Development of a 'humanised' model for renal cancer

免疫检查点抑制剂（icpi）是一种癌症治疗方法，可以增强身体的免疫系统来对抗癌症。icpi正在彻底改变癌症治疗，因为它们可以使多达50%的患者的癌症得到多年的控制。然而，不幸的是，只有不到50%的肾癌患者从这些昂贵的药物治疗中受益（一年的治疗费用高达9万英镑），然而，高达80%的患者经历了与免疫系统“过度激活”相关的副作用，这可能会攻击他们的正常器官。因此，迫切需要准确预测哪些患者将从治疗中受益，同时为不能从治疗中受益的患者提供替代治疗方案。通常，此类研究可以使用实验室模型进行，以防止患者不必要地暴露于次优药物（和组合）及其副作用，但用于肾癌中检测icpi的模型是有限的，因为它们缺乏像人类免疫系统一样工作的免疫细胞。然而，一种新的基因工程小鼠（称为NSG MHC I/II敲除（KO）小鼠）已经被开发出来，当将患者血液中的免疫细胞（称为外周血单个核细胞；PBMCs）注射到小鼠体内时，它可以培养出人类免疫系统，从而产生所谓的“人源化”小鼠。我的项目目标是开发一种新的“人性化”肾癌小鼠模型。具体目标是：1)通过将来自肾癌患者的pbmc注射到NSG MHC I/II KO小鼠中来产生“人源化”小鼠；+移植碾压混凝土和正常肾组织从癌症患者有手术切除肾脏生成一个新的“人性化”为RCC2)来测试新模型小鼠模型来确定的程度反映了比较免疫和癌症病人反应反应肾脏癌症患者对“人性化”老鼠ICPIs3处理)提供初步(试点)数据为未来大型格兰特(称为临床科学家格兰特)这样做我将注入PBMCs肾癌病人注入新的小鼠品系，创造出“人性化”的小鼠。我还将在小鼠体内植入肾脏和正常肾脏组织（这些患者通过手术切除肾癌时获得）。这将创造出一种新的“人性化”肾癌模型，它同时具有患者的免疫系统和肾癌（就像一个“化身”）。我们将对多达30名患者进行这项研究，因为需要做一些工作来优化程序，以确保pbmc、癌症和正常肾细胞在小鼠体内正常生长。然后我将测试这个模型，看看它在多大程度上反映了患者对ICPI治疗的反应。这些小鼠将接受4周的ICPI治疗，它们的免疫、肿瘤和正常组织反应将与在临床接受相同药物作为正常治疗一部分的肾癌患者的相同反应进行比较。这些数据将成为我未来临床科学家申请的重要先导数据，目的是在更长的时间内充分评估和验证不同药物的模型。然后，它可以用来确定肾癌患者最有效的新疗法和不同药物的组合（副作用最小），然后可以在临床试验中进行测试，而不是像目前那样在患者身上测试所有治疗方法和组合。这将节省大量的时间和成本。它还可以从血液或肿瘤中识别标记物，从而预测哪些患者可能对新疗法有反应或有非常严重的副作用，从而使那些无法从特定治疗中获益的患者可以免于治疗或副作用，并提供替代治疗。该模型也将对世界各地的许多学术和商业研究人员有用，他们可以用它来简化药物开发（如上所述），也可以研究免疫系统如何与肾癌相互作用（反之亦然）。

Immune checkpoint inhibitors (ICPIs) are a type of cancer treatment that boosts the body's immune system to fight cancer. ICPIs are revolutionising cancer treatment as they can lead to years of control of cancers in up to 50% of patients. However, unfortunately less than 50% of kidney cancer patients benefit from treatment with these costly drugs (1year treatment up to £90,000), yet up to 80% of patients experience side effects relating to 'over-activation' of their immune system which can attack their normal organs. Therefore, there is an urgent need to accurately predict which patients will benefit from treatment whilst providing alternative treatment options for patients who do not. Normally such studies can be performed using laboratory models to prevent patients being unnecessarily exposed to sub-optimal drugs (and combinations) and their side effects, but models for testing ICPIs in kidney cancer are limited as they lack immune cells that work like a human immune system. However, a new genetically engineered mouse has been developed (called a NSG MHC I/II knockout (KO) mouse) which can grow a human immune system when immune cells from patients' blood (called peripheral blood mononuclear cells; PBMCs) are injected into the mouse, to generate a so-called 'humanised' mouse. The goal of my project is to develop a new 'humanised' mouse model for kidney cancer. The specific objectives are:1) To generate 'humanised' mice by injecting PBMCs from kidney cancer patients into NSG MHC I/II KO mice, plus transplant RCC and normal kidney tissue from patients having surgery to remove their kidney cancer to generate a new 'humanised' mouse model for RCC2) To test the new model to determine the extent to which it reflects patient responses by comparing immune and cancer responses in kidney cancer patients vs 'humanised' mice treated with ICPIs3) To provide preliminary (pilot) data for a future large grant (called a Clinician Scientist grant) To do this I will inject PBMCs from kidney cancer patients into the new strain of mice to create 'humanised' mice. I will also implant kidney and normal kidney tissue (obtained when those patients have surgery to remove their kidney cancer) into the mice. This will create the new 'humanised' model for kidney cancer which has both the immune system and kidney cancer that the patient has (acting like an 'avatar'). We will do this for up to 30 patients as some work will be needed to optimise the procedures to make sure that the PBMCs, cancer and normal kidney cells grow properly in the mice. I will then test the model and see how well it mirrors patient responses to ICPI treatment. The mice will be treated with ICPI for 4 weeks and their immune, tumour and normal tissue responses will be compared to the same responses in kidney cancer patients who receive the same drugs in the clinic as part of their normal treatment. This data will form essential pilot data for my future Clinician Scientist application which will aim to fully assess and validate the model with arrange of different drugs for a longer time period. It could then be used to identify the most effective novel therapies and combinations of different drugs (with the least side effects) for kidney cancer patients which can then be tested in clinical trials, rather than testing all treatments and combinations in patients as currently happens. This would save significant time and cost. It could also identify markers from blood or tumours that could predict which patients are likely to respond or have very serious side effects to new treatments so those patients who would not benefit from a particular treatment could be spared treatment or side effects and offered an alternative treatment. The model will also be useful to many academic and commercial researchers worldwide who can use it to streamline drug development (as above) but also to investigate how the immune system interacts with kidney cancer (and vice versa).