Evidence map›Paper›PMID 28674423›Full record

ArticleLeukemia2018

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

D Beck, J A I Thoms, C Palu, T Herold, A Shah, J Olivier, L Boelen, Y Huang, D Chacon, A Brown and 18 more

Open access · greenAbstract read
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In one paragraph

Article in Leukemia, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 1 pooled it
1.4field-weighted citation impact, top 21% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

24 citing papers in PubMed, 1 synthesis or guideline pooled it, 55 citations in OpenAlex.

  1. Pooled it
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  7. Review
  8. Long Noncoding RNA Expression Independently Predicts Outcome in Pediatric Acute Myeloid Leukemia.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

28 authors at 10 institutions in 5 countries.

D BeckAdult Cancer Program, Lowy Cancer Research Centre, Prince of Wales Clinical School, University of New South Wales, Sydney, New South Wales, Australia.
J A I ThomsAdult Cancer Program, Lowy Cancer Research Centre, Prince of Wales Clinical School, University of New South Wales, Sydney, New South Wales, Australia.
C PaluAdult Cancer Program, Lowy Cancer Research Centre, Prince of Wales Clinical School, University of New South Wales, Sydney, New South Wales, Australia.
T HeroldDepartment of Internal Medicine III, University Hospital Grosshadern, Ludwig Maximilians Universität, Munich, Germany.ORCID 0000-0002-9615-9432
A ShahAdult Cancer Program, Lowy Cancer Research Centre, Prince of Wales Clinical School, University of New South Wales, Sydney, New South Wales, Australia.
J OlivierSchool of Mathematics, UNSW Australia, Sydney, NSW, Australia.ORCID 0000-0002-3144-4507
L BoelenDepartment of Medicine, Faculty of Medicine, Imperial College London, London, UK.
Y HuangAdult Cancer Program, Lowy Cancer Research Centre, Prince of Wales Clinical School, University of New South Wales, Sydney, New South Wales, Australia.
D ChaconAdult Cancer Program, Lowy Cancer Research Centre, Prince of Wales Clinical School, University of New South Wales, Sydney, New South Wales, Australia.
A BrownCentre for Cancer Biology, SA Pathology, University of South Australia, Adelaide, SA, Australia.
M BabicCentre for Cancer Biology, SA Pathology, University of South Australia, Adelaide, SA, Australia.
C HahnCentre for Cancer Biology, SA Pathology, University of South Australia, Adelaide, SA, Australia.ORCID 0000-0001-5105-2554
M PeruginiCentre for Cancer Biology, SA Pathology, University of South Australia, Adelaide, SA, Australia.
X ZhouSchool of Medicine, Wake Forest University, Winston-Salem, NC, USA.
B J HuntlyDepartment of Haematology, Cambridge Institute for Medical Research, Cambridge, UK.
A SchwarzerPediatric Hematology and Oncology, Hannover Medical School, Hannover, Germany.
J-H KlusmannPediatric Hematology and Oncology, Hannover Medical School, Hannover, Germany.
W E BerdelDepartment of Medicine, Hematology and Oncology, University of Münster, Münster, Germany.
B WörmannDepartment of Medicine, Hematology, Oncology, Tumor Immunology, Charité-Universitätsmedizin Berlin, Berlin, Germany.
T BüchnerDepartment of Medicine, Hematology and Oncology, University of Münster, Münster, Germany.
W HiddemannDepartment of Internal Medicine III, University Hospital Grosshadern, Ludwig Maximilians Universität, Munich, Germany.
S K BohlanderDepartment of Molecular Medicine and Pathology, University of Auckland, New Zealand.
L B ToDepartment of Haematology, SA Pathology, Royal Adelaide Hospital, Adelaide, SA, Australia.
H S ScottCentre for Cancer Biology, SA Pathology, University of South Australia, Adelaide, SA, Australia.
I D LewisCentre for Cancer Biology, SA Pathology, University of South Australia, Adelaide, SA, Australia.
R J D'AndreaCentre for Cancer Biology, SA Pathology, University of South Australia, Adelaide, SA, Australia.
J W H WongAdult Cancer Program, Lowy Cancer Research Centre, Prince of Wales Clinical School, University of New South Wales, Sydney, New South Wales, Australia.
J E PimandaAdult Cancer Program, Lowy Cancer Research Centre, Prince of Wales Clinical School, University of New South Wales, Sydney, New South Wales, Australia.
South Australia Pathology · AUUNSW Sydney · AULudwig-Maximilians-Universität München · DEMedizinische Hochschule Hannover · DEUniversity of Münster · DEUniversity of Technology Sydney · AUCharité - Universitätsmedizin Berlin · DEImperial College London · GBUniversity of Auckland · NZWake Forest University · US

Funding

Medical Research Council MC_PC_12009
6 · The paper itself

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.

Indexed as

AdolescentAdultFemaleGene Expression ProfilingHumansLeukemia, Myeloid, AcuteMaleMiddle AgedPrognosisRisk AssessmentRisk FactorsRNA, Long NoncodingTranscriptomeYoung AdultRNA, Long Noncoding

Identifiers

PMID28674423
OpenAlexW2733977382

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.