CLK2 Is an Oncogenic Kinase and Splicing Regulator in Breast Cancer

Author Manuscript Published OnlineFirst on February 10, 2015; DOI: 10.1158/0008-5472.CAN-14-2443 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

Title: CLK2 is an oncogenic kinase and splicing regulator in breast cancer

Authors: Taku Yoshida1,2,3,13, Jee Hyun Kim1,2,3,4, Kristopher Carver1,2,3,14, Ying Su1,2,3, Stanislawa

Weremowicz5,6, Laura Mulvey1,15, Shoji Yamamoto1,2,16, Cameron Brennan7, Shenglin Mei8,9, Henry

Long8, Jun Yao1,2,3,10, Kornelia Polyak1,2,3,7,11,12

Authors’ Affiliations: 1Department of Medical Oncology, and 8Center for Functional Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts, USA. Department of 2Medicine and 4Pathology, Harvard Medical School, Boston, Massachusetts, USA. Department of 3Medicine and 5Pathology, Brigham and Women’s Hospital, Boston, Massachusetts, USA. 4Seoul National University College of Medicine, Seoul, Korea. 7Memorial Sloan-Kettering Cancer Center, New York, New York, USA. 9Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai, China. 10MD Anderson Cancer Center, Houston, TX. 11Harvard Stem Cell Institute, Cambridge, Massachusetts, USA. 12Broad Institute, Cambridge, Massachusetts, USA.

13Present address: Eisai Co., Ltd., Tokyo, Japan. 14Present address: Boston Scientific, St. Paul, MN 55112, USA 15Present address: Maimonides Medical Center, Brooklyn, NY 11219, USA 16Present address: Daiichi Sankyo Co., Ltd., Tokyo, Japan

Running Title: CLK2 as a therapeutic target in breast cancer

Keywords: breast cancer, splicing, epithelial to mesenchymal transition

List of abbreviations: SNP – Single Nucleotide Polymorphism, FISH – fluorescence in situ hybridization, BAC – bacterial artificial chromosome, CEP – centromeric probe, TNBC – Triple Negative Breast Cancer

Notes: Financial support: This work was supported by the Susan G. Komen Foundation and the Tisch Family Fund (to K. Polyak).

Corresponding author: Kornelia Polyak, Dana-Farber Cancer Institute, 450 Brookline Ave. D740C,

Boston, MA 02215. Phone: 617-632-2106; Fax: 617-582-8490; E-mail:

[email protected]

Potential conflicts of interest: No potential conflicts of interest were disclosed.

ABSTRACT

Genetically activated kinases have been attractive therapeutic targets in cancer due to the

relative ease of developing tumor-specific treatment strategies for them. To discover novel

putative oncogenic kinases, we identified 26 genes commonly amplified and overexpressed in

breast cancer and subjected them to a lentiviral shRNA cell viability screen in a panel of breast cancer cell lines. Here we report that CLK2, a kinase that phosphorylates SR proteins

involved in splicing, acts as an oncogene in breast cancer. Deregulated alternative splicing

patterns are commonly observed in human cancers but the underlying mechanisms and

functional relevance are still largely unknown. CLK2 is amplified and overexpressed in a

significant fraction of breast tumors. Downregulation of CLK2 inhibits breast cancer growth in

cell culture and in xenograft models and it enhances cell migration and invasion. Loss of

CLK2 in luminal breast cancer cells leads to the upregulation of epithelial to mesenchymal

transition (EMT) related genes and a switch to mesenchymal splice variants of several genes

including ENAH (MENA). These results imply that therapeutic targeting of CLK2 may be used

to modulate epithelial-mesenchymal splicing patterns and to inhibit breast tumor growth.

Precis: CLK2 is an oncogenic kinase in breast cancer that appears to regulate luminal and basal

cellular phenotypes via its effect on alternative splicing patterns.

INTRODUCTION

Breast cancer is the second most commonly diagnosed cancer and is the main cause of cancer- related mortality in women worldwide (1). Breast tumors are highly heterogeneous and are classified based on the expression of estrogen and progesterone receptors and HER2 into ER+, HER2+, and

ER-PR-HER2- (triple negative breast cancer, TNBC) disease. Based on gene expression profiles, breast tumors are characterized as luminal or basal (2-4). HER2+ and ER+ tumors typically have luminal features whereas TNBCs show significant but not complete overlap with basal-like subtype.

The categorization of breast tumors based on hormone receptor and HER2 status and the use of endocrine and HER2-targeted therapy, respectively, are some of the first examples of a molecular- based classification and personalized cancer treatment leading to a meaningful improvement in cancer clinical outcomes (5-9). Unfortunately, therapeutic resistance is common and a significant fraction of patients is inherently resistant to treatment or acquires resistance during disease progression (10).

The successful development of effective cancer therapies requires the identification of druggable disease-specific molecular pathways, the targeting of which leads to therapeutic response, and the choice of appropriate patient populations likely to realize clinical benefit from the therapeutic intervention. An elusive goal in oncology has been to improve the identification of such targets and patient populations prior to empirical clinical testing. Since cancer is a genetic disease, the identification of genetic alterations playing a pivotal role in tumor initiation and progression has been key towards achieving this goal. Therapeutic inhibition of oncogenic protein kinases has been one of the most successful forms of targeted therapies as demonstrated by the treatment of BCR-ABL mutant CML with imatinib and EGFR-mutant lung cancers with erlotinib.

In the past decade, systematic sequencing of putative therapeutic targets (e.g., kinases) has revealed several previously unknown but frequently mutated genes (e.g., PIK3CA) in breast and other cancer types (11). However, subsequent large scale sequencing of breast cancer genomes in the past few years has somewhat disappointed initial expectations and identified relatively few recurrent 3

mutations that could be explored for therapy (12, 13). This is especially the case in TNBCs where,

aside from the already known cancer genes TP53, PTEN, and PIK3CA, very few new genetic alterations were found (14-18). In addition, most of the mutations were detected only in a subset of tumors and at a low frequency, making it difficult to determine if they are true drivers of tumorigenesis or just happen to be there as “passengers”. Here we describe the identification of amplified kinases required for breast cancer cell growth using functional genomics and the further characterization of

CLK2 in breast cancer.

