Abstract
Over the past three decades, extracellular vesicles (EVs) have arisen as important mediators of intercellular communication that are involved in the transmission of biological signals between cells to regulate various biological processes. EVs are largely responsible for intercellular communication through the delivery of bioactive molecules, such as proteins, messenger RNAs (mRNAs), microRNAs (miRNAs), DNAs, lipids, and metabolites. EVs released from cancer cells play a significant role in signal transduction between cancer cells and the surrounding cells, which contributes to the formation of tumors and metastasis in the tumor microenvironment. In addition, EVs released from cancer cells migrate to blood vessels and flow into various biological fluids, including blood and urine. EVs and EV-loaded functional cargoes, including proteins and miRNAs, found in these biological fluids are important biomarkers for cancer diagnosis. Therefore, EV proteomics greatly contributes to the understanding of carcinogenesis and tumor progression and is critical for the development of biomarkers for the early diagnosis of cancer. To explore the potential use of EVs as a gateway to understanding cancer biology and to develop cancer biomarkers, we discuss the mass spectrometric identification and characterization of EV proteins from different cancers. Information provided in this review may help in understanding recent progress regarding EV biology and the potential roles of EVs as new noninvasive biomarkers and therapeutic targets.
Subject terms: Cancer, Proteomics
Cancer: Protein-filled vesicles offer therapeutic and diagnostic targets
Tumor cells release tiny membrane-encapsulated packages known as extracellular vesicles containing proteins which could serve as prognostic disease biomarkers or therapeutic targets. Kwang Pyo Kim and colleagues from Kyung Hee University in Yongin, South Korea, review the use of mass spectrometry to profile the diversity of proteins found in these tumor-derived packages. The proteins found in these vesicles help mediate communication between cancer cells and their surrounding tissues. Different tumor types share many of these proteins in common, but there are differences in the protein profile related to cancer-associated biological processes such as metastasis and cell proliferation. Tests based on the proteins contained in these vesicles could help clinicians better identify, diagnose and treat specific cancers, although large, multicenter studies are needed to validate such strategies.
Introduction
Extracellular vesicles (EVs) are membrane-surrounded vesicles released by numerous cell types into the extracellular microenvironment1–3. EVs are involved in cell–cell communication, coagulation, inflammation, immune response modulation, and disease progression2,4–7. Although EVs vary in size, biological function, and components, their significance in cancer progression and the potential use of EV molecules as novel cancer biomarkers has gradually increased. Cancer cells actively release EVs into neighboring tissues, and these EVs play dynamic roles in cancer progression and metastasis, invasion, angiogenesis, tumorigenesis, and immune modulation8–10. EVs released by cancer cells are usually chosen as a gateway in the search for biomarkers for a specific cancer type. Recent results pertaining to EV-cargo molecules, including proteins and miRNAs, are summarized in EVpedia (http://evpedia.info), an integrated and comprehensive database of EVs11.
The main focus of this review is proteome profiling of EVs using mass spectrometry (MS)-based proteomic approaches. We discuss the mass spectral characterization of isolated EV proteins from different cancers and the use of these proteins as predictive cancer biomarkers. Additionally, we summarize the key characteristics of enriched proteins in cancer-associated EVs as potential therapeutic targets and provide novel information on their roles in cancer development and progression. Information provided in this review may help in understanding recent progress regarding EV biology and the prospective roles of EVs as new noninvasive biomarkers and therapeutic targets, as well as emerging therapeutic opportunities and associated challenges.
