iMED-RISK: Improvement of risk stratification in infant medulloblastoma using integrated models of clinical, histopathological and molecular data

Medulloblastoma represents the most frequent malignant brain tumor in children, occurring in the cerebellum. At diagnosis, approximately 30% of patients show disseminated (metastatic) disease. Approximately 60% survival can be reached with multimodal treatment including operation, irradiation and chemotherapy. However, survivors suffer from significant side effects, including neurocognitive impairment, which is very severe in young age when the central nervous system is still developing. To reduce these side effects, the most recent treatment strategies try to avoid or at least postpone irradiation before the age of four. In children with desmoplastic/nodular histology, this was successful in contrast to other histologies; these patients mostly show an adverse prognosis. Biological and genetic studies have improved the knowledge on the underlying biology; infant medulloblastoma is now believed to represent biologically diverse diseases with activation of the SHH signaling pathway in one group with good prognosis versus tumors lacking such activation associated with worse clinical outcomes despite aggressive treatment strategies. To reduce side effects in the good prognostic group, the treatment intensity might be reduced, while more aggressive approaches may aim to achieve better outcomes in the tumors with adverse outcomes. As both biological characteristics and the histopathology were found to be related to clinical behavior of the disease, the World Health Organization’s classification of central nervous system tumors defined an integrated diagnosis for medulloblastoma since 2016, with the assignment of one of four histopathological types as well as one of four molecular classes to each tumor. However, most current treatment protocols still stratify treatment regimens according to clinicopathological features only. To be able to tailor an optimized, risk-adapted treatment for these young children with medulloblastoma, an improved stratification is needed. Addressing this urgent medical need, in this study, we will use genome-wide epigenetic as well as high-resolution chromosomal copy number information together with histopathological and clinical data to develop and validate an improved risk classifier for these children.