Journal
NEURO-ONCOLOGY
Volume 18, Issue 7, Pages 982-990Publisher
OXFORD UNIV PRESS INC
DOI: 10.1093/neuonc/now050
Keywords
adult medulloblastoma; histology; molecular subgroup; prognosis; survival
Categories
Funding
- National Science and Technology [2012BAI12B03]
- National Science Foundation of China [7112049]
- Capital Health Development and Research Special Projects of Beijing [2011-1015-01]
- American Cancer Society
- NIH/National Cancer Institute [R35CA197743]
- Department of Defense
- Children's Tumor Foundation
- Drug Discovery Initiative
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Background. Recent transcriptomic approaches have demonstrated that there are at least 4 distinct subgroups in medulloblastoma (MB); however, survival studies of molecular subgroups in adult MB have been inconclusive because of small sample sizes. The aim of this study is to investigate the molecular subgroups in adult MB and identify their clinical and prognostic implications in a large, single-institution cohort. Methods. We determined gene expression profiles for 13 primary adult MBs. Bioinformatics tools were used to establish distinct molecular subgroups based on the most informative genes in the dataset. Immunohistochemistry with subgroup-specific antibodies was then used for validation within an independent cohort of 201 formalin-fixed MB tumors, in conjunction with a systematic analysis of clinical and histological characteristics. Results. Three distinct molecular variants of adult MB were identified: the SHH, WNT, and group 4 subgroups. Validation of these subgroups in the 201-tumor cohort by immunohistochemistry identified significant differences in subgroup-specific demographics, histology, and metastatic status. The SHH subgroup accounted for the majority of the tumors (62%), followed by the group 4 subgroup (28%) and the WNT subgroup (10%). Group 4 tumors had significantly worse progression-free and overall survival compared with tumors of the other molecular subtypes. Conclusions. We have identified 3 subgroups of adult MB, characterized by distinct expression profiles, clinical features, pathological features, and prognosis. Clinical variables incorporated with molecular subgroup are more significantly informative for predicting adult patient outcome.
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