Single Extracellular Vesicles Research Articles

Squeezable Hydrogel Microparticles for Single Extracellular Vesicle Protein Profiling.

Extracellular vesicles (EVs) are promising for molecular diagnostics, but current analyses are limited by the rarity and compositional heterogeneity of EV protein expression. Therefore, single EV profiling methods require high sensitivity, multiplexing, and throughput to address these issues. Here a single EV analysis technique that utilizes squeezable methacrylated hyaluronic acid hydrogel microparticles (MHPs) is described as a scaffold to immobilize EVs and perform an integrated rolling circle amplification (RCA) assay for an ultra-sensitive and multiplex analysis of single EV proteins. EVs are prepared into MHPs in a high-throughput manner with droplet microfluidics and optimally labeled with antibody-oligonucleotide conjugates in MHPs without steric limitations. By designing MHPs with high compressibility, single EV protein signals are amplified as RCA products that can be aligned on the same plane by physically squeezing MHPs and visualized with low magnification. This method provides a simple and scalable single EV imaging analysis pipeline for identifying multiplex marker expression patterns from single EVs. For validation, the single EV heterogeneity of highly expressed cancer cell markers is profiled across different cancer cell lines. These findings exemplify squeezable MHPs as a robust platform with high sensitivity, multiplexing, and scalability for resolving single EV heterogeneity and advancing molecular assay technologies.

Rapid Assessment of Biomarkers on Single Extracellular Vesicles Using "Catch and Display" on Ultrathin Nanoporous Silicon Nitride Membranes.

Extracellular vesicles (EVs) are particles released from cells that facilitate intercellular communication and have tremendous diagnostic and therapeutic potential. Bulk assays lack the sensitivity to detect rare EV subsets relevant to disease, and while single EV analysis techniques remedy this, they are often undermined by complicated detection schemes and prohibitive instrumentation. To address these issues, a microfluidic technique for EV characterization called "catch and display for liquid biopsy (CAD-LB)" is proposed. In this method, minimally processed samples are pipette-injected and fluorescently labeled EVs are captured in the nanopores of an ultrathin membrane. This enables the rapid assessment of EV number and biomarker colocalization by light microscopy. Here, nanoparticles are used to define the accuracy and dynamic range for counting and colocalization. The same assessments are then made for purified EVs and for unpurified EVs in plasma. Biomarker detection is validated using CD9 and Western blot analysis to confirm that CAD-LB accurately reports relative protein expression levels. Using unprocessed conditioned media,CAD-LB captures the known increase in EV-associated ICAM-1 following endothelial cell cytokine stimulation. Finally, to demonstrate CAD-LB's clinical potential, EV biomarkers indicative of immunotherapy responsiveness are successfully detected in the plasma of bladder cancer patients treated with immune checkpoint blockade.

Tetraspanins, GLAST and L1CAM Quantification in Single Extracellular Vesicles from Cerebrospinal Fluid and Serum of People with Multiple Sclerosis.

Objective: This study aimed to unravel the single tetraspanin pattern of extracellular vesicles (EVs), L1CAM+ and GLAST+ EV levels as diagnostic biomarkers to stratify people with multiple sclerosis (pwMS), specifically relapsing-remitting (RRMS) and primary progressive (PPMS). Methods: The ExoView platform was used to directly track single EVs using a clinically feasible volume of cerebrospinal fluid (CSF) and serum samples. This technology allowed us to examine the patterns of classical tetraspanin and quantify the levels of L1CAM and GLAST proteins, commonly used to immunoisolate putative neuron- and astrocyte-derived EVs. Results: The tetraspanin EV pattern does not allow us to differentiate RRMS, PPMS and non-MS donors neither in CSF nor serum, but this was associated with the type of biofluid. L1CAM+ and GLAST+ EVs showed a very low presence of tetraspanin proteins. Additionally, a significant decrease in the particle count of L1CAM+ EVs was detected in L1CAM-captured spots, and L1CAM+ and GLAST+ EVs decreased in GLAST-captured spots in the CSF from PPMS subjects compared to RRMS. Interestingly, only GLAST+ EVs exhibited a lower quantity in the CSF from PPMS compared to both MS and non-MS samples. Finally, GLAST+ EVs demonstrated a medium negative and significative correlation with GFAP levels-a biomarker of MS progression, astrocyte damage and neurodegenerative processes. Conclusions: ExoView technology could track neural EV biomarkers and be potentially useful in the diagnostic evaluation and follow-up of pwMS. GLAST+ EVs might provide insights into the etiology of PPMS and could offer small windows to elucidate the molecular mechanisms behind its clinical presentation.

