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Clin Cancer Res. 2018 Mar 15;24(6):1355-1363. doi: 10.1158/1078-0432.CCR-17-2243. Epub 2018 Jan 19.

A Novel Method for Rapid Molecular Subgrouping of Medulloblastoma.

Author information

1
Developmental Tumor Biology Laboratory, Hospital Sant Joan de Déu, Fundació Sant Joan de Déu, Sant Joan de Déu, Barcelona, Spain.
2
Department of Pathology, Hospital Sant Joan de Déu, Barcelona, Spain.
3
Department of Haematology and Oncology, Hospital Sant Joan de Déu, Barcelona, Spain.
4
Fundació Clínic per a la Recerca Biomèdica, Barcelona, Spain.
5
Developmental & Stem Cell Biology Program, The Hospital for Sick Children, Toronto, Ontario, Canada.
6
The Arthur and Sonia Labatt Brain Tumor Research Centre, The Hospital for Sick Children, Toronto, Ontario, Canada.
7
The Pediatric Brain Tumor Centre, Department of Pediatric Oncology, Dana-Farber/Boston Children's Cancer and Blood Disorders Centre, Boston, Massachusetts.
8
Division of Experimental Medicine, McGill University, Montreal, Quebec, Canada.
9
James J. Peters VA Medical Center, Bronx, New York.
10
The Friedman Brain Institute and Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York.
11
Program in Neuroscience and Mental Health and Division of Neurology, The Hospital for Sick Children, Toronto, Ontario, Canada.
12
Division of Haematology/Oncology, The Hospital for Sick Children, Toronto, Ontario, Canada.
13
Division of Molecular Genetics, German Cancer Research Center (DKFZ), Heidelberg, Germany.
14
Division of Pediatric Neurooncology, German Cancer Research Centre (DKFZ), Heidelberg, Germany.
15
Hopp Children's Cancer Centre at the NCT Heidelberg, Heidelberg, Germany.
16
Department of Pediatric Oncology, Immunology, Haematology and Pulmonology, Heidelberg University Hospital, Heidelberg, Germany.
17
Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.
18
Institut d'Investigacions Biomèdiques August Pi i Sunyer, Barcelona, Spain.
19
Departamento de Fundamentos Clínicos, Universitat de Barcelona, Barcelona, Spain.
20
Developmental Tumor Biology Laboratory, Hospital Sant Joan de Déu, Fundació Sant Joan de Déu, Sant Joan de Déu, Barcelona, Spain. clavarino@fsjd.org.

Abstract

Purpose: The classification of medulloblastoma into WNT, SHH, group 3, and group 4 subgroups has become of critical importance for patient risk stratification and subgroup-tailored clinical trials. Here, we aimed to develop a simplified, clinically applicable classification approach that can be implemented in the majority of centers treating patients with medulloblastoma.Experimental Design: We analyzed 1,577 samples comprising previously published DNA methylation microarray data (913 medulloblastomas, 457 non-medulloblastoma tumors, 85 normal tissues), and 122 frozen and formalin-fixed paraffin-embedded medulloblastoma samples. Biomarkers were identified applying stringent selection filters and Linear Discriminant Analysis (LDA) method, and validated using DNA methylation microarray data, bisulfite pyrosequencing, and direct-bisulfite sequencing.Results: Using a LDA-based approach, we developed and validated a prediction method (EpiWNT-SHH classifier) based on six epigenetic biomarkers that allowed for rapid classification of medulloblastoma into the clinically relevant subgroups WNT, SHH, and non-WNT/non-SHH with excellent concordance (>99%) with current gold-standard methods, DNA methylation microarray, and gene signature profiling analysis. The EpiWNT-SHH classifier showed high prediction capacity using both frozen and formalin-fixed material, as well as diverse DNA methylation detection methods. Similarly, we developed a classifier specific for group 3 and group 4 tumors, based on five biomarkers (EpiG3-G4) with good discriminatory capacity, allowing for correct assignment of more than 92% of tumors. EpiWNT-SHH and EpiG3-G4 methylation profiles remained stable across tumor primary, metastasis, and relapse samples.Conclusions: The EpiWNT-SHH and EpiG3-G4 classifiers represent a new simplified approach for accurate, rapid, and cost-effective molecular classification of single medulloblastoma DNA samples, using clinically applicable DNA methylation detection methods. Clin Cancer Res; 24(6); 1355-63. ©2018 AACR.

PMID:
29351917
DOI:
10.1158/1078-0432.CCR-17-2243
[Indexed for MEDLINE]
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