A team of researchers from China and Poland has developed a new biosensor that can detect hexanal, a compound found at elevated levels in the breath of people with lung cancer, offering a potential tool for early, non-invasive diagnosis of the disease.
Lung cancer is usually detected at an advanced stage, when treatment outcomes are poor. While imaging methods such as chest X-rays and computed tomography improve detection rates, scientists continue to seek faster and less invasive techniques for early screening.
According to the National Centre for Nuclear Research, one of the most promising areas is breathomics, which analyses volatile organic compounds (VOCs) in exhaled air.
Of particular interest is hexanal, an aldehyde whose concentration is significantly higher in the breath of lung cancer patients. Detecting it at very low concentrations, however, remains technically challenging.
Amil Aligayev, PhD, from the NOMATEN CoE at the National Centre for Nuclear Research, together with researchers from China and the Warsaw University of Technology, has been working to create a biosensor sensitive enough to identify trace amounts of hexanal.
The team aimed to develop a device that “combines two complementary detection techniques: surface-enhanced Raman scattering (SERS) and colorimetric sensing,” making it both highly sensitive and simple to use.
When exposed to hexanal, the patch generates a strong Raman signal and turns a distinct blue colour. Low concentrations can be detected through Raman analysis, while slightly higher levels trigger a visible colour change.
“The sensor also shows high selectivity, repeatability of results, long-term stability and antibacterial properties, which make it suitable for practical applications,” said Amil Aligayev from the NOMATEN CoE at the National Centre for Nuclear Research.
The biosensor is based on hydrogel, allowing it to be embedded in a face mask. Tests with breath samples from lung cancer patients and healthy individuals showed clear differences between the two groups in both Raman signals and colour changes.
“This dual-mode approach not only enables sensitive and selective detection of lung cancer biomarkers, but also paves the way for practical, non-invasive, and low-cost early screening tools,” said Jialin Li from Southeast University in China, the first author of the study.
The researchers also created a deep learning recognition system that can analyse changes in the patch’s colour in real time on smartphones or computers.
The full study has been published in the Chemical Engineering Journal (https://doi.org/10.1016/j.cej.2025.168343).
PAP - Science in Poland
lt/ agt/
tr. RL
