ArticleMolecular medicine reports2017
A pilot study identifying a potential plasma biomarker for determining EGFR mutations in exons 19 or 21 in lung cancer patients.
Article in Molecular medicine reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 10 citations in OpenAlex.
- Plasma metabolomic analysis in Thai EGFR-mutated non-small cell lung cancer patients.Computational and structural biotechnology journal · 2025Article
- Article
- Metabolomics of VToxicology and applied pharmacology · 2023Article
- A Comprehensive Analysis of Microflora and Metabolites in the Development of Ulcerative Colitis into Colorectal Cancer Based on the Lung-Gut Correlation Theory.Molecules (Basel, Switzerland) · 2022Article
- Identification of potential serum biomarkers for simultaneously classifying lung adenocarcinoma, squamous cell carcinoma and small cell carcinoma.Cancer biomarkers : section A of Disease markers · 2021Article
- An Integrative Metabolomic and Network Pharmacology Study Revealing the Regulating Properties of Xihuang Pill That Improves Anlotinib Effects in Lung Cancer.Frontiers in oncology · 2021Article
- Early diagnosis and screening in lung cancer.American journal of cancer research · 2020Review
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The most common type of lung cancer is non‑small cell lung cancer (NSCLC), which is frequently characterized by a mutation in the epidermal growth factor receptor (EGFR). Determining the presence of an EGFR mutation in lung cancer is important, as it determines the type of treatment that a patients will receive. Therefore, the aim of the present study was to apply high‑resolution metabolomics (HRM) using liquid chromatography‑mass spectrometry to identify significant compounds in human plasma samples obtained from South Korean NSCLC patients, as potential biomarkers for providing early detection and diagnosis of minimally‑invasive NSCLC. The metabolic differences between lung cancer patients without EGFR mutations were compared with patients harboring EGFR mutations. Univariate analysis was performed, with a false discovery rate of q=0.05, in order to identify significant metabolites between the two groups. In addition, hierarchical clustering analysis was performed to discriminate between the metabolic profiles of the two groups. Furthermore, the significant metabolites were identified and mapped using Mummichog software, in order to generate a potential metabolic network model. Using metabolome‑wide association studies, metabolic alterations were identified. Linoleic acid [303.23 m/z, (M+Na)+], 5‑methyl tetrahydrofolate [231.10 m/z, (M+2H)+] and N‑succinyl‑L‑glutamate‑5 semialdehyde [254.06 m/z, (M+Na)+], were observed to be elevated in patients harboring EGFR mutations, whereas tetradecanoyl carnitine [394.29 m/z, (M+Na)+] was observed to be reduced. This suggests that these compounds may be affected by the EGFR mutation. In conclusion, the present study identified four potential biomarkers in patients with EGFR mutations, using HRM combined with pathway analysis. These results may facilitate the development of novel diagnostic tools for EGFR mutation detection in patients with lung cancer.
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