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

免疫检查点是免疫细胞表面表达的蛋白质，它们抑制免疫细胞的活性（通常是为了使它们不攻击我们）。仅仅在两个免疫检查点上的工作就彻底改变了癌症治疗方法，通过阻断受体的抑制作用，使白细胞可以自由地攻击肿瘤，从而在以前无法治疗的疾病（如黑色素瘤）中产生持久的反应。但有多达60个免疫检查点调节免疫系统，强调了通过检查点进行医疗干预的非凡范围，并强调了还有多少工作要做。值得注意的是，尽管它们具有巨大的意义，但人们对免疫检查点如何工作知之甚少，即它们用于关闭对肿瘤的免疫反应的分子途径。 在这项提案中，我们的目标是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细胞以及骨髓细胞）中的活性分子机制如何不同，并了解是否有可能在治疗上利用这些差异。如果事实证明，免疫检查点调用相同的途径，我们不太可能使它们更好地共同工作。然而，基于对这些途径的已知，这似乎不太可能。我们将在体外模型双细胞共培养系统（即在“试管”中）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。为了研究真实肿瘤的情况，我们将创建实际肿瘤的三维（3D）培养物，我们可以在它们对免疫疗法的反应过程中研究它们。 但是，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传导途径的了解非常不完整，并且高度偏向于研究充分的途径。例如，30-50%的最重要的驱动信号传导的酶群（称为激酶和磷酸酶）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发现。将我们对免疫检查点信号传导的研究限制在已知的途径上，只会揭示拼图的一部分，这意味着治疗癌症的有效新方法可能会被完全忽视。为了规避这个问题，我们建议使用一种策略，该策略结合了遗传扰动，即可能参与所研究的免疫细胞中信号传导途径的所有可能的激酶和磷酸酶的“基因敲除”，以及基于我们可以在单细胞中容易且准确地测量的一组方便、可管理的信号传导途径元素的信号传导结果的测量（一个巨大的飞跃）。我们的目标是能够使用这一小部分通路元素来构建完整的网络。为了做到这一点，我们将开发新的计算管道，以获得整个信号网络的全面和准确的图片，对于参与抗肿瘤反应的每一个主要的leykocytes集。一旦我们证明新的管道起作用，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阻断如何改变免疫细胞攻击癌症的活动。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，我们的工作可以为改善免疫检查点阻断癌症免疫疗法提供重要的新方法。

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.