Extracellular Vesicles Surface Proteins Research Articles

Identification and validation of the surface proteins FIBG, PDGF-β, and TGF-β on serum extracellular vesicles for non-invasive detection of colorectal cancer: experimental study.

The absence of non-invasive biomarkers for the early diagnosis of colorectal cancer (CRC) has contributed to poor prognosis. Extracellular vesicles (EVs) have emerged as promising candidates for cancer monitoring using liquid biopsy. However, the complexity of EVs isolation procedures and absence of clear targets for detecting serum-derived EVs have hindered the clinical application of EVs in early CRC diagnosis. In the discovery phase, we conducted a comprehensive 4D-DIA proteomic analysis of serum-derived EVs samples from 37 individuals, performing an initial screening of EVs surface proteins. In the technical validation phase, we developed an extraction-free CRC-EVArray microarray to assess the expression of these potential EVs surface proteins in a multicenter study comprising 404 individuals. In the application phase, we evaluated the diagnostic efficacy of the CRC-EVArray model based on machine-learning algorithms. Through 4D-DIA proteomic analysis, we identified 7 potential EVs surface proteins showing significantly differential expression in CRC patients compared to healthy controls. Utilizing our developed high-throughput CRC-EVArray microarray, we further confirmed the differential expression of 3 EVs surface proteins, FIBG, PDGF-β and TGF-β, in a large sample population. Moreover, we established an optimal CRC-EVArray model using the NNET algorithm, demonstrating superior diagnostic efficacy with an AUC of 0.882 in the train set and 0.937 in the test set. Additionally, we predicted the functions and potential origins of these EVs-derived proteins through a series of multi-omics approaches. Our systematic exploration of surface protein expression profiles on serum-derived EVs has identified FIBG, PDGF-β, and TGF-β as novel diagnostic biomarkers for CRC. And the development of CRC-EVArray diagnostic model based on these findings provided an effective tool for the large-scale CRC screening, thus facilitating its translation into clinical practice.

Surface Proteome of Extracellular Vesicles and Correlation Analysis Reveal Breast Cancer Biomarkers

Breast cancer (BC) is the second most frequently diagnosed cancer and accounts for approximately 25% of new cancer cases in Canadian women. Using biomarkers as a less-invasive BC diagnostic method is currently under investigation but is not ready for practical application in clinical settings. During the last decade, extracellular vesicles (EVs) have emerged as a promising source of biomarkers because they contain cancer-derived proteins, RNAs, and metabolites. In this study, EV proteins from small EVs (sEVs) and medium EVs (mEVs) were isolated from BC MDA-MB-231 and MCF7 and non-cancerous breast epithelial MCF10A cell lines and then analyzed by two approaches: global proteomic analysis and enrichment of EV surface proteins by Sulfo-NHS-SS-Biotin labeling. From the first approach, proteomic profiling identified 2459 proteins, which were subjected to comparative analysis and correlation network analysis. Twelve potential biomarker proteins were identified based on cell line-specific expression and filtered by their predicted co-localization with known EV marker proteins, CD63, CD9, and CD81. This approach resulted in the identification of 11 proteins, four of which were further investigated by Western blot analysis. The presence of transmembrane serine protease matriptase (ST14), claudin-3 (CLDN3), and integrin alpha-7 (ITGA7) in each cell line was validated by Western blot, revealing that ST14 and CLDN3 may be further explored as potential EV biomarkers for BC. The surface labeling approach enriched proteins that were not identified using the first approach. Ten potential BC biomarkers (Glutathione S-transferase P1 (GSTP1), Elongation factor 2 (EEF2), DEAD/H box RNA helicase (DDX10), progesterone receptor (PGR), Ras-related C3 botulinum toxin substrate 2 (RAC2), Disintegrin and metalloproteinase domain-containing protein 10 (ADAM10), Aconitase 2 (ACO2), UTP20 small subunit processome component (UTP20), NEDD4 binding protein 2 (N4BP2), Programmed cell death 6 (PDCD6)) were selected from surface proteins commonly identified from MDA-MB-231 and MCF7, but not identified in MCF10A EVs. In total, 846 surface proteins were identified from the second approach, of which 11 were already known as BC markers. This study supports the proposition that Evs are a rich source of known and novel biomarkers that may be used for non-invasive detection of BC. Furthermore, the presented datasets could be further explored for the identification of potential biomarkers in BC.

