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Impaired H3K36 methylation defines a subset of head and neck squamous cell carcinomas

Nature Genetics volume 49, pages 180–185 (2017)Cite this article

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Abstract

Human papillomavirus (HPV)-negative head and neck squamous cell carcinomas (HNSCCs) are deadly and common cancers. Recent genomic studies implicate multiple genetic pathways, including cell signaling, cell cycle and immune evasion, in their development. Here we analyze public data sets and uncover a previously unappreciated role of epigenome deregulation in the genesis of 13% of HPV-negative HNSCCs. Specifically, we identify novel recurrent mutations encoding p.Lys36Met (K36M) alterations in multiple H3 histone genes. histones. We further validate the presence of these alterations in multiple independent HNSCC data sets and show that, along with previously described NSD1 mutations, they correspond to a specific DNA methylation cluster. The K36M substitution and NSD1 defects converge on altering methylation of histone H3 at K36 (H3K36), subsequently blocking cellular differentiation and promoting oncogenesis. Our data further indicate limited redundancy for NSD family members in HPV-negative HNSCCs and suggest a potential role for impaired H3K36 methylation in their development. Further investigation of drugs targeting chromatin regulators is warranted in HPV-negative HNSCCs driven by aberrant H3K36 methylation.

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Figure 1: H3K36M and NSD1 alterations define a specific HNSCC subgroup.
Figure 2: Schematic representation of the anatomical locations of NSD1 and H3K36M alterations in HNSCCs.
Figure 3: Representative immunohistochemical staining of H3K36M, NSD1, H3K36me2 and H3K36me3 in H3K36M or NSD1-mutant or wild-type HNSCCs.
Figure 4: H3K36M and NSD1 alterations decrease levels of H3K36me2 in HNSCC.

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References

  1. Gillison, M.L. et al. Evidence for a causal association between human papillomavirus and a subset of head and neck cancers. J. Natl. Cancer Inst. 92, 709–720 (2000).

    CAS  PubMed  Google Scholar 

  2. Ferlay, J. et al. Estimates of worldwide burden of cancer in 2008: GLOBOCAN 2008. Int. J. Cancer 127, 2893–2917 (2010).

    CAS  PubMed  Google Scholar 

  3. Baxi, S., Fury, M., Ganly, I., Rao, S. & Pfister, D.G. Ten years of progress in head and neck cancers. J. Natl. Compr. Canc. Netw. 10, 806–810 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Agrawal, N. et al. Exome sequencing of head and neck squamous cell carcinoma reveals inactivating mutations in NOTCH1. Science 333, 1154–1157 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  5. Stransky, N. et al. The mutational landscape of head and neck squamous cell carcinoma. Science 333, 1157–1160 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Cancer Genome Atlas Network. Comprehensive genomic characterization of head and neck squamous cell carcinomas. Nature 517, 576–582 (2015).

  7. Ang, K.K. et al. Human papillomavirus and survival of patients with oropharyngeal cancer. N. Engl. J. Med. 363, 24–35 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  8. Sun, W. & Califano, J.A. Sequencing the head and neck cancer genome: implications for therapy. Ann. NY Acad. Sci. 1333, 33–42 (2014).

    CAS  PubMed  Google Scholar 

  9. Gaykalova, D.A. et al. Novel insight into mutational landscape of head and neck squamous cell carcinoma. PLoS One 9, e93102 (2014).

    PubMed  PubMed Central  Google Scholar 

  10. Hedberg, M.L. et al. Genetic landscape of metastatic and recurrent head and neck squamous cell carcinoma. J. Clin. Invest. 126, 1606 (2016).

    PubMed  PubMed Central  Google Scholar 

  11. Pickering, C.R. et al. Integrative genomic characterization of oral squamous cell carcinoma identifies frequent somatic drivers. Cancer Discov. 3, 770–781 (2013).

    CAS  PubMed  Google Scholar 

  12. Seiwert, T.Y. et al. Integrative and comparative genomic analysis of HPV-positive and HPV-negative head and neck squamous cell carcinomas. Clin. Cancer Res. 21, 632–641 (2015).

