ArticleFrontiers in oncology2025
Identifying novel biomarkers for biliary tract cancer based on volatile organic compounds analysis and machine learning.
Article in Frontiers in oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- GC-IMS-based analysis of serum volatile organic compounds for diagnosis of gastric cancer.Scientific reports · 2026Article
- Identification of Shared Diagnostic Biomarkers LCN2 and DUOX2 for Inflammatory Bowel Disease and Cholangiocarcinoma Through Integrative Bioinformatics and Machine Learning.Journal of inflammation research · 2025Article
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Authors and funding
5 authors.
Funding
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Abstract
Background: The current diagnostic methods for biliary tract cancer (BTC) have limitations in sensitivity and specificity. This study aims to explore the use of volatile organic compounds (VOCs) in serum to distinguish BTC and benign biliary diseases (BBD). Method: We collected 158 serum samples from BTC and BBD patients, and used gas chromatography ion mobility spectrometry (GC-IMS) for VOCs detection. Six machine learning methods (RF, SVM, LDA, KNN, LASSO, and XGBoost) were used to construct and evaluate diagnostic prediction models. Result: We detected a total of 40 VOCs in patients, of which 14 VOCs were statistically significant ( Conclusion: The diagnostic model based on 4-VOCs may be a feasible method for distinguishing the diagnosis of BTC and BBD patients.
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