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The emerging role of extracellular vesicles as biomarkers for urogenital cancers.

1. January 2014

The emerging role of extracellular vesicles
as biomarkers for urogenital cancers
Muhammad Nawaz, Giovanni Camussi, Hadi Valadi, Irina Nazarenko, Karin Ekström, Xiaoqin Wang, Simona Principe, Neelam Shah, Naeem M. Ashraf, Farah Fatima, Luciano Neder and Thomas Kislinger
Abstract | The knowledge gained from comprehensive profiling projects that aim to define the complex genomic alterations present within cancers will undoubtedly improve our ability to detect and treat those diseases, but the influence of these resources on our understanding of basic cancer biology is still to be demonstrated. Extracellular vesicles have gained considerable attention in past years, both as mediators of intercellular signalling and as potential sources for the discovery of novel cancer biomarkers. In general, research on extracellular vesicles investigates either the basic mechanism of vesicle formation and cargo incorporation,
or the isolation of vesicles from available body fluids for biomarker discovery. A deeper understanding of the cargo molecules present in extracellular vesicles obtained from patients with urogenital cancers, through high‐ throughput proteomics or genomics approaches, will aid in the identification of novel diagnostic and prognostic biomarkers, and can potentially lead to the discovery of new therapeutic targets.
Nawaz, M. et al. Nat. Rev. Urol. 11, 688–701 (2014); published online 18 November 2014; doi:10.1038/nrurol.2014.301
University of Sao Paulo, Brazil (M.N., F.F., L.N.). University of Turin, Italy (G.C.). BIOMATCELL VINN Excellence Center of Biomaterials and Cell Therapy, University of Gothenburg, Sweden (H.V., K.E., X.W.). University Medical Center Freiburg, Germany (I.N.). Princess Margaret Cancer Center,
101 College Street, TMDT 9‐807, Toronto, ON M5G 1L7, Canada (S.P., T.K.). Monash University, Australia (N.S.). University of Gujrat, Pakistan (N.M.A.).
Correspondence to: T.K.
Urogenital cancers—cancers of the reproductive and renal organs—are major causes of morbidity and mor- tality worldwide.1,2 The multistage, stochastic and heterogeneous nature of these malignancies, resulting from genetic and epigenetic modifications, poses a fundamental challenge to monitoring. Although surgi- cal treatment and chemotherapy for urogenital cancers have improved in the last decade, the prognoses for these diseases remain poor, as existing tests are not sufficiently sensitive or specific to diagnose urogenital cancers at early stages, and none has been shown to significantly decrease overall mortality. Current diag- nostic procedures include general examinations and biopsies, such as image-guided prostate biopsy,3 cysto- scopy and transurethral resection of the bladder,4 nephrectomy and percutaneous renal tumour biopsies,5 all of which lack sensitivity and can be associated with significant health complications (for example, biopsies are invasive procedures associated with bleeding and risk of infections). Moreover, the location of urogenital cancers deep within the pelvic region makes them hard to access. Thus, in the absence of early symptoms, cancers are diagnosed at an advanced stage, by which time patients have poor outcomes and tumours have often metastasized.
Extracellular vesicles have gained considerable atten- tion in the past 10 years as potential sources for bio- marker discovery. These small (40–5000 nm diameter) membrane-bound vesicles are categorized into exosomes, microvesicles or ectosomes, apoptotic bodies6–10 or Golgi
Competing interests
The authors declare no competing interests.
vesicles11 on the basis of their size, origin, morphology and mode of release. Well-known for biological effects, such as signalling and transfer of cargo, extracellular vesicles are secreted under various pathophysiologic con- ditions into the extracellular environment by a variety of cell types, promoting tumour progression, survival, invasion and angiogenesis,12–17 as well as influencing the immune response, cell-to-cell communication, extracellular matrix degradation, coagulation, stem- cell renewal, cardiovascular functions and resistance to drugs (Figure 1).18–30
Surprisingly, the biomolecular cargo of extracellular vesicles is stable in biological fluids and protected against exogenous RNases and proteases, owing to its encapsula- tion within membrane vesicles,23,31,32 or association with RNA-binding or DNA-binding proteins33–35 or lipo- protein complexes.36,37 Thus, extracellular vesicles might be stable under adverse physical conditions, such as extremes in pH, long-term storage and multiple freeze– thaw cycles,33,38 making them an appealing source for biomarker development.
