Understanding tumour heterogeneity in glioblastoma
- π€ Speaker: Professor Simon TavarΓ©
- π Date & Time: Wednesday 20 January 2016, 14:00 - 15:00
- π Venue: MR4, Centre for Mathematical Sciences, Wilberforce Road, Cambridge
Abstract
We have undertaken an integrated genomic analysis of the evolution of Glioblastoma (GB) in individual patients across multiple spatial scales. Our data reveal early clonal diversification generating a genetically complex and highly evolved disease environment at clinical presentation. We propose that these fundamental patient-specific tumor evolutionary dynamics underlie clinical phenotypic heterogeneity and may have implications for the emergence of resistant disease. Using a Fluorescence-Guided Multiple Sampling technique we obtained samples from the tumor mass, the sub-ependymal zone and the non-fluorescent tumor margin. These data allow us to study intra-tumour heterogeneity, which is likely to be the key to understanding treatment failure. I will describe our approach, and discuss a statistical problem that arises in the analysis of dependent samples.
Series This talk is part of the Computational and Systems Biology series.
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Wednesday 20 January 2016, 14:00-15:00