ArticleCancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology2015
Investigation of metabolomic blood biomarkers for detection of adenocarcinoma lung cancer.
Article in Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
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Who cites it
41 citing papers in PubMed.
- Prospective proteomics for discovering biomarkers in lung adenocarcinoma: a literature review.Translational cancer research · 2025Review
- Characterizing Plasma-Based Metabolomic Signatures for Metastasis in Non-Small Cell Lung Cancer.Metabolites · 2025Article
- A Comparative Study of Network-Based Machine Learning Approaches for Binary Classification in Metabolomics.Metabolites · 2025Article
- Combining Metabolomics and Machine Learning to Identify Diagnostic and Prognostic Biomarkers in Patients with Non-Small Cell Lung Cancer Pre- and Post-Radiation Therapy.Biomolecules · 2024Article
- Metabolomics-based search for lung cancer markers among patients with different smoking status.Scientific reports · 2024Article
- Non-targeted metabolomics analysis of indoleamine 2,3-dioxygenase inhibitor treatment in a mouse model of early-stage lung adenocarcinoma.Translational cancer research · 2024Article
- Monitoring central nervous system tumour metabolism using cerebrospinal fluid.Frontiers in oncology · 2024Review
- Two-Stage Deep-Learning Classifier for Diagnostics of Lung Cancer Using Metabolites.Metabolites · 2023Article
- Review
- The Importance of the Immune System and Molecular Cell Signaling Pathways in the Pathogenesis and Progression of Lung Cancer.International journal of molecular sciences · 2023Review
- Article
- A Comprehensive Search of Non-Canonical Proteins in Non-Small Cell Lung Cancer and Their Impact on the Immune Response.International journal of molecular sciences · 2022Article
- Imputation of Missing Values for Multi-Biospecimen Metabolomics Studies: Bias and Effects on Statistical Validity.Metabolites · 2022Article
- Metabolomic Fingerprinting for the Detection of Early-Stage Lung Cancer: From the Genome to the Metabolome.International journal of molecular sciences · 2022Review
- A Cost-Effectiveness Analysis of Lung Cancer Screening With Low-Dose Computed Tomography and a Diagnostic Biomarker.JNCI cancer spectrum · 2021Article
- Metabolomics and health: from nutritional crops and plant-based pharmaceuticals to profiling of human biofluids.Cellular and molecular life sciences : CMLS · 2021Review
- Metabolomic Profiling in Lung Cancer: A Systematic Review.Metabolites · 2021Review
- Article
- Evaluation of Single Sample Network Inference Methods for Metabolomics-Based Systems Medicine.Journal of proteome research · 2021Article
- 9G TestCancers · 2020Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
backgroundUntargeted metabolomics was used in case-control studies of adenocarcinoma (ADC) lung cancer to develop and test metabolite classifiers in serum and plasma as potential biomarkers for diagnosing lung cancer.
methodsSerum and plasma were collected and used in two independent case-control studies (ADC1 and ADC2). Controls were frequency matched for gender, age, and smoking history. There were 52 adenocarcinoma cases and 31 controls in ADC1 and 43 adenocarcinoma cases and 43 controls in ADC2. Metabolomics was conducted using gas chromatography time-of-flight mass spectrometry. Differential analysis was performed on ADC1 and the top candidates (FDR < 0.05) for serum and plasma used to develop individual and multiplex classifiers that were then tested on an independent set of serum and plasma samples (ADC2).
resultsAspartate provided the best accuracy (81.4%) for an individual metabolite classifier in serum, whereas pyrophosphate had the best accuracy (77.9%) in plasma when independently tested. Multiplex classifiers of either 2 or 4 serum metabolites had an accuracy of 72.7% when independently tested. For plasma, a multimetabolite classifier consisting of 8 metabolites gave an accuracy of 77.3% when independently tested. Comparison of overall diagnostic performance between the two blood matrices yielded similar performances. However, serum is most ideal given higher sensitivity for low-abundant metabolites.
conclusionThis study shows the potential of metabolite-based diagnostic tests for detection of lung adenocarcinoma. Further validation in a larger pool of samples is warranted. IMPACT: These biomarkers could improve early detection and diagnosis of lung cancer.
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