Evidence map›Paper›PMID 34131280›Full record

ArticleLeukemia2022

Investigation of measurable residual disease in acute myeloid leukemia by DNA methylation patterns.

Tanja Božić, Chao-Chung Kuo, Jan Hapala, Julia Franzen, Monika Eipel, Uwe Platzbecker, Martin Kirschner, Fabian Beier, Edgar Jost, Christian Thiede and 1 more

Open access · hybridAbstract read
In one paragraph

Article in Leukemia, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
3.7field-weighted citation impact, top 6% 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

18 citing papers in PubMed, 28 citations in OpenAlex.

  1. Article
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  4. Epigenetic networks coordinate DNA methylation across the genome.Molecular therapy : the journal of the American Society of Gene Therapy · 2025
    Review
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  14. How to Translate DNA Methylation Biomarkers Into Clinical Practice.Frontiers in cell and developmental biology · 2022
    Review
  15. Review
  16. Article
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  18. Article
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

11 authors at 4 institutions in 2 countries.

Tanja Božić *Helmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, RWTH Aachen University Medical School, Aachen, Germany.
Chao-Chung Kuo *Helmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, RWTH Aachen University Medical School, Aachen, Germany.ORCID http://orcid.org/0000-0001-8879-4754
Jan HapalaHelmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, RWTH Aachen University Medical School, Aachen, Germany.
Julia FranzenHelmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, RWTH Aachen University Medical School, Aachen, Germany.ORCID http://orcid.org/0000-0002-2459-5841
Monika EipelHelmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, RWTH Aachen University Medical School, Aachen, Germany.
Uwe PlatzbeckerDepartment of Hematology, Cellular Therapy and Hemostaseology, Leipzig University Hospital, Leipzig, Germany.ORCID http://orcid.org/0000-0003-1863-3239
Martin KirschnerDepartment of Hematology, Oncology, Hemostaseology and Stem Cell Transplantation, Medical School, RWTH Aachen University, Aachen, Germany.
Fabian BeierDepartment of Hematology, Oncology, Hemostaseology and Stem Cell Transplantation, Medical School, RWTH Aachen University, Aachen, Germany.
Edgar JostDepartment of Hematology, Oncology, Hemostaseology and Stem Cell Transplantation, Medical School, RWTH Aachen University, Aachen, Germany.
Christian ThiedeMedical Department I, University Hospital Carl Gustav Carus, TU Dresden, Dresden, Germany.ORCID http://orcid.org/0000-0003-1241-2048
Wolfgang WagnerHelmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, RWTH Aachen University Medical School, Aachen, Germany. wwagner@ukaachen.de.ORCID http://orcid.org/0000-0002-1971-3217
RWTH Aachen University · DEIntegrated Oncology (United States) · USUniversity Hospital Carl Gustav Carus · DEUniversity Hospital Leipzig · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Assessment of measurable residual disease (MRD) upon treatment of acute myeloid leukemia (AML) remains challenging. It is usually addressed by highly sensitive PCR- or sequencing-based screening of specific mutations, or by multiparametric flow cytometry. However, not all patients have suitable mutations and heterogeneity of surface markers hampers standardization in clinical routine. In this study, we propose an alternative approach to estimate MRD based on AML-associated DNA methylation (DNAm) patterns. We identified four CG dinucleotides (CpGs) that commonly reveal aberrant DNAm in AML and their combination could reliably discern healthy and AML samples. Interestingly, bisulfite amplicon sequencing demonstrated that aberrant DNAm patterns were symmetric on both alleles, indicating that there is epigenetic crosstalk between homologous chromosomes. We trained shallow-learning and deep-learning algorithms to identify anomalous DNAm patterns. The method was then tested on follow-up samples with and without MRD. Notably, even samples that were classified as MRD negative often revealed higher anomaly ratios than healthy controls, which may reflect clonal hematopoiesis. Our results demonstrate that targeted DNAm analysis facilitates reliable discrimination of malignant and healthy samples. However, since healthy samples also comprise few abnormal-classified DNAm reads the approach does not yet reliably discriminate MRD positive and negative samples.

Indexed as

DNA MethylationGene Expression Regulation, LeukemicMutationBiomarkers, TumorHumansLeukemia, Myeloid, AcuteNeoplasm Recurrence, LocalNeoplasm, ResidualPrognosisSurvival RateBiomarkers, Tumor

Identifiers

PMID34131280
PMCPMC8727289
OpenAlexW3166395338

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.