Affiliations: Department of Neurosurgery, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China
Correspondence:
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Corresponding author: Changjun Cao, Department of Neurosurgery, Zhongnan Hospital of Wuhan University, 169 Donghu Road, Wuhan, 430071 Hubei, China. E-mail:caocj2030@163.com
Abstract: BACKGROUND: Medulloblastoma is one the most malignant paediatric brain tumours.
Molecular subgrouping these medulloblastomas will not only help identify
specific cohorts for certain treatment but also improve confidence in
prognostic prediction. OBJECTIVE: Currently, there is a consensus of the existences of four distinct subtypes
of medulloblastoma. We proposed a novel bioinformatics method, clustering of
self-organizing map, to determine the subgroups and their molecular
diversity. METHODS: Microarray expression profiles of 46 medulloblastoma samples were analysed
and five clusters with distinct demographics, clinical outcome and
transcriptional profiles were identified. RESULTS: The previously reported Wnt subgroup was identified as expected. Three
other novel subgroups were proposed for later investigation. CONCLUSIONS: Our findings underscore the value of SOM clustering for discovering the
medulloblastoma subgroups. When the suggested subdivision has been confirmed
in large cohorts, this method should serve as a part of routine
classification of clinical samples.
