Computational modelling human stem cell fitness of pre-leukaemic mutations

白血病前期突变的人类干细胞适应性的计算模型

• 批准号: 2605152
• 金额: --
• 依托单位: University of Edinburgh
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2605152
• 关键词: Computational; modelling; human; stem; cell

This interdisciplinary project will involve the student in a close collaboration between three research groups: Schumacher (computational modelling), Chandra (bioinformatics), and Kirschner (stem cell assays)Age is the single biggest risk factor underlying the onset of many haematological (blood) malignancies. Clonal haematopoiesis of indeterminate potential (CHIP) affects more than 10% of individuals over the age of 60 years and is associated with increased risk for haematological cancers. Little is known about how individual mutations cause clonal outgrowth of blood stem cells and thus contribute to this risk. Knowing the fitness advantage conferred on stem cells by individual CHIP could enable us to predict the risk of progression to leukaemia.The student will be working with data from the Lothian Birth Cohort, a longitudinal cohort of aged individuals, from which we have deeply sequence targeted chromosomal locations in late life over a 15 year span. The student will quantify variant allele frequency (VAF) for CHIP mutations and use mathematical modelling to infer stem cell fitness in vivo. This will allow us to measure how specific CHIP mutations increase stem cell fitness and reveal how they perturb homeostasis (blood production). The results will enable building of an age-dependent predictor of an individual's leukaemic risk based solely on their CHIP mutation frequencies. To test these predictions, we have gained access to Generation Scotland data (20,000 participants). The use of mathematical models will allow us to quantitatively combine both longitudinal data on clonal expansion in vivo over 15 years and in vitro data from the Kirschner lab for increased translational impact, improving our understanding of the effects of CHIP on normal haematopoiesis and how this contributes to leukaemia development.

这个跨学科项目将让学生参与三个研究小组之间的密切合作：舒马赫（计算建模）、钱德拉（生物信息学）和克什纳（干细胞测定）年龄是许多血液恶性肿瘤发病的最大单一风险因素。不确定潜能克隆造血 (CHIP) 影响超过 10% 的 60 岁以上个体，并且与血液癌症风险增加相关。人们对个体突变如何导致造血干细胞克隆生长并从而导致这种风险知之甚少。了解个体 CHIP 赋予干细胞的健康优势可以使我们预测进展为白血病的风险。该学生将使用来自 Lothian 出生队列的数据，这是一个老年个体的纵向队列，我们​​对 15 年跨度的晚年目标染色体位置进行了深度测序。学生将量化 CHIP 突变的变异等位基因频率 (VAF)，并使用数学模型推断干细胞体内的适应性。这将使我们能够测量特定的 CHIP 突变如何提高干细胞的适应性，并揭示它们如何扰乱体内平衡（血液生成）。这些结果将能够仅根据 CHIP 突变频率来构建个体白血病风险的年龄依赖性预测因子。为了测试这些预测，我们获得了苏格兰一代的数据（20,000 名参与者）。数学模型的使用将使我们能够定量结合 15 年来体内克隆扩增的纵向数据和来自 Kirschner 实验室的体外数据，以增加转化影响，加深我们对 CHIP 对正常造血作用的影响以及这如何促进白血病发展的理解。