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T 细胞的遗传特征鉴定出 T-ALL 的合成致死性。

Genetic landscape of T cells identifies synthetic lethality for T-ALL.

机构信息

Department of Developmental Immunology, Max Planck Institute of Immunobiology and Epigenetics, 79108, Freiburg, Germany.

Laboratory of Neurogenetics, National Institute of Alcohol Abuse and Alcoholism (NIAAA), National Institutes of Health (NIH), Bethesda, MD, USA.

出版信息

Commun Biol. 2021 Oct 20;4(1):1201. doi: 10.1038/s42003-021-02694-x.

Abstract

To capture the global gene network regulating the differentiation of immature T cells in an unbiased manner, large-scale forward genetic screens in zebrafish were conducted and combined with genetic interaction analysis. After ENU mutagenesis, genetic lesions associated with failure of T cell development were identified by meiotic recombination mapping, positional cloning, and whole genome sequencing. Recessive genetic variants in 33 genes were identified and confirmed as causative by additional experiments. The mutations affected T cell development but did not perturb the development of an unrelated cell type, growth hormone-expressing somatotrophs, providing an important measure of cell-type specificity of the genetic variants. The structure of the genetic network encompassing the identified components was established by a subsequent genetic interaction analysis, which identified many instances of positive (alleviating) and negative (synthetic) genetic interactions. Several examples of synthetic lethality were subsequently phenocopied using combinations of small molecule inhibitors. These drugs not only interfered with normal T cell development, but also elicited remission in a model of T cell acute lymphoblastic leukaemia. Our findings illustrate how genetic interaction data obtained in the context of entire organisms can be exploited for targeted interference with specific cell types and their malignant derivatives.

摘要

为了以无偏倚的方式捕获调控未成熟 T 细胞分化的全局基因网络,在斑马鱼中进行了大规模正向遗传筛选,并结合遗传相互作用分析。ENU 诱变后,通过减数重组作图、定位克隆和全基因组测序鉴定与 T 细胞发育失败相关的遗传损伤。通过进一步的实验,鉴定并证实了 33 个基因中的隐性遗传变异是致病原因。这些突变影响 T 细胞的发育,但不干扰无关细胞类型——生长激素表达的生长激素细胞的发育,为遗传变异的细胞类型特异性提供了一个重要的衡量标准。随后的遗传相互作用分析建立了包含鉴定出的成分的遗传网络结构,该分析鉴定了许多正(缓解)和负(合成)遗传相互作用的实例。随后使用小分子抑制剂组合对几种合成致死性的例子进行了表型模拟。这些药物不仅干扰了正常的 T 细胞发育,而且在 T 细胞急性淋巴细胞白血病的模型中也引发了缓解。我们的研究结果说明了如何在整个生物体的背景下获得的遗传相互作用数据可以被用于针对特定细胞类型及其恶性衍生物的靶向干预。

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