Natural Product Informatics Research Center, Korea Institute of Science and Technology, Gangneung, Republic of Korea.
Graduate School of Science and Technology, Chungnam National University, Daejeon, Republic of Korea.
PLoS Comput Biol. 2022 Mar 9;18(3):e1009919. doi: 10.1371/journal.pcbi.1009919. eCollection 2022 Mar.
A long-standing practice in the treatment of cancer is that of hitting hard with the maximum tolerated dose to eradicate tumors. This continuous therapy, however, selects for resistant cells, leading to the failure of the treatment. A different type of treatment strategy, adaptive therapy, has recently been shown to have a degree of success in both preclinical xenograft experiments and clinical trials. Adaptive therapy is used to maintain a tumor's volume by exploiting the competition between drug-sensitive and drug-resistant cells with minimum effective drug doses or timed drug holidays. To further understand the role of competition in the outcomes of adaptive therapy, we developed a 2D on-lattice agent-based model. Our simulations show that the superiority of the adaptive strategy over continuous therapy depends on the local competition shaped by the spatial distribution of resistant cells. Intratumor competition can also be affected by fibroblasts, which produce microenvironmental factors that promote cancer cell growth. To this end, we simulated the impact of different fibroblast distributions on treatment outcomes. As a proof of principle, we focused on five types of distribution of fibroblasts characterized by different locations, shapes, and orientations of the fibroblast region with respect to the resistant cells. Our simulation shows that the spatial architecture of fibroblasts modulates tumor progression in both continuous and adaptive therapy. Finally, as a proof of concept, we simulated the outcomes of adaptive therapy of a virtual patient with four metastatic sites composed of different spatial distributions of fibroblasts and drug-resistant cell populations. Our simulation highlights the importance of undetected metastatic lesions on adaptive therapy outcomes.
在癌症治疗中，长期以来的做法是用最大耐受剂量进行猛烈打击，以消灭肿瘤。然而，这种持续治疗会选择耐药细胞，导致治疗失败。最近，一种不同类型的治疗策略——适应性治疗，在临床前异种移植实验和临床试验中都显示出了一定的成功。适应性治疗是通过利用药物敏感细胞和耐药细胞之间的竞争，用最小有效药物剂量或定时药物休假期来维持肿瘤体积。为了进一步了解竞争在适应性治疗结果中的作用，我们开发了一个二维网格基于代理的模型。我们的模拟表明，适应性策略优于连续治疗的优势取决于耐药细胞空间分布所形成的局部竞争。肿瘤内竞争也会受到成纤维细胞的影响，成纤维细胞会产生促进癌细胞生长的微环境因素。为此，我们模拟了不同成纤维细胞分布对治疗结果的影响。作为一个原理验证，我们专注于五种成纤维细胞分布类型，其特征是成纤维细胞区域相对于耐药细胞的位置、形状和方向不同。我们的模拟表明，成纤维细胞的空间结构会调节连续和适应性治疗中的肿瘤进展。最后，作为概念验证，我们模拟了一个由不同空间分布的成纤维细胞和耐药细胞群体组成的四个转移部位的虚拟患者的适应性治疗结果。我们的模拟强调了未检测到的转移病变对适应性治疗结果的重要性。
