Introduction
Exosome biogenesis and contents
Methods for exosome isolation and enrichment
Conventional isolation methods
Ultracentrifugation-based separation
Size-based separation
Precipitation techniques
New enrichment methods
Techniques | Methods | Advantages | Disadvantages | Prominent examples | Ref. |
---|---|---|---|---|---|
Conventional techniques | |||||
Ultracentrifugation-based Separation | Differential ultracentrifugation | High purity; established protocol; | Lengthy process; large sample volume; requires ultracentrifuge | Separation of EVs from reticulocyte culture medium | [44] |
Gradient density ultracentrifugation | High purity; | Lengthy process; large sample volume; requires ultracentrifuge | Sucrose gradient-purified prostasomes | [46] | |
Size-based Separation | Ultracentrifugation with ultrafiltration | High purity; high yield | Contamination of same-sized vesicles; lack specificity; difficulty in scaling | Separation of urinary exosomes | [49] |
size-exclusion chromatography | High yield; gentle processing | Contamination of same-sized vesicles; lack specificity; difficulty in scaling | Isolation of EVs from platelet-free supernatant of platelet concentrates | [50] | |
Precipitation | Polyethylene glycol precipitation | Simple; fast isolation | Lack specificity; much contamination; difficulty in scaling | Isolation of exosomes from plasma, cell culture supernatant | |
Commercial kits | Simple; fast isolation | Lack specificity; much contamination; high price | Isolation of exosomes from serum and/or plasma | [56] | |
Novel techniques | |||||
Immunoaffinity Enrichment | Antibody-conjugated platform | Simple; specificity | High-cost; marker dependent | Enrichment of exosomes from clinical samples | |
Magnetic Separation | Antibody-modified magnetic beads | Convenient; high efficiency | High-cost; marker dependent | Separation of exosomes | |
Physical Feature-based separation | Nanoscale lateral displacement | Reduced membrane blockage; gentle processing | Contamination of same-sized vesicles; lack specificity | On-chip sorting and quantification of exosomes | [75] |
Membrane filter | Gentle processing | Contamination of same-sized vesicles; lack specificity | On-chip isolation of intact extracellular vesicles | ||
Deterministic lateral displacement | Continuous accurate and precise separation | Low throughout and the requirement of high voltage | Efficient isolation of extracellular vesicles | ||
Size-exclusion chromatography | High yield; gentle processing | Contamination of same-sized vesicles; lack specificity | Efficient isolation of extracellular vesicles | ||
Lipid Mediated-Separation | Lipid nanoprobe/TiO2 | Minimal damage | Contamination of other phospholipid membrane vesicles; lack specificity | Efficient isolation of extracellular vesicles | |
Acoustic-based microfluidics | Aacoustic radiation force (ARF) and dielectrophoretic (DEP) | Contact-free; high-throughput; continuous separation; wide range of particles | Design and fabrication finer gradations; finer-grade separation of subpopulations | Active sorting of extracellular vesicles | |
Thermophoretic Enrichment | Thermophoresis | Free from pre-isolation; simple; fast isolation | Contamination of same-sized vesicles; lack specificity | Efficient isolation of extracellular vesicles |
Immunoaffinity enrichment
Magnetic separation and enrichment
Physical feature-based separation
Lipid-based separation