MATERIALS AND METHODS

Cell culture

Breast cancer cell lines were purchased from the American Type Culture Collection or provided by

Dr. S. Ethier, University of Michigan (SUM series) and Dr. Fred Miller, Karmanos Cancer Institute

(MCF10DCIS.com cells). All cell lines were cultured in the medium recommended by the provider at

37°C with 5% CO2. The identity of the cell lines was verified based on SNP array data. 3D Matrigel on

top cultures were performed as previously described (19). Briefly, 96 well plates were coated with

Matrigel (BD Biosciences) and allowed to solidify for 15-30 min at 37°C followed by plating 1 x 104 cells/well. Following the attachment of cells to the Matrigel coating, 10% Matrigel containing medium was added and maintained with medium changes in every 2-3 days. Cell viability was determined using CellTiter-Glo (Promega) eight days after shRNA infection. For colony formation assays, 96-well plates were coated with 0.66% agarose gel, layered with 0.33 % agarose gel containing cells, and topped with medium. Colonies were stained by MTT for imaging and counting as performed using

GelCountTM (OXFORD OPTRONIX).

siRNAs, shRNA plasmids and lentivirus production

siGENOME SMARTpool for negative control, CLK2, RBFOX2, and SF2/ASF were purchased from

Thermo Scientific. pLKO shRNA vectors for control GFP (clone 437) and CLK2 (clones 572, 1640,

1870, and 1969) were obtained from the Broad Institute RNAi consortium (TRC). To express

doxycycline-inducible shRNAs, annealed oligos (LacZ: 5’-CGCGATCGTAATCACCCGAGT-3’, CLK2:

5’-CTATCGGCATTCCTATGAATA-3’) were cloned into pLKO-tet-on lentiviral vector (kindly provided

by Dr. Alex Toker, Beth-Israel Deaconess Medical Center, Boston, MA). For expression of CLK2, full- length cDNA was inserted into pLenti6.3 lentiviral vector (Life Technologies) using Gateway recombination reaction (Life Technologies). To produce lentiviral supernatants, HEK293T cells were co-transfected with shRNA vectors, VSVG, and pDG8.91 using Fugene 6 (Roche). The targeting cells were infected with the viral supernatant containing 8 µg/ml polybrene, followed by spin for 30 minutes 5

at 2,250 rpm. Forty-eight hours post-infection, the target cells were exposed to puromycin (2 µg/ml) to

select for infected cells.

Fluorescence in situ hybridization (FISH)

Bacterial artificial chromosome (BAC) clones corresponding to the amplified kinases were obtained

from Life Technologies (Supplementary Table S1). BAC DNA probes were labeled with digoxigenin

(Roche, Indianapolis, IN) and biotin using reagents from the BioNick labeling kit (Life Technologies,

Carlsbad, CA). The hybridization signals were detected using reagents supplied by Cytocell

Technologies, Ltd. as previously described (20). Metaphase chromosome spreads and FISH were performed essentially as described (21). Images were captured using CytoVysion Imaging System

(Applied Imaging Pittsburgh, PA).

SNP array data analysis and shRNA screen

SNP array data (22) was analyzed to define ARI (Aberration Amplitude and Recurrence Index) and

AFI (Aberration Focality Index) scores essentially as described (23). ARI is a measure of the copy

number gain and the recurrence of such copy numbers across the samples. AFI weights the focality

of the observed copy number changes. Lentiviral shRNA screen was conducted as previously

described (24). Briefly, for primary screen, 11 breast cancer cell lines were infected with lentiviral

shRNAs against the 26 kinases. Infected cells were selected by puromycin, and cultured for 6 days,

followed by cell viability assay using CellTiter-Glo (Promega). To identify hits, Z-score representing

the effect on cell viability was calculated by normalizing the viability score of each well to the plate

mean viability score and standard deviation (SD) of plate viability score:(X-µ)/σ (X=assay value,

µ=mean plate viability score, σ=Standard deviation of plate viability score). Hits showing the lowest

10% of average of Z-score were selected for secondary screening. In secondary shRNA screen,

shRNAs for the 10 selected genes were assayed in 17 breast cancer and 2 immortalized mammary

epithelial cell lines. Hits were identified using ≥ 30% decrease in cell viability compared to control

shRNAs on day 6 after infection.

Cell proliferation, apoptosis, and cell cycle assay

To determine viable cell numbers trypan blue negative cells were counted at days 0, 3, 6, and 9 after

infection. Cells were assayed 4 days after virus infection for apoptosis using Apo-ONE Homogeneous

Caspase-3/7 Assay (Promega) and cell cycle analysis. Cell cycle analysis was performed as follows;

cells were harvested, washed in PBS, and fixed in ice cold 70% ethanol for 1 hr. Fixed cells were re-

suspended in a solution containing 100 μg/ml RNase, 40 μg/ml propidium iodide (Sigma), and incubated for 30 minutes on ice. Finally the cells were suspended in 20 μg/ml PI solution. The DNA

content of 10,000 cells was determined with FACScan (BD Biosciences).

Cell migration and invasion assays

Cell migration assay and invasion assays were performed as described (25). Briefly, cells (5 x 103 and 2.5 x 103) were seeded onto upper chambers of BioCoat Control and Matrigel invasion chambers

(8.0 um pore size, BD Bioscience), respectively. Top chambers (culture inserts) were filled with

serum-free medium, and bottom chambers were filled with medium containing 20% fetal bovine

serum (FBS) as chemoattractant. The number of cells that migrated or invaded to bottom surfaces of

the membranes was counted after 24 hours of incubation followed by staining with Giemsa solution.

RT and qRT-PCR analysis

Total RNA from cultured cells or tumor specimens was prepared using RNeasy Mini kit (Qiagen).

Reverse transcription was carried out using Super Script II Reverse Transcriptase (Life

Technologies). For RT-PCR, synthesized cDNA was amplified and run in 2% agarose gel. For qRT-

PCR, the quantities of DNA amplified with SYBRgreen PCR master mix or TanMan PCR master mix

(Applied Biosystems) were measured by ABI7500 or ABI7900, respectively (Applied Biosystems). 7

Assessment of changes in gene expression was conducted by comparison of delta delta Ct values for

each sample. Primer sequences used in RT PCR are as follows: GAPDH:5’-

GGYCGTATTGGSCGCCTGGTCACC-3’(Forward), 5’-GAGGGGCCATCCACAGTCTTCT-

3’(Reverse), ENAH:5’-TGCTGGCCAGGAGGAGAAGAAT-3’(Forward), 5’-

ACTGGGCTGTGATAAGGGTGTGG-3’ (Reverse). The primers of CDH1, CDH2, VIM, SNAI1, SNAI2,

ZEB1, TWIST1, and FN1 used for qRT-PCR were designed as previously described (20). The primer sequences of GAPDH and CLK2 for qRT-PCR were as follows: GAPDH:5’-

CGAGATCCCTCCAAAATCAA-3’ (Forward), 5’- GTCTTCTGGGTGGCAGTG AT-3’ (Reverse).

