The Influence of EWS-FLI1 on the Rho/MRTF/Actin Circuit in Ewing Sarcoma

The Influence of EWS-FLI1 on the Rho/MRTF/Actin Circuit in Ewing sarcoma

Doctoral thesis at the Medical University of Vienna for obtaining the academic degree

Doctor of Philosophy

Submitted by

Anna Maria Katschnig, MSc

Supervisor: Univ.-Prof. Dr. Heinrich Kovar St. Anna Kinderkrebsforschung/ Children’s Cancer Research Institute Zimmermannplatz 10; 1090 Vienna

Vienna, 02/ 2017 Declaration

The experimental work conducted in this thesis was performed at the Children’s Cancer Research Institute (CCRI)/ St. Anna Kinderkrebsforschung, located in Vienna (Austria), in the “Molecular Biology of Solid Tumours” working group of Prof. Heinrich Kovar. The manuscript arising from this work is the following: “EWS-FLI1 perturbs MRTFB/YAP- 1/TEAD target gene regulation inhibiting cytoskeletal auto-regulatory feedback in Ewing sarcoma.” A.M. Katschnig prepared the manuscript and performed the majority of experiments. M.O. Kauer was responsible for the bioinformatical data analysis of all sequencing data. R. Schwentner was involved in experiment planning and helped in performing experiments. C.N. Mutz was assisting in several experiments. M. Linder was involved in the generation of the wound-healing migration assay data. E.M. Tomazou provided protocols and advice for the ChIP-seq experiments. D.N.T. Aryee assisted with the soft agar assays and supported the progress of the work. M. Sibilia provided material and technical microscopy support. J. Alonso provided the A673/TR/shEF cell line, which was used for the majority of experiments. H. Kovar supervised the work and edited the manuscript. The thesis was written by A.M. Katschnig and edited by H. Kovar.

The manuscript arising from this thesis has been submitted to Cancer Research on February 15th 2017.

Table of Contents

Declaration ...... i Table of Contents ...... ii List of figures ...... iv List of tables...... v Abstract ...... vi Zusammenfassung ...... vii Publications arising from this thesis ...... ix Abbreviations ...... x Acknowledgements ...... xii CHAPTER ONE: INTRODUCTION ...... 1 1.1. Ewing sarcoma ...... 1 1.1.1. General Introduction ...... 1 1.1.2. Classification and Cell of Origin ...... 2 1.1.3. EWS-ETS fusions in EwS ...... 3 1.1.4. EWS ...... 3 1.1.5. FLI1 ...... 4 1.1.6. Other chromosomal abnormalities in EwS ...... 4 1.2. EWS-FLI1 ...... 4 1.2.1. Transcriptional regulation by EWS-FLI1 ...... 5 1.2.2. Chromosomal binding of EWS-FLI1 ...... 7 1.2.3. Protein-Protein interactions involving EWS-FLI1 ...... 8 1.3. EWS-FLI1 and the actin cytoskeleton ...... 9 1.4. The Rho pathway ...... 10 1.4.1. Rho GTPases ...... 11 1.4.2. Function of Rho GTPases ...... 12 1.4.3. Ligand-Receptor induced Rho pathway activation...... 12 1.4.4. The Rho-actin-MRTF-SRF circuit ...... 14 1.4.5. The serum-response factor SRF ...... 16 1.4.6. The myocardin-related transcription factors (MRTF)...... 17 1.4.7. MRTFs and their role in cancer and disease ...... 19 1.4.8. Alternative pathways downstream of Rho: crosstalk between MRTF and YAP/TAZ .... 19 1.5. Aims of this thesis ...... 21 CHAPTER TWO: Results ...... 22

2.1. Prologue ...... 22 2.2. Manuscript by Katschnig A.M. et al. “EWS-FLI1 perturbs MRTFB/YAP-1/TEAD target gene regulation inhibiting cytoskeletal auto-regulatory feedback in Ewing sarcoma.” ...... 22 2.3. Interlude ...... 68 2.4. Extended Results ...... 68 Chapter THREE: Discussion ...... 75 3.1. General discussion ...... 75 CHAPTER FOUR: Material& Methods ...... 84 References ...... 87 Curriculum Vitae ...... 99

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List of figures

Figure 1. Ewing sarcoma (EwS); p.3 Figure 2. EWS-FLI1 fusion gene; p.5 Figure 3. Master-deregulator EWS-FLI1; p.9 Figure 4. Rho family of GTPases; p.11 Figure 5. The Rho GTPase activation cycle; p.11 Figure 6. Activation of Rho via ligand-receptor (GPCR) interaction; p.13 Figure 7. The Rho-actin-MRTF-SRF autoregulatory circuit; p.15 Figure 8. Rho and Ras pathways and SRF; p.17 Figure 9. MRTF protein structure; p.19 Figure 10. Different modes of YAP/TAZ regulation; p.20

Figure E1. Comparison of serum-response and MRTFA/B depletion in EwS and OS cells; p.69 Figure E2. Functional analysis of the combined MRTFA/B knockdown in A673/TR/shEF; p.71 Figure E3. Functional analysis of the single MRTFA/MRTFB knockdown in A673/TR/shEF; p.72 Figure E4. MRTFA ChIP-sequencing results; p.74

List of tables

Table 1. FET/ETS fusions in EwS; p.3 Table 2. EWS-FLI1 transcriptional targets and their function; p.7 Table 3. Western blot gels; p.84 Table 4. Oligonucleotide sequences (extended); p.85

Table E1. RKPM expression values of MRTFA and MRTFB in EwS cell lines; p.86

Abstract

Ewing sarcoma (EwS) is a highly aggressive paediatric bone tumour driven by the ETS fusion-oncogene EWS-FLI1, derived from the chromosomal translocation t(11;22)(q24;q12). EWS-FLI1 fuels EwS pathogenesis mainly by its function as an aberrant transcription factor which deregulates hundreds of genes by either activation (EWS-FLI1-correlated genes) or repression (EWS-FLI1-anticorrelated genes). Several EWS-FLI1-anticorrelated genes are involved in cytoskeletal processes and typically regulated by Rho/F-actin signalling. The Rho pathway is a crucial regulator of the actin cytoskeleton and cellular plasticity, which is a prerequisite of tumour cells in order to become metastatic. Given the fact that EwS cells are highly prone to metastasize we were interested in studying a potential EWS-FLI1-mediated deregulation of Rho signalling. Activation of Rho triggers globular (G)- to filamentous (F)- actin polymerization thereby enabling nuclear translocation of the myocardin-related transcription factors MRTFA (MKL-1) and MRTFB (MKL-2). MRTFs typically serve as transcriptional co-activators of the transcription factor SRF in regulating several cytoskeletal key players. We used the A673/TR/shEF cell line, where EWS-FLI1 levels can be easily modulated upon doxycycline (dox) addition, as a model to study the influence of EWS-FLI1 on MRTFA/B in EwS. Strikingly, MRTFA/B transcriptional activity was overall repressed by EWS-FLI1. MRTFA and especially MRTFB depletion antagonized transcriptional effects of the dox-induced EWS-FLI1 knockdown. Chromatin-immunoprecipitation coupled with sequencing (ChIP-seq) revealed a strong overlap of MRTFB and EWS-FLI1 chromatin binding. MRTFB binding was significantly enriched in distal (enhancer) regions of EWS-FLI1- anticorrelated genes, especially upon EWS-FLI1-low conditions. Of note, an overrepresentation of TEAD motifs, but not SRF binding motifs, was observed in these regions suggesting a potential involvement of TEAD transcription factors in the regulation of the MRTFB/EWS-FLI1 reciprocally regulated targets. In line with this finding, target genes of the mechano sensitive YAP/TAZ/TEAD pathway (CTGF, CYR61, SERPINE1) were found among the MRTFB-bound EWS-FLI1-anticorrelated genes. Genome-wide expression profiling upon combined knockdown of EWS-FLI1 and all four TEADs confirmed that TEAD regulates EWS-FLI1 target genes antagonistically. ChIP-qPCR for selected genes validated binding of TEAD and its transcriptional co-activator YAP-1 to MRTFB/EWS-FLI1 target genes. Whereas chromatin occupancy of EWS-FLI1 was reduced upon low-EWS-FLI1 levels, MRTFB binding was enriched. Among this panel of target genes we found several keyplayers of cytoskeletal signalling (CYR61, CTGF) and remodelling (TPM-1, TAGLN, CALD-1). Our data suggest a model in which EWS-FLI1 disrupts formation of a transcriptional MRTFB/YAP-1/TEAD module thereby perturbing the cytoskeletal autoregulatory feedback loop.

Zusammenfassung

Das Ewing Sarkom ist ein hoch-aggressiver pädiatrischer Tumor, welcher durch die Expression des Fusionsproteins EWS-FLI1, das Produkt der chromosomalen Translokation t(11;22)(q24;q12), angetrieben wird. EWS-FLI1 ist ein entarteter Transkriptionsfaktor, der die Expression hunderter Gene verändert, indem er sie entweder aktiviert (EWS-FLI1 korrelierte Gene) oder reprimiert (EWS-FLI1 antikorrelierte Gene). Unter den EWS-FLI1-antikorrelierten Genen befindet sich eine Vielzahl an Genen für zytoskeletale Komponenten, die normalerweise über den Rho/F-Aktin Signalweg reguliert werden. Der Rho Signaltransduktionsweg ist für die koordinierte Regulation des Aktin-Zytoskeletts und damit für die zelluläre Verformbarkeit hauptverantwortlich. Tumorzellplastizität ist eine Grundeigenschaft der malignen Zelle um zu metastasieren. EwS Zellen metastasieren sehr effizient und üblicherweise noch bevor der Tumor klinisch detektierbar ist. Aus diesem Grund studierten wir den möglichen Einfluss von EWS-FLI1 auf den Rho Signalweg bei der EwS Metastasierung. Wenn Rho GTPasen aktiviert werden, katalysieren sie über ihre Effektoren die Polymerisierung von globulärem (G) Aktin zu filamentösem (F) Aktin. In direkter Folge kann der Myokardin-verwandte Transkriptionsfaktor MRTF in den Kern transloziieren. Zu den MRTFs gehören MRTFA (MKL-1) und MRTFB (MKL-2), welche im Kern üblicherweise an den Serum aktivierten Faktor SRF binden und als Koaktivatoren die Transkription von zytoskeletalen Genen regulieren. In dieser Studie arbeiteten wir mit einer EwS Zelllinie, A673/TR/shEF, bei der die Expression von EWS-FLI1 durch die Zugabe von Doxyzyklin (Dox) effizient reduziert werden kann. Es zeigte sich, dass EWS-FLI1 die transkriptionelle Aktivität von MRTFA/B stark unterdrückte, was sich in einer entgegensetzten Regulation von EWS-FLI1 kontrollierten Genen nach Modulation von MRTFA, vorallem aber MRTFB manifestierte. Chromatin-Immunoprezipitation mit Antikörpern gegen MRTFB und EWS-FLI1 und darauf folgender Sequenzierung (ChIP-seq) zeigte starke Überlappungen im chromosomalen Bindeverhalten der beiden Transkriptionsfaktoren. Wir fanden, dass MRTFB bevorzugt an distalen transkriptionsverstärkenden Regionen (“Enhancer”) von EWS-FLI1- antikorrelierten Genen bindet. Herabsetzung von EWS-FLI1 verstärkte diese Assoziation. Unter den mit MRTFB Enhancer Bindung assoziierten Genen befand sich eine Vielzahl von Genen, welche üblicherweise über den YAP/TAZ/TEAD Signalweg reguliert sind (CTGF, CYR61, SERPINE1). Tatsächlich konnten wir zeigen, dass auch in EwS TEAD Faktoren an die distalen Regionen der EWS-FLI1-antikorrelierten Gene binden und ähnlich MRTFB der transkriptionellen Aktivität von EWS-FLI1 entgegenwirken. Zusätzlich fanden wir auch eine signifikante Anreicherung des TEAD Koaktivators YES-assoziiertes Protein YAP-1 an den distalen MRTFB/TEAD gebundenen Regionen. Während EWS-FLI1 Reduktion die Bindung des Fusionsproteins an die jeweiligen Regionen verminderte, wurde die Bindung von MRTFB

vii dort verstärkt. Besonders hervorzuheben ist, dass viele der gemeinsamen aber entgegengesetzt regulierten MRTFB/TEAD/EWS-FLI1 Zielgene eine wichtige Rolle in der Modulierung des Zytoskeletts einnehmen. So befanden sich darunter sowohl Gene, die für die Kommunikation der Zelle mit der extrazellulären Matrix (CYR61, CTGF) verantwortlich sind, als auch Gene, welche direkt die Stabilität und Integrität des Zytoskeletts beeinflussen (TPM-1, TAGLN, CALD-1). Unsere Daten stützen daher die Hypothese, dass die sich selbstregulierende zytoskeletale Rückkoppelungsschleife von EWS-FLI1 unterbrochen wird, indem es die Bildung eines transkriptionellen Modules von MRTFB, YAP-1 und TEAD verhindert.

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Publications arising from this thesis

Manuscript: “EWS-FLI1 perturbs MRTFB/YAP-1/TEAD target gene regulation inhibiting cytoskeletal auto-regulatory feedback in Ewing sarcoma.” 02/15/2017: submitted to Cancer Research

Abbreviations

ABP Actin binding protein AMKL Acute megakaryocytic leukaemia CCN Connective tissue growth factor (CTGF), Cystein rich protein (Cyr61), and Nephroblastoma overexpressed gene (nov) DNA-BD DNA-binding domain EGF Epithelial growth factor EMT Epithelial to mesenchymal transition ETS E-twenty-six EwS Ewing sarcoma EWS Ewing sarcoma Breakpoint Region 1 FGF Fibroblast growth factor FISH Fluorescent in-situ hybridization FLI1 Friend leukaemia integration 1 transcription factor FOXO1 Forkhead Box Protein O1A GAP GTPase activating enzyme GDI Guanine nucleotide dissociation inhibitors GDP Guanosine diphosphate GEF Guanine nucleotide exchange factor GTP Guanosine triphosphate HCAD Histone deacetylase IDP Intrinsically disordered protein IEG Immediate-early gene LATS Large tumour suppressor homologue lncRNA Long non-coding RNA LPA Lysophosphatidic acid LSD-1 Lysine-specific demethylase-1 MAT Mesenchymal to amoeboid transition mDIA Mammalian homologue of Drosophila diaphanous miRNA Micro RNA MLC Myosin-light chain MRTF Myocardin-related transcription factors MYH9 Myosin Heavy Chain 9 NR0B1 Nuclear Receptor Subfamily 0 Group B Member 1 NSE Neural-specific endolase PDGF Platelet derived growth factor PNET Primitive neuroectodermal tumour x

RHO Ras homologue ROK/ROCK Rho-associated coiled-coil forming kinase RT-PCR Reverse-transcriptase PCR S1P Sphingosine-1-phosphate SAM Significance Analysis of Microarrays SETD1A SET Domain Containing 1A SRBCT Small round blue cell tumour SRE Serum response element SRF Serum response factor TAZ Transcriptional co-activator with PDZ-binding motif TCF Ternary complex factor TEAD Transcriptional enhancer factor domain; TEA domain transcription factor VEGF Vascular endothelial growth factor WES Whole exome sequencing WGS Whole genome sequencing YAP Yes-associated protein ZF Zinc finger

Acknowledgements

First and foremost, I would like to thank my supervisor, Prof Heinrich Kovar, for the opportunity to work in the exciting field of paediatric cancer research. I am very grateful for the many times he has enabled me to visit the United States of America in the course of the Annual Meetings of the American Association of Cancer Research (AACR), where I could share my work with colleagues from the field and which equipped me with a lot of motivation. Furthermore, he has continuously challenged and supported my ideas and left me the freedom to independently plan experiments and follow hypotheses. I would also like to express my gratitude to my colleague and friend Ela, who has been more than supportive in the last four years. With her excellent advice she is a great scientific role model and she profoundly contributed to the progress of this project by joint brain-storming, critical interpretation of results as well as by emotional support. Thanks to her I was never running out of fun in the lab. My gratitude also to Max, who has been a mentor and friend over the last years. He was not only substantial for the bioinformatical analysis of all the data generated in the course of my thesis but was also critically involved in the generation of the MRTF-YAP-TEAD hypothesis. Great thanks also to all the other members of my lab. Dave, for always being supportive and caring. Thanks to Eleni for many fruitful discussions and helping me with methods and the critical interpretation of my data, Guni and Karin for always being friendly and helpful. Also I would like to thank Jozef for many nice discussions and his continuous enthusiasm when it came to my project. Thanks also to my former PhD colleague Nelli for inspiring me with her motivation and for being a good friend. To all the other great people of the CCRI who never grew tired of helping me with technical or personal advice such as Tamara, Fikret, Sabine T- M, Klaus F and Flo. I would like to thank my sister Laura and all my good friends for always being there for me and making my life colourful and full of adventures. Also I want to thank Gabriel, who is my partner and best friend, always listening to my problems and supporting me with his love. Last but not least, I would like to express my deepest gratitude to my parents, who have continuously supported me financially and emotionally and for being proud of me that I have come that far.

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CHAPTER ONE: INTRODUCTION

1. General Introduction

1.1. Ewing sarcoma

1.1.1. General Introduction

Ewing sarcoma (EwS) is the second most common bone cancer in children and adolescents. EwS occurs with an incidence of about 2.93/million in the western hemisphere with a peak occurrence in the first two decades of life. EwS mostly affects the long bones of the lower extremities, pelvic- and chest wall-bones, however, it is also encountered in extra-osseous sites such as soft tissues (10 %) and less common in the viscera (Jedlicka, 2010). Males are slightly more affected than females and the incidence for EwS is highest in caucasian and lowest in the African population (Esiashvili et al, 2008; Kovar, 2011; Kovar, 2014).

Figure 1. Ewing sarcoma: A. primary EwS tumour sites and B. EwS cell morphology shown by Hematoxylin and Eosin staining. magnification: 400x. modified from (Bernstein et al, 2006)

The American pathologist James Ewing first characterized EwS in 1921 and described it as a “diffuse endothelioma of the bone” with highly distinct morphology as compared to osteosarcoma, the most common form of bone cancer (Ewing, 1921). Histologically EwS cells are poorly differentiated round blue cells with a high nuclear to cytoplasmic ratio. In about 90 % of EwS cases the surface marker glycoprotein CD99MIC2 is strongly expressed (Bernstein et al, 2006) (Riggi & Stamenkovic, 2007) but also neural cell markers (NSE, S100, CD56) as well as mesenchymal markers (e.g. vimentin) are frequently presented on EwS cells (Riggi et al, 2009). Although treatment-strategies in systemic and local therapy have 1 improved the overall-survival in EwS, the five-year survival-rate is only about 50 % in case of localized and non-recurrent disease. In approximately a quarter of patients clinically detectable metastases are found upon initial diagnosis further reducing the overall survival rate to approximately 20 % for these patients. Likely due to the presence of undetected micrometastases, patients are frequently faced with relapse (Dahlin et al, 1961). EwS metastasizes to the lungs, bone or bone-marrow and hardly ever to the brain, liver or lymph nodes (Riggi & Stamenkovic, 2007; Toomey et al, 2010). Treatment regimens for EwS have been extensively revised in the last 20 years and include local surgery, radiotherapy, and chemotherapy. Multimodal chemotherapy comprises combinations of vincristine, intercalating agents such as doxorubicine, DNA-crosslinker (nitrogen), the topoisomerase 2 inhibitor etoposide and in rare cases the antibiotic actinomycinD are given (Kovar, 2010). Nevertheless, acute- and, given the young age of patients , especially long-term toxicities remain a great problem in the treatment of EwS (Lawlor & Sorensen, 2015).

1.1.2. Classification and Cell of Origin

EwS is characterized and driven by the expression of ETS-fusion oncogenes, predominantly EWS-FLI1, derived from the chromosomal translocation t(11;22) (q24;q24) (more detailed discussion in chapter 1.1.3) (Jedlicka, 2010). There is still an ongoing debate concerning the cell of origin in EwS. This is in part due to the difficulty in obtaining tumour material. EwS cells cannot be retrieved from blood, plasma or urine and material is typically retained by fine-needle biopsies and hence limited (Bernstein et al, 2006; Jedlicka, 2010). There is evidence that the EwS progenitor cell either belongs to the neural-crest, haematopoetic, epithelial or mesenchymal lineage, however, the latter has so far proven to be the most likely candidate. Several studies in EwS cell lines showed that upon knockdown of the fusion- oncogene EWS-FLI1, the gene expression signature converges with that of mesenchymal stem cells (MSCs) including up regulation of MSC surface marker genes (CD44, CD59) and of neural genes (Kauer et al, 2009; Riggi et al, 2005; Tirode et al, 2007; Toomey et al, 2010). Furthermore, in contrast to other cell types, MSCs are permissive to ectopical expression of EWS-FLI1. Their ability to migrate through the whole body further supports the assumption of MSCs being related to EwS progenitors since the tumour occurs at diverse body sites (Riggi et al, 2009). Nevertheless, definition of the exact cell of origin in EwS has proven challenging due to the lack of differentiation markers and absence of appropriate EwS animal models (Meltzer, 2007; Riggi et al, 2009; Tanaka et al, 2014). Introduction of EWS-FLI1 into murine MSCs blocked differentiation of MSCs towards the adipogenic or osteogenic lineage and resulted in the formation of EwS-like tumours (Torchia et al, 2003) (Riggi et al, 2005) (Castillero-Trejo et al, 2005). Forced expression of EWS-FLI1 in human MSCs resulted in genotypic and phenotypic alterations resembling EwS, however, it was not sufficient for 2 oncogenic transformation (Javaheri et al, 2016; Riggi et al, 2008). The search for the right cell of origin in EwS is aggravated due to EWS-FLI1 perturbing the gene expression program of the EwS progenitor cell (Meltzer, 2007).

1.1.3. EWS-ETS fusions in EwS

The driving force in EwS is the pathognomonic fusion protein EWS-ETS in which the Ewing sarcoma breakpoint region 1 (EWS) RNA binding domain is replaced by the ETS DNA binding domain. In approximately 85% of EwS cases the EWS fusion partner is the Friend leukaemia integration site 1 transcription factor (FLI1) (Figure 2). In the remaining 10-15% of EwS cases the 5’-portion of the EWS gene is fused to the 3’-part of another ETS family member, ERG, and in rare cases ETV-1, ETV-4 or FEV (Kovar, 2010) (Table 1).

Table 1. FET/ETS fusions in Ewing sarcoma. Adapted from: (Kovar, 2011; Trancau, 2014)

All EWS-ETS factors retain a highly homologous ETS DNA binding domain and are aberrant transcription factors with a high transformation potential (Janknecht, 2005). The type of expressed EWS-ETS fusion, however, does not influence survival of EwS patients (Le Deley et al, 2010).

