Electrical and Electronic Engineering - Theses

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End date: 2017 × Type: PhD thesis × Subject: cancer × Subject: mathematical modelling ×

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    Signalling and crosstalk in cytokine pathways: mathematical modelling and quantitative analysis
    Khatibi, Shabnam ( 2016)
    Cancer is a leading cause of death all over the world. Focusing at the intracellular level, there are several cytokine signalling networks involved in inflammation and tumorigenesis. These pathways regulate the cell biological responses to the environment, both directly and via crosstalk. Recently, there have been several reports which have confirmed the strong relationship between inflammatory diseases and tumor development. Two cytokines, in particular, have significant roles in wound healing, inflammation and cancer Transforming growth factor β (TGF-β) and Interleukin-6 (IL-6). Cytokine signalling pathways are an interconnected complex system of biochemical reactions which can be represented by kinetic equations. These signalling pathways can share proteins and genes which make the intracellular signalling networks extremely complex. Systems biology and mathematical modelling are new approaches for the study of complex systems such as intracellular signalling networks. The focus of this research is to model mathematically new descriptions of the TGF-β and IL-6 pathways based on new logistics and then integrate them into a single, robust, self-regulated model which can be used to investigate tumor development in the stomach and colon. At each level, experimental data sets were used iteratively in order to both parameterize and examine the models (e.g. the model and experimental data of Zi et al. (2011) and further model simulations have been used in Chapter 4 to parameterize our TGF-β model.). Different approaches in Systems biology and their applications in cell signalling research are studied. TGF-β and IL-6 signalling pathways and their components are reviewed next. The previous mathematical models of TGF-β and IL-6 signalling are briefly discussed. Additionally, the role of individual signalling in cancer progression and inflammation is studied. We developed a mathematical model which captures the details of TGF-β signalling. The detailed model consists of over 40 differential equations and highlights the necessity for the reduction and simplification methods. The TGF-β signalling model is simplified and reduced via analytical reduction methods to 6 differential equations and is further validated with experiment. For the first time an explicit negative feedback loop has been included in the model. Another contribution of the TGF-β model is that the inherent time-delays in signalling networks are incorporated in detail. In the final chapter different input patterns are studied for TGF-β signalling. Our model of TGF-β signalling indicates that the positive feedback loop is one mechanism by which stability could be achieved. The thesis reports for the first time the coupling of the positive and negative feedback loops for TGF-β signal transduction. Furthermore, our TGF-β signalling model proposes predictions for the responses of cancer cells to TGF-β stimulation, which suggest new experimental protocols for future work. We also developed a mathematical model that describes the IL-6 signalling system thoroughly. The large number of equations involved in this model highlights the need for simplification. Similar to TGF-β signalling model, IL-6 signalling model is simplified and reduced using mathematical methods. In order to develop a realistic model specific kinetics are used for the different reactions. Time-delays are incorporated in the IL-6 transduction mathematical model for the first time. After being validated with different experimental data, the reduced IL-6 signalling model predicts the behaviour of cancer cells in response to IL-6 stimulation. Different pulsatile ligand inputs are studied using IL-6 model and new hypotheses for the TGF-β and IL-6 signalling crosstalk are raised. Our initial hypothesis that IL-6 signalling regulates TGF-β signalling via SMAD7, is examined using our integrated IL-6:TGF-β model. The simulations produced by the integrated model confirm the importance of the negative feedback loop of TGF-β signalling (SMAD7) via IL-6 downstream signalling, previously suggested by Jenkins et al. (2005). Various kinetic models are examined for the link between the two signalling pathways and several predictions are proposed for the pulsatile inputs and different stimulation patterns. The results of the integrated model are compared with the individual TGF-β and IL-6 models. IL-6-induced activation of SMAD7 leads to suppression of TGF-β signalling and causes double peak responses of PSMAD2 in the short-term, however, the long-term responses of the cells to TGF-β stimulation remain unchanged by IL-6 signalling. The integrated model is also validated experimentally. Conclusively, we found that the regulation of TGF-β signal transduction by IL-6 signalling occurs within the first 300 minutes after stimulation, i.e. within the transient phase of the response. This thesis includes both theoretical and experimental work, performed by the applicant. Theoretical part of the thesis consists of designing and developing models, analytical analysis of the models and conducting numerical simulations with the numerical simulation of the models. In the experimental part, various experimental protocols were developed and examined in order to parameterize, test and validate the proposed models.