Analysis of Single Urinary Extracellular Vesicles from Subregions of the Nephron as a Diagnostic Tool in Early Diabetic Nephropathy

Analysis of Single Urinary Extracellular Vesicles from Subregions of the Nephron as a Diagnostic Tool in Early Diabetic Nephropathy

Snorkel-tag based affinity chromatography for recombinant extracellular vesicle purification.

Extracellular vesicles (EVs) are lipid nanoparticles and play an important role in cell-cell communications, making them potential therapeutic agents and allowing to engineer for targeted drug delivery. The expanding applications of EVs in next generation medicine is still limited by existing tools for scaling standardized EV production, single EV tracing and analytics, and thus provide only a snapshot of tissue-specific EV cargo information. Here, we present the Snorkel-tag, for which we have genetically fused the EV surface marker protein CD81, to a series of tags with an additional transmembrane domain to be displayed on the EV surface, resembling a snorkel. This system enables the affinity purification of EVs from complex matrices in a non-destructive form while maintaining EV characteristics in terms of surface protein profiles, associated miRNA patterns and uptake into a model cell line. Therefore, we consider the Snorkel-tag to be a widely applicable tool in EV research, allowing for efficient preparation of EV standards and reference materials, or dissecting EVs with different surface markers when fusing to other tetraspanins in vitro or in vivo.

Simultaneous Protein and RNA Analysis in Single Extracellular Vesicles, Including Viruses.

The individual detection of human immunodeficiency virus (HIV) virions and resolution from extracellular vesicles (EVs) during analysis is a difficult challenge. Infectious enveloped virions and nonviral EVs are released simultaneously by HIV-infected host cells, in addition to hybrid viral EVs containing combinations of HIV and host components but lacking replicative ability. Complicating the issue, EVs and enveloped virions are both delimited by a lipid bilayer and share similar size and density. The feature that distinguishes infectious virions from host and hybrid EVs is the HIV genomic RNA (gRNA), which allows the virus to replicate. Single-particle analysis techniques, which provide snapshots of single biological nanoparticles, could resolve infectious virions from EVs. However, current single-particle analysis techniques focus mainly on protein detection, which fail to resolve hybrid EVs from infectious virions. A method to simultaneously detect viral protein and internal gRNA in the same particle would allow resolution of infectious HIV from EVs and noninfectious virions. Here, we introduce SPIRFISH, a high-throughput method for single-particle protein and RNA analysis, combining single particle interferometric reflectance imaging sensor with single-molecule fluorescence in situ hybridization. Using SPIRFISH, we detect HIV-1 envelope protein gp120 and genomic RNA within single infectious virions, allowing resolution against EV background and noninfectious virions. We further show that SPIRFISH can be used to detect specific RNAs within EVs. This may have major utility for EV therapeutics, which are increasingly focused on EV-mediated RNA delivery. SPIRFISH should enable single particle analysis of a broad class of RNA-containing nanoparticles.

Improving Specificity for Ovarian Cancer Screening Using a Novel Extracellular Vesicle–Based Blood Test: Performance in a Training and Verification Cohort

