Ependymomas are tumors of the central nervous system that can occur in patients of all ages. Guidelines from the World Health Organization (WHO) for the grading of ependymomas consider patient age, tumor resection range, tumor location and histopathological grade. However, recent studies have suggested that a greater focus on both tumor location and patient age in terms of transcriptomic, genetic, and epigenetic analyses may provide a more accurate assessment of clinical prognosis than the grading system proposed by WHO guidelines. The current study identified the differences and similarities in ependymoma characteristics using three different molecular analyses and methylation arrays. Primary intracranial ependymoma tissues were obtained from 13 Korean patients (9 adults and 4 children), after which whole-exome sequencing (WES), ion-proton comprehensive cancer panel (CCP) analysis, RNA sequencing, and Infinium HumanMethylation450 BeadChip array analysis was performed. Somatic mutations, copy number variations, and fusion genes were identified. It was observed that the methylation status and differentially expressed genes were significantly different according to tumor location and patient age. Several novel gene fusions and somatic mutations were identified, including a yes-associated protein 1 fusion mutation in a child with a good prognosis. Moreover, the methylation microarray revealed that genes associated with neurogenesis and neuron differentiation were hypermethylated in the adult group, whereas genes in the homeobox gene family were hypermethylated in the supratentorial (ST) group. The results confirmed the existence of significantly differentially expressed tumor-specific genes based on tumor location and patient age. These results provided valuable insight into the epigenetic and genetic profiles of intracranial ependymomas and uncovered potential strategies for the identification of location- and age-based ependymoma-related prognostic factors.
Keywords: DNA methylation; classification; ependymoma; molecular analysis; next generation sequencing.
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