Evidence map›Paper›PMID 37645423›Full record

ArticleHemaSphere2023

The Gene Expression Classifier ALLCatchR Identifies B-cell Precursor ALL Subtypes and Underlying Developmental Trajectories Across Age.

Thomas Beder, Björn-Thore Hansen, Alina M Hartmann, Johannes Zimmermann, Eric Amelunxen, Nadine Wolgast, Wencke Walter, Marketa Zaliova, Željko Antić, Philippe Chouvarine and 17 more

Abstract read
In one paragraph

Article in HemaSphere, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.

0numbers the graph read from it
0cells of the map it votes in
41citing 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

41 citing papers in PubMed.

  1. Review
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  5. Observational
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  9. AdultHemaSphere · 2026
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  14. HemaSphere · 2026
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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

27 authors.

Thomas BederMedical Department II, Hematology and Oncology, University Hospital Schleswig-Holstein, Kiel, Germany.
Björn-Thore HansenMedical Department II, Hematology and Oncology, University Hospital Schleswig-Holstein, Kiel, Germany.
Alina M HartmannMedical Department II, Hematology and Oncology, University Hospital Schleswig-Holstein, Kiel, Germany.
Johannes ZimmermannInstitute of Experimental Medicine, Research Group Medical Systems Biology, Christian-Albrechts-University Kiel, Germany.
Eric AmelunxenMedical Department II, Hematology and Oncology, University Hospital Schleswig-Holstein, Kiel, Germany.
Nadine WolgastMedical Department II, Hematology and Oncology, University Hospital Schleswig-Holstein, Kiel, Germany.
Wencke WalterMLL Munich Leukemia Laboratory, Munich, Germany.
Marketa ZaliovaChildhood Leukaemia Investigation Prague, Second Faculty of Medicine, Charles University and University Hospital Motol, Prague, Czech Republic.
Željko AntićDepartment of Human Genetics, Hannover Medical School (MHH), Hannover, Germany.
Philippe ChouvarineDepartment of Human Genetics, Hannover Medical School (MHH), Hannover, Germany.
Lorenz BartschMedical Department II, Hematology and Oncology, University Hospital Schleswig-Holstein, Kiel, Germany.
Malwine J BarzMedical Department II, Hematology and Oncology, University Hospital Schleswig-Holstein, Kiel, Germany.
Miriam BultmannMedical Department II, Hematology and Oncology, University Hospital Schleswig-Holstein, Kiel, Germany.
Johanna HornsMedical Department II, Hematology and Oncology, University Hospital Schleswig-Holstein, Kiel, Germany.
Sonja BendigMedical Department II, Hematology and Oncology, University Hospital Schleswig-Holstein, Kiel, Germany.
Jan KässensMedical Department II, Hematology and Oncology, University Hospital Schleswig-Holstein, Kiel, Germany.
Christoph KaletaInstitute of Experimental Medicine, Research Group Medical Systems Biology, Christian-Albrechts-University Kiel, Germany.
Gunnar CarioClinical Research Unit "CATCH ALL" (KFO 5010/1) funded by the Deutsche Forschungsgemeinschaft, Bonn, Germany.
Martin SchrappeClinical Research Unit "CATCH ALL" (KFO 5010/1) funded by the Deutsche Forschungsgemeinschaft, Bonn, Germany.
Martin NeumannMedical Department II, Hematology and Oncology, University Hospital Schleswig-Holstein, Kiel, Germany.
Nicola GökbugetDepartment of Medicine II, Hematology/Oncology, Goethe University Hospital, Frankfurt/M., Germany.
Anke Katharina BergmannDepartment of Human Genetics, Hannover Medical School (MHH), Hannover, Germany.
Jan TrkaChildhood Leukaemia Investigation Prague, Second Faculty of Medicine, Charles University and University Hospital Motol, Prague, Czech Republic.
Claudia HaferlachMLL Munich Leukemia Laboratory, Munich, Germany.
Monika BrüggemannMedical Department II, Hematology and Oncology, University Hospital Schleswig-Holstein, Kiel, Germany.
Claudia D BaldusMedical Department II, Hematology and Oncology, University Hospital Schleswig-Holstein, Kiel, Germany.
Lorenz BastianMedical Department II, Hematology and Oncology, University Hospital Schleswig-Holstein, Kiel, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Current classifications (World Health Organization-HAEM5/ICC) define up to 26 molecular B-cell precursor acute lymphoblastic leukemia (BCP-ALL) disease subtypes by genomic driver aberrations and corresponding gene expression signatures. Identification of driver aberrations by transcriptome sequencing (RNA-Seq) is well established, while systematic approaches for gene expression analysis are less advanced. Therefore, we developed ALLCatchR, a machine learning-based classifier using RNA-Seq gene expression data to allocate BCP-ALL samples to all 21 gene expression-defined molecular subtypes. Trained on n = 1869 transcriptome profiles with established subtype definitions (4 cohorts; 55% pediatric / 45% adult), ALLCatchR allowed subtype allocation in 3 independent hold-out cohorts (n = 1018; 75% pediatric / 25% adult) with 95.7% accuracy (averaged sensitivity across subtypes: 91.1% / specificity: 99.8%). High-confidence predictions were achieved in 83.7% of samples with 98.9% accuracy. Only 1.2% of samples remained unclassified. ALLCatchR outperformed existing tools and identified novel driver candidates in previously unassigned samples. Additional modules provided predictions of samples blast counts, patient's sex, and immunophenotype, allowing the imputation in cases where these information are missing. We established a novel RNA-Seq reference of human B-lymphopoiesis using 7 FACS-sorted progenitor stages from healthy bone marrow donors. Implementation in ALLCatchR enabled projection of BCP-ALL samples to this trajectory. This identified shared proximity patterns of BCP-ALL subtypes to normal lymphopoiesis stages, extending immunophenotypic classifications with a novel framework for developmental comparisons of BCP-ALL. ALLCatchR enables RNA-Seq routine application for BCP-ALL diagnostics with systematic gene expression analysis for accurate subtype allocation and novel insights into underlying developmental trajectories.

Identifiers

PMID37645423
PMCPMC10461941

What Socratic holds

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LicenceCC BY-NC
Read underepoch 390

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 Socratic graph.