Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Letter
  • Published:

EWS–FLI1 increases transcription to cause R-loops and block BRCA1 repair in Ewing sarcoma

An Author Correction to this article was published on 27 June 2018

This article has been updated

Abstract

Ewing sarcoma is an aggressive paediatric cancer of the bone and soft tissue. It results from a chromosomal translocation, predominantly t(11;22)(q24:q12), that fuses the N-terminal transactivation domain of the constitutively expressed EWSR1 protein with the C-terminal DNA binding domain of the rarely expressed FLI1 protein1. Ewing sarcoma is highly sensitive to genotoxic agents such as etoposide, but the underlying molecular basis of this sensitivity is unclear. Here we show that Ewing sarcoma cells display alterations in regulation of damage-induced transcription, accumulation of R-loops and increased replication stress. In addition, homologous recombination is impaired in Ewing sarcoma owing to an enriched interaction between BRCA1 and the elongating transcription machinery. Finally, we uncover a role for EWSR1 in the transcriptional response to damage, suppressing R-loops and promoting homologous recombination. Our findings improve the current understanding of EWSR1 function, elucidate the mechanistic basis of the sensitivity of Ewing sarcoma to chemotherapy (including PARP1 inhibitors) and highlight a class of BRCA-deficient-like tumours.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Ewing sarcoma dysregulates transcription in response to damage.
Figure 2: R-loop accumulation in Ewing sarcoma.
Figure 3: Functional loss of EWSR1 impairs homologous recombination.
Figure 4: BRCA1 is retained at transcriptional complexes in Ewing sarcoma.

Similar content being viewed by others

Accession codes

Primary accessions

Gene Expression Omnibus

Change history

  • 27 June 2018

    In this Letter, the sentence beginning "This work was funded...." in the Acknowledgements should have read "CPRIT (RP140105) to J.C.R." rather than "CPRIT (RP150445) to J.C.R." This error has been corrected online.

References

  1. Turc-Carel, C ., Philip, I ., Berger, M. P ., Philip, T . & Lenoir, G. M. Chromosome study of Ewing’s sarcoma (ES) cell lines. Consistency of a reciprocal translocation t(11;22)(q24;q12). Cancer Genet. Cytogenet. 12, 1–19 (1984)

    Article  CAS  PubMed  Google Scholar 

  2. Paronetto, M. P. Ewing sarcoma protein: a key player in human cancer. Int. J. Cell Biol. 2013, 642853 (2013)

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  3. Li, H . et al. Ewing sarcoma gene EWS is essential for meiosis and B lymphocyte development. J. Clin. Invest. 117, 1314–1323 (2007)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Yang, W . et al. Genomics of Drug Sensitivity in Cancer (GDSC): a resource for therapeutic biomarker discovery in cancer cells. Nucleic Acids Res. 41, D955–D961 (2013)

    Article  CAS  PubMed  Google Scholar 

  5. Kim, N . & Jinks-Robertson, S. Transcription as a source of genome instability. Nat. Rev. Genet. 13, 204–214 (2012)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Spahn, L . et al. Homotypic and heterotypic interactions of EWS, FLI1 and their oncogenic fusion protein. Oncogene 22, 6819–6829 (2003)

    Article  CAS  PubMed  Google Scholar 

  7. Embree, L. J ., Azuma, M. & Hickstein, D. D. Ewing sarcoma fusion protein EWSR1/FLI1 interacts with EWSR1 leading to mitotic defects in zebrafish embryos and human cell lines. Cancer Res. 69, 4363–4371 (2009)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Bertolotti, A . et al. EWS, but not EWS-FLI-1, is associated with both TFIID and RNA polymerase II: interactions between two members of the TET family, EWS and hTAFII68, and subunits of TFIID and RNA polymerase II complexes. Mol. Cell. Biol. 18, 1489–1497 (1998)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Yang, L ., Chansky, H. A. & Hickstein, D. D. EWS.Fli-1 fusion protein interacts with hyperphosphorylated RNA polymerase II and interferes with serine-arginine protein-mediated RNA splicing. J. Biol. Chem. 275, 37612–37618 (2000)

