Faculty of pharmacy, Université de Montréal, Montreal, Quebec H3C 3J7, Canada.
Syneos Health, Clinical Pharmacology, Quebec, Quebec G1P 0A2, Canada.
Chaos. 2021 Feb;31(2):023124. doi: 10.1063/5.0022238.
Quantitative systems pharmacology (QSP) proved to be a powerful tool to elucidate the underlying pathophysiological complexity that is intensified by the biological variability and overlapped by the level of sophistication of drug dosing regimens. Therapies combining immunotherapy with more traditional therapeutic approaches, including chemotherapy and radiation, are increasingly being used. These combinations are purposed to amplify the immune response against the tumor cells and modulate the suppressive tumor microenvironment (TME). In order to get the best performance from these combinatorial approaches and derive rational regimen strategies, a better understanding of the interaction of the tumor with the host immune system is needed. The objective of the current work is to provide new insights into the dynamics of immune-mediated TME and immune-oncology treatment. As a case study, we will use a recent QSP model by Kosinsky et al. [J. Immunother. Cancer 6, 17 (2018)] that aimed to reproduce the dynamics of interaction between tumor and immune system upon administration of radiation therapy and immunotherapy. Adopting a dynamical systems approach, we here investigate the qualitative behavior of the representative components of this QSP model around its key parameters. The ability of T cells to infiltrate tumor tissue, originally identified as responsible for individual therapeutic inter-variability [Y. Kosinsky et al., J. Immunother. Cancer 6, 17 (2018)], is shown here to be a saddle-node bifurcation point for which the dynamical system oscillates between two states: tumor-free or maximum tumor volume. By performing a bifurcation analysis of the physiological system, we identified equilibrium points and assessed their nature. We then used the traditional concept of basin of attraction to assess the performance of therapy. We showed that considering the therapy as input to the dynamical system translates into the changes of the trajectory shapes of the solutions when approaching equilibrium points and thus providing information on the issue of therapy.
定量系统药理学（QSP）被证明是一种强大的工具，可以阐明由生物学变异性加剧并与药物剂量方案的复杂程度重叠的潜在病理生理复杂性。越来越多地使用将免疫疗法与更传统的治疗方法（包括化疗和放疗）相结合的疗法。这些组合旨在放大针对肿瘤细胞的免疫反应并调节抑制性肿瘤微环境（TME）。为了从这些组合方法中获得最佳性能并得出合理的方案策略，需要更好地了解肿瘤与宿主免疫系统的相互作用。目前工作的目的是提供对免疫介导的 TME 和免疫肿瘤学治疗动力学的新见解。作为案例研究，我们将使用 Kosinsky 等人最近的 QSP 模型[J. Immunother. Cancer 6, 17 (2018)]，该模型旨在复制放射治疗和免疫治疗给药时肿瘤与免疫系统之间相互作用的动力学。采用动态系统方法，我们在此研究了该 QSP 模型的代表性组件围绕其关键参数的定性行为。T 细胞渗透肿瘤组织的能力最初被确定为导致个体治疗变异性的原因[Y. Kosinsky 等人，J. Immunother. Cancer 6, 17 (2018)]，这里显示它是鞍点分岔点，动力学系统在两种状态之间振荡：无肿瘤或最大肿瘤体积。通过对生理系统进行分岔分析，我们确定了平衡点并评估了它们的性质。然后，我们使用传统的吸引域概念来评估治疗的性能。我们表明，将治疗视为动态系统的输入会导致在接近平衡点时解决方案轨迹形状的变化，从而提供有关治疗问题的信息。