The low incidence of ovarian cancer (OC) dictates that any screening strategy needs to be both highly sensitive and highly specific. This study explored the utility of detecting multiple colocalized proteins or glycosylation epitopes on single tumor-associated extracellular vesicles (EVs) from blood. The novel OC Test employs immunoaffinity capture of tumor-associated EVs followed by proximity-ligation qPCR to detect combinations of up to three biomarkers to maximize specificity and measures multiple combinations to maximize sensitivity. A high-grade serous carcinoma (HGSC) case-control training set of EDTA plasma samples from 397 women was used to lock down the test design, the data interpretation algorithm, and the cut-off between cancer and non-cancer. Performance was verified and compared to CA125 in an independent blinded case-control set of serum samples from 390 women (132 controls, 66 HGSC, 83 non-HGSC OC, 109 benign). In the verification study, the OC Test showed a specificity of 97.0% (128/132; 95% CI: 92.4%-99.6%), a HGSC sensitivity of 97.0% (64/66; 95% CI: 87.8%-99.2%), and an AUC of 0.97 (95% CI 0.93-0.99) and also detected 73.5% (61/83; 95% CI: 62.7%-82.6%) of the non-HGSC OC cases. This test exhibited fewer false positives in subjects with benign ovarian tumors, non-ovarian cancers, and inflammatory conditions when compared to CA125. The combined sensitivity and specificity of this new test suggests it may have potential in OC screening.

Colocalization of Cancer-Associated Biomarkers on Single Extracellular Vesicles for Early Detection of Cancer

Detection of cancer early, when it is most treatable, remains a significant challenge due to the lack of diagnostic methods sufficiently sensitive to detect nascent tumors. Early-stage tumors are small relative to their tissue of origin, heterogeneous, and infrequently manifest in clinical symptoms. Detection of their presence is made more difficult by a lack of abundant tumor-specific indicators (i.e., protein biomarkers, circulating tumor DNA, etc.) that would enable detection using a non-invasive diagnostic assay. To overcome these obstacles, we have developed a liquid biopsy assay that interrogates circulating extracellular vesicles (EVs) to detect tumor-specific biomarkers colocalized on the surface of individual EVs. We demonstrate the technical feasibility of this approach in human cancer cell line-derived EVs where we show strong correlations between assay signal and cell line gene/protein expression for the ovarian cancer-associated biomarkers BST2, FOLR1, and MUC1. Furthermore, we demonstrate that detecting distinct colocalized biomarkers on the surface of EVs significantly improves discrimination performance relative to single biomarker measurements. Using this approach, we observe promising discrimination of high-grade serous ovarian cancer versus benign ovarian masses and healthy women in a proof-of-concept clinical study.

Extracellular Vesicles heterogeneity through the lens of multiomics.

Extracellular vesicles (EVs) are heterogenous in size, biogenesis, cargo and function. Beside small EVs, aggressive tumor cells release a population of particularly large EVs, namely large oncosomes (LO). This study provides the first resource of label-free quantitative proteomics of LO and small EVs obtained from distinct cancer cell types (prostate, breast, and glioma). This dataset was integrated with a SWATH Proteomic assay on LO, rigorously isolated from the plasma of patients with metastatic prostate cancer (PC). Proteins enriched in LO, which were identified also at the RNA level, and found in plasma LO significantly correlated with PC progression. Single EV RNA-Seq of the PC cell-derived LO confirmed some of the main findings from the bulk RNA-Seq, providing first evidence that single cell technologies can be successfully applied to EVs. This multiomics resource of cancer EVs can be leveraged for developing a multi-analyte approach for liquid biopsy.

Comparison of EV characterization by commercial high-sensitivity flow cytometers and a custom single-molecule flow cytometer.

High-sensitivity flow cytometers have been developed for multi-parameter characterization of single extracellular vesicles (EVs), but performance varies among instruments and calibration methods. Here we compare the characterization of identical (split) EV samples derived from human colorectal cancer (DiFi) cells by three high-sensitivity flow cytometers, two commercial instruments, CytoFLEX/CellStream, and a custom single-molecule flow cytometer (SMFC). DiFi EVs were stained with the membrane dye di-8-ANEPPS and with PE-conjugated anti-EGFR or anti-tetraspanin (CD9/CD63/CD81) antibodies for estimation of EV size and surface protein copy numbers. The limits of detection (LODs) for immunofluorescence and vesicle size based on calibration using cross-calibrated, hard-dyed beads were ∼10 PE/∼80nm EV diameter for CytoFLEX and ∼10 PEs/∼67nm for CellStream. For the SMFC, the LOD for immunofluorescence was 1 PE and ≤ 35nm for size. The population of EVs detected by each system (di-8-ANEPPS+/PE+ particles) differed widely depending on the LOD of the system; for example, CellStream/CytoFLEX detected only 5.7% and 1.5% of the tetraspanin-labelled EVs detected by SMFC, respectively, and median EV diameter and antibody copy numbers were much larger for CellStream/CytoFLEX than for SMFC as measured and validated using super-resolution/single-molecule TIRF microscopy. To obtain a dataset representing a common EV population analysed by all three platforms, we filtered out SMFC and CellStream measurements for EVs below the CytoFLEX LODs as determined by bead calibration (10 PE/80nm). The inter-platform agreement using this filtered dataset was significantly better than for the unfiltered dataset, but even better concordance between results was obtained by applying higher cutoffs (21 PE/120nm) determined by threshold analysis using the SMFC data. The results demonstrate the impact of specifying LODs to define the EV population analysed on inter-instrument reproducibility in EV flow cytometry studies, and the utility of threshold analysis of SMFC data for providing semi-quantitative LOD values for other flow cytometers.

