The integrated landscape of driver genomic alterations in glioblastoma

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Glioblastoma is one of the most challenging forms of cancer to treat. Here we describe a computational platform that integrates the analysis of copy number variations and somatic mutations and unravels the landscape of in-frame gene fusions in glioblastoma. We found mutations with loss of heterozygosity in LZTR1, encoding an adaptor of CUL3-containing E3 ligase complexes. Mutations and deletions disrupt LZTR1 function, which restrains the self renewal and growth of glioma spheres that retain stem cell features. Loss-of-function mutations in CTNND2 target a neural-specific gene and are associated with the transformation of glioma cells along the very aggressive mesenchymal phenotype. We also report recurrent translocations that fuse the coding sequence of EGFR to several partners, with EGFR-SEPT14 being the most frequent functional gene fusion in human glioblastoma. EGFR-SEPT14 fusions activate STAT3 signaling and confer mitogen independence and sensitivity to EGFR inhibition. These results provide insights into the pathogenesis of glioblastoma and highlight new targets for therapeutic intervention.

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Figure 1: Chromosome view of validated GBM genes scoring at the top of each of the three categories by MutComFocal.
Figure 2: Interaction with CUL3 and protein stability of wild-type and mutant LZTR1.
Figure 3: Functional analysis of wild-type LZTR1 and GBM-associated mutants in GBM-derived cells.
Figure 4: Expression of δ-catenin in neurons and δ-catenin–driven loss of mesenchymal markers in GBM.
Figure 5: Functional analysis of δ-catenin in mesenchymal GBM.
Figure 6: The EGFR-SEPT14 gene fusion identified by whole-transcriptome sequencing.
Figure 7: Functional analysis of the EGFR-SEPT14 fusion and the effect of inhibition of EGFR kinase on glioma growth.


  1. 1

    Porter, K.R., McCarthy, B.J., Freels, S., Kim, Y. & Davis, F.G. Prevalence estimates for primary brain tumors in the United States by age, gender, behavior, and histology. Neuro. Oncol. 12, 520–527 (2010).

  2. 2

    Stupp, R. et al. Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. N. Engl. J. Med. 352, 987–996 (2005).

  3. 3

    Cancer Genome Atlas Research Network. Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature 455, 1061–1068 (2008).

  4. 4

    Noushmehr, H. et al. Identification of a CpG island methylator phenotype that defines a distinct subgroup of glioma. Cancer Cell 17, 510–522 (2010).

  5. 5

    Parsons, D.W. et al. An integrated genomic analysis of human glioblastoma multiforme. Science 321, 1807–1812 (2008).

  6. 6

    Verhaak, R.G. et al. Integrated genomic analysis identifies clinically relevant subtypes of glioblastoma characterized by abnormalities in PDGFRA, IDH1, EGFR, and NF1. Cancer Cell 17, 98–110 (2010).

  7. 7

    Bass, A.J. et al. Genomic sequencing of colorectal adenocarcinomas identifies a recurrent VTI1A-TCF7L2 fusion. Nat. Genet. 43, 964–968 (2011).

  8. 8

    Chinnaiyan, A.M. & Palanisamy, N. Chromosomal aberrations in solid tumors. Prog. Mol. Biol. Transl. Sci. 95, 55–94 (2010).

  9. 9

    Singh, D. et al. Transforming fusions of FGFR and TACC genes in human glioblastoma. Science 337, 1231–1235 (2012).

  10. 10

    Rubin, A.F. & Green, P. Mutation patterns in cancer genomes. Proc. Natl. Acad. Sci. USA 106, 21766–21770 (2009).

  11. 11

    Fan, Z. et al. BCOR regulates mesenchymal stem cell function by epigenetic mechanisms. Nat. Cell Biol. 11, 1002–1009 (2009).

  12. 12

    Wamstad, J.A. & Bardwell, V.J. Characterization of Bcor expression in mouse development. Gene Expr. Patterns 7, 550–557 (2007).

  13. 13

    Wamstad, J.A., Corcoran, C.M., Keating, A.M. & Bardwell, V.J. Role of the transcriptional corepressor Bcor in embryonic stem cell differentiation and early embryonic development. PLoS ONE 3, e2814 (2008).

