Detection Of Extracellular Vesicles Research Articles

Tetraspanin immunoassay for the detection of extracellular vesicles and renal cell carcinoma

AbstractHalf of patients with renal cell carcinoma (RCC) develop metastases. New and noninvasive biomarkers are needed for the diagnosis of RCC. The study aims to develop an EV‐based assay for the detection of RCC using a highly sensitive nanoparticle‐aided time‐resolved fluorescence immunoassay (NP‐TRFIA). To confirm the presence of tetraspanins on EVs, size exclusion chromatography is used to separate EV‐ and PE‐fractions from RCC4, 786‐O, and HEK293 cell lines. EV‐ and PE‐fractions are quantified using NP‐TRFIA assays established for CD9, CD63, CD81, and CD151. Tetraspanins are measured from RCC CCM and serum samples of RCC (n = 14), benign (n = 17), and healthy (n = 9) individuals. Among the tetraspanins, CD63 exhibits 3‐5‐fold higher expression on RCC4 and 786‐O CCM compared to HEK293. A sandwich CD63‐CD63 assay demonstrates significant discrimination of RCC patients from benign (p = 0.0003), and healthy (p = 0.005) individuals, respectively. Similarly, the CD81‐CD81 assay also enables significant separation of RCC patients compared to benign (p = 0.014), and healthy (p = 0.003) controls, respectively. This suggests that RCC cell lines and serum of RCC patients show higher amounts of CD63‐ and CD81‐EVs compared to controls. Detection of these EVs using NP‐TRFIA approach may play a vital role in the detection of RCC.

Small extracellular vesicles detection using dielectrophoresis-based microfluidic chip for diagnosis of breast cancer

Small extracellular vesicles (sEVs) reflect the genotype and phenotype of original cells and are biomarkers for early diagnosis and treatment monitoring of tumors. Yet, their small size and low density make them difficult to isolate and detect in body fluid samples. This study proposes a novel acDEP-Exo chip filled with transparent micro-beads, which formed a non-uniform electrical field, and finally achieved rapid, sensitive, and tunable sEVs capture and detection. The method requires only 20–50 μL of sample, achieved a limit of detection (LOD) of 161 particles/μL, and can detect biomarkers within 13 min. We applied the chip to analyze the two markers of sEV's EpCAM and MUC1 in clinical plasma samples from breast cancer (BC) patients and healthy volunteers and found that the combined evaluation of sEV's biomarkers has extremely high sensitivity, specificity and accuracy. The present study introduces an alternative approach to sEVs isolation and detection, has a great potential in real-time sEVs-based liquid biopsy.

Electrochemical detection of extracellular vesicles for early diagnosis: a focus on disease biomarker analysis

This review article presents a detailed examination of the integral role that electrochemical detection of extracellular vesicles (EVs) plays, particularly focusing on the potential application for early disease diagnostics through EVs biomarker analysis. Through an exploration of the benefits and challenges presented by electrochemical detection vetted for protein, lipid, and nucleic acid biomarker analysis, we underscore the significance of these techniques. Evidence from recent studies renders this detection modality imperative in identifying diverse biomarkers from EVs, leading to early diagnosis of diseases such as cancer and neurodegenerative disorders. Recent advancements that have led to enhanced sensitivity, specificity and point-of-care testing (POCT) potential are elucidated, along with equipment deployed for electrochemical detection. The review concludes with a contemplation of future perspectives, recognizing the potential shifts in disease diagnostics and prognosis, necessary advances for broad adoption, and potential areas of ongoing research. The objective is to propel further investigation into this rapidly burgeoning field, thereby facilitating a potential paradigm shift in disease detection, monitoring, and treatment toward human health management.

Applications of Data Characteristic AI-Assisted Raman Spectroscopy in Pathological Classification.

