Single-Exosome-Counting Immunoassays for Cancer Diagnostics

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Single-exosome-counting immunoassays for cancer diagnostics Chunchen Liu, Xiaonan Xu, Bo Li, Bo Situ, Weilun Pan, Yu Hu, Taixue An, Shuhuai Yao, and Lei Zheng Nano Lett., Just Accepted Manuscript • DOI: 10.1021/acs.nanolett.8b01184 • Publication Date (Web): 11 Jun 2018 Downloaded from http://pubs.acs.org on June 11, 2018

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Single-exosome-counting immunoassays for cancer

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diagnostics

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Chunchen Liu123‡, Xiaonan Xu3‡, Bo Li12, Bo Situ12, Weilun Pan12, Yu Hu3, Taixue An12, Shuhuai

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Yao3*, and Lei Zheng12*

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Guangzhou 510515, China

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Nanfang Hospital, Southern Medical University, Guangzhou 510515, China

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Department of Laboratory Medicine, Nanfang Hospital, Southern Medical University,

Guangdong Engineering and Technology Research Center for Rapid Diagnostic Biosensors,

Department of Mechanical and Aerospace Engineering, The Hong Kong University of Science

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and Technology, Hong Kong, China

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KEYWORDS: droplet microfluidics, exosomes, droplet digital ExoELISA, cancer diagnostics

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ABSTRACT

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Exosomes shed by tumor cells have been recognized as promising biomarkers for cancer

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diagnostics due to their unique composition and functions. Quantification of low concentrations

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of specific exosomes present in very small volumes of clinical samples may be used for non-

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invasive cancer diagnosis and prognosis. We developed an immunosorbent assay for digital

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qualification of target exosomes using droplet microfluidics. The exosomes were immobilized

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on magnetic mircobeads through sandwich ELISA complexes tagged with an enzymatic reporter

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that produces a fluorescent signal. The constructed beads were further isolated and encapsulated

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into a sufficient number of droplets to ensure only a single bead was encapsulated in a droplet.

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Our droplet-based single-exosome-counting enzyme-linked immunoassay (droplet digital

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ExoELISA) approach enables absolute counting of cancer-specific exosomes to achieve

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unprecedented accuracy. We were able to achieve a limit of detection (LOD) down to 10

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enzyme-labeled exosome complexes per microliter (~10−17 M). We demonstrated the application

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of the droplet digital ExoELISA platform in quantitative detection of exosomes in plasma

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samples directly from breast cancer patients. We believe our approach may have the potential for

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early diagnosis of cancer and accelerate the discovery of cancer exosomal biomarkers for clinical

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diagnosis.

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Exosomes are extracellular vesicles of 30-150 nm in size that are derived from eukaryotic cells

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that circulate in body fluids.1,2 They carry numerous molecular information like proteins and

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nucleic acids from the parent cells and therefore play a vital role for intercellular

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communication.3,4 In the last decade, accumulated evidence has indicated that the exosome

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molecular cargo shed from tumor tissues can be identified as potential non-invasive biomarkers

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for cancer diagnosis because it reflects the genetic or signaling alterations of the parent tumors.5-9

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For instance, Glypican-1 (GPC-1), an exosomal membrane protein, was discovered to have much

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higher expression on the cancerous exosomes than the noncancerous by immunoblotting

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analysis,10 revealing its clinical value as an exosomal biomarker for the early diagnosis of

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pancreatic, breast and colorectal cancer.11-13

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Exosomes secreted by nucleated cells are widely present in human bio-fluids14,15 and there

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exists various exosome subpopulations. Recently, the subpopulation of tumor-derived exosomes


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is found to be valuable for clinical diagnostics. To accurately quantify and classify the tumor-

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derived exosomes from bio-fluids is potentially significant for cancer diagnostics, prognosis, and

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monitoring the response of therapy. Conventional methods such as nanoparticle tracking analysis

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(NTA), western blot, ELISA, and flow cytometry have been widely adopted in research labs for

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exosome quantity measurement.16-18 However, NTA only provides an estimated number of

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exosomes at a high concentration level (1×107-109 particles/mL) and lacks specificity.19 Western

