Evidence map›Paper›PMID 38965272›Full record

ArticleScientific reports2024

Metabolomics-based search for lung cancer markers among patients with different smoking status.

Agnieszka Klupczynska-Gabryszak, Evangelia Daskalaki, Craig E Wheelock, Mariusz Kasprzyk, Wojciech Dyszkiewicz, Marcin Grabicki, Beata Brajer-Luftmann, Magdalena Pawlak, Zenon J Kokot, Jan Matysiak

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Plasma metabolomic analysis in Thai EGFR-mutated non-small cell lung cancer patients.Computational and structural biotechnology journal · 2025
    Article
  6. Article
  7. Non-small-cell lung cancer.Nature reviews. Disease primers · 2024
    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

10 authors.

Agnieszka Klupczynska-GabryszakDepartment of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, Poznan, Poland. aklupczynska@ump.edu.pl.
Evangelia DaskalakiUnit of Integrative Metabolomics, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
Craig E WheelockUnit of Integrative Metabolomics, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
Mariusz KasprzykDepartment of Thoracic Surgery, Poznan University of Medical Sciences, Poznan, Poland.
Wojciech DyszkiewiczDepartment of Thoracic Surgery, Poznan University of Medical Sciences, Poznan, Poland.
Marcin GrabickiDepartment of Pulmonology, Allergology and Respiratory Oncology, Poznan University of Medical Sciences, Poznan, Poland.
Beata Brajer-LuftmannDepartment of Pulmonology, Allergology and Respiratory Oncology, Poznan University of Medical Sciences, Poznan, Poland.
Magdalena PawlakDepartment of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, Poznan, Poland.
Zenon J KokotFaculty of Health Sciences, Calisia University, Kalisz, Poland.
Jan MatysiakDepartment of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, Poznan, Poland.

Funding

National Science Centre, Poland 2017/01/X/NZ7/02064
6 · The paper itself

Abstract

Tobacco smoking is the main etiological factor of lung cancer (LC), which can also cause metabolome disruption. This study aimed to investigate whether the observed metabolic shift in LC patients was also associated with their smoking status. Untargeted metabolomics profiling was applied for the initial screening of changes in serum metabolic profile between LC and chronic obstructive pulmonary disease (COPD) patients, selected as a non-cancer group. Differences in metabolite profiles between current and former smokers were also tested. Then, targeted metabolomics methods were applied to verify and validate the proposed LC biomarkers. For untargeted metabolomics, a single extraction-dual separation workflow was applied. The samples were analyzed using a liquid chromatograph-high resolution quadrupole time-of-flight mass spectrometer. Next, the selected metabolites were quantified using liquid chromatography-triple-quadrupole mass spectrometry. The acquired data confirmed that patients' stratification based on smoking status impacted the discriminating ability of the identified LC marker candidates. Analyzing a validation set of samples enabled us to determine if the putative LC markers were truly robust. It demonstrated significant differences in the case of four metabolites: allantoin, glutamic acid, succinic acid, and sphingosine-1-phosphate. Our research showed that studying the influence of strong environmental factors, such as tobacco smoking, should be considered in cancer marker research since it reduces the risk of false positives and improves understanding of the metabolite shifts in cancer patients.

Indexed as

Biomarkers, TumorLung NeoplasmsMetabolomicsSmokingAgedChromatography, LiquidFemaleGlutamic AcidHumansLysophospholipidsMaleMetabolomeMiddle AgedPulmonary Disease, Chronic ObstructiveSphingosineSuccinic AcidBiomarkers, TumorGlutamic AcidLysophospholipidsSphingosinesphingosine 1-phosphateSuccinic AcidBiomarkerMass spectrometryMetabolic profileNon-small cell lung cancerTobacco smoking

Identifiers

PMID38965272
PMCPMC11224321

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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.