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适应性免疫对肿瘤化疗及化疗免疫治疗反应影响的模型

A model for effects of adaptive immunity on tumor response to chemotherapy and chemoimmunotherapy.

作者信息

Robertson-Tessi Mark, El-Kareh Ardith, Goriely Alain

机构信息

Program in Applied Mathematics, University of Arizona, Tucson, AZ 85721, United States; Integrated Mathematical Oncology, Moffitt Cancer Center, Tampa, FL 33612, United States.

ARL-Microcirculation Division, University of Arizona, Tucson, AZ 85724, United States.

出版信息

J Theor Biol. 2015 Sep 7;380:569-84. doi: 10.1016/j.jtbi.2015.06.009. Epub 2015 Jun 16.

Abstract

Complete clinical regressions of solid tumors in response to chemotherapy are difficult to explain by direct cytotoxicity alone, because of low growth fractions and obstacles to drug delivery. A plausible indirect mechanism that might reconcile this is the action of the immune system. A model for interaction between tumors and the adaptive immune system is presented here, and used to examine controllability of tumors through the interplay of cytotoxic, cytostatic and immunogenic effects of chemotherapy and the adaptive immune response. The model includes cytotoxic and helper T cells, T regulatory cells (Tregs), dendritic cells, memory cells, and several key cytokines. Nearly all parameter estimates are derived from experimental and clinical data. Individual tumors are characterized by two parameters: growth rate and antigenicity, and regions of tumor control are identified in this parameter space. The model predicts that inclusion of the immune response significantly expands the region of tumor control for both cytostatic and cytotoxic chemotherapies. Moreover, outside the control zone, tumor growth is delayed significantly. An optimal fractionation schedule is predicted, for a fixed cumulative dose. The model further predicts expanded regions of tumor control when several forms of immunotherapy (adoptive T cell transfer, Treg depletion, and dendritic cell vaccination) are combined with chemotherapy. Outcomes depend greatly on tumor characteristics, the schedule of administration, and the type of immunotherapy chosen, suggesting promising opportunities for personalized medicine. Overall, the model provides insight into the role of the adaptive immune system in chemotherapy, and how scheduling and immunotherapeutic interventions might improve efficacy.

摘要

实体瘤对化疗产生完全的临床消退很难仅通过直接细胞毒性来解释,这是因为肿瘤生长分数低以及存在药物递送障碍。一种可能解释这一现象的间接机制是免疫系统的作用。本文提出了一个肿瘤与适应性免疫系统之间相互作用的模型,并用于通过化疗的细胞毒性、细胞生长抑制和免疫原性效应与适应性免疫反应之间的相互作用来研究肿瘤的可控性。该模型包括细胞毒性T细胞和辅助性T细胞、调节性T细胞(Tregs)、树突状细胞、记忆细胞以及几种关键细胞因子。几乎所有参数估计值均来自实验和临床数据。单个肿瘤由两个参数表征:生长速率和抗原性,并在该参数空间中确定肿瘤控制区域。该模型预测,纳入免疫反应会显著扩大细胞生长抑制性化疗和细胞毒性化疗的肿瘤控制区域。此外,在控制区之外,肿瘤生长会显著延迟。对于固定的累积剂量,预测了一种最佳的分割方案。该模型还预测,当几种形式的免疫疗法(过继性T细胞转移、Treg耗竭和树突状细胞疫苗接种)与化疗联合使用时,肿瘤控制区域会扩大。结果在很大程度上取决于肿瘤特征、给药方案以及所选免疫疗法的类型,这为个性化医疗提供了有前景的机会。总体而言,该模型深入了解了适应性免疫系统在化疗中的作用,以及给药方案和免疫治疗干预如何提高疗效。

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