Evidence map›Paper›PMID 32324791›Full record

ArticlePloS one2020

Normal myeloid progenitor cell subset-associated gene signatures for acute myeloid leukaemia subtyping with prognostic impact.

Anna A Schönherz, Julie Støve Bødker, Alexander Schmitz, Rasmus Froberg Brøndum, Lasse Hjort Jakobsen, Anne Stidsholt Roug, Marianne T Severinsen, Tarec C El-Galaly, Paw Jensen, Hans Erik Johnsen and 2 more

Abstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Review
  2. 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

12 authors.

Anna A SchönherzDepartment of Clinical Medicine, Faculty of Medicine, Aalborg University, Aalborg, Denmark.
Julie Støve BødkerDepartment of Haematology, Clinical Cancer Research Center, Aalborg University Hospital, Aalborg, Denmark.
Alexander SchmitzDepartment of Haematology, Clinical Cancer Research Center, Aalborg University Hospital, Aalborg, Denmark.
Rasmus Froberg BrøndumDepartment of Haematology, Clinical Cancer Research Center, Aalborg University Hospital, Aalborg, Denmark.ORCID 0000-0001-5537-6767
Lasse Hjort JakobsenDepartment of Clinical Medicine, Faculty of Medicine, Aalborg University, Aalborg, Denmark.
Anne Stidsholt RougDepartment of Clinical Medicine, Faculty of Medicine, Aalborg University, Aalborg, Denmark.
Marianne T SeverinsenDepartment of Clinical Medicine, Faculty of Medicine, Aalborg University, Aalborg, Denmark.
Tarec C El-GalalyDepartment of Clinical Medicine, Faculty of Medicine, Aalborg University, Aalborg, Denmark.
Paw JensenDepartment of Haematology, Clinical Cancer Research Center, Aalborg University Hospital, Aalborg, Denmark.ORCID 0000-0002-5248-0523
Hans Erik JohnsenDepartment of Clinical Medicine, Faculty of Medicine, Aalborg University, Aalborg, Denmark.
Martin BøgstedDepartment of Clinical Medicine, Faculty of Medicine, Aalborg University, Aalborg, Denmark.
Karen DybkærDepartment of Clinical Medicine, Faculty of Medicine, Aalborg University, Aalborg, Denmark.ORCID 0000-0003-2488-435X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute myeloid leukaemia (AML) is characterised by phenotypic heterogeneity, which we hypothesise is a consequence of deregulated differentiation with transcriptional reminiscence of the normal compartment or cell-of-origin. Here, we propose a classification system based on normal myeloid progenitor cell subset-associated gene signatures (MAGS) for individual assignments of AML subtypes. We generated a MAGS classifier including the progenitor compartments CD34+/CD38- for haematopoietic stem cells (HSCs), CD34+/CD38+/CD45RA- for megakaryocyte-erythroid progenitors (MEPs), and CD34+/CD38+/CD45RA+ for granulocytic-monocytic progenitors (GMPs) using regularised multinomial regression with three discrete outcomes and an elastic net penalty. The regularisation parameters were chosen by cross-validation, and MAGS assignment accuracy was validated in an independent data set (N = 38; accuracy = 0.79) of sorted normal myeloid subpopulations. The prognostic value of MAGS assignment was studied in two clinical cohorts (TCGA: N = 171; GSE6891: N = 520) and had a significant prognostic impact. Furthermore, multivariate Cox regression analysis using the MAGS subtype, FAB subtype, cytogenetics, molecular genetics, and age as explanatory variables showed independent prognostic value. Molecular characterisation of subtypes by differential gene expression analysis, gene set enrichment analysis, and mutation patterns indicated reduced proliferation and overrepresentation of RUNX1 and IDH2 mutations in the HSC subtype; increased proliferation and overrepresentation of CEBPA mutations in the MEP subtype; and innate immune activation and overrepresentation of WT1 mutations in the GMP subtype. We present a differentiation-dependent classification system for AML subtypes with distinct pathogenetic and prognostic importance that can help identify candidates poorly responding to combination chemotherapy and potentially guide alternative treatments.

Indexed as

ADP-ribosyl Cyclase 1Antigens, CD34Cell DifferentiationCell LineageCore Binding Factor Alpha 2 SubunitFemaleGene Expression Regulation, NeoplasticHematopoietic Stem CellsHumansIsocitrate DehydrogenaseLeukemia, Myeloid, AcuteLeukocyte Common AntigensMaleMiddle AgedMutationMyeloid CellsADP-ribosyl Cyclase 1Antigens, CD34Core Binding Factor Alpha 2 SubunitIDH2 protein, humanIsocitrate DehydrogenaseLeukocyte Common AntigensRUNX1 protein, humanWT1 protein, humanWT1 Proteins

Identifiers

PMID32324791
PMCPMC7179860

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.