A Nanopathology Platform for Prediction and Early Detection of Disease in Kidney Transplant Rejection

慢性肾衰竭影响了全球11%的人口。由免疫系统引起的疾病是慢性肾衰竭的第三大常见原因。移植是终末期肾衰竭患者的最佳治疗方法，但遗憾的是，移植的肾脏平均不能持续10-15年，主要是因为移植接受者对捐赠的肾脏产生了免疫反应，称为移植排斥反应。特别是，如果移植接受者产生针对供体组织的抗体，结果就很差。这被称为“抗体介导的排斥反应”。目前对抗体介导的排斥反应的治疗主要包括去除或阻断抗体的作用，但这些都不是很有效。为了开发新的更好的治疗方法，我们需要更好地了解排异反应。我们目前对排斥反应的理解来自于使用标准光学显微镜检查移植组织的活组织检查，以及分析活组织中基因的表达。抗体和其他分子聚集在肾脏的小血管中，并吸引各种免疫细胞。这些免疫细胞被“激活”，破坏血管内壁，导致血管壁增厚。最终，这会阻止肾脏过滤血液中的液体和废物。我们仍然不知道哪些免疫细胞是负责任的，它们是如何被激活的，以及这对血管内壁有什么影响。在某种程度上，这是由于在为诊断而进行的人体活检中，在高分辨率和大组织体积下对小血管内的分子和细胞进行成像的困难。对大块组织进行高分辨率成像的最大挑战是时间。要对长10毫米、直径1毫米的活组织检查成像，以确定单个免疫细胞并观察它们攻击血管壁所需的分辨率，一个样本需要30-55年的时间。这显然是不切实际的。为了克服这个问题，我们将开发一套新的成像技术，并将它们结合起来，这样我们就可以跟踪血管，绘制活检中所有的免疫细胞。然后，我们将放大每个细胞，分析蛋白质和基因，生成条形码，以确认它是哪种免疫细胞，以及它是否在破坏血管方面很活跃。高分辨率图像还将帮助我们评估每个细胞是否处于“攻击模式”。为了做到这一点，我们将使用最新的成像技术，并调整每种技术，使它们在人类活组织检查中诊断完成后留下的组织上跨尺度地协同工作。我们将利用德国佩特拉三号同步加速器的x射线能量，以及伦敦弗朗西斯克里克研究所和欧洲分子生物学实验室的尖端光学和电子显微镜。使用这种新的“多模式多尺度”方法，我们将把分析人体活检所需的时间从55年减少到5天。在这个速度下，我们将能够从足够的活组织检查中收集数据，我们可以开始寻找早期和晚期移植排斥患者肾脏的抗体和免疫细胞募集模式。我们将使用人工智能的最新方法分析丰富的数据。我们的宏伟目标是能够绘制出对肾移植的免疫反应的连续阶段，贯穿于每个活检样本，直至纳米级，并最终利用这些信息来预测哪些移植会失败，并为器官排斥的新治疗方法的发展提供信息。

Chronic kidney failure affects about 11% of the world population. Diseases caused by the immune system are the third most common cause of chronic kidney failure. Transplantation is the best available treatment for patients who reach end stage kidney failure, but sadly a transplanted kidney does not last for more than 10-15 years on average, mainly because the recipient of the transplant mounts an immune reaction against the donated kidney, called transplant rejection. In particular, if the recipient of the transplant develops antibodies against the donor tissue, the outcomes are poor. This is referred to as "antibody mediated rejection". Current treatments for antibody-mediated rejection mainly involve removing or blocking the effect of the antibody, but these are not very effective. We need to better understand rejection in order to develop new and better treatments. Our current understanding of rejection comes from examining biopsies of the transplant using a standard light microscope, and from analysing expression of genes in biopsy tissue. Antibodies and other molecules gather in the small blood vessels of the kidney, and attract a variety of immune cells. These immune cells get 'activated' and damage the lining of the blood vessels, causing thickening of the vessel walls. Eventually, this prevents the kidney from filtering fluid and waste from the blood. There is still a lot we don't know about which immune cells are responsible, how they get activated and what effect this has on the lining of the blood vessels. In part this is due to the difficulties in imaging the molecules and cells within the small blood vessels in human biopsies taken for diagnosis, both at high resolution and in large tissue volumes. The great challenge in imaging large pieces of tissue at high resolution is the time it takes. To image a biopsy of 10 mm length and 1 mm diameter at the resolution required to identify individual immune cells and to see them attacking the vessel walls would take 30-55 years for one sample. This is clearly impractical. To overcome this problem, we will develop a suite of new imaging techniques and combine them, so that we can follow vessels and map all of the immune cells in a biopsy. We will then zoom in on each cell, analysing proteins and genes to produce a barcode that confirms what type of immune cell it is and whether it is active in damaging the vessels. High resolution images will also help us to assess whether each cell is in 'attack mode'. To do this, we will use the latest imaging technology available to us, and adapt each technique to make them work together across scales, on tissue left over after diagnosis is complete in human biopsies. We will harness the power of X-rays at the Petra III synchrotron in Germany, and cutting edge light and electron microscopes at the Francis Crick Institute in London and the European Molecular Biology Laboratory. Using this new 'multimodal multiscale' approach, we will reduce the time taken to analyse a human biopsy from 55 years to 5 days. At this speed, we will be able to amass data from enough biopsies that we can start to look for patterns in the recruitment of antibodies and immune cells to the kidneys of patients with transplant rejection, at early and late stages. We will analyse the abundant data using the latest methods in artificial intelligence. Our grand aim is to be able to map successive stages in the immune reaction to the kidney transplant, throughout each biopsy sample, down to the nanoscale, and ultimately to use this information to predict which transplants will fail and to inform the development of new treatments of organ rejection.