Identification and validation of extracellular vesicle reference genes for the normalization of RT-qPCR data.

Extracellular vesicles (EVs) contain a plethora of biomolecules, including nucleic acids, with diverse diagnostic and therapeutic application potential. Although reverse transcription-quantitative PCR (RT-qPCR) is the most widely applied laboratory technique to evaluate gene expression, its applicability in EV research is challenged by the lack of universal and stably present reference genes (RGs). In this study, we identify, validate and establish SNRPG, OST4, TOMM7 and NOP10 as RGs for the normalization of EV-associated genes by RT-qPCR. We show the stable presence of SNRPG, OST4, TOMM7 and NOP10 in multiple cell lines and their secreted EVs (n = 12) under different (patho)physiological conditions as well as in human-derived biofluids (n = 3). Enzymatic treatments confirm the presence of SNRPG, OST4, TOMM7 and NOP10 inside EVs. In addition, the four EV-associated RGs are stably detected in a size-range of EV subpopulations. RefFinder analysis reveals that SNRPG, OST4, TOMM7 and NOP10 are more stable compared to RGs established specifically for cultured cells or tissues such as HMBS, YWHAZ, SDHA and GAPDH. In summary, we present four universal and stably present EV-associated RGs to enable normalization and thus steer the implementation of RT-qPCR for the analysis of EV-associated RNA cargo for research or clinical applications.

Depletion of soluble cytokines unlocks the immunomodulatory bioactivity of extracellular vesicles.

Despite an enormous interest in understanding the bioactivity of extracellular vesicles (EV) in physiology and disease for the development of therapeutic applications, the impact of EV preparation methods remains minimally explored. In this study, we implemented density gradient ultracentrifugation combined with size-exclusion chromatography (DG-SEC), differential ultracentrifugation (dUC) and/or stand-alone SEC (sSEC) to fractionate media conditioned by different cancer cells and/or cancer-associated fibroblasts (CAF). EV-enriched but protein-depleted versus EV-depleted but protein-enriched DG-SEC fractions, and EV-containing dUC and sSEC preparations were quality controlled for particle number, protein concentration, selected protein composition and ultrastructure, characterized for their cytokine content, and dose-dependently evaluated for monocyte-derived dendritic cell (MoDC) maturation by measuring surface marker expression and/or cytokine secretion. EV preparations obtained by DG-SEC from media conditioned by different cancer cell lines or CAF, were depleted from soluble immune suppressive cytokines such as VEGF-A and MCP-1 and potently stimulated MoDC maturation. In contrast, EV-containing dUC or sSEC preparations were not depleted from these soluble cytokines and were unable to mature MoDC. Subsequent processing of dUC EV preparations by SEC dose-dependently restored the immunomodulatory bioactivity. Overall, our results demonstrate that method-dependent off-target enrichment of soluble cytokines has implications for the study of EV immunomodulatory bioactivity and warrants careful consideration.

Integrating automated liquid handling in the separation workflow of extracellular vesicles enhances specificity and reproducibility.

BACKGROUND: Extracellular vesicles (EV) are extensively studied in human body fluids as potential biomarkers for numerous diseases. Major impediments of EV-based biomarker discovery include the specificity and reproducibility of EV sample preparation as well as intensive manual labor. We present an automated liquid handling workstation for the density-based separation of EV from human body fluids and compare its performance to manual handling by (in)experienced researchers. RESULTS: Automated versus manual density-based separation of trackable recombinant extracellular vesicles (rEV) spiked in PBS significantly reduces variability in rEV recovery as quantified by fluorescent nanoparticle tracking analysis and ELISA. To validate automated density-based EV separation from complex body fluids, including blood plasma and urine, we assess reproducibility, recovery, and specificity by mass spectrometry-based proteomics and transmission electron microscopy. Method reproducibility is the highest in the automated procedure independent of the matrix used. While retaining (in urine) or enhancing (in plasma) EV recovery compared to manual liquid handling, automation significantly reduces the presence of body fluid specific abundant proteins in EV preparations, including apolipoproteins in plasma and Tamm-Horsfall protein in urine. CONCLUSIONS: In conclusion, automated liquid handling ensures cost-effective EV separation from human body fluids with high reproducibility, specificity, and reduced hands-on time with the potential to enable larger-scale biomarker studies.

Detection of Breast Cancer-Specific Extracellular Vesicles with Fiber-Optic SPR Biosensor.

Extracellular vesicles (EVs) have attracted great attention as potential biomarkers for cancer diagnostics. Although several technologies have been developed for EV detection, many of them are still not applicable to clinical settings as they rely on complex EV isolation processes, while lacking sensitivity, specificity or standardization. To solve this problem, we have developed a sensitive breast cancer-specific EV detection bioassay directly in blood plasma using a fiber-optic surface plasmon resonance (FO-SPR) biosensor, previously calibrated with recombinant EVs. First, we established a sandwich bioassay to detect SK-BR-3 EVs by functionalizing the FO-SPR probes with anti-HER2 antibodies. A calibration curve was built using an anti-HER2/Banti-CD9 combination, resulting in an LOD of 2.1 × 107 particles/mL in buffer and 7 × 108 particles/mL in blood plasma. Next, we investigated the potential of the bioassay to detect MCF7 EVs in blood plasma using an anti-EpCAM/Banti-mix combination, obtaining an LOD of 1.1 × 10 8 particles/mL. Finally, the specificity of the bioassay was proven by the absence of signal when testing plasma samples from 10 healthy people unknown to be diagnosed with breast cancer. The remarkable sensitivity and specificity of the developed sandwich bioassay together with the advantages of the standardized FO-SPR biosensor highlight outstanding potential for the future of EV analysis.

Transparent reporting of experimental parameters in assays measuring phenotypic steps in metastasis.

Metastasis is key to cancer mortality. Understanding its biology is vital for developing strategies to prevent and treat metastasis. Phenotypic assays to either study metastasis or evaluate anti-metastatic drugs are widely used in preclinical research. This technical note discusses the adherence of reporting essential experimental and methodological parameters in chemotactic invasion assays in vitro and spontaneous metastasis assays in vivo. Following the analysis of 130 recent (< 5 years) research papers, several shortcomings in reporting were identified. Therefore, we strongly argue to increase experimental rigor which should result in a significant improvement with respect to reproducibility of preclinical metastasis research.