Training an automated circulating tumor cell classifier when the true classification is uncertain.

Circulating tumor cell (CTC) and tumor-derived extracellular vesicle (tdEV) loads are prognostic factors of survival in patients with carcinoma. The current method of CTC enumeration relies on operator review and, unfortunately, has moderate interoperator agreement (Fleiss' kappa 0.60) due to difficulties in classifying CTC-like events. We compared operator review, ACCEPT automated image processing, and refined the output of a deep-learning algorithm to identify CTC and tdEV for the prediction of survival in patients with metastatic and nonmetastatic cancers. Operator review is only defined for CTC. Refinement was performed using automatic contrast maximization CM-CTC of events detected in cancer and in benign samples (CM-CTC). We used 418 samples from benign diseases, 6,293 from nonmetastatic breast, 2,408 from metastatic breast, and 698 from metastatic prostate cancer to train, test, optimize, and evaluate CTC and tdEV enumeration. For CTC identification, the CM-CTC performed best on metastatic/nonmetastatic breast cancer, respectively, with a hazard ratio (HR) for overall survival of 2.6/2.1 vs. 2.4/1.4 for operator CTC and 1.2/0.8 for ACCEPT-CTC. For tdEV identification, CM-tdEV performed best with an HR of 1.6/2.9 vs. 1.5/1.0 with ACCEPT-tdEV. In conclusion, contrast maximization is effective even though it does not utilize domain knowledge.

Flow-based immunomagnetic enrichment of circulating tumor cells from diagnostic leukapheresis product.

The clinical utility of circulating tumor cells (CTCs) is hampered by the low number of cells detected. Diagnostic leukapheresis (DLA) offers a solution but, due to the observed non-specific binding and clumping, processing of DLA samples using the CellSearch system only allows for the processing of aliquots consisting of ~ 2% of the total DLA sample per test. Here, we introduce a flow enrichment target capture Halbach-array (FETCH)-based separation method in combination with a DNase preprocessing step to capture CTCs from larger fractions of DLA products without clumping. To evaluate the FETCH method, we processed peripheral blood samples from 19 metastatic castration-naïve prostate cancer (mCNPC) patients with CellSearch, and processed 2% aliquots of leukapheresis samples from the same patients with CellSearch as well as FETCH with or without DNase preprocessing. Using 2% aliquots from six patients, the use of FETCH with fewer immunomagnetic epithelial cellular adhesion molecule (EpCAM) conjugated ferrofluids was tested, whereas 20% aliquots from four patients were used to evaluate the processing of 10-fold larger DLA samples using FETCH. Results show that the cell clumping normally seen after immunomagnetic enrichment of DLA material was greatly reduced with the use of DNase pretreatment, while the number of CTCs detected was not affected. The number of CTCs detected in 2% aliquots of DLA using FETCH was unchanged compared to CellSearch and did not decrease when using down to 10% of the volume of immunomagnetic anti-EpCAM ferrofluids normally used in a CellSearch test, whereas the number of co-enriched white blood cells reduced a median 3.2-fold. Processing of a 20% aliquot of DLA with FETCH resulted in a 14-fold increase in CTCs compared to the processing of 2% aliquots of DLA using CellSearch and a total 42-fold median increase in CTCs compared to peripheral-blood CellSearch.

Ultra-sensitive CTC-based liquid biopsy for pancreatic cancer enabled by large blood volume analysis.

