Department of Mathematical Sciences

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Browsing Department of Mathematical Sciences by Author "Amima, Innocenter Moraa"

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    Investigating tumour micro environment dynamics based on cytokine-mediated innate-adaptive immunity
    (Stellenbosch : Stellenbosch University, 2018-03) Amima, Innocenter Moraa; Mazandu, Gaston Kuzamunu; Stellenbosch University. Faculty of Science. Dept. of Mathematical Sciences.
    ENGLISH ABSTRACT : Cancer is a leading cause of death worldwide, yet much is still unknown about its mechanism of establishment, recurrence cycle and destruction. It is known that the successive alterations that occur in a set of specific genes in the cell can trigger carcinogenesis which is the process of transforming a normal cell into a cancer cell. This process is usually done in the following three steps: initiation, proliferation and progression. Cancer stem cells are regulated by complex interactions with the components of the tumour micro-environment (TME) through networks of cytokines and growth factors. Thus, understanding the role of cytokines can be crucial in the fight against cancer in the context of improving diagnostic, prognostic and therapeutic strategies. Several studies have investigated tumour-immune cell dynamics. However, some of these studies are mostly limited to cells that directly kill cancer cells, such as natural killer (NK) and cytotoxic T lymphocytes (CTLs), and they do not explicitly integrate cytokines in the cell dynamics. Furthermore, none of these studies has combined cellular-level mathematical models with molecular-level/signalling pathway analysis, to predict biological processes and enriched pathways associated in cancer disease. In this study, a new non-linear mathematical model integrating cytokines in the activation of innate and adaptive immunity was developed to predict the role of cytokines in tumour and immune cell dynamics. Our work complements the role Th2 and Th17 cells play in inhibiting the proliferation of M1 macrophages, CTLs, NK and Th1 cells. Numerical analysis of the model suggested that, lack of TGF-β inhibition effect resulted in tumour clearance, however, the immune cells grew without bound and exceeded the carrying capacity of immune cells. TGF-β is responsible for promoting tumour progression, tumour proliferation and limiting the effectiveness of type 1 immune response. In addition, we established the necessary conditions for tumour clearance by varying parameter values. For an immune (effector) cell to be activated from a resting state, its gene expression must be altered. We used datasets from The Cancer Genome Atlas (TCGA) and an expression level-based model to identify genes specific to cancer patients contributing to the regulation of cytokines in the context of the breast cancer disease. We predicted differentially expressed genes (DEGs) associated with breast cancer disease using a permutation-based significance analysis of micro-array (SAM) approach. Using a selected list of the DEGs, we determined significant pathways and enriched biological processes associated with breast cancer disease. Some of the identified significant biological pathways and processes, happened to be associated with cell differentiation or cell division and the predicted over-expressed genes in tumour samples may contribute to the proliferation of cancer. These genes, pathways and biological processes can be further assessed to check for their suitability as targets for breast cancer disease.