A four-gene LincRNA expression signature predicts risk in multiple cohorts of acute myeloid leukemia patients

A four-gene LincRNA expression signature predicts risk in multiple cohorts of acute myeloid leukemia patients
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DOI:
10.1038/leu.2017.210
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发表时间:
2018-02-01
期刊:
影响因子:
11.4
通讯作者:
Pimanda, J. E.
Pimanda, J. E.
中科院分区:
医学1区
文献类型:
--
作者:
Beck, D.;Thoms, J. A. I.;Pimanda, J. E.

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预后基因表达特征已被认为是阐明急性髓系白血病(AML)治疗选择的临床工具。然而,这些特征依赖于测量大量的基因,当应用于独立队列或老年患者时,往往表现不佳。长基因间隔性非编码RNA(LincRNAs)是细胞特性和肿瘤发生的重要调节因子,但对其作为急性髓细胞白血病预后标志物的作用了解有限。在这里,我们分析了来自临床注释的AML患者的多个队列的转录数据,并报告了(I)为编码基因表达而设计的微阵列可以被重新用于产生健壮的lincRNA表达数据,(Ii)一些lincRNA基因位于靠近造血编码基因的位置并且在AML中表现出很强的表达相关性,(Iii)lincRNA基因表达模式区分AML的细胞遗传学和分子亚型,(4)由三个或四个基因组成的lincRNA签名是临床结果的独立预测因素,并进一步将欧洲白血病网络(ELN)风险组的存活率分为两类;(V)基于Logistic回归分析的四个lincRNA基因定量聚合酶链式反应(LINC4)可用于确定急性髓细胞白血病的风险。
Prognostic gene expression signatures have been proposed as clinical tools to clarify therapeutic options in acute myeloid leukemia (AML). However, these signatures rely on measuring large numbers of genes and often perform poorly when applied to independent cohorts or those with older patients. Long intergenic non-coding RNAs (lincRNAs) are emerging as important regulators of cell identity and oncogenesis, but knowledge of their utility as prognostic markers in AML is limited. Here we analyze transcriptomic data from multiple cohorts of clinically annotated AML patients and report that (i) microarrays designed for coding gene expression can be repurposed to yield robust lincRNA expression data, (ii) some lincRNA genes are located in close proximity to hematopoietic coding genes and show strong expression correlations in AML, (iii) lincRNA gene expression patterns distinguish cytogenetic and molecular subtypes of AML, (iv) lincRNA signatures composed of three or four genes are independent predictors of clinical outcome and further dichotomize survival in European Leukemia Net (ELN) risk groups and (v) an analytical tool based on logistic regression analysis of quantitative PCR measurement of four lincRNA genes (LINC4) can be used to determine risk in AML.