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Chimeric EWSR1-FLI1 regulates the Ewing sarcoma susceptibility gene EGR2 via a GGAA microsatellite

Abstract

Deciphering the ways in which somatic mutations and germline susceptibility variants cooperate to promote cancer is challenging. Ewing sarcoma is characterized by fusions between EWSR1 and members of the ETS gene family, usually EWSR1-FLI1, leading to the generation of oncogenic transcription factors that bind DNA at GGAA motifs1,2,3. A recent genome-wide association study4 identified susceptibility variants near EGR2. Here we found that EGR2 knockdown inhibited proliferation, clonogenicity and spheroidal growth in vitro and induced regression of Ewing sarcoma xenografts. Targeted germline deep sequencing of the EGR2 locus in affected subjects and controls identified 291 Ewing-associated SNPs. At rs79965208, the A risk allele connected adjacent GGAA repeats by converting an interspaced GGAT motif into a GGAA motif, thereby increasing the number of consecutive GGAA motifs and thus the EWSR1-FLI1–dependent enhancer activity of this sequence, with epigenetic characteristics of an active regulatory element. EWSR1-FLI1 preferentially bound to the A risk allele, which increased global and allele-specific EGR2 expression. Collectively, our findings establish cooperation between a dominant oncogene and a susceptibility variant that regulates a major driver of Ewing sarcomagenesis.

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Figure 1: EGR2 overexpression is mediated by EWSR1-FLI1.
Figure 2: EGR2 is critical for the growth and tumorigenicity of Ewing sarcoma.
Figure 3: Fine-mapping and epigenetic profiling revealed candidate EGR2 regulatory elements.
Figure 4: Germline variation at mSat2 modulates EWSR1-FLI1–dependent EGR2 expression.

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Acknowledgements

T.G.P.G. is supported by a grant from the German Research Foundation (DFG GR3728/2-1), by the Daimler and Benz Foundation in cooperation with the Reinhard Frank Foundation, by LMU Munich's Institutional Strategy LMUexcellent within the framework of the German Excellence Initiative and by the Mehr LEBEN für krebskranke Kinder–Bettina-Bräu-Stiftung. D.S. is supported by the Institut Curie–SIRIC (Site de Recherche Intégrée en Cancérologie) program. F.C.-A. is supported by a grant from the Asociación Pablo Ugarte and Instituto de Salud Carlos III RTICC RD12/0036/0027. D.G.C. is supported by a grant from the InfoSarcomes Association. The Childhood Cancer Survivor Study is supported by the National Cancer Institute (CA55727, G.T. Armstrong), with funding for genotyping from the Intramural Research Program of the National Institutes of Health, National Cancer Institute. This work was supported by grants from the Institut Curie; INSERM; the Agence Nationale de la Recherche (Investissements d'Avenir) (ANR-10-EQPX-03); the Canceropôle Ile-de-France (ANR10-INBS-09-08); the Ligue Nationale Contre le Cancer (Equipe labellisée); the Institut National du Cancer (PLBIO14-237); the European PROVABES (ERA-649 NET TRANSCAN JTC-2011), ASSET (FP7-HEALTH-2010-259348) and EEC (HEALTH-F2-2013-602856) projects; and the Société Française des Cancers de l'Enfant. The following associations supported this work: Courir pour Mathieu, Dans les pas du Géant, Olivier Chape, Les Bagouzamanon, Enfants et Santé, and les Amis de Claire. The Charnay laboratory was financed by INSERM, the CNRS, the Ministère de la Recherche et Technologie, and the Fondation pour la Recherche Médicale. It has received support under the program “Investissements d'Avenir” launched by the French Government and implemented by the ANR, with the references ANR-10-LABX-54 MEMOLIFE and ANR-11-IDEX-0001-02 PSL* Research University. We thank J. Maris for providing genotype information for the neuroblastoma data set, and we thank L. Liang and W. Cookson for providing access to genotype data on the LCL data set. We thank H. Kovar (Children's Cancer Research Institute Vienna, Vienna, Austria) for providing cell lines STA-ET-1, STA-ET-3 and STA-ET-8, and F. Redini (University of Nantes, Nantes, France) for providing cell line TC-32. Human MSC lines L87 and V54-2 were kindly provided by P. Nelson (University Hospital LMU, Munich, Germany). We also thank the following clinicians and pathologists for providing samples used in this work: I. Aerts, P. Anract, C. Bergeron, L. Boccon-Gibod, F. Boman, F. Bourdeaut, C. Bouvier, R. Bouvier, L. Brugiéres, E. Cassagnau, J. Champigneulle, C. Cordonnier, J. M. Coindre, N. Corradini, A. Coulomb-Lhermine, A. De Muret, G. De Pinieux, A.S. Defachelles, A. Deville, F. Dijoud, F. Doz, C. Dufour, K. Fernandez, N. Gaspard, L. Galmiche-Rolland, C. Glorion, A. Gomez-Brouchet, J.M. Guinebretiere, H. Jouan, C. Jeanne-Pasquier, B. Kantelip, F. Labrousse, V. Laithier, F. Larousserie, G. Leverger, C. Linassier, P. Mary, G. Margueritte, E. Mascard, A. Moreau, J. Michon, C. Michot, F. Millot, Y. Musizzano, M. Munzer, B. Narciso, O. Oberlin, D. Orbach, H. Pacquement, Y. Perel, B. Petit, M. Peuchmaur, J.Y. Pierga, C. Piguet, S. Piperno-Neumann, E. Plouvier, D. Ranchere-Vince, J. Rivel, C. Rouleau, H. Rubie, H. Sartelet, G. Schleiermacher, C. Schmitt, N. Sirvent, D. Sommelet, P. Terrier, R. Tichit, J. Vannier, J.M. Vignaud and V. Verkarre. We also thank D. Darmon for technical assistance, S. Grossetete-Lalami for bioinformatic assistance, and V.R. Buchholz and E. Butt for critical reading of the manuscript.