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blot, ELISA and flow cytometry all require large amounts of sample input and have limited

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sensitivity.20,21 Unfortunately, in the early stage of cancer, limited tumor-derived exosomes in

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peripheral blood circulation can hardly be detected with these conventional quantification

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methods. Many efforts have been made by researchers to improve the sensitivity of the detection

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methods, including miniaturized microfluidic platforms,22-25 aptamer-based electrochemical

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sensors,26-29 surface plasmon resonance (SPR)30,31 and Raman scattering32,33 However, these

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detection methods are performed in a bulk solution, which hardly enables absolute quantification

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or classification. As the cancer biomarkers that present in the early stage in liquid biopsy are at

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low concentrations in the range of 10–12–10–16 M,34 to quantitate such low abundance markers,

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the required sensitivity for detection needs to be at the single molecule level.35-37 Recently, single

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extracellular vesicle analysis (SEA), based on photon counting techniques, has been applied for

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multiplexed profiling of single extracellular vesicles using ELISA.38 Careful buffer washing and

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complex imaging procedures are required to differentiate single vesicles from protein complexes

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or other clusters due to their low signal-to-noise ratios, and the detection limit is still quite high

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(e.g., with an intensity cutoff of 102 counts).38 Nevertheless, these methods are still impractical

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for wide adoption due to the throughput and cost. Reliable platforms for quantification of

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exosomes with high sensitivity and specificity are still lacking.


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In recent years, digital PCR and digital ELISA platforms have revolutionized detection

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technologies for absolute quantification of nucleic acids and proteins.39-41 In contrast to the

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conventional biological and chemical assays conducted in large volumes, in pipettes, beakers,

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tubes or flasks, the basic principle of digital quantification of molecules is to divide the sample

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uniformly into a large quantity of small compartments (either in microwells or in droplets).42,43

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By doing so, an individual molecule is confined in a small volume where the signal can be

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amplified and concentrated for detection.44 Compartmentalization technology that ensures the

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isolation of molecules in each compartment to follow the Poisson distribution is the core to the

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success of digital quantification.45,46 Droplet microfluidics that generates uniform droplets at the

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pico- to nanoliter scale in high throughput (in kHz) has enabled numerous single-molecule

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assays to be performed in parallel.47,48 In recent years, there has been tremendous progress in the

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development of droplet-based platforms for the formation and manipulation of monodispersed

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droplets and the associated use of a range of fluorescence-based techniques for high-throughput

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and highly sensitive analysis of droplet content.49

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In this letter, we develop a droplet-based single-exosome-counting immunoassay approach for

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digital quantification of exosomes. Exosome enzyme-linked immunosorbent assay (ExoELISA)

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is adopted to identify the exosomes with target membrane protein biomarkers. We named this

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method as droplet digital ExoELISA, the procedure of which is illustrated in Figure 1: Magnetic

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beads serve as a medium for capture and separation of the target exosomes. First, the exosome

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suspension is mixed with a sufficient number of magnetic beads conjugated with capture

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antibodies that can selectively bind a specific protein on the exosome membrane. After effective

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magnetic separation and washing, one target exosome is immobilized and captured onto a

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magnetic bead. A detection antibody tagged with an enzymatic reporter further recognizes the


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antigen on the captured exosome, forming a single enzyme-linked immunocomplex on the bead

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(Figure 1a). Second, the prepared beads and the enzymatic substrate are co-encapsulated into a

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sufficient number of microdroplets to ensure that a majority of droplets contain no more than one

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bead, using a microfluidic chip (Figure 1b, c). Third, for those droplets that contain the beads

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with exosome immunocomplex, the substrate is catalyzed by the enzyme to emit fluorescein

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within the droplets (Figure 1d). Based on the statistics of the fluorescent droplets, the target

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exosome concentration can be calculated. We have demonstrated that the droplet digital

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ExoELISA approach is able to detect as few as ~5 exosomes per µL. Other than high sensitivity,

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the droplet digital ExoELISA offers high specificity and absolute quantification for targeting

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exosomes with specific protein biomarkers. For clinical demonstration, we quantified the GPC-

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1(+) exosomes from breast cancer patients and the results yielded distinct GPC-1(+) expression

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level before and after surgery, suggesting the great potential of the droplet digital ExoELISA

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platform for cancer diagnostics.

