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

Scott L. Pomeroy (), Pablo Tamayo, Michelle Gaasenbeek, Lisa M. Sturla, Michael Angelo, Margaret E. McLaughlin, John Y. H. Kim, Liliana C. Goumnerova, Peter M. Black, Ching Lau, Jeffrey C. Allen, David Zagzag, James M. Olson, Tom Curran, Cynthia Wetmore, Jaclyn A. Biegel, Tomaso Poggio, Shayan Mukherjee, Ryan Rifkin, Andrea Califano, Gustavo Stolovitzky, David N. Louis, Jill P. Mesirov, Eric S. Lander and Todd R. Golub ()
Additional contact information
Scott L. Pomeroy: Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA
Pablo Tamayo: AI Lab, Massachusetts Institute of Technology
Michelle Gaasenbeek: AI Lab, Massachusetts Institute of Technology
Lisa M. Sturla: Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA
Michael Angelo: AI Lab, Massachusetts Institute of Technology
Margaret E. McLaughlin: Massachusetts General Hospital, Harvard Medical School
John Y. H. Kim: Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA
Liliana C. Goumnerova: Massachusetts General Hospital, Harvard Medical School
Peter M. Black: Massachusetts General Hospital, Harvard Medical School
Ching Lau: Baylor College of Medicine
Jeffrey C. Allen: Beth Israel Medical Center
David Zagzag: New York University School of Medicine
James M. Olson: Fred Hutchinson Cancer Research Center
Tom Curran: St Jude Children's Research Hospital
Cynthia Wetmore: St Jude Children's Research Hospital
Jaclyn A. Biegel: The Children's Hospital of Philadelphia, University of Pennsylvania School of Medicine
Tomaso Poggio: McGovern Institute, Center for Biological and Computational Learning, AI Lab, Massachusetts Institute of Technology
Shayan Mukherjee: McGovern Institute, Center for Biological and Computational Learning, AI Lab, Massachusetts Institute of Technology
Ryan Rifkin: McGovern Institute, Center for Biological and Computational Learning, AI Lab, Massachusetts Institute of Technology
Andrea Califano: IBM Watson Research Center
Gustavo Stolovitzky: IBM Watson Research Center
David N. Louis: Massachusetts General Hospital, Harvard Medical School
Jill P. Mesirov: AI Lab, Massachusetts Institute of Technology
Eric S. Lander: AI Lab, Massachusetts Institute of Technology
Todd R. Golub: Children's Hospital, Massachusetts General Hospital, Harvard Medical School

Nature, 2002, vol. 415, issue 6870, 436-442

Abstract: 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.

Date: 2002
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DOI: 10.1038/415436a

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