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Title: Analysis of drug resistance and the role of the stem cell niche in leukaemia
Author: Bakker, E. Y.
ISNI:       0000 0004 6500 167X
Awarding Body: University of Salford
Current Institution: University of Salford
Date of Award: 2017
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Glucocorticoids and etoposide are used to treat acute lymphoblastic leukaemia (ALL) as they induce death in lymphoblasts through the glucocorticoid receptor (GR) and p53. However, glucocorticoid resistance, cell death mechanisms and the contribution of the bone marrow microenvironment to drug response/resistance all require investigation. Using microenvironment-mimicking conditioned media (CM), dexamethasone (a synthetic glucocorticoid) and etoposide to treat glucocorticoid-sensitive (C7-14) and glucocorticoid-resistant (C1-15) cells, pathways by which the microenvironment exerts its chemoprotective effect have been investigated. CM reduced caspase-3/8 activation, downregulated RIPK1 (necroptotic marker), and limited chemotherapy-induced BECN1 downregulation, suggesting protective effects of CM. Glucocorticoids upregulated BIRC3 (which ubiquitinates RIPK1), whilst CM altered GR phosphorylation. GR occupancy was observed on the RIPK1, BECN1 and BIRC3 promoters and changed depending on its phosphorylation. High-molecular weight proteins reacting with the RIPK1 antibody increased with CM, and reduced following AT406 BIRC3 inhibitor treatment suggesting they represent ubiquitinated RIPK1. These results suggest mechanisms by which CM promotes survival, as well as indicating novel glucocorticoid-regulated pathways. Complementing laboratory investigation is the construction of a Boolean model of the GR interaction network (GEB052, GR “interactome”) containing 52 nodes (proteins, inputs/outputs) connected by 241 interactions. In silico mutations and analyses have generated predictions that were subsequently validated on a genome-wide scale via comparison to microarray data. GEB052 demonstrated high prediction accuracy, consistently achieving a better prediction rate than a randomised model. Quantitative algorithmic analysis via microarray superimposition has also been performed, and lastly the model has been preliminarily validated as a clinical tool via superimposition of patient microarray data and comparing model predictions to clinical data. In summary, this thesis provides novel insight into the effects of the microenvironment, and identifies new glucocorticoid-regulated pathways. The GEB052 model of GR signalling represents the novel application of this modelling approach to GR research, and generates accurate predictions.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available