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血液转录组的状态过渡建模预测慢性髓性白血病的疾病演变和治疗反应

David E Frankhouser¹, Russell C Rockne², Lisa Uechi³

¹Department of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope National Medical Center, Duarte, CAL, 91010, USA. dfrankhouser@coh.org.

|February 2, 2024

概括

这项研究引入了基于转录组的模型,以预测慢性髓性白血病 (CML) 的进展和治疗反应. 这些模型显示了在身体症状出现之前早期临床干预的潜力.

科学领域:

在瘤学瘤学.
计算生物学计算生物学
基因组学就是基因组学.

背景情况:

慢性髓性白血病 (CML) 是由BCR::ABL驱动的,由氨酸激酶抑制剂 (TKIs) 作为向.
试管婴儿治疗诱导缓解,但不是治愈,需要新的治疗和预测策略.
CML作为测试基于转录基因组的状态过渡模型的模型,用于预测癌症演变.

研究的目的:

开发和验证基于转录组的状态过渡模型,用于预测CML进展和TKI治疗反应.
为了确定驱动CML状态转换的关键基因.
评估CML进展的可逆性和TKI治疗对疾病转录组的影响.

主要方法:

从BCR::ABL诱导的转基因小鼠和对照群收集了时间序列的血液样本.
从转录基因数据构建了一个CML状态空间和潜在景观.
根据基因表达模式和潜在的景观相似性,确定了疾病状态和驱动基因.

主要成果:

开发了一个三井白血病潜在景观,定义CML疾病状态.
识别了具有抗白血病基因的早期状态和具有亲白血病基因的晚期状态.
状态过渡模型使用初始转录基因数据准确预测疾病进展和TKI反应.

结论:

基于转录组的状态过渡模型可以准确预测CML演变和治疗结果.
疾病进展可能涉及不可逆转的转变,TCI治疗只能产生中间缓解.
这些模型提供了一种潜在的策略,可以在表型变化明显之前定时临床干预.

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