1.1.4. EWS

EWS belongs to the FET family of proteins (FUS, EWS, TAF15), which are ubiquitously expressed RNA-binding proteins. The N-terminal portion of FET-proteins contains a strong transcriptional activation domain, whereas the C-terminus carries sequences for nuclear localization. EWS is known to interact with components of the basal transcriptional machinery such as the RNA polymerase II and the basal transcription factor TFIID (Bertolotti et al, 1998; Kovar, 2010; Riggi & Stamenkovic, 2007). Interestingly, all members of the FET- family can engage in pathogenic fusion-chimaeras with transcription factors. In the case of EwS, the ETS transcription factor is typically fused to EWS (Kovar, 2011), however, a study from 2003 reported a chromosomal rearrangement t(16;21)(p11;q22) of the EWS 3 homologous protein FUS with ERG in four cases of EwS (Shing et al, 2003) that is also described in acute myeloid leukaemia (AML) (Shimizu et al, 1993). FET family members are engaged in oncogenic fusion proteins in human sarcomas as well as in leukaemia and are key players in oncogenic transformation in fusion-driven cancers (Kovar, 2011).

1.1.5. FLI1

Members of the ETS family are potent transcription factors and contain domains for transcriptional activation as well as repression. A winged helix-turn-helix of three α-helices and 4 beta-strands composes the ETS DNA-binding domain, which specifically recognizes the 5’-GGA(A/T)-3’ (ETS) core motif within a 12-15 bp spanning region. FLI1 is one of 30 members of ETS proteins and typically expressed in endothelial, hematopoietic or neural- crest derived mesenchymal cell lineages (Anderson et al, 2012; Hollenhorst et al, 2011) (Riggi & Stamenkovic, 2007). From murine knockout studies it is suggested that FLI1 plays a role in vascular and hematopoietic development. Aberrant activation or overexpression of FLI1 and ERG is associated with malignant transformation in murine cells, which defines them as proto-oncogenes (Janknecht, 2005).

1.1.6. Other chromosomal abnormalities in EwS

EwS is a paediatric tumour with a remarkably low number of genetic abnormalities apart from the EWS-ETS fusion. The rate for somatic mutations is only 0.15–0.65 per megabase (MB) according to Whole genome- (WGS) (Tirode et al, 2014) and whole exome- sequencing (WES) analysis (Crompton et al, 2014b). Approximately 50% of EwS cases exhibit copy- number gains in chromosome 8 and in 25% of patients gains in chromosome 12 or 1q are observed. Furthermore, about 10-20% of EwS have chromosome 20 gains and 1p36 losses. In about 20% of EwS patients, Single nucleotide variants (SNV) in TP35 and CDKN2A are found, which are likely involved in EwS oncogenicity (Lawlor & Sorensen, 2015; Sand et al, 2015). Variants in the STAG2 gene with its consequent loss occur in 9 to 21.5% of patients and are associated with metastatic disease and poor prognosis (Crompton et al, 2014a; Sand et al, 2015).

1.2. EWS-FLI1

EWS-FLI1 was first described in 1984 (Turc-Carel et al, 1984) and molecularly characterized in 1992 by Delattre and colleagues (Delattre et al, 1992).

Figure 2. EWS-FLI1 fusion-gene derived from t(11;22)(q24;q12) chromosomal translocation. SYQG= serine- tyrosine-glutamine-gylcine; RGG= arginine-glycine-glycine; RRM= RNA recognition motif; ZN= zinc finger; PTD= pointed domain; DNA-BD= DNA-binding domain (ETS); Pro= proline-rich. Adapted from (Janknecht, 2005; Riggi & Stamenkovic, 2007).

EWS-FLI1 is composed of the N-terminal domain of EWS, which is rich in glutamine, serine and tyrosine-residues (SYQG) and has strong transcriptional activation potential (Figure 2), and the C-terminal part of FLI1, including the ETS DNA binding domain (DBD). Depending on the relative location of the break points in the involved genes several types of EWS-FLI1 fusions can be observed, most common are type 1 and type 2. In the EWS-FLI1 type 1 fusion the EWS gene is retained until exon 7 and fused to exon 6 of the FLI1 gene. Fusion type 2 contains EWS until exon 7 fused to exon 5 of FLI1 and is therefore slightly longer than type 1 EWS-FLI1 (Trancau, 2014). The DBD on the EWS-FLI1 C-terminus is a prerequisite for the oncogenic capacity of EWS-FLI1. Kim et al showed that mutation in the COOH-region led to incapability of EWS-FLI1 to bind to Fos-Jun (AP-1) and loss of transformation capacity in NIH3T3 cells (Kim et al, 2006). May et al showed that both the carboxy-terminal EWS as well as the amino-terminal FLI1 domain are required for the oncogenic transformation potential of EWS-FLI1 (May et al, 1993). The presence of EWS-FLI1 is the most important diagnostic factor in EwS due to the lack of other specific markers. The fusion is typically detected by RT-PCR and FISH technologies. EWS-FLI1 is required for tumour growth, and knockdown of EWS-FLI1 prohibits anchorage- independent growth in soft-agar (Smith et al, 2006), triggers cell-cycle arrest and apoptosis in EwS cell lines and abrogates tumour-growth in mouse-xenografts (Kovar, 2014).

1.2.1. Transcriptional regulation by EWS-FLI1

The EWS-FLI1 fusion is an aberrant transcription factor with unique properties that stimulates transcription more strongly than FLI1 (May et al, 1993). EWS-FLI1 acts as a potent transcription factor deregulating hundreds of genes by either up- or downregulation 5

(Bilke et al, 2013; Kauer et al, 2009). Genes where EWS-FLI1 binding is assigned to promoter-regions are mainly involved in cell-cycle regulation, proliferation and response to DNA damage. It is assumed that these genes are direct transcriptional targets of EWS-FLI1. They are mostly activated by the fusion-oncogene, their expression declines upon knockdown of EWS-FLI1, hence they are also termed EWS-FLI1-correlated genes (Tomazou et al, 2015). A great number of EWS-FLI1 target genes are repressed and activated upon its knockdown (also referred to as EWS-FLI1-anticorrelated genes). They predominantly are involved in cell differentiation, signalling (Kauer et al, 2009) and migration (Chaturvedi et al, 2014). EWS-FLI1-correlated genes are likely regulated directly via binding of EWS-FLI1 to canonical ETS binding motifs or GGAA repeats. Whether EWS-FLI1 directly or indirectly regulates EWS-FLI1-anticorrelated target genes is quite controversial. It is believed that EWS-FLI1 repression is at least partly mediated via its association with the NuRD repressor complex (Sand 2015). EWS-FLI1 also directly regulates expression of members of the polycomb-repressor complex (EZH2 and BMI-1), which have been shown to be important for EwS transformation (Riggi et al, 2008; Toomey et al, 2010). Furthermore, EWS-FLI1 recruits histone-deacetylases (HDAC) and the polycomb-repressor component lysine-specific demethylase-1 (LSD1), which is also in part responsible for EWS-FLI1-mediated transcriptional repression (Sankar et al, 2013). A study by Niedan et al in 2015 showed that the transcriptional repressor function of Forkhead Box Protein O1A (FOXO1) is directly and indirectly, via CDK2/Akt mediated cytoplasmic retention, inhibited by EWS-FLI1 and constitutes a significant portion of the EWS-FLI1-repressive gene signature (Niedan et al, 2014). Among the EWS-FLI1 targets are several transcription factors per se such as NKX2.2, NR0B1 and GLI1, potentially explaining the global transcriptional effects mediated by EWS-FLI1 (Toomey et al, 2010). NKX2.2 is a transcription factor that harbours both repressor and activator domains. Owen et al showed that a significant portion of the EWS-FLI1-anticorrelated target genes are directly bound by NKX2.2 (Owen et al, 2008). A study from 2006 showed that NKX2.2 is required for oncogenic transformation of EWS-FLI1 (Smith et al, 2006). Knockdown of EWS-FLI1 reduced NKX2.2 protein and RNA levels. A recent study assigned a role in repression of the mesenchymal gene signature and phenotype by NKX2.2 in EwS. NKX2.2 depletion resulted in increased numbers of focal adhesions and stress fibres as well as dramatically altered EwS phenotype, comparable to EWS-FLI1 knockdown. The morphological changes are likely at least in part mediated by the re-expression of the EWS-FLI1/NKX2.2 target gene zyxin. However, only a part of the EwS phenotype is mediated via NKX2.2, the mesenchymal phenotype could not be completely reconstituted upon NKX2.2 knockdown (Fadul et al, 2015).

Hancock et al performed a Significance Analysis of Microarrays (SAM) to compare and define EWS-FLI1 regulated gene sets from different studies. Although they identified great variabilities within the distinct gene-expression datasets they came up with a EWS-FLI1 regulated core-signature of 503 EWS-FLI1-correlated genes and 293 EWS-FLI1- anticorrelated genes. This EWS-FLI1 core signature was also inversely correlated to those of MSCs. Among the EWS-FLI1-correlated genes was the Nuclear Receptor Subfamily 0 Group B Member 1 (NR0B1) (Hancock & Lessnick, 2008), an orphan nuclear receptor that plays a role in the development of the adrenal gland. Kinsey and colleagues demonstrated that NR0B1 is one of the most consistently EWS-FLI1 activated target genes and is required for oncogenic transformation of EwS (Kinsey et al, 2006). Other transcriptional targets of EWS- FLI1 that have been shown to play a role in EwS transformation and tumour-formation are CCND1, MYC, PDGFC, IGF-1, CAV-1, GLI1 as well as TGFBRII and IGFBP3 (Table 2). Another mechanism of indirect transcriptional regulation mediated by EWS-FLI1 is via miRNAs (microRNAs) and long non-coding RNAs (lncRNA) (Ban et al, 2011; Sand et al, 2015).

Table 2. EWS-FLI1 transcriptional targets and their assigned functions (Erkizan et al, 2010).

1.2.2. Chromosomal binding of EWS-FLI1

EWS-FLI1 interacts with the DNA not solely on promoters but also binds intra- and intergenically (Kauer et al, 2009). The fusion-oncogene preferentially binds to purine-rich GGAA sequences, commonly found in ETS motifs and GGAA microsatellites encountered at promoter or enhancer regions (Pishas & Lessnick, 2016). Interestingly, approximately 50% of regions that are bound by EWS-FLI1 are GGAA microsatellites, which have for decades been believed to be “genomic junk” without regulatory functions. Several EWS-FLI1- correlated genes, however, are equipped with multiple GGAA repeats which are specifically bound by EWS-FLI1, suggesting an important role of GGAA repeats in transcriptional activation (Gangwal et al, 2008; Jedlicka, 2010). The strong gene-regulatory effects of EWS- FLI1 likely are a consequence of deregulating events on genetic as well as epigenetic levels. Riggi et al described EWS-FLI1 mediated chromatin remodelling by the fusion-oncogene inducing opening of chromatin at GGAA repeats and hence gene-activation as well as

7 inactivation of conserved enhancer elements leading to transcriptional repression (Riggi et al, 2014). Tomazou, Riggi and others have shown that EWS-FLI1 affects the epigenetic signature of EwS cells and preferentially binds at Histone-3-Lysine-27-acetylation (H3K27ac)-rich enhancer elements, including super-enhancers (Riggi et al, 2014; Tomazou et al, 2015). Several EWS-FLI1-anticorrelated target genes harbour tandem ETS-AP-1 binding sites (Riggi & Stamenkovic, 2007; Tomazou et al, 2015). EWS-FLI1 likely associates with the AP-1 transcription factors Fos and Jun at these regulatory elements (Kim et al, 2006).

1.2.3. Protein-Protein interactions involving EWS-FLI1

EWS-FLI1 is described as an intrinsically disordered protein (IDPs). IDPs are defined by the lack of a specific structure and rapid engagement in large transcriptional complexes with low affinity and high specificity (Erkizan et al, 2010). EWS-FLI1, like EWS, associates with members of the basal transcriptional machinery such as the RNA Pol II subunit RPB7 (Petermann et al, 1998) and TFIID and alters posttranscriptional splicing through direct interaction with the RNA helicase A (RHA) (Erkizan et al, 2015; Toomey et al, 2010). Bilke, Schwentner et al demonstrated an important involvement of E2F transcription factors in the regulation of EWS-FLI1-correlated genes involved in cell cycle regulation likely via direct recruitment of E2F3 and exchange of the repressive E2F4 factor, by EWS-FLI1 (Bilke et al, 2013; Schwentner et al, 2015). Figure 3 illustrates an overview of mechanisms of EWS-FLI1-mediated oncogenic transformation.

Figure 3. Master De-Regulator EWS-FLI1. Overview of the complex EWS-FLI1-driven events in EwS described in chapters 1.2.1.-1.2.3. The majority of EWS-FLI1-driven effects are transcriptional, thereby affecting mRNA expression but also miRNA or lncRNAs have shown to be affected by EWS-FLI1. Direct and indirect transcriptional effects furthermore likely are the sum of direct effects of EWS-FLI1 binding as well as triggered by EWS-FLI1 target gene transcription factors such as NKX2.2, NR0B1, FOXO1 and others. EWS-FLI1 directly interacts with numerous proteins including transcription factors and epigenetic regulators (members of NuRD and PRC complex). Histone acetylation (e.g. H3K27ac) and histone methylation are also affected by EWS-FLI1. Furthermore, EWS-FLI1 affects also post-translational modifications of various signalling proteins (e.g. Akt phosphorylation).

1.3. EWS-FLI1 and the actin cytoskeleton

Although multi-agent-chemotherapy has significantly improved the overall survival rate for patients suffering from EwS in the last two decades, there still is a lack in strategic treatment protocols for the treatment of metastatic and recurrent disease in EwS. It is estimated that the great majority of patients harbour micrometastases, even if not clinically detectable upon diagnosis, since relapse-rates after surgeries are high (Pishas & Lessnick, 2016). Therefore EwS cells are highly prone to early onset of metastasis. The actin cytoskeleton plays a profound role in cellular processes underlying the transformation potential and metastatic capacity of tumour cells (Fife et al, 2014; Yamaguchi & Condeelis, 2007). Amsellem et al reported that the actin-binding protein zyxin1 acts as a tumour suppressor in EwS and its transcript is strongly suppressed by EWS-FLI1. EwS cell lines and primary mouse fibroblasts (NIH3T3) with forced EWS-FLI1 expression were characterized by a strongly disturbed cytoskeletal architecture with disorganized and few focal adhesions and actin-stress fibres. Upon ectopical expression of zyxin the EwS phenotype partly changed towards the

9 mesenchymal lineage (Amsellem et al, 2005). Interestingly, Chaturvedi et al showed that EWS-FLI1 suppresses active cellular processes, such as cell adhesion and migration, rather than promoting them. They proposed a stochastic model of passive EwS cell dissemination where decreased adhesion and cell spreading facilitates initial steps of metastasis. Furthermore, they reported that the three top classes of EWS-FLI1-anticorrelated (repressed) genes are associated with cell structure, extracellular signalling or focal adhesion structure and function. Apart from zyxin1, another EWS-FLI1-anticorrelated gene α-5 integrin (ITGA5) was found to play a crucial role in EwS morphology and metastatic spread. These two candidate genes were shown to promote lung colonization of EwS cells but at the same time hinder cell-proliferation. Hence, the authors came to the conclusion that EWS-FLI1-mediated repression of these genes is advantageous for EwS proliferation and anchorage-independent growth but disadvantageous for second-site colonization of EwS metastases. (Chaturvedi et al, 2014; Chaturvedi et al, 2012). Strikingly, a recent publication by Franzetti et al demonstrated that EWS-FLI1 expression is highly heterogenous in EwS cell lines and that cells toggle between EWS-FLI1-high and EWS-FLI1-low cell states. The EWS-FLI1-high state is characterized by pronounced proliferation whereas the EWS-FLI1-low state is defined by attenuated proliferation and enhanced migration involving substantial cytoskeletal rearrangements. The authors came to the conclusion that EwS cellular plasticity underlying metastasis is determined by this switch from EWS-FLI1-high proliferative to EWS-FLI1-low migratory states (Franzetti et al, 2017). Overall EwS cellular morphology seems to be strongly disrupted by EWS-FLI1, mainly through genome-wide gene-repression of genes involved in cell morphology, adhesion and migration.

1.4. The Rho pathway

Dynamic cellular processes typically involve the actin cytoskeleton, predominantly regulated via the Rho pathway. The Ras-homologue (Rho) proteins of the Ras superfamily of GTPases (Etienne-Manneville & Hall, 2002) were first characterized in 1992 (Ridley & Hall, 1992). Rho GTPases comprise ten major classes, among them the Rho-like, Rac-like, RhoBTB and CDC42 proteins, with several subfamily members (Figure 4). There exist three forms of Rho proteins, RhoA, B and C which share approximately 85 % of amino-acid homology. Rac proteins, consisting of Rac 1, 2 and 3 are also highly homologous (80 % identity). Rho GTPases control processes underlying the dynamic rearrangement of the actin cytoskeleton whereas Rac1 and CDC42 regulate membrane ruffling and formation of membrane protrusions (filopodia) (Burridge & Wennerberg, 2004; Parri & Chiarugi, 2010).

Figure 4. Rho family of GTPases. (Burridge & Wennerberg, 2004)

1.4.1. Rho GTPases

Rho proteins are small (~21 kDa) G-proteins which function as a molecular switch in tuning processes such as adhesion, migration, cell-cycle progression and proliferation. For their activation they depend on the conversion of a bound guanine-diphosphate (GDP) to guanine- triphosphate (GTP) molecule, catalysed by their intrinsic GTPase activity. This process is amplified by guanine-exchange factors (GEFs) (Olson & Nordheim, 2010; Rossman et al, 2005).

Figure 5. The Rho GTPase activation cycle. GEF= guanine-exchange factor; GDI= Guanine nucleotide dissociation inhibitors GAP= GTPase activating enzymes. Rho-GTP= active, guanine-triphosphate bound Rho; Rho-GDP= inactive, guanine-diphosophate bound Rho. (Etienne-Manneville & Hall, 2002).

Numerous cell surface receptors such as G-protein-coupled receptors (GPCR), integrin- receptors and cytokine-receptors induce activation of GEFs. Of note Rho GTPases are activated via more than 60 different Rho-GEFs resulting in a vast diversity of signals that are integrated in Rho GTPase activation. In order to inactivate the activity of Rho, GTP is hydrolysed to GDP triggered by the action of GTPase activating enzymes (GAPs). Approximately 60 different GAP proteins are known in humans. Another class of molecules, the Rho guanine nucleotide dissociation inhibitors (GDIs) bind to and prevent the conversion 11 from Rho-GDP to Rho-GTP as well as sequester Rho-GDP in the cytosol away from their effectors (Etienne-Manneville & Hall, 2002; Karlsson et al, 2009; Rossman et al, 2005). Figure 5 illustrates the cycle of Rho GTPase activation/inactivation, mediated by GEFs, GAPs and GDIs. Rho GTPases are prenylated at their C-terminus, which is required for their interaction with the plasma membrane. Upon activation via GDP to GTP exchange, Rho is able to interact with its effectors (Etienne-Manneville & Hall, 2002; Seabra, 1998).

1.4.2. Function of Rho GTPases

The Rho pathway is a crucial mediator of several cellular processes. It regulates cellular motile processes involving adhesion, which requires changes in cell-cell and cell-ECM, contraction and guided movements of the cell by linking actin turnover to the transcriptional machinery (Olson & Nordheim, 2010). Furthermore, the Rho pathway is crucially involved in the regulation of cell-cycle progression, differentiation, endocytosis, protein secretion and vesicle trafficking. In fact the majority of cellular activities is directly or indirectly affected by Rho signalling (Burridge & Wennerberg, 2004). Rho GTPases are moreover involved in malignancy by affecting tumour cell proliferation, invasion, angiogenesis and evasion from apoptosis (Parri & Chiarugi, 2010). Rho GTPases are key-players in Epithelial to Mesenchymal Transition (EMT) as well as Mesenchymal to Amoeboid Transition (MAT), processes that are prerequisites of cellular plasticity (Sahai & Marshall, 2002). Metastasis is a multi-step process where a high degree of cellular plasticity in terms of response to microenvironmental stimuli is conducive (Parri & Chiarugi, 2010; Yilmaz & Christofori, 2010).

1.4.3. Ligand-Receptor induced Rho pathway activation

The first ligand, which was identified to induce Rho-signalling is the lysophosphatidic acid (LPA), which binds to GPCR. Treatment of serum-starved fibroblasts (Swiss 3T3 cells) led to stress-fibre formation and assembly of focal adhesions, which could be prevented by treatment with the Rho inhibitor C3 transferase (Ridley & Hall, 1992). GPCR receptors are a large class of seven α-helix transmembrane receptors that signal to Rho GTPases. Upon ligand binding GPCRs expose their intracellular site which interacts with heterotrimeric G- proteins and induces the exchange of GDP with GTP from their α-subunit. The α-subunit is then released from the G-protein and activates several downstream effectors among them members of the Rho and Ras family mainly via activation of Rho-GEFs (Aittaleb et al, 2010; Dorsam & Gutkind, 2007).

Figure 6. Activation of Rho via ligand-receptor (GPCR) interaction. GPCR signalling activates heterotrimeric G-proteins, which in turn activate several GPCR effectors including Rho-GEFs and Rho directly. (Dorsam & Gutkind, 2007).

Apart from LPA, GPCR can also be activated by sphingosine-1-phosphate (S1P), bombesin, thrombin and endothelin. GPCRs are frequently overexpressed in cancer and are known to play a role in tumour growth and metastasis (Kjoller & Hall, 1999). Tumour cells that express the GPCR CXCR4 have been shown to migrate towards a S1P gradient (Dorsam & Gutkind, 2007). CXCR4 is the most common expressed chemokine receptor on tumour cells, frequently overexpressed. In EwS, CXCR4 expression has been correlated with metastatic disease and poor prognosis (Bennani-Baiti et al, 2010). Another study described heterogeneous and dynamic expression levels of CXCR4 on EwS cells, which responded to microenvironmental stimuli. Interestingly, the CXCR4 ligand CXCL12 (SDF-1α) is strongly expressed in organs which are prone to EwS metastasis formation such as the lungs and bones. Mechanistically, in EwS cells Krook et al could inhibit CXCR4 mediated migration and invasion by treatment with Rac-1 and CDC42 inhibitors (Krook et al, 2014). Further receptors that activate Rho signalling are tyrosine-kinases (e.g. PDGF, VEGF, EGF, FGF), integrin receptors, Serine/Threonine kinase receptors and the frizzled receptor which activates Wnt signalling (Olson & Nordheim, 2010).

