Personalized diagnosis of medulloblastoma subtypes across patients and model systems

摘要: Molecular subtyping is instrumental towards selection of model systems for fundamental research in tumor pathogenesis, and clinical patient assessment. Medulloblastoma (MB) a highly heterogeneous, malignant brain that the most common cause cancer-related deaths children. Current MB classification schemes require large sample sizes, standard reference samples, subtype predictions. Such approaches are impractical settings with limited biopsies, unsuitable system predictions where samples unavailable. Our developed Medullo-Model To Subtype (MM2S) classifier stratifies single gene expression profiles without or replicates. pathway-centric approach facilitates including cell lines mouse models. MM2S demonstrates >96% accuracy patients well-characterized normal cerebellum, WNT, SHH subtypes, less-characterized Group 4 (86%) 3 (78.2%). also enables models into their human counterparts.