Mechanical property estimation of sarcoma-relevant extracellular vesicles using transmission electron microscopy.

Analysis of single extracellular vesicles (EVs) has the potential to yield valuable label-free information on their morphological structure, biomarkers and therapeutic targets, though such analysis is hindered by the lack of reliable and quantitative measurements of the mechanical properties of these compliant nanoscale particles. The technical challenge in mechanical property measurements arises from the existing tools and methods that offer limited throughput, and the reported elastic moduli range over several orders of magnitude. Here, we report on a flow-based method complemented by transmission electron microscopy (TEM) imaging to provide a high throughput, whole EV deformation analysis for estimating the mechanical properties of liposarcoma-derived EVs as a function of their size. Our study includes extracting morphological data of EVs from a large dataset of 432 TEM images, with images containing single to multiple EVs, and implementing the thin-shell deformation theory. We estimated the elastic modulus, E = 0.16 ± 0.02 MPa (mean±SE) for small EVs (sEVs; 30-150nm) and E = 0.17 ± 0.03 MPa (mean±SE) for large EVs (lEVs; >150 nm). To our knowledge, this is the first report on the mechanical property estimation of LPS-derived EVs and has the potential to establish a relationship between EV size and EV mechanical properties.

Classification of single extracellular vesicles in a double nanohole optical tweezer for cancer detection

A major challenge in cancer prognostics is finding early biomarkers that can accurately identify cancer. Circulating tumor cells are rare and circulating tumor DNA can not provide information about the originating cell. Extracellular vesicles (EVs) contain cell specific information, are abundant in fluids, and have unique properties between cancerous and non-cancerous. Fluorescence measurements have limitations from intrinsic fluorescent background signals, photobleaching, non-specific labelling, and EV structural modifications. Here, we demonstrate a label-free approach to classification of 3 different EVs, derived from non-malignant, non-invasive cancerous, and invasive cancerous cell lines. Using double nanohole optical tweezers, the scattering from single trapped EVs is measured, and using a 1D convolutional neural network, we are able to classify the time series optical signal into its respective EV class with greater than 90% accuracy.

Integrated Antigenic and Nucleic Acid Detection in Single Virions and Extracellular Vesicles with Viral Content.

Virion-mediated outbreaks are imminent and despite rapid responses, continue to cause adverse symptoms and death. Therefore, tunable, sensitive, high-throughput assays are needed to help diagnose future virion-mediated outbreaks. Herein, it is developed a tunable in situ assay to selectively enrich virions and extracellular vesicles (EVs) and simultaneously detect antigens and nucleic acids at a single-particle resolution. The Biochip Antigen and RNA Assay (BARA) enhanced sensitivities compared to quantitative reverse-transcription polymerase chain reaction (qRT-PCR), enabling the detection of virions in asymptomatic patients, genetic mutations in single virions, and enabling the continued long-term expression of viral RNA in the EV-enriched subpopulation in the plasma of patients with post-acute sequelae of the coronavirus disease of 2019 (COVID-19). BARA revealed highly accurate diagnoses of COVID-19 by simultaneously detecting the spike glycoprotein and nucleocapsid-encoding RNA in saliva and nasopharyngeal swab samples. Altogether, the single-particle detection of antigens and viral RNA provides a tunable framework for the diagnosis, monitoring, and mutation screening of current and future outbreaks.

