Genomic Classification and Prognosis in Acute Myeloid Leukemia.
Genomic Classification and Prognosis in Acute Myeloid Leukemia.
复制标题
DOI：
10.1056/nejmoa1516192
复制
发表时间：
2016-06-09
期刊：
影响因子：
--
通讯作者：
Campbell PJ
中科院分区：
文献类型：
--
作者：
Papaemmanuil E;Gerstung M;Bullinger L;Gaidzik VI;Paschka P;Roberts ND;Potter NE;Heuser M;Thol F;Bolli N;Gundem G;Van Loo P;Martincorena I;Ganly P;Mudie L;McLaren S;O'Meara S;Raine K;Jones DR;Teague JW;Butler AP;Greaves MF;Ganser A;Döhner K;Schlenk RF;Döhner H;Campbell PJ
最近的研究提供了一个详细的普查基因突变的急性髓细胞白血病（AML）。我们的下一个挑战是了解这种遗传多样性如何定义AML的病理生理学并为临床实践提供信息。我们共招募了1540名患者参加三项强化治疗的前瞻性试验。结合111个癌症基因的驱动突变与细胞遗传学和临床数据，我们定义了AML基因组亚组及其与临床结局的相关性。我们在76个基因或基因组区域中确定了5234个驱动突变，在86%的患者中确定了2个或更多驱动突变。共突变模式将队列划分为11类，每类具有不同的诊断特征和临床结果。除了目前定义的AML亚组外，还出现了三种异质性基因组类别：编码染色质、RNA剪接调节因子或两者的基因突变的AML（18%的患者）; TP 53突变、染色体非整倍性或两者均存在的AML（13%）;以及IDH 2 R172突变的AML（1%）。染色质剪接体和TP 53非整倍体AML患者的预后较差，各种类别定义突变对预后的贡献是独立和相加的。除了分类定义的病变，其他共同发生的驱动突变也对总生存率有实质性影响。单个突变的预后影响通常会因其他驱动突变的存在或不存在而显著改变。这种基因-基因相互作用在NPM 1突变的AML中尤其明显，其中共突变的模式确定了具有有利或不利预后的组。这些预测需要在前瞻性临床试验中验证。AML中的驱动因素景观揭示了不同的分子亚组，反映了AML演变中的离散路径，为疾病分类和预后分层提供了信息。（由Wellcome Trust和其他人资助; ClinicalTrials.gov编号，NCT 00146120。
Recent studies have provided a detailed census of genes that are mutated in acute myeloid leukemia (AML). Our next challenge is to understand how this genetic diversity defines the pathophysiology of AML and informs clinical practice. We enrolled a total of 1540 patients in three prospective trials of intensive therapy. Combining driver mutations in 111 cancer genes with cytogenetic and clinical data, we defined AML genomic subgroups and their relevance to clinical outcomes. We identified 5234 driver mutations across 76 genes or genomic regions, with 2 or more drivers identified in 86% of the patients. Patterns of co-mutation compartmentalized the cohort into 11 classes, each with distinct diagnostic features and clinical outcomes. In addition to currently defined AML subgroups, three heterogeneous genomic categories emerged: AML with mutations in genes encoding chromatin, RNA-splicing regulators, or both (in 18% of patients); AML with TP53 mutations, chromosomal aneuploidies, or both (in 13%); and, provisionally, AML with IDH2R172 mutations (in 1%). Patients with chromatin–spliceosome and TP53–aneuploidy AML had poor outcomes, with the various class-defining mutations contributing independently and additively to the outcome. In addition to class-defining lesions, other co-occurring driver mutations also had a substantial effect on overall survival. The prognostic effects of individual mutations were often significantly altered by the presence or absence of other driver mutations. Such gene–gene interactions were especially pronounced for NPM1-mutated AML, in which patterns of co-mutation identified groups with a favorable or adverse prognosis. These predictions require validation in prospective clinical trials. The driver landscape in AML reveals distinct molecular subgroups that reflect discrete paths in the evolution of AML, informing disease classification and prognostic stratification. (Funded by the Wellcome Trust and others; ClinicalTrials.gov number, NCT00146120.)