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ETV6 dependency in Ewing sarcoma by antagonism of EWS-FLI1-mediated enhancer activation

Nature Cell Biology volume 25, pages 298–308 (2023)Cite this article

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Abstract

The EWS-FLI1 fusion oncoprotein deregulates transcription to initiate the paediatric cancer Ewing sarcoma. Here we used a domain-focused CRISPR screen to implicate the transcriptional repressor ETV6 as a unique dependency in this tumour. Using biochemical assays and epigenomics, we show that ETV6 competes with EWS-FLI1 for binding to select DNA elements enriched for short GGAA repeat sequences. Upon inactivating ETV6, EWS-FLI1 overtakes and hyper-activates these cis-elements to promote mesenchymal differentiation, with SOX11 being a key downstream target. We show that squelching of ETV6 with a dominant-interfering peptide phenocopies these effects and suppresses Ewing sarcoma growth in vivo. These findings reveal targeting of ETV6 as a strategy for neutralizing the EWS-FLI1 oncoprotein by reprogramming of genomic occupancy.

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Fig. 1: ETV6 is a dependency in Ewing sarcoma.
Fig. 2: ETV6 knockout in Ewing sarcoma drives mesenchymal differentiation.
Fig. 3: ETV6-mediated transcriptional repression is essential in Ewing sarcoma.
Fig. 4: ETV6 antagonizes EWS-FLI1-mediated enhancer activation at select DNA elements.
Fig. 5: ETV6 competes with EWS-FLI1 at short, interspersed GGAA repeats.
Fig. 6: Squelching of ETV6 with a SAM domain reprogrammes EWS-FLI1 occupancy and blocks Ewing sarcoma growth in vivo.

Data availability

All the raw sequencing and related processed data are deposited in and publicly available from the GEO under the accession number GSE189418. These data include processed data such as peak region sets, ChIP signal and RNA-seq quantification. The cancer dependency dataset was obtained online (https://depmap.org/portal/download/, DepMap Public 21Q1). The Ewing sarcoma patient survival time and ETV6 expression level in the primary tumour were obtained from ICGC BOCA-FR dataset (https://dcc.icgc.org/projects/BOCA-FR, EXP-S). Numerical source data for Figs. 1–6 and Extended Data Figs. 1–7 and 9 are provided along with the unprocessed images of immunoblots for Figs. 1, 5 and 6 and Extended Data Figs. 1 and 5–9. Source data are provided with this paper.

Code availability

Customized Python script used to analyse GGAA motif in each peak is available on GitHub (https://github.com/ygaoyg/ETV6-dependency-in-Ewing-sarcoma.git).

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Acknowledgements

This work was supported by Cold Spring Harbor Laboratory NCI Cancer Center Support grants P30-CA045508 and 5P01CA013106-49. Additional funding was provided to C.R.V. by the Pershing Square Sohn Cancer Research Alliance, National Institutes of Health grants CA013106 and CA245859, Friends of T.J. Foundation, Christina Renna Foundation, Michelle Paternoster Foundation, and the William J. Riley Foundation, to M.E. by the National Institutes of Health (NIH) (5R01CA237413). K.M.B. is supported by the NCI award (K08CA252178). L.J. is an investigator of the Howard Hughes Medical Institute. X.-Y.H. is supported by the 2021 AACR-AstraZeneca Breast Cancer Research Fellowship (grant number 21-40-12-HE). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information

Authors and Affiliations

  1. Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA

    Yuan Gao, Xue-Yan He, Xiaoli S. Wu, Yu-Han Huang, Shushan Toneyan, Taehoon Ha, Peter K. Koo, Mikala Egeblad & Christopher R. Vakoc

  2. Genetics Program, Stony Brook University, Stony Brook, NY, USA

    Xiaoli S. Wu

  3. School of Biological Sciences, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA

    Shushan Toneyan

  4. Howard Hughes Medical Institute, W.M. Keck Structural Biology Laboratory, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA

    Jonathan J. Ipsaro & Leemor Joshua-Tor

  5. Department of Pediatrics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA

    Kelly M. Bailey

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Contributions

Y.G., X.-Y.H., X.S.W., Y.-H.H., S.T., J.J.I., T.H. and P.K.K., performed experiments and/or analysed the data; L.J.-T., K.M.B., M.E. and C.R.V. supervised the experiments and analysis; Y.G. and C.R.V. wrote the manuscript.