Extracellular Vesicle Preparation and Analysis: A State-of-the-Art Review.

In recent decades, research on Extracellular Vesicles (EVs) has gained prominence in the life sciences due to their critical roles in both health and disease states, offering promising applications in disease diagnosis, drug delivery, and therapy. However, their inherent heterogeneity and complex origins pose significant challenges to their preparation, analysis, and subsequent clinical application. This review is structured to provide an overview of the biogenesis, composition, and various sources of EVs, thereby laying the groundwork for a detailed discussion of contemporary techniques for their preparation and analysis. Particular focus is given to state-of-the-art technologies that employ both microfluidic and non-microfluidic platforms for EV processing. Furthermore, this discourse extends into innovative approaches that incorporate artificial intelligence and cutting-edge electrochemical sensors, with a particular emphasis on single EV analysis. This review proposes current challenges and outlines prospective avenues for future research. The objective is to motivate researchers to innovate and expand methods for the preparation and analysis of EVs, fully unlocking their biomedical potential.

Heterogeneous Analysis of Extracellular Vesicles for Osteosarcoma Diagnosis.

Osteosarcoma (OS) is the most prevalent primary tumor of bones, often diagnosed late with a poor prognosis. Currently, few effective biomarkers or diagnostic methods have been developed for early OS detection with high confidence, especially for metastatic OS. Tumor-derived extracellular vesicles (EVs) are emerging as promising biomarkers for early cancer diagnosis through liquid biopsy. Here, we report a plasmonic imaging-based biosensing technique, termed subpopulation protein analysis by single EV counting (SPASEC), for size-dependent EV subpopulation analysis. In our SPASEC platform, EVs are accurately sized and counted on plasmonic sensor chips coated with OS-specific antibodies. Subsequently, EVs are categorized into distinct subpopulations based on their sizes, and the membrane proteins of each size-dependent subpopulation are profiled. We measured the heterogeneous expression levels of the EV markers (CD63, BMP2, GD2, and N-cadherin) in each of the EV subsets from both OS cell lines and clinical plasma samples. Using the linear discriminant analysis (LDA) model, the combination of four markers is applied to classify the healthy donors (n = 37), nonmetastatic OS patients (n = 13), and metastatic patients (n = 12) with an area under the curve of 0.95, 0.92, and 0.99, respectively. SPASEC provides accurate EV sensing technology for early OS diagnosis.

Plasmonic nano-aperture label-free imaging of single small extracellular vesicles for cancer detection

BackgroundSmall extracellular vesicle (sEV) analysis can potentially improve cancer detection and diagnostics. However, this potential has been constrained by insufficient sensitivity, dynamic range, and the need for complex labeling.MethodsIn this study, we demonstrate the combination of PANORAMA and fluorescence imaging for single sEV analysis. The co-acquisition of PANORAMA and fluorescence images enables label-free visualization, enumeration, size determination, and enables detection of cargo microRNAs (miRs).ResultsAn increased sEV count is observed in human plasma samples from patients with cancer, regardless of cancer type. The cargo miR-21 provides molecular specificity within the same sEV population at the single unit level, which pinpoints the sEVs subset of cancer origin. Using cancer cells-implanted animals, cancer-specific sEVs from 20 µl of plasma can be detected before tumors were palpable. The level plateaus between 5–15 absolute sEV count (ASC) per µl with tumors ≥8 mm3. In healthy human individuals (N = 106), the levels are on average 1.5 ASC/µl (+/− 0.95) without miR-21 expression. However, for stage I–III cancer patients (N = 205), nearly all (204 out of 205) have levels exceeding 3.5 ASC/µl with an average of 12.2 ASC/µl (±9.6), and a variable proportion of miR-21 labeling among different tumor types with 100% cancer specificity. Using a threshold of 3.5 ASC/µl to test a separate sample set in a blinded fashion yields accurate classification of healthy individuals from cancer patients.ConclusionsOur techniques and findings can impact the understanding of cancer biology and the development of new cancer detection and diagnostic technologies.

Poloxamer-188 as a wetting agent for microfluidic resistive pulse sensing measurements of extracellular vesicles.

