ArticleScientific reports2025
Characterizing volatile organic compound profiles in oral cancer using multiple sample collection approaches by GC-IMS and TD-GC-MS.
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 3 papers.
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Who cites it
3 citing papers in PubMed.
- Oral cancer in the era of precision medicine: molecular targets and technological innovations.Scientific reports · 2026Article
- Identification of oral squamous cell carcinoma by an electronic nose based on an array of metal oxide sensors with machine learning.BMC oral health · 2026Article
- Rapid and noninvasive artificial intelligence-assisted diagnostic method for oral squamous cell carcinoma.NPJ digital medicine · 2026Article
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9 authors.
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Abstract
Oral cancer (OC) is an aggressive malignancy with poor prognosis due to late-stage diagnosis and limited early detection tools. Volatile organic compounds (VOCs) have emerged as potential biomarkers for early OC detection, offering a non-invasive approach. However, the optimal sample collection and analytical workflow remains unclear. This study compares the diagnostic potential and clinical feasibility of exhaled breath, lesional air, and lesional brushings using thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS) and gas chromatography-ion mobility spectrometry (GC-IMS). Twenty-six participants (13 OC or high-grade lesion patients, 13 controls) were recruited. Multivariate analysis assessed group separation and identified key discriminatory features. TD-GC-MS detected more VOCs and demonstrated stronger separation between OC and controls across all sample types compared to GC-IMS. Lesional brushings provided the best separation between groups, followed by lesional air and exhaled breath. Key discriminatory compounds included various alkanes, alkenes, aromatic hydrocarbons, phenylmethanol, and a homologous series of saturated ketones, many of which have been reported as OC biomarkers. Lesional brushings and lesional air analyzed by TD-GC-MS emerged as the most promising approaches for OC detection. GC-IMS, despite limitations, holds potential as a valuable point-of-care OC screening tool. VOC-based diagnostics offer a promising non-invasive approach for early OC detection.
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