Classification of EVs
EVs are small spherical vesicles that are secreted into the extracellular milieu by many cell types. The term “EV” was invented by the International Society of Extracellular Vesicles (ISEV) and is used to define all phospholipid bilayer-bound vesicles that are secreted by cells into the extracellular microenvironment, regardless of the differences in biogenesis, size, and composition12,13. The roles of EVs in different physiological and pathological processes have made them a novel field of research. EVs are categorized into several subtypes based on their size, density, shape, subcellular origin, function, and molecular cargo14. The four major subtypes of EVs are exosomes, microvesicles, apoptotic bodies, and oncosomes (Table 1 and Fig. 1). Exosomes are 30–200-nm-sized homogeneous membrane vesicles, and they form through the endosomal trafficking pathway5,15,16. Exosomes contain late endosomal markers, even though biochemically indistinguishable vesicles can bud directly from the plasma membrane16,17. They play critical roles in cell–cell communications, such as that occurring during the regulation of cell and tissue homeostasis, as well as in pathological conditions18. Microvesicles are 100–1000-nm-sized heterogeneous membrane vesicles that originate via outward budding and the fission of the plasma membrane due to dynamic interactions during phospholipid redistribution. Phospholipid distribution is controlled by aminophospholipid translocases16,18–24 and cytoskeletal protein contraction. Microvesicles are released mostly under cellular stress or in pathological processes18. Like exosomes, microvesicles transfer bioactive molecules into target cells. Apoptotic bodies (> 1 µm) are released by cells that undergo the apoptosis process or programmed cell death18,24, and they can be characterized by cellular organelles and DNA. Finally, the vesicles named “oncosomes” are much larger than most other EV types characterized to date (1–10 μm). Owing to their unusual size, large oncosomes might have unique properties in vivo and would provide novel opportunities for tumor profiling25.
Table 1.
EV subtype | Diameter | Biogenesis | Markers | References |
---|---|---|---|---|
Exosomes | 30–200 nm | Released from multivesicular bodies within the endosomal network | Membrane transport and fusion proteins (annexins, GTPases, and flotillin), tetraspanins (CD9, CD63, CD81, and CD82), heat-shock proteins (Hsc70 and Hsp90), proteins involved in MVB biogenesis (Alix and Tsg101), lipid-related proteins and phospholipases, ESCRT, and MHC | 4, 5, 13– 15 |
Microvesicles | 100–1000 nm | Produced by direct budding from the cell membrane | Selectins, integrins (B1), metalloprotease surface phosphatidylserine, vesicle-associated membrane protein 3, CD34, CD40, CD45, glycophorin, or blood group antigens | 16– 22, 25, 58 |
Apoptotic bodies | >1 µm | Released only by cells undergoing apoptosis or programmed cell death (apoptosis fragments) | Surface phosphatidylserinehistones, calnexin, cytochrome C, annexin V, C3b, and TSP | 4, 14– 22 |
Oncosomes | 1–10 µm | Non-apoptotic plasma membrane blebs shed by “ameboid” migrating tumor cells or from tumors | Cav-1, ARF6, Myr, Akt1, and HB‑EGF | 23 |
EVs contain proteins, lipids, metabolites, and RNAs. However, the mechanisms by which these components enter EVs remain obscure. EVs are shed from almost all cell types and are present in biological fluids and conditioned cell culture media. EVs are involved in cell–cell communication, coagulation, inflammation, immune response modulation, and disease progression4–7. The functional roles of EVs in intercellular communication have made them of major interest in many scientific fields. The biomolecular composition of EVs could play a significant role in disease progression in several neurodegenerative diseases as well as in cancer.
