Early detection of lung cancer is vital for effective treatment, yet the biomarkers for the early stages of the disease are difficult to pick up. One of the most promising diagnostic developments are e-nose (electronic nose) devices, which analyse compounds in the vapour of human breath, combining electronic sensors with mechanisms for pattern recognition, such as neural networks. More sensitive electrodes lead to stronger patterns for the neural networks to analyse, leading to better detection of cancer biomarkers.
With this in mind, the team used multi-layered graphene to create electrodes for a biosensor, demonstrating sensing capabilities for three of the most common lung-cancer biomarkers - ethanol, isopropanol and acetone – across different concentrations. As well as exhibiting enhanced sensitivity for cancer detection, the sensor is also reusable, making it more cost-effective than alternative sensors used in e-nose devices. The research appears in the Royal Society of Chemistry's journal Nanoscale.
"The new biosensors which we have developed show that graphene has significant potential for use as an electrode in e-nose devices,” said study co-author Ben Hogan, a postgraduate researcher from the University of Exeter. “For the first time, we have shown that with suitable patterning graphene can be used as a specific, selective and sensitive detector for biomarkers.”
Although it is one of the most common and aggressive cancers, killing around 1.4 million people worldwide each year, the lack of clinical symptoms in its early stages means many patients go undiagnosed until the later stages. Using multi-layered graphene, the team believes current e-nose devices could transform breath diagnostic techniques and improve patient outcomes for lung cancer treatment.
"We believe that with further development of our devices, a cheap, reusable and accurate breath test for early-stage detection of lung cancer can become a reality,” said Hogan.
Five ways to prepare for your first day
If I may add my own personal Tip No. 6 it goes something like this: From time to time a more senior member of staff will start explaining something...