CLK2:5’-AATATTTTTACCGGGGTCGC-3’ (forward), 5’-AGCCGCTTAGCTGGTTCATA-3’ (Reverse).

TaqMan probes used are GAPDH (Hs99999905_m1), CLK2 (Hs00241874_m1), ESRP1

(Hs00214472_m1), ESRP2 (Hs00227840_m1), RBFOX1 (Hs01125659_m1), RBFOX2

(Hs00204814_m1), and RBFOX3 (Hs01370653_m1).

Immuno blotting, immunoprecipitation, and immunohistochemical analyses

Cells were lysed in RIPA Buffer with Halt protease inhibitor Cocktail (Thermo Scientific). Lysates

mixed with sample buffer were separated by electrophoresis on Novex 4-20% gels and transferred to

membranes. Membranes were blocked with 5% skim milk in TBST, followed by incubations with

primary antibodies. After washing with TBS-0.05% Tween, membranes were incubated with HRP-

conjugated anti-mouse or anti-rabbit IgG, and visualized with Immobilon western detection reagent

(Millipore). Signals were analyzed and quantified using NIH image software. Anti-CLK2 (cat#

(ab65082), RBFOX2 (cat# ab51361), and SRSF1 (cat# ab38017) polyclonal antibodies were

purchased from Abcam. Anti-phospho-SR protein monoclonal antibody (1H4, cat# MABE50) was

purchased from Millipore. Anti-β-actin monoclonal antibody was purchased from Sigma-Aldrich

(cat#A2228). For immunoprecipitation assays, cell lysates were incubated with anti-CLK2 antibody

(AP7530, ABGENT) overnight followed by incubation with protein G beads (Life Technologies) for 2

hr. Immunoprecipitates were applied for immunoblot analysis and membranes were incubated with 8

anti-phospho-serine (4A4, Millipore) or anti-CLK2 antibodies. Signal was visualized with Immobilon

western detection reagent. Immunohistochemical analyses for SMA, Ki67, and TUNEL assay were

performed as recently described (26).

Mouse xenograft assays

Female NCRNU-F mice (6 weeks old) were purchased from Taconic and maintained in pathogen-free

conditions. Mice were injected subcutaneously with 1 x 105 MCF10DCIS.com cells in media with 50%

Matrigel. Control and treatment groups received water supplemented with 2% sucrose in the absence

or presence of 1mg/ml doxycycline. All animal procedures were approved by the Institutional Animal

Care and Use Committee of the Dana-Faber Cancer Institute under protocol #11-023.

RNA-seq and splicing analysis

MCF7 cells were infected with lentiviruses expressing shGFP or shCLK2 and subject to four days of puromycin selection. Total RNA was isolated using RNeasy mini kit (Qiagen), and applied for µMACS mRNA isolation kit (Miltenyi). RNA-seq libraries were prepared using mRNA Sequencing Sample

Preparation Kit (Illumina) with slight modifications. The sequencing library was enriched with 18 cycles of PCR reaction and size-fractionated into 250-400 bp by running on a polyacrylamide gel.

After validation on 2100 Bioanalyzer (Agilent Technologies), samples were subject to 50 bp pair-end sequencing on Hi-seq 2000 (Illumina). Sequence reads were aligned to human reference genome

(hg19) using TopHat software (27). The mapping results were visualized using the Integrative

Genomics Viewer (IGV) genome browser (28). Differentially spliced genes between the basal and luminal A subtype breast cancers were identified using level 3 data from TCGA BRCA dataset

(downloaded from https://tcga-data.nci.nih.gov/tcga/dataAccessMatrix.htm) using a previous described method (29).

RESULTS

Novel amplified kinases required for breast cancer growth

In search of novel oncogenic kinases in breast cancer, we identified 52 genes encoding for protein kinases with common copy number gain based on SNP (Single Nucleotide Polymorphism) array analysis of breast tumors and breast cancer cell lines (22) (Figures 1A, S1A, and Table S1), which we also confirmed by FISH and qPCR for selected genes (Figure 1B and Tables S2,S3). We also analyzed the expression of the most commonly amplified genes in breast tumors and breast cancer cell lines by qRT-PCR (Tables S2, S3). We selected 26 genes that have not been extensively characterized in breast cancer for follow up functional studies due to their frequency and amplitude of copy number gain and overexpression.

To determine whether the amplification and overexpression of these 26 kinases reflect potential oncogenic functions in breast cancer, we performed a targeted lentiviral shRNA screen using cellular viability as end point. The shRNA screen was performed in two phases. In the primary screen we tested all 26 genes (4-5 shRNAs each) in 11 breast cancer lines of different subtypes and defined shRNA hits showing the lowest 10% of average of Z-score representing their effects on cellular viability (Figure 2A). The top ten hits in the primary screen were subject to a secondary screen on an extended panel of 17 breast cancer lines of different subtypes and two immortalized mammary epithelial lines (Figure 2B). In the secondary screen, we considered shRNAs to have

“scored” in a cell line if they decreased viability by ≥ 30% compared to control (after averaging effects with and without puromycin). RIGER analysis (30) of the shRNA data to assess potential tumor subtype-specificity of the hits revealed the preferential requirement for CLK2 in luminal and RIOK2 and AKT3 in basal cell lines. We selected CLK2 for further study due to its high frequency of amplification and overexpression in breast cancer and because it is a relatively poorly characterized kinase.

Expression of CLK2 in breast cancer 10

To investigate the potential role of CLK2 in breast cancer cell growth, we first analyzed its expression

in a panel of breast cancer cell lines by qRT-PCR and immunoblot assays. We found that CLK2

mRNA and protein levels were in general higher in luminal and HER2+ cell lines although the EGFR

amplified MDA-MB-468 and EGF-dependent MCF10DCIS TNBC cell lines also expressed fairly high

levels (Figure 3A-C). Analysis of CLK2 immunoprecipitates by phospho-serine immune blot showed

slightly higher phospho-CLK2 levels in luminal cell lines (Figure 3D). In the TCGA breast cancer

dataset (31), we found a good correlation between CLK2 gene copy number and mRNA levels

(Figure S1B). We also analyzed CLK2 protein levels based on TCGA RPPA (reverse phase protein array) data and categorized tumors into CLK2 low, intermediate, and high classes (Figure S1C). To explore signaling pathways that may be differentially activated depending on CLK2 protein levels, we identified 21 proteins that showed significant differences between CLK2-low and CLK2-high tumors

(Figure S1D). Tumors with high CLK2 expression seem to be more proliferative based on high levels of cyclin B1, CDK1, phospho-Rb, and also display activation of the hippo signaling pathway reflected by high YAP/TAZ levels. Lastly, we explored potential associations between CLK2 expression and clinical outcome in breast cancer by comparing the survival of patients with CLK2-low and CLK2 high tumors. Although there was a trend for shorter survival associated with high CLK2 protein levels, this did not reach significance (Figure S1E) possibly due to relatively small cohort size.