Corresponding author

Correspondence to Christopher R. Vakoc.

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Competing interests

C.R.V. has received consulting fees from Flare Therapeutics, Roivant Sciences and C4 Therapeutics; has served on the advisory boards of KSQ Therapeutics, Syros Pharmaceuticals and Treeline Biosciences; has received research funding from Boehringer-Ingelheim and Treeline Biosciences; and owns a stock option from Treeline Biosciences. M.E. is a member of the research advisory board for brensocatib for Insmed, Inc.; a member of the scientific advisory board for Vividion Therapeutics, Inc.; a consultant for Protalix, Inc.; and holds shares in Agios Pharmaceuticals, Inc. The remaining authors declare no competing interests.

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Nature Cell Biology thanks Thomas Grunewald, Tiebang Kang and Elizabeth Lawlor for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 ETV6 is a dependency in Ewing sarcoma cell lines.

(a) Scatterplot showing the correlation between patient survival time and ETV6 expression level in primary tumours from the ICGC BOCA-FR dataset containing 57 Ewing sarcoma patients. Blue lines mark the mean with 95% confidence interval. (b) Comparison of patient survival time between ETV6-high (Top 25%, n = 15) and ETV6-low patients (Bottom 25%, n = 15). Data are mean ± SEM. P value was calculated using two-tailed unpaired Student’s t-test. (c) Western blot of ETV6 and EWS-FLI1 levels confirming the knockout of ETV6 in different cancer cell lines. Beta-ACTIN (ACTB) was used as a loading control. (d) Photographs of collected tumours at end time point. (e) Western blot indicates that the resulting tumours from A673 xenograft experiments maintain similar levels of ETV6 and EWS-FLI1. ACTB was used as a loading control. (f) Representative images of immunofluorescence staining for PCNA (red) in the resulting tumours from A673 xenograft experiments (left panel). Percentage of PCNA-positive over DAPI-positive cells was quantified in the right panel. Data are mean ± SEM. P values were calculated using one-way ANOVA, Tukey’s multiple comparison tests. (n = 5 tumours) (g) Representative images of immunofluorescence staining for Cleaved Caspase-3 (red) in the resulting tumours from A673 xenografts (left panel). Percentage of Cleaved Caspase-3 positive over DAPI stained cells was quantified in the right panel. Data are mean ± SEM. P values were calculated using one-way ANOVA, Tukey’s multiple comparison tests. (n = 5 tumours).

Source data

Extended Data Fig. 2 ETV6 knockout in Ewing sarcoma drives mesenchymal differentiation.

(a) Representative images of immunofluorescence staining for collagen I (red), alpha smooth muscle actin (α-SMA, green) and the cytoskeleton component F-actin (white) in RH1 cells infected with indicated sgRNAs. (b, c) Representative images of immunofluorescence staining for alpha smooth muscle actin (α-SMA, red) and the cytoskeleton component F-actin (white) in two independent patient-derived Ewing sarcoma tumour cells PSaRC219 (b) and PSaRC318 (c) infected with indicated sgRNAs. (d) Quantification of cell size based on F-actin staining (μm2) in RH1, PSaRC219 and PSaRC318 cells. Data are mean ± SEM. P values were calculated using one-way ANOVA, Dunnett’s multiple comparison tests. (e) Representative images of immunofluorescence staining for collagen I (green) in the resulting tumours from A673 xenografts (left). Percentage of Collagen I stained area was quantified (right). (n = 5 tumours) Data are mean ± SEM. P values were calculated using one-way ANOVA, Dunnett’s multiple comparison tests.

Source data

Extended Data Fig. 3 ETV6 knockout up-regulates mesenchymal differentiation program in Ewing sarcoma cells, but not in non-Ewing cancer cell lines.

