Fusion of TTYH1 with the C19MC microRNA cluster drives expression of a brain-specific DNMT3B isoform in the embryonal brain tumor ETMR

Abstract

Embryonal tumors with multilayered rosettes (ETMRs) are rare, deadly pediatric brain tumors characterized by high-level amplification of the microRNA cluster C19MC1,2. We performed integrated genetic and epigenetic analyses of 12 ETMR samples and identified, in all cases, C19MC fusions to TTYH1 driving expression of the microRNAs. ETMR tumors, cell lines and xenografts showed a specific DNA methylation pattern distinct from those of other tumors and normal tissues. We detected extreme overexpression of a previously uncharacterized isoform of DNMT3B originating at an alternative promoter3 that is active only in the first weeks of neural tube development. Transcriptional and immunohistochemical analyses suggest that C19MC-dependent DNMT3B deregulation is mediated by RBL2, a known repressor of DNMT3B4,5. Transfection with individual C19MC microRNAs resulted in DNMT3B upregulation and RBL2 downregulation in cultured cells. Our data suggest a potential oncogenic re-engagement of an early developmental program in ETMR via epigenetic alteration mediated by an embryonic, brain-specific DNMT3B isoform.

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Figure 1: Genomic regions involved in the rearrangement leading to ETMR.
Figure 2: Analysis of methylation and DNMT3B expression in cancer samples and normal brain.
Figure 3: Expression analysis of RBL2 and DNMT3B in patient samples, an ETMR-derived xenograft and neural stem cells transfected with C19MC miRNAs.

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References

  1. 1

    Li, M. et al. Frequent amplification of a chr19q13.41 microRNA polycistron in aggressive primitive neuroectodermal brain tumors. Cancer Cell 16, 533–546 (2009).

    CAS  Article  Google Scholar 

  2. 2

    Pfister, S. et al. Novel genomic amplification targeting the microRNA cluster at 19q13.42 in a pediatric embryonal tumor with abundant neuropil and true rosettes. Acta Neuropathol. 117, 457–464 (2009).

    CAS  Article  Google Scholar 

  3. 3

    Yanagisawa, Y., Ito, E., Yuasa, Y. & Maruyama, K. The human DNA methyltransferases DNMT3A and DNMT3B have two types of promoters with different CpG contents. Biochim. Biophys. Acta 1577, 457–465 (2002).

    CAS  Article  Google Scholar 

  4. 4

    Benetti, R. et al. A mammalian microRNA cluster controls DNA methylation and telomere recombination via Rbl2-dependent regulation of DNA methyltransferases. Nat. Struct. Mol. Biol. 15, 268–279 (2008).

    CAS  Article  Google Scholar 

  5. 5

    Sinkkonen, L. et al. MicroRNAs control de novo DNA methylation through regulation of transcriptional repressors in mouse embryonic stem cells. Nat. Struct. Mol. Biol. 15, 259–267 (2008).

    CAS  Article  Google Scholar 

  6. 6

    Korshunov, A. et al. Focal genomic amplification at 19q13.42 comprises a powerful diagnostic marker for embryonal tumors with ependymoblastic rosettes. Acta Neuropathol. 120, 253–260 (2010).

    Article  Google Scholar 

  7. 7

    Gessi, M. et al. Embryonal tumors with abundant neuropil and true rosettes: a distinctive CNS primitive neuroectodermal tumor. Am. J. Surg. Pathol. 33, 211–217 (2009).

    Article  Google Scholar 

  8. 8

    Korshunov, A. et al. LIN28A immunoreactivity is a potent diagnostic marker of embryonal tumor with multilayered rosettes (ETMR). Acta Neuropathol. 124, 875–881 (2012).

    Article  Google Scholar 

  9. 9

    Picard, D. et al. Markers of survival and metastatic potential in childhood CNS primitive neuro-ectodermal brain tumours: an integrative genomic analysis. Lancet Oncol. 13, 838–848 (2012).

    Article  Google Scholar 

  10. 10

    Bentwich, I. et al. Identification of hundreds of conserved and nonconserved human microRNAs. Nat. Genet. 37, 766–770 (2005).

    CAS  Article  Google Scholar 

  11. 11

    Suzuki, M. & Mizuno, A. A novel human Cl channel family related to Drosophila flightless locus. J. Biol. Chem. 279, 22461–22468 (2004).

    CAS  Article  Google Scholar 

  12. 12

    Rosenbloom, K.R. et al. ENCODE data in the UCSC Genome Browser: year 5 update. Nucleic Acids Res. 41, D56–D63 (2013).

