Abstract
Diffuse Large B Cell Lymphoma (DLBCL) is the most common blood cancer in the western world. It is a very heterogenous disease, yet therapy is one-size-fits-all, to which 40% of patients have poor prognosis. To address this, a better understanding of mutations and their effect on signalling pathways is needed, that is, a Systems Biology approach.Computational models using Ordinary Differential Equations (ODEs) are well suited to make predictions about the effect of mutations on signalling pathways. The Nuclear Factor kappa B (NF-κB) pathway is central to white blood cell cancer. The Toll Like Receptor (TLR) pathway and B Cell Receptor (BCR) pathways both signal directly to canonical NF-κB; and are hotspots for mutations found in DLBCL. I combined three published models of these pathways to generate a tri-model, capable of predicting the effects of mutations on NF-κB signalling.
The NF-κB signalling pathway has two arms: canonical and non-canonical. Crosstalk between these arms was hypothesised to occur; in this thesis the model predicts the conditions that allow crosstalk to occur, and the protein mechanism (involving the inhibitory protein IκBδ). An environment with constant canonical signal desensitises the canonical pathway to canonical stimulation; and sensitises the canonical pathway to respond to non-canonical stimulation.
In the Toll-like Receptor (TLR) model, the self-activating mutant protein MYD88L265P was simulated, and resulted in a constant IKK signal, which activates canonical NF-κB. In the BCR model another Activated B Cell like DLBCL (ABC DLBCL) mutation, in the protein CARD11, was also simulated and gave a higher basal canonical output; but a poorer response to BCR stimulation. In order to see the effect of such mutations on NF-κB: the BCR, TLR, and NF-κB models were combined into a tri-model.
Simulations predict that MYD88L265P mutations could provide the constant basal canonical signal needed to generate crosstalk. The model also predicts that the level of basal non-canonical signal affects the degree of crosstalk. Fluorescence and flowcytometry experiments done in the Mitchell Lab provide validation. Flow-cytometry measurements validate the mathematical modelling results with single cell resolution.
This is significant in DLBCL because a driver mutation may provide the constant canonical signal; and the tumour microenvironment (TME) may provide the non-canonical signal (CD40L) leading to canonical activation. This canonical activation may result in an inflammatory TME which is linked to a worse prognosis for DLBCL patients. In disentangling how mutations and the microenvironment interact in DLBCL I discovered that healthy and DLBCL cells have unique signalling properties, which may unlock new therapeutic approaches to tackle this disease.
Date of Award | May 2024 |
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Original language | English |
Awarding Institution |
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Supervisor | Simon Mitchell (Supervisor) |