(a) Volcano plots showing the gene expression changes upon ETV6 knockout in 3 different non-Ewing cancer cell lines (RD, U2OS and SUIT2) assessed by RNA-seq. UP-regulated Genes (Log2FC > 0.5, p-adj<0.01, red); DOWN-regulated Genes (Log2FC < −0.5, p-adj<0.01, blue). (b) Venn diagram showing the overlap in up-regulated (Log2FC > 1) and down-regulated (Log2FC < −1) genes upon ETV6 knockout among three Ewing sarcoma cell lines (A673, RH1 and TC71). (c) Heatmap showing the expression changes of the mesenchymal differentiation genes, that are up-regulated upon ETV6 knockout in A673 cells, among 6 cancer cell lines (3 Ewing sarcoma and 3 non-Ewing lines). (d) Venn diagram showing the overlap between EWS-FLI1 repressed signature from Tirode et al. 2007. (n = 297, Log2FC > 1, P value<0.01) and the ETV6 repressed genes (n = 363, Log2FC > 1, P value<0.01) from our study in A673 cells.

Source data

Extended Data Fig. 4 ETV6 knockout does not enhance Ewing sarcoma cell migration or invasion phenotype.

(a) Representative images of migrated cells toward a high serum environment after 24 hours seeded in serum-free media in three Ewing sarcoma cell lines (A673, RH1 and TC71) (left). Comparison of the cell counts that migrate through the pores. Data are mean ± SEM. P values were calculated using one-way ANOVA, Tukey’s multiple comparison tests. (n = 3 biological replicates) (b) Representative images (left) and quantification (right) of trans-well invasion assay measuring the number of cells invade through a Matrigel matrix (24 hours). Data are mean ± SEM. P values were calculated using one-way ANOVA, Tukey’s multiple comparison tests. (n = 3 biological replicates).

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Extended Data Fig. 5 ETV6 represses a unique set of genes that contributes to the dependency in Ewing sarcoma cells.

(a) Venn diagram showing the overlap of ETV6 ChIP-seq peaks between Ewing (A673) and non-Ewing cell lines. The ETV6 peaks in non-Ewing cells were annotated by merging ETV6 peaks from 3 different non-Ewing cancer cell lines. (b) The schematic diagram of genetic bypass screening. (c) Competition-based proliferation assay to validate the genetic bypass screening results using single sgRNAs. The sgNEG-mCherry control related to Fig. 3g. Data are mean ± SEM. (n = 3 biological replicates) (d) Competition-based proliferation assay to validate the genetic bypass screening results in two additional Ewing sarcoma cell lines (TC71 and RH1). Cells were infected with a dual-sgRNA linked to a GFP reporter. The percentage of cells that are positive for GFP were monitored during culturing. Data are mean ± SEM. P values were calculated using two-way ANOVA. (n = 3 biological replicates) (e)Western blot confirming the knockout of ETV6 and SOX11 in A673 cells prior to subcutaneous injections. ACTB was used as a loading control. (f) Average growth curves of ETV6 or/and SOX11, NTRK1 knockout A673 xenografts in immunodeficient mice. Data are mean ± SEM. Linear mixed-effects model with sgRNA, time and sgRNA by time interaction as fixed effects and sample specific random intercept was used to fit the longitudinal tumour volume data. Differences in tumour volume were examined using simultaneous tests for general linear hypotheses of contrasts of interest. P values were adjusted for multiple comparisons using the Bonferroni-Holm method. (sgNEG;sgNEG#2 (n = 11), sgNEG;sgETV6 (n = 12), sgETV6;sgSOX11 (n = 20), sgETV6;sgNTRK1 (n = 16)). (g) Weight of the resected tumours at the end point. Data are mean ± SEM. Log-transformed tumour weight in different groups were compared using Welch’s ANOVA test followed by Dunnett’s T3 multiple-comparison tests. (sgNEG;sgNEG#2 (n = 11), sgNEG;sgETV6 (n = 12), sgETV6;sgSOX11 (n = 20), sgETV6;sgNTRK1 (n = 16)).

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Extended Data Fig. 6 Activation of ETV6 target genes specifically impairs Ewing sarcoma cell growth.

(a) RT-PCR analysis of SOX11 and NTRK1 levels in the CRISPR activation experiments. (-), no virus infection control. NT, non-targeting sgRNA control. Data are mean ± SEM. (n = 3 biological replicates) (b) Western blot confirming the elevation of SOX11 level upon CRISPR activation. ACTB was used as a loading control. (c) Competition-based proliferation assay evaluating the effects of candidate gene activation, using CRISPR activation (CRISPRa), to cell fitness in non-Ewing cancer cell lines (RD, U2OS and SUIT2). The percentage of GFP positive cells was monitored during culturing. Data are mean ± SEM. (n = 3 biological replicates) (d) Gene expression changes of SOX11 and NTRK1 in different cell lines assessed by RNA-seq. The significant expression changes (p < 0.05) were highlighted in red. (NA: mRNA not detected).