    Article  CAS  PubMed  Google Scholar 

  10. Phatnani, H. P. & Greenleaf, A. L. Phosphorylation and functions of the RNA polymerase II CTD. Genes Dev. 20, 2922–2936 (2006)

    Article  CAS  PubMed  Google Scholar 

  11. Schwartz, J. C . et al. FUS binds the CTD of RNA polymerase II and regulates its phosphorylation at Ser2. Genes Dev. 26, 2690–2695 (2012)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Hill, S. J . et al. Systematic screening reveals a role for BRCA1 in the response to transcription-associated DNA damage. Genes Dev. 28, 1957–1975 (2014)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Aguilera, A. & García-Muse, T. R loops: from transcription byproducts to threats to genome stability. Mol. Cell 46, 115–124 (2012)

    Article  CAS  PubMed  Google Scholar 

  14. Paronetto, M. P ., Miñana, B. & Valcárcel, J. The Ewing sarcoma protein regulates DNA damage-induced alternative splicing. Mol. Cell 43, 353–368 (2011)

    Article  CAS  PubMed  Google Scholar 

  15. Selvanathan, S. P . et al. Oncogenic fusion protein EWS-FLI1 is a network hub that regulates alternative splicing. Proc. Natl Acad. Sci. USA 112, E1307–E1316 (2015)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Hamperl, S. & Cimprich, K. A. The contribution of co-transcriptional RNA:DNA hybrid structures to DNA damage and genome instability. DNA Repair (Amst.) 19, 84–94 (2014)

    Article  CAS  Google Scholar 

  17. Ginno, P. A ., Lott, P. L ., Christensen, H. C ., Korf, I . & Chédin, F. R-loop formation is a distinctive characteristic of unmethylated human CpG island promoters. Mol. Cell 45, 814–825 (2012)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Riggi, N . et al. EWS-FLI1 utilizes divergent chromatin remodeling mechanisms to directly activate or repress enhancer elements in Ewing sarcoma. Cancer Cell 26, 668–681 (2014)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Nieto-Soler, M . et al. Efficacy of ATR inhibitors as single agents in Ewing sarcoma. Oncotarget 7, 58759–58767 (2016)

    Article  PubMed  PubMed Central  Google Scholar 

  20. Brenner, J. C . et al. PARP-1 inhibition as a targeted strategy to treat Ewing’s sarcoma. Cancer Res. 72, 1608–1613 (2012)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Zellweger, R . et al. Rad51-mediated replication fork reversal is a global response to genotoxic treatments in human cells. J. Cell Biol. 208, 563–579 (2015)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Pierce, A. J ., Johnson, R. D ., Thompson, L. H . & Jasin, M. XRCC3 promotes homology-directed repair of DNA damage in mammalian cells. Genes Dev. 13, 2633–2638 (1999)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Sankar, S. & Lessnick, S. L. Promiscuous partnerships in Ewing’s sarcoma. Cancer Genet. 204, 351–365 (2011)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Bryant, H. E . et al. Specific killing of BRCA2-deficient tumours with inhibitors of poly(ADP-ribose) polymerase. Nature 434, 913–917 (2005)

    Article  ADS  CAS  PubMed  Google Scholar 

  25. Farmer, H . et al. Targeting the DNA repair defect in BRCA mutant cells as a therapeutic strategy. Nature 434, 917–921 (2005)

    Article  ADS  CAS  PubMed  Google Scholar 

  26. Bouwman, P . et al. 53BP1 loss rescues BRCA1 deficiency and is associated with triple-negative and BRCA-mutated breast cancers. Nat. Struct. Mol. Biol. 17, 688–695 (2010)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Krum, S. A ., Miranda, G. A ., Lin, C. & Lane, T. F. BRCA1 associates with processive RNA polymerase II. J. Biol. Chem. 278, 52012–52020 (2003)