1.4.4. The Rho-actin-MRTF-SRF circuit

Upon activation of Rho GTPase (discussed in chapter 1.4.1 and 1.4.3) they interact with approximately 60 different effectors in humans (Etienne-Manneville & Hall, 2002). The vast majority of Rho downstream effectors is involved in cytoskeletal processes. The best described among them are the Rho-associated coiled-coil forming kinase (ROK/ROCK) and the mammalian homologue of Drosophila diaphanous (mDIA). Dia is a formin family member which is required for actin-filament assembly via nucleation and polymerization of globular (G) to filamentous (F) actin. ROCK, a Ser/Thre kinase, promotes crosslinking of actin with myosin, creating actin-myosin bundles (stress-fibres) which are important for contractility and movement. ROCK is typically regulated downstream of Rho proteins, whereas mDIA is typically a Rac effector protein. The balance of ROCK and mDIA is crucial for the regulation of motility (Olson & Nordheim, 2010) (Narumiya et al, 2009). ROCK targets are involved in actin-myosin fibre formation and include the myosin-light chain (MLC) phosphatase, the LIM kinase (LIMK) and the citron kinase. Other ROCK substrates are adducin, which binds to F- actin, and the ezrin/radixin/moesin (ERM) complex, which links actin to the plasma membrane. Dia binds to profilin upon activation which promotes actin polymerization and stress-fibre formation (Bishop & Hall, 2000). The linkage between Rho activation and gene transcription is established via the actin-binding transcriptional co-activator myocardin-related transcription factor (MRTF), which is in an inactive state bound to G-actin in the cytosol. Upon polymerization of G- to F-actin, MRTFs are liberated and free to translocate to the nucleus, where they interact with the universal transcription factor serum-response factor (SRF) and co-regulate the expression of several cytoskeletal target genes. Figure 7 illustrates the Rho-actin-MRTF-SRF circuit, which is an autoregulatory feedback loop. Actin polymerization regulates transcriptional activity via MRTF subcellular localization, in turn several actin-binding proteins (ABPs) as well as actin itself are transcriptionally regulated by MRTF-SRF (Asparuhova et al, 2009; Olson & Nordheim, 2010).

Figure 7. The Rho-actin-MRTF-SRF autoregulatory circuit. Extracellular ligands activate Rho signalling via seven classes of transmembrane receptors thereby promoting activation of Rho GTPase by Rho-guanine nucleotide exchange factors (GEFs). The Rho kinase (ROCK) promotes G-to F-actin polymerization via the LIM kinase (LIMK). Upon actin polymerization MRTFs translocate to the nucleus where they interact with SRF and regulate transcription of cytoskeletal genes and of actin, fueling the autoregulatory-feedback of the actin-cytoskeleton. (Olson & Nordheim, 2010).

1.4.5. The serum-response factor SRF

SRF is a highly conserved MADS (MCM1, Agamous, Deficiens, SRF) box transcription factor, which controls expression of immediate early genes (IEG) as well as cytoskeletal genes (Miralles et al, 2003; Pipes et al, 2006; Wang et al, 2002). The MADS box domain enables SRF to form homo-dimers on the DNA (Pipes et al, 2006). SRF was originally identified due to its binding to specific elements in the c-fos promoter of Hela cells in response to serum (Prywes & Roeder, 1987; Treisman, 1987). These so called serum- response elements (SRE), which contain single or multiple copies of CC(A/T)6GG called CArG box, are frequently encountered in the promoters of muscle-differentiation or IEG (Morita et al, 2007b). Sun et al identified more than hundred genes containing CArG elements within 4kB of the TSS, the majority being SRF target genes and approximately a third of them cytoskeletal genes (Sun et al, 2006).

The physiological role of SRF

SRF is a ubiquitously expressed master regulator of cell growth, differentiation and motility (Morita et al, 2007b; Pipes et al, 2006). SRF null mice exhibit significant defects in gastrulation and mesoderm development (Arsenian et al, 1998) and are defective in stress fibre and focal adhesion formation (Schratt et al, 2002). In a stable complex with the strong transcriptional co-activator myocardin, SRF transcriptionally regulates the development of smooth-, cardiac and skeletal-muscles (Pipes et al, 2006).

Co-activators/ repressors of SRF

SRF switches between different cellular programs by association with its different proteins and therefore influences a wide variety of cellular functions (Gualdrini et al, 2016; Miano et al, 2007). SRF co-factors either positively (co-activators) or negatively (co-repressors) regulate its transcriptional activity. In order to activate gene expression, SRF primarily interacts with two major classes of transcriptional co-activators (Olson & Nordheim, 2010). The ternary complex factor family (TCFs) are regulated downstream of Ras-MAPK signalling and activated by phosphorylation. TCFs are ETS factors that contact the DNA (ETS site) adjacent to CArG boxes to form a ternary complex with SRF and the DNA. The second class of transcriptional co-activators are the MRTFs, regulated downstream of Rho-actin signalling. Unable to directly bind to the DNA, MRTFs compete with TCFs for association with SRF. Since MRTFs and TCFs bind to the same domain on SRF, their binding is mutually exclusive. Depending on the recruited transcriptional co-activator SRF activates distinct subsets of target genes (Posern & Treisman, 2006). SRF-TCF co-regulate IEG expression in 16 response to mitogenic stimuli (e.g. serum) whereas SRF-MRTF activate transcription of mostly cytoskeletal target genes (Figure 8).

Figure 8. The Rho and Ras pathways are involved in SRF transcriptional activation. (Posern & Treisman, 2006).

Other co-activators of SRF are the zinc-finger transcription factors of the GATA family and NKX2-2. Known SRF co-repressors are the heart-enriched homeodomain cofactor (HOP) and FHL-2, a Lim-only protein (Posern & Treisman, 2006).

1.4.6. The myocardin-related transcription factors (MRTF)

MRTFs, comprising MRTFA (MKL-1, MAL, BSAC) and MRTFB (MKL-2, MAL16), were identified according to their high homology to the muscle-gene regulator myocardin. MRTFs are ubiquitously expressed, actin-sensitive transcriptional co-activators, which regulate proliferation, migration and myogenesis. In contrast to MRTFs, myocardin is a constitutively active (nuclear) transcriptional co-activator specifically expressed in cardiac, skeletal and smooth muscle cells (Morita et al, 2007b; Pipes et al, 2006; Posern & Treisman, 2006). MRTFA is also termed MAL due to its initial discovery as part of the oncogenic fusion protein OTT-MAL (t(11;22)) in acute megakaryocytic leukaemia (AMKL) (Ma et al, 2001). Knockout of MRTFA causes abnormal development of myoepithelial cells (Li et al, 2006). MRTFB null mice, however, are embryonically lethal with severe cardiovascular defects (Oh et al, 2005). Experiments with dominant-negative MRTFs, which compete with the endogenous proteins for SRF binding, have shown that at the cellular level MRTFs mediate the formation of focal adhesions and stress fibres (Morita et al, 2007a).

MRTF expression and regulation

MRTFA and MRTFB are ubiquitously expressed. MRTFA, however, is strongly enriched in mesenchymal stem cell during embryogenesis and highly expressed in adult lung, kidney, spleen, brain, skeletal muscle and the heart (Wang et al, 2002). Expression of MRTFB is highest in neural-crest derived arteries (Pipes et al, 2006). In serum-starved fibroblasts MRTFs constantly toggle between the nucleus and cytoplasm, mediated by CRM-1 driven nuclear export (Vartiainen et al, 2007). The rate of the nuclear export is dependent of the ratio of monomeric to polymerized actin since binding to nuclear G-actin promotes CRM-1 dependent MRTF export, and binding to cytoplasmic G-actin impedes MRTF nuclear import. Stimulation with serum reduces the amount of free G-actin due to Rho-mediated actin polymerization and triggers translocation of MRTF to the nucleus (see also chapter 1.4.4). The actin cytoskeleton hence is the most important regulator of MRTF cellular distribution and activity. On the other hand MRTFs regulate the actin cytoskeleton transcriptionally as Rho-actin downstream effectors (Posern & Treisman, 2006). In many cell types, apart from fibroblasts, MRTF activity is determined by their actin-dependent subcellular localization, however, some cells also exhibit constitutively nuclear MRTF (rat aortic cells) (Medjkane et al, 2009).

Structure of MRTFs

The N-terminal region of MRTFs is strongly conserved and contains two to three RPEL domains, which are required for the interaction with monomeric actin. The basic and glutamine rich-region, also called B-box, is crucial for the interaction with SRF and is also involved in MRTF nuclear localization. The function of the SAP domain is less well characterized. It is assumed that it is important for nuclear localization of MRTFs but does not affect its transcriptional activity. The leucine-zipper domain mediates MRTFA and MRTFB homo- or heterodimerization. A strong transcriptional transactivation domain is located at the MRTF C-terminus (Figure 9). MRTFs require the interaction with a transcription factor for conducting transcriptional activity (Asparuhova et al, 2009; Pipes et al, 2006). In SRF null mice MRTFs are unable to activate SRF target gene expression (Wang et al, 2002). MRTFs, however, also engage with other transcription factors than SRF such as the Smad transcription factors (Morita et al, 2007b). Furthermore, it has been shown that MRTFA is phosphorylated at serine 454 by the signal- regulated kinase ERK1/2 which increases its affinity for nuclear G-actin and hence export into the cytoplasm. This protein modification serves as another layer of competition between Rho and Ras effector proteins (Muehlich et al, 2008).

Figure 9. MRTF protein structure. RPEL domains mediate binding to monomeric actin. The basic and glutamine (Q)-rich region are involved in binding to SRF. The SAP domain is involved in target gene discrimination and the leucine-zipper like domain is important for MRTF homo- or heterodimerization. The transcriptional activation (TAD) domain is potent in enhancing transcriptional activity of the MRTF partner. Adapted from (Mikhailov & Torrado, 2012) and (Cen et al, 2004).

1.4.7. MRTFs and their role in cancer and disease

MRTFs play versatile roles in tissue development and disease. It has been shown that they regulate adipocyte differentiation (Nobusue et al, 2014), cardiovascular- (Mokalled et al, 2015) and megakaryocyte development (Smith et al, 2012). MRTFA is pathogenically involved in AMKL development in children (see also chapter 1.4.6) and coronary artery disease in adults (Hinohara et al, 2009). Due to their known role in the regulation of the actin cytoskeleton it is also not surprising that MRTFs are frequently involved in EMT and metastasis of many cancers (Charbonney et al, 2011; Morita et al, 2007a). In breast carcinoma and melanoma cells MRTFs depletion reduced cell migration and metastasis formation is mouse-xenografts (Medjkane et al, 2009). Via expression of MYL9 and CYR61 MRTFA and the transcription factor STAT3 were shown to synergistically drive breast cancer metastasis (Liao et al, 2014). Depending on the cellular context, MRTFs exert tumour suppressive or tumour promoting functions (Scharenberg et al, 2010). Yoshio et al reported that transfection of constitutively-active (CA) MRTF (A and partly also B) reversed the tumorigenic phenotype of ras or src-induced rat intestinal epithelial cells via stress-fibre restoration (see also discussion) (Yoshio et al, 2010).

1.4.8. Alternative pathways downstream of Rho: crosstalk between MRTF and YAP/TAZ

Apart from MRTF there is also another transcriptional axis that can be activated by Rho- actin, involving the mechano-sensitive factors YAP/TAZ. Typically inhibited by canonical Hippo signalling, the Yes-associated protein 1 (YAP) and its paralogue the Transcriptional co-activator with PDZ-binding motif (TAZ) are involved in proliferation and apoptosis (Huang et al, 2005). By controlling YAP/TAZ activity the highly conserved Hippo pathway serves as an important regulator of organ size and tissue homeostasis. The Hippo kinases Lats1/2,

19 which are activated by Mst1/2, control YAP/TAZ activity by phosphorylation leading to its proteosomal degradation and inhibition of nuclear import (Sharili & Connelly, 2014) (Figure 10A). However, another upstream mechanism which is in part independent of Hippo regulation via Rho-triggered actin-polymerization has also been described to promote nuclear YAP/TAZ and target gene activation in response to chemo- or mechanotransduction (Figure 10B). Like MRTFs YAP/TAZ do not carry a DBD and require interaction with a transcription factor, typically the TEA domain binding factors (TEAD) (Yu & Brown, 2015).

Figure 10. Different modes of YAP/TAZ regulation. A. Canonical Hippo signalling inhibits YAP/TAZ nuclear import by phosphorylation and subsequent proteosomal degradation. B. YAP/TAZ nuclear translocation is promoted by actin-polymerization downstream of Rho, partly involving Lats1/2 inhibition. (Halder et al, 2012).

YAP/TAZ are frequently overexpressed in cancer and are involved in tumorigenesis, cancer stemness and chemoresistance (Guo & Zhao, 2013; Halder et al, 2012; Overholtzer et al, 2006). Interestingly, recent work suggests that MRTF and YAP/TAZ have more in common than just the regulation of their subcellular localization. Yu et al showed that both MRTFA and YAP-1 are required for TEAD-dependent target gene regulation upon S1P-dependent RhoA activation. The “bona-fide” YAP/TAZ target genes connective-tissue growth factor (CTGF, CCN2) and cysteine-rich domain 61 (CYR61), which are also regulated by MRTF, are strongly implicated in tumorigenesis. Moreover, the crosstalk between MRTFs and YAP/TAZ has now been linked to metastasis in breast cancer cells in vitro and in vivo (see also discussion) (Kim et al, 2016).

1.5. Aims of this thesis

The overall aim of this thesis was to investigate a potential deregulation of the Rho transcriptional effectors MRTFA/B in EwS by EWS-FLI1. Characterization of the MRTF transcriptional profiles upon high- or low-EWS-FLI1 levels was a primary goal of this thesis as well as to study the influence of serum on MRTFA/B target gene regulation in EwS as compared to osteosarcoma (OS), a bone cancer lacking the EWS-ETS fusion. We observed a striking effect of MRTFA/B knockdown on the EWS-FLI1 transcriptome and therefore aimed at further elucidation of the underlying mechanisms using ChIP-sequencing. We characterized the genome-wide binding patterns of MRTFA, MRTFB, SRF and EWS-FLI1 upon high or low levels of the fusion oncogene and under different serum conditions. A further goal was to determine potential functional consequences of MRTFA/B depletion in EwS cells, depending on EWS-FLI1 presence. We performed wound-healing migration and soft agar assays and observed strong effects of MRTFA/B on the growth of EwS cells under anchorage-independent conditions as well as on migration.

Finally we came up with a new hypothesis, generated from our results obtained by expression profiling and ChIP-sequencing, which led us to investigate a potential crosstalk of MRTFB with the YAP/TAZ/TEAD axis downstream of Rho-F-actin. We confirmed binding of MRTFB, YAP-1 and TEAD to distal enhancers of EWS-FLI1-anticorrelated target genes, many of them cytoskeletal keyplayers. Our data led us to propose a model that potentially explains how varying expression levels of the pathognomonic fusion protein EWS-FLI1 transcriptionally influence regulators of cytoskeletal remodelling, ultimately resulting in high cellular plasticity that enables cells to efficiently metastasize.

CHAPTER TWO: Results

2.1. Prologue

The actin-cytoskeleton is a versatile mediator of cellular inputs that need to be communicated to the transcriptional machinery for the responsive outputs. Previous studies alongside with unpublished observations from our group have strengthened the idea that the large number of cytoskeletal genes, which are repressed by EWS-FLI1, could be the result of a genome-wide perturbation of the cytoskeletal regulator, the Rho pathway. We therefore interrogated a potential dysregulation of the Rho transcriptional effectors MRTFA/B by the fusion oncogene EWS-FLI1. In the following manuscript “EWS-FLI1 perturbs MRTFB/YAP-1/TEAD target gene regulation inhibiting cytoskeletal auto-regulatory feedback in Ewing sarcoma” we show that MRTFA/B transcriptional function is overall repressed by EWS-FLI1. Furthermore, MRTFA and especially MRTFB strongly antagonize EWS-FLI1-mediated gene expression effects when EWS-FLI1 transcript levels are low (knockdown vs control). Our findings led us to interrogate the nature of the transcriptional repression of MRTFB by EWS-FLI1 and we identified inhibition of crosstalk of MRTFB with YAP-1/TEAD as likely being the underlying mechanism of this deregulation. As a consequence, we found that several important key players of cytoskeletal signalling, which are strongly repressed by EWS-FLI1, are reactivated via MRTFB/TEAD transcriptional activity.

2.2. Manuscript by Katschnig A.M. et al. “EWS-FLI1 perturbs MRTFB/YAP-1/TEAD target gene regulation inhibiting cytoskeletal auto-regulatory feedback in Ewing sarcoma.”

EWS-FLI1 perturbs MRTFB/YAP-1/TEAD target gene regulation inhibiting cytoskeletal autoregulatory feedback in Ewing sarcoma.

Anna M. Katschnig1, Maximilian O. Kauer1, Raphaela Schwentner1, Eleni M. Tomazou1, Cornelia N. Mutz1, Markus Linder2, Maria Sibilia2, Javier Alonso3, Dave N.T. Aryee 1,4, and Heinrich Kovar1,4

1Children's Cancer Research Institute, St. Anna Kinderkrebsforschung, Vienna, Austria. 2Institute of Cancer Research, Medical University Vienna, Vienna, Austria. 3Unidad de Tumores Solidos Infantiles, Instituto de Investigación de Enfermedades Raras, Madrid, Spain. 4Department of Pediatrics, Medical University Vienna, Vienna, Austria.

running title: EWS-FLI1 perturbs MRTFB/YAP-1/TEAD

Keywords: Ewing sarcoma; Rho-actin; MRTF; YAP; TEAD

Additional information

Financial support: This study was supported by the Liddy Shriver Sarcoma Initiative and by the European Commission Framework Program 7 grant 259348 (“ASSET”).

Corresponding author: Prof. Heinrich Kovar. Children’s Cancer Research Institute/ St. Anna Kinderkrebsforschung. Zimmermannplatz 10, 1090 Vienna, Austria. Phone: +43(1)40470-4092. Fax: +43(1)40470-7150. [email protected].

Conflict of interest: the authors declare no conflict of interests. word count: 4971 ; total number of figures: 6

Abstract

Ewing sarcoma is a pediatric bone cancer with high metastatic potential. Cellular plasticity resulting from dynamic cytoskeletal re-organization, typically regulated via the Rho-pathway, is a prerequisite for metastasis initiation. Here, we interrogated the role of the Ewing sarcoma driver oncogene EWS- FLI1 in cytoskeletal reprograming. We report that EWS-FLI1 strongly represses the activity of the Rho- F-actin signal pathway transcriptional effector MRTFB, affecting the expression of a large number of EWS-FLI1-anticorrelated genes including structural and regulatory cytoskeletal genes. Consistent with this finding, ChIP-seq revealed strong overlaps in MRTFB and EWS-FLI1 chromatin occupation, especially for EWS-FLI1-anticorrelated genes. Binding of the transcriptional co-activator YAP-1, enrichment of TEAD binding motifs in these shared genomic binding regions and overlapping transcriptional footprints of MRTFB and TEAD factors led us to propose synergy between MRTFB and the YAP/TEAD complex in the regulation of EWS-FLI1-anticorrelated genes. We propose that EWS- FLI1 suppresses the Rho-actin pathway by perturbation of a MRTFB/YAP-1/TEAD transcriptional module, which directly affects the actin-autoregulatory feedback loop. As spontaneous fluctuations in EWS-FLI1 levels of Ewing sarcoma cells in vitro and in vivo, associated with a switch between a proliferative, non-migratory EWS-FLI1-high and a non-proliferative highly migratory EWS-FLI1-low state, were recently described, our data provide a mechanistic basis for the underlying EWS-FLI1 dependent reversible cytoskeletal reprograming of Ewing sarcoma cells.

Introduction

Ewing sarcoma (EwS) is the second most common bone malignancy affecting children and adolescents. This highly aggressive cancer is prone to early tumor dissemination and about a quarter of patients present with overt metastases at initial diagnosis (1). Pathways underlying metastatic processes in EwS are still poorly investigated (2). EwS is characterized by the expression of an oncogenic ETS fusion product, most frequently EWS-FLI1, which drives proliferation and represses differentiation via global genetic and epigenetic deregulation (3-5). In particular, EWS-FLI1 affects expression of hundreds of genes either by up-regulation (EWS-FLI1-correlated genes), or repression (EWS-FLI1-anticorrelated genes) (6, 7). There is emerging evidence of EWS-FLI1 deregulating processes underlying cellular plasticity. In particular, a substantial part of EWS-FLI1 driven transcriptional repression affects genes involved in cytoskeletal processes such as adhesion and anchorage-independent growth (8-10). The major signaling cascade linking extracellular mechanic and chemical inputs to gene expression is the Rho-F-actin pathway (11). Ligand-induced activation of transmembrane receptors (integrins, TGFβR, GPCR, Frizzled), stimulates the conversion of GDP- to GTP-bound Rho by guanine nucleotide exchange factors (GEFs). Rho downstream effectors promote polymerization of monomeric G-actin to F-actin fibers. The transcriptional co-activators myocardin- related transcription factors (MRTF) are tightly bound to G-actin in the cytoplasm. Upon depletion of G-actin, MRTFs are released and translocate to the nucleus where they interact with cofactor- dependent transcription factors, typically with serum response factor (SRF) on CCW6GG (CArG) elements. Depending on the recruited co-activator, such as the ternary complex factor family (TCFs) or MRTFs, SRF regulates distinct sets of target genes. MRTFs, which comprise MRTFA (MKL-1, MAL, BSAC) and MRTFB (MKL-2), are key effectors of the cytoskeletal auto-regulatory feedback-loop by mediating transcription of numerous cytoskeletal genes in a Rho-actin dependent manner (12, 13). Furthermore, MRTFs were reported to play an important role for the metastatic propensity of aggressive cancer cell lines (14, 15).

In this study we aimed at understanding the molecular mechanism by which EWS-FLI1 compromises genome-wide Rho-actin mediated transcription in EwS. We demonstrate overall repression of MRTFA/B transcriptional activity by EWS-FLI1 and a strong overlap of MRTFB and EWS-FLI1 chromatin occupation. Furthermore, we show that TEA domain (TEAD) and YAP-1 transcription factors bind to shared MRTFB/EWS-FLI1 targets, specifically of EWS-FLI1-anticorrelated genes. TEADs act as downstream transcriptional mediators of the mechano-sensitive Hippo/YAP/TAZ signaling pathway. Like MRTFA/B, nuclear translocation and thereby activation of YAP/TAZ can also be regulated via Rho/F-actin (16, 17). Here, we provide evidence that EWS-FLI1 affects Rho/actin

signaling in EwS by perturbation of MRTFB/YAP-1/TEAD target gene regulation leading to deregulation of the cytoskeletal auto-regulatory feedback-loop.