Single extracellular vesicle surface protein-based blood assay identifies potential biomarkers for detection and screening of five cancers.

Extracellular vesicles (EVs) and EV proteins are promising biomarkers for cancer liquid biopsy. Herein, we designed a case-control study involving 100 controls and 100 patients with esophageal, stomach, colorectal, liver, or lung cancer to identify common and type-specific biomarkers of plasma-derived EV surface proteins for the five cancers. EV surface proteins were profiled using a sequencing-based proximity barcoding assay. In this study, five differentially expressed proteins (DEPs) and eight differentially expressed protein combinations (DEPCs) showed promising performance (area under curve, AUC > 0.900) in pan-cancer identification [e.g., TENM2 (AUC = 0.982), CD36 (AUC = 0.974), and CD36-ITGA1 (AUC = 0.971)]. Our classification model could properly discriminate between cancer patients and controls using DEPs (AUC = 0.981) or DEPCs (AUC = 0.965). When distinguishing one cancer from the other four, the accuracy of the classification model using DEPCs (85-92%) was higher than that using DEPs (78-84%). We validated the performance in an additional 14 cancer patients and 14 controls, and achieved an AUC value of 0.786 for DEPs and 0.622 for DEPCs, highlighting the necessity to recruit a larger cohort for further validation. When clustering EVs into subpopulations, we detected cluster-specific proteins highly expressed in immune-related tissues. In the context of colorectal cancer, we identified heterogeneous EV clusters enriched in cancer patients, correlating with tumor initiation and progression. These findings provide epidemiological and molecular evidence for the clinical application of EV proteins in cancer prediction, while also illuminating their functional roles in cancer physiopathology.

EVs‐on‐a‐Bubble: Self‐Aggregated Click Bubbles Streamline Isolation and Amplified Profiling of Circulating Extracellular Vesicles

AbstractTumor‐derived circulating extracellular vesicles (EVs) provide a non‐invasive solution for cancer diagnostics, but hampered by challenges in EVs isolation and profiling. Herein, this work shows that bioorthogonal microbubbles (click bubbles) combine a panel of fluorescent aptamers for streamlined isolation and profiling of oncologic EVs in a single assay. This click bubble‐driven aptasensor (cBAS) features self‐aggregation, self‐separation and self‐enhancing in fluorescence. The facile protein phase transition renders bubble surface polyvalent with rich clickable motifs, enabling fast enrichment of EVs. Moreover, the buoyancy allows click bubbles to self‐float to the droplet apex for self‐aggregated fluorescence enhancement via a bubble lensing effect, thus achieving a sensitive profiling of EVs without requiring additional signal amplification or ultrasensitive detectors. By using cBAS to profile EVs surface proteins from a cohort (n = 45) across three cancer types, a machine learning algorithm enables cancer diagnosis and classification with an overall accuracy of 91%. This EVs‐on‐a‐bubble assay is fast, sensitive, self‐powered, and provides a promising tool to facilitate EVs‐based cancer diagnosis in clinical settings.

Concentric gradient nanoplasmonic sensors for detecting tumor-derived extracellular vesicles

Quantification of tumor-derived extracellular vesicles (EVs) holds great promise for early cancer diagnosis and prognosis. Developing a rapid and straightforward EV detection platform is essential for timely and specific diagnostics. In this study, we present a novel concentric gradient nanoplasmonic (CGN) sensor to achieve sensitive and label-free EV quantification. The CGN sensor features wafer-scale gradient plasmonic nanostructures, converting resonance wavelength shift into a change in centimeter-scale transmission pattern. Through functionalization with smaller aptamers, a more sensitive area is reserved for EV surface proteins, facilitating the dynamic binding of EVs, which is recorded by a CCD camera to establish a correlation between pattern movement and EV attachment. We quantitatively characterized EVs derived from A549 and MCF-7 cancer cell lines by integrating the CGN sensor into a microfluidic device. With a high sensing performance of 9.23 × 10−5 RIU, we achieved real-time measurements of EV binding as low as 143 femtomolar. Furthermore, the CGN sensor exhibited excellent sensitivity in detecting EVs from cancer patient plasma. We also designed a compact imaging-based sensing device employing an LED and a CCD camera. This device combines the simplicity of large-area and real-time imaging with the robustness of spectroscopic approaches, making it highly promising for point-of-care diagnostics.