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Extended Data Fig. 7 ETV6 antagonizes EWS-FLI1 function at select DNA elements.

(a) Venn diagram showing the overlap between ETV6 and EWS-FLI1 peaks in A673 cells. (b)Western blot assessing EWS-FLI1 and ETV6 levels in A673 cells transduced with indicated dual-sgRNA constructs. (c)Western blot of EWS-FLI1 and ETV6 in EWS-FLI1 reprogrammed RD cells. RD cells were transduced with EV (empty vector) control or EWS-FLI1 linked to indicated sgRNAs. (d) Metagene representation of the mean EWS-FLI1 signal differences at R sites versus microsatellites. (e) Metagene representation of the mean EWS-FLI1 signal differences at all ETV6 binding sites in A673 cells upon targeting ETV6. (f) Gene tracks of ETV6 and EWS-FLI1 ChIP-seq occupancy upon ETV6 knockout at DPEP1 and NTRK1 sites at two different scales. (g) Metagene representation of mean EWS-FLI1 ChIP-seq signal changes across R sites, microsatellites and all ETV6 binding regions in A673 cells upon targeting ETV6 using sgETV6 #2. (h) Western blot of ETV6 and EWS-FLI1 levels in patient-derived tumour cells (PSaRC219, left; PSaRC318, right) infected with indicated sgRNAs. ACTB was used as a loading control. (i) CellTiter Glo assay evaluating the effects of ETV6 knockout to proliferation in the patient-derived tumour cells (PSaRC219, left; PSaRC318, right). The relative luminescence fold changes (FC) to day 1 were plotted. Data are mean ± SEM. P values were calculated using two-way ANOVA. (n = 4 biological replicates) (j) EWS-FLI1 ChIP-qPCR analysis assessing the EWS-FLI1 occupancy changes at the ACTA2 site in the patient-derived Ewing tumour cells (PSaRC219 and PSaRC318) upon ETV6 knockout. A site 5 kb downstream of the ACTA2 site was used as a negative control. Data are mean ± SEM. P values were calculated using one-way ANOVA, Dunnett’s multiple comparison tests. (n = 3 biological replicates).

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Extended Data Fig. 8 EWS-FLI1 does not bind to ETV6.

Immunoprecipitation assay showing ETV6 interacts with wild-type FLI1, but not EWS-FLI1 fusion. HEK293T cells were co-transfected with FLAG tagged ETV6 and HA tagged FLI1 or EWS-FLI1. FLAG IP was performed.

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Extended Data Fig. 9 ETV6 oligomerization is essential in Ewing sarcoma.

(a) Illustration of ETV6 domain structure and SAM induction altering endogenous ETV6 function. (a.a: amino acid) (b) Western blot of A673 cells transduced with EV (empty vector), 3×FLAG tagged sgRNA resistant wild-type or (A94D, V113E) mutant ETV6 cDNA. Beta-ACTIN was used as a loading control. (c) Immunoprecipitation assay showing wild-type, but not (A94D, V113E) mutant SAM domain is able to associate with full-length ETV6. HEK293T cells were co-transfected with HA tagged ETV6 and FLAG tagged wild-type or (A94D, V113E) mutant SAM domain. FLAG IP was performed. (d) Western blot of A673 and RD cells transduced with Dox-inducible GFP or FLAG tagged SAM fragment. The samples were collected 48 hours after control or doxycycline treatment (1 μg/mL). ACTB was used as a loading control. (e) Metagene representation of the mean ETV6 and EWS-FLI1 signal changes upon SAM induction across microsatellites and all ETV6 binding sites. (f) Gene tracks of EWS-FLI1 ChIP-seq occupancy upon doxycycline treatment at ACTA2, DPEP1 and SOX11 sites in two different scales.

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Gao, Y., He, XY., Wu, X.S. et al. ETV6 dependency in Ewing sarcoma by antagonism of EWS-FLI1-mediated enhancer activation. Nat Cell Biol 25, 298–308 (2023). https://doi.org/10.1038/s41556-022-01060-1

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