CLK2 regulates breast cancer cell growth and morphology

To validate our shRNA screen results, we first confirmed the efficacy and specificity of the CLK2- targeting shRNAs by immunoblot analyses and by rescue experiments using a shRNA-resistant CLK2 expression construct (Figure S2A-C). Next, we assessed the proliferation of MCF7 and T-47D luminal breast cancer cell lines following the downregulation of CLK2 by counting viable cell numbers (short- term effect) and performing colony growth assays (long-term effects). Downregulation of CLK2 by two different shRNAs significantly suppressed the growth of both cell lines that was accompanied by a slight increase in apoptosis and arrest in the G1 phase of the cell cycle (Figures 3E-F and S2D-E). 11

Interestingly overexpression of CLK2 in MCF7 cells also decreased cell proliferation (data not shown) implying the requirement for tightly controlled CLK2 levels for optimal breast cancer cell growth.

During the cell proliferation assays we noticed that the morphology of shCLK2-infected MCF7 cells became noticeably more fibroblastoid implying potential epithelial to mesenchymal transition

(EMT) (Figure S3A). To test this hypothesis, we analyzed the migration and invasion of MCF7 cells and found that downregulation of CLK2 significantly increased both cell migration and invasion

(Figures 3G-H). Similar results were obtained in T-47D, BT-474, and MCF10DCIS breast cancer cells as well (Figure S3B and data not shown).

To analyze the effect of CLK2 downregulation on breast cancer cell proliferation and invasive behavior in more physiologic growth conditions, we assessed the growth of MCF10DCIS cells infected with control or CLK2-targeting shRNAs in 3D matrigel cultures. Downregulation of CLK2 significantly decreased both the number and size of MCF10DCIS spheroids in these conditions, but did not make them more invasive (Figures 4A-B).

Lastly, we analyzed the role of CLK2 in breast tumorigenesis in xenograft assays using

MCF10DCIS cells. MCF10DCIS cells form tumors that resemble human DCIS (ductal carcinoma in situ) that spontaneously progress to invasive tumors with time (32, 33). Thus, the use of this cell line allowed us to explore the potential role for CLK2 in breast tumor growth and invasive progression.

Downregulation of CLK2 on day 1 or day 14 after injection using doxycycline-inducible shRNAs significantly decreased the growth of MCF10DCIS xenografts (Figures 4C-D). Analysis of xenograft histology and the expression of smooth muscle actin (SMA), a myoepithelial cell marker, revealed that shCLK2-expressing tumors maintained DCIS histology even at time points when the control tumors have already lost the myoepithelial cell layer and were all invasive (Figure 4E). The apparent delay of invasive progression by downregulation of CLK2 may be in part due to the slower growth of shCLK2-expressing xenografts as demonstrated by lower Ki67 index (Figure 4E) and also potentially due to the upregulation of EMT-related signaling pathways following CLK2 loss that promote the differentiation of myoepithelial cells (33). Correlating with this, a higher fraction of cells were vimentin 12

positive and E-cadherin negative in shCLK2 expressing xenografts (Figure 4E), although the differences in histology and the known luminal (E-cadherin) and myoepithelial (vimentin) cell type- specificity of these markers confound the interpretation of these results.

CLK2-mediated changes in gene expression and splicing patterns

To explore the molecular basis of CLK2 loss-induced changes in cell growth and morphology, we analyzed the gene expression profiles of MCF7 cells by RNA-seq four days after infection with lentiviruses expressing control and CLK2-targeting shRNAs. Downregulation of CLK2 lead to significant changes in the expression of many genes; almost 4,000 transcripts had significantly (Gfold

≥2) (34) increased or decreased levels in shCLK2-expressing cells implying global reprogramming of the transcriptome (Table S4). Many of the most significantly downregulated genes encode for proteins with known roles in epithelial cell differentiation such as SPRR1A, SPRR1B, S100A7,

S100A9. In contrast, many genes upregulated after CLK2 loss encode for extracellular matrix (ECM) related proteins and proteases including ADAM2, TIMP3, and KLK11. Analysis of the gene expression data for pathway and network enrichment using the Metacore suit (35) revealed the activation of EMT and TGFβ signaling pathways following downregulation of CLK2 (Table S5). To confirm the induction of EMT following CLK2 loss, we analyzed the expression of known EMT regulators by qRT-PCR in MCF7, T-47D, MCF10DCIS, and BT-474 breast cancer cell lines. We found significant upregulation of VIM (vimentin) after shCLK2 in all luminal cell lines tested whereas the EMT-inducing transcription factors such as SNAI1, SNAI2, TWIST1, and ZEB1 were upregulated at variable levels (Figures 5A and S3C-D, and data not shown)

One of the few known substrates of CLK2 is the SRSF1 protein that plays key roles in splicing

(36). Phosphorylation of SRSF1 is required for nuclear localization and thus, for its splicing functions

(37). To investigate whether downregulation of CLK2 may modulate SRSF1 and via this potentially influence splicing, we first analyzed the expression and phosphorylation of SRSF1 in MCF7 cells

expressing control or CLK2-targeting siRNAs. Downregulation of CLK2 did not affect overall SRSF1

protein levels, but it significantly decreased its phosphorylation (Figure 5B).

Next, we explored potential changes in alternative splicing patterns in our RNA-seq data. We

processed RNA-seq results after tophat and cuffdiff runs and focused on the top 275 genes with more

than 30% change in splice variants (Table S6). Interestingly, ENAH (MENA), a gene implicated in

breast tumor invasion and metastasis (38, 39), was one of the genes that showed the most significant

changes in splice variants in shCLK2 expressing cells. Exon 11a of ENAH is subject to alternative

splicing in a cell type and epithelial differentiation state-dependent manner: it is included in the ENAH

transcript in luminal but not in basal cells (40). Our RNA-seq data suggested that the levels of the

longer ENAH transcript that includes exon11a are decreased after downregulation of CLK2 (Figure

5C). We confirmed this change by RT-PCR (Figures 5D and S3E) and also verified that luminal

