Medulloblastoma is a devastating disease of the cerebellum, and the most common solid pediatric malignancy of the central nervous system. Recently, transcriptome-wide profiling has dissected medulloblastoma from one single disease into four disparate molecular subgroups – namely WNT, SHH, Group3 and Group4. Distinct genomic, cytogenetic, mutational and clinical spectra associated with these subgroups highlight the pressing need for targeted therapies, of which encouraging preliminary results have been generated. While the promise of personalized medicine is within our reach, improved understanding of the molecular mechanisms driving pathogenesis is critical to this process.
The intent of my PhD thesis research was to characterize the molecular mechanisms contributing to medulloblastoma pathogenesis, and the clinical impact of these aberrations. Through a combinatorial use of genetic and epigenetic profiling, next-generation sequencing and bioinformatics analyses we have identified subsets of tumors with transcriptional signatures that influence their clinical properties. Furthermore, our results have shed light on the establishment of the normal cerebellar cytoarchitecture, identifying a physiological glutamate gradient with critical implications to both cerebellar development and disease.
This thesis stresses the importance of interrogating medulloblastoma in a subgroup-specific manner. Our findings demonstrate the utility of pursuing an integrated (copy number, mutational, transcriptional and epigenetic) molecular approach, to further our understanding of the pathobiology of medulloblastoma. Finally, we propose rationale therapeutic targets that may improve the treatment of aggressive variants of this disease.
Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:OTU.1807/43530 |
Date | 08 January 2014 |
Creators | Dubuc, Adrian |
Contributors | Taylor, Michael |
Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
Language | en_ca |
Detected Language | English |
Type | Thesis |
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