Several reports indicate that cancer cells release more extracellular vesicles than normal cells,17,39,40 and that the biomolecular cargo (that is, proteins, nucleic acids and lipids) is reflective of the cell of origin.41,42 Consequently, knowledge about the content of extracellular vesicles derived from tumour cells with differing stages of aggression could be used to establish new diagnostic approaches using patient-derived vesicles from body fluids. The detection of biomarkers in body fluids has major advantages over the use of tissue markers, which most often require invasive biopsies that can be diffi- cult to perform and potentially dangerous. Urine-based
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Key points
■ Extracellular vesicles are small (40–5,000 nm diameter) membrane‐bound vesicles that can be categorized into exosomes, microvesicles and apoptotic bodies according to their size, origin, morphology and mode of release
■ Whereas the generation of exosomes involves endocytosis, formation of multivesicular bodies and subsequent membrane fusion, microvesicles are produced by membrane budding and apoptotic bodies result from membrane blebbing during apoptosis
■ Over the past 10 years, various methodologies for the effective isolation of extracellular vesicles have been developed, including centrifugation, affinity capture, precipitation and the use of microfluidic devices
■ Extracellular vesicle cargo is thought to reflect the cell‐type of origin, suggesting it could be a promising source for the discovery of novel biomarkers
tests, in particular, could offer attractive approaches for large-scale screening, as large amounts of urine can be collected longitudinally. Ultimately, discriminating between cargoes associated with extracellular vesicles in body fluids using proteomic and genomic profiling approaches could provide insight into disease staging. An important first step is to develop sensitive, rapid and highly effective strategies to enable the collection of extracellular vesicles, and to adapt standardized procedures for routine clinical diagnostic application.
In this Review, we provide a comprehensive overview of the roles of extracellular vesicles in the most common urogenital cancers (prostate, kidney and bladder). This includes a detailed overview of the current knowledge of the different classes of extracellular vesicles, their biogenesis, potential biological functions and avail- able technologies for isolation and downstream analy- ses. Existing knowledge regarding the cancer-specific biology of extracellular vesicles, and their potential use as vehicles for biomarker discovery, are reviewed and discussed.
Biogenesis of extracellular vesicles
Our current understanding of extracellular vesicles suggests that they comprise a heterogeneous popula- tion of exosomes (40–200 nm diameter), microvesicles (also known as ectosomes, 50–1,000 nm) and apoptotic bodies (50–5,000 nm). The formation of exosomes and microvesicles is proposed to occur via two distinct path- ways, while apoptotic bodies arise as a consequence of indiscriminate membrane blebbing during apoptosis. Golgi vesicles could also be considered as part of the extracellular vesicle populations,11 where their existence in body fluids might be representative of distinct disease states. Clearly, an enhanced knowledge of the different mechanisms that drive the biogenesis of these subpopu- lations could help to identify their utility as diagnostic and therapeutic modalities. Furthermore, in spite of their importance in cellular physiology and disease, little is known about the release of extracellular vesicles and how it is precisely regulated.
Exosomes and microvesicles
The formation of exosomes occurs via endocytosis and internalization of cell-surface receptors into early endosomes. From these structures, proteins and lipids are selectively recruited into recycling endosomes, or targeted for lysosomal degradation by ubiquityl- ation and ubiquitin-dependent interactions with endosomal sorting complexes required for transport (ESCRT-0, ESCRT-I and ESCRT-II).43 Alternatively, they can proceed towards a late-endosomal pathway, dependent on multivesicular bodies (MVBs), which is regulated by a ubiquitin-independent recruitment mechanism, for exosome sorting.44,45 In this pathway, ALIX (ALG-2-interacting protein X, a protein that interacts with ESCRT-III) can bind directly to exosomal
Extracellular vesicles
Exosomes (40–200 nm)
Microvesicles (50–1,000 nm)
Apoptotic bodies (50–5,000 nm)
Sorted in multivesicular endosomes, secreted after fusion of multivesicular bodies with the plasma membrane
Bud from the plasma membrane into the extracellular environment
