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Genomics of Acute Myeloid Leukemia Diagnosis and Pathways

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JOURNAL OF CLINICAL ONCOLOGY
卷 35, 期 9, 页码 934-946

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AMER SOC CLINICAL ONCOLOGY
DOI: 10.1200/JCO.2016.71.2208

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  1. Deutsche Forschungsgemeinschaft (DFG) [Sonderforschungsbereich (SFB) 1074]
  2. DFG [BU 1339/8-1]
  3. Else Kroner-Fresenius-Stiftung [2014_A298]

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In recent years, our understanding of the molecular pathogenesis of myeloid neoplasms, including acute myeloid leukemia (AML), has been greatly advanced by genomics discovery studies that use novel high-throughput sequencing techniques. AML, similar to most other cancers, is characterized by multiple somatically acquired mutations that affect genes of different functional categories, a complex clonal architecture, and disease evolution over time. Patterns of mutations seem to follow specific and temporally ordered trajectories. Mutations in genes encoding epigenetic modifiers, such as DNMT3A, ASXL1, TET2, IDH1, and IDH2, are commonly acquired early and are present in the founding clone. The same genes are frequently found to be mutated in elderly individuals along with clonal expansion of hematopoiesis that confers an increased risk for the development of hematologic cancers. Furthermore, such mutations may persist after therapy, lead to clonal expansion during hematologic remission, and eventually lead to relapsed disease. In contrast, mutations involving NPM1 or signaling molecules (eg, FLT3, RAS) typically are secondary events that occur later during leukemogenesis. Genetic data are now being used to inform disease classification, risk stratification, and clinical care of patients. Two new provisional entities, AML with mutated RUNX1 and AML with BCR-ABL1, have been included in the current update of the WHO classification of myeloid neoplasms and AML, and mutations in three genes-RUNX1, ASXL1, and TP53-have been added in the risk stratification of the 2017 European LeukemiaNet recommendations for AML. Integrated evaluation of baseline genetics and assessment of minimal residual disease are expected to further improve risk stratification and selection of postremission therapy. Finally, the identification of disease alleles will guide the development and use of novel molecularly targeted therapies. (C) 2017 by American Society of Clinical Oncology

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