Advertisement

Acta Neuropathologica

, Volume 128, Issue 1, pp 123–136 | Cite as

Genomic and transcriptomic analyses match medulloblastoma mouse models to their human counterparts

  • Julia Pöschl
  • Sebastian Stark
  • Philipp Neumann
  • Susanne Gröbner
  • Daisuke Kawauchi
  • David T. W. Jones
  • Paul A. Northcott
  • Peter Lichter
  • Stefan M. Pfister
  • Marcel Kool
  • Ulrich SchüllerEmail author
Original Paper

Abstract

Medulloblastoma is a malignant embryonal brain tumor with highly variable outcome. In order to study the biology of this tumor and to perform preclinical treatment studies, a lot of effort has been put into the generation of appropriate mouse models. The usage of these models, however, has become debatable with the advances in human medulloblastoma subgrouping. This study brings together multiple relevant mouse models and matches genetic alterations and gene expression data of 140 murine tumors with 423 human medulloblastomas in a global way. Using AGDEX analysis and k-means clustering, we show that the Blbp-cre::Ctnnb1(ex3) Fl/+ Trp53 Fl/Fl mouse model fits well to human WNT medulloblastoma, and that, among various Myc- or Mycn-based mouse medulloblastomas, tumors in Glt1-tTA::TRE-MYCN/Luc mice proved to be most specific for human group 3 medulloblastoma. None of the analyzed models displayed a significant match to group 4 tumors. Intriguingly, mice with Ptch1 or Smo mutations selectively modeled SHH medulloblastomas of adulthood, although such mutations occur in all human age groups. We therefore suggest that the infantile or adult gene expression pattern of SHH MBs are not solely determined by specific mutations. This is supported by the observation that human medulloblastomas with PTCH1 mutations displayed more similarities to PTCH1 wild-type tumors of the same age group than to PTCH1-mutated tumors of the other age group. Together, we provide novel insights into previously unrecognized specificity of distinct models and suggest these findings as a solid basis to choose the appropriate model for preclinical studies on medulloblastoma.

Keywords

WNT SHH Medulloblastoma Gene expression profile Mutations Mouse model 

Notes

Acknowledgments

We thank Dr. Y. Lee and Dr. P. McKinnon (both Memphis, TN, USA) for providing microarray data. We are further indebted to Dr. Dr. M. Dorostkar (Munich, Germany) and all members of the Schüller group for very fruitful discussions. This work was supported by grants from the Deutsche Krebshilfe (Max-Eder junior research program to U.S.), the Wilhelm Sander Foundation (to U.S.), the Else-Kröner-Fresenius Foundation (to U.S.) and the Friedrich Baur Foundation (to J. P.).

Supplementary material

401_2014_1297_MOESM1_ESM.pptx (1.8 mb)
Supplementary material 1 (PPTX 1820 kb)

