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Prediction of central nervous system embryonal tumour outcome based on gene expression

Abstract

Embryonal tumours of the central nervous system (CNS) represent a heterogeneous group of tumours about which little is known biologically, and whose diagnosis, on the basis of morphologic appearance alone, is controversial. Medulloblastomas, for example, are the most common malignant brain tumour of childhood, but their pathogenesis is unknown, their relationship to other embryonal CNS tumours is debated1,2, and patients’ response to therapy is difficult to predict3. We approached these problems by developing a classification system based on DNA microarray gene expression data derived from 99 patient samples. Here we demonstrate that medulloblastomas are molecularly distinct from other brain tumours including primitive neuroectodermal tumours (PNETs), atypical teratoid/rhabdoid tumours (AT/RTs) and malignant gliomas. Previously unrecognized evidence supporting the derivation of medulloblastomas from cerebellar granule cells through activation of the Sonic Hedgehog (SHH) pathway was also revealed. We show further that the clinical outcome of children with medulloblastomas is highly predictable on the basis of the gene expression profiles of their tumours at diagnosis.

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Figure 1: Classification of embryonal brain tumours by gene expression.
Figure 2: Differential expression of genes in classic versus desmoplastic medulloblastomas.
Figure 3: Representative electron micrographs showing medulloblastomas with low ribosome (a) and high ribosome (b) content.
Figure 4: Predicting medulloblastoma outcome by gene expression profiling.

References

  1. Rorke, L. B. The cerebellar medulloblastoma and its relationship to primitive neuroectodermal tumors. J. Neuropathol. Exp. Neurol. 42, 1–15 (1983).

    Article  CAS  Google Scholar 

  2. Kadin, M. E., Rubenstein, L. J. & Nelson, J. S. Neonatal cerebellar medulloblastoma originating from the fetal external granular layer. J. Neuropath. Exp. Neurol. 29, 583–600 (1970).

    Article  CAS  Google Scholar 

  3. Packer, R. J. et al. Treatment of children with medulloblastomas with reduced-dose craniospinal radiation therapy and adjuvant chemotherapy: a children's cancer group study. J. Clin. Oncol. 17, 2127–2136 (1999).

    Article  CAS  Google Scholar 

  4. Mardia, K. V., Kent, J. T. & Bibby, J. M. Multivariate Analysis (Academic, London, 1979).

    MATH  Google Scholar 

  5. Eisen, M. B., Spellman, P. T., Brown, P. O. & Botstein, D. Cluster analysis and display of genome-wide expression patterns. Proc. Natl Acad. Sci. USA 95, 14863–14868 (1998).

    Article  ADS  CAS  Google Scholar 

  6. Golub, T. R. et al. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 286, 531–537 (1999).

    Article  CAS  Google Scholar 

  7. Aruga, J. et al. A novel zinc finger protein, Zic, is involved in neurogenesis, especially in the cell lineage of cerebellar granule cells. J. Neurochem. 63, 1880–1890 (1994).

    Article  CAS  Google Scholar 

  8. Yokota, N. et al. Predominant expression of human Zic in cerebellar granule cell lineage and medulloblastoma. Cancer Res. 56, 377–383 (1996).

    CAS  Google Scholar 

  9. Rorke, L. B., Packer, R. J. & Biegel, J. A. Central nervous system atypical teratoid/rhabdoid tumors of infancy and childhood: definition of an entity. J. Neurosurg. 85, 56–65 (1996).

    Article  CAS  Google Scholar 

  10. Biegel, J. A. et al. Germ-line and acquired mutations of INI1 in atypical teratoid and rhabdoid tumors. Cancer Res. 59, 74–79 (1999).

    CAS  Google Scholar 

  11. Versteege, I. et al. Truncating mutations of hSNF5/INI1 in aggressive paediatric cancer. Nature 394, 203–206 (1998).

    Article  ADS  CAS  Google Scholar 

  12. Hahn, H. et al. Mutations of the human homolog of Drosophila patched in the nevoid basal cell carcinoma syndrome. Cell 85, 841–851 (1996).

    Article  CAS  Google Scholar 

  13. Johnson, R. L. et al. Human homolog of patched, a candidate gene for the basal cell nevus syndrome. Science 272, 1668–1671 (1996).

    Article  ADS  CAS  Google Scholar 

  14. Pietsch, T. et al. Medulloblastomas of the desmoplastic variant carry mutations of the human homologue of Drosophila patched. Cancer Res. 57, 2085–2088 (1997).

    CAS  Google Scholar 

  15. Raffel, C. et al. Sporadic medulloblastomas contain PTCH mutations. Cancer Res. 57, 842–845 (1997).

    CAS  Google Scholar 

  16. Xie, J. et al. Mutations of the PATCHED gene in several types of sporadic extracutaneous tumors. Cancer Res. 57, 2369–2372 (1997).

