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Medulloblastoma exome sequencing uncovers subtype-specific somatic mutations


Medulloblastomas are the most common malignant brain tumours in children1. Identifying and understanding the genetic events that drive these tumours is critical for the development of more effective diagnostic, prognostic and therapeutic strategies. Recently, our group and others described distinct molecular subtypes of medulloblastoma on the basis of transcriptional and copy number profiles2,3,4,5. Here we use whole-exome hybrid capture and deep sequencing to identify somatic mutations across the coding regions of 92 primary medulloblastoma/normal pairs. Overall, medulloblastomas have low mutation rates consistent with other paediatric tumours, with a median of 0.35 non-silent mutations per megabase. We identified twelve genes mutated at statistically significant frequencies, including previously known mutated genes in medulloblastoma such as CTNNB1, PTCH1, MLL2, SMARCA4 and TP53. Recurrent somatic mutations were newly identified in an RNA helicase gene, DDX3X, often concurrent with CTNNB1 mutations, and in the nuclear co-repressor (N-CoR) complex genes GPS2, BCOR and LDB1. We show that mutant DDX3X potentiates transactivation of a TCF promoter and enhances cell viability in combination with mutant, but not wild-type, β-catenin. Together, our study reveals the alteration of WNT, hedgehog, histone methyltransferase and now N-CoR pathways across medulloblastomas and within specific subtypes of this disease, and nominates the RNA helicase DDX3X as a component of pathogenic β-catenin signalling in medulloblastoma.

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Figure 1: Demographic characteristics, molecular subtypes and selected copy number alterations and somatic mutations across 92 medulloblastoma cases.
Figure 2: Location of mutations in histone methyltransferases, RNA helicases and N-CoR complex-associated genes.
Figure 3: Functional consequence of DDX3X point mutations.

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Data deposits

Sequence data used for this analysis are available in dbGaP under accession phs000504.v1.p1.


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This work was supported by NIH grants NHGRI U54HG003067 to E. S. Lander (E.S., D.A., S.B.G., G.G., M.M.); R01CA109467 (S.L.P., J.P.M.); R01CA105607 (H.G., T.M.R., M.M., S.L.P.); P30 HD18655 (S.L.P.); R01 CA030002 and CA050661 (T.M.R.); R01 NS046789 (G.R.C.); R01 CA154480 (P.T.); R25NS070682 (S.S.) and R01CA148699 (M.D.T.); St. Baldrick’s Foundation Scholar Award and the Beirne Faculty Scholar endowment and Center for Children’s Brain Tumors at Stanford University (Y.-J.C.); German Cancer Aid (109252) and the BMBF ICGC-PedBrain project (N.J., D.T.W.J., P.L., S.M.P.); HHMI (G.R.C.); the Pediatric Brain Tumor Foundation (M.D.T.); Canadian Institutes of Health Research Fellowship (T.J.P.); Restracomp funding from the Hospital for Sick Children (P.A.N.); and the Mullarkey Research Fund (S.L.P.). We thank Children’s Oncology Group and the Cooperative Human Tissue Network for providing tumour samples, the staff of the Broad Institute Biological Samples, Genome Sequencing and Genetic Analysis Platforms for their assistance in genomic processing of samples and generating the sequencing data used in this analysis, K. Keho and M. Brown at Pacific Biosciences for technical support with sample barcoding methods, and L. Gaffney of Broad Institute Communications for assistance with figure layout and design.

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Authors and Affiliations



Y.-J.C., M.M. and S.L.P. conceived the project. Y.-J.C., T.J.P., M.M. and S.L.P. wrote the manuscript with input from co-authors. S.D.W., T.C.A., J.P.F., S.S., N.T., Y.-J.C., A.G.K. and F.Y. performed functional characterization studies. D.A.P.K. generated in silico structural modelling of DDX3X mutations. T.J.P. conducted the bioinformatic analysis, supported by S.L.C., P.S., K.C., M.S.L., A.M., A.H.R., A.S., H.G., P.T., J.P.M., N.J. and D.T.W.J.; D.A., E.S., S.B.G., and G.G. facilitated transfer, sequencing and analysis of samples. P.A.N. and M.D.T. provided tissues for analysis. Y.-J.C., J.P.F. and V.A. processed tumour and blood samples for study. G.R.C. generated reagents used in functional characterization studies. P.L., S.M.P. and T.M.R. assisted with interpretation of results. J.B., M.O.C., R.L.E., N.J.L., J.M., M.G.R., C.R. and B.S. performed microfluidic PCR and single-molecule real-time sequencing for validation analysis.

Corresponding authors

Correspondence to Matthew Meyerson, Scott L. Pomeroy or Yoon-Jae Cho.

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Competing interests

M.M. is a paid consultant for and equity holder in Foundation Medicine, a genomics-based oncology diagnostics company, and is a paid consultant for Novartis. Y.-J.C. has served on an advisory board for Novartis.

Supplementary information

Supplementary Information

This file contains Supplementary Text and additional references, Supplementary Figures 1-3 and Supplementary Table 5. (PDF 2067 kb)

Supplementary Data 1

This file contains Supplementary Table 1, showing the clinical, copy number and mutation data matrix. (XLSX 821 kb)

Supplementary Data 2

This file contains Supplementary Table 2 showing the list of candidate somatic mutations, Supplementary Table 4 showing the somatic mutations in histone methyltransferases and Supplementary Table 6, which shows the somatic mutations in RNA helicases. (XLSX 859 kb)

Supplementary Data 3

This file contains Supplementary Table 3, which shows MutSig hits for each medulloblastoma subtype considered independently. (XLSX 13091 kb)

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

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