    CAS  PubMed  Google Scholar 

  13. Hammerman, P.S., Hayes, D.N. & Grandis, J.R. Therapeutic insights from genomic studies of head and neck squamous cell carcinomas. Cancer Discov. 5, 239–244 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Wagner, E.J. & Carpenter, P.B. Understanding the language of Lys36 methylation at histone H3. Nat. Rev. Mol. Cell Biol. 13, 115–126 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Fontebasso, A.M. et al. Mutations in SETD2 and genes affecting histone H3K36 methylation target hemispheric high-grade gliomas. Acta Neuropathol. 125, 659–669 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  16. Wang, G.G., Cai, L., Pasillas, M.P. & Kamps, M.P. NUP98–NSD1 links H3K36 methylation to Hox-A gene activation and leukaemogenesis. Nat. Cell Biol. 9, 804–812 (2007).

    CAS  PubMed  Google Scholar 

  17. Behjati, S. et al. Distinct H3F3A and H3F3B driver mutations define chondroblastoma and giant cell tumor of bone. Nat. Genet. 45, 1479–1482 (2013).

    CAS  PubMed  Google Scholar 

  18. Jaffe, J.D. et al. Global chromatin profiling reveals NSD2 mutations in pediatric acute lymphoblastic leukemia. Nat. Genet. 45, 1386–1391 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Dalgliesh, G.L. et al. Systematic sequencing of renal carcinoma reveals inactivation of histone modifying genes. Nature 463, 360–363 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Schwartzentruber, J. et al. Driver mutations in histone H3.3 and chromatin remodelling genes in paediatric glioblastoma. Nature 482, 226–231 (2012).

    CAS  PubMed  Google Scholar 

  21. Douglas, J. et al. NSD1 mutations are the major cause of Sotos syndrome and occur in some cases of Weaver syndrome but are rare in other overgrowth phenotypes. Am. J. Hum. Genet. 72, 132–143 (2003).

    CAS  PubMed  Google Scholar 

  22. Tonon, G. et al. High-resolution genomic profiles of human lung cancer. Proc. Natl. Acad. Sci. USA 102, 9625–9630 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Zhang, J. et al. The genetic basis of early T-cell precursor acute lymphoblastic leukaemia. Nature 481, 157–163 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Reva, B., Antipin, Y. & Sander, C. Predicting the functional impact of protein mutations: application to cancer genomics. Nucleic Acids Res. 39, e118 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Qiao, Q. et al. The structure of NSD1 reveals an autoregulatory mechanism underlying histone H3K36 methylation. J. Biol. Chem. 286, 8361–8368 (2011).

    CAS  PubMed  Google Scholar 

  26. Sun, W. et al. Activation of the NOTCH pathway in head and neck cancer. Cancer Res. 74, 1091–1104 (2014).

    CAS  PubMed  Google Scholar 

  27. Hayes, D.N., Van Waes, C. & Seiwert, T.Y. Genetic landscape of human papillomavirus–associated head and neck cancer and comparison to tobacco-related tumors. J. Clin. Oncol. 33, 3227–3234 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Vokes, E.E., Agrawal, N. & Seiwert, T.Y. HPV-associated head and neck cancer. J. Natl. Cancer Inst. 107, djv344 (2015).

    PubMed  Google Scholar 

  29. India Project Team of the International Cancer Genome Consortium. Mutational landscape of gingivo-buccal oral squamous cell carcinoma reveals new recurrently-mutated genes and molecular subgroups. Nat. Commun. 4, 2873 (2013).

  30. Pickering, C.R. et al. Mutational landscape of aggressive cutaneous squamous cell carcinoma. Clin. Cancer Res. 20, 6582–6592 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  31. Lewis, P.W. et al. Inhibition of PRC2 activity by a gain-of-function H3 mutation found in pediatric glioblastoma. Science 340, 857–861 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Lu, C. et al. Histone H3K36 mutations promote sarcomagenesis through altered histone methylation landscape. Science 352, 844–849 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Walter, V. et al. Molecular subtypes in head and neck cancer exhibit distinct patterns of chromosomal gain and loss of canonical cancer genes. PLoS One 8, e56823 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. De Cecco, L. et al. Head and neck cancer subtypes with biological and clinical relevance: meta-analysis of gene-expression data. Oncotarget 6, 9627–9642 (2015).

    PubMed  PubMed Central  Google Scholar 

  35. Saloura, V. et al. WHSC1 promotes oncogenesis through regulation of NIMA-related kinase-7 in squamous cell carcinoma of the head and neck. Mol. Cancer Res. 13, 293–304 (2015).

    CAS  PubMed  Google Scholar 

  36. Choufani, S. et al. NSD1 mutations generate a genome-wide DNA methylation signature. Nat. Commun. 6, 10207 (2015).

    CAS  PubMed  Google Scholar 

  37. Dhayalan, A. et al. The Dnmt3a PWWP domain reads histone 3 lysine 36 trimethylation and guides DNA methylation. J. Biol. Chem. 285, 26114–26120 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Baubec, T. et al. Genomic profiling of DNA methyltransferases reveals a role for DNMT3B in genic methylation. Nature 520, 243–247 (2015).

