Preleukemic single-cell landscapes reveal mutation-specific mechanisms and gene programs predictive of AML patient outcomes.
Preleukemic single-cell landscapes reveal mutation-specific mechanisms and gene programs predictive of AML patient outcomes.
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白血病前期单细胞图谱揭示了预测AML患者预后的突变特异性机制和基因程序。
DOI：
10.1016/j.xgen.2023.100426
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发表时间：
2023-12-13
期刊：
影响因子：
--
通讯作者：
Gottgens, Berthold
中科院分区：
文献类型：
--
作者：
Isobe, Tomoya;Kucinski, Iwo;Barile, Melania;Wang, Xiaonan;Hannah, Rebecca;Bastos, Hugo P.;Chabra, Shirom;Vijayabaskar, M. S.;Sturgess, Katherine H. M.;Williams, Matthew J.;Giotopoulos, George;Marando, Ludovica;Li, Juan;Rak, Justyna;Gozdecka, Malgorzata;Prins, Daniel;Shepherd, Mairi S.;Watcham, Sam;Green, Anthony R.;Kent, David G.;Vassiliou, George S.;Huntly, Brian J. P.;Wilson, Nicola K.;Gottgens, Berthold
急性骨髓性白血病（AML）和骨髓肿瘤是通过获得体细胞突变而发生的，这些突变赋予造血干细胞和祖细胞突变特异性的适应性优势。然而，我们对突变效应的理解仍然局限于免疫表型和临床上可获得的大量细胞群中可获得的分辨率。为了解释异质细胞对白血病前突变扰动的适应性，我们对8种不同的骨髓恶性肿瘤驱动突变小鼠模型进行了单细胞RNA测序，产生了269，048个单细胞谱。我们的分析推断突变驱动的细胞丰度，细胞谱系命运，细胞代谢和基因表达的扰动在连续分辨率，精确定位细胞群体与分化偏倚相关的转录改变。我们进一步开发了一个11基因评分系统（Stem11）的基础上，白血病前的转录签名，预测AML患者的结果。我们的研究结果表明，白血病前生物学的单细胞分辨率深度表征有可能增强我们对AML异质性的理解，并为更有效的风险分层策略提供信息。八个白血病前期小鼠模型的单细胞造血景观用于单细胞扰动数据集综合分析的流线型管道突变对细胞丰度、命运概率、代谢和基因表达的影响预测AML患者结局的Stem 11谱系扰动特征Isobe et al.分析了来自8个白血病前小鼠模型的造血干细胞和祖细胞的269，048个单细胞转录组，揭示了细胞丰度、分化命运、代谢活性和基因表达的突变特异性扰动。他们进一步开发了Stem 11，这是一种与AML患者结局相关的白血病前谱系扰动特征。
Acute myeloid leukemia (AML) and myeloid neoplasms develop through acquisition of somatic mutations that confer mutation-specific fitness advantages to hematopoietic stem and progenitor cells. However, our understanding of mutational effects remains limited to the resolution attainable within immunophenotypically and clinically accessible bulk cell populations. To decipher heterogeneous cellular fitness to preleukemic mutational perturbations, we performed single-cell RNA sequencing of eight different mouse models with driver mutations of myeloid malignancies, generating 269,048 single-cell profiles. Our analysis infers mutation-driven perturbations in cell abundance, cellular lineage fate, cellular metabolism, and gene expression at the continuous resolution, pinpointing cell populations with transcriptional alterations associated with differentiation bias. We further develop an 11-gene scoring system (Stem11) on the basis of preleukemic transcriptional signatures that predicts AML patient outcomes. Our results demonstrate that a single-cell-resolution deep characterization of preleukemic biology has the potential to enhance our understanding of AML heterogeneity and inform more effective risk stratification strategies. Single-cell hematopoietic landscape of eight preleukemic mouse models Streamlined pipeline for integrated analysis of single-cell perturbation datasets Mutational impact on cell abundance, fate probability, metabolism, and gene expression Stem11 lineage perturbation signature predictive of AML patient outcomes Isobe et al. profiled 269,048 single-cell transcriptomes of hematopoietic stem and progenitor cells from eight preleukemic mouse models, revealing mutation-specific perturbations in cell abundance, differentiation fate, metabolic activity, and gene expression. They further developed Stem11, a preleukemic lineage perturbation signature correlating with AML patient outcomes.
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影响因子：
50.3
作者：
Chen E;Beer PA;Godfrey AL;Ortmann CA;Li J;Costa-Pereira AP;Ingle CE;Dermitzakis ET;Campbell PJ;Green AR
通讯作者：
Green AR
DOI：
10.1056/nejmoa1409405
发表时间：
2014-12-25
期刊：
The New England journal of medicine
影响因子：
--
作者：
Genovese G;Kähler AK;Handsaker RE;Lindberg J;Rose SA;Bakhoum SF;Chambert K;Mick E;Neale BM;Fromer M;Purcell SM;Svantesson O;Landén M;Höglund M;Lehmann S;Gabriel SB;Moran JL;Lander ES;Sullivan PF;Sklar P;Grönberg H;Hultman CM;McCarroll SA
通讯作者：
McCarroll SA
影响因子：
82.9
作者：
Chen, Jiahao;Kao, Yun-Ruei;Steidl, Ulrich
通讯作者：
Steidl, Ulrich
影响因子：
16.6
作者：
Liu Y;Gu Z;Cao H;Kaphle P;Lyu J;Zhang Y;Hu W;Chung SS;Dickerson KE;Xu J
通讯作者：
Xu J
影响因子：
23.9
作者：
Encabo, Hector Huerga;Aramburu, Iker Valle;Bonnet, Dominique
通讯作者：
Bonnet, Dominique