Evidence map›Paper›PMID 41360907›Full record

ArticleScientific reports2025

Flow cytometry-based targeted diagnostics for rapid assessment of daunorubicin resistance in acute myeloid leukemia.

Aleksandra Kaczorowska, Przemysław Sareło, Marlena Gąsior-Głogowska, Ewa Zioło, Paweł Karpiński, Łukasz Łaczmański, Marta Sobas, Tomasz Wróbel, Halina Podbielska, Marta Kopaczyńska and 1 more

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PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2025. 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. Article
  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

11 authors.

Aleksandra KaczorowskaDepartment of Biomedical Engineering, Faculty of Fundamental Problems of Technology, Wrocław University of Science and Technology, Wybrzeże Wyspianskiego 27, 50-370, Wrocław, Poland. aleksandra.kaczorowska@pwr.edu.pl.
Przemysław SarełoDepartment of Biomedical Engineering, Faculty of Fundamental Problems of Technology, Wrocław University of Science and Technology, Wybrzeże Wyspianskiego 27, 50-370, Wrocław, Poland.
Marlena Gąsior-GłogowskaDepartment of Biomedical Engineering, Faculty of Fundamental Problems of Technology, Wrocław University of Science and Technology, Wybrzeże Wyspianskiego 27, 50-370, Wrocław, Poland.
Ewa ZiołoDepartment of Experimental Oncology, Ludwik Hirszfeld Institute of Immunology and Experimental Therapy, Polish Academy of Sciences, Rudolfa Weigla 12, 53-114, Wrocław, Poland.
Paweł KarpińskiDepartment of Genetics, Wrocław Medical University, Karola Marcinkowskiego 1, 50-368, Wrocław, Poland.
Łukasz ŁaczmańskiLaboratory of Genomics and Bioinformatics, Ludwik Hirszfeld Institute of Immunology and Experimental Therapy, Polish Academy of Sciences, Rudolfa Weigla 12, 53-114, Wrocław, Poland.
Marta SobasDepartment and Clinic of Hematology, Cellular Therapies and Internal Medicine, Faculty of Medicine, Wrocław Medical University, Wybrzeże Pasteura 4, 50-367, Wrocław, Poland.
Tomasz WróbelDepartment and Clinic of Hematology, Cellular Therapies and Internal Medicine, Faculty of Medicine, Wrocław Medical University, Wybrzeże Pasteura 4, 50-367, Wrocław, Poland.
Halina PodbielskaDepartment of Biomedical Engineering, Faculty of Fundamental Problems of Technology, Wrocław University of Science and Technology, Wybrzeże Wyspianskiego 27, 50-370, Wrocław, Poland.
Marta KopaczyńskaDepartment of Biomedical Engineering, Faculty of Fundamental Problems of Technology, Wrocław University of Science and Technology, Wybrzeże Wyspianskiego 27, 50-370, Wrocław, Poland.
Wojciech KałasDepartment of Experimental Oncology, Ludwik Hirszfeld Institute of Immunology and Experimental Therapy, Polish Academy of Sciences, Rudolfa Weigla 12, 53-114, Wrocław, Poland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute myeloid leukemia (AML) is an aggressive hematologic malignancy where chemoresistance, particularly to daunorubicin (DNR), frequently leads to treatment failure and relapse. Current resistance prediction methods are often slow and inaccessible in clinical settings, delaying crucial treatment adjustments. There is an urgent need for rapid, reliable, and clinically accessible diagnostic tools to identify DNR resistance early, enabling personalized therapeutic strategies and improving patient outcomes. To address this problem, we developed a rapid flow cytometric assay to detect reduced intracellular DNR accumulation, a marker of drug resistance. This was complemented by FTIR spectroscopy, confocal microscopy, and proteomic profiling to validate findings and explore underlying mechanisms in drug-resistant and sensitive cells. The flow cytometry method demonstrated that the novel Sensitivity Index (S-index) accurately predicts DNR resistance after short drug exposure and correlates strongly with IC50 values. Complementary FTIR and confocal microscopy revealed distinct biochemical and structural differences between resistant and sensitive cells. Proteomic analysis suggests that increased drug metabolism contributes to DNR resistance, supporting the flow cytometry data. In summary, our findings demonstrate that flow cytometry provides a reliable and clinically accessible tool for targeted diagnostics, crucial for optimizing patient-specific treatment strategies based on rapid assessment of daunorubicin resistance in AML.

Indexed as

Antibiotics, AntineoplasticDaunorubicinDrug Resistance, NeoplasmFlow CytometryLeukemia, Myeloid, AcuteCell Line, TumorHumansMicroscopy, ConfocalProteomicsAntibiotics, AntineoplasticDaunorubicinAcute myeloid leukemiaDaunorubicin resistanceDrug response testingEx vivo cultureFlow cytometry assayPrecision medicine

Identifiers

PMID41360907
PMCPMC12789628

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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.