Understanding the leukaemic niche: computational modeling of intercellular signaling networks in the bone marrow microenvironment

关键词：scRNA-Seq，细胞-细胞通讯，计算模型，癌症慢性髓性白血病（CML）是由患者骨髓（BM）中表达癌基因的干细胞群引起的。越来越多的证据表明，这些白血病干细胞（LSC）破坏骨髓微环境或“生态位”以维持疾病，这是通过改变特定细胞群之间的配体/受体信号来实现的。这个令人兴奋的跨学科项目的首要目标是确定在白血病基底细胞中哪些相互作用是不受控制的，从而为临床确定新的治疗干预措施。DTP候选人将开发、优化和测试新的计算方法，使用多个公开可用的scRNA-seq数据集，在正常BM生态位的相关细胞群体之间构建概率细胞间信号网络。然后，他们将整合从原发性CML样本中产生的表达数据，以评估LSC存在时该网络如何受到干扰，并最终确定这种疾病的新型治疗干预的潜在靶点。特别令人感兴趣的是对当前治疗反应较差的分层患者队列。这个令人兴奋的临床重点项目将为DTP候选人提供获得计算和实验技能的机会，并将由格拉斯哥大学和爱丁堡大学之间的跨学科团队监督。

Studentship strategic priority area:Quantitative Systems MedicineKeywords: scRNA-Seq, Cell-cell communication, computational modelling, cancerChronic myeloid leukaemia (CML) is caused by a population of oncogene expressing stem cells resident in the bone marrow (BM) of patients. There is increasing evidence that these leukaemic stem cells (LSC) disrupt the BM microenvironment or "niche" to maintain the disease, and that this is achieved through altered ligand/receptor signaling between particular cellular populations. The overarching objective of this exciting interdisciplinary project is to identify which interactions are deregulated in the leukaemic BM, thereby identifying novel therapeutic interventions for the clinic.The DTP candidate will develop, optimize and test novel computational methodologies to construct a probabilistic intercellular signaling network between relevant cellular populations in the normal BM niche using multiple, publicly-available scRNA-seq datasets. They will then incorporate expression data generated from primary CML samples to assess how this network is perturbed in the presence of LSC and ultimately identify potential targets for novel therapeutic intervention in this disease. Of particular interest is a stratified patient cohort exhibiting a poor response to current treatments. This exciting and clinically focused project will offer the DTP candidate the opportunity to gain both computational and experimental skills, and will be supervised by an interdisciplinary team between the Universities of Glasgow and Edinburgh.