    Article  CAS  PubMed  Google Scholar 

  28. Hatchi, E . et al. BRCA1 recruitment to transcriptional pause sites is required for R-loop-driven DNA damage repair. Mol. Cell 57, 636–647 (2015)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Escribano-Díaz, C . et al. A cell cycle-dependent regulatory circuit composed of 53BP1-RIF1 and BRCA1-CtIP controls DNA repair pathway choice. Mol. Cell 49, 872–883 (2013)

    Article  PubMed  CAS  Google Scholar 

  30. Riggi, N ., Cironi, L ., Suvà, M. L. & Stamenkovic, I. Sarcomas: genetics, signalling, and cellular origins. Part 1: the fellowship of TET. J. Pathol. 213, 4–20 (2007)

    Article  CAS  PubMed  Google Scholar 

  31. Suzuki, Y. et al. An upstream open reading frame and the context of the two AUG codons affect the abundance of mitochondrial and nuclear RNase H1. Mol. Cell. Biol. 30, 5123–5134 (2010)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Sanz, L. A. et al. Prevalent, dynamic, and conserved R-loop structures associate with specific epigenomic signatures in mammals. Mol. Cell 63, 167–178 (2016)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Hu, Y. et al. PARP1-driven poly-ADP-ribosylation regulates BRCA1 function in homologous recombination-mediated DNA repair. Cancer Discov. 4, 1430–1447 (2014)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. De Luca, P. et al. BRCA1 loss induces GADD153-mediated doxorubicin resistance in prostate cancer. Mol. Cancer Res. 9, 1078–1090 (2011)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Gorski, J. J. et al. Profiling of the BRCA1 transcriptome through microarray and ChIP-chip analysis. Nucleic Acids Res. 39, 9536–9548 (2011)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Wiles, A. M., Ravi, D., Bhavani, S. & Bishop, A. J. An analysis of normalization methods for Drosophila RNAi genomic screens and development of a robust validation scheme. J. Biomol. Screen. 13, 777–784 (2008)

    Article  PubMed  PubMed Central  Google Scholar 

  37. Ravi, D. et al. A network of conserved damage survival pathways revealed by a genomic RNAi screen. PLoS Genet. 5, e1000527 (2009)

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  38. Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA 102, 15545–15550 (2005)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  39. Huang, W., Sherman, B. T. & Lempicki, R. A. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protocols 4, 44–57 (2009)

    Article  CAS  Google Scholar 

  40. Zhang, Y. et al. Model-based analysis of ChIP-seq (MACS). Genome Biol. 9, R137 (2008)

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  41. Liu, R. et al. Computation tools for genome-wide R-loops identification and characterisation. Int. J. Comput. Biol. Drug Des. 10, 123–136 (2017)

    Article  Google Scholar 

Download references

Acknowledgements

We thank F. Chedin for the DRIP–seq protocol and genome-wide restriction enzyme sites file, and R. Crouch, J. Stark and Y. Shiio for plasmids. We are grateful to the UTH-SA/Cancer Center Sequencing core and the Histology & Immunohistochemistry Core at UTH-SA. This work was funded by the NIH (K22ES012264, 1R15ES019128, 1R01CA152063), a Voelcker Fund Young Investigator Award and CPRIT (RP150445) to A.J.R.B.; CPRIT (RP101491), a Translational Science Training Across Disciplines Scholarship (UTHSA) and an NCI postdoctoral training grant (T32CA148724) to A.G.; CPRIT (RP140105) to J.C.R.; NIH (P30CA054174) to Mays Cancer Center; NCI (R01CA204915) and Curing Kids Cancer to K.S.; NIH CTSA (1UL1RR025767-01, P30CA054174) and CPRIT (RP120685-C2) to Y.C.; NIH (1R01CA140394) to S.L.L. and NIH (1R01CA134605) to E.R.L.

