Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, California.
Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, California.
Cancer Immunol Res. 2023 May 3;11(5):614-628. doi: 10.1158/2326-6066.CIR-22-0617.
Myeloid-derived suppressor cells (MDSC) play a prominent role in the tumor microenvironment. A quantitative understanding of the tumor-MDSC interactions that influence disease progression is critical, and currently lacking. We developed a mathematical model of metastatic growth and progression in immune-rich tumor microenvironments. We modeled the tumor-immune dynamics with stochastic delay differential equations and studied the impact of delays in MDSC activation/recruitment on tumor growth outcomes. In the lung environment, when the circulating level of MDSCs was low, the MDSC delay had a pronounced impact on the probability of new metastatic establishment: blocking MDSC recruitment could reduce the probability of metastasis by as much as 50%. To predict patient-specific MDSC responses, we fit to the model individual tumors treated with immune checkpoint inhibitors via Bayesian parameter inference. We reveal that control of the inhibition rate of natural killer (NK) cells by MDSCs had a larger influence on tumor outcomes than controlling the tumor growth rate directly. Posterior classification of tumor outcomes demonstrates that incorporating knowledge of the MDSC responses improved predictive accuracy from 63% to 82%. Investigation of the MDSC dynamics in an environment low in NK cells and abundant in cytotoxic T cells revealed, in contrast, that small MDSC delays no longer impacted metastatic growth dynamics. Our results illustrate the importance of MDSC dynamics in the tumor microenvironment overall and predict interventions promoting shifts toward less immune-suppressed states. We propose that there is a pressing need to consider MDSCs more often in analyses of tumor microenvironments.
髓系来源的抑制细胞 (MDSC) 在肿瘤微环境中起着重要作用。定量理解影响疾病进展的肿瘤-MDSC 相互作用至关重要，但目前仍缺乏相关研究。我们开发了一种在富含免疫细胞的肿瘤微环境中转移性生长和进展的数学模型。我们使用随机时滞微分方程来模拟肿瘤-免疫动力学，并研究了 MDSC 激活/招募延迟对肿瘤生长结果的影响。在肺部环境中，当循环中的 MDSC 水平较低时，MDSC 延迟对新转移灶建立的概率有显著影响：阻断 MDSC 募集可使转移的概率降低多达 50%。为了预测患者特异性 MDSC 反应，我们通过贝叶斯参数推断，将模型拟合到接受免疫检查点抑制剂治疗的个体肿瘤上。我们发现，MDSC 对自然杀伤 (NK) 细胞抑制率的控制比对直接控制肿瘤生长速度对肿瘤结果的影响更大。对肿瘤结果的后分类表明，纳入 MDSC 反应的知识可将预测准确性从 63%提高到 82%。在 NK 细胞含量低且细胞毒性 T 细胞丰富的环境中研究 MDSC 动力学表明，较小的 MDSC 延迟不再影响转移性生长动力学。我们的研究结果表明 MDSC 动力学在肿瘤微环境中的重要性，并预测促进向免疫抑制程度较低状态转变的干预措施。我们提出，在分析肿瘤微环境时，需要更频繁地考虑 MDSC。