Results

Rho target genes are repressed by EWS-FLI1 in EwS

To identify pathways deregulated in EwS we compared published gene expression data-sets from EwS primary tumors (18) to the putative EwS precursors mesenchymal stem cells (MSC) (19, 20). Gene-set enrichment analysis (GSEA) identified a significant overrepresentation of Rho-pathway components among genes repressed in EwS. More specifically we found that expression of genes involved in migration and response to serum and RhoA signaling is compromised in EwS tumors as compared to MSCs (Fig. 1A). To validate suppression of a Rho signature in EwS cells, we interrogated expression of a manually curated set of 14 well characterized Rho/SRF/MRTF target genes (21, 22) in five EwS cell lines (WE68, TC252, SK-N-MC, ET7, ET1) (6) from previously published expression data (GSE14543) with a transient EWS-FLI1 knockdown (Fig. 1B: left panel). Depletion of EWS-FLI1 resulted in upregulation of the majority of genes in this gene-set in all cell lines tested. We recapitulated these results further in another EwS cell line, A673/TR/shEF, where EWS-FLI1 levels can be easily modulated from endogenous (high) levels to low-levels (Fig. 1B: right panel, Supplementary Fig. 1A). A panel of genes was additionally analyzed by q-RT-PCR upon EWS-FLI1-high and -low states in A673/TR/shEF. Expression of zyxin (ZYX), vinculin (VCL) and transgelin (TAGLN) was strongly induced under EWS-FLI1-low conditions while no significant change in SRF mRNA was observed (Supplementary Fig. 1B). These data are consistent with suppression of Rho-mediated transcription by EWS-FLI1 in EwS.

MRTFB knockdown antagonizes the transcriptional effects of EWS-FLI1 depletion

After confirming overall repression of Rho target genes by EWS-FLI1 in EwS, we hypothesized that gene expression via the Rho transcriptional activators MRTFA/B might be suppressed by EWS-FLI1. To study the effects of EWS-FLI1 on the MRTFA/B regulated transcriptome, gene expression analysis was performed upon modulation of MRTFA/B under EWS-FLI1-high and -low conditions. Effective reduction of MRTFA and MRTFB protein was achieved using a double-targeting shRNA vector (23), which was combined with doxycycline (dox) treatment to induce the knockdown of EWS-FLI1 (Fig. 2A and Supplementary Fig. 2A). In order to define the role of serum-stimulation for MRTFA/B target gene expression, cells were analyzed under serum-starved and serum-induced conditions. An overview of all conditions studied can be found in Supplementary Table 1. With the exception of only

few genes, little influence of serum on overall (Supplementary Fig. 2B and Supplementary Table 4) and MRTFA/B dependent gene expression (Fig. 2B and Supplementary Table 3) was observed. Differential gene expression analysis revealed that gene sets affected by EWS-FLI1 knockdown and those affected by MRTFA/B knockdown did not correlate (Fig. 2C: upper left plot).

We then studied the combined effect of EWS-FLI1 and MRTFA/B knockdown on gene expression. Interestingly, MRTFA/B knockdown in cells expressing low levels of EWS-FLI1 significantly reversed the gene expression changes induced by EWS-FLI1 depletion. Figure 2C shows that genome-wide gene-expression changes upon MRTFA/B depletion antagonized the effects of EWS-FLI1 depletion upon combined knockdown (Fig. 2C: upper right plot). The impact of MRTFA/B knockdown on the EWS-FLI1 regulated transcriptome and therefore the strength of the inverse correlation was similar under serum-starved (Supplementary Fig. 2C) and serum-induced conditions (Fig. 2C). This further suggests that serum has a rather small effect in these cells. The results from this RNA expression analysis in the A673/TR/shEF cell line were validated in the EwS cell-line SK-N-MC by co-transfection of short-hairpin constructs targeting EWS-FLI1 and MRTFA/B (Fig. 2C) followed by RNA-seq analysis. Even though the knockdown efficiency of EWS-FLI1 was weaker in SK-N-MC than in A673/TR/shEF (Supplementary Fig. 2D and 2A), the antagonism between MRTFA/B and EWS-FLI1 became also evident in SK-N-MC (Fig. 2C: lower-right plot). Taken together these data suggest that a large number of EWS-FLI1 target genes are antagonistically regulated by MRTFA/B when transcript levels of the fusion oncogene are low.

Next, we categorized genes into clusters according to the differential effects of EWS-FLI1 and MRTFA/B depletion on their expression levels. For this analysis a cutoff of |logFC|>1, p<0.05 was chosen for the EWS-FLI1 knockdown and |logFC|>0.7, p<0.05 for the combined MRTFA/B-EWS-FLI1 knockdown. Using this level of stringency, 390 genes are activated by EWS-FLI1 and are further referred to as EWS-FLI1-correlated target genes in the remainder of the text (Fig. 2D). For 87 of these genes, MRTFA/B knockdown rescued the decline in expression upon EWS-FLI1-depletion. On the other hand EWS-FLI1 repressed the expression of 1076 genes in A673/TR/shEF, further referred to as EWS-FLI1-anticorrelated genes, and MRTFA/B knockdown antagonized this effect for 166 of these genes. Using a more stringent cutoff for differential gene expression (|logFC|>1.5, p<0.05), prime targets of MRTFA/B regulation were identified, and subsequently unsupervised hierarchical clustering was used to identify clusters of differential EWS-FLI1/MRTFA/B response. Five distinct clusters of differential EWS-FLI1/MRTFA/B response were observed (Fig. 2E). Cluster 1 and 2 represent EWS-FLI1-anticorrelated gene-sets, whose activation upon EWS-FLI1 depletion was counteracted by MRTFA/B knockdown. Cluster 3 represents genes activated in response to MRTFA/B knockdown in presence of high EWS-FLI1, but even stronger under EWS-FLI1-low conditions. Cluster

4 contains EWS-FLI1-correlated target genes that show increased expression after the MRTFA/B knockdown under EWS-FLI1-low but not -high conditions. In contrast, cluster 5 comprises EWS-FLI1- correlated genes strongly affected by MRTFA/B knockdown primarily under EWS-FLI1-high conditions. The inverse effects of MRTFA/B and EWS-FLI1 were further validated by q-RT PCR for selected genes from cluster 2 (HPGD, GAS2, MAP2) and cluster 4 (NR0B1, RAD51AP1, MCM10) (Supplementary Fig. 2E).

Subsequently, we sought to separately study the effects of MRTFA and MRTFB on the EWS-FLI1 transcriptome. To this end, MRTFA and MRTFB were individually silenced using specific siRNAs (Supplementary Table 2 and Fig. 2F). Under comparable knockdown efficacies, MRTFB mediated the antagonistic effect on EWS-FLI1 target gene regulation to a higher degree (R=-0.66) than MRTFA (R=- 0.36) upon EWS-FLI1-low levels. Knockdown of MRTFA or MRTFB upon high-EWS-FLI1 resulted in a weak positive correlation with the gene-expression effects of EWS-FLI1 knockdown (Supplementary Fig. 2G). The results for the individual MRTFs are consistent with the results obtained with sh- MRTFA/B, however, MRTFB can be inferred as the main driver of the transcriptional rescue from the EWS-FLI1 knockdown.

MRTFB and EWS-FLI1 overlap in chromatin binding

Since MRTFB transcriptional effects antagonized the effects of EWS-FLI1 much stronger than MRTFA we continued our study focusing on MRTFB. Transcriptomic analysis revealed that MRTFB mediated gene regulation was inhibited in the presence of EWS-FLI1. To more closely investigate the molecular mechanisms underlying this repression, chromatin-immunoprecipitation for MRTFB, SRF and EWS- FLI1, coupled with next-generation sequencing (ChIP-seq) was performed (Fig. 3). Since FLI1 is not expressed in EwS cells (24), a FLI1 antibody was used to specifically precipitate EWS-FLI1. The genome-wide distribution pattern observed for EWS-FLI1 chromatin binding recapitulated previously published results, with predominant binding to distal enhancers and less frequent binding in proximal gene promoter regions (7, 25, 26). The majority of MRTFB ChIP-seq peaks, in contrast, were found in proximity of transcriptional start sites (TSS) (52%). Concordant with previous studies (27), genome-wide SRF binding distribution showed approximately 40% of peaks being >2 kb away from the TSS. Only about 19% of SRF peaks were found within the TSS proximity (Fig. 3A). Using stringent cutoffs (q-value from MACS <10E-10) 11737 MRTFB peaks, 54881 EWS-FLI1 peaks and 32515 SRF peaks were defined. Strikingly, the majority of MRTFB peaks (~82%) overlapped with EWS-FLI1 whereas only half as many peaks overlapped with SRF (~40%). In particular, only 8% of MRTFB binding regions were shared exclusively with SRF, while 31% of MRTFB peaks overlapped with both EWS-FLI1 and SRF (Fig. 3B).

The association between MRTFB and EWS-FLI1 binding was also substantiated by results obtained from HOMER de-novo-motif analysis. ETS and AP-1 motifs, preferentially associated with EWS-FLI1 binding (4, 28), were also found among most significant motifs enriched in the MRTFB ChIP-seq (Fig. 3C). Motif analysis also revealed an overrepresentation of binding motifs for transcriptional enhancer activator domain (TEAD) transcription factors in EWS-FLI1 ChIP-seq peaks. The most prominent sequence motifs associated with SRF-binding in EwS cells were CTCF and ETS, and only to a much lesser extend CArG, the canonical SRF binding motif. Taken together, the results obtained from ChIP- seq analysis suggest an interaction on the chromatin level between EWS-FLI1 and MRTFB that is independent of SRF.

MRTFB binding and TEAD motifs are significantly enriched in distal regions of EWS-FLI- anticorrelated target genes

Given the opposing transcriptional effects upon MRTFB and EWS-FLI1 depletion, we tested for MRTFB direct binding to EWS-FLI1 target genes. RNA expression data from EWS-FLI1 knockdown experiments were integrated with MRTFB ChIP-seq data. We detected binding of MRTFB to EWS- FLI1-correlated as well as -anticorrelated gene sets (Fig. 4A). A high number of MRTFB ChIP-seq peaks (4809) were found around gene-promoters (proximal peaks), but only about 3% (159 peaks) and 6% (280 peaks) of binding regions were found in EWS-FLI1-correlated and EWS-FLI1-anticorrelated genes, respectively. For distal peaks however, although less numerous (756 peaks), a more substantial fraction (23%) was found to be associated with EWS-FLI1-anticorrelated targets. While this association of distal MRTFB peaks with EWS-FLI1-anticorrelated genes was significant (p<10-20, hypergeometric test), all other overlaps were non-significant (Fig. 4A).

To study the effect of EWS-FLI1 on MRTFB chromatin occupancy, MRTFB ChIP-seq was additionally performed upon low-EWS-FLI1 states. We found that MRTFB peak numbers generally increased under low compared to high EWS-FLI1 levels. Of note, under EWS-FLI1-low conditions, MRTFB chromatin occupancy increased to a higher extent in distal enhancer than in proximal promoter regions (48% versus 29%) (Fig. 4B), indicating EWS-FLI1 interference with chromatin-binding of MRTFB.

Motif analysis was repeated for the specific subset of MRTFB peaks, which were associated with distal regions of EWS-FLI1-anticorrelated genes. We identified AP-1 and TEAD motifs to be most prominently enriched. Notably, the significance of this association increased upon EWS-FLI1-low conditions (Fig. 4C). Representative examples for increased MRTFB ChIP-seq signals upon EWS-FLI1- low as compared to –high levels are illustrated in Supplementary Fig. 3B. In distal MRTFB binding

regions associated with EWS-FLI1-correlated gene-sets no significant enrichment in TEAD motifs upon EWS-FLI1-high or –low conditions was observed (Supplementary Table 5).

TEAD depletion recapitulates the effects of MRTFB knockdown on the EWS-FLI1 transcriptome

Co-occurrence of MRTFB peaks with TEAD motifs in regions assigned to EWS-FLI-anticorrelated genes and the fact that several genes inversely regulated by EWS-FLI1 and MRTFB are known target genes of the Hippo/YAP-TAZ/TEAD signaling pathway (CYR61, CTGF, SERPINE1) (29) led us to investigate a potential association of MRTFB with TEAD transcription factors. The TEAD transcription factor family comprises four members, TEAD1-4, which require co-activation for their transcriptional activity commonly provided by the Yes-associated protein (YAP) and its paralogue tafazzin (TAZ). Direct interactions between YAP, TAZ and TEADs with MRTFs have already been described (16, 30, 31). TEADs are furthermore known to associate with AP-1 transcription factors at distal enhancers, regulating motility and proliferation (29, 32). To elucidate the role of TEADs in MRTFB mediated transcriptional regulation in EwS cells, we analyzed the expression signature of combinatorial knockdown of all four TEAD transcription factors (TEAD 1-4) upon EWS-FLI1-high and -low conditions. Depletion of TEAD 1-4 by approximately 50% was achieved by pooling siRNAs directed against TEAD1, 2, 3 and 4 transcripts (Fig. 5A). Strikingly, similar to MRTFA/B knockdown, silencing of TEAD1- 4 antagonized EWS-FLI1–modulation mediated transcriptional effects. In addition, unlike MRTFA/B knockdown, depletion of TEAD1-4 in presence of EWS-FLI1 also resulted in gene expression changes in the opposite direction as caused by EWS-FLI1 knockdown, though to a lesser extent than observed under EWS-FLI1-low conditions (R= -0.29 versus R= -0.57) (Fig. 5B). Comparison of differential gene regulation upon TEAD and MRTFB knockdown showed that there was a positive correlation between gene-regulatory signatures of MRTFB and TEAD depletion at low EWS-FLI1 levels (R= 0.33). However, no such correlation was detected when EWS-FLI1 levels were high (R= -0.05) (Fig. 5C). Furthermore, analysis of the respective TEAD target gene spectra by gene set enrichment analysis (GSEA) (Supplementary Fig. 4B) revealed significant enrichment of genes involved in migration, response to serum or RhoA which was also observed in the comparison of EwS primary tumors to MSCs (Fig. 1A).

These data strongly suggest a synergistic regulation of a set of genes by MRTFB and TEAD, associated with the Rho pathway, which is impeded in the presence of EWS-FLI1. Taking into account the inverse correlation in gene expression observed for EWS-FLI1 versus MRTFB or TEAD modulation, and ChIP-seq data for MRTFB, as well as presence of TEAD motifs in ChIP-seq peaks, a set of target genes for this regulatory module was defined (Fig. 5D). Expression of this panel of genes increased when EWS-FLI1 levels were low, but decreased again upon additional MRTFB or TEAD knockdown. This gene set included the “bona fide” YAP/TAZ-TEAD target genes CYR61 and CTGF. To corroborate a direct functional interaction between MRTFB and TEAD, several candidates from this TEAD/MRTFB 30

target gene list were analyzed by ChIP coupled with q-RT-PCR using primers flanking MRTFB ChIP-seq hits. TEAD ChIP was enriched for ANKRD1 and all tested MRTFB/EWS-FLI1 targets, enrichments were slightly amplified upon low EWS-FLI1 levels (Fig. 5E). EWS-FLI1 ChIP showed enrichments in all tested regions with decreased occupancy upon knockdown of EWS-FLI1 for most of them (Fig. 5E). Furthermore, YAP-1 was found enriched in the respective MRTFB/TEAD/EWS-FLI1 regions as demonstrated by ChIP qPCR (Supplementary Fig. 4C).

Taken together, MRTFB and TEAD bind to EWS-FLI1-anticorrelated targets, especially when the expression of the fusion oncogene is low. Expression of this set of MRTFB-TEAD bound EWS-FLI1- anticorrelated genes is repressed by EWS-FLI1 but re-activated by MRTFB/TEAD upon EWS-FLI1 knockdown. DAVID functional annotation analysis of the inversely EWS-FLI1/TEAD regulated genes demonstrated that cell migration (p= 3.5E-3), adhesion (p= 3.9E-5), and regulation of the extracellular matrix (p= 1E-10) were significantly enriched in this gene set. This indicates that the interaction of MRTFB and TEAD on a transcriptional level, likely perturbed by EWS-FLI1, is a network hub for the regulation of cytoskeletal processes such as migration and adhesion in EwS.

Discussion

Early metastasis onset is still the major clinical challenge in the treatment of EwS patients. EwS cells presumably are of mesenchymal origin, which makes it very unlikely that they undergo the “classic” epithelial-to-mesenchymal (EMT) transition in order to become metastatic. These cells might have gained the ability to adapt to different environmental cues by a high degree of cellular plasticity. Several studies proposed that high EWS-FLI1 suppresses migration and adhesion by disrupting EwS cell morphology (8-10). It was suggested that EWS-FLI1 mediates resistance to cell detachment induced anoikis through suppression of actin-fiber formation. Knockdown of EWS-FLI1 resulted in a more mesenchymal phenotype of EwS cells including increased expression of mesenchymal markers or genes involved in adhesion and cell architecture. Most recently, oscillation of EwS cells between a proliferative, non-migratory, EWS-FLI1-high small cell phenotype and a non-proliferative, highly migratory EWS-FLI1-low state with re-programmed actin cytoskeleton was described (33). This finding is consistent with EWS-FLI1 repressing cytoskeletal genes (e.g. zyxin, α5-integrin) and the formation of actin-rich cytoskeletal structures such as focal adhesions and stress fibers (9, 10). Being mainly regulated by Rho signaling, the actin-cytoskeleton plays an important role in microenvironmental signal integration with gene expression via activation of the transcriptional co- activators MRTF. MRTFA and MRTFB typically engage with SRF and activate transcription of cytoskeletal genes in response to serum stimulation. Interestingly, we found little influence of serum

in EwS cells, which led us to speculate that serum-inducibility is compromised by EWS-FLI1-mediated uncoupling of the transcriptional response from serum-dependent Rho signaling. However, knockdown of EWS-FLI1 did not significantly enhance overall serum-response in gene expression. Only a modest number of genes, mostly MRTFA/B target genes, showed a stronger response to serum treatment under EWS-FLI1-low than under EWS-FLI1–high conditions (Supplementary Tables 3 and 4). A potential explanation for the missing restoration of serum-inducibility by silencing of EWS- FLI1 could be that in the absence of the fusion oncogene cells dramatically enter growth-arrest (34) and hence remain largely unresponsive to external growth stimuli. A recent study in mouse fibroblasts (NIH3T3) demonstrated serum-inducibility for 960 SRF target genes, most of them regulated by MRTF (27). Given the discrepancy in serum-responsiveness between EwS cells and other cell types, it is conceivable that EwS cells have to some degree become independent from extracellular growth signals due to their EWS-FLI1 oncogene-addiction.

In this study we provide evidence for a yet unknown network hub involved in the extra-cellular signaling inhibition by EWS-FLI1. Our data suggest that, in EwS cells, downstream of Rho/F-actin signaling, MRTFs function as co-activators for TEAD and that EWS-FLI1 binds to MRTFB/TEAD target genes and attenuates their transcriptional activation. Since YAP-1 and TEAD chromatin occupancy did not significantly increase upon EWS-FLI1 knockdown, the fusion oncogene is unlikely to compete with YAP-1 or TEAD DNA binding. However, ChIP-seq enrichments for MRTFB to the respective regions were increased upon low-EWS-FLI1 levels. It is therefore conceivable that EWS-FLI1 interferes with the recruitment of MRTFB to the YAP-1-TEAD complex. A recent study in breast cancer cells further corroborates this hypothesis by demonstrating that MRTFA and especially MRTFB are substantial for YAP-1/TEAD target gene activation via direct interaction and recruitment of other transcriptional coactivators. Interestingly, it was shown that while MRTFB is essential for activation of a YAP-1-TEAD luciferase reporter, MRTFA had only a small effect on the luciferase readout (30). In fact MRTFA seems to have a stronger bias towards SRF binding than MRTFB (35).

MRTFB and SRF chromatin binding regions shared relatively little overlap and were not enriched for the same DNA motifs in our study. In contrast to other data sets where the CArG motif was found in ~50% of SRF binding peaks (HOMER motif re-analysis of SRF ChIP-seq data from Encode (36), data not shown), in EwS cells the SRF consensus motif CArG was rarely present in the SRF binding regions. Instead, we found an overwhelming enrichment of CTCF motifs, which are frequently associated with gene-insulators (37). Earlier studies reported CTCF motif enrichments for SRF in neuron-specific lineages (38) and a direct interaction of SRF and CTCF was demonstrated via the chromodomain helicase-DNA binding protein 8 (CHD8), important for protecting smooth muscle alpha cells from

apoptosis (39). Depending on the cellular context it is possible that SRF might have distinct roles and hence might act differently in EwS cells as compared to other cell types.

MRTFs do not carry a DNA binding domain but are recruited to chromatin through interaction with DNA-bound transcription-factors. Recent studies discovered a direct association of the transcriptional co-activators MRTFA/B and the TEAD co-activators YAP-1 (30, 31) and TAZ (16), downstream of Rho-actin regulation. In fact, MRTFs and YAP-1/TAZ exhibit crosstalk on multiple levels, mutually affecting their nucleo-cytoplasmic distribution, expression, and transcriptional activity (31, 40). Several studies indicated that in order to fully activate gene expression of TEAD target genes, MRTF and YAP-1/TAZ are required (30, 31). It was furthermore shown that MRTFA/B interaction with YAP-TEAD via NcoA3 recruitment is essential for target gene activation playing a role in breast cancer metastasis (30). Our data suggest that recruitment of MRTFB to sites of TEAD and YAP-1 binding is hindered by EWS-FLI1. The enrichment of TEAD motifs was predominantly found in distal regions of EWS-FLI1-anticorrelated genes. TEADs have been reported to associate with the transcription factor AP-1 (Fos-Jun) at distal enhancers of genes involved in oncogenic growth in several tumor cell lines (29, 32). Notably, we found co-enrichment of AP-1 motifs with TEAD motifs in MRTFB-enriched sites of EWS-FLI1-anticorrelated genes and AP-1 has previously been demonstrated to bind to EWS-FLI1 at genomic regions equipped with AP-1 binding motifs (28). Hence, AP-1 might provide a link to TEAD occurrence at EWS-FLI1-bound regions associated with EWS-FLI1- anticorrelated genes.

A prerequisite for MRTFB/YAP-1 activity is their nuclear translocation upon signal-induced F-actin polymerization (12, 41, 42), which can be inhibited by pre-treatment with Latrunculin B (LatB). Previous studies reported EWS-FLI1-dependent perturbation of the actin cytoskeleton. To exclude that EWS-FLI1 represses TEAD target genes solely by prohibiting release of transcriptional co- activators YAP-1 and/or MRTFB to the nucleus, we used confocal immunofluorescence microscopy and immunoblotting to visualize the subcellular localization of MRTFB and YAP-1 in A673/TR/shEF cells in absence and presence of serum. Under serum-starved conditions, both proteins were retained in the cytoplasm. However, MRTFB and YAP-1 readily translocated to the nucleus upon 60 minutes of serum stimulation in the absence, but not in presence of LatB despite the continuous presence of EWS-FLI1 (Supplementary Fig. 5). Consistent with cytoplasmic retention of co-activators in response to LatB treatment, a significant reduction in CTGF, ANKRD1 and CYR61 gene expression was observed (Supplementary Fig. 5D). Our data therefore suggest that EWS-FLI1-induced cytoskeletal perturbation is not sufficient to explain aberrant downstream gene regulation, since MRTFA/B and YAP-1 signal-related nuclear localization was functional. We therefore propose

interference of EWS-FLI1 with MRTFB recruitment to a transcriptional module including YAP-1/TEAD as the main mechanism of cytoskeletal target-gene dysregulation in EwS.