MS in EV proteome analyses
EV proteome analysis is a novel approach and is part of the growing interest in proteomics cancer research. Over the past three decades, many proteomics studies performed on EVs have elucidated their diverse roles. Large-scale proteomics datasets and protein-interaction networks have established significant relationships between EV proteins, which improves the understanding of vesicle biogenesis and pathophysiological roles24,26,27. Proteomic studies on EVs from different origins have also suggested a controlled protein-sorting mechanism and the random packaging of EV proteins from various cell types that contain common vesicular proteins. Furthermore, proteomic studies of EVs have produced a high-throughput vesicular proteome dataset from various cell types and body fluids28. Since EVs are normally isolated in small amounts, better sensitivity is required for their analysis. Liquid chromatography (nanoscale or ultra-high performance)–electrospray ionization tandem mass spectrometry (LC/ESI–MS/MS) is the most popular and versatile analytical technique to study the molecular contents of EVs. In particular, nano-ESI–MS/MS provides high sensitivity and resolution, allowing the detection, identification, characterization, and quantification of thousands of proteins from even a single EV sample. Similar to other biological fields, LC–MS/MS-based technological platforms have become the most popular fundamental tools for elucidating the structural and functional architecture of EVs. The fragment ions from ESI (positive- and negative-ion) tandem MS experiments provide the composition, unambiguous structural characterization, and proper identification of proteins present in various biological samples. Due to the high sensitivity and small initial sample volumes required for MS, MS-based proteomic analysis has increased the understanding of EV protein content. Several investigators26,29–32 have used ESI tandem MS experiments in combination with chromatographic methods (HPLC, UHPLC, UPLC, and nano LC) to profile and structurally characterize proteins in various cancer cells, tissues, biofluids, and biological samples, which have been summarized in Table 2.
Table 2.
Cancer type | Cancer-specific EV proteins | Isolation of EVs | Characterization | Sample source | References |
---|---|---|---|---|---|
Bladder cancer | EDIL-3 | UC | WB, TEM | TCC, T24, SV-HUC, and urine | Beckham et al.59 |
UC | TEM, NTA | TCCSUP, T24, UMUC3, RT3 SVHUC, and urine | Silvers et al.60 | ||
ITGB1, ITGA6, CD36, CD44, CD73, CD10, MUC1, BSG, and 5T4 | UC | NTA, TEM, and WB | HT1376, urine | Welton et al.34 | |
UC | NTA, TEM, and WB | T24, FL3, and SLT4 | Jeppesen et al.61 | ||
Colon cancer | HGS | ExoQuick | NTA, TEM, and WB | HCT116 | Sun et al.62 |
Clstn1, VCP, and RuVB-like1 (O-GlcNAcylation) | UC | TEM, WB | CCD841, HT29, SW480, and SW620 | Chaiyawat et al.63 | |
F2 | BDG | NTA, TEM, and WB | SW480, SW620 | Schillaci et al.64 | |
YWHAZ | UC | HCT116, patient colon tumor | Hillary et al.65 | ||
ACACA | UC | Citrus-limon, SW480 | Raimondo et al.66 | ||
UC | NTA, WB | SW620 | Guo et al.67 | ||
EPCAM-CLDN7 and TNIK-RAP2A | BDG | NTA, TEM, and WB | SW480, SW620 | Ji et al.53 | |
BDG | NTA, TEM, and WB | Patient tumor | Choi et al.26 | ||
BDG | NTA, TEM, and WB | HT-29 | Choi et al.27 | ||
GPA33, CDH17, CEA, EpCAM, PCNA, EGFR, MUC13, MINK1, KRT18, MAPK4, CLDN (1, 3, and 7), CEP55, EFNB1, and EFNB2 | TEM, WB | LIM1215 cells, urine, mast and cells | Suresh et al.33 | ||
UC | NTA, TEM, and WB | Dks-8, DLD-1, and DKO-1 | Demory et al.68 | ||
BDG | NTA, TEM, and WB | SW480, SW620 | Choi et al.69 | ||
