Evidence map›Paper›PMID 40208363›Full record

ArticleClinical and experimental medicine2025

Identification of glucuronic acid as a biomarker of poor prognosis in acute myeloid leukemia based on plasma metabolomics.

Jinrong Yang, Zixu Wang, Kun Wu, Jingyan Ruan, Bo Nie, Qiang Zhou, Liyin Li, Li Luo, Fujia Zhang, Mingxia Shi and 1 more

Abstract read
In one paragraph

Article in Clinical and experimental medicine, 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. A Synthetic Lectin for Glucuronate.ACS central science · 2025
    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.

Jinrong YangDepartment of Hematology, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, 650032, People's Republic of China.
Zixu WangDepartment of Dermatology, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, 650032, People's Republic of China.
Kun WuDepartment of Clinical Laboratory, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, 650032, People's Republic of China.
Jingyan RuanDepartment of Hematology, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, 650032, People's Republic of China.
Bo NieDepartment of Hematology, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, 650032, People's Republic of China.
Qiang ZhouDepartment of Hematology, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, 650032, People's Republic of China.
Liyin LiDepartment of Hematology, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, 650032, People's Republic of China.
Li LuoDepartment of Hematology, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, 650032, People's Republic of China.
Fujia ZhangDepartment of Hematology, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, 650032, People's Republic of China.
Mingxia ShiDepartment of Hematology, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, 650032, People's Republic of China. shmxia2002@sina.com.
Yun ZengDepartment of Hematology, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, 650032, People's Republic of China. zengyun_fyy@sina.com.

Funding

Yunnan Province High-Level Talent Training Support Program "Famous Medical Special Project No. RLMY20200020
6 · The paper itself

Abstract

Metabolic abnormalities have been identified in various solid tumors and hematologic diseases, with reprogramming of central carbon metabolism occurring to promote disease progression. However, the metabolic profile of central carbon in acute myeloid leukemia (AML) remains unknown. We employed targeted metabolomics to analyze the alterations in central carbon metabolites present in the blood of acute myeloid leukemia (AML) patients. Models constructed using orthogonal partial least squares discriminant analysis (OPLS-DA) were utilized to evaluate intergroup differences in metabolite levels. Furthermore, a public database facilitated the kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis. Additionally, metabolites exhibiting significant differences were selected, and their effects on the proliferation and drug resistance of human myeloid leukemia cell lines were validated in vitro using CCK-8 analysis, MTT assays, and flow cytometry. Our results indicated that 27 targeted metabolites were up-regulated and eight targeted metabolites were down-regulated in the AML group. These metabolites were primarily enriched in pathways related to the biosynthesis of cofactors, glyoxylate and dicarboxylate metabolism, glucagon signaling, 2-oxocarboxylic acid metabolism, biosynthesis of amino acids, the citrate cycle (TCA cycle), and central carbon metabolism in cancer. Notably, significant changes were observed in malic acid, alpha-ketoisovaleric acid, and glucuronic acid. In vitro experiments demonstrated that exogenous glucuronic acid can promote the growth and drug resistance of human AML cells. In conclusion, this study reveals alterations in central carbon metabolites in the blood of AML patients and identifies metabolites that may play a role in AML development and drug resistance.

Indexed as

Biomarkers, TumorLeukemia, Myeloid, AcuteMetabolomicsAdultAgedCell Line, TumorCell ProliferationDrug Resistance, NeoplasmFemaleHumansMaleMetabolomeMiddle AgedPrognosisBiomarkers, TumorAcute myeloid leukemiaBiomarkerCentral carbon metabolismGlucuronic acidMetabolomics

Identifiers

PMID40208363
PMCPMC11985698

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.