In Situ Simultaneous Detection of Surface Protein and microRNA in Clustered Extracellular Vesicles from Cancer Cell Lines Using Flow Cytometry.

Extracellular vesicles (EVs) are becoming increasingly important in liquid biopsy for cancer because they contain multiple biomarkers, including proteins and RNAs, and circulate throughout the body. Cancer cell-derived EVs are highly heterogeneous, and multiplexed biomarker detection techniques are required to improve the accuracy of diagnosis. In addition, in situ EV biomarker detection increases the efficiency of the detection process because EVs are difficult to handle. In this study, in situ simultaneous detection of EV surface proteins, programmed cell death-ligand 1 (PD-L1), and internal miRNA-21 (miR-21) analyzed by conventional flow cytometry was developed for a breast cancer liquid biopsy. However, the majority of EVs were not recognized by flow cytometry for biomarker detection because the size of EVs was below the detectable size range of the flow cytometer. To solve this problem, the formation of EV clusters was induced by 1,2-distearoyl-sn-glycero-3-phosphoethanolamine (DSPE)-polyethylene glycol-DSPE during biomarker detection. Consequently, both PD-L1 and miR-21 detection signals from cancer cell-derived EVs were drastically increased, making them distinguishable from normal cell-derived EVs. The in situ simultaneous cancer biomarker detection from EV clusters analyzed by flow cytometry contributes to an increase in the sensitivity and accuracy of the EV-based liquid biopsy for cancer.

Surface protein profiling of milk and serum extracellular vesicles unveils body fluid-specific signatures

Cell-derived extracellular vesicles (EVs) are currently in the limelight as potential disease biomarkers. The promise of EV-based liquid biopsy resides in the identification of specific disease-associated EV signatures. Knowing the reference EV profile of a body fluid can facilitate the identification of such disease-associated EV-biomarkers. With this aim, we purified EVs from paired human milk and serum samples and used the MACSPlex bead-based flow-cytometry assay to capture EVs on bead-bound antibodies specific for a certain surface protein, followed by EV detection by the tetraspanins CD9, CD63, and CD81. Using this approach we identified body fluid-specific EV signatures, e.g. breast epithelial cell signatures in milk EVs and platelet signatures in serum EVs, as well as body fluid-specific markers associated to immune cells and stem cells. Interestingly, comparison of pan-tetraspanin detection (simultaneous CD9, CD63 and CD81 detection) and single tetraspanin detection (detection by CD9, CD63 or CD81) also unveiled body fluid-specific tetraspanin distributions on EVs. Moreover, certain EV surface proteins were associated with a specific tetraspanin distribution, which could be indicative of the biogenesis route of this EV subset. Altogether, the identified body fluid-specific EV profiles can contribute to study EV profile deviations in these fluids during disease processes.

Investigating the tumor-immune microenvironment through extracellular vesicles from frozen patient biopsies and 3D cultures.