Figure 1 | Classes of extracellular vesicles. Extracellular vesicles comprise a heterogeneous mixture of exosomes, microvesicles and apoptotic bodies. The biogenesis of these three subtypes differs: microvesicles bud directly from the plasma membrane, whereas exosomes are formed by endocytosis and the subsequent formation of multivesicular bodies, and apoptotic bodies are formed as a consequence of apoptotic disintegration. Extracellular vesicles regulate numerous biological functions, such as cell‐to‐cell communication and horizontal transfer of cargo, and have been implicated in a number of biological pathways.
Generated as a result of apoptotic disintegration, resulting vesicles become part of the extracellular milieu
Biological functions
Cell-to-cell communication, horizontal transfer of cargo Signalling, homeostasis, inflammation and coagulation Immune surveillance
Extracellular matrix degradation
Stem-cell renewal
Cardiovascular functions
Tumour growth and metastasis
Resistance to drugs
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Pathogen, signal or other stimulus
Endocytic pathway
Late endosome, or MVB
Ubiquitin-independent pathway
Golgi apparatus
Rab GTPases
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Endocytic vesicle
Early endosome
Recycling endosome
(ESCRT-0, ESCRT-I, ESCRT-II) Ubiquitin-dependent pathway
Actin motors and cytoskeleton elements
Membrane blebbing and budding
Golgi vesicles
Figure 2 | Extracellular vesicle biogenesis. Extracellular vesicles originate through different mechanisms. a | Exosomes initiate as intraluminal vesicles that are formed by endocytosis in response to pathogens, ligands or other stimuli; these endocytic vesicles mature to early endosomes, and then into late endosomes, or MVBs. Following the ubiquitin‐dependent interactions with ESCRT complexes, MVBs can be sorted for lysosomal degradation or they can fuse with the plasma membrane and be released as exosomes. ALIX binds to MVB cargo, preventing lysosomal degradation and favouring exosomal release. Rab GTPases regulate MVB fusion with the plasma membrane and release of exosomes.
b | Microvesicles are formed by the outward budding and fission of plasma membrane lipid microdomains, which is controlled by regulatory proteins and cytoskeleton elements, that promote membrane curvature at ceramide‐enriched domains (blue bars), resulting in microvesicle budding. After synthesis in the ER, protein cargo is transported to the Golgi apparatus, modified and packaged into small vesicles secreted as transport Golgi vesicles. c | Cells undergoing apoptotic disaggregation produce large membrane blebs, known as apoptotic bodies or apoptosomes. Abbreviations: ALIX, ALG‐2‐interacting protein X; ER, endoplasmic reticulum; ESCRT, endosomal sorting complexes required for transport; MVB, multivesicular body; TSG101, tumour susceptibility gene 101 protein.
cargo molecules, which provides a point of distinction between lysosomal degradation and sorting into exo- somes (Figure 2a).45,46 The ESCRT machinery triggers the formation of vesicles in late-endosomal MVBs,47–50 whereas ceramide-enriched microdomains induce exosome budding through the lateral segregation of cargo within the late-endosomal membrane, protect- ing them from transport to lysosomes.51 Once the late- endosomal cargo is sorted, the constituent exosomes are released to the extracellular environment upon fusion of the limiting membrane of MVBs with the plasma membrane.9,52 The mechanisms that regulate the fusion of MVBs with the plasma membrane are unclear; however, Rab GTPases, such as Rab5 and Rab7, have been shown to regulate endocytic trafficking down- stream of MVB biogenesis and cargo sequestration, whereas Rab27a, Rab27b and Rab35 control the secre- tory pathway and label MVBs for subsequent fusion with the plasma membrane, resulting in the release of exosomes.45,53–55
Microvesicles are produced through membrane- budding processes,22 which follow an ordered pattern: the cellular trafficking of biomolecules towards the cell surface results in membrane protrusion, budding and, finally, the detachment of spherical bodies from specific regions of the plasma membrane enriched in lipid rafts (Figure 2b).56 The formation of microvesicles might share some common features with exosome bio- genesis. For instance, the ESCRT component TSG101, which is involved in the exosomal pathway, is known to interact with arrestin domain-containing protein 1 during microvesicle shedding.57 Another common feature of both types of extracellular vesicle is that their formation is linked to regions of the plasma mem- brane that are enriched in ceramide, cholesterol and lipid rafts. During microvesicle budding, ceramide promotes membrane curvature,58 a process that might resemble abscission steps in cytokinesis and could use actin-based motors.59 Furthermore, the small GTP- binding protein ARF6, well known for its role in cell
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Apoptotic cell
Apoptotic bodies

