The relevance of extracellular vesicles (EVs) has grown exponentially, together with innovative basic research branches that feed medical and bioengineering applications. Such attraction has been fostered by the biological roles of EVs, as they carry biomolecules from any cell type to trigger systemic paracrine signaling or to dispose metabolism products. To fulfill their roles, EVs are transported through circulating biofluids, which can be exploited for the administration of therapeutic nanostructures or collected to intercept relevant EV-contained biomarkers. Despite their potential, EVs are ubiquitous and considerably heterogeneous. Therefore, it is fundamental to profile and identify subpopulations of interest. In this study, we optimized EV-labeling protocols on two different high-resolution single-particle platforms, the NanoFCM NanoAnalyzer (nFCM) and Particle Metrix ZetaView Fluorescence Nanoparticle Tracking Analyzer (F-NTA). In addition to the information obtained by particles’ scattered light, purified and non-purified EVs from different cell sources were fluorescently stained with combinations of specific dyes and antibodies to facilitate their identification and characterization. Despite the validity and compatibility of EV-labeling strategies, they should be optimized for each platform. Since EVs can be easily confounded with similar-sized nanoparticles, it is imperative to control instrument settings and the specificity of staining protocols in order to conduct a rigorous and informative analysis.

We evaluated the advantages and the reliability of novel protocols for the enrichment of tumor extracellular vesicles (EVs), enabling a blood-based test for the noninvasive parallel profiling of multiple androgen receptor (AR) gene alterations. Three clinically relevant AR variants related to response/resistance to standard-of-care treatments (AR-V7 transcript, AR T878A point mutation and AR gene amplification) were evaluated by digital PCR in 15 samples from patients affected by Castration-Resistant Prostate Cancer (CRPC). Plasma was processed to obtain circulating RNA and DNA using protocols based on tumor EVs enrichment through immuno-affinity and peptide-affinity compared to generic extraction kits. Our results showed that immuno-affinity enrichment prior to RNA extraction clearly outperforms the generic isolation method in the detection of AR-V7, also allowing for a distinction between responder (R) and non-responder (NR) patients. The T878A mutation was detected, overall, in nine out of 15 samples and no approach alone was able to reveal mutations in all harboring samples, showing that the employed methods complement each other. AR amplification was detected in the majority of CRPC samples analysed using either cell-free DNA (cfDNA) or exosome isolation kits (80%). We demonstrated that selective isolation of a subset of circulating exosomes enriched for tumor origin, rather than analysis of total plasma exosomes, or total plasma nucleic acids, increases sensitivity and specificity for the detection of specific alterations.

Urine features an ideal source of non-invasive diagnostic markers. Some intrinsic and methodological issues still pose barriers to its full potential as liquid biopsy substrate. Unlike blood, urine concentration varies with nutrition, hydration and environmental factors. Urine is enriched with EVs from urinary-genital tract, while its conservation, purification and normalization can introduce bias in analysis of EV subsets in inter-and intra-individual comparisons. The present study evaluated the methods that decrease such biases such as appropriate and feasible urine storage, optimal single-step EV purification method for recovery of proteins and RNAs from small urine volumes and a normalization method for quantitative analysis of urine EV RNAs. Ultracentrifugation, chemical precipitation and immuno-affinity were used to isolate EVs from healthy donors’ urine that was stored frozen or at room temperature for up to 6 months. Multiple urine biochemical and EV parameters, including particle count and protein content, were compared across urine samples. To this purpose nanoparticle tracking analysis (NTA) and protein assessment by BCA, ELISA and WB assays were performed. These measurements were correlated with relative abundances of selected EV mRNAs and miRNAs assessed by RT-PCR and ranked for the ability to reflect and correct for EV content variations in longitudinal urine samples. All purification methods enabled recovery and downstream analysis of EVs from as few as 1 ml of urine. Our findings highlight long term stability of EV RNAs upon urine storage at RT as well as excellent correlation of EV content in urine with some routinely measured biochemical features, such as total urine protein and albumin, but not creatinine most conventionally used for urine normalization. Comparative evaluation of mRNA and miRNAs in EV isolates revealed specific RNAs, in particular RNY4 and small miRNA panel, levels of which well reflected the inter-sample EV variation and therefore useful as possible post-analytical normalizers of EV RNA content. We describe some realistic urine processing and normalization solutions for unbiased readout of EV biomarker studies and routine clinical sampling and diagnostics providing the input for design of larger validation studies employing urine EVs as biomarkers for particular conditions and diseases.

