cancer panel of epithelial and mesenchymal cell lines. D–F. Relative expression of QKI in tumour subtypes of the University of North Carolina 779 breast cancer set (Harrell et al, 2012), Gleason grades of the TCGA prostate cancers, and primary (P) versus metastases (M) from prostate cancer data sets listed by the first author (Lapointe et al, 2004; Varambally et al, 2005; Chandran et al, 2007; Tamura et al, 2007; Taylor et al, 2010; Grasso et al, 2012) shown as box-and-whisker plots. Box limits represent the 25th–75th percentiles with a median central line. For (D) and (E), whiskers extend to the minimum and maximum values with all data points shown. For (F), whiskers represent the 10th–90th percentiles. Expression differences were assessed by two-sample equal variance t-tests ***P < 0.001, **P < 0.01, *P < 0.05. G, H. Recurrence scores of the top 20 target genes from (B), and the top 20 miRNAs that inversely correlate with QKI in the panTCGA cancer data set as calculated using CancerMiner (Jacobsen et al, 2013). Asterisks refer to minor form mature miRNA derived from the pre-miRNA (in this case miR-7-1-3p, miR-200b-5p and miR-200c-5p). Source data are available online for this figure. Source Data for Figure 1 [embj201899016-sup-0012-SDataFig1.pdf] Download figure Download PowerPoint Click here to expand this figure. Figure EV1. QKI expression in clinical data sets Scatterplot of QKI versus miR-200c expression in cancer data sets with Pearson correlation coefficients and associated P-values indicated. Kaplan–Meier survival analysis showing distant metastasis-free survival (DMFS) from breast cancer in unsegregated combined cohort data from KM plotter (Gyorffy et al, 2010) and the Hatzis et al (GSE25066) (Hatzis et al, 2011) data sets. Hazard ratios (HR) and P-values are indicated. Relative expression of QKI in tumour subtypes of the TCGA breast cancer data set displayed as a minimum-to-maximum box-and-whisker plot. Box limits represent the 25th–75th percentiles with a median central line. Whiskers extend to the minimum and maximum values with all data points shown. Significance between each subtype was calculated by two-tailed unpaired t-tests. Relative expression of QKI in prostate cancers exhibiting biochemical recurrence compared with non-recurrence in the TCGA prostate cancer data set displayed as a minimum-to-maximum box-and-whisker plot. Significance was calculated by a two-tailed unpaired t-test. Scatterplot of QKI versus miR-375 expression in cancer data sets with Pearson correlation coefficients and associated P-values indicated. Download figure Download PowerPoint Examination of QKI expression in breast cancer cohorts showed it was upregulated in basal-like and claudin-low subtypes, which display enhanced EMT-like features, and is indicative of poor distant metastasis-free survival (Figs 1D and EV1B and C). Moreover, in prostate cancer, QKI was elevated with increasing Gleason grade, in recurrent prostate cancers, and in metastases in several cohorts (Figs 1E and F, and EV1D). These data are consistent with QKI-mediating properties that promote tumour progression, such as cell migration and invasion, which are potently repressed by the miR-200 family (Bracken et al, 2014). To assess whether the miR-200c–QKI inverse relationship is observed more broadly across other cancers, we examined the pan TCGA panel, which demonstrated QKI displays a strong negative recurrence score with miR-200c across the 10 represented tumour types (Fig 1G). Furthermore, when we examined all miRNAs for an inverse relationship with QKI across the 10 cancer types, we found the miRNAs with strongest negative recurrence with QKI are the members of the miR-200 family, along with miR-7 and miR-375 (Fig 1H). Together, these data demonstrate a consistent relationship between miR-200c and QKI in diverse experimental and clinical data sets, suggesting miR-200c may directly target QKI, with consequences for cancer progression. QKI-5 is directly targeted by miR-200c and miR-375 The QKI locus encodes three major isoforms, QKI-5, QKI-6, and QKI-7, named as such because the mRNAs were estimated to be 5, 6 and 7 kb, respectively (Ebersole et al, 1996). These isoforms differ in their carboxyl-termini and their 3′UTRs, but the 3′UTR polyadenylation sites were poorly characterised, with their RefSeq entries being discordant with the published sizes of the mRNAs. Consequently, to enable assessment of whether the negative correlation between miR-200c and QKI was due to direct regulation of QKI by miR-200c, we first characterised the 3′UTRs of each major isoform, using short- and long-read RNA-seq, and by RT–PCR using specific reverse transcription primers tiled across the annotated 3′UTRs (Fig EV2). This analysis showed that QKI-6 and QKI-7 have a similar 3′UTR, differentiated only by an additional segment at the beginning of the QKI-7 3′UTR, whereas QKI-5 has a completely distinct 3′UTR of 2.3 kb in length. Isoform-specific qRT–PCR showed that QKI-5 mRNA is expressed at a much higher level than QKI-6 and QKI-7 in breast cancer and TGF-β-treated mammary epithelial cells (Fig EV3A–D), and immunoblotting confirmed QKI-5 protein is much more abundant than the other isoforms (Fig 2A). The QKI-5 3′UTR has two predicted 8-mer binding sites for miR-200b/c that correspond to miR-200b peaks in our previous HITS-CLIP analysis of miR-200 binding sites (Bracken et al, 2014). In addition, we noticed the QKI-5 3′UTR also has multiple potential 7-mer sites for miR-375, which the association analysis