Department of Hematology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
School of Mathematical Sciences, Beijing Normal University, Beijing, China.
Mol Cancer Ther. 2018 Apr;17(4):814-824. doi: 10.1158/1535-7163.MCT-17-0634. Epub 2018 Feb 13.
The emergence of drug resistance is often an inevitable obstacle that limits the long-term effectiveness of clinical cancer chemotherapeutics. Although various forms of cancer cell-intrinsic mechanisms of drug resistance have been experimentally revealed, the role and the underlying mechanism of tumor microenvironment in driving the development of acquired drug resistance remain elusive, which significantly impedes effective clinical cancer treatment. Recent experimental studies have revealed a macrophage-mediated drug resistance mechanism in which the tumor microenvironment undergoes adaptation in response to macrophage-targeted colony-stimulating factor-1 receptor (CSF1R) inhibition therapy in gliomas. In this study, we developed a spatio-temporal model to quantitatively describe the interplay between glioma cells and CSF1R inhibitor-targeted macrophages through CSF1 and IGF1 pathways. Our model was used to investigate the evolutionary kinetics of the tumor regrowth and the associated dynamic adaptation of the tumor microenvironment in response to the CSF1R inhibitor treatment. The simulation result obtained using this model was in agreement with the experimental data. The sensitivity analysis revealed the key parameters involved in the model, and their potential impacts on the model behavior were examined. Moreover, we demonstrated that the drug resistance is dose-dependent. In addition, we quantitatively evaluated the effects of combined CSFR inhibition and IGF1 receptor (IGF1R) inhibition with the goal of designing more effective therapies for gliomas. Our study provides quantitative and mechanistic insights into the microenvironmental adaptation mechanisms that operate during macrophage-targeted immunotherapy and has implications for drug dose optimization and the design of more effective combination therapies. .
耐药性的出现通常是限制临床癌症化疗长期有效性的不可避免的障碍。尽管已经从实验上揭示了各种形式的癌细胞内在耐药机制，但肿瘤微环境在推动获得性耐药发展中的作用和潜在机制仍然难以捉摸，这极大地阻碍了有效的临床癌症治疗。最近的实验研究揭示了一种巨噬细胞介导的耐药机制，其中肿瘤微环境在胶质母细胞瘤中对巨噬细胞靶向集落刺激因子-1 受体（CSF1R）抑制治疗做出反应时会发生适应性改变。在这项研究中，我们开发了一个时空模型，通过 CSF1 和 IGF1 途径定量描述了神经胶质瘤细胞与 CSF1R 抑制剂靶向巨噬细胞之间的相互作用。我们的模型用于研究肿瘤再生的进化动力学以及肿瘤微环境对 CSF1R 抑制剂治疗的相关动态适应。使用该模型获得的模拟结果与实验数据一致。敏感性分析揭示了模型中涉及的关键参数，以及它们对模型行为的潜在影响。此外，我们证明了耐药性是剂量依赖性的。此外，我们定量评估了 CSFR 抑制和 IGF1 受体（IGF1R）抑制联合用药的效果，以期为胶质瘤设计更有效的治疗方法。我们的研究为巨噬细胞靶向免疫治疗过程中的微环境适应机制提供了定量和机制见解，并对药物剂量优化和更有效的联合治疗设计具有重要意义。
