Group of Inflammatory Carcinogenesis, Institute for Experimental Cancer Research, University Hospital Schleswig-Holstein (UKSH), Kiel University, Kiel, Germany.
Department of Internal Medicine II, University Hospital Center Schleswig-Holstein, Kiel, Germany.
Front Immunol. 2023 Aug 10;14:1237565. doi: 10.3389/fimmu.2023.1237565. eCollection 2023.
Immunotherapies are a key therapeutic strategy to fight cancer. Diverse approaches are used to activate tumor-directed immunity and to overcome tumor immune escape. The dynamic interplay between tumor cells and their tumor(immune)microenvironment (T(I)ME) poses a major challenge to create appropriate model systems. However, those model systems are needed to gain novel insights into tumor (immune) biology and a prerequisite to accurately develop and test immunotherapeutic approaches which can be successfully translated into clinical application. Several model systems have been established and advanced into so-called patient avatars to mimic the patient´s tumor biology. All models have their advantages but also disadvantages underscoring the necessity to pay attention in defining the rationale and requirements for which the patient avatar will be used. Here, we briefly outline the current state of tumor model systems used for tumor (immune)biological analysis as well as evaluation of immunotherapeutic agents. Finally, we provide a recommendation for further development to make patient avatars a complementary tool for testing and predicting immunotherapeutic strategies for personalization of tumor therapies.
免疫疗法是对抗癌症的关键治疗策略。人们采用多种方法来激活针对肿瘤的免疫并克服肿瘤免疫逃逸。肿瘤细胞与其肿瘤（免疫）微环境（T（I）ME）之间的动态相互作用给创建合适的模型系统带来了重大挑战。然而，这些模型系统对于深入了解肿瘤（免疫）生物学以及准确开发和测试可以成功转化为临床应用的免疫治疗方法是必要的。已经建立了几种模型系统，并将其推进到所谓的患者虚拟人，以模拟患者的肿瘤生物学。所有模型都有其优点，但也有缺点，这突出表明有必要注意定义患者虚拟人将被用于的基本原理和要求。在这里，我们简要概述了用于肿瘤（免疫）生物学分析以及评估免疫治疗剂的肿瘤模型系统的当前状态。最后，我们提出了进一步发展的建议，以使患者虚拟人成为测试和预测免疫治疗策略的补充工具，以实现肿瘤治疗的个体化。
