Speaker
Description
More than 50% of patients with cancer receive radiotherapy to kill tumor cells. Several mathematical models predicting post-irradiation cell survival are used clinically to plan treatment; however, they often neglect the tumor microenvironment, which can modulate radiotherapy response. A key driver of radioresistance in solid tumors is hypoxia.
In this project, we focus on the effect of initial cell density on hypoxia-induced radioresistance. Our experiments are designed to quantify how reduced oxygen levels before and after irradiation and initial cell density affect survival and post-treatment dynamics. We show that the hypoxia-induced radioresistance is stronger for high initial cell densities. We also present a biologically motivated compartmental model to analyze the dynamic transitions of cells between distinct states (e.g., repaired, senescent, and unrepaired subpopulations) under different conditions. By fitting time-course data, the model estimates key transition rates and incorporates oxygen dependence, enabling accurate simulation of cellular responses under hypoxic conditions. This work provides insight into the oxygen-dependent responses of cancer cells to radiation, informing more effective and context-aware therapeutic strategies.
