Evidence map›Paper›PMID 29625580›Full record

ArticleJournal of hematology & oncology2018

Expression levels of long non-coding RNAs are prognostic for AML outcome.

Arvind Singh Mer, Johan Lindberg, Christer Nilsson, Daniel Klevebring, Mei Wang, Henrik Grönberg, Soren Lehmann, Mattias Rantalainen

Open access · goldAbstract read
In one paragraph

Article in Journal of hematology & oncology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed, 1 pooled it
6.4field-weighted citation impact, top 2% 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

42 citing papers in PubMed, 1 synthesis or guideline pooled it, 101 citations in OpenAlex.

  1. Pooled it
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  11. 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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  20. Web tools to perform long non-coding RNAs analysis in oncology research.Database : the journal of biological databases and curation · 2021
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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

8 authors at 2 institutions in 1 country.

Arvind Singh MerDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Vag 12A, SE-17177, Stockholm, Sweden.
Johan LindbergDepartment of Medical Epidemiology and Biostatistics, Science for Life Laboratory, Karolinska Institutet, Nobels Vag 12A, SE-17177, Stockholm, Sweden.
Christer NilssonHematology Centre, Karolinska University Hospital and Karolinska Institute, Huddinge, Stockholm, Sweden.
Daniel KlevebringDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Vag 12A, SE-17177, Stockholm, Sweden.
Mei WangDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Vag 12A, SE-17177, Stockholm, Sweden.
Henrik GrönbergDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Vag 12A, SE-17177, Stockholm, Sweden.
Soren LehmannHematology Centre, Karolinska University Hospital and Karolinska Institute, Huddinge, Stockholm, Sweden.
Mattias RantalainenDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Vag 12A, SE-17177, Stockholm, Sweden. Mattias.Rantalainen@ki.se.
Karolinska Institutet · SEKarolinska University Hospital · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLong non-coding RNA (lncRNA) expression has been implicated in a range of molecular mechanisms that are central in cancer. However, lncRNA expression has not yet been comprehensively characterized in acute myeloid leukemia (AML). Here, we assess to what extent lncRNA expression is prognostic of AML patient overall survival (OS) and determine if there are indications of lncRNA-based molecular subtypes of AML.

methodsWe performed RNA sequencing of 274 intensively treated AML patients in a Swedish cohort and quantified lncRNA expression. Univariate and multivariate time-to-event analysis was applied to determine association between individual lncRNAs with OS. Unsupervised statistical learning was applied to ascertain if lncRNA-based molecular subtypes exist and are prognostic.

resultsThirty-three individual lncRNAs were found to be associated with OS (adjusted p value < 0.05). We established four distinct molecular subtypes based on lncRNA expression using a consensus clustering approach. LncRNA-based subtypes were found to stratify patients into groups with prognostic information (p value < 0.05). Subsequently, lncRNA expression-based subtypes were validated in an independent patient cohort (TCGA-AML). LncRNA subtypes could not be directly explained by any of the recurrent cytogenetic or mutational aberrations, although associations with some of the established genetic and clinical factors were found, including mutations in NPM1, TP53, and FLT3.

conclusionLncRNA expression-based four subtypes, discovered in this study, are reproducible and can effectively stratify AML patients. LncRNA expression profiling can provide valuable information for improved risk stratification of AML patients.

Indexed as

FemaleHumansLeukemia, Myeloid, AcuteMaleNucleophosminPrognosisRNA, Long NoncodingTreatment OutcomeNPM1 protein, humanNucleophosminRNA, Long NoncodingAcute myeloid leukemialncRNAMolecular subtypePrognosis

Identifiers

PMID29625580
PMCPMC5889529
OpenAlexW2795366323

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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.