References

  1. 1.
    Atkinson SP, Koch CM, Clelland GK et al (2008) Epigenetic marking prepares the human HOXA cluster for activation during differentiation of pluripotent cells. Stem Cells 26:1174–1185. doi: 10.1634/stemcells.2007-0497 PubMedCrossRefGoogle Scholar
  2. 2.
    Bocker MT, Tuorto F, Raddatz G et al (2012) Hydroxylation of 5-methylcytosine by TET2 maintains the active state of the mammalian HOXA cluster. Nat Commun 3:818. doi: 10.1038/ncomms1826 PubMedCentralPubMedCrossRefGoogle Scholar
  3. 3.
    Brugieres L, Remenieras A, Pierron G et al (2012) High frequency of germline SUFU mutations in children with desmoplastic/nodular medulloblastoma younger than 3 years of age. J Clin Oncol 30:2087–2093. doi: 10.1200/JCO.2011.38.7258 PubMedCrossRefGoogle Scholar
  4. 4.
    Di Vinci A, Brigati C, Casciano I et al (2012) HOXA7, 9, and 10 are methylation targets associated with aggressive behavior in meningiomas. Transl Res 160:355–362. doi: 10.1016/j.trsl.2012.05.007 PubMedCrossRefGoogle Scholar
  5. 5.
    Di Vinci A, Casciano I, Marasco E et al (2012) Quantitative methylation analysis of HOXA3, 7, 9, and 10 genes in glioma: association with tumor WHO grade and clinical outcome. J Cancer Res Clin Oncol 138:35–47. doi: 10.1007/s00432-011-1070-5 PubMedCrossRefGoogle Scholar
  6. 6.
    Fattet S, Haberler C, Legoix P et al (2009) Beta-catenin status in paediatric medulloblastomas: correlation of immunohistochemical expression with mutational status, genetic profiles, and clinical characteristics. J Pathol 218:86–94. doi: 10.1002/path.2514 PubMedCrossRefGoogle Scholar
  7. 7.
    Favier B, Dolle P (1997) Developmental functions of mammalian Hox genes. Mol Hum Reprod 3:115–131PubMedCrossRefGoogle Scholar
  8. 8.
    Gibson P, Tong Y, Robinson G et al (2010) Subtypes of medulloblastoma have distinct developmental origins. Nature 468:1095–1099. doi: 10.1038/nature09587 PubMedCentralPubMedCrossRefGoogle Scholar
  9. 9.
    Goodrich LV, Milenkovic L, Higgins KM, Scott MP (1997) Altered neural cell fates and medulloblastoma in mouse patched mutants. Science 277:1109–1113PubMedCrossRefGoogle Scholar
  10. 10.
    Grammel D, Warmuth-Metz M, von Bueren AO et al (2012) Sonic hedgehog-associated medulloblastoma arising from the cochlear nuclei of the brainstem. Acta Neuropathol 123:601–614. doi: 10.1007/s00401-012-0961-0 PubMedCrossRefGoogle Scholar
  11. 11.
    Hershko AY, Kafri T, Fainsod A, Razin A (2003) Methylation of HoxA5 and HoxB5 and its relevance to expression during mouse development. Gene 302:65–72PubMedCrossRefGoogle Scholar
  12. 12.
    Johnson RA, Wright KD, Poppleton H et al (2010) Cross-species genomics matches driver mutations and cell compartments to model ependymoma. Nature 466:632–636. doi: 10.1038/nature09173 PubMedCentralPubMedCrossRefGoogle Scholar
  13. 13.
    Johnson WE, Li C, Rabinovic A (2007) Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics 8:118–127. doi: 10.1093/biostatistics/kxj037 PubMedCrossRefGoogle Scholar
  14. 14.
    Jones DT, Jäger N, Kool M et al (2012) Dissecting the genomic complexity underlying medulloblastoma. Nature 488:100–105. doi: 10.1038/nature11284 PubMedCentralPubMedCrossRefGoogle Scholar
  15. 15.
    Kawauchi D, Robinson G, Uziel T et al (2012) A mouse model of the most aggressive subgroup of human medulloblastoma. Cancer Cell 21:168–180. doi: 10.1016/j.ccr.2011.12.023 PubMedCentralPubMedCrossRefGoogle Scholar
