文章：

整合转录组学和基因组学分析可提高对老年急性髓系白血病患者完全缓解和生存的预测能力

Integrated transcriptomic and genomic analysis improves prediction of complete remission and survival in elderly patients with acute myeloid leukemia

原文发布日期：2020-06-11

DOI: 10.1038/s41408-020-0332-3

类型: Article

开放获取: 是

英文摘要：

Relevant molecular tools for treatment stratification of patients ≥65 years with acute myeloid leukemia (AML) are lacking. We combined clinical data with targeted DNA- and full RNA-sequencing of 182 intensively and palliatively treated patients to predict complete remission (CR) and survival in AML patients ≥65 years. Intensively treated patients with NPM1 and IDH2R172 mutations had longer overall survival (OS), whereas mutated TP53 conferred lower CR rates and shorter OS. FLT3-ITD and TP53 mutations predicted worse OS in palliatively treated patients. Gene expression levels most predictive of CR were combined with somatic mutations for an integrated risk stratification that we externally validated using the beatAML cohort. We defined a high-risk group with a CR rate of 20% in patients with mutated TP53, compared to 97% CR in low-risk patients defined by high expression of ZBTB7A and EEPD1 without TP53 mutations. Patients without these criteria had a CR rate of 54% (intermediate risk). The difference in CR rates translated into significant OS differences that outperformed ELN stratification for OS prediction. The results suggest that an integrated molecular risk stratification can improve prediction of CR and OS and could be used to guide treatment in elderly AML patients.
 

摘要翻译： 

目前缺乏针对年龄≥65岁急性髓系白血病（AML）患者治疗分层的相关分子工具。我们结合182例接受强化与姑息治疗患者的临床资料及靶向DNA与全RNA测序数据，旨在预测高龄AML患者（≥65岁）的完全缓解率（CR）与生存期。研究发现，携带NPM1与IDH2R172突变的强化治疗患者总生存期（OS）更长，而TP53突变则导致CR率降低和OS缩短。在姑息治疗组中，FLT3-ITD与TP53突变预示更差的OS。我们将最具CR预测价值的基因表达水平与体细胞突变整合，建立了综合风险分层模型，并在beatAML队列中完成外部验证。通过该模型界定出高危组（伴TP53突变者CR率为20%）与低危组（无TP53突变且高表达ZBTB7A与EEPD1者CR率达97%），未符合上述标准的患者CR率为54%（中危组）。这种CR率差异转化为显著的总生存期差异，且在OS预测方面优于欧洲白血病网（ELN）风险分层。研究结果表明，整合分子风险分层可提升CR与OS的预测准确性，有望用于指导老年AML患者的临床治疗。

原文链接：

Integrated transcriptomic and genomic analysis improves prediction of complete remission and survival in elderly patients with acute myeloid leukemia