Raman spectroscopy has been widely used for label-free biomolecular analysis of cells and tissues for pathological diagnosis in vitro and in vivo. AI technology facilitates disease diagnosis based on Raman spectroscopy, including machine learning (PCA and SVM), manifold learning (UMAP), and deep learning (ResNet and AlexNet). However, it is not clear how to optimize the appropriate AI classification model for different types of Raman spectral data. Here, we selected five representative Raman spectral data sets, including endometrial carcinoma, hepatoma extracellular vesicles, bacteria, melanoma cell, diabetic skin, with different characteristics regarding sample size, spectral data size, Raman shift range, tissue sites, Kullback-Leibler (KL) divergence, and significant Raman shifts (i.e., wavenumbers with significant differences between groups), to explore the performance of different AI models (e.g., PCA-SVM, SVM, UMAP-SVM, ResNet or AlexNet). For data set of large spectral data size, Resnet performed better than PCA-SVM and UMAP. By building data characteristic-assisted AI classification model, we optimized the network parameters (e.g., principal components, activation function, and loss function) of AI model based on data size and KL divergence etc. The accuracy improved from 85.1 to 94.6% for endometrial carcinoma grading, from 77.1 to 90.7% for hepatoma extracellular vesicles detection, from 89.3 to 99.7% for melanoma cell detection, from 88.1 to 97.9% for bacterial identification, from 53.7 to 85.5% for diabetic skin screening, and mean time expense of 5 s.

DNA walker induced “signal on” fluorescence aptasensor strategy for rapid and sensitive detection of extracellular vesicles in gastric cancer

DNA walker induced “signal on” fluorescence aptasensor strategy for rapid and sensitive detection of extracellular vesicles in gastric cancer

Bacteria proliferation-mediated cascade amplification for visually ultrasensitive detection of extracellular vesicles

In molecular diagnostics, there exist challenges in effectively isolating and sensitively detecting biomarkers such as extracellular vesicles (EVs)11Extracellular vesicles (EVs) visually. Within this study, we propose a highly sensitive and specific point-of-care testing (POCT)22Point-of-Care testing (POCT) strategy that utilizes the rapid capture of E. coli as a surrogate, coupled with volumetric bar-chart chips (V-chip)33volumetric bar-chart chips (V-chip) for EVs markers quantification. Firstly, the signals of EVs markers are transformed to bacteria numbers and exponentially amplified by exploiting the rapid self-proliferative ability of bacteria within a short timeframe. Secondly, the V-chip leverages the catalase activity of platinum nanoparticles (Pt NPs)44platinum nanoparticles (Pt NPs) to achieve further amplification of the bacterial signal. Consequently, integration of both techniques via a cascade amplification strategy significantly enhances the detection sensitivity for EVs biomarkers, enabling a limit of detection (LOD)55limit of detection (LOD) as low as 100 EVs/mL under optimal conditions. Additionally, the entire process of separation and detection is both facile and expeditious. The strategy also exhibits commendable specificity and reliability, making it applicable in the analysis of EVs within clinical samples. Overall, through the amalgamation of bacteria proliferation-mediated cascade amplification, this endeavor furnishes a sensitive and user-friendly platform to enhance EVs detection for POCT diagnostics.

Towards rapid colorimetric detection of extracellular vesicles using optofluidics-enhanced color-changing optical metasurface.

Efficient transportation and delivery of analytes to the surface of optical sensors are crucial for overcoming limitations in diffusion-limited transport and analyte sensing. In this study, we propose a novel approach that combines metasurface optics with optofluidics-enabled active transport of extracellular vesicles (EVs). By leveraging this combination, we show that we can rapidly capture EVs and detect their adsorption through a color change generated by a specially designed optical metasurface that produces structural colors. Our results demonstrate that the integration of optofluidics and metasurface optics enables spectrometer-less and label-free colorimetric read-out for EV concentrations as low as 107 EVs/ml, achieved within a short incubation time of two minutes.

