Exploring endometrial cellular heterogeneity and its role in endometriosis using single-cell transcriptomics

子宫内膜是子宫的粘膜内层，在女性的生殖年龄期间经历再生周期。子宫内膜是由上皮细胞、间质成纤维细胞、血管平滑肌细胞、内皮细胞、免疫细胞、血细胞和干/祖细胞组成的异质性结构。在大约10%的育龄妇女中，在子宫腔外发现类似子宫内膜的细胞。这种情况被称为子宫内膜异位症，其特征是雌激素依赖性慢性炎症性疾病。子宫内膜异位症导致生育能力低下，使人衰弱的慢性和周期性疼痛，估计每年在医疗保健和工作损失方面花费英国经济82亿英镑。缺乏可靠的诊断工具以及疾病治疗是由于对子宫内膜异位症的发病机制认识不足。最近由Zondervan教授领导的GWAS研究确定了增加子宫内膜异位症风险的变异;然而，这些因素对疾病发展的贡献仍不清楚。近年来，干细胞也被发现在子宫内膜异位症中发挥作用，但它们在子宫内膜异位症中的确切功能尚不清楚。为了阐明不同类型的细胞在正常子宫内膜功能中的作用以及子宫内膜异位症的发病机制，必须在单细胞水平上研究子宫内膜。传统的“批量”RNA测序一次处理数十万个细胞，从所有分析的细胞中产生平均值。这掩盖了单个细胞的独特特征，阻止了它们的发现和理解它们在组织生理学中的功能和作用。单细胞RNA测序允许单独研究数百至数千个细胞，从而克服组织异质性。单细胞基因表达谱是一种新的方法，可在牛津大学，并将在拟议的研究中使用。这项研究将建立在Hellner博士最近对子宫内膜单细胞RNA测序的初步研究基础上。该项目旨在利用这一尖端技术研究正常和疾病子宫内膜中的人类子宫内膜，产生单个子宫内膜细胞的第一个全面的转录组图谱。研究健康和患病子宫内膜的细胞异质性，并通过单细胞转录组学探索不同的细胞群及其在子宫内膜生物学中的作用。通过单细胞分子谱鉴定可能在疾病发病机制中发挥作用的稀有细胞群，如正常子宫内膜和子宫内膜异位组织中的子宫内膜干细胞和基质免疫细胞，该项目有望在子宫内膜生物学和子宫内膜异位症领域产生大量新知识。这是第一次，健康子宫内膜和子宫内膜异位症组织的转录组图谱将获得，并提供关键的洞察子宫内膜生物学，这是目前稀疏。差异谱将使我们能够改善疾病的分类，并促进未来发现子宫内膜异位症的特异性生物标志物和治疗靶点。从长远来看，这将有助于改善患者的护理。

Endometrium is the inner mucosal lining of the uterus that undergoes cycles of regeneration during a female's reproductive years. It has a heterogeneous architecture, comprising of epithelial cells, stromal fibroblasts, vascular smooth muscle cells, endothelial cells, as well as immune, blood cells, and stem/progenitor cells.In around 10% of women of child bearing age, cells resembling the endometrium are found outside of the uterine cavity. This condition is called endometriosis and is characterised as an oestrogen dependent, chronic inflammatory disease. Endometriosis causes subfertility, debilitating chronic and cyclical pain and is estimated to cost the UK economy £8.2 billion a year in healthcare and loss of work. The lack of reliable diagnostic tools as well as disease treatment is caused by poor understanding of the pathogenesis of endometriosis. A recent GWAS study led by Prof. Zondervan identified variants that increase the risk of developing endometriosis; however, the contribution of these factors to disease development is still unclear. Recently, stem cells have also been found to play a role in endometriosis, but their exact function in endometriosis is still unknown.In order to decipher the role of different cell types in normal endometrial functioning as well as endometriosis pathogenesis, the endometrium has to be studied at the single cell level. Conventional 'Bulk' RNA sequencing processes hundreds of thousands of cells at a time, yielding an average value from all cells analysed. This masks the unique character of individual cells, preventing their discovery and understanding of their function and role in tissue physiology. Single-cell RNA sequencing allows the study of hundreds to thousands of cells individually, thereby overcoming tissue heterogeneity. Single-cell gene expression profiling is a novel method, available in Oxford and will be utilised in the proposed study. The study will build on a recent pilot study by Dr Hellner on endometrial single cell RNA sequencing of the endometrium. The project aims to use this cutting-edge technology to study the human endometrium in both normal and disease endometrium, generating the first, comprehensive transcriptome profile of individual endometrial cells.The proposed study aims to:i. Investigate cellular heterogeneity of both healthy and diseased endometrium and to explore distinct populations of cells and their role in endometrial biology through single cell transcriptomics.ii. Identify rare cell populations, such as endometrial stem cells and stromal immune cells within the normal endometrium and endometriotic tissue, that may play a role in disease pathogenesis, by single cell molecular profiling.The project is expected to yield substantial amount of new knowledge in the field of endometrial biology and endometriosis. For the first time, transcriptome profiles of both healthy endometrium and endometriosis tissue will be obtained and provide crucial insight into endometrial biology, which is currently sparse. The differential profiles will enable us to improve classification of the disease as well as facilitate future discovery of specific biomarkers and therapeutic targets for endometriosis. In the long term this will lead to improved patient care.