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Cytogenetic Prognostication Within Medulloblastoma Subgroups

Lookup NU author(s): Professor Simon Bailey, Dr Janet Lindsey, Professor Steven Clifford

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Abstract

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.


Publication metadata

Author(s): Shih DJH, Northcott PA, Remke M, Korshunov A, Ramaswamy V, Kool M, Luu B, Yao Y, Wang X, Dubuc AM, Garzia L, Peacock J, Mack SC, Wu XC, Rolider A, Morrissy AS, Cavalli FMG, Jones DTW, Zitterbart K, Faria CC, Schuller U, Kren L, Kumabe T, Tominaga T, Ra YS, Garami M, Hauser P, Chan JA, Robinson S, Bognar L, Klekner A, Saad AG, Liau LM, Albrecht S, Fontebasso A, Cinalli G, De Antonellis P, Zollo M, Cooper MK, Thompson RC, Bailey S, Lindsey JC, Di Rocco C, Massimi L, Michiels EMC, Scherer SW, Phillips JJ, Gupta N, Fan X, Muraszko KM, Vibhakar R, Eberhart CG, Fouladi M, Lach B, Jung S, Wechsler-Reya RJ, Fevre-Montange M, Jouvet A, Jabado N, Pollack IF, Weiss WA, Lee JY, Cho BK, Kim SK, Wang KC, Leonard JR, Rubin JB, de Torres C, Lavarino C, Mora J, Cho YJ, Tabori U, Olson JM, Gajjar A, Packer RJ, Rutkowski S, Pomeroy SL, French PJ, Kloosterhof NK, Kros JM, Van Meir EG, Clifford SC, Bourdeaut F, Delattre O, Doz FF, Hawkins CE, Malkin D, Grajkowska WA, Perek-Polnik M, Bouffet E, Rutka JT, Pfister SM, Taylor MD

Publication type: Article

Publication status: Published

Journal: Journal of Clinical Onocology

Year: 2014

Volume: 32

Issue: 9

Pages: 886-896

Print publication date: 20/03/2014

ISSN (print): 0732-183X

ISSN (electronic): 1527-7755

Publisher: American Society of Clinical Oncology

URL: http://dx.doi.org/10.1200/JCO.2013.50.9539

DOI: 10.1200/JCO.2013.50.9539


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Funding

Funder referenceFunder name
AT1-112286Canadian Institutes of Health Research
CA159859NCI NIH HHS
P30 HD018655NICHD NIH HHS
R01 CA155360NCI NIH HHS
R01 CA159859NCI NIH HHS
R01 CA163737NCI NIH HHS
R01 CA109467NCI NIH HHS
R01 CA148621NCI NIH HHS

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