(including HER2+) breast cancer cell lines expressed the longer, exon11a-containing transcripts, whereas basal ones did not with the exception of MCF10DCIS cells that expressed both variants at about the same levels (Figure 5E). Interestingly, no alteration of ENAH splice variant was observed following downregulation of SRSF1, suggesting that regulation of ENAH splicing might be via other substrates of CLK2 or via indirect mechanisms (Figure 5D). The splicing of ENAH has been shown to be regulated by ESRP1/2 proteins (41-44) and RBFOX family members (45, 46). We investigated whether the expression of these genes may be affected by CLK2 expression. Based on our RNA-seq data we found that ESRP1/2 are not differentially expressed in MCF7 cells expressing control and

CLK2-targeting shRNAs, whereas the expression of RBFOX family members was very low in MCF7 cells; consistent with their lower expression in luminal compared to mesenchymal cells (45, 46). We have also performed qRT-PCR and western blot analysis of these proteins in MCF7 cells after CLK2 downregulation and found that the expression of RBFOX2 was ~50% decreased after CLK2 knock down (Figure 5F-G). Subsequently we tested whether downregulation of RBFOX2 may influence the expression of CLK2 and ENAH splice variants. We found no effect on CLK2 mRNA levels after

RBFOX2 downregulation whereas ENAH splicing switched to the basal pattern, similar to what was 14

observed after shCLK2 (Figures 5H-I). These results imply that RBFOX2 may act downstream of

CLK2 and may mediate its effect on splicing.

We also investigated whether the expression of CLK2 is associated with ENAH exon 11a

usage in the TCGA breast cancer RNA-seq dataset. This revealed a good correlation of CLK2

expression to ENAH exon 11a usage in normal breast tissues (Figures 5J and S3F), which confirms

results from our siCLK2 studies. However, this correlation is completely lost in breast tumors, irrespective of breast tumor subtypes (Figure S3F).

Lastly, to identify genes that show common EMT-related and breast tumor subtype-specific splicing patterns, we explored potential overlaps between splice variants differentially expressed in

MCF7 cells before and after shCLK2 expression and in HMLE mammary epithelial cells undergoing

EMT induced by the overexpression of the TWIST transcription factor, and differentially expressed between luminal and basal breast tumors in the TCGA data (Figure S4A). ENAH was the only gene that showed differential splicing due to EMT in both MCF7 shCLK2 and HMLE –TWIST cells. In contrast, the splice variants of 11 genes (e.g., CASZ1, CD47, GREB1, PMP22, and PTK2) were significantly different in MCF7 cells after CLK2 downregulation and also between basal and luminal breast tumors (Figure S4B). The limited overlap between EMT-related splicing changes between two cell lines is not surprising as HMLE and MCF7 cells are very different and overexpression of TWIST and downregulation of CLK2 may activate different downstream pathways. However, differences in experimental conditions and data analysis may also contribute to the limited overlaps.

DISCUSSION

We describe here a functional genomics screen and the identification of several novel putative oncogenic kinases in breast cancer that may be explored as therapeutic targets. We have previously

reported the detailed characterization of two of these kinases IKBKE (47) and AKT3 (48) that promote

tumorigenesis via activating the NF-kB (49) and PI3K/AKT/mTOR signaling pathways, respectively.

Interestingly, several of the kinases that we identified as hits in our shRNA screen are involved in the 15

AMPK-mTOR-AKT signaling pathway implying a central role for this pathway in breast cancer cell

growth and survival. ULK1 is a substrate of AMPK and a key regulator of autophagy (50) and was

recently reported to promote the growth of HER2+ breast cancer cells (51). NUAK2 is an AMPK-

related kinase and a putative oncogene in melanoma (52, 53). RIOK2 regulates glioblastoma growth

and survival via regulating AKT (54).

In this study, we focused on the more detailed characterization of CLK2, a dual specificity

kinase implicated in the regulation of splicing due to its ability to phosphorylate SR proteins (55-57).

Besides splicing, CLK2 has also been shown to play a role in hepatic gluconeogenesis and fatty acid

oxidation by directly phosphorylating PGC-1α and decreasing its transcriptional activity (58, 59).

CLK2 was also shown to phosphorylate and activate PTP-1B and influence tumor growth via this

action (60). Lastly, CLK2 is a negative regulator of AKT activity via phosphorylating and activating

PP2A that leads to dephosphorylation of AKT (59, 61). At the same time, CLK2 itself is activated by phosphorylation by AKT following ionizing radiation (62). Thus, CLK2 is both up-stream and downstream of AKT forming a self-regulatory loop. However, some of these signaling pathways may be cell type-specific as in human breast cancer cells we did not find conclusive evidence for the regulation of AKT by CLK2 (data not shown).

We found that CLK2 is amplified and overexpressed in a significant fraction of human breast tumors and its downregulation inhibits breast cancer cell growth in cell culture models and tumorigenesis in xenograft assays. Importantly, we show that decreased CLK2 levels induce EMT and EMT-related changes in alternative splicing patterns in luminal breast cancer cells. In line with our findings, a recent study described that changes in alternative splicing by themselves can lead to

EMT-related changes in cellular phenotypes (40). Similarly SRSF1, a splicing factor and substrate of

CLK2, regulates mammary epithelial cell transformation (63) and an oncogenic splice variant of KLF6 induces EMT and promotes breast cancer metastasis (64). One of the genes whose splice variants are changed following downregulation of CLK2 is ENAH (MENA). ENAH is an actin-binding protein that promotes cancer cell invasion and metastasis and its expression in primary breast tumors is 16

associated with poor outcome (38, 39). The switch from epithelial to mesenchymal variant of ENAH after downregulation of CLK2 may underlie the increased cell invasion and migration we detected.

However, change in ENAH splice variants is unlikely to be responsible for all the phenotypic changes

observed following CLK2 loss as several breast cancer cells express both variants of ENAH yet they

are still epithelial and relatively non-invasive (e.g., MCF10DCIS cells). The splicing of ENAH is

regulated by multiple splicing factors including ESRP1 /2 (42-44) and RBFOX2 proteins (46, 65). Our

findings that RBFOX2 levels are decreased following CLK2 downregulation and that knock down of

RBFOX2 in MCF7 cells enhances mesenchymal-type ENAH splicing imply that CLK2’s effects on

ENAH splicing might be mediated via RBFOX2. However, the function and cell type-specificity of

these splicing factors is complex, thus, further studies are required to delineate how CLK2 may

regulate alternative splicing.

In summary, our results should encourage the further preclinical validation of CLK2 and the

other putative oncogenic kinases we identified as therapeutic targets in breast cancer.

ACKNOWLEDGEMENTS

We thank the Dana-Farber Cancer Institute Molecular Biology Core Facilities for excellent high- throughput sequencing services and members of our laboratory for critical reading of the manuscript and useful suggestions.