Melanomas are highly immunogenic tumors that have been shown to activate the immune response. Nonetheless, a significant portion of melanoma cases are either unresponsive to immunotherapy or relapsed due to acquired resistance. During melanomagenesis, melanoma and immune cells undergo immunomodulatory mechanisms that aid in immune resistance and evasion. The crosstalk within melanoma microenvironment is facilitated through the secretion of soluble factors, growth factors, cytokines, and chemokines. In addition, the release and uptake of secretory vesicles known as extracellular vesicles (EVs) play a key role in shaping the tumor microenvironment (TME). Melanoma-derived EVs have been implicated in immune suppression and escape, promoting tumor progression. In the context of cancer patients, EVs are usually isolated from biofluids such as serum, urine, and saliva. Nonetheless, this approach neglects the fact that biofluid-derived EVs reflect not only the tumor, but also include contributions from different organs and cell types. For that, isolating EVs from tissue samples allows for studying different cell populations resident at the tumor site, such as tumor-infiltrating lymphocytes and their secreted EVs, which play a central anti-tumor role. Herein, we outline the first instance of a method for EV isolation from frozen tissue samples at high purity and sensitivity that can be easily reproduced without the need for complicated isolation methods. Our method of processing the tissue not only circumvents the need for hard-to-acquire freshly isolated tissue samples, but also preserves EV surface proteins which allows for multiplex surface markers profiling. Tissue-derived EVs provide insight into the physiological role of EVs enrichment at tumor sites, which can be overlooked when studying circulating EVs coming from different sources. Tissue-derived EVs could be further characterized in terms of their genomics and proteomics to identify possible mechanisms for regulating the TME. Additionally, identified markers could be correlated to overall patient survival and disease progression for prognostic purposes.

Abstract 5308: Analysis of extracellular vesicle surface markers as small cell lung cancer biomarkers

Abstract Small Cell Lung Cancer (SCLC) is an aggressive tumor type, usually metastatic at diagnosis, with a median survival of less than a year. SCLC tumors are heterogeneous and are composed of neuroendocrine (A, A2, N) and non-neuroendocrine (Y) subtypes, with the cooperation by heterogeneous cells being key to drive tumor survival. Unfortunately, the current SCLC treatment approach does not take tumor heterogeneity into consideration. Importantly, there are no consensus markers that can identify SCLC subtypes or early tumors. Extracellular vesicles (EVs), small vesicles known to promote cell to cell communication, have been investigated as non-invasive biomarkers for cancer diagnostics, staging, and treatment monitoring. EVs are attractive candidates for biomarker research due to the selective packaging of RNA, DNA, and proteins that are then secreted in the blood. Therefore, our aim was to identify new biomarkers based on EV surface proteins with potential for early detection and tumor characterization. We used differential ultracentrifugation to isolate EVs from four SCLC subtypes A, A2, N, and Y, which were submitted to label-free mass spectrometry (EV-proteomics). We identified a total of 3011 proteins, with the two most distinct subtypes being A2 and N, with 786 differentially expressed EV-proteins. Meanwhile, the 2 most similar subtypes were N and A, with only 75 differentially expressed EV-proteins. Gene set enrichment analysis of EVs derived from the A2 subtype showed an association with pathways in cancer, chemokine signaling, and neuronal systems. In addition, PANTHER analysis identified enrichment in nicotine pharmacodynamic pathways on these EVs, which corroborate the association of A2 cell lines with drug resistance. EVs derived from the N and A subtypes were enriched in spliceosome, RNA processing, and metabolism, while EVs from Y cell lines were enriched in extracellular matrix organization and metabolic pathways, similar to pathways from cell line RNAseq data. 13 proteins were differentially expressed in all group comparisons, including proteins involved in PI3K and nicotinic acetylcholine receptor signaling pathways. Further comparison of EV-proteomics with top genes from CIBERSORT analysis using cell line RNAseq data showed an overlap of 9 surface proteins, with 3 possible SCLC pan markers. In conclusion, EV-proteins isolated from SCLC cell lines presented a unique signature for each subtype, especially EVs derived from A2 subtype, which has a signature associated with drug resistance. We identified surface proteins on SCLC EVs with potential as SCLC pan and tumor characterization, which will be validated on EVs derived from cell lines and patient plasma by Western blotting and single-EV microflow cytometry. Citation Format: Patricia M. Ozawa, Sarah M. Groves, Vito Quaranta, Alissa M. Weaver. Analysis of extracellular vesicle surface markers as small cell lung cancer biomarkers. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5308.