Table 1 | Summary of extracellular vesicle isolation techniques
Differential centrifugation
Sedimentation based on size and density
Gold standard
Most widely used Suitable for large‐volume isolations
Requires expensive ultracentrifuge
Time consuming
Recovery based on sedimentation efficiency
No absolute separation of vesicle subpopulations
Risk of contamination and formation of protein aggregates
Alvarez et al. (2012)69 Johnstone et al. (1987)164
Density gradient centrifugation
Flotation based on density
Increases the purity by removal of contaminating protein aggregates
Requires expensive ultracentrifuge
Time consuming
Sucrose toxicity might limit downstream functional studies No absolute separation of vesicle subpopulations owing to overlapping density
Tauro et al. (2012)72 Théry et al. (2006)165
Separation based on size
Easy and fast
Small sample volume limitations
Protein contamination
Loss of yield owing to trapping in filter pores
Cheruvanky et al. (2007)78 Merchant et al. (2010)79
Separation based on size
Increases purity and integrity Suitable for isolation from complex biofluids
Requires specialized equipment Small sample volume limitations Time consuming
Chen et al. (2011)80 Lai et al. (2012)81 Taylor et al. (1983)82
Affinity isolation
Separation based on affinity interactions
Increases purity
High specificity to isolate subpopulations
Requires prior knowledge of vesicle characteristics Requires specific antibody
Not suitable for large sample volumes
Captured vesicles might not retain functionality after elution
Chen et al. (2010)84 Clayton et al. (2001)83
Polymeric precipitation
Separation based on PEG precipitation
Quick and relatively cheap High yield
Low purity caused by contamination Low specificity
Burns et al. (2014)166 Rekker et al. (2014)71
Microfluidic devices
Separation based on mechanics of fluid flow
Increases throughput
and allows multiplexing Reduced cost, sample size and processing time
Not applicable to large sample volumes
Chen et al. (2010)84
Abbreviation: PEG, polyethylene glycol.
invasion and actin remodelling,60,61 is thought to regu- late the release of protease-loaded vesicles derived from the plasma membrane.62 Crosstalk between ARF6 and Rho signalling pathways has been implicated in the release of microvesicles,63 and commonalities have been observed between mechanisms governing microvesicle formation and membrane blebbing at the cell surface that increases cell motility by amoeboid projection.64,65 Altogether, these observations indicate that actin motors and elements of the cytoskeleton might be involved in the formation of extracellular vesicles. Consistent with this, Nawaz et al.11 have speculated that extracellular vesicle budding might occur as a result of cell extrusion and membrane blebbing at lipid rafts through ‘spindle rocking’ (previously observed in aberrant cytokinesis66).
Apoptotic bodies
Tumour cells undergoing apoptotic disaggregation can produce apoptotic bodies or apoptosomes6,67—relatively large membrane blebs formed by indiscriminate bleb- bing of the plasma membrane (Figure 2c). Apoptotic bodies contain fragmented nuclei as well as fragmented cytoplasmic organelles, which might be taken up by cells in the tumour microenvironment, thereby influencing the cellular response by transferring their oncogenic contents to recipient cells.68
Analysis of extracellular vesicles
Prior to the biochemical or high-throughput analyses of extracellular vesicles, their rapid and efficient isolation is required. A variety of isolation technologies exist (and
more are being developed), and each technique provides unique advantages and disadvantages depending on the sample source, and the desired yield and purity.
Isolation of extracellular vesicles
Extracellular vesicles can be isolated by many different methods, including differential centrifugation, density gradient centrifugation, ultrafiltration, chromatography, affinity isolation, polymeric precipitation and by the use of microfluidic devices (Table 1). However, no ‘one size fits all’ approach exists, and all available methods have advantages and disadvantages. The method of choice should take into account the sample volume (for example, whether the sample is derived from biofluids or from cell-culture media), the purity, integrity and yield of extracellular vesicles required for specific downstream analysis (such as proteomic analysis or RNA profiling), as well as the available instrumentation and processing time. A comparison of isolation methods for different samples, such as blood plasma, milk, urine and cancer cell culture media, has been previously undertaken.69–74 In addition to the existing, validated methods, novel and developing technologies are available for extracellular vesicle isolation.
Currently, differential centrifugation, with or without size filtration, is the most widely used isolation method. This approach comprises three centrifugation steps: low speed (300–500 g, 5–10 min) to eliminate cells and cell debris; medium speed (10,000–20,000 g, 10–20 min) to
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eliminate larger vesicles; and high speed (100,000 g, 1–3 h) to pellet extracellular vesicles. Important considerations are the rotor type and the viscosity of the sample, which strongly influence the sedimentation efficiency and reso- lution of extracellular vesicle preparations.75–77 To increase the purity of the yield, density gradient centrifugation using sucrose or iodixanol (OptiPrepTM, AXIS–SHIELD, Norway) gradients can be applied as an additional clean-up step, to separate vesicles with different densities.
