Matrix Matters: Which Biological Sample Holds the Key to Non-Invasive Diagnostics?

At analytica 2026 in Munich, Germany, LCGC International spoke with Jef Focant from the University of Liège in Belgium, about his presentation, “GC×GC-TOFMS for Medical Volatolomics.”

In this video interview, Focant answers the following question:

• Your group works across a remarkably broad range of biological matrices — exhaled breath, serum, sputum, bronchoalveolar lavage, urine, and tissue among others — and your presentation alone spans breath VOCs and blood metabolomics and lipidomics for very different diseases. Do you find that the analytical and data handling workflows developed for one matrix translate readily to another, or does each matrix essentially demand its own bespoke optimisation from sampling all the way through to statistical modelling — and is there a matrix you consider most promising for the future of minimally invasive disease monitoring?

Medical volatolomics is a non-invasive diagnostic field that analyzes volatile organic compounds (VOCs) emitted by the human body (in breath, sweat, urine, saliva) to detect and monitor diseases, and it has received increasing attention from the medical community in recent decades. The VOC composition found in a patient's breath or bodily fluids is associated with metabolic activity and may be influenced by various conditions. As VOCs are also present in the bloodstream, they may also reflect broader physiological states.¹

Over recent years, a range of biological matrices and sampling strategies have been examined using comprehensive two-dimensional gas chromatography coupled with high-resolution time-of-flight mass spectrometry (GC×GC-HR-TOF-MS) to identify candidate biomarkers and chemical profiles for use in diagnostic models, developed in accordance with quality assurance and control protocols. Chemometric and data processing approaches were also investigated to establish data processing workflows, including validation of the statistical models used. This was applied to multi-centre breath studies across several lung conditions, including asthma subtype classification² and the identification of metabolic changes associated with systemic sclerosis (SSc) and its pulmonary complication, interstitial lung disease (ILD).³ A metabolomics and lipidomics profiling method involving multiple derivatisation steps was also developed for blood samples from colorectal cancer (CRC) patients at various disease stages.⁴

Jef Focant is professor at the University of Liège, Belgium, with a focus on the application of GC×GC–TOF-MS for medical volatolomics and metabolomics applications.

References

1. Focant, J. GC×GC-TOFMS for Medical Volatolomics. Presented at analytica 2026, Munich, Germany. https://analytica.de/en/event-program/conference/lecture/gcgc-tofms-for-medical-volatolomics-16291/ (accessed 2026-04-24).
2. Stefanuto, P.-H.; Zanella, D.; Vercammen, J.; et al. Multimodal Combination of GC×GC-HRTOFMS and SIFT-MS for Asthma Phenotyping Using Exhaled Breath. Sci Rep 2020, 10 (1), 16159. DOI: 10.1038/s41598-020-73408-2
3. Zanella, D.; Guiot, J.; Stefanuto, P.-H.; et al. Breathomics to Diagnose Systemic Sclerosis Using Thermal Desorption and Comprehensive Two-Dimensional Gas Chromatography High-Resolution Time-of-Flight Mass Spectrometry. Anal Bioanal Chem 2021, 413 (14), 3813–3822. DOI: 10.1007/s00216-021-03333-4
4. Bhatt, K.; Orlando, T.; Meuwis, M.A.; et al. Comprehensive Insight into Colorectal Cancer Metabolites and Lipids for Human Serum: A Proof-of-Concept Study. Int J Mol Sci 2023, 24 (11), 9614. DOI: 10.3390/ijms24119614