Personalized Diagnosis of Medulloblastoma Subtypes
Across Patients and Model Systems

Molecular subtyping is instrumental towards selection of model systems for fundamental research in tumour pathogenesis, and clinical patient assessment. Medulloblastoma (MB) is a highly heterogeneous, malignant brain tumour that is the most common cause of cancer-related deaths in children. Current MB classification schemes require large sample sizes, and standard reference samples, for subtype predictions. Such approaches are impractical in clinical settings with limited tumour biopsies, and unsuitable for model system predictions where standard reference samples are unavailable.

The absence of a versatile and personalized classification system hinders effective assessment of MB patients, and fundamental research into subtype-specific pathogenesis using model systems. Our developed Medullo-Model To Subtypes (MM2S) classifier stratifies single MB gene expression profiles without reference samples or replicates. Our pathway-centric approach facilitates subtype predictions of patient samples, and model systems including cell lines and mouse models. MM2S demonstrates >96% accuracy for patients of well-characterized normal cerebellum, WNT, or SHH subtypes, and the less-characterized Group4 (86%) and Group3 (78.2%). MM2S also enables classification of MB cell lines and mouse models into their human counterparts.

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Sample Data:

GSE36594:Gene expression for 56 Medulloblastoma mouse samples, normalized using expresso and BrainArray CDFs (see references for details). This dataset contains 32 replicates for the GTML mouse model.

GSE37418: Gene expression for 76 primary Medulloblastoma human samples, normalized using expresso and BrainArray CDFs (see references for details).