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Title: Mechanistic modelling to determine the limits of clinical and pre-clinical cancer immunotherapies
Author: Brown, Liam
ISNI:       0000 0004 7971 5737
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2018
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Immune-mediated clearance of a tumour is predicated on successful activation, migration and engagement of cytotoxic CD8+ T-cells. There are numerous factors that may impede these processes and that vary considerably between patients. In this thesis, I describe the use of mechanistic models to quantify and identify mechanisms that limit immune responses and immunotherapeutics against tumours. I describe the use of a model of T-cell activation in the lymph node to quantify the impact of patient and vaccine-specific variables on short peptide vaccination success. The model is used to simulate a virtual clinical trial, with predicted patient responses consistent with IMA901, a clinical trial of a short peptide vaccination in renal cell carcinoma patients. This leads to the conclusion that the limited efficacy of IMA901 could be due to the short peptide off-rates, and to suggestions that could have improved IMA901's results. I then describe an ODE model of T-cell trafficking through the bloodstream to quantify the maximum delivery rate of bioengineered T-cells to healthy tissue and tumours in different organs and species, and how these rates scale between species. Predicted absolute delivery rates of T-cells in mice are found to be much larger than equivalent rates in humans. This could explain why pre-clinical success of bioengineered T-cells in solid tumours has not translated to the clinic as it has for haematological cancers. Finally, this model is extended with PDEs to quantify the persistence of T-cells within organs and fit to lymphocyte localisation data in the rat. The advantages over the use of ODEs for describing T-cell localisation are discussed along with potential and planned future work. I close by discussing results in an immuno-oncological context, and the extent to which mouse, mathematical and mechanistic models are representative or useful in human medicine.
Supervisor: Gaffney, Eamonn ; Coles, Mark Sponsor: Engineering and Physical Sciences Research Council ; Clarendon Fund ; Hoffman-La Roche
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Cancer--Mathematical models ; Mathematical Biology ; Immunology--Mathematical models