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Authors and Affiliations

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Contributions

T.G.P.G. coordinated and designed the study, performed all functional experiments, analyzed the sequencing data, performed bioinformatic analyses, wrote the paper, designed the figures and helped with grant applications. V. Bernard processed the sequencing data and performed bioinformatic analyses. P.G.-H. participated in the study design, cloned enhancer elements and contributed to data analysis. V.R. performed all sequencing experiments and helped analyze the bioinformatic data. D.S. contributed to the in vivo experiments, performed the ChIP-MiSeq experiments and provided experimental protocols. M.-M.A., F.C.-A., A.H.J. and S.Z. helped with functional experiments. O.M., F.T. and C.L. provided statistical advice and helped in the bioinformatic analyses. G. Perot assisted in generation of the shRNA constructs. M.-C.L.D., O.O. and P.M.-B. provided Ewing sarcoma samples and annotation. G. Pierron, S.R. and E.L. provided and prepared Ewing sarcoma samples. T.R.F. coordinated and supervised sequencing experiments. V. Boeva helped analyze ChIP-Seq data. J.A. provided the A673-TR-shEF1 and SK-N-MC–TR–shEF1 cell lines. A.S.V. performed principal-component analysis clustering of Ewing sarcoma subjects and controls. G.C.-T. and O.C. provided DNA from healthy controls. D.G.C. and S.J.C. provided genetic and statistical guidance. S.B., L.M.M., M.J.M. and S.J.C. provided data for the CCSS replication cohort and performed imputation analyses. P.C. provided advice on analyses concerning EGR2 and laboratory infrastructure. O.D. initiated, designed and supervised the study; provided biological and genetic guidance; analyzed the data; wrote the paper together with T.G.P.G.; and provided laboratory infrastructure and financial support. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Olivier Delattre.

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The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Expression pattern of EGR2 and ADO in normal tissues relative to Ewing sarcoma.

The normal-body atlas consisted of 353 microarrays representing 63 individual tissue types (GSE3526). Gene expression levels are shown as the mean and s.e.m. of n ≥ 3 samples per tissue type. The normal-body atlas and the Ewing sarcoma (EwS) data (GSE34620) were normalized simultaneously by RMA using custom brainarray CDF (v18, ENTREZG). All microarray data were generated on Affymetrix HG-U133Plus2.0 arrays.

Supplementary Figure 2 eQTL analyses across tissue types identify Ewing sarcoma-specific correlations of EGR2 and ADO expression with the risk-allele (G) at rs1848797.

Data are shown as medians (horizontal bars) with ranges for the 25th−75th percentile (box) and 10th−90th percentile (whiskers). Outliers are depicted as dots. P values determined via linear regressions. EwS, Ewing sarcoma; AML, acute myeloid leukemia; LCL, lymphoblastoid cell lines.

Supplementary Figure 3 Analysis of EGR2 and ADO expression in Ewing sarcoma cell lines after knockdown of EWSR1-FLI1.

A673, SK-N-MC, EW7 and POE cells were transfected either with non-targeting control siRNA or siRNA targeting EWSR1-FLI1. Gene expression was assessed 48 h thereafter by qRT-PCR. FC, fold change. Data are shown as the mean and s.e.m.; n ≥ 5 independent experiments. Two-tailed unpaired Student’s t-test; ns, not significant; * P < 0.05, ** P < 0.01, *** P < 0.001.

Supplementary Figure 4 Knockdown of EGR2 reduces clonogenic growth, cell cycle progression, and viability of Ewing sarcoma cells.