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FIGURE LEGENDS

Figure 1. Analysis of amplified kinases in breast cancer. A, Two-dimensional Genome

Topography Scanning (GTS) plot of amplified kinases. Aberration amplitude and Recurrence Index

(ARI) (x-axis) is a measure of the copy number gain and the recurrence of such copy numbers across the samples. Aberration Focality Index (AFI) (y-axis) weights the focality of the copy number changes.

Genes in the upper right corner have large copy number gains that are both recurrent and focal. Red diamonds indicate genes selected for follow up studies. B, Representative images of FISH analysis of selected amplified kinases in the indicated cell lines.

Figure 2. shRNA screen results. Blue, pink, red, and orange colors indicate breast cancer subtypes

(luminal, TNBC, and HER2+) and immortalized cells, respectively, in all panels. A, Primary screen

results. Average z-scores [(average viability - plate median average viability)/(plate median absolute

deviation of average viability)] from primary shRNA screen of 26 amplified kinases in breast cancer

are shown. shRNA clones highlighted in blue, pink, and red colors with the lowest 10% z-score were

identified as hits. B, Results of the secondary shRNA screen for 10 kinases in 17 breast cell lines.

Numbers indicated % cell viability compared to control. Shading indicates shRNAs that showed ≥

30% decrease in viability compared to control shRNAs.

Figure 3. CLK2 function in breast cancer cells. Blue, pink, red, and orange colors of the cell lines indicate breast cancer subtypes (luminal, TNBC, and HER2+) and immortalized cells, respectively, in

all panels. A, Analysis of CLK2 mRNA levels in breast cancer cell lines by qRT-PCR. Expression

levels are depicted as a ratio relative to that observed in MCF7. *p < 0.05 by t-test. B, Immunoblot

analysis of CLK2 protein levels in a panel of breast cell lines. β-actin was used as loading control. C,

Quantification of the immunoblot results in panel B. y-axis indicates CLK2 protein levels relative to β-

actin. *p < 0.05 by t-test. D, Immunoblot analysis of CKL2 immunoprecipitates (CLK2 ip) for phospho-

serine (pSer) levels in breast cancer cell lines. Immunoblot for β-actin (ACTB) on total cell lysates

was used as loading control. E, Cell growth curve of MCF7 and T-47D cells infected with the

indicated shRNAs. Error bars represent mean ± standard error of the mean (SEM). F, Cell cycle prolife of MCF7 (upper) and T-47D (lower) cells following CLK2 downregulation. The effects of CLK2 downregulation on cell migration (G) and invasion (H) in MCF7 cells. Data represent means ± SEM

(n=3). * * P < 0.01, * P < 0.05 by t-test.

Figure 4. Downregulation of CLK2 attenuates cell growth in 3D matrigel and suppresses tumorigenesis. A, Representative phase contrast images of MCF10DCIS spheroids in Matrigel after

8 days of growth. B, Viability of MCF10DCIS cells expressing control shGFP and shCLK2 following growth for 8 days in matrigel. Error bars represent mean ± standard error of the mean (SEM, n=3), * indicates p < 0.01 by t-test. C, Weight of xenografts derived from MCF10DCIS cells expressing doxycycline-inducible CLK2-targeting shRNAs 35 days after injection into immunodeficient mice.

Doxycycline (dox) was administrated to mice starting on day 1 or day 14 after injection. * and ** indicates p < 0.05 and p < 0.01 by t-test, respectively. D, Tumors harvested from control and dox- treated mice were subjected to immunoblot analysis to confirm the downregulation of CLK2. Cell lysates from shLacZ-expressing xenografts were loaded as additional controls. E, Representative images of hematoxylin-eosine stained slides of control (no dox) and shCLK2 expressing xenografts

(Dox at d14) to depict histology, immunohistochemical analyses of smooth muscle actin (SMA) to visualize myoepithelial cells, Ki67 to assess proliferation, and TUNEL to visualize apoptosis.

Multicolor immunofluorescence for vimentin (VIM) and E-cadherin (CDH1) basal and luminal cell markers, respectively.

Figure 5. Downregulation of CLK2 alters splicing patterns. A, RT-PCR analysis of the expression of EMT-related genes in MCF7 cells. Gene expression levels were normalized to GAPDH. Y-axis indicates normalized mRNA levels relative to shGFP. B, Immunoblot analysis of SF2/ASF 26

Downloaded from cancerres.aacrjournals.org on October 4, 2021. © 2015 American Association for Cancer Research. Author Manuscript Published OnlineFirst on February 10, 2015; DOI: 10.1158/0008-5472.CAN-14-2443 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. phosphorylation in MCF7 cells. β-actin was used as loading control. C, RNA-seq analysis of alternatively spliced exon11a in the ENAH gene. Numbers indicate RPKM values. D, RT-PCR analysis of the levels of exon 11a ENAH splice isoforms in MCF7 cells following downregulation of

CLK2 or SRSF1. GAPDH was loaded as an internal control. E, RT-PCR analysis of ENAH splicing patterns in a panel of breast cell lines. GAPDH was used as control. Blue, pink, red, and orange colors of the cell lines indicate breast cancer subtypes (luminal, TNBC, and HER2+) and immortalized cells, respectively. F, qRT-PCR analysis of mRNA levels of ESRP1/2 and RBFOX proteins following downregulation of CLK2 in MCF7 cells. Y-axis shows levels in shCLK2 expressing cells relative to control. G, Immunoblot analysis of RBFOX2 protein levels in MCF7 cells expressing control and

CLK2-targeting siRNAs. H, Expression of CLK2 in MCF7 cells transfected with control or RBFOX2- targeting siRNAs. I, RT-PCR analysis of the levels of exon 11a ENAH splice isoforms in MCF7 cells following downregulation of RBFOX2. GAPDH was loaded as an internal control. J, Heatmap depicting the expression of ENAH exons based on TCGA breast cancer RNA-seq dataset. Samples were grouped into normal and breast tumor subtypes and ordered based on CLK2 expression within each group. Red, high expression; black, low expression.