    CAS  PubMed  Google Scholar 

  39. Johnson, B.E. et al. Mutational analysis reveals the origin and therapy-driven evolution of recurrent glioma. Science 343, 189–193 (2014).

    CAS  PubMed  Google Scholar 

  40. Nikbakht, H. et al. Spatial and temporal homogeneity of driver mutations in diffuse intrinsic pontine glioma. Nat. Commun. 7, 11185 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Aryee, M.J. et al. Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays. Bioinformatics 30, 1363–1369 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Wang, K., Li, M. & Hakonarson, H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 38, e164 (2010).

    PubMed  PubMed Central  Google Scholar 

  43. Liao, Y., Smyth, G.K. & Shi, W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923–930 (2014).

    CAS  PubMed  Google Scholar 

  44. Love, M.I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA–seq data with DESeq2. Genome Biol. 15, 550 (2014).

    PubMed  PubMed Central  Google Scholar 

  45. Nii, M., Kayada, Y., Yoshiga, K., Takada, K. & Yanagihara, K. Expression of type IV collagen-degrading metalloproteinases and tissue inhibitors of metalloproteinases in newly established human oral malignant tumor lines. Jpn. J. Clin. Oncol. 26, 117–123 (1996).

    CAS  PubMed  Google Scholar 

  46. Heo, D.S. et al. Biology, cytogenetics, and sensitivity to immunological effector cells of new head and neck squamous cell carcinoma lines. Cancer Res. 49, 5167–5175 (1989).

    CAS  PubMed  Google Scholar 

  47. Zietman, A.L., Suit, H.D., Ramsay, J.R., Silobrcic, V. & Sedlacek, R.S. Quantitative studies on the transplantability of murine and human tumors into the brain and subcutaneous tissues of NCr/Sed nude mice. Cancer Res. 48, 6510–6516 (1988).

    CAS  PubMed  Google Scholar 

  48. Rheinwald, J.G. & Beckett, M.A. Tumorigenic keratinocyte lines requiring anchorage and fibroblast support cultured from human squamous cell carcinomas. Cancer Res. 41, 1657–1663 (1981).

    CAS  PubMed  Google Scholar 

  49. Sidoli, S., Bhanu, N.V., Karch, K.R., Wang, X. & Garcia, B.A. Complete workflow for analysis of histone post-translational modifications using bottom-up mass spectrometry: from histone extraction to data analysis. J. Vis. Exp. http://dx.doi.org/10.3791/54112 (2016).

  50. Sidoli, S., Simithy, J., Karch, K.R., Kulej, K. & Garcia, B.A. Low resolution data-independent acquisition in an LTQ-Orbitrap allows for simplified and fully untargeted analysis of histone modifications. Anal. Chem. 87, 11448–11454 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank EMD Millipore for its role in H3.3K36M antibody generation, A. Ponce de Leon for help with figure formatting, and the TCGA group for the wealth of data available and for their rapid and helpful answers to other enquiries we had on this data set. This research was supported by US National Institutes of Health (NIH) grants (P01CA196539 to N.J., J.M., P.W.L., B.A.G. and C.D.A.; K99CA212257 to C.L.; T32GM008275 to D.M.M.), the Rockefeller University (to C.D.A.), startup funding provided by the Wisconsin Institute for Discovery (to P.W.L.), the Greater Milwaukee Foundation (to P.W.L.), the Sidney Kimmel Foundation (Kimmel Scholar Award to P.W.L.), Canadian Institutes for Health Research (CIHR) grants (MOP 142491 to J.S.M. and A.C.N.; MOP 340674 to A.C.N.) and the Cedars Cancer Foundation (N.J.). B.A.G. is funded by a Leukemia and Lymphoma Society Dr. Robert Arceci Scholar Award. This work was performed within the context of the I-CHANGE consortium and supported by funding from Genome Canada, Genome Quebec, the Institute for Cancer Research of the CIHR, McGill University and the Montreal Children's Hospital Foundation. C.L. is a Kandarian Family Fellow supported by the Damon Runyon Cancer Research Foundation (DRG-2195-14). N.J. is a member of the Penny Cole Laboratory and the recipient of a Chercheur Boursier, Chaire de Recherche Award from the Fond de la Recherche du Québec en Santé. J.M. holds a Canada Research Chair (tier 2). S.P.-C. is supported by a studentship from the Fond de la Recherche du Québec en Santé. D.B. and T.G. are supported by a fellowship from the TD Trust/Montreal Children's Hospital Foundation and CIHR, respectively.

