Evidence map›Paper›PMID 29316075›Full record

ArticleCancer science2018

Monitoring tyrosine kinase inhibitor therapeutic responses with a panel of metabolic biomarkers in chronic myeloid leukemia patients.

Bingyu Yang, Chang Wang, Yiyu Xie, Liangjing Xu, Xiaojin Wu, Depei Wu

Abstract read
In one paragraph

Article in Cancer science, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Trial
  2. 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
    Review
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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

6 authors.

Bingyu YangJiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, China.ORCID http://orcid.org/0000-0003-4096-5707
Chang WangState Key Laboratory of Radiation Medicine and Protection, Collaborative Innovation Center of Radiological Medicine of Jiangsu Higher Education Institutions, Jiangsu Provincial Key Laboratory of Radiation Medicine and Protection, School of Radiation Medicine and Protection, Soochow University, Suzhou, China.
Yiyu XieJiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, China.
Liangjing XuJiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, China.
Xiaojin WuJiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, China.
Depei WuJiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of this study is to investigate the potential biomarkers associated with chronic myeloid leukemia (CML), reveal the metabolite changes related to the continuous phases of tyrosine kinase inhibitors (TKIs), and find the potential biomarkers associated with treatment effects. Fifty-two patients with CML and 26 matched healthy people were enrolled as the discovery set. Another 194 randomly selected CML patients treated with TKI were chosen as the external validation set. Plasma samples from the patients and controls were profiled using the gas chromatography-mass spectrometry-based metabonomic approach. Multivariate and univariate statistical analyses were combined to select the differential metabolic features. The gas chromatography-mass spectrometry-based metabolomics showed a clear clustering and separation of metabolic patterns from healthy controls and pre- and post-TKI treatment CML patients in the discovery set. We identified 9 metabolites that differentiated CML patients from healthy controls, including lactic acid, isoleucine, glycerol, glycine, myristic acid, d-sorbitol, d-galactose, d-glucose, and myo-inositol. Among the 9 markers, glycerol and myristic acid had the most significant association with TKI treatment effects in both discovery and external validation sets. In the receiver operating characteristic analysis, the combination of glycerol and myristic acid showed a better discrimination performance compared to a single biomarker. The results indicated that metabolic profiling has the potential for diagnosis of CML and the panel of biomarkers including myristic acid and glycerol could be useful in monitoring TKI therapeutic responses.

Indexed as

Biomarkers, TumorDrug Resistance, NeoplasmFemaleGas Chromatography-Mass SpectrometryGlycerolHumansLeukemia, Myelogenous, Chronic, BCR-ABL PositiveMaleMetabolomeMetabolomicsMyristic AcidProtein Kinase InhibitorsROC CurveBiomarkers, TumorGlycerolMyristic AcidProtein Kinase Inhibitorschronic phasegas chromatography-mass spectrometryleukemiametabolomicsmyeloid

Identifiers

PMID29316075
PMCPMC5834806

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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.