Doxorubicin Loading into Milk and Mesenchymal Stem Cells’ Extracellular Vesicles as Drug Delivery Vehicles

Extracellular vesicles (EVs) have great potential as drug delivery vehicles. While mesenchymal/stromal stem cell (MSC) conditioned medium (CM) and milk are potentially safe and scalable sources of EVs for this purpose, the suitability of MSC EVs and milk EVs as drug delivery vehicles has never been compared and so was the objective of this study. Here EVs were separated from MSCs' CM and from milk and were characterised by nanoparticle tracking analysis, transmission electron microscopy, total protein quantification, and immunoblotting. An anti-cancer chemotherapeutic drug, doxorubicin (Dox), was then loaded into the EVs by one of three methods: by passive loading or by active loading by either electroporation or sonication. Dox-loaded EVs were analysed by fluorescence spectrophotometer, high-performance liquid chromatography (HPLC), and imaging flow cytometer (IFCM). Our study showed that EVs were successfully separated from the milk and MSC CM, with significantly (p < 0.001) higher yields of milk EVs/mL starting material compared to MSC EVs/mL of starting material. Using a fixed amount of EVs for each comparison, electroporation achieved significantly more Dox loading when compared to passive loading (p < 0.01). Indeed, of 250 µg of Dox made available for loading, electroporation resulted in 90.1 ± 12 µg of Dox loading into MSC EVs and 68.0 ± 10 µg of Dox loading into milk EVs, as analysed by HPLC. Interestingly, compared to the passive loading and electroporation approach, after sonication significantly fewer CD9+ EVs/mL (p < 0.001) and CD63+ EVs/mL (p < 0.001) existed, as determined by IFCM. This observation indicates that sonication, in particular, may have detrimental effects on EVs. In conclusion, EVs can be successfully separated from both MSC CM and milk, with milk being a particularly rich source. Of the three methods tested, electroporation appears to be superior for achieving maximum drug loading while not causing damage to EV surface proteins.

Photometric method for dual targeting of surface and surface-associated proteins on extracellular vesicles in the multiparametric test.

Extracellular vesicles (EVs) have become a topic of interest within the field of diagnostic biomarkers; however, recent developments in the study of EVs have increased the need for simpler but still comprehensive methods for characterization. Here, we describe how to simultaneously measure several surface or surface-associated proteins on EVs using a multiparametric microarray-based analysis termed Extracellular Vesicle Array (EV Array), which is developed to catch and phenotypically characterize small EVs. Previously, this analysis has been limited to measuring only one fluorescent signal per analysis. The analysis relies on antibodies printed onto a solid surface, for catching the EVs carrying the specific surface or surface-associated proteins, and on the subsequent fluorescent detection. For the optimization of detection, two antibodies with attached Cy3 or Cy5 were added to various combinations of the EV surface or surface-associated proteins: CD9, CD63, CD81, flotillin-1, and HSP90. In this study, the EV surface or surface-associated proteins were analyzed in human plasma from six healthy subjects. Changes observed in signal intensities from Cy3 and Cy5 related specifically to these combinations and allowed for a comparison of the two different fluorescent signals. When comparing the results, it was observed that it is possible to measure the EV surface or surface-associated proteins at both 532nm (Cy3) and 635nm (Cy5) simultaneously without a significant change in signals from the detection molecules. This allows us to measure multiple EV marker proteins in a single analysis, thereby more quickly finding complex biomarker patterns in a sample.

Men and women display distinct extracellular vesicle biomarker signatures in response to military operational stress.

Extracellular vesicles (EVs) are mediators of physiological changes that occur during physical exertion. This study examined the effects of physical exertion with and without sleep and caloric restriction on EV size, concentration, and surface proteins in men and women. Twenty participants (10 men) completed a 5-day simulated military operational stress protocol with daily physical exertion. Blood was drawn before and immediately after exertion at baseline (D1) and following 48-h of sleep and caloric restriction (D3). EV size and concentration were assessed using nanoparticle tracking analysis. EVs were identified with markers associated with exosomes (CD63), microvesicles (VAMP3), apoptotic bodies (THSD1), and skeletal muscle-derived EVs (SGCA) and quantified using imaging flow cytometry. Interactive and main effects of sex, day, and time on EVs were assessed using three-way ANOVAs. EV concentration declined pre to postexertion in women on D1 and D3 but was stable in men. EV size increased from pre to postexertion and from D1 to D3 in men and women. Physical exertion following sleep and caloric restriction increased CD63+ EV concentration, proportion of total EVs, and CD63 surface protein expression regardless of sex. The proportion of SGCA+ EVs increased in men and women following exertion and from D1 to D3 but was higher in women than in men. No differences were observed in VAMP3+ and THSD1+ EVs. This study identified sexually dimorphic EV profiles in response to various stressors. Further investigations are necessary to determine if dimorphic EV responses affect health and performance outcomes during stress.NEW & NOTEWORTHY Sex is understudied in EV research, and most studies limit EV analysis to single stress conditions such as exercise. Multistress conditions consisting of physical exertion and sleep and caloric restriction are common in real-world settings. We demonstrate that physical exertion results in sex-specific EV signatures and that EV profiles vary according to single versus multistress conditions. Our data highlight important biological and ecological characteristics that should be considered in EV research.

