Evidence map›Paper›PMID 40351532›Full record

ArticleFrontiers in molecular biosciences2025

Early potential metabolic biomarkers of T1 stage lung adenocarcinoma based on serum metabolomics.

Bin Wu, Min Zheng, Qingkui Guo, Ning Wang, Chen Zhu, Wen Zhao, Ye Xu

Abstract read
In one paragraph

Article in Frontiers in molecular biosciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Bin WuDepartment of Thoracic Surgery, Tongren Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Min ZhengDepartment of Thoracic Surgery, Tongren Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Qingkui GuoDepartment of Thoracic Surgery, Tongren Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Ning WangDepartment of Thoracic Surgery, Tongren Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Chen ZhuDepartment of Thoracic Surgery, Tongren Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Wen ZhaoDepartment of Thoracic Surgery, Tongren Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Ye XuDepartment of Thoracic Surgery, Tongren Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This study aims to investigate serum metabolite changes in patients with early-stage (T1) lung adenocarcinoma, identify potential diagnostic biomarkers, and establish an early warning mechanism for T1 stage lung adenocarcinoma. Methods: The study included two groups: a lung adenocarcinoma group and a healthy control group. Serum samples underwent non-targeted metabolomics analysis. Total ion chromatograms (TIC) were generated to assess system stability. Chromatographic data were analyzed using multivariate statistical methods, including principal component analysis (PCA) for dimensionality reduction. Partial least squares discriminant analysis (PLS-DA) further validated PCA findings. Variables with VIP scores >1.0 in the PLS-DA model were selected, combined with ANOVA and T-tests (P < 0.05), to identify differentially expressed metabolites. Receiver operating characteristic (ROC) curve analysis was conducted to evaluate the diagnostic performance of selected metabolites. Results: Serum metabolites significantly differed between the lung adenocarcinoma group and the healthy control group. Multivariate statistical analysis and ROC curve evaluation identified four potential diagnostic biomarkers: Cortisol, 3-Oxo-OPC4-CoA, PE-NMe(14:1(9Z)/14:1(9Z)), and Ceramide (d18:1/9Z-18:1), with AUC values of 0.930, 0.895, 0.890, and 0.795, respectively. Conclusion: Cortisol,3-Oxo-OPC4-CoA,PE-NMe(14:1(9Z)/14:1(9Z)), and Ceramide (d18:1/9Z-18:1) exhibit significantly altered metabolic levels in T1 stage lung adenocarcinoma patients and can serve as metabolic biomarkers. These markers may enhance the sensitivity and specificity of early diagnosis, facilitating improved detection of T1 stage lung adenocarcinoma.

Indexed as

biomarkerLC-MSlipid metabolismlung adenocarcinomametabolomics

Identifiers

PMID40351532
PMCPMC12061714

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