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急性髓系白血病的分子治疗

Molecular therapy for acute myeloid leukaemia.

作者信息

Coombs Catherine C, Tallman Martin S, Levine Ross L

机构信息

Leukemia Service, Department of Medicine, Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, New York 10065, USA.

Weill Cornell Medical Center, 1300 York Avenue, New York, New York 10065, USA.

出版信息

Nat Rev Clin Oncol. 2016 May;13(5):305-18. doi: 10.1038/nrclinonc.2015.210. Epub 2015 Dec 1.

Abstract

Acute myeloid leukaemia (AML) is a heterogeneous disease that is, in general, associated with a very poor prognosis. Multiple cytogenetic and molecular abnormalities that characterize different forms of AML have been used to better prognosticate patients and inform treatment decisions. Indeed, risk status in patients with this disease has classically been based on cytogenetic findings; however, additional molecular characteristics have been shown to inform risk assessment, including FLT3, NPM1, KIT, and CEBPA mutation status. Advances in sequencing technology have led to the discovery of novel somatic mutations in tissue samples from patients with AML, providing deeper insight into the mutational landscape of the disease. The majority of patients with AML (>97%) are found to have a clonal somatic abnormality on mutational profiling. Nevertheless, our understanding of the utility of mutation profiling in clinical practice remains incomplete and is continually evolving, and evidence-based approaches to application of these data are needed. In this Review, we discuss the evidence-base for integrating mutational data into treatment decisions for patients with AML, and propose novel therapeutic algorithms in the era of molecular medicine.

摘要

急性髓系白血病(AML)是一种异质性疾病,总体预后通常很差。多种细胞遗传学和分子异常是不同形式AML的特征,已被用于更好地预测患者预后并为治疗决策提供依据。事实上,该疾病患者的风险状态传统上基于细胞遗传学结果;然而,其他分子特征已被证明可用于风险评估,包括FLT3、NPM1、KIT和CEBPA突变状态。测序技术的进步导致在AML患者的组织样本中发现了新的体细胞突变,从而更深入地了解了该疾病的突变图谱。大多数AML患者(>97%)在突变分析中被发现存在克隆性体细胞异常。尽管如此,我们对突变分析在临床实践中的效用的理解仍然不完整且不断发展,因此需要基于证据的方法来应用这些数据。在本综述中,我们讨论将突变数据整合到AML患者治疗决策中的证据基础,并提出分子医学时代的新型治疗算法。

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