(a) Analysis of EGR2 protein expression by immunoblot in Ewing sarcoma cell lines (loading control: β-actin). The neuroblastoma cell line SK-N-SH served as negative control. (b) Analysis of EGR2 protein expression by immunohistochemistry in tumors of xenografted Ewing sarcoma cell lines (A673, TC-71 and SK-ES1), the alveolar rhabdomyosarcoma cell line SJ-RH30, and the neuroblastoma cell line IMR-32, and comparison with EGR2 mRNA expression levels as determined by Affymetrix HG-U133Plus2.0 arrays (GSE36133). Scale bars = 200 µm. (c) qRT-PCR analysis of knockdown efficacy of siRNAs used to silence EGR2 or ADO (48 h after transfection). Data are shown as the mean and s.e.m.; n ≥ 4 independent experiments. (d) Analysis of clonogenic growth after seeding at low-density and serial re-transfection with siRNA every four days. Cells were fixed 9–14 days after seeding and individual colonies were colorized with crystal violet. (e) Analysis of cell cycle phases by PI staining 96 h after transfection with siRNA. EGR2 knockdown reduces the percentage of cells in S phase (P < 0.01 for A673, SK-N-MC, and POE; P = 0.12 for EW7), while increasing the percentage in sub G1 phase (all P < 0.0001). (f) Analysis of apoptosis by Annexin-V-staining 96 h after transfection with siRNA. Data in d-f are shown as the mean and s.e.m. of results obtained with two different siRNAs for EGR2 and three different siRNAs for ADO as displayed in c; n ≥ 3 independent experiments. Two-tailed unpaired Student’s t-test; ns, not significant; *** P < 0.001.

Supplementary Figure 5 EGR2 is a downstream component of the FGF pathway in Ewing sarcoma.

(a) Scatter-dot plot and medians (horizontal bars) of EGFRs (gray) and FGFRs (red) expression levels in n = 117 primary Ewing sarcoma tumors (GSE34620). (b) Analysis of proliferation of Ewing sarcoma cell lines with a Resazurin assay. Cells were seeded in RPMI 1640 medium with 0.5–1% FCS and stimulated with the indicated growth factor (GF) concentrations for 72 h. Data are shown as the mean and s.e.m.; n ≥ 6 experiments. (c) Analysis of EGR2 induction by qRT-PCR in Ewing sarcoma cell lines after incubation with either EGF or bFGF (both 10 ng/ml). The EGFR expressing MDA-MB-231 breast cancer cell line served as a positive control for EGF action. Data are shown as the mean and s.e.m.; n ≥ 3 independent experiments. Two-tailed unpaired Student’s t-test, ** P < 0.01, *** P < 0.001.

Supplementary Figure 6 Targeted germline deep sequencing of principal-component analysis (PCA)-matched Ewing sarcoma cases and controls.

(a) PCA-clustering of the selected core population (dashed box) for sequencing. (b) Analysis of target-region coverage after mapping and base quality filtering of reads (MQ20 and BQ20). (c) Analysis of average nucleotide coverage (high-quality reads) of the chr10 target-region across all samples. The median nucleotide coverage is reported (217X).

Supplementary Figure 7 Schematic illustration of the workflow for next-generation sequencing and variant analysis.

AAR, alternative allele ratio.

Supplementary Figure 8 Genomic coordinates, evolutionary sequence conservation, aligned DNA sequences and homology of EGR2 enhancer elements.

Mammal Cons, 46 vertebrates basewise conservation from the UCSC genome browser60; GERP, Genomic Evolutionary Rate Profiling of 30 vertebrate species from the UCSC genome browser; MultiZ Align, multiple sequence alignment from the UCSC Genome browser; MSE, Myelinating Schwann cell Enhancer; BoneE, Bone Enhancer. Sequence alignment of murine and human DNA sequences was carried out using Clustal Ω (v1.2.0)45. Asterisks indicate homologous nucleotides.

Supplementary Figure 9 Genomic coordinates, epigenetic profile and reference sequence of the mSat1 locus.

GGAA repeats are underlined by arrows. The reported numbers of GGAA motifs correspond to the reference sequence (hg19).

Supplementary Figure 10 Validation of ChIP efficiency by qRT-PCR in the Ewing sarcoma cell line MHH-ES1 (A/T at rs79965208).

A described CCND1 EWSR1-FLI1 binding site was used as positive control47, and an intronic CCND1 locus (intron 2) served as negative control. Data are shown as the mean and s.d.

Supplementary Figure 11 Conditional association analysis suggests that rs79965208 within mSat2 is the major EGR2 regulatory variant at the chr10 susceptibility locus.

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Grünewald, T., Bernard, V., Gilardi-Hebenstreit, P. et al. Chimeric EWSR1-FLI1 regulates the Ewing sarcoma susceptibility gene EGR2 via a GGAA microsatellite. Nat Genet 47, 1073–1078 (2015). https://doi.org/10.1038/ng.3363

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