Author information

Authors and Affiliations

Authors

Contributions

A.G. and A.J.R.B. conceived and designed the study and wrote the manuscript. A.G. conducted the majority of the research. J.C.R. contributed to replication of experiments for homologous recombination and BRCA1 localization. E.G. performed EU incorporation experiments. L.A.L. performed RNaseH rescue of replication stress and EU incorporation experiments. E.L., L.C., V.P.M. and X.B. provided technical support. A.B.I. and K.S. performed EWS–FLI1 knockdown for the phospho-RNAPII experiment. S.R. and J.A.T. provided recombinant EWS–FLI1 protein. Y.C. conducted bioinformatics analysis support. S.L.L. and E.R.L. provided reagents/insights.

Corresponding author

Correspondence to Alexander J. R. Bishop.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Additional information

Reviewer Information Nature thanks B. Braun and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Figure 1 Characterizing Ewing sarcoma chemosensitivity.

a, Cell lines used in the study. b, Level of cell death caused by EWS–FLI1 knockdown alone in TC32 cells. Immunoblot shows extent of knockdown; n = 4 transfection replicates. c, Cell viability of U2OS cells transfected either with empty vector (EV) or EWS–FLI1 for 24 h before etoposide exposure for a further 48 h. Immunoblot shows transfection efficiency; n = 3 transfection replicates. d, IC50 levels of etoposide or mitomycin in EWS–FLI1 mutant (n = 16) versus pan-cancer (n = 143) dataset. Brown lines, range of screening concentrations of the drug. Red lines, geometric mean of drug concentration. e, Heat map of basal gene expression profile in control and Ewing sarcoma cell lines after hierarchical clustering. f, g, Top enriched pathways from gene set enrichment analysis of the differences between Ewing sarcoma and IMR90 cells are listed (f) and relevant signature plots are illustrated (g). We found differential upregulation of replication stress, BRCA1-mutation driven network and altered transcription regulation pathways in Ewing sarcoma. h, Cross-screen pathway comparison of top survival hits from RNAi screens in Drosophila Kc167 cells exposed to MMS, bleomycin or etoposide. Nearly a third of the top 5% hits in each screen were genes involved in transcription and RNA metabolism, highlighting the importance of this pathway in DNA damage survival. Mean ± s.e.m., *P < 0.05, **P < 0.005, two-tailed t-test.

Extended Data Figure 2 Aberrant transcription regulation in Ewing sarcoma.

a, Immunoblot depicting the phosphorylation of RNAPII CTD fragment used as the substrate in Fig. 1d. Recombinant EWSR1 and hypophosphorylated RNAPII are also displayed. b, Level of inhibition of CDK9 activity by buffer (vehicle) or recombinant EWS–FLI1 protein on the two RNAPII CTD substrates. The immunoblot on top is confirmation of kinase activity measured by the assay. c, Cytotoxicity profile in response to camptothecin in control, Ewing sarcoma and EWSR1-depleted cells. n = 4 technical replicates, one-way ANOVA against IMR90 cells. d, IC50 levels of camptothecin in EWS–FLI1 mutant (n = 15) versus pan-cancer (n = 132) dataset. Brown lines, range of screening concentrations of the drug. Red lines, geometric mean of drug concentration. e, Transcription restart assay measured in U2OS cells transfected with either scrambled or EWSR1 siRNA. n = 4 transfection replicates, two-way ANOVA. Mean ± s.e.m., *P < 0.05, **P < 0.005.

