Mechanistic characterisation of enhancer hijacking: identifying essential and targetable chromatin interactions

我们的遗传密码就像一本食谱：我们需要指令和成分来制造我们体内的细胞。这些成分被称为基因，在健康细胞中，增强剂提供指令，说明哪些基因应该被激活，以及何时被激活。在血癌患者中，一些增强子被转移到遗传密码中的新位置，因此它们最终开启了错误的基因。这被称为“增强子劫持”，并已被证明有助于癌症的发展。为了了解增强剂如何指导错误的基因，我们需要了解增强剂与健康细胞和癌细胞中的基因之间的联系。我们还需要关闭这些增强剂，以防止通信并记录细胞的反应。通过阻止增强剂与错误的基因交流，我们希望杀死癌细胞。我们可以在实验室中编辑癌细胞的基因组，对增强剂中的区域进行改变，以关闭它们。这可以帮助我们了解增强子劫持是如何工作的，并开发新的治疗方法来逆转劫持的影响(即阻止错误的基因被打开)。然而，确定增强剂最重要的部分是困难的，实验室实验既耗时又昂贵。在这个项目中，我们将开发和测试一个新的计算机程序，它可以识别这些重要的位置，并预测基因组编辑实验的效果。在进入实验室之前，可以使用计算机程序快速模拟实验，尝试许多不同的场景。这将加快和改进实验的针对性，节省时间和金钱，并彻底改变我们设计实验的方式。除此之外，计算机模型将为增强剂如何开启错误的基因而导致疾病，以及基因和增强剂如何进行更广泛的沟通提供新的见解和理解。这项工作很重要，因为我们感兴趣的遗传密码变化在对当前治疗反应不佳的患者中发现。通过了解增强剂如何与基因沟通，我们可以阻止这种相互作用。从长远来看，这将使我们能够开发出只针对癌细胞的更具体的治疗方法，减少治疗的副作用，并改善癌症患者的生活。我们的团队将拥有非常不同技能的研究人员聚集在一起-基于实验室的癌症生物学和计算生物物理学。拥有这两个方面将是推动这项令人兴奋的工作的关键。我们已经成功地合作了三年多，并已经为科学界发表了新的发现。我们将使用的实验方案已经在小组内建立，我们计划建立的计算机模型已经在多个项目中被证明是成功的。通过继续这一成功的合作，与我们的项目合作伙伴一起，我们希望为了解被劫持的增强子如何与基因通信做出重大贡献。如果成功，这种方法可以应用于许多不同的癌症，其中包括增强子劫持。

Our genetic code is like a recipe book: we need instructions and ingredients to produce the cells within our body. The ingredients are called genes, and in healthy cells, enhancers provide the instructions that say which genes are to be switched on and when. In patients with blood cancers, some enhancers get moved to new locations within the genetic code, and because of this they end up switching on the wrong gene. This is known as 'enhancer hijacking' and has been shown to contribute to the development of cancer. To understand how enhancers instruct the wrong genes we need to learn about the communication between enhancers and genes in both healthy and cancer cells. We also need to shut down these enhancers to prevent communication and record the response of the cells. By stopping enhancers communicating with the wrong genes, we hope to kill the cancer cells.We can edit the genomes of cancer cells in the laboratory, making alterations to regions within enhancers to shut them down. This can help us understand how enhancer hijacking works, and develop new treatments to reverse the effects of the hijacking (i.e., to stop the wrong genes from being switched on). However, identifying the most important parts of the enhancers is difficult, and the laboratory experiments are time consuming and expensive. In this project, we will develop and test a new computer programme which can identify these important sites, and predict the effects of the genome editing experiments. It will be possible to quickly mimic an experiment using the computer programme, trying many different scenarios before going into the lab. This will accelerate and improve the targeting of the experiments, saving time and money, and revolutionise the way we design our experiments. As well as this, the computer models will provide new insight and understanding of how enhancers switch on the wrong genes to cause disease, and how genes and enhancers communicate more generally. This work is important because the changes to the genetic code that we are interested in are found in patients who do not respond well to current treatments. By understanding how enhancers communicate with genes, we can look to block this interaction. In the longer term, this will enable us to develop more specific treatments that only target the cancer cells, reducing side-effects of treatment and improving the lives of those living with cancer.Our team brings together researchers with very different skill sets - laboratory-based cancer biology and computational biophysics. Having both of these aspects will be crucial for taking this exciting work forward. We have successfully worked together for over three years and have already published new findings for the scientific community. The experimental protocols that we will use are already established within the group and the computer model that we plan to build on has already proved successful in multiple projects. By continuing this successful collaboration, together with our project partners, we hope to make significant contributions to knowledge about how hijacked enhancers communicate with genes. If successful this approach could be applied to many different cancers which involve enhancer hijacking.