Improved mouse models to assess tumour immunity and irAEs after combination cancer immunotherapies

改进的小鼠模型用于评估联合癌症免疫疗法后的肿瘤免疫和免疫相关不良事件

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Abstract

The current excitement surrounding cancer immunotherapy stems particularly from clinical data involving agents mediating immune checkpoint receptor blockade, which have induced unprecedented efficacy against a range of tumours compared with previous immunotherapeutic approaches. However, an important consideration in targeting checkpoint receptors has been the emergence of associated toxicities termed immune-related adverse events (irAEs). In light of the clinical benefits observed after co-blockade of checkpoint receptors and data from preclinical mouse models, there is now a strong rationale to combine different checkpoint receptors together, with other immunotherapies or more conventional therapies to assess if clinical benefits to cancer patients can be further improved. However, one may predict the frequency and severity of irAEs will increase with combinations, which may result in premature therapy cessation, thus limiting the realization of such an approach. In addition, there is a limit to how many different combination therapies that can be tested in a timely manner given the legal, regulatory and budgetary issues associated with conducting clinical trials. Thus, there is a need to develop preclinical mouse models that more accurately inform us as to which immunotherapies might combine best to provide the optimal therapeutic index (maximal anti-tumour efficacy and low level irAEs) in different cancer settings. In this review we will discuss the irAEs observed in patients after checkpoint blockade and discuss which mouse models of cancer can be appropriate to assess the development of tumour immunity and irAEs following combination cancer immunotherapies.

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