Gene expression data from ependymal tumor samples

Ependymal tumors across age groups have been classified and graded solely by histopathology. It is, however, commonly accepted that this classification scheme has limited clinical utility based on its lack of reproducibility in predicting patient outcome. We aimed at establishing a reliable molecular classification using DNA methylation fingerprints and gene expression data of the tumors on a large cohort of 500 tumors. Nine robust molecular subgroups, three in each anatomic compartment of the central nervous system (CNS), were identified. Total RNA from 209 ependymal tumor samples were hybridised to the Affymetrix HG U133 Plus 2.0 microarrays.