Researchers at the University Medical Center Hamburg-Eppendorf have developed a robust assay that could serve as a diagnostic tool for monitoring disease status, treatment response and tumor progression in patients with glioma.
The method uses imaging flow cytometry (IFCM) to characterize and isolate tumor-specific extracellular vesicle populations in this patient population.
Image Credits: Maltsev Semion / Shutterstock.com
Detecting changes that indicate treatment response is challenging
A significant clinical hurdle in cancer management is the detection of molecular and cellular changes in tumors during treatment that will indicate patients’ response or resistance to therapy.
While increasingly sensitive and specific technologies are emerging, they are expensive and often not suitable for use over frequent, short-interval sequential time points. Researchers have therefore become interested in biological materials released by tumors that can be obtained by liquid biopsy and could serve as biomarkers for cancer progression.
Aside from circulating tumor cells and circulating tumor DNA, which are the most common analytes used in liquid biopsy assays, extracellular vesicles (EVs) have received increasing interest over the last few years.
Cells release nano-sized vesicles either as exosomes or through budding from the plasma membrane as EVs. These EVs are known to play important roles in disease and could serve as biomarkers in cancer patients, including in glioma patients.
Most cancer cells shed EVs into the tumor microenvironment that contains molecular cargo such as proteins, nucleic acids, and lipids. The EV content reflects the cell of origin, meaning EVs can serve as a source of genetically or biologically active material.
However, current technologies are not yet specific enough to characterize individuals EVs. Previous studies analyzing EVs circulating in blood and plasma have generally used Western blotting, bead-based flow cytometry or nanoparticle tracking analysis (NTA) to asses bulk EV preparations.
Since EVs are also shed by normal cells, such preparations are invariably “contaminated” by non-tumor derived EVs. This results in low detection sensitivity of tumor-specific molecular alterations by methods such as DNA and RNA sequencing or mass spectrometry and is not suitable for the detection of rare mutations, treatment monitoring or for the precise analysis of single EVs.
Such analysis would require more sophisticated techniques that enable the identification and enrichment of tumor-specific EVs to reduce signals derived from healthy cells.
Using IFCM for single EV analysis
IFCM has previously been used to track cellular EV-uptake and to monitor the particles’ ability to bind to the outer cell membrane. However, due to their tiny size (typically <1000 nm) of these nanoparticles, the surface protein analysis of single EVs presents a significant challenge.
EVs are commonly identified by members of the tetraspanin family CD9, CD63, and CD81, which are highly abundant on the EV surface. However, few studies have looked at the heterogeneity between different tetraspanin-positive EV subpopulations.
Now, Katrin Lamszus and colleagues have demonstrated IFCM to be a robust, multiparametric technique for single EV analysis of the CD9, CD63, CD81 surface profiles for the discrimination of distinct glioma EV subpopulations.
EVs were stained using a robust immunofluorescence protocol, and concurrent membrane filtration was used to eliminate unbound excessive antibodies prior to IFCM analysis.
The suitability of commercially available fluorophore-conjugated antibodies for single EV detection was validated by correlative light and electron microscopy. Multiparameter IFCM analysis was optimized through the integration of distinct software settings for robust, practical and simple single-EV characterization.
Testing EV tetraspanin profiles in cancer cell lines and glioma patients
As reported in the Journal of Extracellular Vesicles, CD9, CD63, and CD81 fluorescent-labeled antibodies stained single EVs in a multiparametric surface protein fashion and enabled the detection of triple-positive EVs as well as single positive EVs.
After establishing that IFCM can detect different tetraspanins on single EVs, the team analyzed the EV tetraspanin expression profiles in human cancer cell lines and non-tumor cells, as well as in the cells themselves.
After finding that glioblastoma cell lines secrete EVs with different tetraspanin profiles compared with normal cells, the team decided to test whether tetraspanin profiles are also altered on circulating EVs from glioblastoma patients.
“IFCM analysis of EVs expressing CD9, CD63 or CD81 isolated from patient plasma revealed significantly increased levels of CD63+ EVs in patients with glioblastoma compared with healthy donors,” reports the team. A similar but not significant trend was observed for CD81.
The total numbers of double-positive CD63+/CD81+ and CD9+/CD63+ EVs were increased in glioblastoma patients and the proportion of all three different double-positive EV fractions was elevated, with the CD63+/CD81+ combination being the most significant.
The authors say the study provides proof-of-principle for the feasibility of using IFCM to identify distinct EV subpopulations that circulate in the blood of glioma patients.
“Currently, glioma patients are followed by periodic MRI scans, and the detection of suspicious lesions requires invasive biopsy or tumor resection for diagnostic confirmation,” they write.
EVs, on the other hand, which can easily be obtained by liquid biopsy, “could become a non-invasive alternative to provide dynamic information on the tumour state and its molecular profile,” conclude Lamszus and team.
Lamszus K, et al. Imaging flow cytometry facilitates multiparametric characterization of extracellular vesicles in malignant brain tumours. Journal of Extracellular Vesicles, 2019;8(1) Available at: https://doi.org/10.1080/20013078.2019.1588555