Nanomaterials for Molecular Detection and Analysis of Extracellular Vesicles

Abstract

Extracellular vesicles (EVs) have emerged as a novel resource of biomarkers for cancer and certain other diseases. Probing EVs in body fluids has become of major interest in the past decade in the development of a new-generation liquid biopsy for cancer diagnosis and monitoring. However, sensitive and specific molecular detection and analysis are challenging, due to the small size of EVs, low amount of antigens on individual EVs, and the complex biofluid matrix. Nanomaterials have been widely used in the technological development of protein and nucleic acid-based EV detection and analysis, owing to the unique structure and functional properties of materials at the nanometer scale. In this review, we summarize various nanomaterial-based analytical technologies for molecular EV detection and analysis. We discuss these technologies based on the major types of nanomaterials, including plasmonic, fluorescent, magnetic, organic, carbon-based, and certain other nanostructures. For each type of nanomaterial, functional properties are briefly described, followed by the applications of the nanomaterials for EV biomarker detection, profiling, and analysis in terms of detection mechanisms.

Keywords: cancer; diagnostics; exosome; extracellular vesicle; molecular detection; nanomaterials.

Figure 8

Exosome detection with CNTs. (a) Schematic of a colorimetric aptasensor based on DNA−capped SWCNTs for exosome detection. Reprinted with permission from ref. [173]. Copyright@ 2017 Elsevier B.V. (b) Schematic of the detection mechanism of a MoS₂−MWCNT-based nanosensor for exosome detection and quantification. Reproduced from ref. [174] with permission from the Royal Society of Chemistry. (c) Schematic of the detection of exosomal miRNA21 using DNA-functionalized CNT FET biosensor. Reprinted with permission from [175]. Copyright {2021} American Chemical Society. (d) Schematic of an electrochemical aptasensor for the multiplexed detection of exosome biomarkers. Reprinted with permission from ref. [178]. Copyright@ 2017 Elsevier.

Figure 1

Overview of the application of nanomaterials and detection methods for extracellular vesicles. Abbreviation: NPs—nanoparticles, SPR—surface plasmon resonance, SERS—surface enhanced Raman scattering, µNMR: micro-nuclear magnetic resonance.

Figure 2

AuNP−amplified iNPS assay for the detection of intravesicular and transmembrane proteins. (a) Schematic of the methodology for EV protein detection. EVs are lysed to release proteins. Targeted proteins are captured on the iNPS chip via affinity ligands and detected by antibodies on AuNPs. (b) Scanning electron microscope image showing AuNPs on the iNPS sensor. (c) Finite difference time−domain (FDTD) simulation showing the concentration of the electrical fields on AuNPs. (d) Comparison of the signals with and without AuNPs on the iNPS sensor. (e) Protein profiling of EVs derived from ovarian cells. (f) Drug (HSP90 inhibitor) response monitoring of OV90 cells by EV protein detection with iNPS. The fold change is the protein level changes monitored by the iNPS spectral shifts after drug treatment. Reprinted with permission from [62]. Copyright (2018) American Chemical Society.

Figure 3

DISVT for surface protein detection of single EVs. (a) Schematic of the DISVT principle showing exosome capture with CD81 antibodies, membrane labeling with lipophilic Chol–PEG−Cy5, and surface protein labeling with antibody-conjugated AuNPs. (b) Optical properties of AuNPs and Chol–PEG−Cy5. (c) Fluorescence image of CD81−captured plasma EVs from a stage III HER2-positive breast cancer patient after dual labeling with Chol–PEG−Cy5 and HER2/AuNPs. (d) Dark field image of (c). (e) Superimposed image of (c) and (d) showing AuNP-bound EVs (overlapped red and yellow labels) and AuNP−free EVs (red labels only). (f) EV population density histogram showing the AuNP−bound EVs (blue peak) and AuNP−free EVs (orange peak). (g) EV population density histogram of EVs from a stage I HER2−positive breast cancer patient. (h) EV population density histogram of EVs from a stage III HER2−positive breast cancer patient. (i) Box plot showing the diagnostic potential of DISVT for early detection of HER2−positive breast cancer (n = 10 for each group). Reprinted with permission from [68]. Copyright (2023) American Chemical Society.