Extended Data Figure 3 R-loops in Ewing sarcoma.

a, Quantification of RNA–DNA hybrids in TC32 cells transfected with either empty vector (EV) or RNaseH1 (RNH1). The immunoblot to the right indicates RNaseH1 transfection efficiency; n = 4 transfection replicates. b, RNA–DNA hybrid levels in TC32 cells with scrambled (siCtrl) or EWS–FLI1 (siFLI1) knockdown; n = 3 transfection replicates. c, Schematic of the EWS–FLI1 R2L2 construct. Arginine residues 383 and 386 (black bars) in EWS–FLI1 are converted to leucine to render the fusion oncogene deficient in DNA binding. Below is a quantification of RNA–DNA hybrids in U2OS cells expressing empty vector, EWS–FLI1 or EWS–FLI1 R2L2; n = 4 transfection replicates. d, e, Fold change in RNA–DNA hybrids after damage (etoposide, 6 h) in IMR90 versus Ewing sarcoma cells (d) or U2OS cells with either EWSR1 depletion or EWS–FLI1 expression (e). NT, no treatment; n = 4 technical or transfection replicates. f, Quantification of nucleoplasmic RNA–DNA hybrids in the immunofluorescence images (n = 80 nuclei) demonstrated a clear increase in overall R-loop intensity in Ewing sarcoma cells. Nucleolin signal was used to subtract nucleolar R-loops. One-way ANOVA. Mean ± s.e.m., #,*P < 0.05, ##,**P < 0.005. # indicates significance of Ewing sarcoma relative to untreated IMR90 cells or transfections relative to U2OS cells.

Extended Data Figure 4 DRIP–seq data validation.

a, Quantification of DRIP (coverage of DRIP region multiplied by reads in that region) across all samples. y-axis is graphed in logarithmic scale. b, Representative whole-genome heat maps centred around TSS ordered by average expression of Ewing sarcoma cells. c, Probability density graph plotted with a Gaussian smoothing kernel of the distribution of DRIP peaks and EWS–FLI1 ChIP peaks at EWS–FLI1 bound genes relative to uniform distribution. n = 281 genes (top 16%). Inset, P values depicting significance of enrichment for each sample. d, Fold enrichment of qPCR product from ChIP experiments done with RNAPII antibody in control and Ewing sarcoma cell lines. The primers target well-known R-loop regions within APOE and EGR1 genes. Mean ± s.e.m., n = 3 technical replicates, ***P < 0.0005, ****P < 0.00005. One-way ANOVA across cell lines compared to IMR90 cells and two-tailed t-test within cell lines.

Extended Data Figure 5 R-loop-dependent replication stress and recombination defect in Ewing sarcoma.

a, Representative immunoblots evaluating decrease in ATR kinase pathway activation upon overexpression of RNaseH1 in TC32 cells. b, Schematic of the DR-GFP construct integrated into U2OS cells. Below are representative scatter plots of the gating scheme used to determine percentage of GFP-positive cells after inducing a DSB via ISceI vector compared to empty vector. c, RNA-seq data of BRCA1 transcript levels in Ewing sarcoma cell lines compared to IMR90 cells. d, Immunoblots demonstrating transfection efficiency of indicated siRNA and expression constructs used in Fig. 3f, g.

Extended Data Figure 6 Similarity of Ewing sarcoma to BRCA-deficient tumours.

a, IC50 levels of olaparib in EWS–FLI1 mutant cells (n = 17) versus breast cancers (n = 13) or pan-cancer (n = 147) dataset. b, Cell viability of IMR90 and Ewing sarcoma cells with increasing doses of olaparib. Mean ± s.d., n = 3 technical replicates, one-way ANOVA compared to IMR90 cells. c, Cell viability plot demonstrating the role of EWS–FLI1 in mediating exquisite sensitivity to olaparib in U2OS cells transfected with either the oncogene or empty vector; n = 3 transfection replicates. d, Immunoblots depicting transfection efficiency of indicated siRNA and expression constructs used in Fig. 3h. e, TP53BP1 knockdown improved Ewing sarcoma (TC32 cell) survival in response to damage. Immunoblots depict level of TP53BP1 knockdown. n = 4 transfection replicates. f, Representative immunoblots showing equivalent levels of BRCA1 in whole cell lysates (upper panel) from control and Ewing sarcoma cells with and without etoposide treatment (2 h). The lower panel shows BRCA1 redistribution in subcellular fractions of U2OS or TC32 cells. GAPDH and lamin B1 were used as loading controls for the cytoplasmic and nuclear fractions, respectively. g, Immunoblots of whole cell lysates and subcellular fractions from U2OS cells with and without EWSR1 depletion. Data indicated no change in BRCA1 levels with EWSR1 knockdown. Loading controls include: GAPDH for cytoplasm, Sp1 for nuclei and histone H3 for chromatin. Mean ± s.e.m., **P < 0.005, two-tailed t-test at each dose.