The limited sensitivity of circulating tumor cell (CTC) detection in pancreatic adenocarcinoma (PDAC) stems from their extremely low concentration in the whole circulating blood, necessitating enhanced detection methodologies. This study sought to amplify assay-sensitivity by employing diagnostic leukapheresis (DLA) to screen large blood volumes. Sixty patients were subjected to DLA, with a median processed blood volume of ~ 2.8 L and approximately 5% of the resulting DLA-product analyzed using CellSearch (CS). Notably, DLA significantly increased CS-CTC detection to 44% in M0-patients and 74% in M1-patients, yielding a 60-fold increase in CS-CTC enumeration. DLA also provided sufficient CS-CTCs for genomic profiling, thereby delivering additional genomic information compared to tissue biopsy samples. DLA CS-CTCs exhibited a pronounced negative prognostic impact on overall survival (OS), evidenced by a reduction in OS from 28.6 to 8.5 months (univariate: p = 0.002; multivariable: p = 0.043). Additionally, a marked enhancement in sensitivity was achieved (by around 3-4-times) compared to peripheral blood (PB) samples, with positive predictive values for OS being preserved at around 90%. Prognostic relevance of CS-CTCs in PDAC was further validated in PB-samples from 228 PDAC patients, consolidating the established association between CTC-presence and reduced OS (8.5 vs. 19.0 months, p < 0.001). In conclusion, DLA-derived CS-CTCs may serve as a viable tool for identifying high-risk PDAC-patients and aiding the optimization of multimodal treatment strategies. Moreover, DLA enables comprehensive diagnostic profiling by providing ample CTC material, reinforcing its utility as a reliable liquid-biopsy approach. This high-volume liquid-biopsy strategy presents a potential pathway for enhancing clinical management in this malignancy.

Improved enrichment of circulating tumor cells from diagnostic leukapheresis product.

The median number of circulating tumor cells (CTCs) detected in 7.5 mL of peripheral blood by CellSearch (PB-CS) in patients with metastatic prostate cancer is in the order of 1-10, which means many samples have insufficient tumor cells for comprehensive characterization. A significant increase is obtained through diagnostic leukapheresis (DLA), however, only 2%-3% of the DLA product can be processed per CellSearch test, limiting the gain. We processed aliquots from 30 DLA products of metastatic prostate cancer patients consisting of 0.2 × 109 leukocytes using CellSearch (DLA-CS) as well as the newly introduced reduced enrichment reagent protocol (RER), which uses 10-fold less enrichment reagents than DLA-CS. The number of tumor cells and the total number of captured cells were determined using the CellTracks Analyzer. Additionally, for six DLA samples, a 1.0 × 109 leukocyte aliquot was processed (RER+), using twofold less enrichment reagents than DLA-CS. A median 2.7-fold reduction in leukocyte co-enrichment was found between DLA-CS and RER methods without any loss in tumor cell recovery (Wilcoxon Signed Ranks Test, p = 0.953). Using 1.0 × 109 leukocyte aliquots a fourfold increase in tumor cells was found compared to DLA-CS and a 19-fold increase compared to PB-CS was obtained. The here-introduced RER protocol results in a higher final sample purity without any loss in tumor cell recovery while using 10-fold less CellSearch capture reagent. With this improved method, 26% of the leukapheresis sample can now be processed using reagents from a single CellSearch test, enabling the obtainment of a sufficient number of CTCs for comprehensive characterization in most metastatic prostate cancer patients.

Tumor-Derived Extracellular Vesicles as Complementary Prognostic Factors to Circulating Tumor Cells in Metastatic Breast Cancer.

PURPOSE: Circulating tumor cells (CTCs) are strongly prognostic for overall survival (OS) in metastatic breast cancer although additional prognostic biomarkers are needed. We evaluated the complementary prognostic value of tumor-derived extracellular vesicles (tdEVs) next to CTCs. METHODS: We applied the open-source ACCEPT software to archived CellSearch images from the prospective clinical trial SWOG0500 to enumerate CTCs and tumor-derived extracellular vesicles (tdEVs) before and after one cycle of chemotherapy. RESULTS: CTCs enumerated by ACCEPT were strongly correlated with classical ocular enumeration (correlation r = 0.98). OS was worse with elevated tdEVs (median OS for high/medium/low groups: 17.1 v 29.0 v 43.3 months; P < .0001). In patients with longer OS by CTC counts (< 5 CTC/7.5 mL blood), elevated tdEV levels were independently associated with poorer OS (multivariable analysis P < .001). OS was also longer for patients with low tdEVs after one cycle of chemotherapy (median OS for high/medium/low group: 10.8 v 17.8 v 26.7; P < .0001). CONCLUSION: This study highlights the complementary prognostic significance of tdEVs in metastatic breast cancer before and after one cycle of chemotherapy.