The Application of Exosomes in the Diagnosis and Treatment of Renal Cell Carcinoma

Renal cell carcinoma (RCC) is an epithelial tumor originating from the proximal renal tubule of the urinary system. RCC is one of the most common and deadly tumors representing clear cell renal cell carcinoma (ccRCC) (about 75%) as major subtype characterized by high incidence and poor prognosis. There are no obvious clinical symptoms in the early stage ccRCC, but are readily visible in the late stage with >30% patients diagnosed with diffusion and metastasis. The incidence of RCC is higher in males than females and frequent in developed countries than in developing ones. The current treatment for rRCC mainly focuses on surgical excision and chemotherapy, however, it still suffers from high recurrence and poor survival, due to metastatic growth and insensitivity to radiotherapy and chemotherapy. Early diagnosis of RCC is very important and remains a top priority for its treatment. Exosomes are small vesicles with a lipid bilayer membrane structure that are actively secreted by normal and cancer cells in the body, containing bioactive substances such as proteins, nucleic acids, and lipids. The detection of extracellular vesicles in body fluids can play an important role in the early diagnosis of RCC. This article reviews the role of exosomes in the diagnosis and treatment of RCC.

Combination of specific proteins as markers for accurate detection of extracellular vesicles using proximity ligation-mediated bHCR amplification

As the molecular characteristics of extracellular vesicles (EVs) are closely related to the occurrence and progression of cancer, the detection of tumor-derived EVs provides a promising non-invasive tool for the early diagnosis and treatment of cancer. However, it would be difficult for most of the existing methods to avoid false positives because the obtained result declares the amounts of proteins, but cannot accurately reflect the protein sources, including EV proteins and interfering proteins, in the actual samples. In this manuscript, a robust, accurate, and sensitive fluorescent strategy for profiling EV proteins is developed by using the combination of specific proteins as markers (Co-marker). Our strategy relies on the Co-marker recognition-activated cascade bHCR amplification, which forms numerous G-quadruplex structures that are integrated with fluorescent dyes for signal transduction. Notably, the detection accuracy can be improved owing to the effective avoidance of false positives from interfering proteins or single protein markers. Moreover, by using the double-positive protein recognition mode, unpurified detection can be achieved that avoids time-consuming EVs purification procedures. With its capacities of accuracy, portability, sensitivity, high throughput, and non-purification, the developed strategy might provide a practical tool for EV identification and the related early diagnosis and treatment of cancer.

Multiplexing Biosensor for the Detection of Extracellular Vesicles as Biomarkers of Tissue Damage and Recovery after Ischemic Stroke.

The inflammatory, reparative and regenerative mechanisms activated in ischemic stroke patients immediately after the event cooperate in the response to injury, in the restoration of functions and in brain remodeling even weeks after the event and can be sustained by the rehabilitation treatment. Nonetheless, patients' response to treatments is difficult to predict because of the lack of specific measurable markers of recovery, which could be complementary to clinical scales in the evaluation of patients. Considering that Extracellular Vesicles (EVs) are carriers of multiple molecules involved in the response to stroke injury, in the present study, we have identified a panel of EV-associated molecules that (i) confirm the crucial involvement of EVs in the processes that follow ischemic stroke, (ii) could possibly profile ischemic stroke patients at the beginning of the rehabilitation program, (iii) could be used in predicting patients' response to treatment. By means of a multiplexing Surface Plasmon Resonance imaging biosensor, subacute ischemic stroke patients were proven to have increased expression of vascular endothelial growth factor receptor 2 (VEGFR2) and translocator protein (TSPO) on the surface of small EVs in blood. Besides, microglia EVs and endothelial EVs were shown to be significantly involved in the intercellular communications that occur more than 10 days after ischemic stroke, thus being potential tools for the profiling of patients in the subacute phase after ischemic stroke and in the prediction of their recovery.

Cover Picture: In vitro diagnostic technologies for the detection of extracellular vesicles: current status and future directions (View 2/2023)

Extracellular vesicles (EVs) provide real-time information about the physiological and pathological states of parental cells and are potential biomarkers for disease diagnosis. Many methods for isolating EVs from body fluids and techniques for analyzing EVs biomolecules, including protein, nucleic acids, and lipids, have emerged with potential for clinical application.