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Figure 1. Schematic showing the droplet digital ExoELISA for exosome quantification. (a)


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Single exosome immunocomplex constructed on a magnetic bead. (b) Substrate and beads are

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co-encapsulated into microdroplets. (c) Droplet digital ExoELISA chip. (d) Fluorescent readout

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for counting the positive droplets with the target exosomes.

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Exosomes were purified and isolated from a breast tumor cell line (MDA-MB-231) by

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multiple steps of ultracentrifugation following our previous work.50 Standard characterization of

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exosomes was performed using transmission electron microscopy (TEM), NTA and western blot,

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respectively. As shown in Figure 2a, the TEM image revealed the lipid bilayer structure

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remained intact on the purified exosomes after ultracentrifugation and the size of the exosomes

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ranged from 50 nm to 150 nm in diameter. With NTA analysis, we obtained the size distribution

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and concentration of the exosomes (Figure 2b). The prepared exosomes had an average size of

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104.2 ± 3.9 nm in diameter and the corresponding concentration was 6.39×108 ± 4.90×106

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particles per mL. In our experiments, CD63 protein, a member of the transmembrane 4

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superfamily, was selected as the protein biomarker for capturing exosomes because CD63 is the

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exosome-enriched protein located on the membrane and, according to the literature, is commonly

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used for exosome capture.51,52 We performed the western blot analysis, which showed the

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exosomal marker CD63 on the exosomes isolated from the MDA-MB-231 culture media was

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consistent with the CD63 protein extracted from the same cell line as a positive control, clearly

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indicating the existence of CD63 on these samples (Figure 2c, top row). Also, we used a dual-

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color super resolution microscopy to confirm the localization of CD63 on the exosome

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membrane (Figure S1a-c). We selected GPC-1 protein as the breast cancer reporter in our

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experiments as it has already been reported for breast cancer detection.12 The high expression of

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GPC-1 on exosomes from the MDA-MB-231 cell line and the location of GPC-1 on exosome

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membranes was confirmed by western bolt analysis (Figure 2c, bottom row) and the dual-color


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super resolution microscopy (Figure S1d-f). Thus, the isolated breast cancer exosomes can be

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further used for the construction of exosome immunocomplexes on magnetic beads using

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ExoELISA.

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Figure 2. Characterization of exosomes. (a) TEM shows exosomes with double-wall lipid

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membrane layers ranging approximately 30-150 nm in diameter. (b) size distribution of MDA-

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MB-231 exosomes by NTA analysis. Red band depicts three repetitive experiments. (c) The

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expression of CD63 (the exosomal marker) and GPC-1 (the diagnostic marker) in MDA-MB-231

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exosomes and parent cells by western blot analysis. Equal amounts of proteins (20 µg) in

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exosomes and cells were loaded.

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Inspired by the magnetic bead based digital ELISA for the single molecule quantification of

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proteins.40,41 we developed the protocol to construct single exosome immunocomplexes on

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beads. We first prepared magnetic beads conjugated with CD63 antibody. The functionalized

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beads were then used for capturing exosomes. The probability of the number of exosomes


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binding on one bead follows the Poisson statistics.53 that is, when the mean number of exosomes

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captured by each bead is smaller than 0.1, most beads (> 99.53%) capture at most one target

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exosome.54 Therefore, in our experiments we input 10x more beads than the expected exosomes

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to ensure single-exosome capture. To prove the successful capture of exosomes via CD63

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antibody-antigen binding on beads, we carried out the TEM experiments for validation. The

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magnetic beads coated with CD63 capture antibody were exposed to two samples: one with

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MDA-MB-231 exosomes and the other without exosomes as the control group. Figure S2a

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shows a bare bead without exosomes on the surface while Figure S2b clearly shows that one

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exosome was constructed on a magnetic bead. These results demonstrated that the functionalized

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magnetic beads were able to bind the exosomes specifically in a single complex through

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ExoELISA. After single exosomes were captured on beads, we used anti-GPC-1, previously

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biotinylated with a biotin tag, as the detection antibody to bind GPC-1 protein marker on the

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membranes of the target exosomes. After forming immunocomplex on the beads, the detection

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antibody was further conjugated with an enzymatic reporter, β-Galactosidase, which catalyzes

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the fluorescein-di-β-D-galactopyranoside (FDG) substrate to produce a fluorescent signal for

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detection in the droplet microfluidic system.

