Understanding the Role of Translational Control in Humanized Mouse Models for Medulloblastoma
Background
Medulloblastoma (MB) is the most common malignant pediatric brain tumor. While 70-80% of patients survive more than 5 years, survivors have significant neurocognitive and neuro-endocrine disabilities. Several recent studies have identified 4 distinct molecular subgroups (WNT, SHH, Group 3 and Group 4). These subgroups differ in their mutational spectra, gene expression signatures and clinical features including outcome. While some children with Sonic Hedgehog (SHH) tumors survive >5 years, nearly all of the highest risk group (MYCN amplified, GLI2 amplified, p53 mutant) have metastatic spread at diagnosis, do not respond to standard of care treatments, and die of their disease. Thus, it is essential to model this high-risk medulloblastoma to understand the mechanism of tumor growth and relapse to therapies, so that the prognosis with high-risk medulloblastoma could be improved.
Project Goal
We hypothesize that MYCN cooperates with GLI2 and p53 loss to drive therapy-resistant medulloblastomas, and that modeling this highest-risk subtype of MB offers opportunities to test new pharmacological drugs. We propose to establish a model of MB that can be easily and rapidly manipulated, allowing us to understand how each mutation contributes to MB tumorigenesis, and how these mutations cooperate in tumor formation. We further hypothesize that MYCN and GLI2 disrupt the translational apparatus to drive transformation, and that inhibition of mTOR kinase, the mammalian target of rapamycin, represents a therapeutic strategy for this highly malignant SHH subtype medulloblastoma.