On the basis of passage through filters with nanopores or micropores, extracellular vesicles can also be isolated by ultrafiltration, which does not require expensive equip- ment.78,79 Although ultrafiltration is rapid, abundant protein contamination and retention of extracellular vesicles in membrane pores are among the factors that decrease extracellular vesicle yield.
Similarly to ultrafiltration, chromatography is used to isolate extracellular vesicles based on the concept that size differences alter their chromatographic retention times.80–82 Although chromatographic isolation increases the purity of the yield, it does not reduce the processing time, and requires specialized equipment.
Affinity isolation
Immunoaffinity isolation can also increase the purity of extracellular vesicles, and enables the selective capture of specific subpopulations. Antibodies against proteins located on the surface of extracellular vesicles are pre- coated on beads or plates to either capture or deplete specific subpopulations of extracellular vesicles, which are isolated by high-affinity interactions with the desired antibody, and further separated by low-speed centrifuga- tion or magnetic-bead techniques.83 Dynabeads®-related products for the isolation of extracellular vesicle sub- populations have been developed by Life Technologies (UK). Chen et al.84 have developed a microfluidic device that contains antibody-coated magnetic beads bound to a magnetic sensor on the surface of the chip, enabling the single-step capture of extracellular vesicles. Balaj et al.85 have also reported a novel affinity isolation method using heparin-coated beads, but the application and validation of this method has been limited to date.
Polymeric precipitation
On the basis of polyethyleneglycol (PEG) precipitation of extracellular vesicles, System Biosciences (USA) have released a commercial isolation kit (ExoQuickTM) that reduces hands-on time and yields high levels of extra- cellular vesicles, although the purity is lower than with some other isolation methods.
Qualitative and quantitative analysis
The characterization, determination of purity and quantification of isolated extracellular vesicles can be performed using various methods, some of which have been used for many years, whereas others are relatively
novel (Table 2). A combination of different methods is often required to overcome some of the challenges related to extracellular vesicle detection, such as their small size and lack of distinct markers. Here, we provide a brief overview of qualitative and quantitative approaches for the analysis of extracellular vesicles. However, for a more comprehensive characterization of extracellular vesicles, additional methods could be used to determine their protein, RNA and lipid content.7,86,87
Electron microscopy techniques are commonly used to visualize extracellular vesicles. The vesicles can be mounted on grids, fixed, stained with a contrast dye and visualized by transmission electron microscopy (TEM).88,89 Furthermore, specific proteins can be visualized using immuno-electron microscopy with gold-labelled antibodies, enabling the detection of subpopulations of extracellular vesicles. However, the dehydration and fixation treatments used for conven- tional TEM might alter the morphology of the vesicles, and certain subpopulations might not adhere to the grid. Cryo-electron microscopy might, therefore, be more suitable for studying the morphology of extra- cellular vesicles,89 as it does not require any fixation or staining, enabling biological specimens to be preserved and visualized to near-atomic resolution. However, the application of cryo-electron microscopy requires highly sophisticated equipment and technical expertise. Other methods to examine the morphology and 3D struc- ture of extracellular vesicles include scanning electron microscopy and atomic force microscopy.90,91
New methods based on light scattering, such as dynamic light scattering and nanoparticle tracking analysis, have emerged for the detection of single exo- somes.92–94 Another instrument that can be used for nanoparticle sizing, enumeration and charge measure- ment is qNanoTM (Izon, New Zealand), which provides a label-free method for detecting charged particles passing through a nanopore via electrophoresis.
The application of flow cytometry to extracellular vesicle characterization has been limited by the existence of some subpopulations that are below the detection range of a conventional cytometer—for which vesicles must be >500 nm—but this limitation can be circumvented by attaching extracellular vesicles to antibody-coated beads, which can easily be detected by conventional flow cytometers.83 This method does, however, preclude the analysis of single extracellular vesicles, as multiple vesicles attach to each bead. Interestingly, a new, fluorescence- based, high-resolution, flow cytometry method is able to detect different subsets of extracellular vesicles and to determine the phenotypes of single entities.95
Surface and/or intravesicular proteins can be analysed using a range of methods, including Western blot, ELISA and extracellular vesicle arrays.96,97 Other sensitive quali- tative and quantitative technologies have been developed to detect extracellular vesicles, such as magnetic-labelled (micronuclear magnetic resonance [μNMR] system) and nonlabelled (nanoplasmonic exosome [nPLEX]) methods, as well as a photosensitizer-bead detection system (ExoScreen).98–100
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Table 2 | Summary of techniques for extracellular vesicle detection and characterization
Size detection range/ detection limit
Size distribution*
Marker detection*
Quantitative methods
1nm to 6μm