    CAS  Article  Google Scholar 

  13. 13

    Meacham, F. et al. Identification and correction of systematic error in high-throughput sequence data. BMC Bioinformatics 12, 451 (2011).

    Article  Google Scholar 

  14. 14

    Bernstein, B.E. et al. The NIH Roadmap Epigenomics Mapping Consortium. Nat. Biotechnol. 28, 1045–1048 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  15. 15

    Jin, B. et al. DNA methyltransferase 3B (DNMT3B) mutations in ICF syndrome lead to altered epigenetic modifications and aberrant expression of genes regulating development, neurogenesis and immune function. Hum. Mol. Genet. 17, 690–709 (2008).

    CAS  Article  Google Scholar 

  16. 16

    Watanabe, D., Uchiyama, K. & Hanaoka, K. Transition of mouse de novo methyltransferases expression from Dnmt3b to Dnmt3a during neural progenitor cell development. Neuroscience 142, 727–737 (2006).

    CAS  Article  Google Scholar 

  17. 17

    Hayette, S. et al. High DNA methyltransferase DNMT3B levels: a poor prognostic marker in acute myeloid leukemia. PLoS ONE 7, e51527 (2012).

    CAS  Article  Google Scholar 

  18. 18

    Okano, M., Bell, D.W., Haber, D.A. & Li, E. DNA methyltransferases Dnmt3a and Dnmt3b are essential for de novo methylation and mammalian development. Cell 99, 247–257 (1999).

    CAS  Article  Google Scholar 

  19. 19

    Tan, M.H. et al. An Oct4-Sall4-Nanog network controls developmental progression in the pre-implantation mouse embryo. Mol. Syst. Biol. 9, 632 (2013).

    Article  Google Scholar 

  20. 20

    Morales-Prieto, D.M., Ospina-Prieto, S., Chaiwangyen, W., Schoenleben, M. & Markert, U.R. Pregnancy-associated miRNA-clusters. J. Reprod. Immunol. 97, 51–61 (2013).

    CAS  Article  Google Scholar 

  21. 21

    Vaira, V. et al. The microRNA cluster C19MC is deregulated in parathyroid tumours. J. Mol. Endocrinol. 49, 115–124 (2012).

    CAS  Article  Google Scholar 

  22. 22

    Flor, I. & Bullerdiek, J. The dark side of a success story: microRNAs of the C19MC cluster in human tumours. J. Pathol. 227, 270–274 (2012).

    CAS  Article  Google Scholar 

  23. 23

    Fornari, F. et al. In hepatocellular carcinoma miR-519d is up-regulated by p53 and DNA hypomethylation and targets CDKN1A/p21, PTEN, AKT3 and TIMP2. J. Pathol. 227, 275–285 (2012).

    CAS  Article  Google Scholar 

  24. 24

    Rhee, I. et al. DNMT1 and DNMT3b cooperate to silence genes in human cancer cells. Nature 416, 552–556 (2002).

    CAS  Article  Google Scholar 

  25. 25

    Oka, M. et al. De novo DNA methyltransferases Dnmt3a and Dnmt3b primarily mediate the cytotoxic effect of 5-aza-2′-deoxycytidine. Oncogene 24, 3091–3099 (2005).

    CAS  Article  Google Scholar 

  26. 26

    Ostler, K.R. et al. Cancer cells express aberrant DNMT3B transcripts encoding truncated proteins. Oncogene 26, 5553–5563 (2007).

    CAS  Article  Google Scholar 

  27. 27

    You, J.S. & Jones, P.A. Cancer genetics and epigenetics: two sides of the same coin? Cancer Cell 22, 9–20 (2012).

    CAS  Article  Google Scholar 

  28. 28

    Martins-Taylor, K., Schroeder, D.I., LaSalle, J.M., Lalande, M. & Xu, R.H. Role of DNMT3B in the regulation of early neural and neural crest specifiers. Epigenetics 7, 71–82 (2012).

    CAS  Article  Google Scholar 

  29. 29

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

    CAS  Article  Google Scholar 

  30. 30

    Shi, Y. & Majewski, J. FishingCNV: a graphical software package for detecting rare copy number variations in exome-sequencing data. Bioinformatics 29, 1461–1462 (2013).

    CAS  Article  Google Scholar 

  31. 31

    Olshen, A.B., Venkatraman, E.S., Lucito, R. & Wigler, M. Circular binary segmentation for the analysis of array-based DNA copy number data. Biostatistics 5, 557–572 (2004).