DKK4 and DNMT3A | UC | TEM, WB | SW480, SW480APC | Lim et al.70 | |
MAC2BP, ALIX, 14–3–3 isoforms, PFN1, CALU, and IL-8 | UC | TEM | LIM1215 cells | Ji et al.71 | |
Prostate cancer | UC | DLS, TEM | pc3-HSP27, HEK-293 | Rauschenberger et al.72 | |
UC | PC3, DU145, VCaP, LNCaP, C4–2, and RWPE-1 | Hosseini-Beheshti et al.73 | |||
THBS1, GSN, and ITGB1 | UC | WB | LNCaP | Soekmadji et al.74 | |
ITGB4 and VCL | UC, CD9 antibody magnetic beads | NTA, WB, and TEM | PC-3 | Kawakami et al.75 | |
CD9 | UC | TEM, WB | LNCaP, DUCaP PCa cells, and plasma | Soekmadji et al.76 | |
UC | TEM, WB, and NTA | DU145 Tax-Sen, DU145 Tax-Res | Kharaziha et al.77 | ||
CD151 and CDCP1 | UC | PC-3 | Sandvig et al.78 | ||
PDCD6IP, FASN, XPO1, and ENO1 | UC, SG | TEM, WB | PNT2C2, RWPE1, PC346C, and VCaP | Duijvesz et al.30 | |
UC | Osteoblasts | Bilen et al.79 | |||
Lung cancer | AKT and ERK1/2 | UC | WB | H3255, H1650 | Van et al.80 |
AKT1, GSK3B, EIF4E, MTOR, RELA, and RAS | BDG | TEM, WB | PC9, PC9R | Choi et al.81 | |
ALLIX, TSG101, CD3, EGFR, SRC, KRAS, and NRP1 | PEG precipitation, UC, and BDG | TEM, WB | A54, HCC827, and HBEC | Clark et al.39 | |
P53 and EGFR | qEV | TRPS, TEM, and WB | 30KTp53/EGFR | Lobb et al.82 | |
HCC | ExoQuick | TEM, WB | Hep3B, 97 H, and LM3 | Zhang et al.83 | |
RRAS, CD44, CDC42, and CLND3 | UC | WB | HKCI-C3, HKCI-8, MHCC97L and MIHA | He et al.84 | |
UC | NTA, TEM, and WB | HepG2 | Wang et al.43 | ||
UC | WB, EM | Huh7.5.1 Huh7-ET | Ramakrishnaiah et al.85 | ||
Breast cancer | UC | TEM | Plasma, bone metastasis explant-conditioned media, and pleural effusion | Tucker et al.86 | |
vn96 affinity capture of EV | WB and TEM | SKBR3, MCF-7, and MCF-10a | Griffiths et al.87 | ||
Free-flow electrophoresis | SKBR3 (hypoxia, normoxia) | Thomas et al.88 | |||
UC | TEM, WB, and NTA | MCF-7, MDA-MB-231 | Harris et al.32 | ||
DEL-1 | Plasma, MDA-MB-231 | Moon et al.89 | |||
EDIL3 | BDG | NTA, TEM, and WB | MCF-7, MDA-MB-231 | Lee et al.29 | |
IL-6, TNFa, GCSF, and CCL2 | UC | TEM, WB, and FC | MCF10A, MDA-MB-231, and MCF7 | Chow et al.90 | |
POSTN | UC, SG | NTA, TEM, and WB | MCF7, MDA-MB-231, 67NR, 4T1, and plasma | Vardaki et al.91 | |
UC | TEM, WB, and NTA | cal51 TNBC | Kavanagh et al.92 | ||
UC | TEM, WB | MDA-MB-231 cells | Palazzolo et al.37 | ||
MTDH and CP | UC | TEM, WB, and NTA | 4T1, 4T1.2, 67NR, and 66cl4 | Gangoda et al.93 | |
UC | TEM, DLS, and WB | VCaP | Domenyuk et al.94 | ||
Ovarian cancer | UC | TEM, WB | OVCAR3, OVCAR433, OVCAR5, and SKOV3 | Sinha et al.95 | |
UC | WB, TEM | SKOV3, OVM | Escrevente et al.96 | ||
G6PD and TKT | UC | WB, TEM | OVCA429, HO8910PM | Yi et al.97 | |
UC | TEM, WB | OVCAR-3, IGROV1 | Liang et al.41 | ||
UC | TEM, WB | SKOV3, CAOV3, and HUVEC | Yi et al.98 | ||
Pancreatic cancer | EGFR | UC | WB | BxPC3, MiaPaca2, and Panc1 | Adamczyk et al.99 |
ZIP4 | SBI ExoQuick‐TC Kit | TEM, WB | PC‐1.0 (highly malignant), PC‐1 (moderately malignant) | Jin et al.100 | |
CEACAMs and ECM proteins | UC | TEM | Pancreatic duct fluid | Zheng et al.101 | |
UC, SG | EM | SOJ-6, BxPC-3, MiaPaCa-2, and Panc-1 | Ristorcelli et al.36 | ||
MYOF | UC | DLS, TEM, and WB | MDA-MB-231, MDA-MB-468, BT-549, Hs 578 T, MCF7, MCF-10A, ZR-75–1, BT-474, SK-BR-3, and CFPAC-1 | Blomme et al.102 | |
BDG | TEM, WB | Panc1, BxPc3, MiaPaca2, and HPSC | Klein-Scory et al.103 | ||
MIF | UC | NTA | PKCY, PAN02 | Costa-Silva et al.31 | |
UC, SG | TEM, WB | Panc02, Panc02-H7 cells | Yu et al.104 | ||
CLDN4, EPCAM, CD151, LGALS3BP, HIST2H2BE, and HIST2H2BF | UC | WB | 13 human PDAC, 2 non-neoplastic cell lines | Castillo et al.105 | |