  14. 14

    Pugh, T.J. et al. Medulloblastoma exome sequencing uncovers subtype-specific somatic mutations. Nature 488, 106–110 (2012).

  15. 15

    Zhang, J. et al. A novel retinoblastoma therapy from genomic and epigenetic analyses. Nature 481, 329–334 (2012).

  16. 16

    Beroukhim, R. et al. The landscape of somatic copy-number alteration across human cancers. Nature 463, 899–905 (2010).

  17. 17

    Kantarci, S. et al. Mutations in LRP2, which encodes the multiligand receptor megalin, cause Donnai-Barrow and facio-oculo-acoustico-renal syndromes. Nat. Genet. 39, 957–959 (2007).

  18. 18

    Willnow, T.E. et al. Defective forebrain development in mice lacking gp330/megalin. Proc. Natl. Acad. Sci. USA 93, 8460–8464 (1996).

  19. 19

    Christ, A. et al. LRP2 is an auxiliary SHH receptor required to condition the forebrain ventral midline for inductive signals. Dev. Cell 22, 268–278 (2012).

  20. 20

    Cowin, P.A. et al. LRP1B deletion in high-grade serous ovarian cancers is associated with acquired chemotherapy resistance to liposomal doxorubicin. Cancer Res. 72, 4060–4073 (2012).

  21. 21

    Lima, F.R. et al. Glioblastoma: therapeutic challenges, what lies ahead. Biochim. Biophys. Acta 1826, 338–349 (2012).

  22. 22

    Bekker-Jensen, S. et al. HERC2 coordinates ubiquitin-dependent assembly of DNA repair factors on damaged chromosomes. Nat. Cell Biol. 12, 80–86 (2010).

  23. 23

    Harlalka, G.V. et al. Mutation of HERC2 causes developmental delay with Angelman-like features. J. Med. Genet. 50, 65–73 (2013).

  24. 24

    Nacak, T.G., Leptien, K., Fellner, D., Augustin, H.G. & Kroll, J. The BTB-kelch protein LZTR-1 is a novel Golgi protein that is degraded upon induction of apoptosis. J. Biol. Chem. 281, 5065–5071 (2006).

  25. 25

    Stogios, P.J., Downs, G.S., Jauhal, J.J., Nandra, S.K. & Prive, G.G. Sequence and structural analysis of BTB domain proteins. Genome Biol. 6, R82 (2005).

  26. 26

    Errington, W.J. et al. Adaptor protein self-assembly drives the control of a cullin-RING ubiquitin ligase. Structure 20, 1141–1153 (2012).

  27. 27

    Ji, A.X. & Prive, G.G. Crystal structure of KLHL3 in complex with Cullin3. PLoS ONE 8, e60445 (2013).

  28. 28

    Canning, P. et al. Structural basis for Cul3 assembly with the BTB-Kelch family of E3 ubiquitin ligases. J. Biol. Chem. 288, 7803–7814 (2013).

  29. 29

    Lo, S.C., Li, X., Henzl, M.T., Beamer, L.J. & Hannink, M. Structure of the Keap1:Nrf2 interface provides mechanistic insight into Nrf2 signaling. EMBO J. 25, 3605–3617 (2006).

  30. 30

    Boyden, L.M. et al. Mutations in kelch-like 3 and cullin 3 cause hypertension and electrolyte abnormalities. Nature 482, 98–102 (2012).

  31. 31

    Louis-Dit-Picard, H. et al. KLHL3 mutations cause familial hyperkalemic hypertension by impairing ion transport in the distal nephron. Nat. Genet. 44, 456–460 (2012).

  32. 32

    Emanuele, M.J. et al. Global identification of modular cullin-RING ligase substrates. Cell 147, 459–474 (2011).

  33. 33

    Galan, J.M. & Peter, M. Ubiquitin-dependent degradation of multiple F-box proteins by an autocatalytic mechanism. Proc. Natl. Acad. Sci. USA 96, 9124–9129 (1999).

  34. 34

    Zhang, D.D. et al. Ubiquitination of Keap1, a BTB-Kelch substrate adaptor protein for Cul3, targets Keap1 for degradation by a proteasome-independent pathway. J. Biol. Chem. 280, 30091–30099 (2005).

