The coronavirus disease 2019 (COVID-19) pandemic has highlighted the need for different types of diagnostics, comparative validation of new tests, faster approval by federal agencies, and rapid production of test kits to meet global demands. In this Perspective, we discuss the utility and challenges of current diagnostics for COVID-19.

Circulating exosomes contain a wealth of proteomic and genetic information, presenting an enormous opportunity in cancer diagnostics. While microfluidic approaches have been used to successfully isolate cells from complex samples, scaling these approaches for exosome isolation has been limited by the low throughput and susceptibility to clogging of nanofluidics. Moreover, the analysis of exosomal biomarkers is confounded by substantial heterogeneity between patients and within a tumor itself. To address these challenges, we developed a multichannel nanofluidic system to analyze crude clinical samples. Using this platform, we isolated exosomes from healthy and diseased murine and clinical cohorts, profiled the RNA cargo inside of these exosomes, and applied a machine learning algorithm to generate predictive panels that could identify samples derived from heterogeneous cancer-bearing individuals. Using this approach, we classified cancer and precancer mice from healthy controls, as well as pancreatic cancer patients from healthy controls, in blinded studies.

In the last several years, nanoscale vesicles that originate from tumor cells and which can be found circulating in the blood (i.e. exosomes and microvesicles) have been discovered to contain a wealth of proteomic and genetic information to monitor cancer progression, metastasis, and drug efficacy. However, the use of exosomes and microvesicles as biomarkers to improve patient care has been limited by their small size (30 nm–1 μm) and the extensive sample preparation required for their isolation and measurement. In this Critical Review, we explore the emerging use of micro and nano-technology to isolate and detect exosomes and microvesicles in clinical samples and the application of this technology to the monitoring and diagnosis of cancer.