Bio-Physical Modeling of Immuno-Radiotherapy Combinations based on Patient Data

放射治疗与抗肿瘤免疫相关的免疫调节作用 最近在一系列迹象中成为调查的重点。同时， 临床试验中的辐射剂量、分割和时间选择一直存在很大的变数。一个 协调一致地确定刺激免疫所需的放射治疗方案 人类的系统是必要的。 动物实验证实了免疫疗法和免疫疗法之间存在协同作用。 辐射，但尚不清楚这些结果如何在剂量方面转化为患者， 测序、计时和分级。 这项建议的目标是开发一种新的生物物理方法来获得 放射治疗与免疫治疗的直接协同作用，即不使用参数 来自动物实验，来自临床患者和结果数据。该模型是 基于可观察的患者信息，如肿瘤负荷和循环中的淋巴细胞 计算，并将使用我们机构的临床试验数据进行验证。 在SA1中，我们将首先开发肿瘤免疫辐射模型，使我们能够预测 辐射的淋巴细胞耗尽效应和肿瘤与淋巴细胞的相互作用 肝细胞癌放射治疗的临床资料分析多数 重要的是，我们将能够模拟不同分馏方案对 循环淋巴细胞计数。在SA2中，我们将包括基于以下因素的免疫疗法的效果 并通过预测结果验证组合方法的有效性 创新的免疫-RT试验目前在我们机构进行。我们随后将 应用该模型研究最佳剂量和分割方案及其相关性 根据患者在治疗局部晚期和转移性肝癌中的特点。

The immuno-modulatory effects of radiotherapy (RT) associated with anti-tumor immunity have recently become a focus of investigations in a range of indications. Meanwhile, the radiation dose, fractionation and timing on clinical trials has been highly variable. A concerted approach to determine the radiation regimen needed to stimulate the immune system in humans is needed. Animal experiments have confirmed the existence a synergy between immunotherapy and radiation, but it is unclear how these results translate to patients in terms of dose, sequencing, timing and fractionation. The objective of this proposal is to develop a novel bio-physical approach to derive the synergism of radiotherapy with immunotherapy directly, i.e. without using parameters derived from animal experiments, from clinical patient and outcome data. The model is based on observable patient information, such as tumor load and circulating lymphocyte counts, and will be validated using clinical trial data from our institution. In SA1 we will first develop the tumor-immune-radiation model, enabling us to predict the lymphocyte depleting effect of radiation and the tumor-lymphocyte interaction, validated by clinical data of hepatocellular carcinoma (HCC) patients treated with radiotherapy. Most importantly, we will be able to simulate the effect of different fractionation regimen on the circulating lymphocyte count. In SA2 we will include the effect of immunotherapy based on HCC patient data and validate the combined approach by predicting the results of an innovative Immuno-RT trial currently conducted at our institution. We will subsequently apply the model to investigate optimal dose & fractionation regimen and their dependence upon patient characteristics in the treatment of locally advanced and metastatic HCC.