Microfluidic resistive pulse sensing (MRPS) can determine the concentration and size distribution of extracellular vesicles (EVs) by measuring the electrical resistance of single EVs passing through a pore. To ensure that the sample flows through the pore, the sample needs to contain a wetting agent, such as bovine serum albumin (BSA). BSA leaves EVs intact but occasionally results in unstable MRPS measurements. Here, we aim to find a new wetting agent by evaluating Poloxamer-188 and Tween-20. An EV test sample was prepared using an outdated erythrocyte blood bank concentrate. The EV test sample was diluted in Dulbecco's phosphate-buffered saline (DPBS) or DPBS containing 0.10% BSA (w/v), 0.050% Poloxamer-188 (v/v) or 1.00% Tween-20 (v/v). The effect of the wetting agents on the concentration and size distribution of EVs was determined by flow cytometry. To evaluate the precision of sample volume determination with MRPS, the interquartile range (IQR) of the particles transit time through the pore was examined. To validate that DPBS containing Poloxamer-188 yields reliable MRPS measurements, the repeatability of MRPS in measuring blood plasma samples was examined. Flow cytometry results show that the size distribution of EVs in Tween 20, in contrast to Poloxamer-188, differs from the control measurements (DPBS and DPBS containing BSA). MRPS results show that Poloxamer-188 improves the precision of sample volume determination compared to BSA and Tween-20, because the IQR of the transit time of EVs in the test sample is 11 μs, which is lower than 56 μs for BSA and 16 μs for Tween-20. Furthermore, the IQR of the transit time of particles in blood samples with Poloxamer-188 are 14, 16, and 14 μs, which confirms the reliability of MRPS measurements. The solution of 0.050% Poloxamer-188 in DPBS does not lyse EVs and results in repeatable and unimpeded MRPS measurements.

305 Extracellular Vesicular mRNA and miRNA Biomarkers in Patients With Glioblastoma

INTRODUCTION: Glioblastoma (GBM) is a highly lethal primary brain cancer that is resistant to conventional immunotherapies. However, currently, there is a lack of reliable biomarkers for clinical practice. Extracellular vesicles (EVs) present in biofluids are a potential biomarker for GBM diagnosis. METHODS: EVs from cell culture medium, healthy donor and GBM patient serum were purified using tangential flow filtration (TFF). Morphology, size, and numbers of EVs were characterized by TEM and qNano, respectively. EVs from healthy donor and GBM patient serum were compared against other cancer EV samples using bulk mRNA and miRNA sequencing analysis. Selected mRNA and miRNA name are not mentioned due to patents being drafted. mRNA and miRNA expression in EVs were quantified by a fluorescent nucleic acid detection method using a biochip platform at a single-EV level. Fluorescence images were recorded using high-resolution total internal reflection fluorescence (TIRF) microscopy. RESULTS: From bulk mRNA and miRNA sequencing and bioinformatics analysis, three miRNA and two mRNA were selected as potential candidate biomarkers for GBM. Subsequently, EVs from the serum of GBM patients (n = 39) were evaluated through our biochip platform. mRNA and miRNA expression of these biomarkers were positive in single EVs, for which we detected colocalization of protein/RNAs or multiple RNAs in subpopulations of EVs. Our platform was benchmarked with a standard PCR method showing 100X more sensitivity. Moreover, levels of expression of the different RNAs were compared to a cohort of serum from healthy donors (n=20), and showing significant differences between the two groups. CONCLUSIONS: Our non-invasive biochip assay outperformed qRT-PCR for EV RNA detection. Selected mRNAs and miRNAs in subpopulations of EVs could be used as potential GBM biomarkers.

Precise analysis of single small extracellular vesicles using flow cytometry

Methods that enable specific and sensitive quantification of small extracellular vesicles (sEVs) using flow cytometry are still under development. Aggregation or adsorption of antibodies causes sub-nano sized particles or non-specific binding and largely affects the results of flow cytometric analysis of single sEVs. Comparison of control IgG and target-specific IgG is inappropriate because they have different characters. Here, we evaluate four preparation methods for flow cytometry, including ultracentrifugation, density gradient centrifugation, size exclusion chromatography (SEC), and the TIM4-affinity method by using tetraspanin-deficient sEVs. The ultracentrifugation or density gradient centrifugation preparation method has large false-positive rates for tetraspanin staining. Conversely, preparation methods using SEC or the TIM4-affinity method show specific detection of single sEVs, which elucidate the roles of sEV biogenesis regulators in the generation of sEV subpopulations. The methods are also useful for the detection of rare disease-related markers, such as PD-L1. Flow cytometric analysis using SEC or the TIM4-affinity method could accelerate research into sEV biogenesis and the development of sEV-based diagnostics and therapies.

