Cancer-ID is a Dutch research program with the goal to develop new technology for monitoring cancer therapy through extracellular vesicle (EV) identification. In the program, 11 fundamental and applied research groups and 22 industrial partners collaborate. The program runs from 2015 to 2020.
Body fluids, such as blood, urine and cerebrospinal fluid, contain billions of submicrometer EVsextracellular vesicles per mL. These EVsextracellular vesicles originate from a variety of cell-types and play a role in intercellular communication, cellular waste management, innate immunity, immunology, coagulation and inflammation. Because the concentration, function and composition of EVsextracellular vesicles change during disease, EVextracellular vesicle-based diagnostics are expected to provide an entirely new level of clinically relevant information. Unfortunately, state-of-the-art techniques to identify and characterize EVsextracellular vesicles lack the sensitivity and specificity for the detection of rare EVextracellular vesicle types, including tumour-derived EVsextracellular vesicles. This is explained by the extremely small size and heterogeneity of EVsextracellular vesicles, and further compounded by isolation difficulties of EVsextracellular vesicles from complex body fluids. Plasma, for example, also contains high concentrations of proteins and lipoprotein particles whose size and density is similar to EVsextracellular vesicles.
Flow cytometry is currently the workhorse in clinical research on EVsextracellular vesicles, owing to its fast and sensitive measurement of fluorescence and scatter. We recognized two key problems with scatter measurements by flow cytometry. First, the sensitivity of scatter detectors requires improvement. In an international standardization study, we have shown that the majority of flow cytometers used by EV scientist cannot detect EVs <1,000 nm by scatter. Second, flow cytometers measure light scattering in arbitrary units, thereby making data interpretation and comparison difficult.
The goal of project 3.2 of Cancer-ID is to improve the sensitivity and specificity of EVextracellular vesicle measurements by modifying the hardware of an existing flow cytometer.
The contribution of Exometry to project 3.2 of Cancer-ID is to model the light scattering signals of the modified flow cytometer to (1) quantify improvements in the sensitivity and (2) determine the size and refractive index of individual particles.
Because flow cytometers measure light scattering in arbitrary units, it is difficult to quantify the sensitivity of a scatter detector. However, with Rosetta Calibration, light scattering signals of reference particles can be related to their scattering cross section in standardized units of nm2. Together with the Amsterdam University Medical Centers, Exometry will evaluate whether the scattering cross section can be used to quantify the background and photoelectron quantum yield of flow cytometry scatter detectors.
We will further evaluate whether refractive index measurements can be used to differentiate between EVsextracellular vesicles and lipoprotein particles in plasma.
We kindly thank the Dutch Research Council for funding this project.
Within Cancer-ID, Exometry contributed to the following scientific publications: