Huntsman Cancer Institute, University of Utah Health Sciences Center, Salt Lake City, Utah, USA.
Department of Pathology, University of Utah School of Medicine, Salt Lake City, Utah, USA.
Immunol Rev. 2023 Sep;318(1):110-137. doi: 10.1111/imr.13250. Epub 2023 Aug 10.
Cancer patients treated with immune checkpoint inhibitors (ICIs) are susceptible to a broad and variable array of immune-related adverse events (irAEs). With increasing clinical use of ICIs, defining the mechanism for irAE development is more critical than ever. However, it currently remains challenging to predict when these irAEs occur and which organ may be affected, and for many of the more severe irAEs, inaccessibility to the tissue site hampers mechanistic insight. This lack of understanding of irAE development in the clinical setting emphasizes the need for greater use of preclinical models that allow for improved prediction of biomarkers for ICI-initiated irAEs or that validate treatment options that inhibit irAEs without hampering the anti-tumor immune response. Here, we discuss the utility of preclinical models, ranging from exploring databases to in vivo animal models, focusing on where they are most useful and where they could be improved.
接受免疫检查点抑制剂 (ICI) 治疗的癌症患者易发生广泛而多变的免疫相关不良事件 (irAE)。随着 ICI 的临床应用不断增加,定义 irAE 发展机制比以往任何时候都更加关键。然而,目前仍然难以预测这些 irAE 何时发生以及哪些器官可能受到影响,对于许多更严重的 irAE,组织部位的不可及性阻碍了对发病机制的深入了解。在临床环境中对 irAE 发展缺乏了解,强调需要更多地使用临床前模型,这些模型可以更好地预测 ICI 引发的 irAE 的生物标志物,或者验证抑制 irAE 而不影响抗肿瘤免疫反应的治疗选择。在这里,我们讨论了临床前模型的实用性,范围从探索数据库到体内动物模型,重点讨论了它们最有用的地方和可以改进的地方。