Characterization of surface markers on extracellular vesicles isolated from lymphatic exudate from patients with breast cancer

BackgroundBreast cancer is the most common cancer, and the leading cause of cancer-related deaths, among females world-wide. Recent research suggests that extracellular vesicles (EVs) play a major role in the development of breast cancer metastasis. Axillary lymph node dissection (ALND) is a procedure in patients with known lymph node metastases, and after surgery large amounts of serous fluid are produced from the axilla. The overall aim was to isolate and characterize EVs from axillary serous fluid, and more specifically to determine if potential breast cancer biomarkers could be identified.MethodsLymphatic drain fluid was collected from 7 patients with breast cancer the day after ALND. EVs were isolated using size exclusion chromatography, quantified and detected by nanoparticle tracking analysis, electron microscopy, nano flow cytometry and western blot. The expression of 37 EV surface proteins was evaluated by flow cytometry using the MACSPlex Exosome kit.ResultsLymphatic drainage exudate retrieved after surgery from all 7 patients contained EVs. The isolated EVs were positive for the typical EV markers CD9, CD63, CD81 and Flotillin-1 while albumin was absent, indicating low contamination from blood proteins. In total, 24 different EV surface proteins were detected. Eleven of those proteins were detected in all patients, including the common EV markers CD9, CD63 and CD81, cancer-related markers CD24, CD29, CD44 and CD146, platelet markers CD41b, CD42a and CD62p as well as HLA-DR/DP/DQ. Furthermore, CD29 and CD146 were enriched in Her2+ patients compared to patients with Her2- tumors.ConclusionsLymphatic drainage exudate retrieved from breast cancer patients after surgery contains EVs that can be isolated using SEC isolation. The EVs have several cancer-related markers including CD24, CD29, CD44 and CD146, proteins of potential interest as biomarkers as well as to increase the understanding of the mechanisms of cancer biology.

Nanoparticle-Enabled Multiplexed Electrochemical Immunoassay for Detection of Surface Proteins on Extracellular Vesicles.

Extracellular vesicles (EVs) are lipid bilayer particles secreted from various cells. EVs carry molecular information of parent cells and hold considerable promise for early disease diagnostics. This paper describes a general strategy for multiplexed immunosensing of EV surface proteins, focusing on surface markers CD63, CD81, nephrin, and podocin to prove the concept. This sensing strategy entailed functionalizing gold nanoparticles (AuNPs) with two types of antibodies and then tagging with metal ions, either Pb2+ or Cu2+. The metal ions served as redox reporters, generating unique redox peaks at -0.23 and 0.28 V (vs Ag/AgCl) during electrochemical oxidation of Pb2+ and Cu2+, respectively. Capture of EVs on the working electrode, followed by labeling with immunoprobes and square wave voltammetry, produced redox currents proportional to concentrations of EVs and levels of expression of EV surface markers. Importantly, metal-ion tagging of immunoprobes enabled detection of two EV surface markers simultaneously from the same electrode. We demonstrated dual detection of either CD63/CD81 or podocin/nephrin surface markers from urinary EVs. The NP-enabled immunoassay had a sensitivity of 2.46 × 105 particles/mL (or 40.3 pg/mL) for CD63- and 5.80 × 105 particles/mL (or 47.7 pg/mL) for CD81-expressing EVs and a linear range of four orders of magnitude. The limit of detection for podocin and nephrin was 3.1 and 3.8 pg/mL, respectively. In the future, the capacity for multiplexing may be increased by extending the repertoire of metal ions used for redox tagging of AuNPs.