Abstract 1066: Colocalization of ovarian cancer-associated biomarkers in tumors, cancer cells and extracellular vesicles

Abstract Introduction: We have previously shown that ovarian cancer can be detected with high specificity and sensitivity by interrogating colocalized membrane-associated cell-surface biomarkers on single tumor-associated extracellular vesicles (EVs). Our blood based Ovarian Cancer Test (OC Test) is composed of 5 cancer-associated biomarkers (BST-2, FOLR1, MUC-1, MUC-16, and sialylated Thomsen-nouveau antigen (sTn)) known to be overexpressed in ovarian cancer relative to healthy tissues. The test employs these 5 biomarkers in 3 combinations to capture and detect EVs from human plasma to distinguish high-grade serous ovarian carcinoma (HGSC) from both benign ovarian tumors and normal samples. Using super-resolution microscopy on ovarian cancer cell lines and EVs and multiplex immunohistochemistry of ovarian benign and tumor tissue, our study aimed to show that the 5 ovarian cancer biomarkers show 1) colocalization on ovarian cancer cells, 2) colocalization on the surface of EVs, and 3) colocalization on cancer cells within ovarian tumor biopsies. Methods: Super-resolution microscopy was employed to visualize stained biomarkers on the cell surface of a collection of ovarian cancer cell lines as well as on the surface of extracellular vesicles released by these cell lines. 58 HGSC (17 Stage I, 30 Stage II, and 10 Stage III) and 17 benign ovarian tumor K2EDTA plasma samples and paired FFPE tissue were sourced from the Ovarian Cancer Research Program (OVCARE, Vancouver BC, Canada). A tumor microarray from identical tissue samples was stained with an Opal multiplex-IHC (mIHC) assay comprised of antibodies to BST2, MUC1, sTn, and pan-cytokeratin and a DAPI counterstain. Machine learning based image analysis was utilized to determine colocalization of the biomarkers at the cellular level within benign and tumor tissue. RNA sequencing was carried out to assess expression levels of the biomarkers in each FFPE tissue sample. OC Tests were run on each plasma sample. Results: Super-resolution microscopy showed colocalization of OC Test combination biomarkers on ovarian cancer cells and EVs derived therefrom. Machine learning-based image analysis of tumor and benign tissue microarrays stained for BST2/MUC1/sTn using mIHC, showed strong evidence for colocalization of these biomarkers on single cells within ovarian tumor tissue, particularly in early-stage tumors, but not on benign tissue. RNA sequencing analysis showed good correlation of biomarker RNA expression levels and with the OC Test results. Conclusions: The results presented here demonstrate that the OC Test biomarkers are colocalized on tumor tissue, ovarian cancer cells, and EVs from ovarian cancer cell lines. RNA and protein expression levels show good correlation with OC Test results. These results provide further evidence that colocalized biomarkers on EVs can be utilized for early detection of cancer. Citation Format: Anthony D. Couvillon, Emily S. Winn-Deen, Shelby Thornton, Shuhong Liu, Michael DeRan, Maciej Pacula, Sanchari Banerjee, Daniel Gusenleitner, Laura T. Bortolin, Jonian Grosha, Timothy Santos-Heiman, Gabrielle Sangiuliano, Kelly M. Biette, Christopher R. Sedlak, Bilal Hamzeh, Delaney M. Byrne, Peter A. Duff, Julie Ho, Dongxia Gao, Amy Jamieson, Lauren T. Cuoco, MacKenzie S. King, Dawn R. Mattoon, Toumy Guettouche, Jessica N. McAlpine, David Huntsman. Colocalization of ovarian cancer-associated biomarkers in tumors, cancer cells and extracellular vesicles [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1066.