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

Beck, D; Thoms, JAI; 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, BJ; Schwarzer, A; Klusmann, JH; Berdel, WE; Wörmann, B; Büchner, T; Hiddemann, W; Bohlander, SK; To, LB; Scott, HS; Lewis, ID; D'Andrea, RJ; Wong, JWH; Pimanda, JE

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

Beck, D Thoms, JAI Palu, C Herold, T Shah, A Olivier, J Boelen, L Huang, Y

Brown, A Babic, M Hahn, C Perugini, M Zhou, X Huntly, BJ Schwarzer, A Klusmann, JH Berdel, WE Wörmann, B Büchner, T Hiddemann, W Bohlander, SK To, LB Scott, HS Lewis, ID D'Andrea, RJ Wong, JWH Pimanda, JE

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Publication Type:: Journal Article
Citation:: Leukemia, 2018, 32 (2), pp. 263 - 272
Issue Date:: 2018-02-01

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Field	Value	Language
dc.contributor.author	Beck, D	en_US
dc.contributor.author	Thoms, JAI	en_US
dc.contributor.author	Palu, C	en_US
dc.contributor.author	Herold, T	en_US
dc.contributor.author	Shah, A	en_US
dc.contributor.author	Olivier, J	en_US
dc.contributor.author	Boelen, L	en_US
dc.contributor.author	Huang, Y https://orcid.org/0000-0002-7003-3110	en_US
dc.contributor.author	Chacon, D https://orcid.org/0000-0003-3729-1385	en_US
dc.contributor.author	Brown, A	en_US
dc.contributor.author	Babic, M	en_US
dc.contributor.author	Hahn, C	en_US
dc.contributor.author	Perugini, M	en_US
dc.contributor.author	Zhou, X	en_US
dc.contributor.author	Huntly, BJ	en_US
dc.contributor.author	Schwarzer, A	en_US
dc.contributor.author	Klusmann, JH	en_US
dc.contributor.author	Berdel, WE	en_US
dc.contributor.author	Wörmann, B	en_US
dc.contributor.author	Büchner, T	en_US
dc.contributor.author	Hiddemann, W	en_US
dc.contributor.author	Bohlander, SK	en_US
dc.contributor.author	To, LB	en_US
dc.contributor.author	Scott, HS	en_US
dc.contributor.author	Lewis, ID	en_US
dc.contributor.author	D'Andrea, RJ	en_US
dc.contributor.author	Wong, JWH	en_US
dc.contributor.author	Pimanda, JE	en_US
dc.date.available	2017-06-21	en_US
dc.date.issued	2018-02-01	en_US
dc.identifier.citation	Leukemia, 2018, 32 (2), pp. 263 - 272	en_US
dc.identifier.issn	0887-6924	en_US
dc.identifier.uri	http://hdl.handle.net/10453/131979
dc.description.abstract	© 2018 Macmillan Publishers Limited, part of Springer Nature. All rights reserved. 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.	en_US
dc.relation	http://purl.org/au-research/grants/nhmrc/APP1073768
dc.relation.ispartof	Leukemia	en_US
dc.relation.isbasedon	10.1038/leu.2017.210	en_US
dc.subject.classification	Immunology	en_US
dc.subject.mesh	Humans	en_US
dc.subject.mesh	Prognosis	en_US
dc.subject.mesh	Risk Assessment	en_US
dc.subject.mesh	Risk Factors	en_US
dc.subject.mesh	Gene Expression Profiling	en_US
dc.subject.mesh	Adolescent	en_US
dc.subject.mesh	Adult	en_US
dc.subject.mesh	Middle Aged	en_US
dc.subject.mesh	Female	en_US
dc.subject.mesh	Male	en_US
dc.subject.mesh	Leukemia, Myeloid, Acute	en_US
dc.subject.mesh	Young Adult	en_US
dc.subject.mesh	Transcriptome	en_US
dc.subject.mesh	RNA, Long Noncoding	en_US
dc.title	A four-gene LincRNA expression signature predicts risk in multiple cohorts of acute myeloid leukemia patients	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.citation.volume	32	en_US
utslib.for	1103 Clinical Sciences	en_US
utslib.for	1112 Oncology and Carcinogenesis	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Biomedical Engineering
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Software
pubs.organisational-group	/University of Technology Sydney/Strength - AAI - Advanced Analytics Institute Research Centre
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
utslib.copyright.status	closed_access
pubs.issue	2	en_US
pubs.publication-status	Published	en_US
pubs.volume	32	en_US

Abstract:

© 2018 Macmillan Publishers Limited, part of Springer Nature. All rights reserved. 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.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/131979