Ackermann Joseph, Bernard Chiara, Sirven Philemon, Salmon Helene, Fraldi Massimiliano, Ben Amar Martine D
Laboratoire Jean Perrin, Sorbonne Université, Paris, France.
Laboratoire de Physique de l'Ecole normale supérieure, ENS, Université PSL, CNRS, Sorbonne Université, Université Paris Cité, Paris, France.
Elife. 2025 Apr 10;13:RP101885. doi: 10.7554/eLife.101885.
The tumor stroma consists mainly of extracellular matrix, fibroblasts, immune cells, and vasculature. Its structure and functions are altered during malignancy: tumor cells transform fibroblasts into cancer-associated fibroblasts, which exhibit immunosuppressive activities on which growth and metastasis depend. These include exclusion of immune cells from the tumor nest, cancer progression, and inhibition of T-cell-based immunotherapy. To understand these complex interactions, we measure the density of different cell types in the stroma using immunohistochemistry techniques on tumor samples from lung cancer patients. We incorporate these data into a minimal dynamical system, explore the variety of outcomes, and finally establish a spatio-temporal model that explains the cell distribution. We reproduce that cancer-associated fibroblasts act as a barrier to tumor expansion, but also reduce the efficiency of the immune response. Our conclusion is that the final outcome depends on the parameter values for each patient and leads to either tumor invasion, persistence, or eradication as a result of the interplay between cancer cell growth, T-cell cytotoxicity, and fibroblast activity. However, despite the existence of a wide range of scenarios, distinct trajectories, and patterns allow quantitative predictions that may help in the selection of new therapies and personalized protocols.
肿瘤基质主要由细胞外基质、成纤维细胞、免疫细胞和脉管系统组成。在恶性肿瘤发生过程中，其结构和功能会发生改变：肿瘤细胞将成纤维细胞转化为癌症相关成纤维细胞，这些细胞具有免疫抑制活性，肿瘤的生长和转移依赖于此。这些活性包括将免疫细胞排除在肿瘤巢之外、癌症进展以及抑制基于T细胞的免疫疗法。为了理解这些复杂的相互作用，我们使用免疫组织化学技术对肺癌患者的肿瘤样本进行检测，以测量基质中不同细胞类型的密度。我们将这些数据纳入一个最小动力系统，探索各种结果，最终建立一个解释细胞分布的时空模型。我们再现了癌症相关成纤维细胞既作为肿瘤扩张的屏障，又降低免疫反应效率的现象。我们的结论是，最终结果取决于每位患者的参数值，由于癌细胞生长、T细胞细胞毒性和成纤维细胞活性之间的相互作用，会导致肿瘤侵袭、持续存在或根除。然而，尽管存在多种情况、不同轨迹和模式，但独特的轨迹和模式能够进行定量预测，这可能有助于选择新的治疗方法和个性化方案。