Extracellular vesicle therapeutics: the issue of one size fits all

Extracellular vesicles (EV) are mediators of intercellular communication locally in tissue microenvironments and enable distal across organ communication between cells of the same origin and those from different sources. EV surface proteins and lipids enable interaction with particular cells, whereas their internal payload of RNA, transcription factors, DNA, enzymes and metabolites functionally alters recipient cells. EV-interactions and uptake induce changes in cellular proliferation, differentiation, cell movement, as well as transcriptional and epigenetic regulation. These unique properties of EV poise them as attractive therapeutics in a broad range of pathologies, but questions remain in translating EV discoveries to effective therapies. Here, I briefly discuss the need for more stringent considerations for EV-therapeutic effects with a focus on EV biodistribution profiles in appropriate disease models and routes of EV administration with a particular focus on the vasculature.

Multiplex protein profiling method for extracellular vesicle protein detection

Extracellular vesicles (EVs) are small nanometer-sized membrane sacs secreted into biological fluids by all cells. EVs encapsulate proteins, RNAs and metabolites from its origin cell and play important roles in intercellular communication events. Over the past decade, EVs have become a new emerging source for cancer diagnostics. One of the challenges in the study of EVs and there utility as diagnostic biomarkers is the amount of EVs needed for traditional protein analysis methods. Here, we present a new immuno-PCR method that takes advantage of commercially available TotalSeq antibodies containing DNA conjugated oligos to identify immobilized protein analysts using real-time qPCR. Using this method, we demonstrate that multiple EV surface proteins can be profiled simultaneously with high sensitivity and specificity. This approach was also successfully applied to similar protocol using cell and serum samples. We further described the development of a micro-size exclusion chromatography method, where we were able to detect EV surface proteins with as little as 10 μL of human serum when combined with immuno-PCR. Overall, these results show that the immuno-PCR method results in rapid detection of multiple EV markers from small sample volumes in a single tube.

Single Step In Situ Detection of Surface Protein and MicroRNA in Clustered Extracellular Vesicles Using Flow Cytometry.

Because cancers are heterogeneous, it is evident that multiplexed detection is required to achieve disease diagnosis with high accuracy and specificity. Extracellular vesicles (EVs) have been a subject of great interest as sources of novel biomarkers for cancer liquid biopsy. However, EVs are nano-sized particles that are difficult to handle; thus, it is necessary to develop a method that enables efficient and straightforward EV biomarker detection. In the present study, we developed a method for single step in situ detection of EV surface proteins and inner miRNAs simultaneously using a flow cytometer. CD63 antibody and molecular beacon-21 were investigated for multiplexed biomarker detection in normal and cancer EVs. A phospholipid-polymer-phospholipid conjugate was introduced to induce clustering of the EVs analyzed using nanoparticle tracking analysis, which enhanced the detection signals. As a result, the method could detect and distinguish cancer cell-derived EVs using a flow cytometer. Thus, single step in situ detection of multiple EV biomarkers using a flow cytometer can be applied as a simple, labor- and time-saving, non-invasive liquid biopsy for the diagnosis of various diseases, including cancer.

Non-pigmented ciliary epithelium derived extracellular vesicles uptake mechanism by the trabecular meshwork.

