Urinary Volatilomic Signatures for Non-Invasive Detection of Lung Cancer: A HS-SPME/GC-MS Proof-of-Concept Study

Area of Science:

• Biochemistry
• Analytical Chemistry
• Oncology

Background:

• Lung cancer (LC) is a leading cause of cancer death, often diagnosed late.
• Current screening methods for LC have limited performance.
• Urinary volatile organic compounds (VOCs) offer a potential non-invasive biomarker source.

Purpose of the Study:

• To characterize the urinary volatilome in lung cancer patients and healthy controls.
• To identify a distinct LC-associated volatilomic signature.
• To discover volatile organic metabolites (VOMs) with potential as diagnostic biomarkers for LC.

Main Methods:

• Headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry (HS-SPME/GC-MS) was employed.
• The urinary volatilome of 56 lung cancer patients and healthy controls was analyzed.
• Multivariate statistical analyses, including partial least squares-discriminant analysis (PLS-DA), were used for classification.

Main Results:

• A distinct metabolic profile was observed between lung cancer patients and healthy controls.
• LC patients showed elevated levels of terpenoids and aldehydes, indicative of oxidative stress.
• Healthy controls exhibited a predominance of sulfur-containing compounds and volatile phenols.
• Octanal, dehydro-p-cymene, 2,6-dimethyl-7-octen-2-ol, and 3,7-dimethyl-3-octanol were identified as potent discriminatory VOMs.

Conclusions:

• Urinary volatilomic profiling using HS-SPME/GC-MS can reveal disease-specific molecular signatures.
• This approach shows promise as a non-invasive tool for early lung cancer detection.
• Further validation in independent cohorts and integration into multi-omics frameworks are warranted.