Extended Data Figure 7 Association of BRCA1 with the transcription complex in Ewing sarcoma.

a, Co-immunoprecipitation: immunoblots of IMR90 and EWS502 nuclear lysates with and without exposure to etoposide (2 h). The left panel indicates 10% of the input used for immunoprecipitation. BRCA1 antibody was used for immunoprecipitation in the middle panel and the rightmost panel indicates specificity of interaction against IgG pulldown. b, Real-time qPCR analysis of BRCA ChIP samples from control and Ewing sarcoma cell lines with and without etoposide treatment, using primers within the FEN1 and PARP8 genes. c, Representative sequencing track image of gene expression (red tracks), R-loop sites (black and grey tracks) and BRCA1 binding sites (blue tracks) across the FEN1 gene demonstrating the enrichment of R-loops and BRCA1 in the region amplified by the primers in b. d, qPCR analysis as in b with primers targeting a well-known R-loop region within the APOE gene. e, Representative sequencing track image as in c across the APOE gene. f, Agarose gel blots evaluating amplicons generated using EWS502 DRIPs with primers against FEN1 and PARP8. NT, no treatment; Etop, etoposide-treated (6 h); RNH, RNaseH-treated samples. Mean ± s.e.m., n = 3 technical replicates, **P < 0.005, two-tailed t-test.

Extended Data Figure 8 Genome-wide heat maps.

a, Heat maps representing genome-wide localization of RNAPII, BRCA1 and R-loop sites centred on the TSS. The data were sorted by DRIP sites. The upper panel represents untreated (NT) samples and the lower panel represents etoposide (Etop, 6 h) treated samples. There was a clear decrease in BRCA1 and R-loop signal upon damage in the control cell lines, unlike in Ewing sarcoma. b, KS plots to demonstrate empirical distribution of the top 13.8% of DRIP and ChIP peaks and higher expression relative to uniform distribution. Data are sorted by BRCA1 ChIP, n = 3,066 genes. c, P values of statistical comparisons between RNAPII ChIP and R-loop probability distributions for all cell lines against IMR90 DRIP data centred on the TSS. The top 27% of DRIP–seq peaks corresponding to 6,127 genes were used for the analysis and data were sorted by BRCA1 binding sites.

Extended Data Figure 9 Correlation between BRCA1 and RNAPII binding.