Consistent with increasing findings, extracellular vesicles (EVs), consider as a major constituents of the aqueous humor, have a role as signaling mediators in glaucoma. Following secretion, EVs hold immense promise for utilization as bio-therapeutics and drug delivery vehicles due to their nature as biological nanoparticles that facilitate intercellular molecular transport. Yet, the specific pathway utilizing for transferring signals by EVs in the ocular drainage system is not fully understood. Hence, the objective of this study was to examine internalization mechanisms by which Non-Pigmented Ciliary Epithelium (NPCE)-derived EVs deliver their signals to the Trabecular Meshwork (TM) cells. EVs were isolated and size and concentration were determined. Internalization study of treated EVs with Proteinase-K to achieve removal of surface membrane proteins on EVs was conducted. Energy dependent uptake mechanism was examined under various temperatures. Using uptake inhibitors endocytosis, phagocytosis, and Wnt-TGFβ2 signaling were investigated. TM cells exposed to NPCE EVs demonstrate a significant decrease in the levels of two proteins in two Wnt-TGFb2 signaling proteins levels: p-GSK3β and β-catenin. A significant decrease in the uptake by TM cells of Proteinase-K-treated EVs was found, followed by attenuation of the Wnt-TGFβ2 proteins expression. Energy dependent uptake revealed a significant decrease in EVs internalization. The exposure of TM cells to endocytosis uptake inhibitors abolished the decrease of the Wnt-TGFβ2 proteins levels. Exposure to phagocytosis uptake inhibitor resulted in a partial inhibition of NPCE EVs effect in TM cells. The attenuation of proteins expression levels following uptake inhibitors treatment or EVs membrane proteins removal indicates that Wnt-TGFβ2 signaling in TM cells is mediated through NPCE EVs surface proteins in an active manner that involves endocytosis-dependent routes.

Extracellular Vesicles in Human Preterm Colostrum Inhibit Infection by Human Cytomegalovirus In Vitro.

Breast milk is a complex biofluid that nourishes infants, supports their growth and protects them from diseases. However, at the same time, breastfeeding is a transmission route for human cytomegalovirus (HCMV), with preterm infants being at a great risk of congenital disease. The discrepancy between high HCMV transmission rates and the few reported cases of infants with severe clinical illness is likely due to the protective effect of breast milk. The aim of this study was to investigate the anti-HCMV activity of human preterm colostrum and clarify the role of colostrum-derived extracellular vesicles (EVs). Preterm colostrum samples were collected and the EVs were purified and characterized. The in vitro anti-HCMV activity of both colostrum and EVs was tested against HCMV, and the viral replication step inhibited by colostrum-purified EVs was examined. We investigated the putative role EV surface proteins play in impairing HCMV infection using shaving experiments and proteomic analysis. The obtained results confirmed the antiviral action of colostrum against HCMV and demonstrated a remarkable antiviral activity of colostrum-derived EVs. Furthermore, we demonstrated that EVs impair the attachment of HCMV to cells, with EV surface proteins playing a role in mediating this action. These findings contribute to clarifying the mechanisms that underlie the protective role of human colostrum against HCMV infection.

Isolation and mutational assessment of pancreatic cancer extracellular vesicles using a microfluidic platform.

Cancer cells release extracellular vesicles known as extracellular vesicles (EVs), containing tumor-derived DNA, RNA and proteins within their cargo, into the circulation. Circulating tumor-derived extracellular vesicles (TEV) can be used in the context of serial "liquid biopsies" for early detection of cancer, for monitoring disease burden in patients, and for assessing recurrence in the post-resection setting. Nonetheless, isolating sufficient TEV by ultracentrifugation-based approaches, in order to enable molecular assessment of EVs cargo, can be an arduous, time-consuming process and is inconsistent in the context of yield and purity among institutions. Herein, we describe a microfluidic platform, which we have named MITEV (Microfluidic Isolation of Tumor-derived Extracellular Vesicles) for the rapid isolation of TEV from the plasma of pancreatic cancer patients. The device, which has ~100,000 pillars placed in a zigzag pattern and is coated with antibodies against generic EV surface proteins (anti-CD63, -CD9, and -CD81 antibodies) or the TEV specific anti-Epithelial Cell Adhesion Molecule (EpCAM) antibody, is capable of high-throughput EVs isolation and yields sufficient DNA (total of ~2-14ng from 2-ml plasma) for downstream genomic analysis. Using two independent quantitative platforms, droplet digital polymerase chain reaction (ddPCR) and molecular barcoding using nanoString nCounter® technology, we can reliably identify KRAS mutations within isolated TEV of treatment-naïve metastatic pancreatic cancer patients. Our study suggests that the MITEV device can be used for point-of-care applications, such as in the context of monitoring residual or recurrent tumor presence in pancreatic cancer patients undergoing therapy.