  16. 16.
    Kim JJ, Gill PS, Rotin L et al (2011) Suppressor of fused controls mid-hindbrain patterning and cerebellar morphogenesis via GLI3 repressor. J Neurosci 31:1825–1836. doi: 10.1523/JNEUROSCI.2166-10.201131/5/1825 PubMedCrossRefGoogle Scholar
  17. 17.
    Kool M, Korshunov A, Remke M et al (2012) Molecular subgroups of medulloblastoma: an international meta-analysis of transcriptome, genetic aberrations, and clinical data of WNT, SHH, Group 3, and Group 4 medulloblastomas. Acta Neuropathol 123:473–484. doi: 10.1007/s00401-012-0958-8 PubMedCentralPubMedCrossRefGoogle Scholar
  18. 18.
    Kool M, Koster J, Bunt J et al (2008) Integrated genomics identifies five medulloblastoma subtypes with distinct genetic profiles, pathway signatures and clinicopathological features. PLoS ONE 3:e3088. doi: 10.1371/journal.pone.0003088 PubMedCentralPubMedCrossRefGoogle Scholar
  19. 19.
    Kool M, Jäger N, Northcott P et al (2014) Genome sequencing of SHH medulloblastoma predicts genotype-related response to smoothened-inhibition. Cancer Cell 25(3):393–405. doi: 10.1016/j.ccr.2014.02.004 PubMedCrossRefGoogle Scholar
  20. 20.
    Krivtsov AV, Feng Z, Lemieux ME et al (2008) H3K79 methylation profiles define murine and human MLL-AF4 leukemias. Cancer Cell 14:355–368. doi: 10.1016/j.ccr.2008.10.001 PubMedCentralPubMedCrossRefGoogle Scholar
  21. 21.
    Lattin JE, Schroder K, Su AI et al (2008) Expression analysis of G Protein-Coupled Receptors in mouse macrophages. Immunome Res 4:5. doi: 10.1186/1745-7580-4-5 PubMedCentralPubMedCrossRefGoogle Scholar
  22. 22.
    Lau J, Schmidt C, Markant SL, Taylor MD, Wechsler-Reya RJ, Weiss WA (2012) Matching mice to malignancy: molecular subgroups and models of medulloblastoma. Childs Nerv Syst 28:521–532. doi: 10.1007/s00381-012-1704-1 PubMedCentralPubMedCrossRefGoogle Scholar
  23. 23.
    Laurent L, Wong E, Li G et al (2010) Dynamic changes in the human methylome during differentiation. Genome Res 20:320–331. doi: 10.1101/gr.101907.109 PubMedCentralPubMedCrossRefGoogle Scholar
  24. 24.
    Lee Y, Kawagoe R, Sasai K et al (2007) Loss of suppressor-of-fused function promotes tumorigenesis. Oncogene 26:6442–6447. doi: 10.1038/sj.onc.1210467 PubMedCrossRefGoogle Scholar
  25. 25.
    Leek JT, Johnson WE, Parker HS, Jaffe AE, Storey JD (2012) The sva package for removing batch effects and other unwanted variation in high-throughput experiments. Bioinformatics 28:882–883. doi: 10.1093/bioinformatics/bts034 PubMedCentralPubMedCrossRefGoogle Scholar
  26. 26.
    Lepourcelet M, Tou L, Cai L et al (2005) Insights into developmental mechanisms and cancers in the mammalian intestine derived from serial analysis of gene expression and study of the hepatoma-derived growth factor (HDGF). Development 132:415–427PubMedCrossRefGoogle Scholar
  27. 27.
    Li H (2011) Improving SNP discovery by base alignment quality. Bioinformatics 27:1157–1158. doi: 10.1093/bioinformatics/btr076 PubMedCentralPubMedCrossRefGoogle Scholar
  28. 28.
    Li H, Handsaker B, Wysoker A et al (2009) The sequence alignment/map format and SAMtools. Bioinformatics 25:2078–2079. doi: 10.1093/bioinformatics/btp352 PubMedCentralPubMedCrossRefGoogle Scholar
  29. 29.