Characterizing Circulating Tumor Cells and Tumor-Derived Extracellular Vesicles in Metastatic Castration-Naive and Castration-Resistant Prostate Cancer Patients.

Circulating tumor cell (CTC)- and/or tumor-derived extracellular vesicle (tdEV) loads in the blood of metastatic castration-resistant prostate cancer (CRPC) patients are associated with worse overall survival and can be used as predictive markers of treatment response. In this study, we investigated the quantity/quality of CTCs and tdEVs in metastatic castration-naive prostate cancer (CNPC) and CRPC patients, and whether androgen deprivation therapy (ADT) affects CTCs and tdEVs. We included 104 CNPC patients before ADT initiation and 66 CRPC patients. Blood samples from 31/104 CNPC patients were obtained 6 months after ADT. CTCs and tdEVs were identified using ACCEPT software. Based on the morphology, CTCs of metastatic CNPC and CRPC patients were subdivided by manual reviewing into six subclasses. The numbers of CTCs and tdEVs were correlated in both CNPC and CRPC patients, and both CTCs (p = 0.013) and tdEVs (p = 0.005) were significantly lower in CNPC compared to CRPC patients. Qualitative differences in CTCs were observed: CTC clusters (p = 0.006) and heterogeneously CK expressing CTCs (p = 0.041) were significantly lower in CNPC patients. CTC/tdEV numbers declined 6 months after ADT. Our study showed that next to CTC-load, qualitative CTC analysis and tdEV-load may be useful in CNPC patients.

StarDist Image Segmentation Improves Circulating Tumor Cell Detection.

After a CellSearch-processed circulating tumor cell (CTC) sample is imaged, a segmentation algorithm selects nucleic acid positive (DAPI+), cytokeratin-phycoerythrin expressing (CK-PE+) events for further review by an operator. Failures in this segmentation can result in missed CTCs. The CellSearch segmentation algorithm was not designed to handle samples with high cell density, such as diagnostic leukapheresis (DLA) samples. Here, we evaluate deep-learning-based segmentation method StarDist as an alternative to the CellSearch segmentation. CellSearch image archives from 533 whole blood samples and 601 DLA samples were segmented using CellSearch and StarDist and inspected visually. In 442 blood samples from cancer patients, StarDist segmented 99.95% of CTC segmented by CellSearch, produced good outlines for 98.3% of these CTC, and segmented 10% more CTC than CellSearch. Visual inspection of the segmentations of DLA images showed that StarDist continues to perform well when the cell density is very high, whereas CellSearch failed and generated extremely large segmentations (up to 52% of the sample surface). Moreover, in a detailed examination of seven DLA samples, StarDist segmented 20% more CTC than CellSearch. Segmentation is a critical first step for CTC enumeration in dense samples and StarDist segmentation convincingly outperformed CellSearch segmentation.

Platelet removal by single-step centrifugation.

The study of extracellular vesicles (EVs) in plasma requires removal of cells including platelets. At present, a two-step centrifugation protocol is recommended and commonly used. A simpler protocol that is less operator dependent is likely to improve the quality of plasma samples collected for EV research. The objective of this study is to develop an easy, fast and clinically applicable centrifugation protocol to produce essentially platelet-free plasma with a high yield for EV research. We compared the two-step centrifugation protocol to a single-step protocol at 5,000 g for 20 minutes. The removal of platelets was computationally predicted and experimentally validated. Flow cytometry was used to detect residual platelets and platelet-derived (CD61+) EVs. The single-step protocol at 5,000 g (i) is less laborious and approximately ten minutes faster, (ii) removes platelets as effective as the two-step centrifugation protocol, and (iii) has a ~ 10% higher plasma yield, whereas (iv) the recovery of platelet-derived EVs is comparable. For future research on plasma EVs we recommend the newly developed, easy and fast single-step protocol for preparation of platelet-free plasma for research on plasma biomarkers including EVs.