Figure 4

SERS—based molecular detection of exosomes. (a) Exosome classification through SERS detection of exosomes from normal and lung cancer cells. Left: Schematic of SERS detection of exosomes. Middle: SERS spectra of exosomes from different origins and control using PBS. Right: Principle component scatter plot showing clusters of exosomes from different origins. Reprinted with permission from [71]. Copyright (2017) American Chemical Society. (b) Individual molecular detection of exosome-like vesicles by label-free SERS spectroscopy. Left: Schematic of single EV detection. Each spectrum was recorded from one vesicle to another by moving the laser to a different spatial location of 1, 2, 3, etc. Middle: Representative SERS spectrum of EVs derived from B16F10 melanoma cells. Right: Representative SERS spectrum of EVs derived from red blood cells. Reprinted with permission from [75]. Copyright 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. (c) Molecular detection and analysis of exosomes with SERS AuNRs. Left: Schematic of the detection principle showing exosome capture with target-specific antibodies on an Au array device and exosome detection with SERS AuNRs via electrostatic interactions with exosome membranes. Middle: Detection of different surface protein markers on exosomes derived from SKBR3 breast cancer cells. Right: Detection of HER2-breast cancer by quantification of HER2-positive plasma exosomes. Cited from ref. [34].

Figure 5

Fluorescent detection of exosomes using QDs. (a) Isolation and multiplexed detection of exosomal tumor markers using QDs and magnetic beads in a microarray chip. Left: Schematic of the methodology showing exosome isolation with single magnetic bead trapped in the microfluidic pillars and multiplexed detection with multicolor QDs. Right: Fluorescence images of exosomes derived from different cell lines using three different target-specific QDs: QD525, QD585, and QD625. Cited from ref. [115]. (b) EV labeling and visualization with QDs. Left: Schematic of EV labeling with QDs. Middle: Photostability of QDs in comparison to Dil dye. Right: Fluorescence imaging showing the distribution of QD-labeled EVs (red) on lection stained BV-2 cells (green). Reprinted with permission from [117]. Copyright (2020) American Chemical Society. (c) Detection of breast cancer with QDs combined with immunomagnetic separation. Left: Schematic of the immunomagnetic isolation with magnetic beads and fluorescence detection of surface protein markers by QD655. Right: Fluorescence spectrum of exosomes from HER2-positive breast cancer patients and healthy donors after labeling with HER2-targeted QDs showing diagnosis potential of QDs for detection of HER2-positive breast cancer. Cited from ref. [119].

Figure 6

Magnetic nanosensor for the detection and profiling of microvesicles derived from red blood cells (RBC). (a) Schematic of microvesicle labeling with MNPs. (b) Schematic of the µNMR system showing the derived sensor coupled with membrane filter for microvesicle separation. (c) Relaxation rate change (ΔR₂CD235a) versus the number of microvesicles using CD235a targeted MNPs. (d) ΔR₂CD235a at different days of red blood cell storage showing stable vesicle expression of CD235a. (e) Relative changes in the expression levels of CD44, CD47, and CD55 during storage of red blood cells showing little changes in the expression levels of these proteins on microvesicles. * p > 0.48; ** p > 0.15; *** p > 0.17. (f) Microvesicle concentration over storage time showing the increase of the amount of microvesicles with storage time. Reprinted with permission from [148]. Copyright (2013) American Chemical Society.

Figure 7

Detection of Glioblastoma-derived exosomes with Zr−based MOFs. (a) Schematic of the preparation of MB@UiO−66 nanoprobes. (b) Scanning microscope image of MB@UiO−66 nanoprobes. (c) Schematic of the principle of electrochemical detection of exosomes using MB@UiO−66 nanoprobes. (d) SWV recorded with different concentrations of exosomes. (e) Scattered dot plots of exosomes from different human subjects. HS: healthy subjects. GBM: Glioblastoma. GBM−AS: GMB after surgery. ***: p < 0.0001. **: p < 0.001. Error bars represent the standard deviation of three independent experiments. Reprinted with permission from [155]. Copyright (2020) American Chemical Society.