PLEC | UC, ExoQuick-TC | DLS, TEM, and WB | PDAC, C6 glioma cells, and HPDE | Shin et al.106 | |
WNT5B | BDG, SG | EM | CHO, Caco-2 cells | Harada et al.46 | |
CCA | UC | TEM, WB | Human bile, H69 cell line | Chaiyadet et al.107 | |
S100A6, LUM, LCP1, YWHAZ, and VIM | UC | TEM | Hamster liver tissue, KKU055 | Khoontawad et al.108 | |
UC | TEM, WB | KKU-100, KKU-M213, and H69 | Dutta et al.42 | ||
Blood cancer | MARCKS | UC, SG | CM, FACS | K562, LAMA84 | Taverna et al.109 |
VCP | UC | TEM | U937, Mec1 | Bosque et al.56 | |
UC | WB, FC | Primary CLL cells | Paggetti et al.110 | ||
DNMT1 and HELLS | UC | NTA, FC | Molm-14, HL-60, and OP9 cells | Huan et al.111 | |
MHC-1, MHC-2, HSC70, HSP90, and ICMA-1 | UC | TEM, WB | Raji cells | Yao et al.40 | |
Oral cancer | ExoQuick | NTA, TEM | HUVEC, SCC15 | Andrade et al.112 | |
NAP1 | Ultrafiltration | NTA, TEM, WB, and CM | CAL 27, SCC-25 | Wang et al.44 | |
HSP90 | UC | TEM, NTA | HSC-3, HSC-3-M3 | Ono et al.113 |
WB western blotting, TEM transmission electron microscopy, NTA nanoparticle tracking analysis, DLS dynamic light scattering, TRPS tunable resistive pulse sensing, FC flow cytometry, CM confocal microscopy
EV proteomes in various cancers and biomarker discovery
Proteomic analysis of EVs has revealed significant changes in protein expression under various physiological and pathological conditions26,29,30. Characterization of these proteomic profiles may be useful in understanding disease pathogenesis and assisting in the discovery of new biomarkers for different diseases. The secretion of EVs from several types of tumor cells is a significant means of conditioning and altering the tumor microenvironment by malignant cells31,32. Multiple studies have reported that the secretion of EVs from cancer cells contributes to angiogenesis, metastasis, tumor formation, and disease progression2,10,31,32. EVs are more attractive sources of biomarkers because of their biological consequences and relatively noninvasive accessibility in a wide range of biological fluids. EVs have been studied in relation to numerous cancers, such as colorectal27,33, bladder34, prostate35, pancreatic36, breast37, gastric38, lung39, blood40, ovarian41, cholangiocarcinoma42, hepatocellular carcinoma43, and oral squamous cell carcinoma44 (Table 2), as well as cardiovascular diseases45 and malignancies of the central nervous system21. The proteomic analysis of EVs, specifically the analysis of their protein composition, may be helpful for further understanding the mechanisms of their biogenesis and their functional roles. Molecular communication between cancer cells and their stromal microenvironment is a key factor for cancer progression46,47. In conjunction with typical secretory pathways, it was proposed that these small membranous vesicles are alternate mediators of intercellular communication19. EVs carry an effector-rich proteome with the ability to control different functional properties of the recipient cell48. The protein composition of EVs from different sources was studied previously by using MS30,49–54, providing a robust basis for the identification of biomarker proteins in EVs for the purpose of quality control research. A thorough understanding of the protein composition of EV subtypes and the extent to which EV composition reflects the source cell composition is essential for further development of diagnostics and therapeutics. Although EVs are secreted by almost all cell types, some available data suggest the enhanced release of EVs under pathological conditions, such as cancer55. It is reasonable to expect that these vesicles may also play key roles in tumorigenesis since they can facilitate distant intercellular communication. Tumor-derived EVs typically carry tumor antigens, and functional proteins can be transferred to recipient cells through EVs23,54,56. A better understanding of the molecular bases underlying cancer invasion and metastasis is necessary to develop effective targets for therapy.