Highly Stable Fe/Co-TPY-MIL-88(NH2) Metal-Organic Framework (MOF) in Enzymatic Cascade Reactions for Chemiluminescence-Based Detection of Extracellular Vesicles.

Metal-Organic Frameworks (MOFs) can deliver many advantages when acting as enzyme mimics to assist with signal amplification in molecular detection: they have abundant active catalytic sites per unit volume of the material; their structures and elemental compositions are highly tunable, and their high specific surface area and porous property can assist with target separation and enrichment. In the present work, we have demonstrated that, by adding the pore partition agent, 2,4,6-tris(4-pyridyl)pyridine (TPY) during synthesis of the bimetallic Fe/Co-MIL-88(NH2) MOF to block the open metal sites, a highly porous MOF of Fe/Co-TPY-MIL-88(NH2) can be produced. This material also exhibits high stability in basic solutions and biofluids and possesses high peroxidase-mimicking activity, which can be utilized to produce long-lasting chemiluminescence (CL) from luminol and H2O2. Moreover, acting as the peroxidase-mimic, the Fe/Co-TPY-MIL-88(NH2) MOF can form the enzymatic cascade with glucose oxidase (GOx) for biomarker detection. When applied to detect extracellular vesicles (EVs), the MOF material and GOx are brought to the proximity on the EVs through two surface proteins, which triggers the enzyme cascade to produce high CL from glucose and luminol. EVs within the concentration range of 5 × 105 to 4 × 107 particles/mL can be detected with an LOD of 1 × 105 particles/mL, and the method can be used to analyze EV contents in human serum without sample preparation and EV purification. Overall, our work demonstrates that the high versatility and tunability of the MOF structures could bring in significant benefits to biosensing and enable ultrasensitive detection of biomarkers with judicious material designs.

Amplified EQCM-D detection of extracellular vesicles using 2D gold nanostructured arrays fabricated by block copolymer self-assembly.

Extracellular vesicles (EVs) are routinely released from nearly all cell types as transport vehicles and for cell communication. Crucially, they contain biomolecular content for the identification of health and disease states that can be detected from readily accessible physiological fluids, including urine, plasma, or saliva. Despite their clinical utility within noninvasive diagnostic platforms such as liquid biopsies, the currently available portfolio of analytical approaches are challenged by EV heterogeneity in size and composition, as well as the complexity of native biofluids. Quartz crystal microbalance with dissipation monitoring (QCM-D) has recently emerged as a powerful alternative for the phenotypic detection of EVs, offering multiple modes of analyte discrimination by frequency and dissipation. While providing rich data for sensor development, further progress is required to reduce detection limits and fully exploit the technique's potential within biosensing. Herein, we investigate the impact of nanostructuring the sensor electrode surface for enhancing its detection capabilities. We employ self-assembly of the block copolymer polystyrene-block-poly(4-vinylpyridine) to create well defined 2D gold islands via selective impregnation of the pyridine domain with gold precursors and subsequent removal of the template. When matched to the EV length scale, we find a 4-fold improvement in sensitivity despite a 4-fold reduction in area for analyte and ligand anchoring in comparison to a flat sensor surface. Creation of tailored and confined sensing regions interspersed by non-binding silica provides optimal spatial orientation for EV capture with reduced steric effects and negative cooperativity of grafted antibodies, offering a promising route for facilitated binding and enhanced performance of sensor platforms.

Ultrafast sensitivity-controlled and specific detection of extracellular vesicles using optical force with antibody-modified microparticles in a microflow system.

Extracellular vesicles (EVs), including nanoscale exosomes and ectosomes, hold promise as biomarkers that provide information about the cell of origin through their cargo of nucleic acids and proteins, both on their surface and within. Here, we develop a detection method of EVs based on light-induced acceleration of specific binding between their surface and antibody-modified microparticles, using a controlled microflow with three-dimensional analysis by confocal microscopy. Our method successfully detected 103-104 nanoscale EVs in liquid samples as small as a 500 nanoliters within 5 minutes, with the ability to distinguish multiple membrane proteins. Remarkably, we achieved the specific detection of EVs secreted from living cancer cell lines with high linearity, without the need for a time-consuming ultracentrifugation process that can take several hours. Furthermore, the detection range can be controlled by adjusting the action range of optical force using a defocused laser, consistent with the theoretical calculations. These findings demonstrate an ultrafast, sensitive, and quantitative approach for measuring biological nanoparticles, enabling innovative analyses of cell-to-cell communication and early diagnosis of various diseases, including cancer.