Acoustic-based isolation method
Thermophoretic enrichment
Exosome characterization
Visible characterization
Quantitative characterization
Techniques for detecting exosome contents
Conventional protein analysis
New protein detection methods
Colorimetric detection
Methods | Exosome sources | Sample volume | Sensing mechanism | Sensing substances | Detection limit | Ref. |
---|---|---|---|---|---|---|
Colorimetric Detection | MCF-7 cells and breast cancer patient’s serum | H2O2-mediated oxidation of TMB | s-SWCNTs; CD63-specific aptamer | 5.2 × 105 particles/μL | [109] | |
Cell-culture medium and prostate cancer patient’s plasma | 500 μL | H2O2-mediated oxidation of TMB | Aptamer-capped Fe3O4 nanoparticles | 3.58 × 106 particles/mL | [72] | |
Urine | 100 mL | H2O2-mediated oxidation of TMB | Biotinylated anti-CD63 antibody; streptavidin-labeled HRP | 35.0 AU/mL | [76] | |
MCF-7 cells and cancer patient’s serum | 100 μL | H2O2-mediated oxidation of TMB | CD9, CD63 antibody mixture; HRP-labeled secondary antibody | 2.2 × 104 particles/μL | [110] | |
BeWo cell | H2O2-mediated oxidation of TMB | Au-NP; Fe2O3NC | 103 exosomes/mL | [148] | ||
Fluorescence Detection | Plasma specimens from NSCLC and OVCA patients | 30 μL | Chemifluorescence reagents | EpCAM, IGF-1R or CA125 antibodies; AP-conjugated secondary antibody, and the DiFMUP substrate | 0.281 pg/mL; 0.383 pg/mL | [36] |
SKOV3 cells and plasma of OVCA patients | 10 μL | The reaction of SβG with FDG | Biotin conjugated detection antibodies and streptavidin conjugated SβG | 21 exosomes/μL | [149] | |
MCF-7 and MDA-MB-231 cell culture medium | 1 mL | Fluorescent carbocyanine dye (DiO) | CD63 antibody functionalized microbead and DIO labelling | [150] | ||
Cell culture supernatant and serum from pancreatic cancer patients | Fluorescent carbocyanine dye (DiO) | CD63 antibody-functionalized EXOchip | [20] | |||
MCF-7 cells and blood samples from cancer patients | 100-300 μL | Fluorescent second antibody | Anti-EpCAM antibody and Alexafluor®647-conjugated secondary antibody | [59] | ||
Cell-culture medium and plasma from breast cancer patients | Fluorescent second antibody | CD63 antibody-coated magnetic beads; fluorescent dye-conjugated antibodies | 107 particles/μL | [151] | ||
A549 cancer cell line and plasma samples of lung cancer patients | 0.5 μL | Fluorescent aptamer | TMR-aptamer | 500 particles/μL | [152] | |
Serum samples | Fluorescent aptamer | CD63 aptamer-modified magnetic beads; Cy3-labeled short sequence | 1.0 × 105 particles/μL | [126] | ||
Cancer cell line and plasma samples | 500 μL | Fluorescent aptamer | TPE-TAs/aptamer complexes; graphene oxide surface | 3.43 × 105 particles/μL | [99] | |
MDA-MB-231 cell-culture medium and plasma from breast cancer patients | 80 μL | Fluorescence quenching | GPC-1 antibody coated magnetic beads; CD63 aptamer | 6.56 × 104 particles/μL | [84] | |
Cancer cell line and serum samples | Fluorescence quenching | FAM-labeled aptamers; graphene oxide | 1.6 × 105 particles/mL | [113] | ||
Cancer cell line and blood samples | Fluorescence quenching | Anti-CD63-PE/MoS2–MWCNT | 14.8 × 105 particles/mL | [153] | ||
Electrochemical Detection | Ovarian cancer cell lines and plasma from patients with ovarian cancer | 10 μL | Integrated magneto-electrochemical sensor | Immunomagnetic beads; HRP-labeled secondary antibody | 3 × 104 | [128] |
Plasma samples | 20 μL | Electrochemical biosensor | Immunomagnetic beads; probing antibodies | [129] | ||