  35. 35

    Günther, H.S. et al. Glioblastoma-derived stem cell–enriched cultures form distinct subgroups according to molecular and phenotypic criteria. Oncogene 27, 2897–2909 (2008).

  36. 36

    Abu-Elneel, K. et al. A δ-catenin signaling pathway leading to dendritic protrusions. J. Biol. Chem. 283, 32781–32791 (2008).

  37. 37

    Arikkath, J. et al. δ-catenin regulates spine and synapse morphogenesis and function in hippocampal neurons during development. J. Neurosci. 29, 5435–5442 (2009).

  38. 38

    Kosik, K.S., Donahue, C.P., Israely, I., Liu, X. & Ochiishi, T. δ-catenin at the synaptic-adherens junction. Trends Cell Biol. 15, 172–178 (2005).

  39. 39

    Israely, I. et al. Deletion of the neuron-specific protein δ-catenin leads to severe cognitive and synaptic dysfunction. Curr. Biol. 14, 1657–1663 (2004).

  40. 40

    Jun, G. et al. δ-catenin is genetically and biologically associated with cortical cataract and future Alzheimer-related structural and functional brain changes. PLoS ONE 7, e43728 (2012).

  41. 41

    Hicks, S., Wheeler, D.A., Plon, S.E. & Kimmel, M. Prediction of missense mutation functionality depends on both the algorithm and sequence alignment employed. Hum. Mutat. 32, 661–668 (2011).

  42. 42

    Phillips, H.S. et al. Molecular subclasses of high-grade glioma predict prognosis, delineate a pattern of disease progression, and resemble stages in neurogenesis. Cancer Cell 9, 157–173 (2006).

  43. 43

    Carro, M.S. et al. The transcriptional network for mesenchymal transformation of brain tumours. Nature 463, 318–325 (2010).

  44. 44

    Pierotti, M.A. & Greco, A. Oncogenic rearrangements of the NTRK1/NGF receptor. Cancer Lett. 232, 90–98 (2006).

  45. 45

    Dunn, G.P. et al. Emerging insights into the molecular and cellular basis of glioblastoma. Genes Dev. 26, 756–784 (2012).

  46. 46

    Liu, C. et al. Chemokine receptor CXCR3 promotes growth of glioma. Carcinogenesis 32, 129–137 (2011).

  47. 47

    Vivanco, I. et al. Differential sensitivity of glioma- versus lung cancer-specific EGFR mutations to EGFR kinase inhibitors. Cancer Discov. 2, 458–471 (2012).

  48. 48

    Forbes, S.A. et al. COSMIC (the Catalogue of Somatic Mutations in Cancer): a resource to investigate acquired mutations in human cancer. Nucleic Acids Res. 38, D652–D657 (2010).

  49. 49

    Northcott, P.A. et al. Subgroup-specific structural variation across 1,000 medulloblastoma genomes. Nature 488, 49–56 (2012).

  50. 50

    Tiacci, E. et al. BRAF mutations in hairy-cell leukemia. N. Engl. J. Med. 364, 2305–2315 (2011).

  51. 51

    Iyer, M.K., Chinnaiyan, A.M. & Maher, C.A. ChimeraScan: a tool for identifying chimeric transcription in sequencing data. Bioinformatics 27, 2903–2904 (2011).

  52. 52

    Vilella, A.J. et al. EnsemblCompara GeneTrees: complete, duplication-aware phylogenetic trees in vertebrates. Genome Res. 19, 327–335 (2009).

  53. 53

    Seal, R.L., Gordon, S.M., Lush, M.J., Wright, M.W. & Bruford, E.A. the HGNC resources in 2011. Nucleic Acids Res. 39, D514–D519 (2011).

  54. 54

    Danecek, P. et al. The variant call format and VCFtools. Bioinformatics 27, 2156–2158 (2011).

  55. 55

    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).

  56. 56

    Söding, J. Protein homology detection by HMM-HMM comparison. Bioinformatics 21, 951–960 (2005).

  57. 57

    Roy, A., Kucukural, A. & Zhang, Y. I-TASSER: a unified platform for automated protein structure and function prediction. Nat. Protoc. 5, 725–738 (2010).

  58. 58

    Zhuang, M. et al. Structures of SPOP-substrate complexes: insights into molecular architectures of BTB-Cul3 ubiquitin ligases. Mol. Cell 36, 39–50 (2009).

