The Bhatia Lab’s peptide-based nanosensors offer a non-invasive strategy for early cancer detection. In a study published in Science Translational Medicine, researchers used intratracheally administered particles in combination with machine learning algorithms to accurately detect lung tumors as small as 2.8 cubic millimeters. Working with Jacks Lab collaborators, they showed in genetically engineered mouse models that their urine-based diagnostic could also distinguish between early-stage cancer and noncancerous inflammation of the lungs, which could greatly reduce the number of false positives in a clinical setting. Watch video.
The research was supported in part by the Marble Center for Cancer Nanomedicine, the Koch Institute Frontier Research Program through a gift from Upstage Lung Cancer, and the Johnson & Johnson Lung Cancer Initiative.