Transcriptional assessment of haematopoietic differentiation to risk-stratify acute lymphoblastic leukaemia

造血分化的转录评估对急性淋巴细胞白血病的风险分层

• 批准号: MR/Y009568/1
• 负责人: Laura Jardine
• 金额: $ 182.1万
• 依托单位: Newcastle University
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FY009568%2F1
• 关键词: Transcriptional; assessment; haematopoietic; differentiation; risk

B-cell acute lymphoblastic leukaemia (B-ALL) is a life-threatening blood cancer which can affect both the young and the elderly. Many children with B-ALL can now be cured, but the outlook for adults is less favourable. In treating B-ALL there are two main challenges:1) Identifying which children can be cured with less treatment. B-ALL treatment is long and challenging. It has psychological, social and educational consequences for children and families. It also increases the risk of health problems in later life, such as heart disease, bone or joint problems and infertility. 2) Identifying which adults are least likely to be cured with standard treatments. Options for these patients include using new combinations of drugs and therapies that harness the anti-cancer functions of the immune system. To personalise treatment in this way, we need to accurately predict the risk of leukaemia relapsing (coming back after treatment). At present, we predict risk using the patient's age, white blood cell count at diagnosis and certain changes in the leukaemia DNA (the genetic instructions of the leukaemia cell). It may be possible to improve this prediction by adding measurements of RNA (an indication of which DNA instructions the leukaemia cell is currently using).In recent work, I matched signals from leukaemia RNA to signals from the RNA of healthy maturing blood cells. This 'fingerprint of maturation' allowed me to separate the known subgroups of B-ALL, which are based on DNA changes. Subgroups with a higher risk of relapse had more 'immature' signals. However, signals varied between patients, and it isn't yet clear what this means.In the following work, I aim to:1) Ensure that the method for matching signals is sensitive to maturation and reliable across RNA datasets 2) Test whether immature signals correlate with relapse risk, by comparing signals in leukaemia cells from patients who relapsed versus patients who were cured3) Compare the maturation extremes within subgroups of B-ALL to understand what changes in DNA structure, DNA readability, and RNA affect maturationWith these insights, I will establish whether determining the RNA 'fingerprint of maturation' could improve our predictions of relapse risk. If successful, this method could support personalised B-ALL treatment decisions. Further exploration of the data could help identify ways of changing B-ALL maturation to modify how the leukaemia cells behave and respond to treatment. All RNA data generated will be shared with the research community to maximise scientific advances in this disease.

B细胞急性淋巴细胞白血病（B-All）是一种威胁生命的血液癌，可能影响年轻人和老年人。现在可以治愈许多B-All的孩子，但是成人的前景不太有利。在治疗B-All时，有两个主要挑战：1）确定可以减少治疗方法可以治愈哪些儿童。 B-所有治疗都是漫长而又具有挑战性的。它对儿童和家庭产生心理，社会和教育后果。它还增加了以后生活中健康问题的风险，例如心脏病，骨骼或关节问题和不育。 2）确定哪些成年人最不可能使用标准治疗方法治愈。这些患者的选择包括使用新的药物和疗法组合，以利用免疫系统的抗癌功能。要以这种方式进行个性化治疗，我们需要准确预测白血病复发的风险（治疗后恢复）。目前，我们预测使用患者的年龄，诊断时的白细胞计数以及白血病DNA（白血病细胞的遗传指示）的风险。可以通过添加RNA的测量值来改善这种预测（DNA指示白血病细胞目前正在使用的指示）。在最近的工作中，我将白血病RNA的信号与来自健康成熟血细胞的RNA的信号匹配。这种“成熟的指纹”使我能够将基于DNA变化的B-all的已知亚组分开。复发风险较高的亚组具有更多的“未成熟”信号。 However, signals varied between patients, and it isn't yet clear what this means.In the following work, I aim to:1) Ensure that the method for matching signals is sensitive to maturation and reliable across RNA datasets 2) Test whether immature signals correlate with relapse risk, by comparing signals in leukaemia cells from patients who relapsed versus patients who were cured3) Compare the maturation extremes within subgroups of B-ALL to understand what changes in DNA结构，DNA的可读性和RNA会影响到这些见解，我将确定确定RNA的“成熟指纹”是否可以改善我们对复发风险的预测。如果成功，此方法可以支持个性化的B-所有治疗决策。进一步探索数据可以帮助确定改变B-所有成熟的方法，以修改白血病细胞的表现并对治疗做出反应。生成的所有RNA数据将与研究界共享，以最大程度地提高该疾病的科学进步。