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Type: Journal article
Title: A four-gene lincRNA expression signature predicts risk in multiple cohorts of acute myeloid leukemia patients
Author: Beck, D.
Thoms, J.
Palu, C.
Herold, T.
Shah, A.
Olivier, J.
Boelen, L.
Huang, Y.
Chacon, D.
Brown, A.
Babic, M.
Hahn, C.
Perugini, M.
Zhou, X.
Huntly, B.
Schwarzer, A.
Klusmann, J.-H.
Berdel, W.
Wörmann, B.
Büchner, T.
et al.
Citation: Leukemia, 2018; 32(2):263-272
Publisher: Springer Nature
Issue Date: 2018
ISSN: 0887-6924
Statement of
D Beck, JAI Thoms, C Palu, T Herold, A Shah, J Olivier, L Boelen, Y Huang, D Chacon, A Brown, M Babic, C Hahn, M Perugini, X Zhou, BJ Huntly, A Schwarzer, J-H Klusmann, WE Berdel, B Wörmann, T Büchner, W Hiddemann, SK Bohlander, LB To, HS Scott, ID Lewis, RJ D’Andrea, JWH Wong, and JE Pimanda
Abstract: 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.
Keywords: Humans
Risk Assessment
Risk Factors
Gene Expression Profiling
Middle Aged
Leukemia, Myeloid, Acute
Young Adult
RNA, Long Noncoding
Rights: © 2018 Macmillan Publishers Limited, part of Springer Nature. All rights reserved
DOI: 10.1038/leu.2017.210
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