Rapid Discrimination of Extracellular Vesicles by Shape Distribution Analysis

A rapid and simple cancer detection method independent of cancer type is an important technology for cancer diagnosis. Although the expression profiles of biological molecules contained in cancer cell-derived extracellular vesicles (EVs) are considered candidates for discrimination indexes to identify any cancerous cells in the body, it takes a certain amount of time to examine these expression profiles. Here, we report the shape distributions of EVs suspended in a solution and the potential of these distributions as a discrimination index to discriminate cancer cells. Distribution analysis is achieved by low-aspect-ratio nanopore devices that enable us to rapidly analyze EV shapes individually in solution, and the present results reveal a dependence of EV shape distribution on the type of cells (cultured liver, breast, and colorectal cancer cells and cultured normal breast cells) secreting EVs. The findings in this study provide realizability and experimental basis for a simple method to discriminate several types of cancerous cells based on rapid analyses of EV shape distributions.