Evidence map›Paper›PMID 31409822›Full record

ArticleScientific reports2019

Allelic Imbalance of Recurrently Mutated Genes in Acute Myeloid Leukaemia.

Aarif M N Batcha, Stefanos A Bamopoulos, Paul Kerbs, Ashwini Kumar, Vindi Jurinovic, Maja Rothenberg-Thurley, Bianka Ksienzyk, Julia Philippou-Massier, Stefan Krebs, Helmut Blum and 12 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.5field-weighted citation impact, top 17% 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

8 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
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  8. RUNX1 Dosage in Development and Cancer.Molecules and cells · 2020
    Review
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

22 authors at 7 institutions in 5 countries.

Aarif M N BatchaInstitute of Medical Data Processing, Biometrics and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Munich, Germany. nazeer@ibe.med.uni-muenchen.de.
Stefanos A BamopoulosLaboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany.
Paul KerbsLaboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany.
Ashwini KumarInstitute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.
Vindi JurinovicInstitute of Medical Data Processing, Biometrics and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Munich, Germany.
Maja Rothenberg-ThurleyLaboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany.
Bianka KsienzykLaboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany.
Julia Philippou-MassierLaboratory for Functional Genome Analysis (LAFUGA), Gene Center, University of Munich, Munich, Germany.
Stefan KrebsLaboratory for Functional Genome Analysis (LAFUGA), Gene Center, University of Munich, Munich, Germany.
Helmut BlumLaboratory for Functional Genome Analysis (LAFUGA), Gene Center, University of Munich, Munich, Germany.
Stephanie SchneiderLaboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany.
Nikola KonstandinLaboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany.
Stefan K BohlanderLeukaemia and Blood Cancer Research Unit, Department of Molecular Medicine and Pathology, University of Auckland, Auckland, New Zealand.ORCID http://orcid.org/0000-0002-2202-9088
Caroline HeckmanInstitute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.
Mika KontroDepartment of Haematology, Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland.
Wolfgang HiddemannLaboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany.
Karsten SpiekermannLaboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany.
Jan BraessDepartment of Oncology and Hematology, Hospital Barmherzige Brüder, Regensburg, Germany.
Klaus H MetzelerLaboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany.
Philipp A GreifLaboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany.
Ulrich MansmannInstitute of Medical Data Processing, Biometrics and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Munich, Germany.ORCID http://orcid.org/0000-0002-9955-8906
Tobias HeroldLaboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany. tobias.herold@med.uni-muenchen.de.ORCID http://orcid.org/0000-0002-9615-9432
LMU Klinikum · DEGerman Cancer Research Center · DEUniversity of Helsinki · FIHelsinki University Hospital · FIKrankenhaus Barmherzige Brüder · DEUniversity of Auckland · NZZimmer Biomet (Netherlands) · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The patho-mechanism of somatic driver mutations in cancer usually involves transcription, but the proportion of mutations and wild-type alleles transcribed from DNA to RNA is largely unknown. We systematically compared the variant allele frequencies of recurrently mutated genes in DNA and RNA sequencing data of 246 acute myeloid leukaemia (AML) patients. We observed that 95% of all detected variants were transcribed while the rest were not detectable in RNA sequencing with a minimum read-depth cut-off (10x). Our analysis focusing on 11 genes harbouring recurring mutations demonstrated allelic imbalance (AI) in most patients. GATA2, RUNX1, TET2, SRSF2, IDH2, PTPN11, WT1, NPM1 and CEBPA showed significant AIs. While the effect size was small in general, GATA2 exhibited the largest allelic imbalance. By pooling heterogeneous data from three independent AML cohorts with paired DNA and RNA sequencing (N = 253), we could validate the preferential transcription of GATA2-mutated alleles. Differential expression analysis of the genes with significant AI showed no significant differential gene and isoform expression for the mutated genes, between mutated and wild-type patients. In conclusion, our analyses identified AI in nine out of eleven recurrently mutated genes. AI might be a common phenomenon in AML which potentially contributes to leukaemogenesis.

Indexed as

Allelic ImbalanceFemaleGene Expression Regulation, LeukemicHigh-Throughput Nucleotide SequencingHumansLeukemia, Myeloid, AcuteMaleMutationNeoplasm ProteinsNeoplasm Recurrence, LocalNucleophosminPrognosisNeoplasm ProteinsNPM1 protein, humanNucleophosmin

Identifiers

PMID31409822
PMCPMC6692371
OpenAlexW2968438858

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.