EV proteins from many cancers have similar biological processes and functions. To understand the functions of differentially expressed proteins (DEPs) in cancer, we performed gene ontology analysis on a variety of DEPs57. As expected, the EV–DEPs from different cancer types were implicated in similar biological processes, such as cell adhesion, migration, and transport. Considering that EVs are potential metastasis factors, those proteins appear to be relevant for cancer metastasis or cancer cell proliferation. Of the 12 different cancers evaluated, we observed that DEPs that overlapped more than five times were primarily related to cancer metastasis or cancer cell proliferation, and many of the DEPs had strong interactions with each other (Fig. 2). Even though the selection of these DEPs from different cancers was biased, the roles of EVs in different cancers focused mainly on cell adhesion and cell migration.
Conclusions
In this review, we summarized different EV studies to discuss the potential of EVs in cancer treatment. All studies discussed in this review indicated that the specific protein composition of various EVs has high potential for identifying different cancers. The majority of these studies revealed the relationship of cancer with changes in the protein contents of various body fluids. Moreover, we have highlighted the emerging roles of EVs in cancer, specifically their role in metastasis, which opens the possibility of the rapid translation of EV research for clinical applications in diagnosis, prognosis, and treatment. Ultimately, the majority of the investigations discussed in this review need further verification in large-cohort, multicenter clinical studies. In the future, highly reliable EV proteome data could be combined with well-developed current popular genomic and other “omics-” studies to provide extended knowledge of EVs from the perspective of systems biology approaches.
Future perspectives
There are many perspectives on the potential contribution of EV research for the development of cancer therapeutics and diagnosis. EVs could play key roles in intercellular communication during cancer development, which may offer new therapeutic strategies for various cancers. EV protein composition in different body fluids reveals the overall condition of the patient and is also useful for screening the efficacy and toxicity of anticancer treatments. Additionally, EVs could be used as cancer vaccines and drug delivery components. Moreover, the inhibition of intercellular communication through EVs might provide opportunities to suppress tumor progression. In the near future, clinical applications of EVs could contribute to cancer management and treatment. However, before EV-targeted therapy can be applied in cancer, the identification of cancer-specific genes or molecules that are crucial for EV communication is necessary.
Acknowledgements
This work was supported by a grant from Kyung Hee University in 2017 (KHU-20171191) and the GRRC program of Gyeonggi province [GRRC-kyunghee2018(B03)].
Conflict of interest
The authors declare that they have no conflict of interest.
Footnotes
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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