had indicated is negatively correlated with QKI in multiple cancer types (Figs 1H and EV1E). Click here to expand this figure. Figure EV2. Mapping of the QKI locus 3′UTRs The full QKI gene locus is shown in the upper panel, with the divergent C-terminal end and 3′UTRs for each isoform magnified below. Track names for each major isoform are indicated. Annotation of a full-length read from a PacBio IsoSeq experiment (Pacific Biosciences), and sequencing coverage reads from in-house HMLE, mesHMLE and MDA-MB-231 cells are shown, which terminate in close proximity to the decline of high sequence conservation. Putative locations of polyA signal sequences, miR-200b/c (8mer) and miR-375 (7mer-1A) sites are shown. The locations of miR-200b HITS-CLIP peaks (Bracken et al, 2014) and RT primers used for priming cDNA synthesis are indicated. QKI-5, QKI-6 or QKI-7 isoform PCR on cDNA synthesised using the specific RT primers numbered in (A) using MDA-MB-231 and mesHMLE RNA. Location of functional miR-200c and miR-375 binding sites showing their cross-species conservation. The red box indicates the miRNA binding site complementary to the seed sequence. Source data are available online for this figure. Download figure Download PowerPoint Click here to expand this figure. Figure EV3. Expression and function of QKI in cancer cell lines A–D. Quantitative PCR showing QKI-5, QKI-6 and QKI-7 or total QKI levels (panQKI) across the EMT timecourses and breast cancer cell lines described in Fig 2. E. Heat map of microarray data showing a subset of EMT genes following transfection of MDA-MB-231 cells with miR-200c, QKI-5 siRNA or negative controls. F. Invasion assay following QKI-5-specific siRNA knockdown or miR-200c transfection in SH-EP cells. Experiments were performed with three biological replicates and are shown as mean ± SEM. Significance was measured by two-tailed unpaired t-tests. *P < 0.05 and **P < 0.01. Download figure Download PowerPoint Figure 2. Quaking is directly targeted and repressed by miR-200c and miR-375 Real-time PCR and Western blot of total QKI (panQKI) and individual QKI isoforms following transfection of MDA-MB-231 and TGF-β-treated mammary epithelial cells (mesHMLE) with miRNA precursors (Pre-miRs). Schematic of the luciferase QKI-5 3′UTR reporter constructs indicating the miR-200c and miR-375 binding sites (top) and reporter assays of indicated QKI-5 3′UTR constructs with co-transfection of Pre-miRs into MDA-MB-231 cells (bottom). Constructs with mutations in the miR-375 or miR-200c sites are suffixed with "m". Data are represented as mean ± SD (n = 3). Significance was measured by two-tailed unpaired t-tests. *P < 0.05 and ***P < 0.001. Source data are available online for this figure. Source Data for Figure 2 [embj201899016-sup-0013-SDataFig2.pdf] Download figure Download PowerPoint To verify that miR-200c and miR-375 regulate QKI levels, we examined the effect of overexpression of these miRNAs on QKI mRNA and protein, and on luciferase reporters bearing the QKI-5 3′UTR (Fig 2). Overexpression of miR-200c and miR-375 each reduced the level of QKI-5 and QKI-6 mRNAs and decreased all three QKI isoform proteins (Fig 2A). In contrast, miR-141, which differs from miR-200c by one nucleotide in its seed region, did not reduce QKI levels. Since QKI-5 is the major isoform in the breast cancer cells, we used the QKI-5 3′UTR to test for direct miRNA targeting. Both miR-200c and miR-375, but not miR-141, strongly repressed the full-length QKI-5 3′UTR reporter, replicating their effects on QKI expression (Fig 2B). Analysing the QKI-5 3′UTR proximal and distal regions in isolation revealed direct targeting of the distal region by the conserved miR-200c sites and the proximal region by two miR-375 sites, with repression of each abrogated by mutation of these sites (Fig 2B). These data demonstrate that miR-200c and miR-375 directly target the major QKI isoform by binding its 3′UTR and also directly or indirectly reduce the levels of the QKI-6 and QKI-7 isoforms. QKI-5 is dynamically regulated during EMT Having confirmed QKI is regulated by miR-200 and miR-375, we assessed whether the expression of QKI is physiologically regulated during EMT, and in a reciprocal manner to these miRNAs. Consistent with its reciprocal relationship with miR-200 and miR-375 in cancer, QKI expression increased during TGF-β-induced EMT of human breast and canine kidney epithelial cells (Fig 3A) and during ZEB1-induced EMT of LNCaP human prostate cancer cells (Fig 3B). In each of these systems, QKI-5 protein was more responsive to the changes in miR-200c and miR-375 than was QKI-5 mRNA, consistent with the stronger effect on protein seen in Fig 2A. Examining this further, we observed that short-term inhibition of miR-200c or miR-375 increased QKI-5 protein in a dose-dependent manner with little effect on QKI-5 mRNA, suggesting these miRNAs especially affect translation of the QKI-5 mRNA (Fig 3C). Together, these findings show QKI-5 is robustly and dynamically regulated as cells transition between epithelial and mesenchymal states in a manner consistent with its control by miR-200 and miR-375. Figure 3. Quaking is dynamically regulated during EMT/MET and is translationally repressed by miR-200c and miR-375 Epithelial cell lines were treated with TGF-β for the indicated time periods. Changes in expression of proteins were measured by Western blot, miR-200c by qPCR, with relative changes in QKI-5 mRNA and protein represented in graphs
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