Mathematical modelling of heterogeneity in tumour-immune cell interactions
<p>Tumours are highly heterogeneous entities. To understand cancer devel- opment from its initiation to metastases, research is needed to reveal the impact of heterogeneous populations of immune cells and tumour cells on outcomes. The presence of T cells of the adaptive immune response are cor...
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| Other Authors: | |
| Format: | Thesis |
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2018
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| _version_ | 1826305372952985600 |
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| author | Dritschel, H |
| author2 | Byrne, H |
| author_facet | Byrne, H Dritschel, H |
| author_sort | Dritschel, H |
| collection | OXFORD |
| description | <p>Tumours are highly heterogeneous entities. To understand cancer devel- opment from its initiation to metastases, research is needed to reveal the impact of heterogeneous populations of immune cells and tumour cells on outcomes. The presence of T cells of the adaptive immune response are correlated with favourable outcomes across a broad range of cancers. In this thesis we focus specifically on the T cell population and the impact of heterogeneity in both immune and tumour cells on model outcomes. To reveal the role played by the various aspects of heterogeneity in tumour- immune cell interactions, we develop a suite of mathematical models that explores in turn heterogeneity in: subpopulations of T cells; in different states of functionality of the same T cell (or states of exhaustion); and different subpopulations of tumour cells.</p> <p>The models are formulated as ordinary differential equations. Each model is examined through a combination of numerical and analytical techniques. All three models exhibit three generic responses to immune cells: tumour elimination, equilibrium and escape (the three Es of immunoediting) [52]. The first model focuses on the behaviour of a tumour interacting with two subpopulations of T cells: helper and cytotoxic T cells. The likelihood of tumour elimination, equilibrium and escape is found to vary with both the rates of infiltration of cytotoxic and helper T cells. The results indi- cate that combined immunotherapies, where both rates of infiltration are increased comparably, may elicit the most favourable response outcomes.</p> <p>The second model focuses on heterogeneity in the level of functionality of the cytotoxic T cells (exhaustion state). Tumour elimination, equilibrium and escape are found to depend on the rates of exhaustion of individual T cell functions, together with the ratio of the baseline T cell population (in the absence of a tumour) to the T cell population required to arrest tumour growth. The model suggests that the appropriate treatment is to block the ability of the tumour to dampen T cell proliferation.</p> <p>The final model focuses on heterogeneity in both tumour and T cell populations. The tumour population is divided into an immune-resistant and an immune-sensitive subpopulation, and the T cell population is divided into a cytotoxic and an exhausted subpopulation. The likelihood of tumour elimination, equilibrium and escape are found to vary with the rate of infiltration of cytotoxic T cells, together with the growth rate of the tumour, the rate at which immune-sensitive tumour cells produce immune-resistant tumour cells, the rate of conversion of cytotoxic T cells to exhausted T cells and the exhausted T cell kill rate. The results suggest that boosting the infiltration of cytotoxic T cells would be most effective and that the necessary increase depends on the growth rate of the tumour.</p> <p>This thesis uses a series of ODE models to comprehensively study how aspects of tumour-immune system heterogeneity impact tumour progres- sion. All three models show a close link between moderate immunosuppression and the presence of a dormant tumour state. The results suggest a number of potentially promising therapies depending on the degree of immunosuppression, tumour growth rate, and immune cell composition.</p> |
| first_indexed | 2024-03-07T06:31:54Z |
| format | Thesis |
| id | oxford-uuid:f644678e-1139-443e-a170-88c4c35c63aa |
| institution | University of Oxford |
| last_indexed | 2024-03-07T06:31:54Z |
| publishDate | 2018 |
| record_format | dspace |
| spelling | oxford-uuid:f644678e-1139-443e-a170-88c4c35c63aa2022-03-27T12:33:53ZMathematical modelling of heterogeneity in tumour-immune cell interactionsThesishttp://purl.org/coar/resource_type/c_db06uuid:f644678e-1139-443e-a170-88c4c35c63aaORA Deposit2018Dritschel, HByrne, HWaters, SRoller, A<p>Tumours are highly heterogeneous entities. To understand cancer devel- opment from its initiation to metastases, research is needed to reveal the impact of heterogeneous populations of immune cells and tumour cells on outcomes. The presence of T cells of the adaptive immune response are correlated with favourable outcomes across a broad range of cancers. In this thesis we focus specifically on the T cell population and the impact of heterogeneity in both immune and tumour cells on model outcomes. To reveal the role played by the various aspects of heterogeneity in tumour- immune cell interactions, we develop a suite of mathematical models that explores in turn heterogeneity in: subpopulations of T cells; in different states of functionality of the same T cell (or states of exhaustion); and different subpopulations of tumour cells.</p> <p>The models are formulated as ordinary differential equations. Each model is examined through a combination of numerical and analytical techniques. All three models exhibit three generic responses to immune cells: tumour elimination, equilibrium and escape (the three Es of immunoediting) [52]. The first model focuses on the behaviour of a tumour interacting with two subpopulations of T cells: helper and cytotoxic T cells. The likelihood of tumour elimination, equilibrium and escape is found to vary with both the rates of infiltration of cytotoxic and helper T cells. The results indi- cate that combined immunotherapies, where both rates of infiltration are increased comparably, may elicit the most favourable response outcomes.</p> <p>The second model focuses on heterogeneity in the level of functionality of the cytotoxic T cells (exhaustion state). Tumour elimination, equilibrium and escape are found to depend on the rates of exhaustion of individual T cell functions, together with the ratio of the baseline T cell population (in the absence of a tumour) to the T cell population required to arrest tumour growth. The model suggests that the appropriate treatment is to block the ability of the tumour to dampen T cell proliferation.</p> <p>The final model focuses on heterogeneity in both tumour and T cell populations. The tumour population is divided into an immune-resistant and an immune-sensitive subpopulation, and the T cell population is divided into a cytotoxic and an exhausted subpopulation. The likelihood of tumour elimination, equilibrium and escape are found to vary with the rate of infiltration of cytotoxic T cells, together with the growth rate of the tumour, the rate at which immune-sensitive tumour cells produce immune-resistant tumour cells, the rate of conversion of cytotoxic T cells to exhausted T cells and the exhausted T cell kill rate. The results suggest that boosting the infiltration of cytotoxic T cells would be most effective and that the necessary increase depends on the growth rate of the tumour.</p> <p>This thesis uses a series of ODE models to comprehensively study how aspects of tumour-immune system heterogeneity impact tumour progres- sion. All three models show a close link between moderate immunosuppression and the presence of a dormant tumour state. The results suggest a number of potentially promising therapies depending on the degree of immunosuppression, tumour growth rate, and immune cell composition.</p> |
| spellingShingle | Dritschel, H Mathematical modelling of heterogeneity in tumour-immune cell interactions |
| title | Mathematical modelling of heterogeneity in tumour-immune cell interactions |
| title_full | Mathematical modelling of heterogeneity in tumour-immune cell interactions |
| title_fullStr | Mathematical modelling of heterogeneity in tumour-immune cell interactions |
| title_full_unstemmed | Mathematical modelling of heterogeneity in tumour-immune cell interactions |
| title_short | Mathematical modelling of heterogeneity in tumour-immune cell interactions |
| title_sort | mathematical modelling of heterogeneity in tumour immune cell interactions |
| work_keys_str_mv | AT dritschelh mathematicalmodellingofheterogeneityintumourimmunecellinteractions |