Systems level cancer disease target identification using tumor microenvironment dynamics

[摘要] ENGLISH ABSTRACT : Cancer is the second driving reasons for death around the world. It is an abnormalgrowth of cells which can migrate and recreate cellular microenvironment and can alsobe caused by successive alterations that occur in a set of specific genes in the cell. Asdangerous and deadly as cancer is, there is still a gap in our understanding of the mechanism of its establishment, its recurrence cycle and its elimination. It was observed thatcancer stem cells are regulated by the complex interaction component that makes up thetumor microenvironment (TME), through a network of growth factors and cytokines.Therefore, focusing on and understanding the role of these components and the levelof concentration of modulating factors present in the TME can play a significant role inbattling cancer. Many research projects have investigated the dynamics of these cytokines in the context of cancer in order to understand the evolution of cancer for improving diagnostic, prognostic and therapeutic strategies. However, these research aremostly restricted to cells that directly perform cytotoxic effect on cancer cells, such as thenatural killer (NK) and cytotoxic T lymphocytes (CTLs or CD8 + T) cells. They do notexplicitly integrate cytokine-mediated innate-adaptive immunity in the tumor dynamics. Moreover, none of those research has combined cellular-level mathematical modelswith protein-protein interaction network analysis, to predict essential proteins, biological processes and enriched pathways associated with cancer disease. Hence, in this study, we present a new mathematical model to investigate the dynamics between tumor cell and host immune system component (i.e., innate and adaptive immune cells and cytokines) in the TME . Results from the numerical solution of ourmodel indicate the capacity of a tumor to escape from immunologic surveillance due tolow cytotoxic immune cells (i.e. NK cells and CD8 + T cells) at the tumor site whilemore of these cytotoxic immune cells at the tumor site results in tumor regression. Ourmodel, therefore, supports strengthening the cytotoxic immune cells in the TME whichwe see as a significant way of contributing to tumor regression. Also, from the analysisof our model, cytokines such as IL-10, IL-23, TNF-α, TGB-β and IFN-γ has been shownto make contributions significantly to the dynamics of tumor development based on theobserved dynamics in the level of concentrations in the TME.Finally, switching of an immune (effector) cell from resting to active states, is triggered by some proteins working in a complex protein-protein interaction (PPI) network.We identified proteins which likely regulate immune cells and cytokines contributing tobreast cancer disease outcome and infer essential proteins based on Protein-proteinsinteraction network, as well as significant pathways and enriched biological processesassociated with breast cancer. These biological processes and pathways and essentialproteins identified can be further assessed to check for their suitability as targets for thebreast cancer disease for the improvement of effective therapeutic strategies.

[发布机构] Stellenbosch University