Abstract
To investigate the interaction between tumor and immune system during radiation therapy (RT) and predict the impact of different fractionation regimen on immune-mediated response. A model based on differential equations for each cell compartment was developed including the time-dependent rates of malignant tumor cells, lymphocytes, and apoptotic tumor cells. This mathematical framework describes how the recruited lymphocytes inhibit tumor progression. These rates and interaction terms were parameterized based on clinical observables. Blood samples during and after radiation treatment were collected from 17 patients with hepatocellular carcinoma receiving a median dose of 58 Gy in 15 fractions. The circulating T-lymphocytes (CTLs) levels in blood samples were used as a proxy for the activated immune effector population in our model. Radiation dose delivered to CTLs was estimated using a probability-based method. A set of virtual patients with different tumor radiosensitivity was generated using observed local failure rates. The model is able to describe the depletion and recovery of circulating lymphocytes in patients. The CTLs level dropped on average down to 74.6% with 3 fractions, which was better than 62.4% with 15 fractions. The increased average CTLs number with a smaller number of fractions indicated more immune surveillance with hypofractionation (Table 1). The number of apoptotic cells, which are key for the creation of an immune response in radiation therapy, was maximized at the second- and fifth-day during treatment with 3 and 15 fractions, respectively. Furthermore, it allows predicting local failure rate (Table 1). In order to inform clinical trial design, we have subsequently applied the model to study the effect of different fractionation regimen. The model predicts large changes in immune activation with varying fractionation regimen, while predicting stable local control rates. The established mathematical model is able to predict the decline and recovery of circulating CTL population in patients treated with RT. Our model can be applied to design immuno-RT combination trials.Abstract 8; Table 1Number of fractions35101520Average number of lymphocytes for 50 days (%)74.670.865.462.460.3Local failure (%)1.62.33.65.07.2 Open table in a new tab
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