Evidence map›Paper›PMID 38071228›Full record

ArticleScientific reports2023

Metabolomic profile of acute myeloid leukaemia parallels of prognosis and response to therapy.

Lukasz Bolkun, Tomasz Pienkowski, Julia Sieminska, Joanna Godzien, Karolina Pietrowska, Janusz Kłoczko, Agnieszka Wierzbowska, Marcin Moniuszko, Mariusz Ratajczak, Adam Kretowski and 1 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
5.2field-weighted citation impact, top 4% 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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.

  1. Pooled it
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  8. Metabolic Signature ofJournal of personalized medicine · 2025
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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

11 authors at 3 institutions in 2 countries.

Lukasz Bolkun *Department of Hematology, Medical University of Bialystok, 15-276, Bialystok, Poland.
Tomasz Pienkowski *Clinical Research Centre, Medical University of Bialystok, M. Sklodowskiej-Curie 24A, 15-276, Bialystok, Poland.
Julia SieminskaClinical Research Centre, Medical University of Bialystok, M. Sklodowskiej-Curie 24A, 15-276, Bialystok, Poland.
Joanna GodzienClinical Research Centre, Medical University of Bialystok, M. Sklodowskiej-Curie 24A, 15-276, Bialystok, Poland.
Karolina PietrowskaClinical Research Centre, Medical University of Bialystok, M. Sklodowskiej-Curie 24A, 15-276, Bialystok, Poland.
Janusz KłoczkoDepartment of Hematology, Medical University of Bialystok, 15-276, Bialystok, Poland.
Agnieszka WierzbowskaDepartment of Hematology, Medical University of Lodz, 93-513, Lodz, Poland.
Marcin MoniuszkoDepartment of Regenerative Medicine and Immune Regulation, Medical University of Bialystok, Bialystok, Poland.
Mariusz RatajczakStem Cell Institute at James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA.
Adam KretowskiClinical Research Centre, Medical University of Bialystok, M. Sklodowskiej-Curie 24A, 15-276, Bialystok, Poland.
Michal CiborowskiClinical Research Centre, Medical University of Bialystok, M. Sklodowskiej-Curie 24A, 15-276, Bialystok, Poland. michal.ciborowski@umb.edu.pl.
Medical University of Białystok · PLJames Graham Brown Foundation · USMedical University of Lodz · PL

Funding

Ministerstwo Edukacji i Nauki Excellence Initiative - Research UniversitUniwersytet Medyczny w Białymstoku B.SUB.23.192.
6 · The paper itself

Abstract

The heterogeneity of acute myeloid leukemia (AML), a complex hematological malignancy, is caused by mutations in myeloid cells affecting their differentiation and proliferation. Thus, various cytogenetic alterations in AML cells may be characterized by a unique metabolome and require different treatment approaches. In this study, we performed untargeted metabolomics to assess metabolomics differences between AML patients and healthy controls, AML patients with different treatment outcomes, AML patients in different risk groups based on the 2017 European LeukemiaNet (ELN) recommendations for the diagnosis and management of AML, AML patients with and without FLT3-ITD mutation, and a comparison between patients with FLT3-ITD, CBF-AML (Core binding factor acute myelogenous leukemia), and MLL AML (mixed-lineage leukemia gene) in comparison to control subjects. Analyses were performed in serum samples using liquid chromatography coupled with mass spectrometry (LC-MS). The obtained metabolomics profiles exhibited many alterations in glycerophospholipid and sphingolipid metabolism and allowed us to propose biomarkers based on each of the above assessments as an aid for diagnosis and eventual classification, allowing physicians to choose the best-suited treatment approach. These results highlight the application of LC-MS-based metabolomics of serum samples as an aid in diagnostics and a potential minimally invasive prognostic tool for identifying various cytogenetic and treatment outcomes of AML.

Indexed as

Leukemia, Myeloid, Acutefms-Like Tyrosine Kinase 3HumansMutationPrognosisRisk FactorsTreatment Outcomefms-Like Tyrosine Kinase 3

Identifiers

PMID38071228
PMCPMC10710498
OpenAlexW4389509167

What OpenQuestion holds

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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.