In vitro diagnostic technologies for the detection of extracellular vesicles: current status and future directions

AbstractExtracellular vesicles (EVs) are natural vehicles carrying and transferring bioactive molecules for intercellular communication and play key roles in physiological and pathological processes. EVs are promising biomarkers for disease diagnosis due to their rich biological information and minimally invasive sampling. In this review, we summarize the current methods for isolating EVs from the body fluids and the techniques for analyzing EVs’ biomolecules including the proteins, nucleic acids, and lipids. The advantages, feasibility, and challenges of EV‐based in vitro diagnosis toward clinical application are discussed. Finally, an outlook on the marketing and routine clinical application of EV‐based in vitro diagnosis is provided.

Antenna-enhanced mid-infrared detection of extracellular vesicles derived from human cancer cell cultures

BackgroundExtracellular Vesicles (EVs) are sub-micrometer lipid-bound particles released by most cell types. They are considered a promising source of cancer biomarkers for liquid biopsy and personalized medicine due to their specific molecular cargo, which provides biochemical information on the state of parent cells. Despite this potential, EVs translation process in the diagnostic practice is still at its birth, and the development of novel medical devices for their detection and characterization is highly required.ResultsIn this study, we demonstrate mid-infrared plasmonic nanoantenna arrays designed to detect, in the liquid and dry phase, the specific vibrational absorption signal of EVs simultaneously with the unspecific refractive index sensing signal. For this purpose, EVs are immobilized on the gold nanoantenna surface by immunocapture, allowing us to select specific EV sub-populations and get rid of contaminants. A wet sample-handling technique relying on hydrophobicity contrast enables effortless reflectance measurements with a Fourier-transform infrared (FTIR) spectro-microscope in the wavelength range between 10 and 3 µm. In a proof-of-principle experiment carried out on EVs released from human colorectal adenocarcinoma (CRC) cells, the protein absorption bands (amide-I and amide-II between 5.9 and 6.4 µm) increase sharply within minutes when the EV solution is introduced in the fluidic chamber, indicating sensitivity to the EV proteins. A refractive index sensing curve is simultaneously provided by our sensor in the form of the redshift of a sharp spectral edge at wavelengths around 5 µm, where no vibrational absorption of organic molecules takes place: this permits to extract of the dynamics of EV capture by antibodies from the overall molecular layer deposition dynamics, which is typically measured by commercial surface plasmon resonance sensors. Additionally, the described metasurface is exploited to compare the spectral response of EVs derived from cancer cells with increasing invasiveness and metastatic potential, suggesting that the average secondary structure content in EVs can be correlated with cell malignancy.ConclusionsThanks to the high protein sensitivity and the possibility to work with small sample volumes—two key features for ultrasensitive detection of extracellular vesicles- our lab-on-chip can positively impact the development of novel laboratory medicine methods for the molecular characterization of EVs.Graphical

Monocrystalline Labeling Enables Stable Plasmonic Enhancement for Isolation-Free Extracellular Vesicle Analysis.

Sensitive detection of extracellular vesicles (EVs) as emerging biomarkers has shown great promises for disease diagnosis. Plasmonic metal nanostructures conjugated with molecules that bind specific biomarker targets are widely used for EVs sensing but involve tradeoffs between particle-size-dependent signal intensity and conjugation efficiency. One solution to this problem would be to induce nucleation on nanoparticles that have successfully bound a target biomarker to permit in situ nanoparticle growth for signal amplification, but approaches that are evaluated to date require harsh conditions or lack nucleation specificity, prohibiting their effective use with most biological specimens. This study describes a one-step in situ strategy to induce monocrystalline copper shell growth on gold nanorod probes without decreasing signal by disrupting probe-target interactions or lipid bilayer integrity to enable EV biomarker detections. This approach increases the detected nanoparticle signal about two orders of magnitude after a 10 min copper nanoshell growth reaction. This has significant implications for improved disease detection, as indicated by the ability of a novel immunoassay using this approach to detect low abundance EVs carrying a pathogen-derived biomarker, after their direct capture from serum, to facilitate the diagnosis of tuberculosis cases in a diagnostically challenging pediatric cohort.

