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Mathematical modelling of the effect of low-dose radiation on the G2/M transition and the survival fraction via the ATM/Chk2 pathway
- Author / Creator
- Contreras, Carlos
Radiation therapy is an important component of cancer treatment. It consists of applying ionizing radiation to kill cells by damaging their DNA and reducing their ability to reproduce and survive. It is reasonable to think that more radiation causes more damage and kills more cells. However, in the low-dose range (less than 1 Gy radiation dose), some cell lines experience counter-intuitive experimental behaviour: at about 0.3~Gy, more radiation less cells. This phenomenon, known as hyper radio-sensitivity and increased radioresistance (HRS/IRR), has intrigued radiobiologists for the last two decades. Below 0.3 Gy, cells are very sensitive to radiation; but above 0.3 Gy, they gain some resistance to radiation. Eventually, for higher dose, radiation damage becomes too much for the cell to bear. In the search for an effective radiation therapy that maximizes the damage on cancer cells and minimizes the damage on normal cells, the understanding of this phenomenon may improve the efficiency of radiation therapy.
One hypothesis that explains the HRS/IRR phenomenon is that activation of the G2 checkpoint, a mechanism that controls cell cycle progression to mitosis, occurs around the 0.3~Gy threshold. The G2 checkpoint activation provides extra time to repair DNA damage instead of carrying it to mitosis and compromising the integrity of daughter cells. However, testing this hypothesis experimentally is challenging. Mathematical modelling can provide insight into the validity of this hypothesis and the improve understanding of the underlying mechanisms governing HRS/IRR.
The effect of radiation on cells is commonly assessed through the cell survival fraction, which measures the ability of a culture of cells to reproduce several days after ionizing radiation application. The Linear Quadratic (LQ) model is the simplest model to describe survival fraction data. However, the LQ model fails to describe HRS/IRR data, which is better described by the Induced Repair (IR) model, a variation of the LQ model. Although these are widely acceptable models, they fail to explain why HRS/IRR occurs. In recent years, attempts to explain HRS/IRR with survival fraction models have included more details of the molecular and cellular networks governing the cell dynamics. However, the question as to what is the involvement of the G2 checkpoint on the HRS/IRR phenomenon remains open.
In this thesis, I study the effect of radiation on the cell cycle and the survival fraction. For this purpose, I model the problem at two levels, the effect of radiation on the cell cycle at the individual level, and the effect of radiation on cells at the population level. At the individual level, I model the kinetic pathway triggered by radiation, namely, the activation of ATM and Chk2 proteins by radiation-induced Double Strand Breaks (DSBs); and the cell cycle, characterized by proteins MPF, Wee1, and Cdc25 and the G2-phase. The model for the cell cycle and radiation pathway consists of a system of differential equations, which involve Law of Mass Action and Goldbeter-Koshland kinetics. At the population level, I model lethal lesions for the cells based on the count of DSBs remaining during mitosis (obtained at the individual level), a distribution of a cell population over the cell cycle, and Poisson's Law for lethal events.
I use this mathematical modelling to study the role of the G2-phase in the survival fraction. I establish numerical and theoretical arguments to support the~hypothesis that the G2/M transition plays a major role in the HRS/IRR phenomenon. Moreover, I provide a biological and mechanistic interpretation of the parameters in the IR model. The methodology presented in this thesis provides meaningful insights into the understanding of the effect of radiation on the G2/M transition and can be used to study the role that other radiation-induced pathways play in the cell cycle dynamics.
- Graduation date
- Spring 2020
- Type of Item
- Doctor of Philosophy
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