a, Distribution of RNAPII abundance across the genome for IMR90 and TC32 cells. The bars depict the number of RNAPII bound sites as a function of the number of peaks (y-axis) and relative abundance (peak height, log-transformed) within these peaks (x-axis). The blue bars indicate the total number of peaks determined from RNAPII ChIP–seq and the red bars represent the peaks that co-localize with BRCA1 peaks obtained from BRCA1 ChIP–seq. The data indicated a similar number of RNAPII peaks for TC32 (11,024) compared to IMR90 (9,813), but a greater amount of DNA bound at these peaks, implying increased RNAPII binding. Furthermore, a higher proportion of RNAPII-bound loci also co-localized to BRCA1 binding sites (red bars) in TC32 than in IMR90 cells (23% compared to 2.7%) and there was a clear increase in RNAPII abundance at these sites. b, Distribution of BRCA1 abundance across the genome for IMR90 and TC32, similar to a. The data indicate a significantly higher number of total BRCA1 peaks in TC32 cells as well as a significantly higher enrichment of BRCA1 within these peaks in TC32 cells compared to IMR90 cells. The data also suggest that the majority of the BRCA1 peaks were co-localized with RNAPII. c, Scatter plots represent the correlation of RNAPII (left) and BRCA1 (right) peak heights between TC32 and IMR90 cells. Data were plotted after being normalized to read count and log-transformed to make comparisons. Loci that are unique to each cell line map to the axes whereas common loci are scattered around the diagonal. The data clearly suggest an increase in enrichment of both RNAPII and BRCA1 in TC32 cells compared to IMR90 cells. d, Scatter plots represent the relationship between co-localized BRCA1 and RNAPII peaks as a function of BRCA1 peak height (x-axis) and level of expression of the gene associated with these binding sites (y-axis). TC32 cells showed a greater than fivefold increase in the number of BRCA1 peaks that were associated with RNAPII at highly expressed genes. Further, as in b, there was a greater abundance of BRCA1 (peak height) at these highly expressed genes in TC32 cells than in IMR90 cells.

Extended Data Figure 10 Immunohistochemical analysis of tissue sections.

a, Representative images depicting R-loop staining by S9.6 antibody on sections derived from fixed TC32 cell pellets. Sections were treated with buffer (left), RNaseH (middle) or RNaseA (right) after antigen retrieval. The slides demonstrate loss of R-loop signal after treatment with RNaseH, as expected. RNaseA treatment, which at higher salt concentrations specifically cleaves single-stranded RNA, did not result in a significant loss of R-loop signal confirming the specificity of S9.6 antibody in detecting RNA–DNA hybrids. b, Representative images from a pan-sarcoma tissue microarray. The left and centre panels were probed with S9.6 antibody with or without RNaseH treatment. The right panel was stained with secondary antibody alone and serves as a non-specific control. Each row represents images from one tumour indicated on the left. Images were scanned at 40× (bar at the bottom right denotes resolution).

Extended Data Table 1 Comparison of Ewing sarcoma to normal cells and BRCA-mutant cancers.

Supplementary information

Supplementary Figure 1

This file contains full scans of the western blots presented in Figures 1e-g, 2e, 3i, 4a and Extended Data Figures 1b,c, 2a,b, 3a, 5a,d, 6d-g and 7a. (PDF 3040 kb)

Life Sciences Reporting Summary (PDF 174 kb)

Supplementary Table 1

Damage-induced changes in gene expression between IMR90 and EwS cell lines. Supplementary Table 1.1 contains a list of genes that are at least two-fold altered upon etoposide treatment in IMR90 but not in EwS cell lines. The criterion for evaluation of EwS cells was as follows: genes that were upregulated at least 2-fold in IMR90 but less than 0-fold (no change or downregulated) in EwS and vice versa. Supplementary Table 1.2 contains a list of genes that are at least two-fold altered upon etoposide treatment in EwScell lines but not in IMR90. The criterion for evaluation is as follows: genes that were upregulated at least 2-fold in EwS but less than 0-fold (no change or downregulated) in IMR90 and vice versa. Supplementary Table 1.3 contains a list of genes that were similarly altered (minimum 2-fold change) by gene expression in response to damage between IMR90 and EwS. (XLSX 54 kb)

Supplementary Table 2

This table shows the top 5% hits in the Drosophila kc167 RNAi screens. Data was collected as percent survival upon damage induction (3 days) for each RNAi. The loci that mapped to NCBI gene IDs are listed (XLSX 57 kb)

PowerPoint slides

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gorthi, A., Romero, J., Loranc, E. et al. EWS–FLI1 increases transcription to cause R-loops and block BRCA1 repair in Ewing sarcoma. Nature 555, 387–391 (2018). https://doi.org/10.1038/nature25748

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nature25748

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer