A tumor-immune interaction model for hepatocellular carcinoma based on measured lymphocyte counts in patients undergoing radiotherapy. (October 2020)

• Record Type: Journal Article
• Authors: Sung, Wonmo; Grassberger, Clemens; McNamara, Aimee Louise; Basler, Lucas; Ehrbar, Stefanie; Tanadini-Lang, Stephanie; Hong, Theodore S.; Paganetti, Harald
• Is Part Of: Radiotherapy and oncology. Volume 151(2020)
• Page Start: 73
• Page End: 81
• Publication Date: 2020-10
• Subjects: Lymphocyte depletion -- Immune checkpoint inhibitor -- Mathematical modeling -- Radiation therapy -- Clinical trials; Oncology -- Periodicals; Radiotherapy -- Periodicals; Tumors -- Periodicals; Medical Oncology -- Periodicals; Neoplasms -- radiotherapy -- Periodicals; Radiotherapy -- Periodicals; Radiothérapie -- Périodiques; Cancérologie -- Périodiques; Tumeurs -- Périodiques; Electronic journals; 616.9940642
• DOI: 10.1016/j.radonc.2020.07.025
• Languages: English
• ISSNs: 0167-8140

Abstract

Highlights: A model of lymphocyte depletion was developed based on radiotherapy patient data. The model predicts the ability of short fractionation to mitigate lymphopenia. The model predicts the effect of fractionation, dose and timing on lymphocyte counts. The model aids in the design of clinical trials to improve the immunogenicity of RT. Abstract: Purpose: The impact of radiation therapy on the immune system has recently gained attention particularly when delivered in combination with immunotherapy. However, it is unclear how different treatment fractionation regimens influence the interaction between the immune system and radiation. The goal of this work was to develop a mathematical model that quantifies both the immune stimulating as well as the immunosuppressive effects of radiotherapy and simulates the effects of different fractionation regimens based on patient data. Methods and materials: The framework describes the temporal evolution of tumor cells, lymphocytes, and inactivated dying tumor cells releasing antigens during radiation therapy, specifically modeling how recruited lymphocytes inhibit tumor progression. The parameters of the model were partly taken from the literature and in part extracted from blood samples (circulating lymphocytes: CLs) collected from hepatocellular carcinoma patients undergoing radiotherapy and their outcomes. The dose volume histograms to circulating lymphocytes were calculated with a probability-based model. Results: Based on the fitted parameters, the model enabled a study into the depletion and recovery of CLs in patients as a function of fractionation regimen. Our results quantify the ability of short fractionation regimens to lead to shorter periods of lymphocyte depletion and predict faster recovery after the end of treatment. The model shows that treatment breaks between fractions can prolong the period of lymphocyte depletion and should be avoided. Conclusions: This study introduces a mathematical model for tumor-immune interactions using clinically extracted radiotherapy patient data, which can be applied to design trials aimed at minimizing lymphocyte depleting effects in radiation therapy.