Endothelium-Derived Extracellular Vesicles Associate with Poor Prognosis in Metastatic Colorectal Cancer.

Elevated, tumor-derived extracellular vesicle (tdEV) and circulating tumor cell (CTC) loads in metastatic cancer are associated with poor clinical outcome. Herein, we investigate whether endothelium-derived extracellular vesicles (edEVs) can be detected in the blood of metastatic colorectal cancer (mCRC) patients, and whether those vesicles associate with prognosis. The open-source ACCEPT (Automated CTC Classification, Enumeration, and Phenotyping) software was used to enumerate edEVs, tdEVs, and other objects from digitally stored CellSearch images acquired after CTC and circulating endothelial cell (CEC) enrichment from the blood of 395 mCRC patients before the initiation of a new therapy. Patients had participated in the prospective phase III CAIRO2 study. The presence of edEVs was found 5- to 10-fold higher than CECs. The hazard ratio (HR) (95% CI) of progression-free survival (PFS) for increased CTCs (≥3 in 7.5 mL), tdEVs (≥40 in 7.5 mL), and edEVs (≥287 in 4.0 mL.) was 1.4 (1.1-1.9), 2.0 (1.5-2.6), and 1.7 (1.2-2.5), respectively. The HR of Overall Survival (OS) for increased CTCs, tdEVs and edEVs was 2.2 (1.7-3.0), 2.7 (2.0-3.5), and 2.1 (1.5-2.8), respectively. There was no cut-off value for CECs, leading to a dichotomization of patients with a significant HR. Only tdEVs remained a significant predictor of OS in the final multivariable model.

Rate zonal centrifugation can partially separate platelets from platelet-derived vesicles.

BACKGROUND: Centrifugation is commonly used as a first step to enrich biomarkers from blood. Biomarkers are separated on the basis of density and/or diameter. However, the centrifugation protocol affects the yield and purity of biomarkers, for example, isolation of platelets results in co-isolation with extracellular vesicles (EVs). OBJECTIVE: To assess the ability of rate zonal centrifugation (RZC) to separate platelets from co-isolated EVs. METHODS: Using a linear Optiprep gradient, RZC was able to separate a mixture of beads with different diameters but similar density. Next, RZC was applied to samples containing both platelets and platelet-derived EVs (n = 3). After RZC, all fractions were collected and stained with anti-CD61-Alexa 488 to measure the concentrations of platelets and platelet-derived EVs by flow cytometry. RESULTS: We confirm that RZC separates polystyrene beads with diameters of 140 nm, 380 nm and 1,000 nm. Next, we show that the majority of platelets occur in fractions 8-19, whereas the majority of platelet-derived EVs are detectable in fractions 1-7. Furthermore, each fraction contains a different diameter range of platelets, which suggests that separation is indeed diameter based. CONCLUSION: RZC can partially separate platelets from EVs.

Detection of extracellular vesicles in plasma and urine of prostate cancer patients by flow cytometry and surface plasmon resonance imaging.

Large (> 1 µm) tumor-derived extracellular vesicles (tdEVs) enriched from the cell fraction of centrifuged whole blood are prognostic in metastatic castration-resistant prostate cancer (mCRPC) patients. However, the highest concentration of tdEVs is expected in the cell-free plasma fraction. In this pilot study, we determine whether mCRPC patients can be discriminated from healthy controls based on detection of tdEVs (< 1µm, EpCAM+) and/or other EVs, in cell-free plasma and/or urine. The presence of marker+ EVs in plasma and urine samples from mCRPC patients (n = 5) and healthy controls (n = 5) was determined by flow cytometry (FCM) and surface plasmon resonance imaging (SPRi) using an antibody panel and lactadherin. For FCM, the concentrations of marker positive (+) particles and EVs (refractive index <1.42) were determined. Only the lactadherin+ particle and EV concentration in plasma measured by FCM differed significantly between patients and controls (p = 0.017). All other markers did not result in signals exceeding the background on both FCM and SPRi, or did not differ significantly between patients and controls. In conclusion, no difference was found between patients and controls based on the detection of tdEVs. For FCM, the measured sample volumes are too small to detect tdEVs. For SPRi, the concentration of tdEVs is probably too low to be detected. Thus, to detect tdEVs in cell-free plasma and/or urine, EV enrichment and/or concentration is required. Furthermore, we recommend testing other markers and/or a combination of markers to discriminate mCRPC patients from healthy controls.