Figure 1 A 0 -2.5 -2 -1.5 -1 -0.5 0

-0.5

-1

-1.5 ULK1 RIOK2 RET MAPK11/MAPK12 ERBB2

GRK1 MAPK7 -2 SRMS UCKL1 PTK6 log AFI AFI log PDK2 MAPK15 -2.5 RIPK2 NRBP2 PTK2 STK3 NTRK1 PSKH2 CLK2 -3 NPR1 MAPKAPK2 AKT3 ITPKB DSPYK DYRK3 -3.5 IKBKE

-4 log ARI B

A Figure 2

B SYMBOL

CloneID CLONENAME MCF-7 T47D SUM185PE ZR-75-1 ZR-75-30 BT-474 BT-483 MDA-MB-453 SKBR3 BT-549 HCC-1937 Hs578T MDA-MB-231 MDA-MB-468 SUM149PT SUM159PT SUM52PE MCF-10A MCF-12A TRCN0000010186 NM_005465.x-569s1c1 57 65 85 86 93 57 91 87 80 49 45 39 65 55 61 59 80 38 67 TRCN0000195243 NM_005465.3-2995s1c1 65 52 99 86 110 63 85 93 84 77 65 90 69 81 95 69 78 62 66 AKT3 TRCN0000196520 NM_005465.3-2101s1c1 54 42 97 79 104 116 93 79 64 56 40 34 50 21 29 16 48 61 38 TRCN0000196521 NM_005465.3-437s1c1 91 100 118 99 72 89 102 94 70 100 87 84 79 98 80 102 74 96 92 TRCN0000197265 NM_005465.3-211s1c1 49 26 96 90 88 83 81 84 106 70 70 48 79 90 84 73 66 89 85 TRCN0000195230 NM_003993.2-572s1c1 27 30 66 70 52 56 73 55 68 42 30 16 37 27 51 19 42 43 35 TRCN0000195366 NM_003993.2-945s1c1 50 38 72 105 98 113 91 107 86 70 103 69 85 95 88 60 76 95 70 CLK2 TRCN0000196747 NM_003993.2-1969s1c1 64 55 89 93 79 82 98 96 94 82 64 57 93 68 92 65 57 50 68 TRCN0000197205 NM_003993.2-1640s1c1 53 54 100 92 99 89 105 81 102 85 78 95 75 91 103 76 82 94 95 TRCN0000199189 NM_003993.2-1870s1c1 89 103 105 88 95 104 103 103 97 109 68 67 81 81 92 86 108 52 58 TRCN0000001486 NM_002929.x-1344s1c1 47 36 90 84 53 54 103 95 72 54 55 90 48 48 62 59 74 80 79 TRCN0000001487 NM_002929.x-372s1c1 61 69 53 58 58 61 57 56 56 61 68 61 55 49 54 58 56 55 57 GRK1 TRCN0000195622 NM_002929.2-1466s1c1 44 37 78 72 87 86 81 103 89 68 42 23 66 82 84 59 42 63 50 TRCN0000199366 NM_002929.2-1901s1c1 41 41 108 90 93 77 87 76 85 41 20 18 36 52 50 46 71 75 54 TRCN0000199423 NM_002929.2-1682s1c1 73 135 78 114 79 94 110 104 120 113 56 60 92 82 73 90 111 94 85 TRCN0000009972 NM_002751.x-424s1c1 124 102 103 93 109 93 101 79 80 45 125 90 75 62 61 64 35 99 82 TRCN0000195259 NM_002751.5-637s1c1 91 65 95 71 83 89 95 95 91 59 64 70 88 72 66 84 92 104 83 MAPK11 TRCN0000199347 NM_002751.5-1391s1c1 119 110 103 103 78 117 106 114 104 90 111 98 116 105 71 108 116 84 100 TRCN0000199671 NM_002751.5-545s1c1 63 35 78 82 54 57 87 61 88 38 36 48 48 42 58 31 59 47 57 TRCN0000199694 NM_002751.5-822s1c1 92 48 105 91 84 108 95 88 93 91 66 54 100 99 109 95 64 87 103 TRCN0000038661 NM_139021.1-653s1c1 46 42 90 90 91 86 78 100 94 67 53 57 72 90 84 65 66 68 65 TRCN0000038662 NM_139021.1-507s1c1 62 56 79 78 93 61 86 97 92 59 68 69 68 80 83 66 88 71 85 MAPK15 TRCN0000199135 NM_139021.2-329s1c1 76 96 100 91 90 91 105 112 84 53 28 54 82 70 65 67 93 61 69 TRCN0000199687 NM_139021.2-1051s1c1 58 54 84 89 116 90 89 88 89 59 57 72 75 96 75 51 48 87 75 TRCN0000199957 NM_139021.2-108s1c1 80 56 101 94 115 102 111 93 110 83 96 127 92 90 99 77 97 104 95 TRCN0000007325 NM_000906.2-3750s1c1 52 28 75 82 41 48 85 67 38 27 19 25 63 34 39 11 20 59 53 TRCN0000007326 NM_000906.2-3474s1c1 67 46 74 90 26 54 87 75 76 75 39 73 78 62 75 94 67 81 83 NPR1 TRCN0000007327 NM_000906.2-1418s1c1 84 80 87 103 107 99 112 94 86 76 55 49 68 88 54 54 63 60 50 TRCN0000007328 NM_000906.2-3198s1c1 67 66 92 93 127 90 93 89 101 67 60 67 68 62 84 71 82 74 84 TRCN0000007329 NM_000906.2-1633s1c1 74 50 89 93 115 97 89 102 94 46 51 49 76 76 81 57 70 76 62 TRCN0000003206 NM_030952.x-2219s1c1 61 57 85 83 106 107 104 113 113 74 39 57 82 80 112 32 32 83 47 TRCN0000003207 NM_030952.x-713s1c1 28 36 57 74 46 63 78 83 71 61 26 22 65 60 46 60 48 81 70 NUAK2 TRCN0000003208 NM_030952.x-454s1c1 72 56 92 92 102 88 98 75 93 81 24 111 70 63 96 42 77 90 61 TRCN0000195372 NM_030952.1-1616s1c1 74 51 93 89 92 86 102 87 92 67 54 81 68 81 103 87 83 71 81 TRCN0000199900 NM_030952.1-1234s1c1 90 75 107 101 95 86 110 89 87 68 61 67 76 70 69 62 90 72 89 TRCN0000003217 NM_033126.x-388s1c1 12 18 70 109 54 25 48 64 95 79 66 57 84 90 76 71 57 90 73 TRCN0000003218 NM_033126.x-647s1c1 64 40 85 94 56 81 84 68 95 70 29 37 109 99 82 47 82 77 69 PSKH2 TRCN0000195178 NM_033126.1-541s1c1 44 45 90 85 77 75 82 96 75 76 56 45 74 77 85 66 61 76 78 TRCN0000199072 NM_033126.1-177s1c1 65 62 62 91 88 71 96 90 102 57 42 18 58 46 60 50 85 58 56 TRCN0000199480 NM_033126.1-848s1c1 67 63 85 88 54 44 95 103 81 81 68 60 79 77 79 62 79 69 74 TRCN0000121129 NM_005607.3-2217s1c1 58 48 89 87 92 79 89 92 76 60 62 58 65 74 68 63 43 72 49 TRCN0000121207 NM_005607.3-4258s1c1 74 104 87 104 55 78 86 84 72 72 85 105 101 92 85 94 101 85 96 PTK2 TRCN0000121318 NM_005607.3-2779s1c1 80 70 111 93 101 77 97 89 79 52 40 71 66 71 75 60 91 83 68 TRCN0000121319 NM_005607.3-1043s1c1 61 63 88 81 91 84 89 87 79 42 66 74 31 67 69 43 32 76 60 TRCN0000196310 NM_005607.3-817s1c1 74 94 92 106 103 79 88 92 98 69 33 32 79 80 79 46 89 79 77 TRCN0000037507 NM_018343.1-1604s1c1 46 38 88 84 85 76 97 81 81 48 56 56 50 48 51 79 48 79 75 TRCN0000194682 NM_018343.1-1403s1c1 121 105 104 112 120 76 118 100 92 53 88 47 104 83 63 120 91 84 103 RIOK2 TRCN0000196672 NM_018343.1-153s1c1 76 70 93 86 75 80 96 98 93 57 77 85 76 70 78 104 62 98 92 TRCN0000196684DownloadedNM_018343.1-1464s1c1 from cancerres.aacrjournals.org 89 92 108 99 on 73October 100 1044, 2021. 104 110© 2015 94 American55 117 Association 95 98 89 for 87Cancer 76 96 102 TRCN0000197250 NM_018343.1-1082s1c1 81 66 76 93 104Research. 81 94 69 76 65 58 65 57 44 64 55 52 75 60 Author Manuscript Published OnlineFirst on February 10, 2015; DOI: 10.1158/0008-5472.CAN-14-2443 * A 1.5 Author manuscripts have been peer reviewedB and accepted for publication but have not yet been edited. Figure 3

