Modeling EV Kinetics for Use in Early Cancer Detection.

Abstract

Tumor-derived extracellular vesicles (EVs) represent promising biomarkers for monitoring cancers. Technological advances have improved the ability to measure EV reliably in blood using protein, RNA, or lipid detection methods. However, it is less clear how efficacious current EV assays are for the early detection of small and thus curable tumors. Here, a mathematical model is developed to estimate key parameter values and future requirements for EV testing. Tumor volumes in mice correlate well with increases in total number of circulating EV allowing the researchers to calculate EV shed rates for four different published cancer models. Model extrapolations to human physiology show good agreement with published clinical data. Specifically, it is shown that current bulk EV detection systems are ≈104 -fold too insensitive to detect human cancers of ≈1 cm3 . Conversely, it is predicted that emerging single EV methods will allow blood-based detection of cancers of <1 mm3 in humans.