Taken together, this study supports a model for EWS-FLI1 perturbing feed-back regulation of genes involved in Rho signaling via the actin-cytoskeleton by a transcription modulatory mechanism (Fig. 6). The EWS-FLI1-low state drastically alters EwS cell morphology (A673/TR/shEF: Supplementary Fig. 5E). We hypothesize that this change in morphology is due to the perturbation of transcriptional complex formation of MRTFB with YAP-1-TEAD by EWS-FLI1. Among MRTFB and TEAD regulated genes we identified several key players of the Rho-pathway involved in upstream regulation (e.g. CYR61, CTGF) and actin-fiber formation and stability (e.g. TAGLN, CALD-1, TPM-1) to be repressed by EWS-FLI1 (Fig. 5D). Given the established role of Rho signaling in cellular plasticity this study provides novel molecular insights into the nature of initial events of metastasis in EwS.

Methods

Cell Culture

The A673/TR/shEF cell line, stably carrying a sh-EWS-FLI1 construct under a doxycycline (dox)- inducible promoter was previously described (43). Knockdown of EWS-FLI1 was achieved by addition of 1µg/ml dox to the medium (24-72 h). The SK-N-MC EwS cell line, kindly provided by J. Biedler (Memorial Sloan-Kettering Cancer Centre, New York, USA), was cultivated in RPMI supplemented with 10% FBS and penicillin/streptomycin (Gibco by Life Technologies, Carlsbad, CA, USA). Cell lines were regularly tested for mycoplasma (Mykoalert detection kit) (Lonza, Basel, Switzerland) and their identities confirmed by STR profiling. For serum-starvation, cells were washed twice with PBS (Gibco by Life Technologies) and starved over-night in 0.2% FBS-medium. For serum-induction cells were treated for 60 minutes 20% FBS-medium. Latrunculin B (LatB) (Cayman Chemicals, Ann Arbor, MI) was added in serum-free DMEM at 1µM concentration to the over-night starved cells 30 minutes before serum-induction. Vehicle controls were treated with DMSO (< 0.05 %).

Transfection experiments

To simultaneously knockdown MRTFA and MRTFB the pLKO sh-MKL-1/2 plasmid (Addgene; #27161) was transiently transfected into cells. A control plasmid (sh-NS) containing an inert shRNA (CAACAAGATGAAGAGCACCAA) was used. For combined knockdown of EWS-FLI1 dox was added 48 h prior to harvest. To transiently silence EWS-FLI1 in SK-N-MC, the sh-EF30 pSUPER plasmid and, as a control, a scrambled-shRNA control plasmid (44) were used. Transfections were carried out using lipofectamine Plus reagent (Invitrogen, Groningen, the Netherlands).

Transfections with siRNA were carried out using oligofectamine reagent (Invitrogen, Groningen, the Netherlands) according to the manufacturer’s instructions. For concomitant knockdown of EWS-FLI1 in A673/TR/shEF cells, cells were additionally dox-treated for 48 h. Cells transfected with siRNA were cultured in the presence of serum.

Protein Extraction and Immunoblot

Approximately 300,000 cells were lysed in PBS and 2x SDS-loading buffer (TRIS, SDS, beta- mercaptoethanol, glycerin) and processed on 6.5% or 8.5% SDS-polyacrylamide gels for western blotting. For separation of cytoplasmic and nuclear protein fractions, approximately 6 million cells were isolated as described previously (45). About 30µg of the nuclear or cytoplasmic fraction were loaded on a polyacrylamide gel for Western blot analysis. Quantification of protein band intensities was achieved using the LI-COR Odyssey® Infrared Imaging System (LI-COR Biosciences, Bad Homburg vor der Höhe, Germany).

Antibodies

The following antibodies were used for immunoblotting and immunofluorescence microscopy: MRTFA (MKL-1) H-140 (sc-32909), SRF G20 (sc-335) (Santa Cruz, TX, USA), MRTFB (MKL-2) (A302- 768A) (Bethyl Laboratories, TX, USA), FLI1 (MBS177100) (MyBiosource, San Diego, CA, USA), α- TUBULIN (CP06) (Calbiochem/Merckmilipore, Darmstadt, Germany), Lamin A/C (2032S) (Cell Signaling, Danvers, MA, USA). The following antibodies were used for ChIP experiments: SRF G20 (sc- 335X) (Santa Cruz, CA, USA), MRTFB (MKL-2) (A302-767A) (Bethyl laboratories, TX, USA), FLI1 ChIP grade (ab15289) (Abcam, Cambridge, UK), pan-TEAD (#13295) (Cell Signaling), and rabbit IgG antibody (MAGnify Chromatin Immunoprecipitation System, Invitrogen, Groningen, The Netherlands). The YAP-1 antibody (ab52771) (Abcam, Cambridge, UK) was used for Western blot analysis as well as for ChIP experiments.

Oligonucleotides

Information on all oligonucleotides used in this study (q-PCR, ChIP-qPCR, si-RNA) is enclosed in Supplementary Table 2.

Gene expression data

Gene expression data obtained from Affymetrix expression arrays (Supplementary Table 1: Affymetrix array treatment conditions) or RNA-sequencing including bioinformatical analysis are described in detail in the supplementary information.

ChIP-qPCR and ChIP-Seq 35

Chromatin Immunoprecipitation (ChIP)

Approximately 10 million cells were collected and double-cross-linked using disuccinimidyl glutarate (DSG) (Thermo Fisher Scientific, Waltham, MA, USA) and formaldehyde (FA) (Thermo Fisher Scientific, Waltham, MA, USA). ChIP was performed as described previously (46), with some adaptations. Briefly, cells were harvested and cross-linked with 0.5M DSG for 20 minutes at room temperature. Pellets were washed twice and cells were cross-linked for 5 minutes with 1% FA. Cells were washed and subsequently lysed in the lysis buffers described in the reference above before sonication with Covaris ultrasonicator for 15 minutes. Sheared chromatin (50µg) was incubated with 5µg (or as indicated) of the respective antibody over-night. For immunoprecipitation 50µl/ChIP of the Protein G Dynabeads (Thermo Fisher Scientific) were used.

ChIP-qPCR

Three biological replicates were performed per ChIP experiment and analyzed by q-RT-PCR using SYBR-Green (Maxima SYBRGreen/ROX qPCR Master Mix) (Thermo Fisher Scientific). Data were normalized to the input control according to the following equation: Normalized to Input= 2∧(Average Ct Input – Average Ct IP). IgG controls were performed for every ChIP experiment.

Library Preparation

Approximately 5ng ChIP-DNA was used for library prep with the NEBNext® Ultra™ DNA Library Prep Kit from Illumina (New England Biolabs, Frankfurt, Germany) and the NEBNext® Multiplex Oligos from Illumina® (New England Biolabs) were used for adapter labelling in a multiplex sample preparation. The NEBNext Q5 Hot Start HIFI PCR Master mix was used and no size-selection of adapter-ligated DNA was performed. Library preparation was accomplished according to manufacturer’s instructions.

ChIP-seq

Sequencing of DNA from ChIP experiments was performed in duplicates for each experimental condition on an Illumina Hi-Seq 2000. For FLI1 and SRF ChIP, 50 bp single reads, and for MRTFB ChIP, 100 bp paired-end reads were obtained, yielding a minimum of 28 million reads for each sample. The bioinformatical analysis of the ChIP-seq data is described in detail in the supplementary information.

Immunofluorescence

For Immunofluorescence (IF) microscopy cells were fixed and primary antibodies were added in 0.1%TritonX/1%BSA-PBS with 3% goat serum over-night. Secondary antibodies were added in 0.3%TritonX/2%BSA-PBS with 3% goat serum for 60 minutes. Cells were mounted with VECTASHIELD

mounting solution containing TRITC-phalloidin to stain actin fibers (Vector laboratories, Burlingame, CA, USA). Immunostainings were visualized using the Leica TCS SP8 confocal microscope and images were taken using the Leica LAS-AF software (Leica Microsystems, Wetzlar, Germany) at 40x magnification. For Supplementary Fig. 5e, images were taken on the Axioplan 2 imaging fluorescence microscope at 100x magnification (Zeiss, Oberkochen, Germany). IF microscopy was carried out for three independent experiments.

Statistics

P-values were calculated from three independent experiments (mean±SEM) using the Graph Pad- software (http://www.graphpad.com/) (Graph Pad Prism Software Inc., La Jolla, CA, USA). If not indicated otherwise, data were analyzed using the two-tailed One-Sample T-Test including Welch’s correction, setting the hypothetical mean-value to 1. P-values of ≤0.05 were considered significant. ***p≤0.001; **p≤0.01; *p≤0.05.

Data availability

All genomic data obtained from Affymetrix arrays, RNA-seq or ChIP-seq were submitted to the Gene Expression Omnibus from NCBI (GEO; http://www.ncbi.nlm. nih.gov/geo/) under accession number GSE92741.

Acknowledgements

The authors thank Fikret Rifatbegovic for his assistance with the generation of graphical figures

Author contributions

A.M.K. and H.K. designed the study. A.M.K. performed the experiments with contributions from R.S., E.M.T., C.N.M., M.L. and D.N.T.A. M.S. provided technical support and assistance with data interpretation. M.O.K performed all high-throughput data analysis. J.A. provided the A673/TR/shEF cell line. A.M.K., M.O.K., and H.K. wrote the manuscript.

References

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Figures

Figure 1│ Rho target genes are repressed by EWS-FLI1 in EwS. A. GSEA plots showing the differential analysis of 117 EwS tumors (GSE34620) (18) versus mesenchymal stem cells (MSCs) (GSE31215) (19). Genes involved in the response to serum, RhoA or involved in migration are repressed in the EwS tumors versus MSCs. B. Heatmap showing a manually curated set of Rho/SRF target genes under EWS-FLI1-high or –low conditions in six different EwS cell lines: left panel: WE68, TC252, SK-N-MC, ET7, ET1 (data from GSE14543) (6), and right panel: A673/TR/shEF, this study: 2 replicates. Expression values are scaled row-wise.

Figure 2│ MRTFB knockdown antagonizes the transcriptional effects of EWS-FLI1 depletion. A. Immuno-blot of MRTFA and MRTFB knockdown by transient shRNA-transfection with and without concomitant dox-induced (48 h) EWS-FLI1 silencing. Alpha-TUBULIN was used as a loading control. B. Scatter plot showing effects of serum on MRTFA/B dependent gene regulation. X-axis: sh-MRTFA/B vs sh-Ctrl under starved-conditions. Y-axis: 42

sh-MRTFA/B vs sh-Ctrl under serum-induced conditions. Red dots indicate serum responsive MRTFA/B regulated genes at |logFC|≥0.8 with some examples given. C. Comparison of effects of MRTFA/B knockdown versus EWS-FLI1 knockdown in A673/TR/shEF and SK-N-MC. Scatter plots showing log2 fold gene expression changes upon EWS-FLI1 knockdown (x-axis) (dox vs. no dox), and upon MRTFA/B knockdown (y-axis) (sh- MRTFA/B vs. sh-Ctrl) alone (EWS-FLI1-high) or in combination with EWS-FLI1-knockdown (EWS-FLI1-low) in A673/TR/shEF (upper panel) and SK-N-MC cell line (lower panel). D. Inverse gene regulation by MRTFA/B and EWS-FLI1. Venn diagrams of EWS-FLI1-correlated and -anticorrelated genes (green circles) and MRTFA/B regulated genes under EWS-FLI1-low conditions (yellow circles) in A673/TR/shEF cells. Overlapping area indicates the number of genes that are partially rescued from EWS-FLI1 knockdown effects by MRTFA/B depletion. Arrows indicate direction of gene expression change for EWS-FLI1 knockdown (dox vs. no dox; red, |logFC|≥1, p<0.05), and for combined EWS-FLI1/MRTFA/B knockdown (sh-MRTFA/B vs. sh-Ctrl under dox; blue, |logFC|≥0.7, p<0.05). E. Heatmap and unsupervised hierarchical clustering of gene expression changes induced by MRTFA/B knockdown under EWS-FLI1-high and –low conditions (cutoff: |logFC|≥1.5 ; p<0.05.) from 2 independent experiments. F. Gene expression effects of specific siRNA mediated depletion of either MRTFA or MRTFB. Left: representative Immuno-blot showing the individual siRNA mediated knockdown of MRTFA and MRTFB on protein level. Right: Scatter plots of gene expression (log2 fold) changes induced by EWS-FLI1 (x-axis) versus combined MRTFA/B+EWS-FLI1 (y-axis) silencing. The inverse correlation is higher for MRTFB (R= -0.66) than for MRTFA (R= -0.36).

Figure 3│ ChIP-seq of MRTFB and EWS-FLI1 suggests functional interaction on chromatin level. A. Genome- wide distribution pattern of MRTFB, EWS-FLI1 and SRF ChIP-seq peaks. Peaks were defined as “proximal” (-5kb to +1kb from the TSS), “genebody” or “distal” (all other peaks). B. Venn diagram showing the genome-wide overlaps of EWS-FLI1, SRF and MRTFB ChIP-seq peaks. C. Table of most enriched sequence motifs (with P- values and percentage of peaks harboring the motif) found in the MRTFB, EWS-FLI1 and SRF binding regions (motif analysis was performed by the HOMER software, n.f. indicates that motif was not found in the HOMER analysis). For detailed HOMER motif analysis output see Supplementary Table 5.

Figure 4│ MRTFB binding and TEAD motifs are significantly enriched in distal regions of EWS-FLI1 anticorrelated target genes. A. Venn diagram representing the overlap of MRTFB ChIP-seq peaks (green circles) in promoter (proximal) or distal gene regions of EWS-FLI1-correlated or EWS-FLI1-anticorrelated genes (yellow circles). Significant enrichment of the MRTFB binding was solely found in distal genomic regions of EWS-FLI1- anticorrelated genes (lower right, ***p= 1.039E-25). B. MRTFB ChIP-seq peaks in proximal (-5kb to +1kb from the TSS) and distal gene regions under EWS-FLI1-high and –low conditions. * percentage of newly appearing MRTFB peaks as compared to all MRTFB peaks upon EWS-FLI1-low. C. HOMER motif analysis of MRTFB ChIP- seq peaks in EWS-FLI1-anticorrelated genes under EWS-FLI1-high and -low conditions. The peak-set was filtered allowing for only one peak per gene (the nearest to the TSS). Motif analysis was performed by the HOMER software, n.f. indicates that motif was not found in the HOMER analysis. For detailed HOMER motif analysis output see Supplementary Table 5.

Figure 5│ Effect of TEAD transcription factors on the EWS-FLI1 regulated transcriptome. A. Western blot analysis showing combined knockdown of all four TEAD transcription factors (TEAD1-4) using siRNA targeting each individual TEAD mRNA. TEAD1-4 factors are recognized by a pan-TEAD antibody. Relative mRNA levels demonstrate that the knockdown efficiency of the four TEAD factors is comparable. Mean±SEM of two biological replicates is shown. B. Scatter plots showing the effects of the TEAD1-4 knockdown on EWS-FLI1 regulated genes upon EWS-FLI1-high (left plot; R= -0.29) and EWS-FLI1-low (right plot; R= -0.57). TEAD1-4 knockdown antagonizes the effect of EWS-FLI1 depletion, however, more potently upon EWS-FLI1 low conditions. C. Comparison of gene expression changes induced by MRTFB knockdown (y-axis) versus TEAD1-4 depletion (x-axis) upon high (left scatter plot; R= -0.05) or low (right scatter plot; R= 0.33) EWS-FLI1 levels.

Effects of the MRTFB and TEAD1-4 knockdown correlate upon EWS-FLI1-low state only. D. Heatmap of “inversely regulated” EWS-FLI1/MRTFB target genes (genes for which expression is rescued after the combined EWS-FLI1/MRTFB or EWS-FLI1/TEAD knockdown in comparison to the single EWS-FLI1 knockdown), which were further filtered according to the presence of significant MRTFB ChIP-seq hits, and the presence of TEAD binding motifs. Gene expression cutoff: EWS-FLI1 knockdown (dox vs. no dox) |logFC|≥1, p<0.05; MRTFB or TEAD knockdown upon EWS-FLI1-low conditions (si-MRTFB+dox/si-TEAD+dox vs. si-Ctrl+dox): |logFC|≤0.4, p<0.1. E. ChIP-qPCR of for TEAD, FLI1 and IgG ChIP for selected “inversely regulated” genes. ANKRD1 was used as a positive control for the TEAD ChIP-qPCR. Mean±SEM of three biological replicates is shown.

Figure 6│ Model of Rho/F-actin pathway repression by EWS-FLI1 via MRTFB/YAP-1/TEAD transcriptional perturbation. A673/TR/shEF: Left: EWS-FLI1-low state: EWS-FLI1 binds to distal genomic elements of EWS-FLI1- anticorrelated target genes and thereby likely hinders MRTFB/YAP-1/TEAD interaction and transcriptional activation of genes involved in actin-cytoskeletal structure (TAGLN, TPM-1, CALD-1) or involved in binding to the extracellular matrix (ECM) and insulin-growth-factors (IGF) (CYR61, CTGF). Low expression of these genes might affect cytoskeletal integrity due to compromised actin-polymerization and upstream signaling via ECM- receptor interactions. As a consequence cells exhibit few focal adhesions and stress-fibers (F-actin filaments) and F-actin polymerization is reduced (9, 10). Right: Upon knockdown of EWS-FLI1 (EWS-FLI1-low), expression of MRTFB/YAP-1/TEAD target genes, which are cytoskeletal key players, is increased and thereby likely promoting signaling via Rho both upstream and downstream of actin-polymerization. Consequently, cell morphology is drastically altered with increased numbers of focal adhesions and stress-filaments as compared to the high-EWS-FLI1 cell state.

Supplementary Information:

Methods:

GSEA (gene set enrichment analysis):

GSEA was performed using the java command line tool and MSigDb gene sets from the Broad- Institute (http://software.broadinstitute.org/gsea) (1). For the analysis in Fig. 1A, 117 Ewing tumors from (2) (GEO: GSE34620) were compared to pediatric mesenchymal stem cells (3) (GEO: GSE31215) and the resulting gene list with log2fold changes was used as input for GSEA.

Gene expression analysis

Normalization of CEL files and all further analyses were performed in R statistical environment using Bioconductor packages (4), Affymetrix CEL files were normalized using frma (5) using the “summarize="robust_weighted_average" setting. Normalized data were further filtered by the z- score calculated with the “barcode” function of the frma package. Genes with z-scores < 2 in all samples were excluded and finally the probe set with the highest variance across samples per gene was chosen for further analysis. Differential gene expression analysis was performed using the limma package (6). Two biological replicates were analyzed in the expression arrays. Supplementary Table 6 provides all gene expression data used in this study obtained from microarrays (Affymetrix HGU-133- PLUS2).

RNA-Seq

Total RNA was isolated using the RNeasy Kit (Qiagen, Hilden, Germany) according to manufacturer’s instructions. RNA was sequenced on a HiSeq2000, yielding >17Mio 50bp single end reads for all samples. Short read sequencing data was quality checked using FASTQC, RNA-SeqQC (http://www.bioinformatics.babraham.ac.uk/projects), and then aligned to the human genome hs37d5 (ftp://ftp.1000genomes.ebi.ac.uk/) using the STAR aligner (7) allowing for 1 mismatch and no multimappers yielding a minimum of 13 million aligned reads in each sample. Further analysis was performed in R statistical environment using Bioconductor packages. Count statistics for Ensembl (GRCh37.75) genes were obtained by the “featureCounts” function (package “Rsubread”) and differential expression analysis was performed by edgeR and voom (8). For differential gene expression analysis only genes passing a cpm (counts per gene per million reads in library) cutoff of 5 in more than two samples were included. Two biological replicates were sequenced per experiment. Supplementary Table 6 provides all gene expression data used in this study obtained from RNA-seq.

DAVID analysis

Gene ontology (GO) analysis of gene-expression data was performed using the DAVID bioinformatics database (https://david.ncifcrf.gov/) (9).

ChIP-sequencing: bioinformatical analysis

Reads were aligned to the human genome hs37d5 (ftp://ftp.1000genomes.ebi.ac.uk/) using the bwa aligner (10), and aligned reads were used as input for macs2 (callpeak, down-sample and otherwise default parameters(11)) and compared to a large combined ChIP-input sample from Tomazou et al (12). Further analysis was done in R statistical environment using Bioconductor packages. DiffBind (13) was used to construct a consensus peak matrix from all ChIP experiments yielding a list of 50798 peak regions. MACS2 results (samplename_peaks.xls) of the two replicas of each experimental condition were combined, and only peaks were retained that yielded a log10-q-value>10 in both replicas. The combined peak matrix is reported as Supplementary Table 7, where the reported q- value is the lower of each pair of replicas.

Peak Annotation and motif analysis

Peak annotation and motif analysis was done using the Perl programs findMotifsGenome.pl and annotatePeaks.pl of the HOMER software suite (http://homer.salk.edu/homer/) (14). Bed files of ChIP-seq peaks were generated as input for HOMER. Only peaks were included that yielded a log10- q-value>10 in both replicas. Subsequently, for Fig. 3C the de-novo output from HOMER was summarized for the most relevant motifs (ETS, CArG, AP1, TEAD and CTCF). HOMER-known motifs yielded the same qualitative results (not shown). Based on the annotation from HOMER, using a nearest-gene heuristic in further analyses, peaks were defined as “proximal” (-5kb-+1kb around the TSS), and “distal” (all other peaks). For the calculations in Fig. 4C the peak set was filtered so that for each gene only one peak (the nearest to the TSS) was retained.

Supplementary Figure 1│ Rho/SRF target genes are repressed by EWS-FLI1 in EwS. A. Schematic representation of the A673/TR/shEF EwS model cell line: reduction of endogenous EWS-FLI1-high levels is achieved by the addition of doxycycline (dox) to the medium. Knockdown of EWS-FLI1 upon 24 h- 72 h of dox treatment is denoted as EWS-FLI1-low state. A representative western blot of the EWS-FLI1 protein is shown. Linear protein quantification of EWS-FLI1 protein levels from three independent experiments (mean± SEM) was achieved with the use of the LI-COR Odyssey® Infrared Imaging System. GAPDH was used as a loading control. **p≤ 0.01. B. Relative mRNA expression values of selected Rho/SRF target genes upon doxycycline-induced EWS-FLI1 knockdown. Shown is mean±SEM. The no-dox control was normalized to 1 and p-values were calculated using One-sample t-test. ***p≤0.001, **p≤0.01; *p≤0.5.

