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  current news   Press   selected story    
     
  22 November 2013  
  Sleeping Beauty mutagenesis in a mouse medulloblastoma model defines networks that discriminate between human molecular subgroups
 
 



Authors
Laura A. Genovesia,*, Ching Ging Ngb,*, Melissa J. Davisa, Marc Remkec, Michael D. Taylorc, David J. Adamsd, Alistair G. Rustd, Jerold M. Wardb , Kenneth H. Banb,e, Nancy A. Jenkinsb,f, Neal G. Copelandb,f and Brandon J. Wainwrighta

a The University of Queensland, Institute for Molecular Bioscience, St Lucia, 4072
b Cancer Genetics Group, Institute for Molecular and Cell Biology, Singapore, 138673
c Division of Neurosurgery, Arthur and Sonia Labatt Brain Tumor Research Centre and Program in    Developmental and Stem Cell Biology, Hospital for Sick Children, University of Toronto,
   Toronto, Ontario ONM5G 1X8, Canada
d Experimental Cancer Genetics, Wellcome Trust Sanger Institute, Hinxton, Cambridge, CB101SA, UK
e Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore,   Singapore 117597
f Cancer Research Program, The Methodist Hospital Research Institute, Houston, TX77030

* Co-first author

Published online in PNAS on 28 October 2013.

Abstract

The Sleeping Beauty (SB) transposon mutagenesis screen is a powerful tool to facilitate the discovery of novel cancer genes that drive tumorigenesis in mouse models.  In this study, we sought to identify genes that functionally co-operate with sonic hedgehog signaling to initiate medulloblastoma (MB), a tumor of the cerebellum.  By combining SB mutagenesis with Patched1 heterozygous mice (Ptch1lacZ/+), we observed an increased frequency of MB and decreased tumor-free survival compared to Ptch1lacZ/+ controls.  From an analysis of 85 tumors we identified 77 common insertion sites (CISs) that map to 56 genes potentially driving increased tumorigenesis. The CIS genes identified in the mutagenesis screen were mapped to human orthologs which were used to select probes and corresponding expression data from an independent set of previously described human MB samples, and surprisingly were capable of accurately clustering known molecular subgroups of MB, thereby defining common regulatory networks underlying all forms of MB irrespective of subgroup.  We performed a network analysis to discover the likely mechanisms of action of sub-networks, and used an in vivo model to confirm a role for a highly ranked candidate gene, Nfia, in promoting MB formation. Our analysis implicates novel candidate cancer genes in the deregulation of apoptosis and translational elongation, and reveals a strong signature of transcriptional regulation that will have broad impact on expression programs in MB.  These networks provide novel functional insights into the complex biology of human medulloblastoma and identify potential avenues for intervention common to all clinical subgroups.

Figure Legend: Circos plot of Medulloblastoma common insertion sites (CISs) identified by the Gaussian kernel convulution (GKC) method. Mouse chromosomes are illustrated on the outer perimeter of the plot.  GKC CIS’s are illustrated on the second most outer ring of the plot marking SB insertions in both the forward and reverse orientation.  The number of unique insertions at each CIS is represented by orange bars, with the number of tumors containing each CIS represented by blue bars.  The black lines in the center connect CIS’s that significantly co-occur in tumors (Fisher exact test, P <0.01).

For more information on Kenneth BAN's laboratory, please click here