    CAS  Google Scholar 

  17. Wechsler-Reya, R. J. & Scott, M. P. Control of neuronal precursor proliferation in the cerebellum by Sonic Hedgehog. Neuron 22, 103–114 (1999).

    Article  CAS  Google Scholar 

  18. Wetmore, C., Eberhart, D. E. & Curran, T. The normal patched allele is expressed in medulloblastomas from mice with heterozygous germ-line mutation of patched. Cancer Res. 60, 2239–2246 (2000).

    CAS  Google Scholar 

  19. Giangaspero, F. et al. in World Health Organization Histological Classification of Tumours of the Nervous System (eds Kleihues, P. & Cavenee, W. K.) 129–137 (International Agency for Research on Cancer, Lyon, 2000).

    Google Scholar 

  20. Murone, M., Rosenthal, A. & deSauvage, F. J. Sonic hedgehog signaling by the patched-smoothened receptor complex. Curr. Biol. 28, 76–84 (1999).

    Article  Google Scholar 

  21. Hahn, H. et al. Patched target IGF2 is indispensable for the formation of medulloblastoma and rhabdomyosarcoma. J. Biol. Chem. 275, 28341–28344 (2000).

    Article  CAS  Google Scholar 

  22. Segal, R. A., Goumnerova, L. C., Kwon, Y. K., Stiles, C. D. & Pomeroy, S. L. Expression of the neurotrophin receptor TRKC is linked to a favorable outcome in medulloblastoma. Proc. Natl Acad. Sci. USA 91, 12867–12871 (1994).

    Article  ADS  CAS  Google Scholar 

  23. Kim, J. Y. H. et al. Activation of neurotrophin-3 receptor TRKC induces apoptosis in medulloblastomas. Cancer Res. 59, 711–719 (1999).

    CAS  Google Scholar 

  24. MacDonald, T. J. et al. Expression profiling of medulloblastoma: PDGFRA and the RAS/MAPK pathway as therapeutic targets for metastatic disease. Nature Genet. 29, 143–152 (2001).

    Article  CAS  Google Scholar 

  25. Tamayo, P. et al. Interpreting patterns of gene expression with self-organizing maps: Methods and application to hematopoietic differentiation. Proc. Natl Acad. Sci. USA 96, 2907–2912 (1999).

    Article  ADS  CAS  Google Scholar 

  26. Dasarathy, V. B. (ed). Nearest Neighbor (NN) Norms: NN Pattern Classification Techniques (IEEE Computer Society Press, Los Alamitos, California, 1991).

    Google Scholar 

  27. Slonim, D. K. et al. in Proc. 4th Annu. Int. Conf. Computational Mol. Biol. 263–272 (ACM Press, New York, 2000).

    Google Scholar 

  28. Mukherjee, S. et al. Support vector machine classification of microarray data. CBCL paper 182/AI memo 1676 (Massachusetts Institute of Technology, Cambridge, Massachusetts, 1999); also at http://www.ai.mit.edu/projects/cbcl/publications/ps/cancer.ps.

  29. Brown, M. P. S. et al. Knowledge-based analysis of microarray gene expression data by using support vector machines. Proc. Natl Acad. Sci. USA 97, 262–267 (2000).

    Article  ADS  CAS  Google Scholar 

  30. Califano, et al. in Proc. 8th Int. Conf. Intel. Syst. Mol. Biol. (eds Bourne, P. et al.) 75–85 (AAAI Press, Menlo Park, CA, 2000.

    Google Scholar 

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Acknowledgements

We thank members of the Whitehead/MIT Center for Genome Research, Program in Cancer Genomics, and J. Volpe for discussions and comments on the manuscript. This work was supported in part by Millennium Pharmaceuticals, Affymetrix and Bristol-Myers Squibb (E.S.L.); NIH grants (S.L.P. and T.C.); NIH-supported Mental Retardation Research Center (S.L.P.) and Cancer Center Support CORE (T.C.); the American Lebanese Syrian Associated Charities (ALSAC); and the Kyle Mullarkey Medulloblastoma Research Fund. We acknowledge the Cooperative Human Tissue Network and the Children's Oncology Group for contributing tumour samples.

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Correspondence to Scott L. Pomeroy or Todd R. Golub.

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We received research funding from Affymetrix (manufacturer of the microarrays used in this study) but do not have a financial (ownership) interest in the company.

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Pomeroy, S., Tamayo, P., Gaasenbeek, M. et al. Prediction of central nervous system embryonal tumour outcome based on gene expression. Nature 415, 436–442 (2002). https://doi.org/10.1038/415436a

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