Cell-culture medium and blood samples from breast cancer patients | Electrochemical biosensor | Anti-PD-L1-linked DNA strand; PVP@HRP@ZIF-8 | 334 particles/mL | [114] | ||
HepG2 cells and human serum of liver cancer patients | 30 μL | Aptamer-based biosensors | CD63 aptamer and mimicking DNAzyme sequence | 4.39 × 103 particles/mL | [65] | |
Culture medium of HepG2 cells | Aptamer-based biosensors | NTH-assisted aptasensor | 2.09 × 104/mL | [154] | ||
Cell-culture medium and serum | Aptamer-based biosensors | Aptamer-magnetic bead bioconjugates; electroactive Ru (NH3)63+ | 70 particles/μL | [155] | ||
Cellular supernatant and human plasma samples | Aptamer-based biosensors | anti-CD63 antibody modified gold electrode and a gastric cancer exosome specific aptamer | 9.54 × 102/mL | [156] | ||
Human hepatoma cell lines MHCC97H/L and mouse melanoma cell lines B16-F1/10 | Antibody microarray SPRi sensor | Anti-CD9, CD41b,21 and tyrosine kinase receptor MET8a antibodies immobilized gold-coated glass sensor chip | [157] | |||
SPR Detection | MCF-7 breast cancer cells and MCF-10A normal breast cells | SPR-based aptasensor | Dual gold nanoparticle-assisted signal amplification | 5 × 103 exosomes/mL | [158] | |
Human NSCLC cell lines, normal lung cell and plasma | 1.5 mL | Bioaffinity interactions of antibodies and different recognition sites | Antibodies modified-gold chip and different recognition sites | 104 particles/μL | [159] | |
Urine samples from lung cancer patients and controls | 500 μL | SPR-induced improved scattering intensity | Anti CD81/LRG1 antibody modified nanoporous gold nanocluster membrane; second antibody-conjugated Au nanorod probes | < 1000 particles/mL | [58] | |
Breast cancer cell line and serum | 250 μL | SPR-induced improved scattering intensity | Anti-HER2-functionalised SPR chip | 8280 exosomes/μL | [160] | |
Cancer cells and serum and the CSF of an orthotopic mouse model | Strong localization of surface plasmon polaritons | TIC-AFM and TiN–NH-LSPR biosensors | 5.29 × 10−1 μg/ml; 3.46 × 10 -3 μg /ml | [161] | ||
Breast cancer cells and normal breast cells; plasma from HER2-positive breast cancer patients | Raman reporters | Gold-coated glass microscopy slide; QSY21-coated gold nanorods | 2 × 106/mL | [134] | ||
SERS | Plasma of cancer patients | 400 μL | P-O bond signature | Beehives-like Au-coated TiO2 macroporous inverse opal | [117] | |
Cell-culture medium and serum sample | 4 μL | MBA signature | Fe3O4@TiO2 nanoparticles; anti-PD-L1 antibody modified Au@Ag@MBA | 1 PD-L1 exosome/μL | [90] | |
Normal and lung cancer cell lines; plasma | Deep learning | Deep learning model | [162] | |||
Cell-culture medium; serum and plasma | < 1 μL | Enrichment of aptamer-bound EVs | Seven aptamers targeting specific proteins; machine-learning algorithm | 3.3 × 103/μl | [68] | |
CRISPR/Cas-assisted detection | A549 cell-culture medium and serum from lung cancer patients | CRISPR/Cas12a | CD63 aptamer; CRISPR/Cas12a | Linear range of 3 × 103–6 × 107 particles/μL | [136] | |
SUNE2 cell-culture medium and serum from NPC patients | 50 μL | CRISPR/Cas12a | Nucleolin and PD-L1 aptamers; CRISPR/Cas12a | 102 particles/μL | [137] | |
SUNE2 cell-culture medium and serum from NPC patients | CRISPR/Cas12a | CD109 and EGFR aptamers; CRISPR/Cas12a | 102 particles/μL | [138] | ||
Single EV Analysis | Human serum | 10 μL | Rolling circle amplification | ssDNA-assisted single EV detection platform | 82 vesicles/μL | [139] |
