Cytogenetic prognostication within medulloblastoma subgroups

David J.H. Shih, Paul A. Northcott, Marc Remke, Andrey Korshunov, Vijay Ramaswamy, Marcel Kool, Betty Luu, Yuan Yao, Xin Wang, Adrian M. Dubuc, Livia Garzia, John Peacock, Stephen C. Mack, Xiaochong Wu, Adi Rolider, A. Sorana Morrissy, Florence M.G. Cavalli, David T.W. Jones, Karel Zitterbart, Claudia C. FariaUlrich Schüller, Leos Kren, Toshihiro Kumabe, Teiji Tominaga, Young Shin Ra, Miklós Garami, Peter Hauser, Jennifer A. Chan, Shenandoah Robinson, László Bognár, Almos Klekner, Ali G. Saad, Linda M. Liau, Steffen Albrecht, Adam Fontebasso, Giuseppe Cinalli, Pasqualino De Antonellis, Massimo Zollo, Michael K. Cooper, Reid C. Thompson, Simon Bailey, Janet C. Lindsey, Concezio Di Rocco, Luca Massimi, Erna M.C. Michiels, Stephen W. Scherer, Joanna J. Phillips, Nalin Gupta, Xing Fan, Karin M. Muraszko, Rajeev Vibhakar, Charles G. Eberhart, Maryam Fouladi, Boleslaw Lach, Shin Jung, Robert J. Wechsler-Reya, Michelle Fèvre-Montange, Anne Jouvet, Nada Jabado, Ian F. Pollack, William A. Weiss, Ji Yeoun Lee, Byung Kyu Cho, Seung Ki Kim, Kyu Chang Wang, Jeffrey R. Leonard, Joshua B. Rubin, Carmen De Torres, Cinzia Lavarino, Jaume Mora, Yoon Jae Cho, Uri Tabori, James M. Olson, Amar Gajjar, Roger J. Packer, Stefan Rutkowski, Scott L. Pomeroy, Pim J. French, Nanne K. Kloosterhof, Johan M. Kros, Erwin G. Van Meir, Steven C. Clifford, Franck Bourdeaut, Olivier Delattre, François F. Doz, Cynthia E. Hawkins, David Malkin, Wieslawa A. Grajkowska, Marta Perek-Polnik, Eric Bouffet, James T. Rutka, Stefan M. Pfister, Michael D. Taylor

Research output: Contribution to journalArticlepeer-review

236 Citations (Scopus)


Purpose: Medulloblastoma comprises four distinct molecular subgroups: WNT, SHH, Group 3, and Group 4. Current medulloblastoma protocols stratify patients based on clinical features: patient age, metastatic stage, extent of resection, and histologic variant. Stark prognostic and genetic differences among the four subgroups suggest that subgroup-specific molecular biomarkers could improve patient prognostication. Patients and Methods: Molecular biomarkers were identified from a discovery set of 673 medulloblastomas from 43 cities around the world. Combined risk stratification models were designed based on clinical and cytogenetic biomarkers identified by multivariable Cox proportional hazards analyses. Identified biomarkers were tested using fluorescent in situ hybridization (FISH) on a nonoverlapping medulloblastoma tissue microarray (n = 453), with subsequent validation of the risk stratification models. Results: Subgroup information improves the predictive accuracy of a multivariable survival model compared with clinical biomarkers alone. Most previously published cytogenetic biomarkers are only prognostic within a single medulloblastoma subgroup. Profiling six FISH biomarkers (GLI2, MYC, chromosome 11 [chr11], chr14, 17p, and 17q) on formalin-fixed paraffin-embedded tissues, we can reliably and reproducibly identify very low-risk and very high-risk patients within SHH, Group 3, and Group 4 medulloblastomas. Conclusion: Combining subgroup and cytogenetic biomarkers with established clinical biomarkers substantially improves patient prognostication, even in the context of heterogeneous clinical therapies. The prognostic significance of most molecular biomarkers is restricted to a specific subgroup. We have identified a small panel of cytogenetic biomarkers that reliably identifies very high-risk and very low-risk groups of patients, making it an excellent tool for selecting patients for therapy intensification and therapy de-escalation in future clinical trials.

Original languageEnglish
Pages (from-to)886-896
Number of pages11
JournalJournal of Clinical Oncology
Issue number9
Publication statusPublished - 20 Mar 2014
Externally publishedYes


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