Supplementary Figure 2│ MRTFB knockdown antagonizes the transcriptional effects of EWS-FLI1 depletion. A. Relative protein expression values (LI-COR Odyssey® Infrared Imaging System) are shown for MRTFA, MRTFB and EWS-FLI1. Graph represents mean±SEM of three independent experiments. One-sample t-test was calculated relative to sh-Ctrl (no dox) sample, which was normalized to 1. ***p≤0.001, **p≤0.01; *p≤0.5. B. Effect of serum on gene expression. Scatter plot showing overall gene expression levels upon treatment with serum in A673/TR/shEF cells. Normalized gene expression levels from Affymetrix microarray analysis are

shown. X-axis: serum-starved conditions. Y-axis: serum-induction. Red dots represent genes that change upon serum-induction versus serum-starvation (see also Supplementary Table 4). C. Scatter plot of gene-expression changes upon MRTFA/B knockdown from Affymetrix microarray expression arrays performed under serum- starved conditions. Log2-fold changes are shown. X-axis: dox (EWS-FLI1-low) versus no dox (EWS-FLI1-high). Y- axis: sh-MRTFA/B versus sh-Ctrl. D. Western blot of combined knockdown of MRTFA, MRTFB and EWS-FLI1 in SK-N-MC EwS cells with linear protein quantification of three biological replicates. ALPHA-TUBULIN was used as a loading control. Relative mRNA expression values of three independent experiments are additionally shown (mean±SEM). One-sample t-test was calculated comparing values to sh-Ctrl (no dox), which was normalized to 1. ***p≤0.001, **p≤0.01; *p≤0.5. E. Selected EWS-FLI1-anticorrelated genes (HPGD, GAS2, MAP2) from heatmap cluster 2 and EWS-FLI1-correlated genes from cluster 4 (NR0B1, RAD51AP1, MCM10) (for heatmap see: Fig. 2E) were analyzed for their inverse regulation by EWS-FLI1 and MRTFA/B in three independent experiments by q-RT-PCR. Mean±SEM. ***p≤0.001, **p≤0.01; *p≤0.5. F. MRTFA, MRTFB and EWS-FLI1 protein expression shown by western blot. MRTFA and MRTFB knockdown was achieved using siRNA and was combined with the dox-induced EWS-FLI1 knockdown. Alpha-TUBULIN was used as a loading control. Protein quantification from three independent experiments was achieved by normalization to ALPHA-TUBULIN. Relative mRNA values for MRTFA, MRTFB and EWS-FLI1 are depicted from three independent experiments (mean±SEM). One-sample t-test was calculated comparing values to si-Ctrl (no dox), which was normalized to 1. ***p≤0.001, **p≤0.01; *p≤0.5. G. Scatter plot of gene-expression changes (RNAseq) induced by MRTFA or MRTFB knockdown performed under EWS-FLI1-high conditions. Log2-fold changes are shown. X-axis: dox (EWS- FLI1-low) versus no dox (EWS-FLI1-high). Y-axis: si-MRTFA/ si-MRTFB versus si-Ctrl.

Supplementary Figure 3│ ChIP-seq of MRTFB and EWS-FLI1 suggests functional interaction on chromatin level. A. Representative western blot of EWS-FLI1 protein reduction by dox-treatment for 48 h as compared to the no dox control. EWS-FLI1 knockdown efficiency was attested before the MRTFB ChIP. Protein quantification of EWS-FLI1 from three individual western blots is also shown. mean±SEM. One-sample t-test was calculated by normalization of the no-dox sample as 1. **≤0.01. B. Integrative Genomics Viewer (IGV) screenshots of selected target genes shared by EWS-FLI1 and MRTFB (TPM-1, CTGF, COL1A1) upon EWS-FLI1-high (EWS-FLI1 and MRTFB ChIP-seq) and EWS-FLI1-low (MRTFB ChIP-seq) conditions. Target genes were selected according to the presence of a significant MRTFB ChIP-seq hit with increased signal upon EWS-FLI1 depletion. See also Supplementary Table 7 (Q-values from MACS2 analysis).

Supplementary Figure 4│ TEAD knockdown does not affect EWS-FLI1 protein levels, and genes affected by TEAD knockdown are enriched for processes involving migration and response to serum or RhoA. A. Western blot from TEAD knockdown experiment showing EWS-FLI1 knockdown efficiency upon dox-induced knockdown. TEAD 1-4 depletion did not significantly affect EWS-FLI1 protein levels. B. GSEA of the TEAD1-4 knockdown (si-TEAD1-4 vs si-Ctrl) upon EWS-FLI1-low conditions. Genes responsive to TEAD1-4 knockdown are significantly enriched in serum response, RhoA or migration. C. ChIP-qPCR of selected inversely regulated EWS- FLI1/MRTFB-TEAD target genes after YAP-1 ChIP. ANKRD1 was used as a positive control. YAP-1 ChIP was performed in parallel with pan-TEAD, EWS-FLI1 and IgG ChIPs depicted in Fig. 5e. Mean±SEM of three biological replicates is shown.

Supplementary Figure 5│ Subcellular localization of MRTFB and YAP-1 is regulated via serum-induced F-actin polymerization in EwS, and inversely regulated MRTFB-TEAD/EWS-FLI1 target genes respond to F-actin inhibition. A. Schematic illustration of the G-protein coupled receptor (GPCR)-Rho-F-actin axis. Serum-induced actin polymerization triggers nuclear accumulation of Rho-regulated factors such as MRTFB and YAP-1, which can be inhibited with use of the actin polymerization inhibitor Latrunculin B (LatB). B. Confocal immunofluorescence microscopy images of endogenous MRTFB (FITC) and F-actin (phalloidin-TRITC), counterstained with DAPI for nuclear staining. DMSO (<0.05%) was used as a mock control. n=3. Stvd= serum- starved (18 h); SI = serum-induced (60 min); SI+LatB = serum-induced (60 min) with 1 µM LatB pre-treatment (30 min). Size scale: 100 µm. C. Immunoblot image of cytoplasmic and nuclear protein fractions showing MRTFB and YAP-1 subcellular distribution. n=3. Stvd = serum-starved; SI = serum-induced; SI+LatB = serum- induced with 1µM LatB pre-treatment. Upon addition of LatB, serum-induced nuclear accumulation of MRTFB and YAP-1 (n=1) was strongly reduced. LaminA/C was used as loading control for the nuclear protein fraction and ALPHA-TUBULIN was used for the cytoplasmic fraction. Mean ±SEM of linear protein-quantification of three biological replicates is shown. D. Relative mRNA abundance of selected EWS-FLI1/ MRTFB-TEAD target genes shows that serum-induced F-actin polymerization affects their expression. Mean ±SEM. n=3. ***p=≤0.001; **p=≤0.01; *p≤0.5. E. Immuofluorescence-microscopy image of F-actin, stained by FITC- phalloidin, in A673/TR/shEF upon EWS-FLI1-high (no dox) and –low (+ 72 h dox) conditions. 100x magnification. n=3.

Supplementary Table 1:

plasmid treatment 1 treatment 2 1 sh-Ctrl no dox stvd 2 sh-MKL-1/2 no dox stvd 3 sh-Ctrl dox (48 h) stvd 4 sh-MKL-1/2 dox (48 h) stvd 5 sh-Ctrl no dox SI 6 sh-MKL-1/2 no dox SI 7 sh-Ctrl dox (48 h) SI 8 sh-MKL-1/2 dox (48 h) SI Affymetrix array sample conditions. Summary of all sample conditions used for Affymetrix gene expression arrays. A673/TR/shEF cells were transfected with the pLKO sh-MKL-1/2 plasmid to simultaneously knockdown MRTFA and MRTFB. The sh-Ctrl plasmid containing an inert sequence was transfected as a control. Additionally, cells were dox-treated for 48 h to induce EWS-FLI1 knockdown. Furthermore, cells were serum-starved (stvd) overnight with 0.2% FBS-DMEM and the next day serum-induced (SI) with 20% FBS-DMEM for 60 minutes, or left under serum-starvation. Cells were harvested and RNA was isolated for subsequent gene-expression analysis. Two biological replicates were done per condition.

Supplementary Table 2. Oligonucleotides sequences. Summary of oligonucleotide sequences used in this study. Provided as excel file.

Supplementary Table 4. Serum-responsive genes (A673/TR/shEF). List of genes that respond to treatment with serum with |logFC|>1.5, p<0.05 upon EWS-FLI1-high or –low conditions. Provided as excel file.

Supplementary Table 5. HOMER motif analysis. Results obtained from de-novo HOMER-motif analysis of MRTFB, EWS-FLI1 and SRF ChIP-seq enriched sequences. Additional de-novo HOMER analysis is shown for distal peaks associated with EWS-FLI1-anticorrelated genes. The peak set was filtered to allow only one gene per peak. Provided as excel file.

Supplementary Table 6. Gene-expression data. LogFC values and adjusted p-values of gene-expression data obtained from Affymetrix microarray analysis and RNA-seq analysis. Provided as excel file.

Supplementary Table 7. ChIP-seq data. Summary of results obtained from EWS-FLI1, SRF and MRTFB ChIP-seq under EWS-FLI1-high conditions. MRTFB ChIP-seq was additionally performed upon EWS-FLI1-low. Table includes exact peak-regions as well as Q-values from MACS2 analysis with gene-annotation information from HOMER (annotatePeaks.pl). Provided as excel file.

Supplementary Information: References

1. Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proceedings of the National Academy of Sciences of the United States of America. 2005;102:15545- 50. 2. Postel-Vinay S, Veron AS, Tirode F, Pierron G, Reynaud S, Kovar H, et al. Common variants near TARDBP and EGR2 are associated with susceptibility to Ewing sarcoma. Nature genetics. 2012;44:323-7. 3. Riggi N, Suva ML, De Vito C, Provero P, Stehle JC, Baumer K, et al. EWS-FLI-1 modulates miRNA145 and SOX2 expression to initiate mesenchymal stem cell reprogramming toward Ewing sarcoma cancer stem cells. Genes Dev. 2010;24:916-32. 4. Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, et al. Bioconductor: open software development for computational biology and bioinformatics. Genome biology. 2004;5:15. 5. McCall MN, Bolstad BM, Irizarry RA. Frozen robust multiarray analysis (fRMA). Biostatistics (Oxford, England). 2010;11:242-53. 6. Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015;43:e47. 7. Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics (Oxford, England). 2013;29:15-21. 8. Law CW, Chen Y, Shi W, Smyth GK. voom: Precision weights unlock linear model analysis tools for RNA-seq read counts. Genome biology. 2014;15:R29. 9. Dennis G, Sherman BT, Hosack DA, Yang J, Gao W, Lane HC, et al. DAVID: Database for Annotation, Visualization, and Integrated Discovery. Genome biology. 2003;4:R60. 10. Li H, Durbin R. Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics (Oxford, England). 2010;26:589-95. 11. Zhang Y, Liu T, Meyer CA, Eeckhoute J, Johnson DS, Bernstein BE, et al. Model-based analysis of ChIP-Seq (MACS). Genome biology. 2008;9:R137. 12. Tomazou EM, Sheffield NC, Schmidl C, Schuster M, Schonegger A, Datlinger P, et al. Epigenome mapping reveals distinct modes of gene regulation and widespread enhancer reprogramming by the oncogenic fusion protein EWS-FLI1. Cell Rep. 2015;10:1082-95. 13. Ross-Innes CS, Stark R, Teschendorff AE, Holmes KA, Ali HR, Dunning MJ, et al. Differential oestrogen receptor binding is associated with clinical outcome in breast cancer. Nature. 2012;481:389-93. 14. Heinz S, Benner C, Spann N, Bertolino E, Lin YC, Laslo P, et al. Simple combinations of lineage- determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Molecular cell. 2010;38:576-89.

Chapter 2.2. Tables Supplementary Table 2. Oligonucleotide sequences. Summary of oligonucleotide sequences used in this study. siRNA oligonucleotides for transfections: Name 5'-3' Reference si-MRTFA GUGUCUUGGUGUAGUGUAA Fang et al. Circulation Research. 2011 si-MRTFB L-019279-00-0005 Dharmacon, GE Healthcare ON-TARGETplus Human MKL2 (57496) si-TEAD1 GGCCGAUUUGUAUACCGAA Zanconato et al. Nature Cell dTdT Biology. 2015 si-TEAD2 CCUGGUGAAUUUCUUGCACA A dTdT si-TEAD3 UACCUUGCUCUCAAUCUGGA G dTdT si-TEAD4 UUUCCUGCACACACGUCUCU U dTdT cDNA oligonucleotides: Name 5'-3' Reference GAPDH_fw TTCACCACCATGGAGAAGGC GAPDH_rev GGAGGCATTGCTGATGATCTT G MRTFA_fw TCAGGATGCACATTTTGGAA MRTFA_rev CTTCCTTCAGGCTGGACTCA MRTFB_fw CACTCAGGGCGATTTCTCAT MRTFB_rev AGGAACTGTTGGGGACACTG EWS-FLI1_fw TCCTACAGCCAAGCTCCAAGT C EWS-FLI1_rev ACTCCCCGTTGGTCCCCTCC SRF_fw CCTGACAGCATCATCTGGGA SRF_rev TATCACAGCCATCTGGTGGAG VCL_fw TCACACCCCAGGTGGTCTC VCL_rev GTCCACCAGCCCTGTCATTT ZYX_fw CCGGCTCAGAACCAAAACCA ZYX_rev CAGAGTTCGTTGACAGCCACA TAGLN_fw GCAAAGACATGGCAGCAGTG TAGLN_rev TGCTCCTGCGCTTTCTTCATA GAS2_fw CCCAAACAGCACTAAAAGGAG C GAS2_rev CTTGTAATACCCCCGCGTCC MAP2_fw AGATGAAGCAAAGGCACCTC MAP2_rev ACCCTCTTCATCCTCCCTGT HPGD_fw TTTTGGACCCACCATTGATT HPGD_rev GGGTTTTTGCTTGAAATGGA MCM10_fw CAAGACGTGCGCCTATACCC

MCM10_rev AGTGCTTGTTCGGGAGTCTG NR0B1_fw TCCAAATGCTGGAGTCTGAA NR0B1_rev CCACTGGAGTCCCTGAATGT CTGT_fw GGCTTACCGACTGGAAGACA CTGF_rev ATCCCACAGGTCTTGGAACA CYR61_fw TCACCCTTCTCCACTTGACC CYR61_rev AGTCCTCGTTGAGCTGCTTG TEAD1_fw GCCTCCCAACATCCATAGCA Zanconato et al. Nature Cell Biology. 2015 TEAD1_rev TCTGTCCACCAGCCGAGATT TEAD2_fw TGCCTTCTTCCTGGTCAAGTTC Zanconato et al. Nature Cell Biology. 2015 TEAD2_rev GGCTCTCATACTGGCTGCTCA TEAD3_fw GCCGTCTTCTCCACTTCCTC Zanconato et al. Nature Cell Biology. 2015 TEAD3_rev CCAGGGGCTCATAACTGCTG TEAD4_fw GGGCAGACCTCAACACCAAC Zanconato et al. Nature Cell Biology. 2015 TEAD4_rev TGTCCATTCTCATAGCGAGCA RAD51AP1_fw GCGGCCTGTGAGACATAAGA RAD51AP1_rev GGCACTGCACTAGCTGGAATA ANKRD1_fw ACGCCAAAGACAGAGAAGGA ANKRD1_rev TTCTGCCAGTGTAGCACCAG SERPINE1_fw ACTGGAAAGGCAACATGACC SERPINE1_rev TGACAGCTGTGGATGAGGAG gDNA oligonucleotides for ChIP-qPCR: Name 5'-3' Reference SRF-ChIP: MYH9_promoter_fw TGGGAAGGTCTGGAACTCTG MYH9_promoter_rev CTCAAGACGCTCACAATGGA MYH9_Negctrl_fw ATCACACCACTGCACTCCAA MYH9_Negctrl_rev GTGCCCAGCCATGTAAAGAT MRTFB ChIP: Cyr61_far_fw GGGCAAACTCATCCTCAA Liao, Wang et al. Cellular Cyr61_far_rev CACGCAATCTGTCCATCA Signaling. 2014 CYR61_Negctrl_fw TCACCTCTGCCCTCTGAACT Liao, Wang et al. Cellular CYR61_Negctrl_rev ACCACCCCTAAGCGTTTTCT Signaling. 2014 FLI1 ChIP: ADRB3_enhancer_fw GAGGTCACGAGTCCCACCTA ADRB3_enhancer_rev ATCCTGCGTCACTGCTTT pan-TEAD/YAP-1 ChIP ANKRD1_fw GGTGGTGATCACATCGCTCA Liu et al. Cell Reports.2015 ANKRD1_rev GGGGGTGTGATATGTAGGGC CTGF_fw TGTGCCAGCTTTTTCAGACG Zanconato et al. Nature Cell CTGF_rev TGAGCTGAATGGAGTCCTACA Biology. 2015 CA 61

CYR61_fw CACACACAAAGGTGCAATGGA G CYR61_rev CCGGAGCCCGCCTTTTATAC TPM1_fw TGAGGCAGGAAAGCAAAAGT TPM1_rev GGAGAAAACCACCGCAGATA POSTN_fw GCTTGGAACTTGCATTCCTC POSTN_rev TGCTGGCTTTTTCCTCGTAT COL11A1_Fw GGGAATGTGTGTCAGCAAAA COL11A1_rev AACCAATGTGGATCAAGTCAA Negctrl_fw AATCCCCTGCAAATGTCAAA Negctrl_rev TGGGATGCAGACAGTATTGG

Supplementary Table 3. Serum-responsive MRTFA/B target genes (A673/TR/shEF). List of genes that respond to MRTFA/B knockdown and serum-treatment. Data were obtained from Affymetrix gene-expression analysis. Shown are log2 FC values and adjusted p-values for MRTFA/B knockdown (sh-MRTFA/B), in the EWS-FLI1-high (no dox) or in the EWS-FLI1- low (+dox) state, under serum-starvation (stvd) and serum-induction (SI). syms EG logFC logFC logFC logFC logFC adjP. adjP. adjP. adjP. EFkd MKLkd MKLkd MKLkd MKLkd MKLkd MKLkd MKLkd MKLkd _d_st _c_st _d_si _c_si _d_st _c_st _d_si _c_si AP1AR 55435 -0.91 0.66 -0.61 0.63 0.51 0.2862 0.3253 0.3017 0.4342

SCAF11 9169 -1.7 1.05 -0.77 0.27 0.79 0.0783 0.1806 0.6568 0.1891

PRIM2 5558 -1.31 0.34 -1.16 0.14 0.04 0.4892 0.0255 0.8017 0.9446

LOC645513 645513 -0.71 0.07 -0.5 -0.08 0.63 0.8554 0.1248 0.8359 0.0664

MAP9 79884 0.02 0.03 -0.08 0.67 1.15 0.9367 0.8216 0.0317 0.0037

LIN9 286826 -1.95 0.74 -0.63 1.22 0.49 0.1904 0.2648 0.038 0.4018

G3BP1 10146 -1.23 -0.07 -0.61 0.03 0.56 0.9098 0.2068 0.9562 0.2558

WDR17 116966 -1.72 0.26 -0.72 0.71 0.33 0.5069 0.0674 0.0642 0.4044

FILIP1L 11259 2.76 -0.6 0.6 -1.01 -0.48 0.0404 0.039 0.0032 0.0996

TAGLN 6876 2.18 -0.81 0.29 -0.95 -0.82 0.2702 0.72 0.1887 0.2796

ID1 3397 0.8 -0.3 -0.41 -1.36 -1.51 0.1202 0.042 1.00E-04 2.00E-04

CDC14A 8556 -1.11 0.47 -0.39 0.76 0.92 0.0812 0.1367 0.0102 0.006

GLIPR1 11010 1.21 -0.24 0.3 -0.54 -0.87 0.6738 0.5926 0.3017 0.115

CTGF 1490 3.25 -0.84 0.36 -0.94 -1.58 0.1333 0.5304 0.0887 0.0156

CYR61 3491 2.85 -1.34 -0.25 -1.32 -1.74 0.0048 0.5253 0.0044 0.0018

EGR3 1960 -1.04 0.52 0.42 -1.53 -0.92 0.3545 0.4662 0.0135 0.1138

Ad Supplementary Table 3. Table description:

syms HGNC official gene symbol treatment 1 treatment 2 EG entrez gene-ID logFC_EFkd log2fold change of EWS-FLI1 - dox (48 h) knockdown (dox vs no dox) logFC_MKLkd_d_st log2fold change of MRTFA/B starved dox (48 h) knockdown (sh-MRTFA/B vs sh-Ctrl) logFC_MKLkd_c_st log2fold change of MRTFA/B starved no dox knockdown (sh-MRTFA/B vs sh-Ctrl) logFC_MKLkd_d_si log2fold change of MRTFA/B serum-induced (SI) dox (48 h) knockdown (sh-MRTFA/B vs sh-Ctrl) logFC_MKLkd_c_si log2fold change of MRTFA/B serum-induced (SI) no dox knockdown (sh-MRTFA/B vs sh-Ctrl) adjP.MKLkd_d_st adjusted p-value of MRTFA/B starved dox (48 h) knockdown (sh-MRTFA/B vs sh-Ctrl) adjP.MKLkd_c_st adjusted p-value of MRTFA/B starved no dox knockdown (sh-MRTFA/B vs sh-Ctrl) adjP.MKLkd_d_si adjusted p-value of MRTFA/B serum-induced (SI) dox (48 h) knockdown (sh-MRTFA/B vs sh-Ctrl) adjP.MKLkd_c_si adjusted p-value of MRTFA/B serum-induced (SI) no dox knockdown (sh-MRTFA/B vs sh-Ctrl)

Supplementary Table 4. Serum-responsive genes (A673/TR/shEF). List of genes that respond to treatment with serum with |logFC|>1.5, p<0.05 upon EWS-FLI1-high or –low conditions.