    Article  Google Scholar 

  32. 32

    Lohse, M. et al. RobiNA: a user-friendly, integrated software solution for RNA-Seq-based transcriptomics. Nucleic Acids Res. 40, W622–W627 (2012).

    CAS  Article  Google Scholar 

  33. 33

    Trapnell, C., Pachter, L. & Salzberg, S.L. TopHat: discovering splice junctions with RNA-Seq. Bioinformatics 25, 1105–1111 (2009).

    CAS  Article  Google Scholar 

  34. 34

    Langmead, B., Trapnell, C., Pop, M. & Salzberg, S.L. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 10, R25 (2009).

    Article  Google Scholar 

  35. 35

    Thorvaldsdóttir, H., Robinson, J.T. & Mesirov, J.P. Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. Brief. Bioinform. 14, 178–192 (2013).

    Article  Google Scholar 

  36. 36

    Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).

    PubMed  PubMed Central  Google Scholar 

  37. 37

    Quinlan, A.R. & Hall, I.M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).

    CAS  Article  Google Scholar 

  38. 38

    Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).

    CAS  Article  Google Scholar 

  39. 39

    Kent, W.J. BLAT—the BLAST-Like Alignment Tool. Genome Res. 12, 656–664 (2002).

    CAS  Article  Google Scholar 

  40. 40

    Untergasser, A. et al. Primer3Plus, an enhanced web interface to Primer3. Nucleic Acids Res. 35, W71–W74 (2007).

    Article  Google Scholar 

  41. 41

    1000 Genomes Project Consortium. A map of human genome variation from population-scale sequencing. Nature 467, 1061–1073 (2010).

  42. 42

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

    CAS  Article  Google Scholar 

  43. 43

    Maksimovic, J., Gordon, L. & Oshlack, A. SWAN: subset-quantile within array normalization for Illumina Infinium HumanMethylation450 BeadChips. Genome Biol. 13, R44 (2012).

    Article  Google Scholar 

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Acknowledgements

This work was supported by the Cancer Research Society and was funded in part by Hungarian Scientific Research Fund (OTKA) contract T-04639, by National Research and Development Fund (NKFP) contracts 1A/002/2004 (P.H., M. Garami and L.B.) and TÁMOP-4.2.2A-11/1/KONV-2012-0025 (A.K. and L.B.), and by Canadian Institutes of Health Research grant 102684 (A.H.). N.J. is a member of the Penny Cole laboratory and is the recipient of a Chercheur Clinicien Senior Award. S.B. is supported by an RMGA (Reseau Médical de Génétique Apliquée; Network of Applied Genetic Medicine) fellowship. T.P. and J.M. hold Canada Research Chairs (tier 2). C.L.K. is the recipient of a fellowship award from the Fonds de Recherche du Québec-Santé, N.G. is the recipient of a studentship award from Cedars, and A.M.F. is the recipient of a studentship from the Canadian Institutes of Health Research and the McGill–Canadian Institutes of Health Research Training Program in Systems Biology. R.S. is supported by the Canadian Institutes of Health Research.

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N.G., D.-A.K.Q., A.P., P.S.-C., V.A., S.B., A.M.F., Z.D., C.P., T.S., D.F. and P.M.S. performed experimental work. C.L.K., M.C., H.D., S.B., S.P.-C., A.B., A.M. and J.S. performed bioinformatic analyses. C.L.K., N.G., Z.D., A.H., P.S.-C., T.D., S.P.-C., T.P., S.B., V.A., A.S., P.B., R.S., J.M. and N.J. performed data analyses and generated the text and figures. C.L.K., S.P.-C., P.H., A.K., M. Garami, M.Z., M.R., M. Gallo, P.D., M.D.T., P.P.L., L.B., J.-L.M., J.A.C., K.Z., S.A., A.F. and N.J. collected data and provided patient materials. J.M. and N.J. provided leadership for the project. All authors contributed to the final manuscript.

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Correspondence to Annie Huang or Jacek Majewski or Nada Jabado.

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The authors declare no competing financial interests.

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Supplementary Figures 1–16 and Supplementary Tables 1–7 (PDF 3736 kb)

Supplementary Table 8

Differential expression analysis for all UCSC genes expressed above a minimum cutoff level (XLSX 4406 kb)

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Kleinman, C., Gerges, N., Papillon-Cavanagh, S. et al. Fusion of TTYH1 with the C19MC microRNA cluster drives expression of a brain-specific DNMT3B isoform in the embryonal brain tumor ETMR. Nat Genet 46, 39–44 (2014). https://doi.org/10.1038/ng.2849

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