Evidence map›Paper›PMID 40559400›Full record

ArticleMetabolites2025

Metabolomic Profiling and Bioanalysis of Chronic Myeloid Leukemia: Identifying Biomarkers for Treatment Response and Disease Monitoring.

Selim Sayın, Murat Yıldırım, Batuhan Erdoğdu, Ozan Kaplan, Emine Koç, Tuba Bulduk, Melda Cömert, Mustafa Güney, Mustafa Çelebier, Meltem Aylı

Abstract read
In one paragraph

Article in Metabolites, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Oxidative Phosphorylation and Fatty Acid Oxidation Are Central to Mitochondrial Metabolism Rewiring in CML Stem/Progenitor Cell Survival.Pathophysiology : the official journal of the International Society for Pathophysiology · 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

10 authors.

Selim SayınDepartment of Hematology, Gülhane Training and Research Hospital, Ankara 06010, Türkiye.ORCID 0000-0002-7197-6890
Murat YıldırımDepartment of Hematology, Gülhane Training and Research Hospital, Ankara 06010, Türkiye.ORCID 0000-0001-6416-9575
Batuhan ErdoğduDepartment of Hematology, Gülhane Training and Research Hospital, Ankara 06010, Türkiye.ORCID 0000-0001-8968-3917
Ozan KaplanDepartment of Analytical Chemistry, Faculty of Pharmacy, Hacettepe University, Ankara 06230, Türkiye.
Emine KoçDepartment of Analytical Chemistry, Faculty of Pharmacy, Hacettepe University, Ankara 06230, Türkiye.
Tuba BuldukDepartment of Hematology, Gülhane Training and Research Hospital, Ankara 06010, Türkiye.
Melda CömertDepartment of Hematology, Gülhane Training and Research Hospital, Ankara 06010, Türkiye.
Mustafa GüneyBlood Center, Gülhane Training and Research Hospital, Ankara 06010, Türkiye.
Mustafa ÇelebierDepartment of Analytical Chemistry, Faculty of Pharmacy, Hacettepe University, Ankara 06230, Türkiye.ORCID 0000-0001-7712-5512
Meltem AylıDepartment of Hematology, Gülhane Training and Research Hospital, Ankara 06010, Türkiye.ORCID 0000-0001-5766-5642

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIncluding Chronic Myeloid Leukemia (CML) patients with deep molecular responses (MR4.5) and those with suboptimal responses provides valuable insights into treatment-associated metabolic changes. This study aimed to characterize the metabolomic alterations associated with CML and identify potential biomarkers for treatment response, particularly in patients achieving a deeper molecular response versus those with poorer responses.

methodsPlasma samples were collected from 51 chronic-phase CML patients and 24 healthy controls. CML patients were classified into two groups based on molecular responses: T1 (BCR-ABL1 IS ≤ 0.0032%) and T2 (BCR-ABL1 IS > 0.0032%, <1%). Metabolomic profiling was conducted using quadrupole time-of-flight liquid chromatography/mass spectrometry. The data analysis involved a partial least squares discriminant analysis, variable importance in projection (VIP) scores, and a pathway enrichment analysis. Significant metabolites were identified.

resultsThe PLS-DA revealed distinct metabolomic profiles between CML patients and healthy controls as well as between the T1 and T2 groups. Key differentiating metabolites with VIP scores > 1.5 included glutamate, hypoxanthine, and D-galactonic acid. In the T2 group, significant increases in malate and 5-aminoimidazole-4-carboxamide ribonucleotide were observed, reflecting disruptions in purine metabolism, the tricarboxylic acid cycle, and amino acid metabolism. The pathway enrichment analysis highlighted significant alterations in CML energy metabolism, nucleotide synthesis, and amino acid biosynthesis.

conclusionsCML patients exhibit pronounced metabolic changes, particularly in energy and nucleotide metabolism, which are linked to treatment response. These findings provide novel insights into CML biology and suggest potential biomarkers for monitoring treatment efficacy and predicting outcomes and therapeutic targets for improving treatment outcomes and overcoming tyrosine kinase inhibitor resistance.

Indexed as

chronic myeloid leukemiaLC/MSmetabolomicsmolecular responsetyrosine kinase inhibitors

Identifiers

PMID40559400
PMCPMC12195291

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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.