Cell Type-Specific Analysis of Immune Checkpoint Signalling Networks Underpinning Cancer Immunotherapy

支持癌症免疫治疗的免疫检查点信号网络的细胞类型特异性分析

• 批准号: MR/W025507/1
• 负责人: Evangelia Petsalaki
• 金额: $ 132.43万
• 依托单位: European Bioinformatics Institute
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FW025507%2F1
• 关键词: Cell; Type; Specific; Analysis; Immune

Immune checkpoints are proteins expressed on the surfaces of immune cells that suppress their activity (normally so that they don't attack us). Work on just two immune checkpoints has revolutionised cancer therapy by producing durable responses in previously untreatable diseases such as melanoma, by blocking the suppressive effects of the receptors so that the leukocytes are free to attack tumours. But there are as many as 60 immune checkpoints regulating the immune system, underscoring the extraordinary scope for medical intervention via the checkpoints, and emphasising how much work is still to be done. Remarkably, despite their enormous significance, very little is known about how the immune checkpoints work, i.e. the molecular pathways they use to switch off immune responses to tumours. In this proposal we aim to explore how immune checkpoints differ with regard to the molecular mechanisms of their activity in three major types of immune cells (i.e. B cells and T cells, and myeloid cells), and to learn whether it will be possible to exploit these differences therapeutically. If it turns out that the immune checkpoints invoke the same pathways, it is unlikely that we will be able to make them work better collectively. However, based on what is already known about these pathways, this seems very unlikely to be the case. We will start our study at the level of a model two-cell co-culture system in vitro (i.e. in "test tubes"), where we will be able to test multiple approaches. To study what happens in the setting of authentic tumours, we will create three-dimensional (3D) cultures of actual tumours, which we can study in the course of their responses to immunotherapy. But the main problem with understanding how the immune checkpoints work is that our current knowledge of human cellular signalling pathways is very incomplete and highly biased to well-studied ones. For example, 30-50% of the targets for the most important groups of enzymes driving signalling, called kinases and phosphatases, are completely unknown. This suggests that important pathways and processes may currently be undiscovered. Limiting our studies of immune checkpoint signalling to the known pathways would reveal only part of the jigsaw and would mean that effective new ways to treat cancer might be wholly overlooked. To circumvent this issue, we are proposing to use a strategy that combines genetic perturbations, i.e. "gene knockouts" of all the possible kinases and phosphatases that could be involved in the signaling pathways in the immune cells under study, with measurements of signalling outcomes based on a convenient, manageable set of signaling pathway elements we can easily and accurately measure in single cells (a great leap forward). Our goal is to be able to use this small set of pathway elements to build out to the complete network. To do this we will be developing new computational pipelines in order to obtain comprehensive and accurate pictures of the whole signalling network, for each of the main sets of leykocytes involved in anti-tumour responses. Once we show that the new pipeline works, we will be able to compare and contrast how immune checkpoints vary and how different types of blockade of these proteins alters the activities of the immune cells attacking cancers. We're very confident that our work will plug major gaps in our basic understanding of immune checkpoints which will be of considerable interest to all immunologists. But more importantly, our work could suggest important new ways to improve immune checkpoint blockade cancer immunotherapy.

免疫检查点是在免疫细胞表面表达的蛋白质，这些蛋白质抑制了其活性（通常是使它们不攻击我们）。仅在两个免疫检查点上的工作通过在以前无法治疗的疾病（例如黑色素瘤）中产生持久反应，通过阻断受体的抑制作用，从而彻底改变了癌症治疗，从而使白细胞可以自由攻击肿瘤。但是，有多达60个免疫检查站来调节免疫系统，强调了通过检查站的非凡范围，并强调仍将完成多少工作。值得注意的是，尽管具有巨大的意义，但对免疫检查点的工作方式，即它们用于关闭肿瘤免疫反应的分子途径知之甚少。 在此提案中，我们旨在探讨在三种主要类型的免疫细胞（即B细胞和T细胞以及髓样细胞）中其活性的分子机制如何不同，并了解是否可以治疗这些差异。如果事实证明免疫检查点可以调用相同的途径，那么我们不太可能能够使它们更好地共同工作。但是，基于对这些途径的已知知识，这似乎不太可能是这种情况。我们将在体外（即“测试管”中）的模型两公共培养系统的水平上开始研究，在那里我们将能够测试多种方法。为了研究正宗肿瘤的环境中发生的情况，我们将创建三维（3D）实际肿瘤的培养物，我们可以在它们对免疫疗法的反应过程中进行研究。 但是，了解免疫检查点的工作方式的主要问题是，我们目前对人类细胞信号通路的了解非常不完整，并且对良好的途径高度偏见。例如，最重要的一组酶驱动信号传导的靶标（称为激酶和磷酸酶）完全未知。这表明目前可能未发现重要的途径和过程。将我们对免疫检查点信号传导的研究限制为已知途径只会显示部分拼图，这意味着有效治疗癌症的有效方法可能会被完全忽略。为了避免这个问题，我们建议使用一种结合遗传扰动的策略，即可能涉及的所有可能的激酶和磷酸酶的“基因敲除”，这些激酶和磷酸酶可能涉及研究的免疫细胞中的信号传导途径，以及基于信号的测量值，基于信号量的测量值，基于信号途径的便利，可以轻松地衡量单个细胞（一个很好地衡量）。我们的目标是能够使用这一小途径元素来构建到完整的网络。为此，我们将开发新的计算管道，以获取整个信号网络的全面图像，对于参与反肿瘤响应的每个主要集合。一旦我们证明了新管道有效，我们将能够比较和对比免疫检查点如何变化，以及这些蛋白质的不同类型的封锁如何改变免疫细胞攻击癌症的活性。我们非常有信心，我们的工作将弥补我们对免疫检查点的基本理解，这对所有免疫学家都非常感兴趣。但更重要的是，我们的工作可以提出改善免疫检查点阻断癌症免疫疗法的重要新方法。