Multi-modal Discovery of Mechanistic Drivers of Pulmonary Fibrosis

特发性肺纤维化(IPF)是以肺部瘢痕形成(纤维化)为特征的进行性肺部疾病。这种疤痕会使肺部变形，降低肺部吸氧的能力，从而使人感到呼吸困难和咳嗽。目前尚不清楚为什么一些人会患上IPF，但IPF患者往往进展很快而死亡，而且没有治愈方法。在英国，每年有6000人死于IPF，超过大多数癌症的死亡人数，超过卵巢癌、宫颈癌和甲状腺癌的总和。这使得IPF成为一种值得研究的重要疾病。目前认为，排列在肺内的细胞(上皮细胞)的基因变化使它们容易受到损伤和疤痕形成，尽管这些基因变化如何促进疤痕形成仍不清楚。肺疤痕形成的主要特征是，由于形成疤痕组织的细胞异常高活性，肺部变得小而僵硬。众所周知，排列在小气道上的细胞的遗传变化会导致粘液的产生增加，我们认为这会使排列在气囊(肺泡)上的细胞变得更加僵硬，无法以正常的方式对损伤做出反应。当肺受损时，受损的细胞死亡，需要由新细胞取代，新细胞来自一种特殊类型的气囊细胞，称为肺泡2型细胞。然而，在疤痕肺中，这些细胞开始改变为衬里细胞，但停留在既不是专门化也不是衬里细胞的过渡状态，我们认为这与粘液堆积和肺僵硬增加有关。研究表明，当肺细胞在僵硬的环境中生长时，比如在有疤痕的肺内，它们会变得更加活跃，产生更多的疤痕组织。然而，机械力如何影响IPF中发现的基因变化的细胞，或者基因变化如何影响上皮细胞发出的信号以及受损上皮细胞经历的命运仍是未知的。重要的是，通过调整肺内的机械力来改变细胞的命运是可能的，目前尚不清楚。这项工作计划将使用一些截然不同但相互补充的科学技术，包括遗传学、细胞和分子生物学、生物信息学、生物工程和生物物理学，以了解这些相互作用，并确定我们是否可以改变肺细胞的命运，并通过改变它们存在的机械环境来重新编程它们。这项研究将带来来自广泛学科的世界领先科学家，试图找到新的见解，以减轻这种毁灭性疾病的痛苦。该方案将侧重于一个关键的细胞过程，该过程可能将与IPF相关的已知遗传、分子、细胞和机械故障联系起来。这个项目的目的是了解1)在肺的小气囊中是否发生了一种称为细胞挤出的过程，通过这种过程，异常的或多余的细胞被挤出细胞层2)了解这一过程在疤痕肺中是如何改变的，以及是否可以改变它以促进肺愈合3)了解细胞生活的环境可以影响它们的行为4)使用人工智能和深度学习算法来学习我们在目标1到3中的实验并为其提供信息。

Idiopathic pulmonary fibrosis (IPF) is a progressive lung condition characterised by scarring (fibrosis) of the lungs. This scarring deforms the lungs and reduces the ability of the lungs to take in oxygen, which causes a person to feel breathless and cough. It is not clear why some people develop IPF, but people with IPF often progress quickly to death and there is no cure. Each year 6000 people in the UK die of IPF, more than deaths from most cancers, and more than ovarian, cervical and thyroid cancers combined. This makes IPF an important disease to research. It is currently thought that genetic changes in the cells that line the lung (epithelial cells) make them susceptible to injury and scar formation, although, how these genetic changes promote scarring remains unknown. The main feature of lung scarring is that the lungs become small and stiff due to the abnormally high activity of cells that make scar tissue. It is known that genetic changes in cells that line the small airways lead to the production of increased mucous which we believe makes the cells that line the airsacs (alveoli) stiffer and unable to respond to injury in a normal way. When the lung is damaged the injured cells die and need to be replaced by new cells that originated from a special type of airsac cell called (an alveolar type 2 cell) however in scarred lung these cells begin to change to the lining cells but get stuck in a transitional state that is neither a specialised nor lining cell which we believe is related to the build up of mucous and increased stiffness of the lung. Research has shown that when lung cells grow in stiff surroundings, such as that within a scarred lung, they become even more active and produce more scar tissue. However, how mechanical forces affect cells with genetic changes found in IPF, or how the genetic changes affect the signals the that epithelial cells send and the fate that injured epithelial cells undergo remains unknown. Importantly it is possible to change the cell fate through adapting the mechanical forces within the lung is not currently known.This programme of work will use a number of distinct but complementary scientific techniques including genetics, cell and molecular biology, bioinformatics, bioengineering and biophysics to understand these interactions and determine whether we can alter the fate of lung cells and reprogram them by changing the mechanical environment they exist.This study will bring world leading scientist from a wide range of disciplines to try and find new insights to alleviate the suffering from this devastating disease. The programme will focus on a key cellular process which could link the known genetic, molecular, cellular and mechanical faults that are associated with IPF. The aim of this project is to understand 1) whether a process called cellular extrusion by which abnormal, or excess cells are squeezed out of cell layers occurs in the small airsacs of the lung 2) understand how this process is altered in scarred lung and whether it can be changed to promote lung healing 3) understand the environment in which the cells live can affect how they behave 4) use artificial intelligence and deep learning algorithms to both learn from and inform our experiment in aims 1 to 3.