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  4. Modeling of Tumor and Immune Cell Interactions in Hepatocellular Carcinoma Patients Treated with Radiotherapy

Modeling of Tumor and Immune Cell Interactions in Hepatocellular Carcinoma Patients Treated with Radiotherapy

W Sung1*, C Grassberger1 , A McNamara1 , L Basler2 , S Ehrbar2 , S Tanadini-Lang2 , A Hammi1 , T Hong1 , H Paganetti1 , (1) Department of Radiation Oncology, Massachusetts General Hospital/Harvard Medical School, Boston, MA, (2) Department of Radiation Oncology, University Hospital Zurich, Zurich, Switzerland

Presentations

(Monday, 7/15/2019) 4:30 PM - 5:30 PM

Room: Exhibit Hall | Forum 3

Purpose: To establish a mathematical model for tumor-immune cell interactions using clinically extracted radiotherapy (RT) patient blood counts.

Methods: We describe tumor-immune cell interactions using ordinary differential equations adapted from a predator-prey model. The model has three compartments: clonogenic tumor cells, dying tumor cells, and circulating lymphocytes. Both clonogenic or apoptotic cells stimulate the immune response by antigens. We did extract interaction parameters by fitting the model to clinical data of circulating cytotoxic T-lymphocytes (CTLs) levels in blood samples of 17 hepatocellular carcinoma patients treated with hypofractionated proton therapy. In addition to serum data, the radiation dose distributions per field to individual hepatic segments is an important input parameter because CTLs are very radiosensitive. A blood flow model was applied to calculate the radiation dose to the circulating lymphocytes for each fraction. Within the model framework we created a set of 103 virtual patients with different tumor radiosensitivity with a random normal distribution. The standard deviation was set to result in 5% local failure at 2 years with 15 fractions, as observed in clinical data.

Results: The model is able to predict trajectories of circulating lymphocytes over the course of a fractionated treatment. We found that hypofractionation causes not only more stable CTL counts but also maximizes the number of apoptotic cells in a shorter time period. The local failure rate was predicted depending on the various fractionation schedules. From an immune response perspective, hypofractionated regimes lead to favorable tumor-immune dynamics improving tumor control and, reducing the local failure rate by 32%, down to 3.4%.

Conclusion: This study introduces the first mathematical model for tumor-immune interactions using clinically extracted radiotherapy patient data. Our model can be applied to design immuno-RT combination trials aiming at improving the immunogenicity of RT regimens.

Keywords

Not Applicable / None Entered.

Taxonomy

TH- Radiobiology(RBio)/Biology(Bio): RBio- LQ/TCP/NTCP/outcome modeling

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