Risk assessment in paediatric glioma-Time to move on from the binary classification.

BACKGROUND: Paediatric glioma encompasses a wide range of entities with highly variable prognoses. Gliomas are grouped by histopathological features into high- and low-grade glioma but this classification until recently has not taken into account many emerging risk factors in this disease. A comprehensive risk classification has not been published for paediatric glioma despite many risk factors being established in this disease. METHODS: A comprehensive literature review was carried out identifying risk factors for paediatric low-grade and high-grade glioma. RESULTS: The most consistently described risk factors in high-grade glioma included midline location and extent of surgical resection. For patients with progressive unresectable low-grade glioma, age under 1, neurofibromatosis type I status and location were the most consistently prognostic. Molecular classification shows promise in accurately reassigning diagnosis for some gliomas. CONCLUSION: Risk profiling in paediatric glioma will require a focused multinational effort but will result in a more accurate and nuanced assessment of prognosis.

The potential for epigenetic analysis of paediatric CNS tumours to improve diagnosis, treatment and prognosis.

Tumours of central nervous system (CNS) origin are the second most prevalent group of cancers in children, yet account for the majority of childhood cancer-related deaths. Such tumours show diverse location, cell type of origin, disease course and long-term outcome, both across and within tumour types, making treatment problematic and contributing to the relatively modest progress in reducing mortality over recent decades. As technological advances begin to reveal the genetic landscape of all cancers, it is becoming increasingly clear that genetic disruption represents only one 'layer' of molecular disruption associated with disease aetiology. Obtaining a full understanding of tumour behaviour requires an understanding of the cellular and molecular pathways disrupted during tumourigenesis, particularly in relation to gene expression. The utility of such an approach has allowed stratification of cancers such as medulloblastoma into subgroups based on molecular features, with potential to refine risk prediction. Given that epigenetic disruption is a universal feature of all human cancers, it is logical to speculate that interrogating epigenetic marks may help to further define the molecular profile, and therefore the clinical trajectory, of tumours. An integrated approach to build a molecular 'signature' of individual tumours that incorporates traditional morphological and demographic information, genetic and transcriptome analysis, in addition to epigenomics (DNA methylation and non-coding RNA analysis), offers tremendous promise to (i) inform treatment approach, (ii) facilitate accurate early identification (preferably at diagnosis) of variable risk groups (both good and poor prognosis groups), and (iii) track disease progression in childhood CNS tumours.