Gene. EG logFC_SI_ logFC_SI_ adjP.SI_c adjP.SI_d con_SI_s con_starved_ doxy_SI_s doxy_starved_ Symbol c_ns d_ns _ns _ns hNS shNS hNS shNS EGR3 1960 4.14 5.45 3.00E-04 0 9.91 5.77 10.18 4.73

FOS 2353 2.96 4.01 6.00E-04 0 10.37 7.41 11.09 7.08

EGR4 1961 2.3 3.76 0.3357 0.0085 8.48 6.18 7.6 3.85

FOSB 2354 1.98 3.41 3.00E-04 0 7.87 5.89 9.07 5.66

EGR1 1958 2.6 3.18 1.00E-04 0 10.69 8.09 10.77 7.59

EGR2 1959 1.96 3.08 2.00E-04 0 10.16 8.19 10.43 7.35

NR4A3 8013 0.96 2.76 0.0197 0 7.32 6.36 7.92 5.16

ATF3 467 1.52 2.45 5.00E-04 0 10.24 8.72 12.03 9.58

DUSP1 1843 1.55 2.42 0.0024 0 10.53 8.98 12.03 9.6

ARC 23237 1.52 2.2 0.003 1.00E-04 8.09 6.57 8.03 5.83

KLF10 7071 1.67 2.18 0.0012 1.00E-04 9.77 8.11 10.75 8.58

ZFP36 7538 0.94 2.11 6.00E-04 0 8.55 7.61 10.35 8.24

SERPIN 5054 1.03 2.08 0.9998 0.0526 6 4.98 9.05 6.97 E1 GADD4 4616 1.11 1.96 0.3971 0.0069 9.02 7.9 11.28 9.31 5B NR4A1 3164 1.25 1.93 0.0088 2.00E-04 7.83 6.57 8.41 6.49

BHLHE4 8553 0.71 1.93 0.9612 0.0026 7.65 6.95 9.58 7.66 0 LOC202 202025 1.3 1.89 0.0197 7.00E-04 6.46 5.16 7.79 5.89 025 KRTAP4 100132 1.09 1.87 0.9998 0.053 6.46 5.38 6.59 4.71 -7 476 SERTA 29950 1 1.86 0.1606 0.0012 9.22 8.23 9.83 7.97 D1 LOC284 284454 0.88 1.84 0.3971 0.0021 8.26 7.38 10.2 8.36 454 HES1 3280 0.57 1.78 0.9998 0.0047 9.67 9.11 10.2 8.42

JUNB 3726 1.32 1.72 3.00E-04 0 8.83 7.51 9.27 7.55

DUSP5 1847 0.92 1.69 0.0085 0 9.14 8.21 10.66 8.97

IER2 9592 1.69 1.68 1.00E-04 0 11.89 10.2 12.19 10.51

CYR61 3491 3.06 1.67 2.00E-04 0.0078 11.27 8.21 12.72 11.05

KRTAP4 100132 1.23 1.63 0.0384 0.0026 8.41 7.18 8.6 6.97 -9 386 C11orf9 387763 0.68 1.59 0.7742 0.004 7.37 6.69 9.69 8.09 6 SOCS3 9021 0.7 1.55 0.1312 3.00E-04 6.87 6.17 8.32 6.77

EIF5 1983 0.63 1.54 0.2037 3.00E-04 7.97 7.34 8.55 7.01

JUN 3725 1.73 1.53 1.00E-04 1.00E-04 11.01 9.28 11.29 9.76

KLF4 9314 1.52 1.5 0.009 0.0052 6.67 5.15 7.82 6.33

ID1 3397 1.61 1.42 2.00E-04 2.00E-04 9.75 8.14 10.36 8.94

KLF2 10365 1.72 1.39 0.003 0.0078 9.49 7.76 10.25 8.85

CTGF 1490 3.04 1.32 0.0027 0.2077 11.59 8.55 13.12 11.8

RHOB 388 1.66 0.96 0.0024 0.0447 9.88 8.22 10.57 9.61

PTGS2 5743 1.74 0.77 0.0029 0.2042 6.2 4.46 8.66 7.9

ANAPC 51433 -0.48 -1.55 0.9998 0.0206 6.33 6.81 5.32 6.86 5 KATNB 79768 -0.94 -1.7 0.5396 0.0101 5.55 6.49 4.75 6.45 L1 65

Ad Supplementary Table 4. Table description:

Gene-symbol HGNC official gene symbol treatment 1 treatment 2 EG entrez gene-ID logFC_SI_c_ns log2 fold change serum-induced vs. no dox sh-Ctrl transfected starved (SI) logFC_SI_d_ns log2 fold change serum-induced vs. dox sh-Ctrl transfected starved (SI) adjP.SI_c_ns adjusted p-value serum-induced vs. no dox sh-Ctrl transfected starved (SI) adjP.SI_d_ns adjusted p-value serum-induced vs. dox sh-Ctrl transfected starved (SI) con_SI_shNS frma normalized expression (Affymetrix no dox sh-Ctrl transfected hgu-133-plus2); serum-induced con_starved_shNS fram normalized expression (Affymetrix no dox sh-Ctrl transfected hgu-133-plus2); starved doxy_SI_shNS frma normalized expression (Affymetrix dox sh-Ctrl transfected hgu-133-plus2); serum-induced doxy_starved_shNS fram normalized expression (Affymetrix dox sh-Ctrl transfected hgu-133-plus2); starved

Supplementary Table 6. Gene-expression data. LogFC values and adjusted p-values of gene- expression data obtained from Affymetrix microarray analysis and RNA-seq analysis. (data available upon publication of manuscript).

2.3. Interlude

In the manuscript, provided in section 2.2, we have investigated the molecular mechanisms of Rho-actin repression via MRTFB/YAP-1/TEAD transcriptional perturbation by EWS-FLI1 in EwS. In further experiments, we aimed at elucidation of the functional impact of MRTFA and MRTFB in EwS, depending on EWS-FLI1 presence or absence. Using wound-healing migration and soft agar assays we interrogated the effect of MRTFA/B depletion on the ability of EwS cells to migrate and to grow under anchorage-independent conditions. In parallel, we performed cell cycle analysis to exclude cell-cycle dysregulation as responsible for obtained effects. MRTFA and MRTFB depletion both significantly inhibited wound-healing as well as soft-agar colony formation, without affecting cell cycle progression. These data further undermine the biological significance of these versatile transcriptional effectors, downstream of Rho-actin signalling.

2.4. Extended Results

Expression of MRTFA and MRTFB in EwS cell lines is comparable. Reads per kilo base per million mapped reads (RPKM) values of MRTFA and MRTFB in various EwS cell lines are enlisted in Table E1.

EwS cell line MRTFA (MKL-1) MRTFB (MKL-2) A673 3.91 3.17 StaET7.1 3.46 3.71 StaET7.2 3.61 4.38 StaET7.3 3.47 4.41 WE68 3.45 1.98 EW18 3.43 3.95 EW7 4.13 3.15 TC71 3.46 2.58 SKES1 3.73 3.57 TC252 3.34 3.51 SKNMC 3.25 3.55 RDES 3.42 3.83 VH64 3.61 3.17

Table E1. RPKM expression values of MRTFA and MRTFB in EwS cell lines (unpublished RNAseq data Kovar lab).

Expression arrays: comparison of serum-effect between EwS and OS cells

As already discussed in the manuscript (Chapter 2.2; see also discussion) the effect of serum in A673/TR/shEF cells was quite modest. To check whether this effect is Ewing- specific we also used U2OS, an osteosarcoma (OS) cell line lacking an ETS fusion factor,

68 where we analysed the respective gene-expression profiles of the serum and MRTFA/B depletion effect. As depicted in Figure E1, the effects of serum-induction were slightly greater in U2OS than in A673/TR/shEF cells. Genes that responded to serum-treatment were mostly IEG (e.g. EGR3,4) and CCN (Connective tissue growth factor (CTGF), Cystein rich protein (CYR61), and Nephroblastoma overexpressed gene (NOV)) family members such as CYR61 and CTGF (see also chapter 2.2; Supplementary Tables 3+4) More genes, however, responded to MRTFA/B knockdown in A673/TR/shEF than in U2OS cells, especially under serum-starved conditions (Fig. E1). This might also be due to the slightly weaker knockdown efficiency of MRTFB in U2OS cells than in A673/TR/shEF.

Figure E1. Comparison of serum-response and MRTFA/B depletion in EwS and OS cells. A. A673/TR/shEF. B. U2OS OS cells. Left: western blot testing MRTFA/MRTFB knockdown efficiency upon transfection with sh-Ctrl (control) or sh-MRTFA/B plasmids. Right: table of gene expression effects upon serum-treatment of MRTFA/B depletion. SI= serum-induced; Stvd= starved; c= no dox induction. UP= number of genes where expression goes up, DOWN= number of genes where expression declines.

Wound-healing migration assays

MRTFA and MRTFB are known for their role in cancer metastasis (Liao et al, 2014; Olson & Nordheim, 2010). Depletion of MRTFA/B was shown to result in reduced cell adhesion, motility and invasion in human breast cancer cells (Medjkane et al, 2009). To investigate the effects of MRTFA/B depletion in EwS cells we performed knockdown of MRTFA, MRTFB or both in the presence or absence of doxycycline in A673 cells before creating a scratch for analysis of wound healing capacity. Combined knockdown of MRTFA and MRTFB (si- MRTFA+B) strongly inhibited the ability of cells to close the wound as compared to controls (Fig. E2A). Single knockdown of MRTFA and MRTFB had a similar effect, however, less significant (Fig. E3A). Interestingly, knockdown of EWS-FLI1 (EWS-FLI1-low) did not 69 drastically alter the anti-migratory effect of MRTFA/B depletion in the early timepoints of the wound-healing migration assay. At the 42 h and 48 h timepoints post wounding, however, the inhibitory effect of MRTFA/B knockdown on the wound-closure capacity was slightly increased upon EWS-FLI1-low levels as compared to EWS-FLI1-high (Fig. E2A). Knockdown of MRTFA alone was inhibiting wound-closure more significantly in the absence of EWS-FLI1 than in the presence (Figure E3A). Nevertheless, we observed that silencing of EWS-FLI1 per se inhibited wound-closure of the A673/TR/shEF cells at 48h post knockdown (Fig. E3B), which is opposite to what has been published so far for prolonged EWS-FLI1 knockdown (>1 week) (Chaturvedi et al, 2012; Pedersen et al, 2016). At this point we cannot exclude that the effects of the wound-healing migration assays might be biased by altered proliferation capacity upon EWS-FLI1 depletion, and further studies are needed to draw conclusions from these experiments. A potential influence of MRTFA/B knockdown on cell cycle regulation can, however, be excluded as responsible for the observed effects in the wound-healing assays, since MRTFA, MRTFB or combined depletion did not affect the cell cycle (Fig. E2B). As already described (Hu et al, 2008; Schwentner et al, 2015) knockdown of EWS-FLI1 strongly induces G1 proliferation arrest in EwS cells, which we also observed in our A673/TR/shEF cell line.

Assessment of clonogenicity (Soft agar assays)

The effects of MRTFA and MRTFB depletion were also assessed by soft-agar clonogenicity assays to determine whether the ability of EwS cells to form colonies under surface independent growth conditions would be influenced by MRTFA/B. Interestingly, both MRTFA and MRTFB knockdown significantly reduced the ability of A673/TR/shEF cells to form colonies in soft agar as compared to the si-Control (Fig. E2C). EWS-FLI1 knockdown completely abolished the ability of cells to grow in an anchorage-independent manner (Fig. E3C) (Smith et al, 2006).

Figure E2. Functional analysis of the combined MRTFA/B knockdown in A673/TR/shEF. A. Wound-healing migration assays of the combined si-RNA mediated MRTFA and MRTFB knockdown under EWS-FLI1-high (left) and –low (right) conditions. Scratches were imaged at timepoint zero (timepoint of scratch) and 36 h or 48 h post scratch. Quantificantion of the relative wound area (in %) is shown below. n=3. mean±SEM. p-values were calculated using Anova with Bonferroni post-testing. * p≤0.05; **p≤0.01; ***p≤0.001. B. Cell cycle analysis of MRTFA, MRTFB or MRTFA+B depleted cells upon EWS-FLI1-high (no dox) or –low (+dox). Percentage of cells in G1, S or G2 phase is shown. n=3 mean±SEM. C. Soft agar assays after MRTFA or MRTFB knockdown in the presence of EWS-FLI1. Number of colonies are quantified in the graph. n=3 mean±SEM. Statistics were calculated using Two-tailed t-test. **p≤0.01.

Figure E3. Functional analysis of the single MRTFA or MRTFB knockdown in A673/TR/shEF. A. Wound- healing migration assays upon MRTFA or MRTFB depletion as compared to control (si-Ctrl) transfected cells. Images were taken at timepoint of the scratch (0 h), 36 h or 48 h post scratch. Relative wound area at various timepoints were quantified and are shown below. n=3 mean±SEM. Statistics were calculated using Anova with Bonferroni post-testing. * p≤0.05; **p≤0.01; ***p≤0.001. B. Quantification of the relative wound area comparing the effects of EWS-FLI1-high (no dox) with –low (+ dox) levels in si-Control transfected cells only. n=3. mean±SEM. statistics were calculated using Anova with Bonferroni post- testing. * p≤0.05; **p≤0.01; ***p≤0.001. C. Soft agar assays comparing the effects of dox versus no dox. n=3. 72

MRTFA ChIP-sequencing

Additionally to the data shown in chapter 2.2 (manuscript), we also performed ChIP-seq for MRTFA. MRTFA ChIP efficiency was attested before ChIP-seq using primers for a promoter region in the MYH9 gene. After the first round of MRTFA ChIP-seq we identified a significant MRTFA ChIP-seq hit in the promoter of the SETD1A gene, which we then used for the validation of MRTFA ChIP efficiency (Fig. E4A). For attesting the ChIP-efficiency, we considered a five to ten fold change between positive control and negative control as sufficient. The pull-down efficiency for MRTFA, however, was much weaker than for MRTFB (271 peaks versus 11737 peaks at cut-off 10). Nevertheless, the results obtained from the MRTFA ChIP-seq resembled those obtained from the MRTFB ChIP-seq (Fig.E4) (chapter 2.2. Fig.3). The genome-wide ChIP-seq distribution pattern of MRTFA highly resembled those of MRTFB (chapter 2.2; Fig.3A) with more than half of the peaks (66 %) being located close to the TSS of genes (Fig. E4B). About 62 % of MRTFB peaks overlapped with MRTFA (Fig.E4C), however, MRTFB peaks overlapped only to 1.4% with MRTFA. This result is due to the high discrepancy of peak numbers in the MRTFA and MRTFB ChIP-seq. Forty-eight percent of MRTFA peaks overlapped with SRF (Fig. E4C) whereas 77 % of MRTFA peaks overlapped with EWS-FLI1, the majority of this peaks was also shared by MRTFB (Fig. E4D). These results are comparable to the results obtained in the MRTFB ChIP (chapter 2.2., Fig.3). Analysis of enriched motifs of the MRTFA, MRTFB, SRF and EWS-FLI1 ChIP-seq are shown in Figure E4D and were obtained by HOMER de-novo motif analysis. MRTFA and MRTFB ChIP-seq are highly enriched for ETS and AP-1 motifs, which are also strongly enriched in the EWS-FLI1 ChIP-seq (Fig. E4D). For further discussion of ChIP-seq motifs see chapter 2.2.

Figure E4. MRTFA ChIP-seq results. A. ChIP-qPCR of MRTFA ChIP before sequencing. PK= positive control primer, Neg.Ctrl= negative control primer. Shown is promoter occupancy relative to input of one representative replicate. B. Genomic distribution of MRTFA ChIP-seq peaks (271 peaks). C. Venn diagram of overlaps between SRF (32515 peaks), MRTFA (271 peaks) and MRTFB (11737 peaks) ChIP-seq peaks under serum-induced (SI) conditions. D. Venn diagram of overlaps of EWS-FLI1 (54881 peaks), MRTFA and MRTFB ChIP-seq peaks under SI. E. HOMER de-novo motif analysis of MRTFA, MRTFB, SRF and EWS-FLI1 ChIP-seq.

Chapter THREE: Discussion

3.1. General discussion

The clinical fight against recurrent tumours and metastatic disease is still far from won in the case of EwS. Improved treatment regimens led to relatively high survival rates when it comes to treating patients with localized tumours if no metastases are present, however, a great portion of EwS patients are encountered with metastases already upon diagnosis (Bernstein et al, 2006; Lawlor & Sorensen, 2015). In order to improve the existing treatment protocols and develop effective compounds targeting the metastatic propensity of EwS cells, a deeper understanding of the molecular mechanisms driving these events is urgently needed. Our study aimed at investigating the molecular mechanisms in EwS that might favour metastatic spread. We directed our attention towards the fact that the major driver of EwS, the oncogenic fusion protein EWS-FLI1, profoundly affects EwS cellular morphology (Amsellem et al, 2005; Chaturvedi et al, 2014; Chaturvedi et al, 2012). In particular, EWS- FLI1 seems to repress cytoskeletal structures such as actomyosin bundles (stress fibres) and focal adhesions. Depletion of EWS-FLI1 results in restoration of actin-fibres, numbers of focal adhesions concordant with a drastically altered cellular phenotype that resemble those of mesenchymal stem cells (MSCs) (Tirode et al, 2007) (for more information see chapter 2.1: introduction and discussion). So far only a panel of cytoskeletal genes, whose expression is repressed by EWS-FLI1, has been linked to this phenotype (Amsellem et al, 2005; Chaturvedi et al, 2014). The genome-wide mechanism by which EWS-FLI1 represses the actin-cytoskeleton, however, is still under-investigated. We directed our attention towards the strong transcriptional deregulation of EWS-FLI1, which we found to affect a great number of Rho-regulated genes. Our investigations led us to question a potential perturbation of the Rho transcriptional effectors MRTFA/B, which we confirmed by our data. We furthermore found that the Rho/actin-regulated transcriptional co-activators YAP/TAZ, seem to be involved in MRTF-target gene expression involving TEAD transcription factors. Moreover, knockdown of MRTFB and TEAD strongly antagonized the effects of EWS-FLI1 knockdown. We found that a great number of these shared inversely regulated target genes are cytoskeletal key players, important for the formation of actin-structures and cell- communication with the ECM. Our data led to the development of a model that explains the effects of EWS-FLI1 on cellular morphology by perturbation of the transcriptional module downstream of Rho-actin, involving MRTFB and YAP-1/TEAD which is responsible for signalling back to the actin-cytoskeleton. EWS-FLI1, hence, via this transcriptional hub represses cytoskeletal integrity, potentially promoting the metastatic propensity of EwS cells.

Serum-stimulation in EwS

One of our initial hypotheses was based on observations form previous serum-deprivation experiments in our group. Interestingly, we found that serum-deprivation did only marginally impact gene expression in EwS cell lines (unpublished data, Kovar lab). Given the great number of Rho-SRF target genes among the typical serum-inducible genes, which did however not respond to serum in our system, we hypothesized that serum-response is uncoupled in these cells by EWS-FLI1. First, we recapitulated our initial observations by starving A673 EwS cells overnight followed by serum-induction for 60 minutes with medium containing a high concentration (20%) of serum. Only a small number of genes responded to serum treatment as compared to starved conditions, which were mostly IEGs. Since, we hypothesized that the serum-effect is inhibited in the presence of EWS-FLI1, we performed the same experiments upon knockdown of the fusion oncogene (see also: section 2.1, Supplementary Table 4). To our great surprise, however, knockdown of EWS-FLI1 did not drastically increase the number of serum-responsive genes. We also used an osteosarcoma cell line (U2OS) to compare the effects of serum in EwS and OS cells (Fig. E1). Osteosarcoma is the most common form of bone cancer and, in contrast to EwS, is not driven by an ETS-fusion-oncogene (Heare et al, 2009). Although slightly more genes were affected by treatment with serum in OS, especially with an increase in gene expression, overall the effects of serum-treatment were comparable to the EwS cells (59 genes in OS and 38 genes in EwS) (Fig. E1). Interestingly, the effect on MRTFA/B knockdown on gene- expression was greater in EwS cells than in OS cells, especially under starved conditions (Fig. E1). Two third of the upregulated serum-inducible genes were affected by MRTFA/B knockdown in EwS but only 9 of 59 upregulated genes did respond to MRTFA/B knockdown in U2OS. Given the strong effects of MRTFA/B knockdown in EwS cells upon combined knockdown with EWS-FLI1 (chapter 2.2; Fig.2C), MRTFA/B might play different roles in EwS than in OS.

Phenotypic effects of MRTFA/B in EwS

In chapter 2.4 the functional significance of MRTFA/B depletion was investigated (Fig E2+E3). Combined MRTFA and MRTFB knockdown significantly reduced the ability of EwS cells for wound-healing and to form colonies in soft-agar. Interestingly, although MRTFA/B transcriptional function is overall repressed by EWS-FLI1, in our functional migration assay depletion of MRTFA and MRTFB showed significant effects upon EWS-FLI1-low as well as – high conditions (Fig. E2A and Fig. E3A). Since a small number of MRTFA/B target genes is regulated independently of EWS-FLI1 high/low levels, it is conceivable that the MRTFA/B target gene/s which is/are responsible for the observed effects is/are among them.

Knockdown of EWS-FLI1 completely abolishes the ability of EwS cells to grow under anchorage-independent conditions in soft agar (Fig. E2C). We could therefore solely investigate the effects of MRTFA and MRTFB depletion on colony-formation in the presence of EWS-FLI1. Both MRTFA and MRTFB knockdown significantly reduced the number of colonies grown in soft agar (Fig. E2C). Given the strong transcriptional effects observed under combined knockdown of EWS-FLI1, MRTFA and especially MRTFB (chapter 2.2. Fig. 2) we expected a big difference in the functional consequence of MRTFA/B depletion depending on presence/absence of the fusion oncogene. However, due to the growth inhibitory effect of EWS-FLI1 knockdown we were unable to test this hypothesis by wound-healing assay with confidence and further in depth analyses comparing different time points after EWS-FLI1 modulation are required.

Are Rho inhibitors an option in the treatment of cancer?

The Rho pathway is the mediator of cellular movements. It is involved in the formation of acto-myosin bundles (stress fibres), which are important for contraction and dislocation of the cell body, as well as formation of membrane protrusions (lamellipodia, filopodia) required to pull the cell body forward and perform directed cell movements (polarity). Focal adhesions are actin-rich structures which serve as anchors of stress-fibres. They contain hundreds of different receptors among them integrins, which coordinate interactions with the ECM or neighbouring cells (Mattila & Lappalainen, 2008). All these processes underlie tight regulations, achieved by composition of multiple processes within the cells. A myriad of extracellular signals activates a number of different receptor types. The bottleneck of this complex signal integration is activation of Rho GTPase, which in turn regulates a large number of effectors. Targeting Rho GTPases or their most important downstream effectors hence seems like a promising strategy for the treatment of highly metastatic cancers. The majority of molecules developed to inhibit Rho GTPase activity target the C-terminal isoprenylation site, required for membrane association of Rho GTPase. However, inhibitors of this modification are not very specific. The lack of a unique targetable pocket has complicated the development of specific molecules directed against Rho family members. Nevertheless, with the use of nuclear magnetic resonance (NMR) and large drug-screens (e.g. virtual ligand screening) characterization of Rho protein crystal structure and identification of novel inhibitors is progressing (Evelyn et al, 2007; Smithers & Overduin, 2016). So far inhibitors of Rho GTPases or their downstream effectors such as ROCK1/2 have not entered clinical trials when it comes to treating cancer. Rho and ROCK inhibitors have, however, been applied in clinical trials as therapy for atherosclerosis and glaucoma, diseases where Rho/ROCK inhibition confers a vasorelaxative effect (Deng et al, 2011; https://clinicaltrials.gov/; Wang & Chang, 2014). The ROCK inhibitor Fasudil was used in a 77 recent phase 3 clinical trial for the treatment of Raynaud’s syndrome (Scleroma), a malfunction of the digital arteries and cutaneous arterioles (https://clinicaltrials.gov/). Among the Rho family members, especially RhoA and RhoC have caught the attention of cancer researchers in the development of novel treatment strategies for prevention of metastatic disease (Evelyn et al, 2007; Narumiya et al, 2009; Sahai & Marshall, 2002). RhoA and RhoC are implicated in the malignancy of several tumours and frequently overexpressed in cancers (Evelyn et al, 2007). Using a SRE-reporter plasmid Evelyn et al performed a high throughput screen in order to identify novel compounds which target the GPCR-Rho axis. They came up with two compounds, one of them a very potent inhibitor of SRF-MRTF transcriptional activity downstream of RhoA signalling (Evelyn et al, 2007). This small molecule inhibitor, CCG- 1423, has shown to inhibit invasion of several cancer cell lines (Evelyn et al, 2007) and is also effective in vitro in the ETS-fusion driven prostate cancer cell line, PC-3 (Evelyn et al, 2016). Most inhibitors do not target Rho proteins directly but compete with GEFs or Rho downstream effectors (Smithers & Overduin, 2016). CASIN (Florian et al, 2012), ML141 and ZCL278 block the interaction of CDC42 with its GEF intersectin and inhibit GTP binding. The Rac1 inhibitor Secramide (NSC23766) was shown to be effective in prostate cancer cells (Nassar et al, 2006). Several ROCK inhibitors have been developed, among them the widely studied pan-ROCK inhibitor Y27634. Interestingly, a recent study proposed that in EwS cell lines treatment with a specific ROCK2 inhibitor significantly reduced migration and colony formation in soft agar (Pinca et al, 2017). Taken together, inhibition of Rho or their downstream effectors could be effective in preventing migration and invasion in ETS-driven cancers such as prostate cancer as well as EwS.

