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

免疫检查点是表达在免疫细胞表面的蛋白质，它抑制了免疫细胞的活动(通常是为了让它们不攻击我们)。仅在两个免疫检查点上的研究就彻底改变了癌症治疗，对黑色素瘤等以前无法治疗的疾病产生持久反应，阻断受体的抑制作用，使白细胞可以自由攻击肿瘤。但有多达60个免疫检查站在监管免疫系统，这突显了通过这些检查点进行医疗干预的非凡范围，并强调了仍有许多工作要做。值得注意的是，尽管免疫检查点具有巨大的意义，但人们对免疫检查点的工作原理知之甚少，即它们用来关闭对肿瘤的免疫反应的分子途径。在这项建议中，我们旨在探索免疫检查点在三种主要类型的免疫细胞(即B细胞和T细胞，以及髓系细胞)中的活性的分子机制的不同，并了解是否有可能在治疗上利用这些差异。如果事实证明，免疫检查点调用的是相同的途径，我们就不太可能使它们共同更好地发挥作用。然而，根据对这些途径的已知情况，情况似乎不太可能是这样。我们将在体外模型双细胞共培养系统(即“试管”)的水平上开始我们的研究，在那里我们将能够测试多种方法。为了研究在真实肿瘤的背景下会发生什么，我们将创建实际肿瘤的三维(3D)培养，我们可以研究它们对免疫治疗的反应。但理解免疫检查点如何工作的主要问题是，我们目前对人类细胞信号通路的了解非常不完整，而且高度偏向于那些研究得很好的通路。例如，驱动信号转导的最重要的一组酶，即激酶和磷酸酶，有30%-50%的靶标是完全未知的。这表明，重要的途径和过程目前可能尚未被发现。将我们对免疫检查点信号的研究局限于已知的途径，只会揭示拼图的一部分，这意味着有效的治疗癌症的新方法可能会被完全忽视。为了绕过这个问题，我们建议使用一种结合遗传扰动的策略，即在研究中的免疫细胞中可能参与信号通路的所有可能的激酶和磷酸酶的“基因敲除”，以及基于一组方便、可管理的信号通路元件的信号结果测量，我们可以在单细胞中轻松和准确地测量(这是一大飞跃)。我们的目标是能够使用这一小部分途径元素来构建完整的网络。为此，我们将开发新的计算管道，以获得参与抗肿瘤反应的每组主要细胞的整个信号网络的全面和准确的图像。一旦我们证明新的管道有效，我们将能够比较和对比免疫检查点是如何变化的，以及这些蛋白质的不同类型的阻断是如何改变攻击癌症的免疫细胞的活动的。我们非常有信心，我们的工作将填补我们对免疫检查点的基本理解中的主要空白，这将引起所有免疫学家的极大兴趣。但更重要的是，我们的工作可能会为改进免疫检查点阻断癌症免疫治疗提供重要的新方法。

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.