A Systematic Approach to Improve Scatter Sensitivity of a Flow Cytometer for Detection of Extracellular Vesicles.

Extracellular vesicles (EVs) are commonly studied by flow cytometry. Due to their small size and low refractive index, the scatter intensity of most EVs is below the detection limit of common flow cytometers. Here, we aim to improve forward scatter (FSC) and side scatter (SSC) sensitivity of a common flow cytometer to detect single 100 nm EVs. The effects of the optical and fluidics configuration on scatter sensitivity of a FACSCanto (Becton Dickinson) were evaluated by the separation index (SI) and robust coefficient of variation (rCV) of polystyrene beads (BioCytex). Improvement is defined as increased SI and/or reduced rCV. Changing the obscuration bar improved the rCV 1.9-fold for FSC. A 10-fold increase in laser power improved the SI 19-fold for FSC and 4.4-fold for SSC, whereas the rCV worsened 0.8-fold and improved 1.5-fold, respectively. Confocalization worsened the SI 1.2-fold for FSC, and improved the SI 5.1-fold for SSC, while the rCV improved 1.1-fold and worsened 1.5-fold, respectively. Replacing the FSC photodiode with a photomultiplier tube improved the SI 66-fold and rCV 4.2-fold. A 2-fold reduction in sample stream width improved both SI and rCV for FSC by 1.8-fold, and for SSC by 1.3- and 2.2-fold, respectively. Decreasing the sample flow velocity worsened rCVs. Decreasing the flow channel dimensions and the pore size of the sheath filter did not substantially change the SI or rCV. Using the optimal optical configuration and fluidics settings, the SI improved 3.8∙104 -fold on FSC and 30-fold on SSC, resulting in estimated detection limits for EVs (assuming a refractive index of 1.40) of 246 and 91 nm on FSC and SSC, respectively. Although a 50-fold improvement on FSC is still necessary, these adaptions have produced an operator-friendly, high-throughput flow cytometer with a high sensitivity on both SSC and FSC. © 2020 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry.

Centrifugation affects the purity of liquid biopsy-based tumor biomarkers.

Biomarkers in the blood of cancer patients include circulating tumor cells (CTCs), tumor-educated platelets (TEPs), tumor-derived extracellular vesicles (tdEVs), EV-associated miRNA (EV-miRNA), and circulating cell-free DNA (ccfDNA). Because the size and density of biomarkers differ, blood is centrifuged to isolate or concentrate the biomarker of interest. Here, we applied a model to estimate the effect of centrifugation on the purity of a biomarker according to published protocols. The model is based on the Stokes equation and was validated using polystyrene beads in buffer and plasma. Next, the model was applied to predict the biomarker behavior during centrifugation. The result was expressed as the recovery of CTCs, TEPs, tdEVs in three size ranges (1-8, 0.2-1, and 0.05-0.2 µm), EV-miRNA, and ccfDNA. Bead recovery was predicted with errors <18%. Most notable cofounders are the 22% contamination of 1-8 µm tdEVs for TEPs and the 8-82% contamination of <1 µm tdEVs for ccfDNA. A Stokes model can predict biomarker behavior in blood. None of the evaluated protocols produces a pure biomarker. Thus, care should be taken in the interpretation of obtained results, as, for example, results from TEPs may originate from co-isolated large tdEVs and ccfDNA may originate from DNA enclosed in <1 µm tdEVs. © 2018 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry.

