Abstract 680: Predicting the effect of radiotherapy on tumor growth inhibition and time to progression in head and neck cancer

We have previously developed a tumor model that replicates and predicts the effect that irradiation (IR) has on tumor growth inhibition in several preclinical studies. These studies utilize different IR doses and regimes as well as combination with therapeutic agents with disparate mechanisms of action. The primary outcome measure of these models was tumor size over time up to 1-2 months post-treatment.Encouraging results in the preclinical space led us to develop an enhanced strategy for modelling RT treatments using a tumor model that has enabled us to predict tumor shrinkage and longer term regrowth in human studies of squamous cell carcinoma head and neck tumors. To achieve this goal we analysed historical clinical data sourced from different clinical trials (NCT00094081; NCT00415194) in head and neck cancers which suggested that i) the initial rate sum of longest diameter (SLD) shrinkage depends on the SLD before treatment where the larger the initial SLD the faster the tumor shrinkage rate; ii) the magnitude of the tumor shrinkage can not only be explained by depletion of the peripheral growing layer of the tumor; and iii) a significant proportion of tumors remained suppressed for years following treatment. We used these findings to update and adapt the mathematical model to the clinical setting as well as to calibrate the model to describe the behavior of head and neck tumors treated with RT alone. We assumed that the mechanism of action of RT at the cell cycle level is unaltered between preclinical and clinical model, i.e. only the growing cell layer is directly depleted by radiation induced DNA damage. However, we hypothesized that the integrity of the growing layer plays a role protecting the necrotic core from degradation by biological or physical processes. Therefore, reducing the width of the growing layer width by depleting the number of viable cells indirectly contributes to overall tumor size shrinkage through erosion or leakage from the necrotic core. The other major challenge was to develop a mechanism to reflect the wide variation in time to tumor regrowth post-treatment. Literature evidence suggested that this regrowth can be explained by variation in cellular doubling times and we were able to calibrate our modeled cell population using a distribution of doubling times that enabled to the model to accurately predict regrowth profiles from literature. We were able to extent the mathematical model from a tool that explained and predicted