  59. 59

    Fülop, V. & Jones, D.T. Beta propellers: structural rigidity and functional diversity. Curr. Opin. Struct. Biol. 9, 715–721 (1999).

  60. 60

    Tropepe, V. et al. Distinct neural stem cells proliferate in response to EGF and FGF in the developing mouse telencephalon. Dev. Biol. 208, 166–188 (1999).

  61. 61

    Niola, F. et al. Id proteins synchronize stemness and anchorage to the niche of neural stem cells. Nat. Cell Biol. 14, 477–487 (2012).

  62. 62

    Niola, F. et al. Mesenchymal high-grade glioma is maintained by the ID-RAP1 axis. J. Clin. Invest. 123, 405–417 (2013).

  63. 63

    Zhao, X. et al. The N-Myc-DLL3 cascade is suppressed by the ubiquitin ligase Huwe1 to inhibit proliferation and promote neurogenesis in the developing brain. Dev. Cell 17, 210–221 (2009).

  64. 64

    Zhao, X. et al. The HECT-domain ubiquitin ligase Huwe1 controls neural differentiation and proliferation by destabilizing the N-Myc oncoprotein. Nat. Cell Biol. 10, 643–653 (2008).

  65. 65

    Friedman, H.S. et al. Experimental chemotherapy of human medulloblastoma cell lines and transplantable xenografts with bifunctional alkylating agents. Cancer Res. 48, 4189–4195 (1988).

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This work was supported by National Cancer Institute grants R01CA101644 and R01CA131126 (A.L.) and R01CA085628 and R01CA127643 (A.I.), the Stewart Foundation (R.R.), the Partnership for Cure (R.R.), US National Institutes of Health (NIH) grant NIH 1 P50 MH094267-01 (R.R.), the Lymphoma Research Foundation (R.R.), NIH 1 U54 CA121852-05 (R.R.), NIH 1R01CA164152-01 (R.R.), the Leukemia and Lymphoma Society (R.R.), the Canadian Cancer Society (G.G.P.), the Cancer Research Society (G.G.P.), the National Institute of Neurological Disorders and Stroke R01NS061776 (A.I.) and a grant from The Chemotherapy Foundation (A.I.). G.F. was supported by grants from the Associazione Italiana per la Ricerca sul Cancro and from the Italian Ministry of Health. V.F., P.Z., C.D. and F.N. are supported by fellowships from the Italian Ministry of Welfare/Provincia di Benevento and the Federazione Italiana Associazioni Genitori Oncoematologia Pedriatica (FIAGOP) (C.D.). We thank J. Parkinson for helpful discussions on the phylogeny of LZTR1 genes, L. Bertin for help with protein blots, J. Kroll (Tumor Biology Center, Freiburg) for the LZTR1 plasmids and M. Pagano (New York University) for CUL3 expression plasmids.

Author information

A.L., R.R. and A.I. conceived the ideas for this study. R.R. designed and supervised the computational approach, and A.L. and A.I. designed and supervised the experimental platform. A.L. performed or assisted in each step of the experimental platform. V.F., A.C., M.L., F.N. and C.D. conducted biological experiments. V.T. performed the MutComFocal analysis. J.M.C. and F.A. performed the gene fusion analysis, allele-specific expression and most of the bioinformatics analyses. P.Z. performed bioinformatics and statistical analyses. S.T.K., H.Y., R.E.M. and D.D.B. performed the human glioma xenograft analyses to evaluate the effects of EGFR inhibitors and provided human GBM specimens. A.X.J. and G.G.P. performed the modeling analysis of LZTR1. I.D. and A.H. conducted the targeted sequencing analysis. P.P., S.P., D.J.P., P.C., J.N.B., K.A., G.G., G.F. and T.M. provided tissue materials from study subjects. A.L., R.R. and A.I. wrote the manuscript with contributions from all other authors.

Correspondence to Anna Lasorella or Raul Rabadan or Antonio Iavarone.

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Frattini, V., Trifonov, V., Chan, J. et al. The integrated landscape of driver genomic alterations in glioblastoma. Nat Genet 45, 1141–1149 (2013) doi:10.1038/ng.2734

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