ArticleScientific reports2025
Identification of a panel of volatile organic compounds in urine for early detection of for bladder cancer.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Urinary and cellular volatile organic compounds as biomarkers for urological cancers: a systematic review of GC-MS-based volatolomics.Metabolomics : Official journal of the Metabolomic Society · 2026Pooled it
- Urinary volatilomics for biomarker discovery in kidney stone patients and healthy controls.Urolithiasis · 2026Article
- Article
- Urinary Volatilomic Signatures for Non-Invasive Detection of Lung Cancer: A HS-SPME/GC-MS Proof-of-Concept Study.International journal of molecular sciences · 2026Article
- Headspace SPME GC-MS Analysis of Urinary Volatile Organic Compounds (VOCs) for Classification Under Sample-Limited Conditions.Metabolites · 2026Article
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Authors and funding
8 authors.
Funding
Abstract
The absence of specific markers makes early detection of bladder cancer (BC) challenging. Recent studies have reported the reliable diagnostic significance of volatile organic compounds (VOCs) in several cancers. This study aimed to investigate whether urinary VOCs could serve as potential biomarkers for BC. A total of 89 BC patients and 67 healthy individuals were recruited for this study. VOCs in urine samples were detected using gas chromatography-ion mobility spectrometry (GC-IMS). Machine learning algorithms were used to establish diagnostic models for predicting BC based on differential expressed VOCs. Compared with healthy individuals, A total of 20 differentially expressed VOCs were identified, including 17 upregulated and 3 downregulated. Among five machine-learning algorithms, the Random Forests (RF) provided the highest accuracy. Based on RF analysis, eight important VOCs (2-Undecenal, 2-propanone, 1-octanal, Ethyl 2-hydroxybenzoate, 2-ethyl hexanol-D, 2-Pentanone, 1-Propanol,3-(methylthio), 1-nonanal) were identified and used to constructed a diagnostic model, showing the highest diagnostic accuracy and area under the curve (AUC) of 91.5% and 0.958, respectively. Our results suggest a VOCs panel might be used as novel biomarker for early detection of BC.
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