Dragovic et al. (2011)92 Gardiner et al. (2013)93 Sokolova et al. (2011)94
70nm to 10μm

Momen‐Heravi et al. (2012)76 Momen‐Heravi et al. (2012)77
Qualitative methods
Western blot and ELISA

Logozzi et al. (2009)97 Raposo et al. (1996)167
Extracellular vesicle array

Jorgensen et al. (2013)96
<1 nm

Raposo et al. (1996)167 Yuana et al. (2013)89
~1 nm

Sharma et al. (2011)90
<1 nm

Sharma et al. (2011)90 Sharma et al. (2010)91
Quantitative and qualitative methods
50nm to 1μm
Dragovic et al. (2011)92 Gardiner et al. (2013)93
Conventional flow cytometry
≥300 nm
<300 nm
(binding with beads)
– –

  • +
    Clayton et al. (2001)83
    Fluorescence high‐ resolution flow cytometry
    ~100 nm

    Nolte‐‘t Hoen et al. (2012)95 Nolte‐‘t Hoen et al. (2013)168
    μNMR system
    50–150 nm

    Shao et al. (2012)99
    nPLEX assay

    Im et al. (2014)98

    Yoshioka et al. (2014)100
    *+ indicates variable can be measured, – indicates it cannot. Abbreviations: AFM, atomic force microscopy; DLS, dynamic light scattering; μNMR, micronuclear magnetic resonance; NTA, nanoparticle tracking analysis; nPLEX, nanoplasmonic exosome; SEM, scanning electron microscopy; TEM, transmission electron microscopy.
    Urogenital cancers
    Cancers of the prostate, kidney and bladder are classi- fied as urogenital cancers. Despite intensive research, no biomarkers are yet available to deliver accurate early detection or precise prognoses. Extracellular vesicles provide a novel target to potentially improve on these shortcomings (Figure 3).
    Prostate cancer
    Prostate cancer is the most commonly occurring cancer in men, but fewer than 20% of those affected will present with lethal disease.1,2 Although the diagnostic regimen of digital rectal examination (DRE) combined with serum PSA screening has considerably improved the early detection of prostate cancers, it has also led to a dramatic increase in overtreatment of the disease. A major clini- cal challenge is to accurately distinguish patients with indolent disease from those with aggressive tumours that require increased intervention. Furthermore, patients who are under active surveillance would benefit from less-invasive monitoring assays to overcome the potential dangers associated with repeated needle biopsies.
    PSA testing is approved by the FDA for diagnosis of prostate cancer, but has a considerable number of limi- tations: it shows a lack of sensitivity and specificity,101 its levels in serum are elevated in some nonmalignant
    conditions and it does not provide a reliable indication about the metastatic potential of prostate cancer cells.102 The FDA has approved a test in urine for the noncoding RNA of prostate cancer antigen 3 (PCA3) as a biomarker for prostate cancer—its upregulation is believed to be an exclusive characteristic of prostate cancer, and it shows improved specificity and sensitivity compared to PSA.103,104 Early prostate cancer antigen (EPCA), an integ- ral nuclear membrane protein unique to the nuclei of prostate cancer cells,105,106 has been proposed as a poten- tial serum biomarker, and protein kinase C α (PKCα)107 as a tissue biomarker for early detection, but these proteins have not, as yet, undergone systematic validation.
    Thus, although the application of next-generation genomic and proteomic technologies to blood, urine and prostate proximal fluids is likely to add new candidates to the already long list of putative RNA, DNA and protein biomarkers identified over decades of research (such as prostatic acid phosphatase, EPCA, glutathione-S- transferase π and α-methylacyl-CoA racemase), most of these require further validation, and they often lack sensitivity and specificity. Alternative strategies for bio- marker discovery are, therefore, required, and extracellu- lar vesicles can be considered a promising source for future investigations. They have gained considerable attention as candidate biomarkers to distinguish between
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    Patient-derived body fluids
    Isolation and identification of extracellular vesicles using sensitive capture platforms
    Determine biomarker relevance:
    ■ Assess tumour type, stage, grade ■ Survival prediction
    ■ Therapeutic response
    Analyte-specific reagent (research use only)
    Clinical tests for validation
    (results must be positive, safe and effective)
    Validation of alternative
    biomarkers with greater sensitivity and specificity
    Biomarker qualification Application for FDA approval
    Accepted application for routine use as clinical biomarker
    Directly to CMS if for research purposes only
    Centers for Medicare and Medicaid Services (CMS)
    have been considered to distinguish patients with pros- tate cancer from healthy subjects,33 and its expression has been associated with an increased Gleason score and advanced pathologic stages.123
