Mathew, Ryan Koshy (2018) Reprogramming to Pluripotency Facilitates the Study of Genotype-Phenotype Relationships in Glioma. PhD thesis, University of Leeds.
Abstract
Dysregulated, stem cell-like self-renewal has been implicated in glioma treatment resistance and tumour recurrence. Drugs that eliminate tumour cells possessing this malignant characteristic are urgently needed. It remains, however, an experimental challenge to link heterogeneous glioma genotypes to cell phenotypes that can indicate positive and negative drug responses. To this end, we successfully derived patient-specific induced pluripotent stem cell (iPSC) models from both low- (LGG) and high-grade gliomas (HGG) and developed an initial drug discovery application, based on the characterisation of a HGG iPSC differentiation blockade. Brain tumour tissue, acquired at surgery, was reprogrammed. Derived iPSC models were characterised using pluripotency markers, tri-germinal layer differentiation, gene expression, karyology and deep whole genome sequencing (WGS, iPSC versus parental tumour). Glioma iPSC differentiation in 2- dimensional (adherent, optically clear 96-well imaging plates) and 3-dimensional (organoid) culture was carried out. Gene expression of neural induction and neuronal differentiation was analysed using mRNA-seq. Neural cancer stem cells from each of the three glioma iPSC lines were orthotopically implanted in vivo. Reprogrammed cells were confirmed as fully-reprogrammed/stable iPSCs, with preserved mutational variants (CNVs, total copy number) as compared to the parental tumours. Glioma iPSC maturation and quantification of TUJ1 staining indicated a ‘differentiation block’ in the HGG iPSC models. This phenotype was concordant in HGG iPSC-derived tumour organoids which displayed SOX2- positive neural rosettes. Consistently, mice developed xenograft tumours. Expression profiling during neuronal differentiation (from iPSC to neural stem cells to neurons) has revealed candidate genes that may be responsible for the phenotypic differences between HGG and control/LGG iPSC models. Our adherent, organoid and in vivo iPSC models may uncover genetic mutations and regulatory networks underlying glioma stem cell self-renewal and cellular differentiation capability and provide a basis for linking glioma genotypes and phenotypes in drug discovery applications. Here, we have successfully implemented the first stages towards this development (in a 96-well assay format). Ultimately, our patient-derived iPSC-based approach may enable personalised precision medicine strategies against glioma.
Metadata
Supervisors: | Wurdak, Heiko and Chumas, Paul and Short, Susan |
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Awarding institution: | University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) |
Depositing User: | Mr Ryan K Mathew |
Date Deposited: | 09 Jul 2019 08:58 |
Last Modified: | 09 Jul 2019 08:58 |
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