School of Mathematics and Statistics, University of St Andrews, St Andrews, Scotland, UK.
School of Medicine, Jacqui Wood Cancer Centre, Ninewells Hospital and Medical School, University of Dundee, Dundee, Scotland, UK.
NPJ Syst Biol Appl. 2024 May 15;10(1):51. doi: 10.1038/s41540-024-00379-9.
In vertical inhibition treatment strategies, multiple components of an intracellular pathway are simultaneously inhibited. Vertical inhibition of the BRAFV600E-MEK-ERK signalling pathway is a standard of care for treating BRAFV600E-mutated melanoma where two targeted cancer drugs, a BRAFV600E-inhibitor, and a MEK inhibitor, are administered in combination. Targeted therapies have been linked to early onsets of drug resistance, and thus treatment strategies of higher complexities and lower doses have been proposed as alternatives to current clinical strategies. However, finding optimal complex, low-dose treatment strategies is a challenge, as it is possible to design more treatment strategies than are feasibly testable in experimental settings. To quantitatively address this challenge, we develop a mathematical model of BRAFV600E-MEK-ERK signalling dynamics in response to combinations of the BRAFV600E-inhibitor dabrafenib (DBF), the MEK inhibitor trametinib (TMT), and the ERK-inhibitor SCH772984 (SCH). From a model of the BRAFV600E-MEK-ERK pathway, and a set of molecular-level drug-protein interactions, we extract a system of chemical reactions that is parameterised by in vitro data and converted to a system of ordinary differential equations (ODEs) using the law of mass action. The ODEs are solved numerically to produce simulations of how pathway-component concentrations change over time in response to different treatment strategies, i.e., inhibitor combinations and doses. The model can thus be used to limit the search space for effective treatment strategies that target the BRAFV600E-MEK-ERK pathway and warrant further experimental investigation. The results demonstrate that DBF and DBF-TMT-SCH therapies show marked sensitivity to BRAFV600E concentrations in silico, whilst TMT and SCH monotherapies do not.
在垂直抑制治疗策略中，同时抑制细胞内途径的多个组成部分。抑制 BRAFV600E-MEK-ERK 信号通路是治疗 BRAFV600E 突变黑色素瘤的标准治疗方法，其中联合使用两种靶向癌症药物，即 BRAFV600E 抑制剂和 MEK 抑制剂。靶向治疗与药物耐药性的早期发作有关，因此提出了更高复杂性和更低剂量的治疗策略作为替代当前临床策略。然而，找到最佳的复杂、低剂量治疗策略是一个挑战，因为在实验环境中可能设计出比可行的测试更多的治疗策略。为了定量解决这个挑战，我们开发了一个 BRAFV600E-MEK-ERK 信号对 BRAFV600E 抑制剂 dabrafenib（DBF）、MEK 抑制剂 trametinib（TMT）和 ERK 抑制剂 SCH772984（SCH）组合反应的数学模型。从 BRAFV600E-MEK-ERK 通路模型和一组分子水平的药物-蛋白相互作用中，我们提取了一组化学反应，这些反应由体外数据参数化，并使用质量作用定律转换为常微分方程（ODE）系统。使用数值方法求解 ODE 以产生如何根据不同的治疗策略（即抑制剂组合和剂量）随时间改变途径成分浓度的模拟。因此，该模型可用于限制针对 BRAFV600E-MEK-ERK 通路的有效治疗策略的搜索空间，并需要进一步的实验研究。结果表明，DBF 和 DBF-TMT-SCH 治疗在计算机模拟中对 BRAFV600E 浓度表现出明显的敏感性，而 TMT 和 SCH 单药治疗则没有。