Deriving Extracellular Vesicle Size From Scatter Intensities Measured by Flow Cytometry.

Flow cytometry is commonly used to investigate the potential for extracellular vesicles (EVs) to be biomarkers of disease. A typical flow cytometer detects fluorescence and scatter intensities of single EVs in arbitrary units. These arbitrary units complicate data interpretation and data comparison between different flow cytometers. For example, comparison of detected EV concentrations requires knowledge of the detectable EV sizes. Using Mie theory and knowledge of the optical configuration of the flow cytometer, EV size can be derived from the scatter intensity for a given EV refractive index. Here, a protocol is described to derive the size of EVs and other nanoparticles from the scatter intensity. The resulting size distribution allows the comparison of data between flow cytometers, which is a prerequisite for clinical application of EVs as biomarkers and may advance other fields where sizing of nanoparticles is essential. © 2018 by John Wiley & Sons, Inc.

Label-Free Prostate Cancer Detection by Characterization of Extracellular Vesicles Using Raman Spectroscopy.

Mammalian cells release extracellular vesicles (EVs) into their microenvironment that travel the entire body along the stream of bodily fluids. EVs contain a wide range of biomolecules. The transported cargo varies depending on the EV origin. Knowledge of the origin and chemical composition of EVs can potentially be used as a biomarker to detect, stage, and monitor diseases. In this paper, we demonstrate the potential of EVs as a prostate cancer biomarker. A Raman optical tweezer was employed to obtain Raman signatures from four types of EV samples, which were red blood cell- and platelet-derived EVs of healthy donors and the prostate cancer cell lines- (PC3 and LNCaP) derived EVs. EVs' Raman spectra could be clearly separated/classified into distinct groups using principal component analysis (PCA) which permits the discrimination of the investigated EV subtypes. These findings may provide new methodology to detect and monitor early stage cancer.

Circulating tumor cells, tumor-derived extracellular vesicles and plasma cytokeratins in castration-resistant prostate cancer patients.

PURPOSE: The presence of Circulating Tumor Cells (CTCs) in Castration-Resistant Prostate Cancer (CRPC) patients is associated with poor prognosis. In this study, we evaluated the association of clinical outcome in 129 CRPC patients with CTCs, tumor-derived Extracellular Vesicles (tdEVs) and plasma levels of total (CK18) and caspase-cleaved cytokeratin 18 (ccCK18). EXPERIMENTAL DESIGN: CTCs and tdEVs were isolated with the CellSearch system and automatically enumerated. Cut-off values dichotomizing patients into favorable and unfavorable groups of overall survival were set on a retrospective data set of 84 patients and validated on a prospective data set of 45 patients. Plasma levels of CK18 and ccCK18 were assessed by ELISAs. RESULTS: CTCs, tdEVs and both cytokeratin plasma levels were significantly increased in CRPC patients compared to healthy donors (HDs). All biomarkers except for ccCK18 were prognostic showing a decreased median overall survival for the unfavorable groups of 9.2 vs 21.1, 8.1 vs 23.0 and 10.0 vs 21.5 months respectively. In multivariable Cox regression analysis, tdEVs remained significant. CONCLUSIONS: Automated CTC and tdEV enumeration allows fast and reliable scoring eliminating inter- and intra- operator variability. tdEVs provide similar prognostic information to CTC counts.

Comparison of Generic Fluorescent Markers for Detection of Extracellular Vesicles by Flow Cytometry.