    A highly specific and sensitive method known as the proximity ligation assay has been used to quantify levels of prostasomes—extracellular vesicles secreted by epithelial cells in the prostate gland—in the plasma of patients.114 This assay could offer a promising tool for the diagnosis and prognosis of prostate cancer.
    Prostate tissues
    Prostasomes are considered to provide the most accu- rate source of proteomic or transcriptomic biomark- ers for prostate cancer. So far, however, only one study has reported the isolation of extracellular vesicles from metastatic prostate cancer tissue, documenting an altered expression of annexins A1, A3, A5 and dimethylarginine dimethylaminohydrolase 1.124
    Prostate cancer cell lines
    A large number of proteins have been found to associate with extracellular vesicles derived from prostate cancer cell lines (Table 3).110,125–127 However, with the exception of fatty acid synthase, which has also been identified in extracellular vesicles derived from expressed prostatic secretions (EPS) in urine,29 the majority of these pro- teins have not been identified in vesicles derived from urine, serum or plasma, which limits the use of pros- tate cancer cell lines in the identification of potentially useful biomarkers, as they fail to accurately recapitulate this disease.26
    Prostate proximal fluids and urine
    Prostate proximal fluids, such as seminal fluid and EPS, contain considerable amounts of extracellular vesicles and hence could represent ideal fluids for the discov- ery of extracellular-vesicle-derived biomarkers. To date, however, few systematic biomarker discovery studies have been conducted using these fluids.26,28,29,128 At present, the lack of a systematic, high-quality biobanking system for prostate proximal fluids is a limiting factor, but this is expected to change in the future, following the approval of the PCA3 diagnostic test in 2012, which uses post-DRE urine that contains EPS.
    An in-depth proteomic study carried out in 2013 identified 877 exosomal proteins derived from EPS in urine, 14 of which were most-readily detectable in extracellular vesicles (Table 3).29 Furthermore, urine- derived extracellular vesicles comprise a rich source of N-glycoproteins, as they originate from the endocytic pathway.26 In a comprehensive study, >25 key N-linked glycan species were found to be associated with extra- cellular vesicles derived from EPS in urine, with levels that varied according to disease status.129
    Other studies have also investigated the proteomic cargo of prostate-derived extracellular vesicles from urine.130–133 Increased levels of α1-integrin and β1- integrin were found in urine exosomes of patients with metastatic prostate cancer, compared with patients
    Figure 3 | Multistep validation of biomarkers from extracellular vesicles. A potential flowchart for the validation and clinical implementation of biomarkers based on extracellular vesicles. The flowchart shows a step‐by‐step process by which the profiling and discovery of exosomal cargo molecules could ultimately be translated into a clinically applicable biomarker signature. At each step defined goals and criteria must be met in order to proceed to the next level.163
    indolent and aggressive forms of prostate cancer, and multiple studies have documented the presence of prostate-derived extracellular vesicles in body fluids as well as in prostate cancer cell lines and tissue.102,108–117
    Extracellular vesicles isolated from plasma harbour pro- teins specific to prostate cancer, such as phosphatase and tensin homolog (PTEN) and survivin. PTEN has been detected in patients with prostate cancer but not in plasma of healthy subjects, and survivin has been shown to be present at higher levels in the plasma of patients with prostate cancer compared with patients with BPH, or healthy individuals.118,119
    Plasma extracellular vesicles have also been shown to contain a rich repertoire of RNA species. In the context of urological cancers, extracellular vesicles containing microRNA (miRNA) have attracted the most interest.120 Interestingly, higher levels of miRNA were observed in plasma vesicles compared with vesicle-depleted super- natant,121 suggesting either increased stability or selective packaging of miRNAs into extracellular vesicles. Bryant and colleagues122 reported the differential expression of 12 miRNAs associated with extracellular vesicles in the serum and plasma of patients with prostate cancer (Table 3). miR-141 and miR-375 were among 11 miRNAs that were found at significantly higher levels in extra- cellular vesicles obtained from the serum of patients with metastatic, compared with nonmetastatic, prostate cancer.122 Elevated levels of miR-141 in plasma or serum
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Table 3 | Candidate biomarkers for prostate cancer derived from extracellular vesicles
Ultracentrifugation, Western blot, immunofluorescence