Recent advancements in DNA nanotechnology-enabled extracellular vesicles detection and diagnosis: A mini review

Extracellular vesicles (EVs) are cell-derived nanosized vesicles widely recognized for their critical roles in various pathophysiological processes. Molecular analysis of EVs is currently being considered an emerging tool for diseases diagnosis. However, the small size and heterogeneity of EVs has staggered the EVs research for diseases diagnosis. DNA nanotechnology enables self-assembly of versatile DNA nanostructures and has shown enormous potential in assisting EVs biosensing. In this review, we briefly introduce the recent advances in DNA nanotechnology approaches for EVs detection. The approaches were categorized based on the dimension of DNA nanostructures. We provide critical evaluation of these approaches, and summarize the pros and cons of specific methods. Further, we discuss the challenges and future perspectives in this field.

Highly sensitive detection of extracellular vesicles on ZnO nanorods integrated microarray chips with cascade signal amplification and portable glucometer readout

Extracellular vesicle (EV) has become a type of potential biomarker for cancer diagnosis in liquid biopsy. However, the accurate detection of EVs for large-scale cancer scanning is still challenge due to the low sensitivity, high cost, and requirement of large instruments, which impedes their wide applications in clinical trials, especially in resource limited areas. Herein, we report a ZnO nanorods integrated microarray chip (ZnO-chip) for effective capture and sensitive detection of EVs. The ZnO-chip provides abundant binding sites for EVs capture. Meanwhile, the high-ordered hybridization chain reaction and non-ordered enzyme catalytic reaction are collaborated for cascade signal amplification. The oxidized product, glucose, can be read out directly by portable glucometer to realize accurate quantitation of EVs with a linear range of 1.0 × 104 to 8.4 × 107 particles/μL and a minimal detectable concentration of 3.3 × 103 particles/μL. Our approach could distinguish cancer patients from healthy individuals, proving the statistically increase of EVs in serums of cancer patients. Finally, we verify that the captured EVs can be released for downstream molecular assays by dissolving ZnO nanorods under slightly acidic condition. We believe our approach has remarkable possibility for the routine screening of cancer patients in clinical trials.

Biomimetic 3D Recognition with 2D Flexible Nanoarchitectures for Ultrasensitive and Visual Extracellular Vesicle Detection.

Despite increasing recognition of extracellular vesicles being important circulating biomarkers in disease diagnosis and prognosis, current strategies for extracellular vesicle detection remain limited due to the compromised sample purification and extensive labeling procedures in complex body fluids. Here, we developed a 2D magnetic platform that greatly improves capture efficiency and readily realizes visible signal conversion for extracellular vesicle detection. The technology, termed high-affinity recognition and visual extracellular vesicle testing (HARVEST), leverages 2D flexible Fe3O4-MoS2 nanostructures to recognize extracellular vesicles through multidentate affinity binding and feasible magnetic separation, thus enhancing the extracellular vesicle capture performance with both yield and separation time, affording high sensitivity with the detection limit of 20 extracellular vesicle particles/μL. Through integration with lipid labeling chemistry and the fluorescence visualization system, the platform enables rapid and visible detection. The number of extracellular vesicles can be feasibly determined by smart mobile phones, readily adapted for point-of-care diagnosis. When clinically evaluated, the strategy accurately differentiates melanoma samples from the normal cohort with an AUC of 0.98, demonstrating the efficient extracellular vesicle detection strategy with 2D flexible platforms for cancer diagnosis.