T3M4 pancreas cancer line and serum from PDAC patients | 10 mL | Flow cytometry | Aldehyde/sulfate latex beads; anti-GPC-1 antibody and Alexa-488-tagged antibody | [38] | ||
Breast cancer cell lines and serum of breast cancer patients | 500 μL | Flow cytometry | Aldehyde/sulfate latex beads; anti-EpCAM or anti-HER2 antibody; Alexa-488- or − 594-tagged secondary antibodies | [141] | ||
Human cell lines and serum of glioma patients | 250 μL | Flow cytometry | Aldehyde/sulfate latex beads; anti-EGFR or anti-CXCR4 antibody | [118] | ||
HCT15 cell-culture medium and plasma | 500 μL | Nano-flow cytometry | [142] |
Fluorescence detection
Electrochemical detection
Surface plasmon resonance detection
Surface enhanced Raman scattering
CRISPR/Cas system-assisted detection
Single exosome detection
Conventional nucleic acids analysis
Methods | Exosome sources | Sample volume | Nucleic acids | Detection mechanism | Advantages | Disadvantages | Ref. |
---|---|---|---|---|---|---|---|
Droplet digital PCR | Urine | 2 mL | miRNA; gene variation | Nucleic acid amplification of droplets in an oil emulsion | Absolute quantification; small sample volume; high accuracy and sensitivity; | High-cost; limited throughout; complex operation | [163] |
Cerebrospinal fluid of GBM patients | 1 mL | IDH1 mutation | [164] | ||||
Plasma samples of HCC patients and control cohorts | 90 μL | HCC-specific mRNA | [61] | ||||
Cancer cell lines and patient plasma | 2 μL | GAPDH mRNA | [165] | ||||
Human plasma | miR-15a-5p | [40] | |||||
Human plasma | PGR mRNA; ESR1 mRNA; ERBB2 mRNA | [120] | |||||
Clinical blood | 1.5 mL | EV-lncRNA of SLC9A3-AS1 and PCAT6 | [166] | ||||
Serum | 100 μL | circHIPK3 and circSM ARCA5 | [167] | ||||
Molecular beacons | Cancer cells and human serums | 35 μL | miRNA-21 | Fluorescent, enzyme-labeled oligonucleotide probes identifying and detecting nucleic acid with complementary sequences | High specificity, simplicity; low background fluorescence; rapid detection | High-cost; limited throughout | [122] |
Breast cancer cell line and human plasma | miR-21; miR-375; and miR-27a | [121] | |||||
Prostate cancer cells and human urine | miRNA-375 and miRNA-574-3p | [168] | |||||
Human plasma | 10 μL | miR-1246 | [169] | ||||
RBC-derived EVs | miRNA-451a | [170] | |||||
PCA cell | miR-21 | [151] | |||||
DNA tetrahedron probe | Serum | miR-21 | Leverage localized reaction and cascade amplification | High specificity and sensitivity | High-cost | [171] | |
Plasma | 1 mL | miR-1246; miR-221; miR-375; miR-21 | [172] | ||||
SPR Detection | Pancreatic cancer cells and plasma | 50 μL | miR-10b | The change of dielectric constant caused by molecule adsorption on the heavy metal film | High specificity and sensitivity; label-free | Nonspecific adsorption | [173] |
Plasma | miRNA | [123] | |||||
Mouse serum | miR-10b | [174] | |||||
Single Vesicle Analysis | Serum | hsa-miRNA-21 | Single-vesicle imaging | Direct visualization; acknowledgement of heterogeneity at the single-vesicle level | Nonspecific adsorption | [119] | |
Thermophoretic Detection | Serum | 0.5 μL | miRNA | Nanoflare induced amplified fluorescence signal | Without the need for EV pre-isolation; high sensitivity; rapid detection; low cost | [175] | |
CRISPR/Cas-assisted detection | Plasma | 500 μL | miRNA-21; miRNA-221; miRNA-222 | CRISPR/Cas9 | High sensitivity and specificity | [176] |
New nucleic acids detection technologies
