Wenbo Li, Wang Jin
State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin, People's Republic of China.
State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin, People's Republic of China
J R Soc Interface. 2017 Jun;14(131). doi: 10.1098/rsif.2017.0105.
The study of the cancer-immune system is important for understanding tumorigenesis and the development of cancer and immunotherapy. In this work, we build a comprehensive cancer-immune model including both cells and cytokines to uncover the underlying mechanism of cancer immunity based on landscape topography. We quantify three steady-state attractors, normal state, low cancer state and high cancer state, for the innate immunity and adaptive immunity of cancer. We also illustrate the cardinal inhibiting cancer immunity interactions and promoting cancer immunity interactions through global sensitivity analysis. We simulate tumorigenesis and the development of cancer and classify these into six stages. The characteristics of the six stages can be classified further into three groups. These correspond to the escape, elimination and equilibrium phases in immunoediting, respectively. Under specific cell-cell interactions strength oscillations emerge. We found that tumorigenesis and cancer recovery processes may need to go through cancer-immune oscillation, which consumes more energy. Based on the cancer-immune landscape, we predict three types of cells and two types of cytokines for cancer immunotherapy as well as combination immunotherapy. This landscape framework provides a quantitative way to understand the underlying mechanisms of the interplay between cancer and the immune system for cancer tumorigenesis and development.
癌症 - 免疫系统的研究对于理解肿瘤发生、癌症发展以及免疫治疗具有重要意义。在这项工作中,我们构建了一个包括细胞和细胞因子的综合癌症 - 免疫模型,以基于景观地形学揭示癌症免疫的潜在机制。我们对癌症固有免疫和适应性免疫的三种稳态吸引子,即正常状态、低癌症状态和高癌症状态进行了量化。我们还通过全局敏感性分析阐明了主要的抑制癌症免疫相互作用和促进癌症免疫相互作用。我们模拟了肿瘤发生和癌症发展,并将其分为六个阶段。这六个阶段的特征可进一步分为三组。它们分别对应免疫编辑中的逃逸、清除和平衡阶段。在特定的细胞 - 细胞相互作用强度下会出现振荡。我们发现肿瘤发生和癌症恢复过程可能需要经历癌症 - 免疫振荡,这会消耗更多能量。基于癌症 - 免疫景观,我们预测了三种类型的细胞和两种类型的细胞因子用于癌症免疫治疗以及联合免疫治疗。这种景观框架提供了一种定量方法来理解癌症与免疫系统之间相互作用的潜在机制,以促进癌症肿瘤发生和发展。