    Li P, Du F, Yuelling LW et al (2013) A population of Nestin-expressing progenitors in the cerebellum exhibits increased tumorigenicity. Nat Neurosci 16:1737–1744. doi: 10.1038/nn.3553 PubMedCrossRefGoogle Scholar
  30. 30.
    Mao J, Ligon KL, Rakhlin EY et al (2006) A novel somatic mouse model to survey tumorigenic potential applied to the Hedgehog pathway. Cancer Res 66:10171–10178PubMedCentralPubMedCrossRefGoogle Scholar
  31. 31.
    Northcott PA, Hielscher T, Dubuc A et al (2011) Pediatric and adult sonic hedgehog medulloblastomas are clinically and molecularly distinct. Acta Neuropathol (Berl) 122:231–240CrossRefGoogle Scholar
  32. 32.
    Northcott PA, Jones DT, Kool M et al (2012) Medulloblastomics: the end of the beginning. Nat Rev Cancer 12:818–834. doi: 10.1038/nrc3410nrc3410 PubMedCentralPubMedCrossRefGoogle Scholar
  33. 33.
    Northcott PA, Korshunov A, Witt H et al (2011) Medulloblastoma comprises four distinct molecular variants. J Clin Oncol 29:1408–1414PubMedCrossRefGoogle Scholar
  34. 34.
    Northcott PA, Shih DJ, Peacock J et al (2012) Subgroup-specific structural variation across 1,000 medulloblastoma genomes. Nature 488:49–56. doi: 10.1038/nature11327 PubMedCentralPubMedCrossRefGoogle Scholar
  35. 35.
    Novak P, Jensen T, Oshiro MM et al (2006) Epigenetic inactivation of the HOXA gene cluster in breast cancer. Cancer Res 66:10664–10670. doi: 10.1158/0008-5472.CAN-06-2761 PubMedCrossRefGoogle Scholar
  36. 36.
    Oliver TG, Read TA, Kessler JD et al (2005) Loss of patched and disruption of granule cell development in a pre-neoplastic stage of medulloblastoma. Development 132:2425–2439PubMedCrossRefGoogle Scholar
  37. 37.
    Pei Y, Moore CE, Wang J et al (2012) An animal model of MYC-driven medulloblastoma. Cancer Cell 21:155–167. doi: 10.1016/j.ccr.2011.12.021 PubMedCentralPubMedCrossRefGoogle Scholar
  38. 38.
    Pounds S, Gao CL, Johnson RA et al (2011) A procedure to statistically evaluate agreement of differential expression for cross-species genomics. Bioinformatics 27:2098–2103. doi: 10.1093/bioinformatics/btr362 PubMedCentralPubMedCrossRefGoogle Scholar
  39. 39.
    Robinson G, Parker M, Kranenburg TA et al (2012) Novel mutations target distinct subgroups of medulloblastoma. Nature 488:43–48. doi: 10.1038/nature11213 PubMedCentralPubMedCrossRefGoogle Scholar
  40. 40.
    Rutkowski S, von Hoff K, Emser A et al (2010) Survival and prognostic factors of early childhood medulloblastoma: an international meta-analysis. J Clin Oncol 28:4961–4968PubMedCrossRefGoogle Scholar
  41. 41.
    Schüller U, Heine VM, Mao J et al (2008) Acquisition of granule neuron precursor identity is a critical determinant of progenitor cell competence to form Shh-induced medulloblastoma. Cancer Cell 14:123–134. doi: 10.1016/j.ccr.2008.07.005 PubMedCentralPubMedCrossRefGoogle Scholar
  42. 42.
    Shiraishi M, Sekiguchi A, Oates AJ, Terry MJ, Miyamoto Y (2002) HOX gene clusters are hotspots of de novo methylation in CpG islands of human lung adenocarcinomas. Oncogene 21:3659–3662. doi: 10.1038/sj.onc.1205453 PubMedCrossRefGoogle Scholar
  43. 43.
    Shirasawa S, Arata A, Onimaru H et al (2000) Rnx deficiency results in congenital central hypoventilation. Nat Genet 24:287–290. doi: 10.1038/73516 PubMedCrossRefGoogle Scholar
  44. 44.
    Strathdee G, Holyoake TL, Sim A et al (2007) Inactivation of HOXA genes by hypermethylation in myeloid and lymphoid malignancy is frequent and associated with poor prognosis. Clin Cancer Res 13:5048–5055. doi: 10.1158/1078-0432.CCR-07-0919 PubMedCrossRefGoogle Scholar
