Evidence map›Paper›PMID 32127641›Full record

ArticleLeukemia2021

Comprehensive diagnostics of acute myeloid leukemia by whole transcriptome RNA sequencing.

Wibowo Arindrarto, Daniel M Borràs, Ruben A L de Groen, Redmar R van den Berg, Irene J Locher, Saskia A M E van Diessen, Rosalie van der Holst, Edith D van der Meijden, M Willy Honders, Rick H de Leeuw and 16 more

Open access · hybridAbstract read
In one paragraph

Article in Leukemia, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers.

0numbers the graph read from it
0cells of the map it votes in
61citing papers in PubMed
6.1field-weighted citation impact, top 3% 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

61 citing papers in PubMed, 102 citations in OpenAlex.

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1 more citing papers are in PubMed but not listed here.

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

26 authors at 4 institutions in 2 countries.

Wibowo Arindrarto *Center for Computational Biology, Leiden University Medical Center, 2300RC, Leiden, The Netherlands.
Daniel M Borràs *GenomeScan B.V, 2333 BZ, Leiden, The Netherlands.
Ruben A L de GroenDepartment of Hematology, Leiden University Medical Center, 2300RC, Leiden, The Netherlands.
Redmar R van den BergDepartment of Human Genetics, Leiden University Medical Center, 2300RC, Leiden, The Netherlands.
Irene J LocherDepartment of Hematology, Leiden University Medical Center, 2300RC, Leiden, The Netherlands.
Saskia A M E van DiessenDepartment of Hematology, Leiden University Medical Center, 2300RC, Leiden, The Netherlands.
Rosalie van der HolstDepartment of Hematology, Leiden University Medical Center, 2300RC, Leiden, The Netherlands.
Edith D van der MeijdenDepartment of Hematology, Leiden University Medical Center, 2300RC, Leiden, The Netherlands.
M Willy HondersDepartment of Hematology, Leiden University Medical Center, 2300RC, Leiden, The Netherlands.
Rick H de LeeuwForensic Laboratory for DNA Research, Department of Human Genetics, Leiden University Medical Center, 2300RC, Leiden, The Netherlands.
Wina VerlaatDepartment of Hematology, Leiden University Medical Center, 2300RC, Leiden, The Netherlands.
Inge JedemaDepartment of Hematology, Leiden University Medical Center, 2300RC, Leiden, The Netherlands.
Wilma G M KroesDepartment of Clinical Genetics, Leiden University Medical Center, 2300RC, Leiden, The Netherlands.
Jeroen KnijnenburgDepartment of Clinical Genetics, Leiden University Medical Center, 2300RC, Leiden, The Netherlands.
Tom van WezelDepartment of Pathology, Leiden University Medical Center, 2300RC, Leiden, The Netherlands.
Joost S P VermaatDepartment of Hematology, Leiden University Medical Center, 2300RC, Leiden, The Netherlands.
Peter J M ValkDepartment of Hematology, Erasmus University Medical Center, 3015CN, Rotterdam, The Netherlands.
Bart JanssenGenomeScan B.V, 2333 BZ, Leiden, The Netherlands.
Peter de KnijffForensic Laboratory for DNA Research, Department of Human Genetics, Leiden University Medical Center, 2300RC, Leiden, The Netherlands.
Cornelis A M van BergenDepartment of Hematology, Leiden University Medical Center, 2300RC, Leiden, The Netherlands.
Erik B van den AkkerCenter for Computational Biology, Leiden University Medical Center, 2300RC, Leiden, The Netherlands.ORCID http://orcid.org/0000-0002-7693-0728
Peter A C 't HoenDepartment of Human Genetics, Leiden University Medical Center, 2300RC, Leiden, The Netherlands.
Szymon M KiełbasaCenter for Computational Biology, Leiden University Medical Center, 2300RC, Leiden, The Netherlands.ORCID http://orcid.org/0000-0003-2805-6535
Jeroen F J LarosDepartment of Human Genetics, Leiden University Medical Center, 2300RC, Leiden, The Netherlands.
Marieke Griffioen *Department of Hematology, Leiden University Medical Center, 2300RC, Leiden, The Netherlands. M.Griffioen@lumc.nl.
Hendrik Veelken *Department of Hematology, Leiden University Medical Center, 2300RC, Leiden, The Netherlands.
Leiden University Medical Center · NLErasmus MC · NLGenomeScan (Netherlands) · NLRadboud University Nijmegen · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute myeloid leukemia (AML) is caused by genetic aberrations that also govern the prognosis of patients and guide risk-adapted and targeted therapy. Genetic aberrations in AML are structurally diverse and currently detected by different diagnostic assays. This study sought to establish whole transcriptome RNA sequencing as single, comprehensive, and flexible platform for AML diagnostics. We developed HAMLET (Human AML Expedited Transcriptomics) as bioinformatics pipeline for simultaneous detection of fusion genes, small variants, tandem duplications, and gene expression with all information assembled in an annotated, user-friendly output file. Whole transcriptome RNA sequencing was performed on 100 AML cases and HAMLET results were validated by reference assays and targeted resequencing. The data showed that HAMLET accurately detected all fusion genes and overexpression of EVI1 irrespective of 3q26 aberrations. In addition, small variants in 13 genes that are often mutated in AML were called with 99.2% sensitivity and 100% specificity, and tandem duplications in FLT3 and KMT2A were detected by a novel algorithm based on soft-clipped reads with 100% sensitivity and 97.1% specificity. In conclusion, HAMLET has the potential to provide accurate comprehensive diagnostic information relevant for AML classification, risk assessment and targeted therapy on a single technology platform.

Indexed as

Exome SequencingGene Expression ProfilingTranscriptomeBiomarkers, TumorComputational BiologyFemaleGene Expression Regulation, LeukemicGenetic VariationGenomicsHumansLeukemia, Myeloid, AcuteMaleMolecular Diagnostic TechniquesMutationOncogene Proteins, FusionPrognosisBiomarkers, TumorOncogene Proteins, Fusion

Identifiers

PMID32127641
PMCPMC7787979
OpenAlexW3009454107

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.