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.

免疫检查点是免疫细胞表面表达的蛋白质，可抑制其活动（通常是为了防止它们攻击我们）。仅针对两个免疫检查点的研究就彻底改变了癌症治疗，通过阻断受体的抑制作用，使白细胞能够自由地攻击肿瘤，对以前无法治疗的疾病（如黑色素瘤）产生持久的反应。但调节免疫系统的免疫检查点多达 60 个，这凸显了通过检查点进行医疗干预的巨大范围，并强调仍有大量工作要做。值得注意的是，尽管免疫检查点意义重大，但人们对它们如何工作（即它们用来关闭肿瘤免疫反应的分子途径）知之甚少。 在本提案中，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、T 细胞和骨髓细胞）中的活性分子机制方面有何不同，并了解是否有可能利用这些差异在治疗上。如果事实证明免疫检查点调用相同的途径，我们不太可能让它们更好地共同发挥作用。然而，根据对这些途径的已知信息，情况似乎不太可能发生。我们将在体外（即“试管”）模型双细胞共培养系统的水平上开始我们的研究，我们将能够测试多种方法。为了研究真实肿瘤环境中发生的情况，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治疗的反应过程中研究它们。 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传导途径的了解非常不完整，并且高度偏向于经过充分研究的知识。例如，驱动信号传导的最重要酶类（称为激酶和磷酸酶）的 30-50% 的靶标是完全未知的。这表明目前可能尚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在已知的途径上只会揭示拼图的一部分，并且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，我们建议使用一种结合遗传扰动的策略，即对所研究的免疫细胞中可能参与信号传导途径的所有可能的激酶和磷酸酶进行“基因敲除”，并根据信号传导结果进行测量通过一组方便、可管理的信号通路元件，我们可以轻松、准确地在单细胞中进行测量（这是一个巨大的飞跃）。我们的目标是能够使用这一小组路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个主要白细胞组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的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动。我们非常有信心，我们的工作将填补我们对免疫检查点基本理解的重大空白，这将引起所有免疫学家的极大兴趣。但更重要的是，我们的工作可以提出改善免疫检查点阻断癌症免疫治疗的重要新方法。