解读急性髓系白血病患者基因组数据的复杂性
The complexity of interpreting genomic data in patients with acute myeloid leukemia
原文发布日期:2016-12-16
DOI: 10.1038/bcj.2016.115
类型: Original Article
开放获取: 是
英文摘要:
摘要翻译:
原文链接:
Acute myeloid leukemia (AML) is a heterogeneous neoplasm characterized by the accumulation of complex genetic alterations responsible for the initiation and progression of the disease. Translating genomic information into clinical practice remained challenging with conflicting results regarding the impact of certain mutations on disease phenotype and overall survival (OS) especially when clinical variables are controlled for when interpreting the result. We sequenced the coding region for 62 genes in 468 patients with secondary AML (sAML) and primary AML (pAML). Overall, mutations in FLT3, DNMT3A, NPM1 and IDH2 were more specific for pAML whereas UTAF1, STAG2, BCORL1, BCOR, EZH2, JAK2, CBL, PRPF8, SF3B1, ASXL1 and DHX29 were more specific for sAML. However, in multivariate analysis that included clinical variables, only FLT3 and DNMT3A remained specific for pAML and EZH2, BCOR, SF3B1 and ASXL1 for sAML. When the impact of mutations on OS was evaluated in the entire cohort, mutations in DNMT3A, PRPF8, ASXL1, CBL EZH2 and TP53 had a negative impact on OS; no mutation impacted OS favorably; however, in a cox multivariate analysis that included clinical data, mutations in DNMT3A, ASXL1, CBL, EZH2 and TP53 became significant. Thus, controlling for clinical variables is important when interpreting genomic data in AML.
急性髓系白血病(AML)是一种异质性肿瘤,其特征是积累导致疾病发生和进展的复杂遗传改变。在将基因组信息转化为临床实践的过程中,由于某些突变对疾病表型和总生存期(OS)的影响存在争议性结果,尤其是在解释结果时控制临床变量的情况下,这一转化仍具挑战性。我们对468例继发性AML(sAML)和原发性AML(pAML)患者进行了62个基因编码区的测序。总体而言,FLT3、DNMT3A、NPM1和IDH2突变更特异性见于pAML,而UTAF1、STAG2、BCORL1、BCOR、EZH2、JAK2、CBL、PRPF8、SF3B1、ASXL1和DHX29则更特异性见于sAML。然而,在纳入临床变量的多变量分析中,仅FLT3和DNMT3A仍特异性关联pAML,而EZH2、BCOR、SF3B1和ASXL1特异性关联sAML。在整个队列中评估突变对OS的影响时,DNMT3A、PRPF8、ASXL1、CBL、EZH2和TP53突变对OS产生负面影响;未发现任何突变对OS有利;但在纳入临床数据的Cox多变量分析中,DNMT3A、ASXL1、CBL、EZH2和TP53突变的影响变得显著。因此,在解读AML基因组数据时,控制临床变量至关重要。
The complexity of interpreting genomic data in patients with acute myeloid leukemia
……