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A flow-focusing droplet generation device with two sample inlets for the prepared bead sample

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and FDG substrate solutions respectively40 was used to generate droplets of 40 µm diameter in

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mineral oil (Figure 3a). Likewise, the encapsulation of beads in microdroplets is also based on

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the Poisson distribution. In our experimental protocol, we set the mean number of beads per

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droplet < 0.3 to ensure most droplets contain none or one bead (see captured bright images of

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bead-encapsulated droplet arrays as examples in Figure S3). Importantly, the positive droplets

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that contain at least one target exosomes can be calculated accordingly to the target molecule to


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magnetic bead ratio and the magnetic bead to droplet ratio following the analysis of two

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dependent Poisson distribution.54 In our experiments, we set both ratios sufficiently low to allow

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a linear dynamic range of Poisson statistics for counting the target exosomes. That is, in our

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droplet assays, almost all positive droplets only contained one target exosome. Therefore, direct

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“digital” counting of target exosomes was made feasible by simply counting the fluorescent

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droplets without the need of highly sensitive detection methods or complicated image processing

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for measuring the real number of the magnetic beads.

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The produced droplets were spread in the droplet storage chamber in a single layer

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configuration and incubated before observation. We observed that the florescence signal rising

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time took a few minutes which suggested the effect of premixing in microchannels prior to

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droplet generation was negligible. The FDG catalysis reaction was investigated to optimize the

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assay incubation time (Figure S4). In the current device, 30 mins was chosen as the optimal

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incubation time for 40 µm diameter droplets, but a shorter time may be feasible if using smaller

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droplets. The end point counting of the fluorescent droplets (positive copies) was conducted once

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the incubation was completed. The number of fluorescent droplets represented the number of

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target exosomes.

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We calibrated our droplet digital ExoELISA assays using the MDA-MB-231 exosomes

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mentioned above. We conducted a 10-fold serial dilution of the sample with an initial

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concentration of 6.39×108 exosomes per mL. The results are shown in Figure 3b. The detected

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GPC-1 exosomes were in an excellent linearity with the total particles measured in NanoSight.

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The error bars represent the standard deviation of three repeated experiments. Due to the

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picolitre droplet size, the LOD of our droplet digital ExoELISA, determined by the background

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(negative control) signal plus 3 times of standard deviation (SD) of the background signal, was


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approximately 10 exosomes/µL. Compared with the reported methods for detection of exosomes

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(Table S1), our method achieved the lowest LOD. Since in sample discretization we input a

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sufficient quantity of beads to mix with exosomes and compartmentalize the beads into a

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sufficient number of droplets, in most measurements, we were able to achieve one fluorescent

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droplet representing one target exosome with over 99% confidence. Figure 3c shows the

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background of the assay, possibly caused by non-specific binding to the surface of the beads or

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carry-through of free reporter enzymes into the encapsulated droplets, as suggested by previous

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reports.40,54 Therefore, special surface treatment and more effective washing steps may be needed

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to further improve the accuracy of our approach.55 Figure 3 (d-h) are the images of the

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fluorescent droplets in the chamber by taking the 10-fold serial dilution. It is noted that among

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the fluorescent droplets, some droplets emitted stronger fluorescence signals than others. The

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variations could be due to various expressions of GPC-1 on a single exosome or the

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heterogeneous nature of single-enzyme catalysis.56 In our experiments, one million droplets were

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generated and the dynamic range allowed to reach the range of 5log of the linear regime. The

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dynamic range can be further extended by employing the two dependent Poisson statistics.41,54


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Figure 3. (a) Prepared beads and FDG substrate are co-encapsulated into 40 µm diameter

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droplets which spread in one layer in the device for detection. (b) Droplet digital ExoELISA

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calibration results showing the dynamic range of the captured exosomes spans 5 orders of

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magnitude. Dashed line is the background plus 3 times of standard deviation indicating the LOD

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(~10 exosomes/µL). (c) Negative control without target exosomes. (d-h) gradient of the

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fluorescence readout by serial dilution of the exosome sample isolated from MDA-MB-231.

