Honeybees Detect Lung Cancer Biomarkers with 82% Success Rate – Groundbreaking Study Reveals

East Lansing, Michigan – Researchers at Michigan State University have made a groundbreaking discovery involving honeybees and their ability to detect chemicals associated with lung cancer in human breath. In a study published in the journal Biosensors and Bioelectronics, the researchers found that honeybees were able to identify lung cancer biomarkers with an impressive 82% success rate.

The study’s lead author, MSU professor Debajit Saha, compared the honeybees’ sense of smell to that of dogs, highlighting the insects’ remarkable olfactory capabilities. Saha and his team aimed to determine whether honeybees could differentiate between the chemicals present in the breath of a healthy individual and those of someone with lung cancer.

To conduct the study, the researchers created a synthetic breath mixture that contained six compounds found in the breath of a person with cancer, as well as a synthetic “healthy” breath mixture. They then exposed approximately 20 bees to these mixtures and observed their neural responses by attaching tiny electrodes to their brains.

The results were astounding, as the bees were able to detect even small concentrations of the cancer-indicating compounds. This ability to differentiate between synthetic lung cancer breath and healthy breath showcases the potential for using honeybees as a biological sensor for detecting lung cancer in humans.

Autumn McLane-Svoboda, a graduate student on Saha’s team, emphasized the significance of this research, highlighting the bees’ capability to identify different types of lung cancer cells. The hope is that this innovative approach could lead to the development of a sensor based on the honeybee brain, enabling swift and accurate cancer diagnoses for patients.

With lung cancer being the leading cause of cancer-related deaths globally, early detection is crucial for improving survival rates. The researchers’ findings offer a promising outlook for early detection strategies and personalized treatment approaches for lung cancer patients.