Author information

Author notes

  1. Simon Papillon-Cavanagh and Chao Lu: These authors contributed equally to this work.

  2. Jacek Majewski and Nada Jabado: These authors jointly supervised this work.

Authors and Affiliations

  1. Department of Human Genetics, McGill University, Montreal, Quebec, Canada

    Simon Papillon-Cavanagh, Tenzin Gayden, Denise Bechet, Octavia Maria Dancu, Jacek Majewski & Nada Jabado

  2. Laboratory of Chromatin Biology and Epigenetics, The Rockefeller University, New York, New York, USA

    Chao Lu & C David Allis

  3. Department of Pediatrics, McGill University and McGill University Heath Centre Research Institute, Montreal, Quebec, Canada

    Leonie G Mikael & Nada Jabado

  4. Princess Margaret Cancer Centre, Toronto, Ontario, Canada

    Christina Karamboulas & Laurie Ailles

  5. Department of Pathology, Montreal Neurological Hospital, McGill University, Montreal, Quebec, Canada

    Jason Karamchandani

  6. Department of Biochemistry and Biophysics, Epigenetics Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA

    Dylan M Marchione & Benjamin A Garcia

  7. Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA

    Dylan M Marchione

  8. Department of Pathology, University Health Network, Toronto, Ontario, Canada

    Ilan Weinreb

  9. Department of Otolaryngology and Department of Surgical Oncology, Princess Margaret Cancer Center, University Health Network, Toronto, Ontario, Canada

    David Goldstein

  10. Wisconsin Institute for Discovery and Department of Biomolecular Chemistry, School of Medicine and Public Health, University of Wisconsin, Madison, Wisconsin, USA

    Peter W Lewis

  11. Department of Otolaryngology—Head and Neck Surgery, University of Western Ontario, London, Ontario, Canada

    Sandeep Dhaliwal, John W Barrett & Anthony C Nichols

  12. Department of Oncology, University of Western Ontario, London, Ontario, Canada

    Sandeep Dhaliwal, John W Barrett & Anthony C Nichols

  13. Department of Pathology and Laboratory Medicine, University of Western Ontario, London, Ontario, Canada

    William Stecho & Christopher J Howlett

  14. Department of Microbiology and Immunology, Oncology and Otolaryngology—Head and Neck Surgery, University of Western Ontario, London, Ontario, Canada

    Joe S Mymryk

  15. London Regional Cancer Program and Lawson Health Research Institute, London, Ontario, Canada

    Joe S Mymryk, John W Barrett & Anthony C Nichols

Authors
  1. Simon Papillon-Cavanagh
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Contributions

S.P.-C., C.L., J.M. and N.J. conceived and designed the experiments and analyzed data. C.L., T.G., L.G.M., D.B., C.K., J.K., O.M.D., S.D., W.S., C.J.H., J.W.B., D.M.M. and B.A.G. performed experiments and analyzed data. L.A., I.W., D.G., J.S.M., P.W.L., A.C.N. and C.D.A. contributed materials and analyzed data. All authors contributed to the written manuscript.

Corresponding authors

Correspondence to Jacek Majewski or Nada Jabado.

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Integrated supplementary information

Supplementary Figure 1 TCGA data set on HNSCCs reanalyzed in this study.

Summary of the TCGA dataset on HNSCCs re-analyzed in this study and the respective numbers of samples available within each.

Supplementary Figure 2 The methylation-defined H3 K36 subgroup consists of samples carrying damaging NSD1 or H3 K36M alterations.

(a) Our analysis reveals that the H3K36 methylation cluster (Fig. 1) is comprised of 61 samples. Ten samples carry H3K36M alterations, while 51 samples have NSD1 alterations, with one carrying both. One sample had no available genomic/transcriptome data. (b) H3K36M alteraions are observed in a wide array of histone H3 genes, supporting the dominant nature of this K-to-M substitution as reported32. (c) Samples in the H3K36 cluster are enriched for nonsense (in red) NSD1 mutations. Missense mutations (in green) are often observed near or at the functional SET domain.

Supplementary Figure 3 IGV screenshots of complex genomic events in NSD1 using RNA-seq data.