BACKGROUND: Extracellular vesicles (EVs) in biofluids are potential biomarkers of disease. To explore the clinical relevance of EVs, a specific generic EV marker would be useful, one that does not require antibodies and binds to all EVs. Here we evaluated 5 commonly used generic markers for flow cytometry. METHODS: Flow cytometry (A60-Micro, Apogee) was used to evaluate the ability of the generic EV markers calcein acetoxymethyl ester, calcein acetoxymethyl ester violet, carboxyfluorescein succinimidyl ester (CFSE), 4-(2-[6-(dioctylamino)-2-naphthalenyl]ethenyl)-1-(3-sulfopropyl)pyridinium (di-8-ANEPPS), and lactadherin to stain EVs from MCF7 human breast adenocarcinoma cell line-conditioned culture medium [epithelial cell adhesion molecule positive (EpCAM+)] or platelet EVs from human plasma [integrin ß3 positive (CD61+)]. Side scatter triggering was applied as a reference, and the influence of non-EV components (proteins and lipoproteins) was evaluated. RESULTS: Di-8-ANEPPS, lactadherin, and side scatter detected 100% of EpCAM+ MCF7 EVs. Lactadherin and side scatter detected 33% and 61% of CD61+ EVs, respectively. Di-8-ANEPPS detected platelet EVs only if soluble protein was first removed. Because all generic markers stained proteins, at best 33% of platelet EVs in plasma were detected. The calcein markers and CFSE were either insensitive to EVs in both samples or associated with swarm detection. CONCLUSIONS: None of the generic markers detected all and only EVs in plasma. Side scatter triggering detected the highest concentration of plasma EVs on our A60-Micro, followed by lactadherin. The choice between scatter or lactadherin primarily depends on the analytical sensitivity of the flow cytometer used.

Absolute sizing and label-free identification of extracellular vesicles by flow cytometry.

Blood contains extracellular vesicles (EVs), which are biological nanoparticles with clinical applications. In blood plasma, EVs are outnumbered by similar-sized lipoprotein particles (LPs), leading to controversial data such as non-specific binding of antibodies to LPs. Flow cytometry is a clinically applicable technique to characterize single EVs in body fluids. However, flow cytometry data have arbitrary units, impeding standardization, data comparison, and data interpretation, such as differentiation between EVs and LPs. Here we present a new method, named flow cytometry scatter ratio (Flow-SR), to relate the ambiguous light scattering signals of flow cytometry to the diameter and refractive index (RI) of single nanoparticles between 200-500 nm in diameter. Flow-SR enables label-free differentiation between EVs and LPs and improves data interpretation and comparison. Because Flow-SR is easy to implement, widely applicable, and more accurate and faster than existing techniques to size nanoparticles in suspension, Flow-SR has numerous applications in nanomedicine.

Surface Plasmon Resonance is an Analytically Sensitive Method for Antigen Profiling of Extracellular Vesicles.

BACKGROUND: Identification, enumeration, and characterization of extracellular vesicles (EVs) are hampered by the small size of EVs, a low refractive index, and low numbers of antigens on their surface. METHODS: We investigated the potential of a 48-multiplex surface plasmon resonance imaging (SPRi) system to perform EV phenotyping. Antigen surface density of 11 antigens was measured on the human breast cancer cell lines HS578T, MCF7, and SKBR3 and their EVs by use of both SPRi and the widely used flow cytometry (FCM). RESULTS: For cells, the SPRi and FCM signals for antigen exposure correlated (RHS578T cells2 = 0.66, RMCF7 cells2 = 0.78, RSKBR3 cells2 = 0.60). With regard to EVs, SPRi detected 31 out of 33 tested antibody-EV pairs, whereas our flow cytometer detected 5 antibody-EV pairs because of high blank and isotype control signals. For HS578T-derived EVs, the SPRi and FCM signals correlated (R2HS578T EVs = 0.98). However, on MCF7- and SKBR3-derived EVs, insufficient antigens were detected by our flow cytometer. To confirm that the SPRi responses correlated with mean antigen density on EVs, the SPRi responses of EVs were correlated with antigen density on parental cells as measured by FCM (RHS578T2 = 0.77, RMCF72 = 0.49, RSKBR32 = 0.52). CONCLUSIONS: SPRi responses correlate with mean antigen density. Moreover, SPRi detects lower antigen-exposure levels than FCM because SPRi measures an ensemble of EVs binding to the sensor surface, whereas FCM detects antigens of single EV.