1.0

0.5 MCF7 T-47D ZR-75-1 ZR-75-30 SK-BR-3 BT-483 BT-474 MCF10DCIS SUM159PT Hs578-T MDA-MB-231 MDA-MB-468 MCF10A MCF12A Relative to MCF7 MCF7 to Relative CLK2 0.0 MCF7 T-47D BT-549 BT-474 ACTB Hs578-T ZR-75-30 SUM159PT MDF10DCIS MDA-MB-231 MDA-MB-453 C * 1.5 D

1.0 MCF7 T-47D SUM159PT MDA-MB-231 -actin ratio -actin

β pSer 0.5 CLK2 ip CLK2/ CLK2 0.0 Total lysate ACTB MCF7 T-47D BT-483 BT-474 ZR-75-1 Hs578-T MCF10A MCF12A SK-BR-3 ZR-75-30 SUM159PT MCF10DCIS MDA-MB-231 MDA-MB-468 25 20 E MCF7 T-47D

20 shGFP 15 shGFP shCLK2-572 15 shCLK2-572 shCLK2-1969 10 shCLK2-1969

Cell growth Cell growth

5 (Relative to day 0) (Relative to day 0) 5

0 0 F 0 3 6 9 0 3 6 9 Time (days) Time (days)

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0 0 9 9 P P 6 72 72 6 9 5 5 9 - GF GF -1 h -1 h 2 s 2 s K K L L hC shCLK2- shCLK2 Downloaded from cancerres.aacrjournals.org on October 4, 2021. © 2015 American Association for Cancer hC s Research. s C

Tumor Volume (mm3) A 2 400 600 800 00 0

No dox Downloaded from hF shCLK2 shGFP Author manuscriptshavebeenpeerreviewedandacceptedforpublicationbutnotyetedited. Author ManuscriptPublishedOnlineFirstonFebruary10,2015;DOI:10.1158/0008-5472.CAN-14-2443 B Relative to control Dox at d1 0.0 0 0.4 0.6 0.8 1.0 1.2 .2 hF shCLK2 shGFP cancerres.aacrjournals.org Dox at d14 β-ACTIN D CLK2

shCLK2 dox (-) E shCLK2 dox (+) SMA CDH1 VIM T Ki67 H &E unel oDxDoxatd14 No Dox Figure 4 Author Manuscript Published OnlineFirst on February 10, 2015; DOI: 10.1158/0008-5472.CAN-14-2443 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. shGFP D A 6 B shCLK2 siControl siSRSF1 siCLK2

Control 4 i

s siCLK2 CLK2 11 11a 12 2

mRNA levels ENAH phospho-SRSF1 11 12 (Relative to control) to (Relative

0 SRSF1 GAPDH VIM FN1 β-ACTIN ZEB1 CDH1 CDH2 SNAI1 SNAI2 TWIST1 C E

shControl 181

219 MCF7 T-47D ZR-75-1 ZR-75-30 BT-483 BT-474 SUM159PT Hs578-T MDA-MB-231 BT-549 MCF10DCIS shCLK2 11 11a 12 ENAH 500 bp ENAH 11 12 NM_018212.4 NM_001008493.1 Exon 11A Exon 11 GAPDH

1.5 F G H 1.5 I

1.0 1.0 siControl siCLK2

0.5 RBFOX2 siControl siRBFOX2 mRNA levels 0.5

(Relative to control) to (Relative ENAH N N.D..D. ACTB 0.0 (Relative to control) to (Relative CLK2 mRNA levels GAPDH

ESRP1 ESRP2 0.0 RBFOX1 RBFOX2 RBFOX3 siControl siRBFOX2 J Normal Basal HER2+ Luminal B Luminal A

CLK2 expression

exon1 exon2 exon3 exon4 exon5 exon6 exon7 exon8 exon9

exon10 ENAHexons exon11 exon11a exon12 exon13 Downloaded from cancerres.aacrjournals.org on October 4, 2021. © 2015 American Association for Cancer Figure 5 Research. exon14 Author Manuscript Published OnlineFirst on February 10, 2015; DOI: 10.1158/0008-5472.CAN-14-2443 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

CLK2 is an oncogenic kinase and splicing regulator in breast cancer

Taku Yoshida, Jee Hyun Kim, Kristopher Carver, et al.

Cancer Res Published OnlineFirst February 10, 2015.

Updated version Access the most recent version of this article at: doi:10.1158/0008-5472.CAN-14-2443

Supplementary Access the most recent supplemental material at: Material http://cancerres.aacrjournals.org/content/suppl/2015/02/11/0008-5472.CAN-14-2443.DC1

Author Author manuscripts have been peer reviewed and accepted for publication but have not yet been Manuscript edited.

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