(a) A focal deletion of a set of 10 exons in sample BA-4074. (b) Near absent expression of NSD1 in sample CN-4731. (c) Aberrant NSD1 splicing, possibly due to a translocation in sample D6-6823. (d) A Focal deletion of a set of 14 exons in sample UF-A7JH

Supplementary Figure 4 Heat map showing hierarchical clustering of HNSCC samples based on DNA methylation and genetic alterations in other genes associated with HNSSC.

(Top) Previous 4-class, expression-based classification (Atypical (black), Classical (red), Mesenchymal (green), Basal (blue)). (Middle) Other genes involved in the H3K36 methylation pathways are infrequently mutated in HNSCC and do not vary within HPV- HNSCC subgroups. (Bottom) Only TP53, CASP8, NSD1 and H3K36M vary significantly among HPV- HNSCC subgroups. For color coding of methylation groups and anatomical locations, please see Figure 1.

Supplementary Figure 5 Mean sample methylation levels of HNSCC.

Mean sample methylation levels of HNSCC subgroups showing that NSD1 and H3K36M alterations are similarly associated with a DNA hypomethylated phenotype compared to the other four methylation clusters identified in HNSCCs.

Supplementary Figure 6 Global DNA methylation, NSD1 expression level and the types of mutations in the H3 K36M cluster.

(a,b) Samples with NSD1 mutations outside the H3K36M cluster (grey bars) show higher global DNA methylation levels (a) and higher NSD1 gene expression levels (b) compared to samples in the H3K36 cluster (blue bars). (c) Samples in the H3K36 cluster frequently carry NSD1 truncating (nonsense and frameshift) mutations compared to NSD1 mutated samples in the other HNSCC subgroups.

Supplementary Figure 7 Mean somatic mutations per sample of HNSCC subgroups.

Mean somatic mutations per sample of HNSCC subgroups showing that NSD1 mutant samples have higher somatic mutation count than H3K36M samples or other HNSCC subgroups.

Supplementary Figure 8 NSD1 but not H3 K36M mutant samples have smoking-induced somatic mutation signatures.

(a) In NSD1 samples, similar to lung adenocarcinoma (LUAD) and lung squamous cell carcinomas (LUSC), a large proportion of somatic mutations is accounted by the smoking-associated signature S4 (red). In comparison, other HNSCC samples (left) have much less smoking-induced somatic mutations. (b) Unsupervised clustering of mutation frequencies groups NSD1, but not H3K36M, with lung cancers, suggesting the mutational spectrum in NSD1 samples is associated with smoking. (c) A five-signature model identifies UV exposure (S1), Temozolomide (S2) and smoking (S4) as major mutation generation processes.

Supplementary Figure 9 Kaplan–Meier curve for HNSCC patients, grouped by DNA-methylation-defined molecular subgroups.

Supplementary Figure 10 Anatomical distribution of HNSCC samples relative to K36M and NSD1 alterations.

Anatomical distribution of HNSCC samples showing that H3K36M samples are exclusively found in the oral cavity whereas the majority of NSD1 mutated samples are found in the larynx and oral cavity.

Supplementary Figure 11 NSD1 and NSD2 expression in the H3K36 cluster and other HNSCC subgroups

(a) Samples in the H3K36 cluster show lower NSD1 expression levels. (b) NSD2 levels are uniform among al HNSCC subgroups.

Supplementary Figure 12 RNA-expression clustering of HNSCC samples.

Similar to our findings using DNA methylation, we observe a group of samples enriched in NSD1/H3K36M alterations (H3K36 cluster) and another enriched for HPV+ HNSCC. For color coding of methylation groups and anatomical locations, please see Figure 1.

Supplementary Figure 13 Gene ontology enrichment analysis on H3K36-specific differentially expressed genes.

Differential expression analysis performed on H3K36 samples versus all other HNSCCs tumors, controlling for anatomical location.

Supplementary Figure 14 Western blots for H3 K36M and NSD1 in HNSSC cell lines.

Full length immunoblots including molecular weights that were used in Figure 4.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–14 and Supplementary Tables 1–4 and 6 (PDF 2037 kb)

Supplementary Table 5

Complete clinical annotation for the 528 samples used in the methylation clustering. (XLSX 213 kb)

Supplementary Table 7

List of differentially expressed genes in H3K36 versus other HNSCC samples, controlled for anatomical location. (XLSX 51 kb)

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Papillon-Cavanagh, S., Lu, C., Gayden, T. et al. Impaired H3K36 methylation defines a subset of head and neck squamous cell carcinomas. Nat Genet 49, 180–185 (2017). https://doi.org/10.1038/ng.3757

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