ddPCR
Molecular beacons
DNA tetrahedron probe
Localized surface plasmon resonance
TIRF-based single-vesicle imaging
Thermophoresis-assisted detection
CRISPR/Cas system-assisted detection
Machine learning
The implication of exosomes in cancer liquid biopsy
Cancer types | Exosome sources | Sample volume | Exosomal biomarker | Clinical samples | Diagnostic performance | Clinical significance | Ref. |
---|---|---|---|---|---|---|---|
Gastric Cancer | Serum | lnc HOTTIP | 126 GC patients; 120 healthy donors | AUC = 0.827 | Early diagnosis | [191] | |
Serum | miR-15b-3p | 108 GC patients; 108 healthy donors | AUC of 0.820; specificity of 80.6%; sensitivity of 74.1% | Early diagnosis | [192] | ||
HCC | Plasma | 100 μL | AFP; GPC3; ALB; APOH; FABP1; FGB; FGG; AHSG; RBP4; TF mRNA | 36 HCC patients; 26 Cirrhosis | AUC of 0.87; sensitivity of 93.8%; specificity of 74.5% | Early diagnosis | [61] |
Serum | 500 μL | miRNA-21; lncRNA-A TB | 72 HCC patients | Higher in HCC patients | Prognostic significance | [189] | |
Serum | miR-21 | Higher in HCC patients | Early diagnosis | [193] | |||
Serum | 250 μL | miR-92b | 28 non-HCC; 28 HCC patients without recurrence; 43 HCC patients with early recurrenc | Sensitivity of 85.7%; specificity of 86.0%; AUC = 0.925 | Early recurrence diagnosis after LDLT | [194] | |
Serum | 100 μL | CEA; GPC-3 and PD-L1 | 12 HCC patients; 12 hepatitis B; 6 healthy donors | Higher in HCC patients | Early diagnosis and progression monitoring | [112] | |
PDAC | Plasma | 500 μL | miRNA-10b | 3 PDAC Patients; 3 CP Patients; 3 healthy donors | Higher in PDAC patients | Early diagnosis and progression monitoring | [173] |
Plasma | miRNA-10b | PDAC patients; CP patients and healthy donors | Higher in PDAC patients | Early diagnosis | [195] | ||
Mouse plasma samples | miR-3970-5p | 9 healthy donors; 9 PanIN patients; 9 PDAC patients | Accuracy of 65% | Early diagnosis | [196] | ||
Serum | 250 μL | Glypican1 | 192 patients; 100 healthy donors | Sensitivity of 100%; specificity of 100%; positive predictive value of 100%; negative predictive value of 100%; AUC of 1.0 | Early diagnosis | [38] | |
Plasma | 25 μL | Glypican1 | 20 PDAC patients; 7 benign pancreatic disease; 11 healthy donors | 99% sensitivity and 82% specificity | Stage classification | [197] | |
Serum | 5 μL | EpCAM, Glypican1 | 90% accuracy for pancreatic cancer or normal pancreatic epithelial cell lines; 87 and 90% predictive accuracy for HC and EPC individual samples | Early diagnosis | [198] | ||
Serum | 2 μL | MIF | 4 patients at stage 1 ~ 2; 37 patients at stage 3 | Discriminatory sensitivity of 95.7% | Stage classification | [199] | |
CRC | Serum | hsa-circ-0004771 | 179 patients; 45 healthy donors | AUC of 0.86, 0.88 to differentiate stage I/II CRC patients and CRC patients from HCs | Early diagnosis | [200] | |
Plasma | 25 μL | Epcam-CD63 | 59 cancer patients; 20 healthy donors | AUC of 0.96 | Early diagnosis; prognosis prediction | [125] | |
NSCLC | Plasma | miRNA-21; miRNA-139; miRNA-200; miRNA-378 | 5 patients; 5 healthy donors | Higher in NSCLC patients | Early diagnosis | [123] | |
Plasma | 1 mL | miRNA-21 | NSCLC patients; recurrence of NSCLC patients; healthy individuals | Higher in NSCLC patients | Early diagnosis and drug resistance in advanced cancers | [201] | |
Plasma | 1.5 mL | CD63; EGFR; EpCAM | 4 patients; 4 treated patients; 4 healthy donors | Higher in NSCLC patients | Early diagnosis and therapeutic effect evaluation | [159] | |
