Functional genomic landscape of acute myeloid leukaemia.
Functional genomic landscape of acute myeloid leukaemia.
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DOI：
10.1038/s41586-018-0623-z
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发表时间：
2018-10
期刊：
影响因子：
64.8
通讯作者：
Druker BJ
中科院分区：
文献类型：
--
作者：
Tyner JW;Tognon CE;Bottomly D;Wilmot B;Kurtz SE;Savage SL;Long N;Schultz AR;Traer E;Abel M;Agarwal A;Blucher A;Borate U;Bryant J;Burke R;Carlos A;Carpenter R;Carroll J;Chang BH;Coblentz C;d'Almeida A;Cook R;Danilov A;Dao KT;Degnin M;Devine D;Dibb J;Edwards DK 5th;Eide CA;English I;Glover J;Henson R;Ho H;Jemal A;Johnson K;Johnson R;Junio B;Kaempf A;Leonard J;Lin C;Liu SQ;Lo P;Loriaux MM;Luty S;Macey T;MacManiman J;Martinez J;Mori M;Nelson D;Nichols C;Peters J;Ramsdill J;Rofelty A;Schuff R;Searles R;Segerdell E;Smith RL;Spurgeon SE;Sweeney T;Thapa A;Visser C;Wagner J;Watanabe-Smith K;Werth K;Wolf J;White L;Yates A;Zhang H;Cogle CR;Collins RH;Connolly DC;Deininger MW;Drusbosky L;Hourigan CS;Jordan CT;Kropf P;Lin TL;Martinez ME;Medeiros BC;Pallapati RR;Pollyea DA;Swords RT;Watts JM;Weir SJ;Wiest DL;Winters RM;McWeeney SK;Druker BJ
急性髓性白血病的靶向治疗的实施受到了患者内和患者间复杂突变模式以及缺乏大多数突变事件的药理学药物的挑战。在这里，我们报告了Beat AML项目对从562名患者中收集的672份肿瘤标本的初步发现。我们使用全外显子组测序、RNA测序和离体药物敏感性分析来评估这些标本。我们的数据揭示了以前在AML中未检测到的新突变事件。我们显示了药物反应与突变状态的关联，包括特定于组合突变事件的药物敏感性的实例。与RNA测序的整合还揭示了基因表达特征，其预测了特定基因网络在药物反应中的作用。总的来说，本报告提供了一个数据集，可通过Beat AML数据查看器（www.vizome.org）访问，可用于解决AML生物学的临床，基因组，转录组和功能调查。
The implementation of targeted therapies for acute myeloid leukemia has been challenged by complex mutational patterns within and across patients as well as a dearth of pharmacologic agents for most mutational events. Here, we report initial findings from the Beat AML program on a cohort of 672 tumor specimens collected from 562 patients. We assessed these specimens using whole exome sequencing, RNA-sequencing, and ex vivo drug sensitivity analyses. Our data reveal novel mutational events not previously detected in AML. We show association of drug response with mutational status, including instances of drug sensitivity that are specific to combinatorial mutational events. Integration with RNA-sequencing also revealed gene expression signatures, which predict a role of specific gene networks in drug response. Collectively, this report offers a dataset, accessible by the Beat AML data viewer (www.vizome.org), that can be leveraged to address clinical, genomic, transcriptomic, and functional inquiries into the biology of AML.