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NanoSight was used as a benchmark measurement for the exosome number concentration.

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The variety of exosome subpopulation protein biomarkers significantly complicate exosome

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counting. The differentiation of exosome subpopulations in our approach is based on

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immunoassay, which possesses excellent specificity. To check the specificity of GPC-1(+)

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exosome detection in breast cancer exosomes (MDA-MB-231 exo), we performed control

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experiments using three kinds of non-cancerous exosomes including human normal liver


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exosomes (HL-7702 exo), mouse normal macrophage exosomes (RAW264.7 exo), and human

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embryonic stem exosomes (hES exo). We first used western blot analysis to identify the

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expression levels of GPC-1 in MDA-MB-231 exo, HL-7702 exo, RAW264.7 exo, and hES exo,

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and found that the expression of GPC-1 in MDA-MB-231 exo was slightly higher than the other

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three groups (Figure 4a). Due to the limited detection capacity of western blot, if the sample

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contains a small amount of GPC-1(+) exosomes, other proteins on the exosomes in the sample

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may interfere with the GPC-1(+) in western blot analysis. Moreover, the western blot analysis

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can only qualitatively indicate whether GPC-1 is expressed in the sample as it cannot measure

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the specific number of GPC-1(+) exosomes. Next, we investigated the specificity of our droplet

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digital ExoELISA for GPC-1(+) exosome detection among the four chosen exosomes and two

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negative controls: a sample using magnetic beads without CD63 Ab and a sample with no

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exosomes (Figure 4b). Before the experiments, NTA analysis was used to estimate the exosome

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number concentrations. The measured values were 4.22×108, 2.86×108, and 2.85×108 particles

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per mL for HL-7702 exo, RAW264.7 exo, and hES exo, respectively (Figure S5a-c). After

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proper dilution, each sample contained 6.39×104 exosomes per µL. Among these samples, only

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MDA-MB-231 exo showed significantly high number of GPC-1(+) exosomes (40141 exosomes

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per µL). For the negative control cases, we consistently observed very few fluorescent droplets

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per experiment (~5 detectable copies per µL), confirming the background of our assay is mainly

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due to the low enzyme non-specific binding to the magnetic beads.40,54


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Figure 4. Specificity of the assay. (a) Western blot analysis showing different expressions of

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GPC-1 in MDA-MB-231 cells (positive control) and exosomes isolated from MDA-MB-231,

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HL-7702, RAW264.7, and hES cell culture media. Each lane was loaded with 20 µg proteins. (b)

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The specificity of the droplet digital ExoELISA with exosomes isolated from MDA-MB-231,

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HL-7702, RAW264.7, and hES cell culture media. Cases of the magnetic beads without CD63

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Ab and detection sample solution without exosomes served as the negative controls. Each sample

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solution contained 6.39×104 exosome particles per µL.

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To demonstrate a clinically relevant application of our approach, we performed the droplet

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digital ExoELISA for detection of GPC-1(+) exosomes using clinical samples from serum of 5

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healthy sample (HS), 5 patients with benign breast disease (BBD), 12 patients with breast cancer

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(BC), and 2 patients with breast cancer after surgery (BC-AS) (Figure 5). Serum samples

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obtained from HS were used as the control for this study. According to previous reports,10,57

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there are about 0.3%-4.7% (average of 2.3%) GPC-1(+) exosomes even in healthy human serum

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samples, and around 109 vesicles per mL in blood. Figure 5a shows that there was an average of

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5448 GPC-1(+) exosomes per microliter in HS and similar GPC-1(+) exosomes (~6914


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exosomes/µL) in BBD, while the average GPC-1(+) exosomes in the BC group increased by five

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to seven folds. Our data were in great concordance with the previously published data,12

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revealing that the expression of GPC-1 significantly increased on tumor-derived exosomes as

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compared to the normal and benign breast disease samples. The increase may be a result of a

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higher level of GPC-1(+) exosomes shed by tumor cells than normal cells. Figure 5b shows that