Serum | 50 μL | PD-L1 | 5 patients; 4 healthy donors | Higher in NSCLC patients | Early diagnosis | [132] | |
Serum | 4 μL | PD-L1 | 7 patients at stage 1 ~ 2; 10 patients at stage 3 ~ 4; 12 healthy controls | AUC of 0.97 | Early diagnosis | [90] | |
Breast Cancer | Plasma | EpCAM | 6 BC patients; 3 healthy donors | Higher in BC patients | Early diagnosis | [71] | |
Plasma | EpCAM; HER2 | 10 BC patients; 5 healthy donors | AUC of 1; AUC of 1 | Early diagnosis | [134] | ||
Serum | 3.6 μL | EpCAM | 20 BC patients; 10 healthy donors | AUC BC versus HD = 0.99; AUC HER2+ BC versus HER2– BC = 0.94 | Cancer classification | [202] | |
Serum | PD-L1 | 7 patients with metastatic; 8 patients without metastatic; 6 healthy donors | Higher in BC patients | Prognosis prediction and progression monitoring | [114] | ||
Blood | CA153 | 104 BC patients; 100 breast hyperplasia patients and 100 healthy controls | Higher in BC patients | Differential diagnosis | [203] | ||
Serum | miR-21; miR-222; miR-200c | Luminal, HER2+, and TN breast cancer patients | Higher in BC patients | Classification of molecular subtypes of breast cancer | [204] | ||
Plasma | 1 μL | CA153; EpCAM | 36 MBC patients before salvage treatment; 21 NMBC patients before surgical therapy; 66 age-matched healthy donors | AUPRC CA153 = 0.9286 | Differential diagnosis of BC and healthy donors | [69] | |
AUPRC EpCAM = 0.9709 | |||||||
Plasma | 1 μL | CA153; CA125; CEA; HER2; EGFR; PSMA; EpCAM; VEG | 36 MBC patients before salvage treatment; 21 NMBC patients before surgical therapy; 66 age-matched healthy donors | AUPRC of 0.9826 | Differential diagnosis of BC and healthy donors | [69] | |
Plasma | 1 μL | CA153; CA125; CEA; HER2; EGFR; PSMA; EpCAM; VEG | 36 MBC patients before salvage treatment; 21 NMBC patients before surgical therapy; 66 age-matched healthy donors | AUPRC of 0.8672 | Differential diagnosis of MBC and NMBC | [69] | |
Plasma samples | EpCAM | Various breast cancer patients and healthy individuals | Higher in BC patients | Early diagnosis | [115] | ||
Prostate Cancer | Urine | 50-150 mL | miR-196a; miR-143-3p; miR-196-5p; miR-501-3p; | 28 PCA patients; 19 healthy donors | AUC miR-196a = 0.92 | Early diagnosis | [205] |
AUC miR143-3p = 0.72 | |||||||
AUC miR196-5p = 0.73 | |||||||
AUC miR501-3p = 0.69 | |||||||
Plasma | 750 μL | miR-217; miR-23b-3p | 10 patients; 10 healthy donors | Higher in PCA patients | Early diagnosis | [206] | |
Serum | 400 μL | EphrinA2 | 50 PCA patients; 21 BPH patients; 20 healthy donors | AUC of 0.7666 | Early diagnosis; distinguish PCA from BPH patients | [207] | |
Serum | 25 μL | EpCAM and PSMA | 10 PCA patients; 5 healthy donors | Higher in PCA patients | Early diagnosis | [127] | |
Serum | TUBB3 mRNA | 52 mCRPC patients | Higher in PCA patients | Prognosis | [208] | ||
Ovarian Cancer | Ascites | EpCAM; CD24 | 20 patients; 10 healthy donors | Higher in OVCA patients | Early diagnosis | [116] | |
Plasma | 2 mL | CA125; EpCAM; CD24 | 15 patients; 5 healthy donors | AUC CA125 = 1.0 | Early diagnosis | [74] | |
AUC EpCAM = 1.0 | |||||||
AUC CD24 = 0.91 | |||||||
Plasma | 20 μL | CD24; EpCAM; FRα | 20 OVCA patients; 10 non-cancer controls | AUC CD24 = 1.0 | Early diagnosis | [165] | |
AUC EpCAM = 1.0 | |||||||
AUC FRα = 0.995 | |||||||
Plasma | 200 μL | miR-4732-5p | 21 healthy controls and 34 epithelial ovarian cancer patients | AUC miR-4732-5p = 0.889 | Early diagnosis | [209] |