  45. 45.
    Swartling FJ, Grimmer MR, Hackett CS et al (2010) Pleiotropic role for MYCN in medulloblastoma. Genes Dev 24:1059–1072. doi: 10.1101/gad.190751024/10/1059 PubMedCentralPubMedCrossRefGoogle Scholar
  46. 46.
    Swartling FJ, Savov V, Persson AI et al (2012) Distinct neural stem cell populations give rise to disparate brain tumors in response to N-MYC. Cancer Cell 21:601–613. doi: 10.1016/j.ccr.2012.04.012 PubMedCentralPubMedCrossRefGoogle Scholar
  47. 47.
    Taylor MD, Northcott PA, Korshunov A et al (2012) Molecular subgroups of medulloblastoma: the current consensus. Acta Neuropathol 123:465–472. doi: 10.1007/s00401-011-0922-z PubMedCentralPubMedCrossRefGoogle Scholar
  48. 48.
    Uziel T, Zindy F, Xie S et al (2005) The tumor suppressors Ink4c and p53 collaborate independently with Patched to suppress medulloblastoma formation. Genes Dev 19:2656–2667. doi: 10.1101/gad.1368605 PubMedCentralPubMedCrossRefGoogle Scholar
  49. 49.
    Wang K, Li M, Hakonarson H (2010) ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res 38:e164. doi: 10.1093/nar/gkq603gkq603 PubMedCentralPubMedCrossRefGoogle Scholar
  50. 50.
    Wefers AK, Warmuth-Metz M, Pöschl J et al (2014) Subgroup-specific localization of human medulloblastoma based on pre-operative MRI. Acta Neuropathol 127:931–933. doi: 10.1007/s00401-014-1271-5 PubMedCrossRefGoogle Scholar
  51. 51.
    Wetmore C, Eberhart DE, Curran T (2001) Loss of p53 but not ARF accelerates medulloblastoma in mice heterozygous for patched. Cancer Res 61:513–516PubMedGoogle Scholar
  52. 52.
    Yang ZJ, Ellis T, Markant SL et al (2008) Medulloblastoma can be initiated by deletion of Patched in lineage-restricted progenitors or stem cells. Cancer Cell 14:135–145. doi: 10.1016/j.ccr.2008.07.003 PubMedCentralPubMedCrossRefGoogle Scholar
  53. 53.
    Zhukova N, Ramaswamy V, Remke M et al (2013) Subgroup-specific prognostic implications of TP53 mutation in medulloblastoma. J Clin Oncol 31:2927–2935. doi: 10.1200/JCO.2012.48.5052 PubMedCrossRefGoogle Scholar
  54. 54.
    Zindy F, Uziel T, Ayrault O et al (2007) Genetic alterations in mouse medulloblastomas and generation of tumors de novo from primary cerebellar granule neuron precursors. Cancer Res 67:2676–2684. doi: 10.1158/0008-5472.CAN-06-3418 PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Julia Pöschl
    • 1
  • Sebastian Stark
    • 2
    • 6
  • Philipp Neumann
    • 3
  • Susanne Gröbner
    • 2
  • Daisuke Kawauchi
    • 2
  • David T. W. Jones
    • 2
  • Paul A. Northcott
    • 2
  • Peter Lichter
    • 4
  • Stefan M. Pfister
    • 2
    • 5
  • Marcel Kool
    • 2
  • Ulrich Schüller
    • 1
    Email author
  1. 1.Center for Neuropathology and Prion ResearchLudwig-Maximilians-UniversityMunichGermany
  2. 2.Division of Pediatric Neuroncology (B062)German Cancer Research Center (DKFZ)HeidelbergGermany
  3. 3.Department of InformaticsTechnical UniversityMunichGermany
  4. 4.Division of Molecular GeneticsGerman Cancer Research Center (DKFZ)HeidelbergGermany
  5. 5.Department of Pediatric Hematology and OncologyHeidelberg University HospitalHeidelbergGermany
  6. 6.Department of General PediatricsHeidelberg University HospitalHeidelbergGermany

Personalised recommendations