Harnessing insect olfactory neural circuits for noninvasive detection of human cancer

There is overwhelming evidence that metabolic processes are altered in cancer cells and these changes are manifested in the volatile organic compound (VOC) composition of exhaled breath. Here, we take a novel approach of an insect olfactory neural circuit-based VOC sensor for cancer detection. We combined an in vivo antennae-attached insect brain with an electrophysiology platform and employed biological neural computation rules of antennal lobe circuitry for data analysis to achieve our goals. Our results demonstrate that three different human oral cancers can be robustly distinguished from each other and from a non-cancer oral cell line by analyzing individual cell culture VOC composition-evoked olfactory neural responses in the insect antennal lobe. By evaluating cancer vs. non-cancer VOC-evoked population neural responses, we show that olfactory neurons response-based classification of oral cancer is sensitive and reliable. Moreover, this brain-based cancer detection approach is very fast (detection time ~ 250 ms). We also demonstrate that this cancer detection technique is effective across changing chemical environments mimicking natural conditions. Our brain-based cancer detection system comprises a novel VOC sensing methodology that will spur the development of more forward engineering technologies for noninvasive detection of cancer.