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the BC patients overexpressed GPC-1(+) exosomes and can be well discriminated from the HS

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and BBD groups (p < 0.0001). Notably, for BC1-AS and BC2-AS, two samples of patients BC1

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and BC2 after surgery, the measured values of GPC-1(+) exosomes in BC1-AS and BC2-AS

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were significantly lower than BC1 and BC2 (Figure 5c), respectively, but relatively higher than

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HS and BBD (Figure 5a). Therefore, these data not only verified the GPC-1 can be regarded as

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an exosomal biomarker to distinguish non-BC subjects from patients with breast cancer, but also

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suggested that our method may be suitable for detection of GPC-1(+) exosomes for pre- and

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post-surgical monitoring. Our droplet digital ExoELISA has been demonstrated as a reliable

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method for quantifying target exosomes from HS, BBD, and BC-AC from BC clinical samples,

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however, in current studies, we have not maximized the superior sensitivity of our approach

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because of the relatively high baseline value of GPC-1(+) exosomes (~5448 exosomes/µL) in

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HS. It is worth mentioning that in the early stage of the diseases (especially cancer), where some

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exosome subpopulations only secreted by tumor cells are extremely small, our approach can be

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more suitable for detecting the extremely low abundance exosomes than other reported methods

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(Table S1). Therefore, our approach is promising for early cancer diagnostics and post-surgical

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monitoring in clinical research.


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Figure 5. Clinical analyses of GPC-1(+) exosomes by droplet digital ExoELISA. (a)

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Quantification of GPC-1(+) exosomes from serum samples of 5 healthy samples (HS), 5 patients

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with benign breast disease (BBD), 12 patients with breast cancer (BC). (b) Scattered dot plots

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show significant overexpression of GPC-1(+) exosomes of BC patients compared to HS and

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BBD (****, p < 0.0001). (c) Quantification of GPC-1(+) exosomes in 2 patients with breast

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cancer (BC) and breast cancer after surgery (BC-AS). Error bars represent the standard deviation

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of three independent experiments.

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In this study, to leverage the droplet microfluidics for single molecule/copy detection, we

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extended the standard ExoELISA techniques to detection of ultralow ambulance exosomes with

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specific target proteins. Our droplet digital ExoELISA method is able to achieve unprecedented

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accuracy and high specificity for exosome quantification, and has the potential to distinguish the

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target protein expression level on single exosomes through the fluorescence signal level in

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droplets. We demonstrated that our system detected the target exosomes in a dynamic range of

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5log and the detection limit can be as few as 10 exosomes per µL. The high specificity was also

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demonstrated by quantifying the exosomes with target GPC-1 biomarker from a variety of

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exosome subpopulation protein biomarkers. We successfully used this method for absolute

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quantification of exosomes in serum samples from breast cancer patients, manifesting the

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prospective clinical value of the droplet digital ExoELISA method that may propel the discovery

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of cancer exosomal biomarkers.

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AUTHOR INFORMATION

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Corresponding Author

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*E-mail: [email protected].


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*E-mail: [email protected].

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Author Contributions

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The manuscript was written through contributions of all authors. All authors have given approval

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to the final version of the manuscript. ‡These authors contributed equally.

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ACKNOWLEDGMENTS

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This study was supported by the Innovation and Technology Fund (ITS/224/16), the National

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Natural Science Foundation of China (81702100), the Science and Technology Program of

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Guangzhou (201510010097), the Major Program of Health Care and Innovation of Guangzhou

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Project (201704020213, 201604020015).

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Supporting Information

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The Supporting Information is available free of charge on the ACS Publications website at DOI:

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10.1021/xxxxxx.

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Details of Methods; Figures S1-S5: dual-color super-resolution images of fluorescence labelled

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exosomes; TEM images of an immunomagnetic captured single exosome; bright field images of

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beads in droplets; Incubation time optimization; NTA plots of exosomes isolated from HL-7702,

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RAW264.7, and hES cell culture media; Table S1: Comparison of current assays for detection of

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exosomes. (PDF)

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SYNOPSIS

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Single-Exosome-Counting Immunoassays for Cancer Diagnostics

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