| Literature DB >> 28436447 |
Li-Guo Liang1,2,3, Meng-Qi Kong1,2,3, Sherry Zhou4, Ye-Feng Sheng1,2,3, Ping Wang5, Tao Yu1,2,3, Fatih Inci4, Winston Patrick Kuo6,7, Lan-Juan Li1,2, Utkan Demirci4,8, ShuQi Wang1,2,3,4.
Abstract
Extracellular vesicles (EVs), including exosomes and microvesicles, are present in a variety of bodily fluids, and the concentration of these sub-cellular vesicles and their associated biomarkers (proteins, nucleic acids, and lipids) can be used to aid clinical diagnosis. Although ultracentrifugation is commonly used for isolation of EVs, it is highly time-consuming, labor-intensive and instrument-dependent for both research laboratories and clinical settings. Here, we developed an integrated double-filtration microfluidic device that isolated and enriched EVs with a size range of 30-200 nm from urine, and subsequently quantified the EVs via a microchip ELISA. Our results showed that the concentration of urinary EVs was significantly elevated in bladder cancer patients (n = 16) compared to healthy controls (n = 8). Receiver operating characteristic (ROC) analysis demonstrated that this integrated EV double-filtration device had a sensitivity of 81.3% at a specificity of 90% (16 bladder cancer patients and 8 healthy controls). Thus, this integrated device has great potential to be used in conjunction with urine cytology and cystoscopy to improve clinical diagnosis of bladder cancer in clinics and at point-of-care (POC) settings.Entities:
Mesh:
Year: 2017 PMID: 28436447 PMCID: PMC5402302 DOI: 10.1038/srep46224
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Figure 1Isolation and detection of EVs from urine using an integrated double-filtration microfluidic device.
(A) Schematic of a double-filtration microfluidic device for isolation and detection of EVs. Based on size-exclusion, particles larger than 200 nm are excluded by the membrane with a pore size of 200 nm in the sample chamber, whereas particles smaller than 30 nm pass through the double-filtration device. EVs with a size between 30 and 200 nm are isolated and enriched in the isolation chamber. (B) Image of an assembled double-filtration device. (C) Schematic of direct ELISA for EV detection on-chip. The EVs isolated in the double-filtration device are labeled with biotinylated anti-CD63 antibodies, and then with streptavidin-HRP. Addition of TMB substrate enables blue color development in the double-filtration device. (D) The ELISA result is imaged using a smart phone and then transferred to a laptop for data analysis using ImageJ.
Figure 2Validation of size-exclusion for double-filtration devices.
(A) Schematic of Devices I and II to mimic the primary and secondary filtration process of the double-filtration device. A mixture of 500 and 100 nm FNPs was flowed through Device I (contained a 200 nm pore-sized membrane only). The filtrate collected from the waste chamber of Device I was then injected into Device II (contained a 30 nm pore-sized membrane only). The number of 500 and 100 nm FNPs collected from the filtrates was measured with the aid of a fluorescence microscope. (B) An scanning electron microscopy (SEM) image of a 200 nm pore-sized membrane (scale bar 1 μm). (C) An SEM image of a 30 nm pore-sized membrane (scale bar 1 μm). (D) A typical image of 500 nm and 100 nm FNPs. (E) Recovery rates of FNPs collected at the waste chambers of Devices I and II.
Figure 3Characterization of EVs isolated from urine using a double-filtration device.
(A) Size distribution of urinary EVs prior to double filtration. (B) Size distribution of urinary EVs after double filtration at a flow rate of 20, 30 or 40 μL/min. (C) EVs were stained with Alexa Fluo® 488-labeled anti-CD9 antibody, and then observed under a fluorescence microscope. Scale bar is 1 μm. (D) The morphology and size of EVs were observed under TEM. Scale bar is 100 nm. (E) Standard curve of the BCA method for protein quantification. (F) Quantification of EV-associated protein. EVs isolated from 8 mL of T24 cell culture media or 8 mL of urine collected from a healthy donor using ultracentrifugation were then flowed through double-filtration devices. The concentration of total protein before and after double filtration was quantified using the BCA method. A two-sided Student’s t-test was performed using SPSS V22. The asterisk (*) indicates statistical significance (p < 0.05).
Figure 4Development of microchip ELISA for detection of EVs.
(A) Standard curve of microplate ELISA for detection of EVs from cell culture. EVs were isolated from 8 mL of T24 cell media using ultracentrifugation and were 10-fold diluted. The lowest detection point was defined as 10 AU/mL. Side-view images of 96-well microplate ELISA were shown. (B) Detection of urinary EVs using microplate ELISA. EVs were isolated from 8 mL of urine from a healthy donor using ultracentrifugation and subsequently quantified using microplate ELISA. (C) Standard curve of microchip ELISA for detection of EVs, which were isolated from 8 mL of T24 cell media using ultracentrifugation. Images of microchip ELISA were presented for each standard concentration. (D) Comparison of isolation efficiency of EVs between ultracentrifugation and double-filtration. The concentration of EVs was quantified using microchip ELISA. A two-sided Student’s t-test was performed using SPSS V22. The asterisk (*) indicates statistical significance (p < 0.05).
Figure 5Clinical validation of urinary EVs for differentiating bladder cancer patients from healthy individuals.
(A) EVs were isolated and enriched from urine samples collected from bladder cancer patients (n = 16) and healthy controls (n = 8), and subsequently tested using microchip ELISA. The log-transformed EV concentrations in bladder cancer patients and healthy controls were compared in a box-plot. A two-sided Student’s t-test was used to analyze the statistical difference between the two groups. The asterisk (*) indicates statistical significance (p < 0.05). (B) Receiver operating characteristic (ROC) curve was plotted for assessment of sensitivity and specificity. The sensitivity, specificity and the area under ROC curve (AUROC) were analyzed using SPSS V22. The results demonstrated that this integrated EV double-filtration device had a sensitivity of 81.3% at a specificity of 90%.