EWS-FLI1, the actin cytoskeleton and cellular plasticity

The effects that EWS-FLI1 exerts on the cellular cytoskeleton seem counterintuitive since EWS-FLI1 expression suppresses migration, adhesion and invasion. Knockdown of EWS- FLI1 restores these functional effects alongside with profound changes in cellular morphology including increased numbers of stress-fibres and focal adhesions (Chaturvedi et al, 2014; Chaturvedi et al, 2012). Given the fact that EwS cells are prone for early metastasis onset the lack of active migration of EWS-FLI1-expressing cells seems quite irrational. However, more and more studies appreciate the idea of a tumour cell, which constantly toggles between proliferative and migratory cell states (Chaturvedi et al, 2014; Franzetti et al, 2017; Pedersen et al, 2016). The proliferative state is characterized by non-polarized cells which exhibit few membrane protrusions (lamellipodia/invadopodia). The migratory state is an active polarized cell state with actin-rich structures such as focal-adhesions and protrusions, needed for directed cellular movements (Mattila & Lappalainen, 2008). The

78 former described cell state resembles that of EwS cells which highly express EWS-FLI1, whereas the latter state resembles that of MSCs or EwS cells with low EWS-FLI1 levels (Franzetti et al, 2017; Tirode et al, 2007) (see also: chapter 2.2. Fig.6). A recent study by the group of O. Delattre corroborated this ideas by showing that different expression levels of EWS-FLI1 determine the phenotypic plasticity of EwS cells. They showed that EWS-FLI1-low cells are migratory and highly invasive, whereas EWS-FLI1-high cells are actively proliferating (Franzetti et al, 2017). Chaturvedi et al furthermore noted that the proliferative EWS-FLI1-high cell state contributes to survival of EwS cells under anchorage-independent conditions but is disadvantageous for metastatic second-site colonization (Chaturvedi et al, 2014). By switching EWS-FLI1 expression levels between high and low states, EwS cells might have perfected metastasis establishment. Several factors could furthermore influence EWS-FLI1 levels, and hence EwS cellular plasticity, directly. Growth factors such as the fibroblast growth factor FGF where shown to affect EWS-FLI1 levels (Girnita et al, 2000). Pedersen and colleagues reported an effect of Wnt ligands on EWS-FLI1 protein expression and observed that induction of EwS cell with Wnt ligands correlates with the gene-expression signature upon EWS-FLI1 knockdown. Furthermore, Krook et al described the response of EwS cells to stress (e.g. serum deprivation) by upregulation of the CXCR4 chemokine receptor. They showed that stress increases CXCR4 expression and promotes chemotactic migration and invasion towards CXCL12 (SDF-1), the CXCR4 ligand (Krook et al, 2014). EwS cells hence are highly responsive to the microenvironment and respond to changes by adapting their metastatic program accordingly.

Genes involved in the cytoskeletal autoregulatory feedback-loop

The cytoskeleton has the ability to regulate itself via the autoregulatory actin-MRTF feedback loop. As discussed in detail in chapter 1.4.4 Rho-induced polymerization of actin triggers the release of MRTFA/B to the nucleus and activates transcription of the cytoskeletal gene program. Among our candidate gene-set of MRTFB/TEAD and EWS-FLI1 shared target genes, which are repressed by EWS-FLI1 but reactivated upon combined MRTFB or TEAD knockdown upon low-EWS-FLI1 levels, are several important genes which are involved in feed-back signalling to the actin cytoskeleton or are components of the actin-cytoskeleton per se (chapter 2.2. Fig. 5D and Fig.6). Tropomyosin 1 (TPM-1) is a cytoskeletal gene that is a major constituent of actin filaments (Gunning et al, 2015). Caldesmon 1 (CALD1) is a member of the calmodulin family of calcium dependent proteins that controls the actin cytoskeleton and is an important regulator of smooth muscle function (Kakiuchi, 1985). Transgelin (TAGLN, SM22) belongs to the calponin family and is an actin-binding protein which influences the bundling of actin filaments and subsequently actin-cytoskeleton stability.

Interestingly, TAGLN is not only repressed in EwS and several other cancer cell lines, but also inhibits invasion of the ETS-fusion driven prostate cancer cell line PC-3 in matrigel upon ectopic overexpression (Thompson et al, 2012). Transcriptional repression of the above described genes by EWS-FLI1 potentially contributes to the EwS phenotype due to compromised actin-cytoskeleton integrity. Furthermore, we found the CCN family proteins cysteine-rich protein 61 CYR61 (CCN1) and connective-tissue growth factor CTGF (CCN2) to be inversely transcriptionally regulated by MRTFB/TEAD and EWS-FLI1. This proteins are key molecules involved in extracellular signalling via integrins and the ECM and regulate adhesion, migration as well as chemotaxis (Holbourn et al, 2008). Repression of the CCN family proteins could therefore lead to an alteration in response of EwS cells to extracellular stimuli. Taken together EWS-FLI1 represses a big number of genes that are involved in the cytoskeletal autoregulatory feedback signalling.

MRTFs and EWS-FLI1: where is the link?

Given the strong similarities of MRTFB and EWS-FLI1 binding patterns and the profound overlaps in inversely regulated shared target genes the question for the missing link between MRTF and EWS-FLI1 remains. We initially hypothesized that EWS-FLI1 might compete with MRTFs for binding to SRF. This hypothesis was based on observations back in 1997 by Watson et al. who showed that the oncogenic fusion protein EWS-FLI1, like other ETS factors such as ELK1 and FLI1, can form a ternary complex with SRF on the SRE of the EGR1 promoter (Watson et al, 1997). Since TCFs and MRTFs compete for a common binding site on SRF (B-box) and their binding is mutually exclusive, we hypothesized that in the context of EwS EWS-FLI1 competes with MRTF for binding to SRF. As a consequence cytoskeletal target gene regulation as well as response to serum is disrupted as proposed by this model. Analysis of the MRTFA/B transcriptome further supported this hypothesis, showing a strong overall repression of MRTFA/B transcriptional function in the presence of EWS-FLI1. On top of this, upon combined knockdown of MRTFA/B and EWS-FLI1, MRTFA/B depletion antagonized the transcriptional effects of EWS-FLI1 depletion (Chapter 2.2). However, upon further investigation of the nature of these effects by ChIP-seq our initial hypothesis became quite unrealistic. To begin with, we found a weak overlap of EWS-FLI1 with SRF ChIP-seq peaks (chapter 2.2. Fig.3B). In contrast to, MRTFB ChIP-seq peaks overlapped profoundly with EWS-FLI1 (82% total) but only half as many peaks overlapped with SRF (40%). Only 8% of peaks were exclusively shared by MRTFB and SRF (see: Chapter 2.2. Fig 3B). Furthermore, we observed significant enrichments of MRTFB ChIP-seq peaks in distal regions associated with EWS-FLI1-anticorrelated target genes. These enrichments were

80 shared by EWS-FLI1, but not by SRF, irrespective of EWS-FLI1 presence or absence. Within these specific set of peaks, however, significant enrichments of the TEA domain family transcription factor (TEAD) binding motif was encountered (chapter 2.2. Fig4C). This led us to hypothesize that in regions associated with EWS-FLI1-anticorrelated genes MRTFs might rather associate with TEADs than with SRF. Recent literature further strengthened this hypothesis (Kim et al, 2016; Speight et al, 2016; Yu et al, 2015) (see also discussion chapter 2.2). Moreover, SRF shows a highly distinct chromatin binding pattern in EwS as compared to other cell systems (Esnault et al, 2014) (see also discussion chapter 2.2). We hardly encountered SRF binding to the bona-fide SRF binding motif, CArG, and found overwhelming enrichments of CTCF motifs in the SRF ChIP-seq. Taken together, these data contradicted our initial hypothesis of EWS-FLI1 competition with MRTFs for SRF binding, but rather supported a model of increased MRTFB binding to the DNA upon low-EWS-FLI1 levels, likely via recruitment to TEAD transcription factors in a complex with YAP-1.

EWS-FLI1 has been shown to engage in protein complexes with a wide range of regulators of the transcriptional machinery such as the hRBP7 subunit of the RNA polymerase 2 and the RNA helicase A (RHA) (Erkizan et al, 2010) (see also: chapter 1.2.3.). These interactions are mainly due to its function as an intrinsically disordered protein (IDP) rather than specific protein domains. The large overlaps in MRTFB and EWS-FLI1 binding could be the result of interactions of EWS-FLI1 with MRTFB and associated factors (e.g. TEAD, YAP-1), which potentially inhibits MRTFB´s transcriptional function.

MRTFB versus MRTFA

In our study we directed our investigations towards the molecular regulatory mechanisms of MRTFB, rather than MRTFA. This was primarily based on the finding that MRTFB antagonized EWS-FLI1-mediated transcriptional effects much stronger than MRTFA (chapter 2.2; Fig.2F), despite comparable expression levels in EwS cell lines (chapter 2.4. Table E1) and exclusion of differences in MRTFA and MRTFB knockdown efficiencies (chapter 2.2; Supplementary Fig. 2). Nevertheless, MRTFA ChIP-seq was performed additionally to MRTFB ChIP-seq (Fig.E4). Although the MRTFA pull-down resulted in far less peaks than the MRTFB ChIP-seq, peak distribution overlapped between MRTFA and EWS-FLI1, and transcription factor binding motifs enriched in MRTFA bound chromatin regions (Figure E4C- D) were comparable to the results obtained from the MRTFB ChIP-seq (chapter 2.4, Fig. 4A- C). The MRTFA ChIP likely resulted in less peaks due to weaker affinity of the MRTFA antibody, since ChIP-PCR for validated MRTFA targets (MYH9, SETD1A) attested specificity of the antibody (Figure E4A).

Conclusions and future perspectives

In conclusion the results obtained from this doctoral thesis emphasize the theory that cytoskeletal deregulation of EwS cells by EWS-FLI1 is achieved on a transcriptional level via perturbation of Rho-actin regulated transcription factors. Nevertheless, future studies are needed to understand the complex nature of the observed effects. We have yet not succeeded in demonstrating a direct interaction of MRTF and YAP/TAZ or TEAD in EwS by co-immunoprecipitation. Transcriptional complexes typically show a rapid turnover, which makes it difficult to detect direct binding of involved factors. It is yet unclear how EWS-FLI1 perturbs MRTFB and TEAD transcriptional activity and why they share so many common target genes. Interestingly we found that MRTFB chromatin occupancy in distal enhancers associated with EWS-FLI1-anticorrelated genes is not only enriched for TEAD binding motifs, but also for AP-1 motifs (chapter 2.1. Fig.4C). In fact TEAD and the AP-1 (Fos/Jun) transcription factors engage at enhancer regions and have been shown to drive oncogenicity (Liu et al, 2016; Zanconato et al, 2015). The occurrence of AP-1 sites in the respective MRTFB/TEAD and EWS-FLI1 enriched regions and the fact that EWS-FLI1 can bind AP-1 directly (Kim et al, 2006) could explain the missing link between MRTFB and EWS-FLI1 association.

The role of YAP/TAZ in EwS is still under-investigated. Hsu and Lawlor reported that the polycomb repressor protein BMI1 is responsible for aberrant stabilization of YAP-1 in EwS cells, which confers resistance to contact inhibition and promotes cell growth (Hsu & Lawlor, 2011). In fact, YAP/TAZ are important sensors of extracellular mechanic stress communicated via the stiffness of the ECM and the cell shape (Dupont et al, 2011). Among other cell types, MSCs are dependent on YAP/TAZ activity, which determines the differentiation lineage depending on the ECM rigidity. High stiffness of the cells´ environment promotes differentiation of MSCs into osteogenic cells whereas soft substrates promotes differentiation into the adipogenic lineage (Halder et al, 2012; Piccolo et al, 2014). EwS occurs in osteogenic as well as adipogenic tissues and MSCs are the presumed EwS precursors. Deregulation of YAP/TAZ activity could hence be trigger by oncogenic deregulation resulting in inhibition of differentiation and EwS formation. Interestingly, mechano transduction via YAP/TAZ seems to be mainly independent of the canonical Hippo pathway and conducted via Rho-mediated actin polymerization (Dupont et al, 2011) (see also chapter 2.2. discussion). We found that subcellular localization of YAP-1, like for MRTFs, is promoted by serum-induced actin polymerization and can be inhibited with the F- actin inhibitor latrunculin B (LatB) (chapter 2.2. Supplementary Fig. 5). Our candidate genes of the cytoskeletal autoregulatory-feedback (chapter 2.2. Fig. 5D and Fig. 6) were also tested

82 for YAP-1 regulation by ChIP q-PCR. Indeed we found that YAP-1 also binds to the distal enhancers which are occupied by MRTFB and EWS-FLI1 of several of these genes (chapter 2.2., Supplementary Fig. 4C). Given the emerging role of YAP/TAZ and TEADs in cancer, investigation of their functional significance in EwS is highly promising for future targeted therapies. Our data support synergy of the Rho-actin regulated transcriptional co-activators MRTFB and YAP-1 in complex with TEAD and suggest that EWS-FLI1 directly or indirectly interferes with their transcriptional regulation. The Rho-actin transcriptional axis likely serves as a regulatory hub (ab)used by EWS-FLI1 in order to deregulate cytoskeletal target gene regulation and influence EwS cell morphology and plasticity. Given the urgent need of novel therapies for treatment of metastatic EwS, the gain in knowledge obtained from this study could open doors for novel treatment options for this devastating disease.

CHAPTER FOUR: Material& Methods

A detailed Materials and Methods section can be found in Chapter 2.2 (manuscript). Extended Materials and Methods used for the generation of this thesis are described below:

Extended Methods for Thesis:

Cell lines The U2OS OS cell line was kindly provided by Prof. Michael Grusch (Institute of Cancer Research of the Medical University Vienna, Borschkegasse, Vienna, Austria).

Plasmids and Vectors For efficient reduction of MRTFA (MKL-1) and MRTFB (MKL-2) RNA and protein levels a short-hairpin RNA (CATGGAGCTGGTGGAGAAGAA) integrated into a pLKO plasmid was transfected into the cells (Addgene #27161). For ectopic overexpression of MRTFA, the p3xFLAG-MKL1 plasmid (Addgene #11978) and MRTFB the p3XFLAG-MKL2 plasmid (Addgene #27175), which were both kindly provided by Dr. Ron Prywes (Columbia University, NY, USA) were used.

Western Blot Western blot was carried out as described in Chapter 2.2 (Methods). Briefly, polyacrylamide- gels were manufactured using reagents and volumes described in Table 3.

Separation gel Stacking gel 8.5 % Bis-AA 6.5 % Bis-AA µl per gel µl per gel 30%AA / 0,8% Bis 1400 1100 30%AA / 0,8% Bis 415 Aqua dest 2275 2575 Aqua dest 1700 1,5M Tris (pH8.8) 1250 1250 1,5M Tris (pH6.5) 315 20% SDS 25 25 20% SDS 12.5 10% APS 50 50 10% APS 25 TEMED 6 6 TEMED 2.5

Table 3. Concentrations of reagents used for preparation of western blot gels. AA/Bis= Rotiphorese Bisacrylamid (Rotiphorese Gel 30, Lactan Chemicals, Graz, Austria).

Antibodies Additional antibodies used in this study are MRTFA (Santa Cruz, TX, USA; sc-32909) for ChIP experiments. Anti-Flag (Sigma, St.Louis, USA; F3165) was used for western blot analysis.

Wound healing assays For wound-healing assays, A673/TR/shEF cells were transfected with the indicated si-RNAs (si-MRTFA, si-MRTFB or both) and additionally treated with doxycycline for 48 h, and cultured in 24-well plates under standard serum conditions (10% FBS). After the attached cells formed a confluent cell layer, cells were wounded using a sterile 200µl pipette tip. Images were captured at one hour intervals over 48 h using a Nikon Ti-E Live Cell Imaging microscope with Ti-ND6-PFS-S Perfect Focus System. Relative wounding area was measured with ImageJ and normalized to the respective zero hour time point. Wound healing assay was performed in technical as well as biological triplicates. Statistics were performed using Two-way Anova with Bonferroni post-testing.

Soft agar assays Soft agar assays were performed as described previously (Aryee et al, 2010). Briefly, A673 cells were transfected with si-MRTFA or si-MRTFB and additionally treated with doxycycline for 48h. Approximately 120.000 cells were seeded per triplicate in a 6-well and cultivated for three weeks before staining and counting of the colonies. Mean of three independent experiments is shown, statistics were performed using paired t-test for continuous data.

Cell Cycle analysis Cell cycle analysis was carried out using the CycletestTM Plus DNA Reagent Kit (Becton Dickinson, New Jersey, USA) according to manufacturer’s recommendations. Briefly, cells were transfected with si-MRTFA, si-MRTFB or both and additionally treated with dox for 48h. Cells were subsequently harvested and approximately 250,000 cells were used for the cell cycle analysis, which was measured by FACS.

Extended primer list

g.DNA primer for ChIP q-PCR MRTFA ChIP SETD1A_PK_fw TCTAGATCGTCGTGGCGAAG SETD1A_PK_rev GTCTGCATTCGCACTTTCG SETD1A_Neg-Ctrl TCTCCCTTCCACCTTTTCCT SETD1A_Neg-Ctrl CCCTCGCTATATGGCCTTG Table 4. Table of oligonucleotides (extended).

MRTFA ChIP MRTFA ChIP, like for MRTFB, SRF and EWS-FLI1, was performed under serum-induced conditions. Cells were serum-starved over-night with 0.2% FBS-DMEM, the next day serum-

85 induced for 60 minutes and subsequently harvested for fixation (see chapter 2.2; methods section).

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Curriculum Vitae

Anna Maria Katschnig, MSc Schumanngasse 16/1, 1180 Vienna, Austria phone: +43/650/3909510 email: [email protected]

PERSONAL INFORMATION

Date of birth July 26th, 1986 Place of birth Klagenfurt, Austria Nationality Austrian

EDUCATION

2012-2017* PhD in Molecular Biology Medical University Vienna, Austria PhD thesis at the Children’s Cancer Research Institute (CCRI) Vienna (St. Anna Kinderkrebsforschung). 2009-2012 Master in Biochemistry and Molecular Biomedicine Karl-Franzens University (KFU) Graz, Austria Master exam passed with excellent success 2006-2009 Bachelor in Molecular Biology KFU Graz, Austria

EXPERTISE

. cell and bacterial culture, cloning, work with virus . RNA-seq, ChIP-seq and interpretation of large genomic data-sets . confocal microscopy . functional assays (immunoblot, migration assays, cell cycle analysis)

SCIENTIFIC WORK EXPERIENCE

2012-2017 PhD student Lab of Prof. Heinrich Kovar: “Molecular Biology of Solid Tumors” (Ewing Sarcoma). 2011-2012 Master student Lab of Prof. Heinz Sill at the Department of Hematology (MUG) 2010 Research assistant Lab of Prof. Horst Olschewski at the Department of Pulmonology (MUG). Duration: 2 months. 2007/ 2008/ 2009 Holiday internship at the Department of Hygiene, MUG in the field of bacteriology for altogether 3 months

SCIENTIFIC PRESENTATIONS

2014/ 2015/ 2016 Poster presentations of scientific work related to doctoral thesis at the international annual conference of the AACR (American Association of Cancer Research)

2015/2016 Poster presentation at the 11th and 12th YSA-PhD Symposium in Vienna 2013/ 2014/ 2016 Poster presentations at the annual meeting of the ÖGMBT (Austrian Association of Molecular Life Sciences and Biotechnology) 12/ 2015 Oral presentation of scientific work related to doctoral thesis at the ASSET (Analysing and Striking the Sensitivities of Embryonal Tumours) Joint meeting in Vienna 05/2014 Poster presentation at the 27th Annual Meeting of the European Musculo- Skeletal Oncology Society (EMSOS) in Vienna

FURTHER QUALIFICATIONS

Languages German (native), English (fluent), French (basic), Italian (basic) IT MS office, basic knowledge in bioinformatical databases (Uniprot, UCSC, DAVID, NCBI) 08/ 2015 Project planning and supervision of a chemistry school student at the CCRI

PUBLICATIONS

Mutz C.N, Schwentner R, Bouchard E, Mejia E.M, Katschnig A.M, Kauer M.O., Aryee D.N.T, Garten A, Banerji V, Kovar H. EWS-FLI1 confers exquisite sensitivity to NAMPT inhibition in Ewing sarcoma cells. Oncotarget. 2016. Schwentner R, Herrero-Martin D, Kauer M.O, Mutz C.N, Katschnig A.M, Sienski G, Alonso J, Aryee DNT, and Kovar H. The role of miR-17-92 in the miRegulatory landscape of Ewing sarcoma. Oncotarget. 2016. Mutz C.N, Schwentner R, Kauer M.O, Katschnig A.M, Kromp F, Aryee DNT, Erhardt S, Goiny M, Alonso J, Fuchs D, and Kovar H. EWS-FLI1 impairs aryl hydrocarbon receptor activation by blocking tryptophan breakdown via the kynurenine pathway activation. FEBS Letters. 2016; 590(14): 2063– 2075

Manuscripts in preparation:

Katschnig A.M, Kauer M.O, Schwentner R, Tomazou E.M, Mutz C.N, Linder M, Sibilia M, Alonso J, Aryee D.N.T, Kovar H. EWS-FLI1 perturbs MRTFB/YAP-1/TEAD target gene regulation inhibiting cytoskeletal auto-regulatory feedback in Ewing sarcoma. Submitted 02/2017.

Tsafou K, Radic B, Katschnig A.M, Mutz C.N, Iljin K, Kovar H. Targeting the druggable interactome of EWS-FLI1 in Ewing Sarcoma. Paper submission in 2017.

GRANTS&AWARDS

2016 Youth Travel Fund (YTF) of the ÖGMBT

HOBBIES&INTERESTS Yoga, Running, Kite-surfing, Arts, Travelling