Kimmel Gregory J, Locke Frederick L, Altrock Philipp M
Department of Integrated Mathematical Oncology, Research Institute, Tampa, FL, USA.
Department of Blood and Marrow Transplant and Cellular Immunotherapy, Research Institute, Tampa, FL, USA.
Proc Biol Sci. 2021 Mar 31;288(1947):20210229. doi: 10.1098/rspb.2021.0229. Epub 2021 Mar 24.
Chimeric antigen receptor (CAR) T cell therapy is a remarkably effective immunotherapy that relies on expansion of engineered CAR T cells, after lymphodepletion (LD) by chemotherapy. The quantitative laws underlying this expansion and subsequent tumour eradication remain unknown. We develop a mathematical model of T cell-tumour cell interactions and demonstrate that expansion can be explained by immune reconstitution dynamics after LD and competition among T cells. CAR T cells rapidly grow and engage tumour cells but experience an emerging growth rate disadvantage compared to normal T cells. Since tumour eradication is deterministically unstable in our model, we define cure as a stochastic event, which, even when likely, can occur at variable times. However, we show that variability in timing is largely determined by patient variability. While cure events impacted by these fluctuations occur early and are narrowly distributed, progression events occur late and are more widely distributed in time. We parameterized our model using population-level CAR T cell and tumour data over time and compare our predictions with progression-free survival rates. We find that therapy could be improved by optimizing the tumour-killing rate and the CAR T cells' ability to adapt, as quantified by their carrying capacity. Our tumour extinction model can be leveraged to examine why therapy works in some patients but not others, and to better understand the interplay of deterministic and stochastic effects on outcomes. For example, our model implies that LD before a second CAR T injection is necessary.
嵌合抗原受体(CAR)T细胞疗法是一种非常有效的免疫疗法,它依赖于经化疗进行淋巴细胞清除(LD)后工程化CAR T细胞的扩增。这种扩增以及随后肿瘤根除背后的定量规律仍然未知。我们建立了一个T细胞与肿瘤细胞相互作用的数学模型,并证明扩增可以通过LD后的免疫重建动力学以及T细胞之间的竞争来解释。CAR T细胞迅速生长并与肿瘤细胞结合,但与正常T细胞相比,其生长速率逐渐处于劣势。由于在我们的模型中肿瘤根除是确定性不稳定的,我们将治愈定义为一个随机事件,即使很有可能发生,也可能在不同时间出现。然而,我们表明时间上的变异性在很大程度上由患者的变异性决定。虽然受这些波动影响的治愈事件发生较早且分布较窄,但进展事件发生较晚且在时间上分布更广泛。我们使用随时间变化的群体水平CAR T细胞和肿瘤数据对模型进行参数化,并将我们的预测与无进展生存率进行比较。我们发现,通过优化肿瘤杀伤率以及CAR T细胞的适应能力(以其承载能力来量化),可以改善治疗效果。我们的肿瘤灭绝模型可用于研究为什么该疗法在一些患者中有效而在另一些患者中无效,并更好地理解确定性和随机效应在治疗结果中的相互作用。例如,我们的模型表明在第二次注射CAR T细胞之前进行淋巴细胞清除是必要的。