Extracellular Vesicles as Biomarkers in Cancer Immunotherapy
Abstract
:Simple Summary
Abstract
1. Background
2. Challenges with Current Biomarkers for Cancer Immunotherapy
3. Tumor Mutational Burdens and Its Challenges
4. EVs and Tumor Microenvironment
5. EVs as Cancer Biomarkers
6. EVs and Cancer Immunotherapy
7. Challenges for Using EVs as Biomarkers: ISOLATION, Clinical Challenges, and EV Heterogeneity
7.1. Challenges in EV Isolation and Assay Development
7.2. Clinical Challenges and Variables for Standardization of EV-Based Biomarker Discovery
7.3. EVs Heterogeneity
8. EVs’ RNA, DNA, Proteomics for Cancer Biomarker Discovery
9. EVs for Cancer Therapy
10. Conclusions and Future Directions
Author Contributions
Funding
Conflicts of Interest
References
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Isolation Methods | Time | Indication | Advantages | Disadvantages | References |
---|---|---|---|---|---|
Ultracentrifugation/differential centrifugation | 3 h–12 h | Large volume of biofluids | Most commonly used, could be combined with other methods such as size exclusion, immune affinity isolation and sucrose gradient method | Need of expensive equipment, time consuming, low efficiency, deformity, impurity and protein co-aggregation, limit in processing sample quantity, low RNA yield | [86,87,88,89] |
Size exclusion (filtration+ chromatography) | 2 h | Large volume of biofluids, could be combined with nano-membrane ultrafiltration concentrators | Feasible, quick, inexpensive, low risk of contamination/deformity, yields functional EVs | EV dilution, yield variation | [90,91,92,93] |
Immune affinity isolation (antibody against EVs surface proteins) | 4–6 h | High purity isolation of EVs, isolation of sub-set of EVs, isolation of EVs from viruses and LPP | High specificity and selectivity, reproducibility, isolating special sub-set of EVs and possibility of negative selection | Cross reactivity of antibody, costly, low yield, expensive equipment | [94,95] (Bukong et al., 2014, Momen-Heravi et al., 2013) |
Microfluidic technologies | 5–14 µL/min | Low volume of input biofluids | Can be combined by immune affinity methods | Early stage of development, low throughput, high cost | [96] |
Participation with hydrophilic polymers | 1 h (some protocols overnight) | Relatively low cost and high yield of EVs and biomolecules, simplicity, no need for expensive equipment | Contamination of EVs with protein complexes and lipoproteins, polymer retention | [97] | |
Porous structures (Capturing EVs through in ciliated micropillar structure) | 2 h | Selectively trap particles in the range of 40–100 nm based on the research question | Purity, rapidness | Not suitable for isolation of larger particles, not validated with clinical samples, can handle only small amount of biofluids | [96,98] |
Developmental Process | Current or Future Challenges | Required Strategies |
---|---|---|
Sample processing and pre-analytical steps |
|
|
Biomarker discovery |
|
|
Clinical validation |
|
|
Clinical feasibility |
|
|
Class | Exosome Biomarker | Cancer Type | Biofluid | Indication | References |
---|---|---|---|---|---|
RNA | MEG3 | Bladder | Serum | Diagnosis, recurrence | [137] |
HOTAIR | Bladder | Urine | Prognosis | [138] | |
miR-21 | Esophageal | Serum | Diagnosis, prognosis | [139] | |
miR-4772-3p | Colon | Serum | Recurrence | [131] | |
PCA-3, TMPRSS2:ERG | Prostate | Urine | Diagnosis, monitoring | [140] | |
MALAT-1 | Lung | Serum | Diagnosis, prognosis | [136] | |
GOLM1-NAA35 | Esophageal | Saliva | Early detection, recurrence, therapeutic response | [127] | |
miR-141, miR-375 | Prostate | Serum | Diagnosis, prognosis | [141] | |
DNA | RET, HIF2A, VHL, SDHB | Neuroendocrine | Serum | Genetic diagnosis | [134] |
KRASG12D, TP53R273H | Pancreatic | Serum | Genetic diagnosis | [47,135] | |
Proteomics | CD36, CD44, 5T4, basigin, CD73 | Bladder | Urine | Diagnosis | [142] |
LRG1 | Lung | Urine | Diagnosis | [143] | |
BARF1 | Nasopharyngeal | Serum, saliva | Diagnosis | [144] | |
CD24, EpCAM, TGF-B1, MAGE3/6 | Ovarian | Plasma, ascitic | Diagnosis, prognosis, therapeutic response | [145,146] | |
Fibronectin | Breast | Plasma | Early detection | [147] | |
GPC1 | Pancreatic | Serum | Diagnosis, prognosis | [57] | |
MMP9 | Renal | Urine | Diagnosis | [148] |
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Mathew, M.; Zade, M.; Mezghani, N.; Patel, R.; Wang, Y.; Momen-Heravi, F. Extracellular Vesicles as Biomarkers in Cancer Immunotherapy. Cancers 2020, 12, 2825. https://doi.org/10.3390/cancers12102825
Mathew M, Zade M, Mezghani N, Patel R, Wang Y, Momen-Heravi F. Extracellular Vesicles as Biomarkers in Cancer Immunotherapy. Cancers. 2020; 12(10):2825. https://doi.org/10.3390/cancers12102825
Chicago/Turabian StyleMathew, Matthen, Mariam Zade, Nadia Mezghani, Romil Patel, Yu Wang, and Fatemeh Momen-Heravi. 2020. "Extracellular Vesicles as Biomarkers in Cancer Immunotherapy" Cancers 12, no. 10: 2825. https://doi.org/10.3390/cancers12102825
APA StyleMathew, M., Zade, M., Mezghani, N., Patel, R., Wang, Y., & Momen-Heravi, F. (2020). Extracellular Vesicles as Biomarkers in Cancer Immunotherapy. Cancers, 12(10), 2825. https://doi.org/10.3390/cancers12102825