Background: Intercellular communication is mediated by extracellular vesicles (EVs), as they enclose selectively packaged biomolecules that can be horizontally transferred from donor to recipient cells. Because all cells constantly generate and recycle EVs, they provide accurate timed snapshots of individual pathophysiological status. Since blood plasma circulates through the whole body, it is often the biofluid of choice for biomarker detection in EVs. Blood collection is easy and minimally invasive, yet reproducible procedures to obtain pure EV samples from circulating biofluids are still lacking. Here, we addressed central aspects of EV immunoaffinity isolation from simple and complex matrices, such as plasma. Methods: Cell-generated EV spike-in models were isolated and purified by size-exclusion chromatography, stained with cellular dyes and characterized by nano flow cytometry. Fluorescently-labelled spike-in EVs emerged as reliable, high-throughput and easily measurable readouts, which were employed to optimize our EV immunoprecipitation strategy and evaluate its performance. Plasma-derived EVs were captured and detected using this straightforward protocol, sequentially combining isolation and staining of specific surface markers, such as CD9 or CD41. Multiplexed digital transcript detection data was generated using the Nanostring nCounter platform and evaluated through a dedicated bioinformatics pipeline. Results: Beads with covalently-conjugated antibodies on their surface outperformed streptavidin-conjugated beads, coated with biotinylated antibodies, in EV immunoprecipitation. Fluorescent EV spike recovery evidenced that target EV subpopulations can be efficiently retrieved from plasma, and that their enrichment is dependent not only on complex matrix composition, but also on the EV surface phenotype. Finally, mRNA profiling experiments proved that distinct EV subpopulations can be captured by directly targeting different surface markers. Furthermore, EVs isolated with anti-CD61 beads enclosed mRNA expression patterns that might be associated to early-stage lung cancer, in contrast with EVs captured through CD9, CD63 or CD81. The differential clinical value carried within each distinct EV subset highlights the advantages of selective isolation. Conclusions: This EV isolation protocol facilitated the extraction of clinically useful information from plasma. Compatible with common downstream analytics, it is a readily implementable research tool, tailored to provide a truly translational solution in routine clinical workflows, fostering the inclusion of EVs in novel liquid biopsy settings.

Background: The analysis of liquid biopsies brings new opportunities in the precision oncology field. Under this context, extracellular vesicle circular RNAs (EV-circRNAs) have gained interest as biomarkers for lung cancer (LC) detection. However, standardized and robust protocols need to be developed to boost their potential in the clinical setting. Although nCounter has been used for the analysis of other liquid biopsy substrates and biomarkers, it has never been employed for EV-circRNA analysis of LC patients. Methods: EVs were isolated from early-stage LC patients (n = 36) and controls (n = 30). Different volumes of plasma, together with different number of pre-amplification cycles, were tested to reach the best nCounter outcome. Differential expression analysis of circRNAs was performed, along with the testing of different machine learning (ML) methods for the development of a prognostic signature for LC. Results: A combination of 500 μL of plasma input with 10 cycles of pre-amplification was selected for the rest of the study. Eight circRNAs were found upregulated in LC. Further ML analysis selected a 10-circRNA signature able to discriminate LC from controls with AUC ROC of 0.86. Conclusions: This study validates the use of the nCounter platform for multiplexed EV-circRNA expression studies in LC patient samples, allowing the development of prognostic signatures.

Blood plasma is available with minimal invasive sampling, it has significant diagnostic utility, and it is a valuable source of extracellular vesicles (EVs). Nevertheless, rich protein content, the presence of lipoproteins (LPs) that share similar biophysical properties, and relatively low abundance of EVs, especially those of rare subpopulations, make any downstream application a very challenging task. The growing evidence of the intricate surface interactome of EVs, and the association of EVs with LPs, impose further challenges during EV purification, detection, and biomarker analyses. In this study, we tackled the fundamental issues of plasma EV yield and LP co-isolation and their implications in the subsequent marker analyses. Moderate acidification of plasma was combined with size exclusion chromatography (SEC) and/or differential centrifugation (DC) to disrupt LPs and improve recovery of EVs and their subsequent detection by immunoassays and single-particle analysis methods. Our results demonstrate a surprisingly efficient enrichment of EVs (up to 3.3-fold higher than at pH 7) and partial depletion of LPs (up to 61.2%). Acidification of blood plasma samples enabled a quick single-step isoelectric precipitation of up to 20.4% of EVs directly from plasma, upon short low-speed centrifugation. Thus, acidification holds potential as a simple and inexpensive methodological step, which improves the efficacy of plasma EV enrichment and may have implications in future biomarker discoveries.