Gabriel et al. (2013)118
Ultracentrifugation, Western blot, ELISA
Khan et al. (2012)119
miR‐107, miR‐130b, miR‐181a‐2, miR141, miR‐301a, miR‐326, miR‐331‐3p, miR‐375, miR‐432, miR‐574‐3p, miR‐22110, miR‐625
Plasma, serum and urine
ExoMiR extraction, filtration, qRT‐PCR
Bryant et al. (2012)122
Ultracentrifugation, gel filtration chromatography, 2D–PAGE, mass spectrometry (MALDI–TOF)
Ronquist et al. (2010)124
CDCP1, CD151, CD147
Ultracentrifugation, mass spectrometry (LC–MS/MS), bead immuno‐isolation, Western blot
Sandvig et al. (2012)127
EPS‐urine PCCL
Ultracentrifugation, mass spectrometry (LC–MS/MS) Centrifugation, sucrose gradient, mass spectrometry (LC–Q–TOF)
Principe et al. (2013)29 Utleg et al. (2003)116
Ultracentrifugation, mass spectrometry (LC–MS/MS)
Duijvesz et al. (2013)125
Ultracentrifugation, mass spectrometry (LC–MS/MS)
Principe et al. (2013)29
Ultracentrifugation, mass spectrometry (LC–MS/MS), Western blot, flow cytometry
Bijnsdorp et al. (2013)130
Ultracentrifugation, immunoprecipitation, Western blot, electron microscopy
Lu et al. (2009)131
N‐linked glycans
Ultracentrifugation, mass spectrometry (MALDI–TOF)
Nyalwidhe et al. (2013)129
TMPRSS2–ERG, PCA3 transcripts
Urine EPS‐urine
Ultracentrifugation, filtration, sucrose gradient, PCR Centrifugation, filtration, RT‐PCR, gene expression
Khan et al. (2012)119 Dijkstra et al. (2014)134
Abbreviations: 2D‐PAGE, 2D polyacrylamide gel electrophoresis; ACPP, prostatic acid phosphatase; ANPEP, aminopeptidase N; ANX, annexin; AZGP1, zinc‐alpha‐2‐glycoprotein; CDCP, CUB domain‐containing protein 1; CLSTN1, calsyntenin‐1; DDAH1, dimethylarginine dimethylaminohydrolase 1; DDP4, dipeptidyl peptidase‐4; ENO1, enolase‐1; EPS, expressed prostatic secretions; FASN, fatty acid synthase; FLNC, filamin‐C; FOLH1, folate hydrolyase 1; G3BP, galectin 3 binding protein; GDF15, growth/differentiation factor 15; ITG, integrin; KLK, kallikrein; LC–MS/MS, liquid chromatography–mass spectrometry; LC–Q–TOF, liquid chromatography, quadrupole, time‐of‐flight; LGALS3, galectin‐3; LTF, lactotransferrin; MALDI–TOF, matrix‐assisted laser desorption/ ionization–time‐of‐flight mass spectrometry; miR, microRNA; MME, neprilysin; PCA3, prostate cancer antigen 3; PCCL, prostate cancer cell line; PDCD6IP, programmed cell death 6‐interacting protein; PSA, prostate‐specific antigen; PSCA, prostate stem cell antigen; PSMA, prostate‐specific membrane antigen; PTEN, phosphate and tensin homolog; qRT‐PCR, quantitative reverse transcription PCR; SEMG1, semenogelin‐1; TGM4, protein‐glutamine gamma‐glutamyltransferase 4; TIMP1, tissue inhibitor of matrix metalloproteinase 1; TMPRSS2, transmembrane protease serine 2; XPO‐1, exportin‐1.
with nonmetastatic disease or those with BPH.130 Like- wise, δ-catenin associated with extracellular vesicles has been found at high levels in urine,131 whereas prostate- specific membrane antigen and prostate stem cell antigen have also been identified in urine-derived exosomes of patients with prostate cancer.26,29,129 In addition to exo- somal protein markers, some transcriptomic changes have also been identified, including those affecting the expression of TMPRSS2 and, of course, PCA3.112,134 Urine and EPS-enhanced urine are suitable clinical samples for the isolation of extracellular vesicles owing to their ease of collection and considerable protein content.129 Furthermore, the composition of urine is far less complex than that of blood, providing a sample type that is straightforward to analyse by current proteomic techno- logies. Further studies are needed to validate whether the content of extracellular vesicles derived from patients with prostate cancer provides a source, so far relatively unexplored, for the discovery of novel biomarkers.
Kidney cancer
Accounting for 3% of all human cancers, renal cell carcinoma (RCC) has a high frequency of relapse and a mortality rate that reaches >40%.135 RCC subtypes include clear cell, papillary, chromophobe and collect- ing duct RCC—clear cell RCC (ccRCC) accounts for 75–80% of all renal tumours.136 An accurate diagno- sis of RCC subtype is critical, as the different subtypes have different biological features and clinical outcomes
and, consequently, different prognoses and responses to therapy. In the absence of reliable biomarkers to facili- tate early detection, diagnosis mainly relies on the renal histopathological profiles.
Most biomarkers so far identified are related to angio- genesis, which has a critical role in RCC development and progression. In ccRCC, hypermethylation or muta- tion of the von Hippel–Lindau (VHL) tumour suppres- sor gene frequently occurs (in 35–57% of cases), leading to altered regulation of the hypoxia-inducible factor (HIF1 and HIF2) genes and consequent constitutive activation of angiogenesis.137 Attempts to correlate the levels of expression of carbonic anhydrase IX (CAIX), β-catenin and HIF2α with the progression and sever- ity of RCC have been made, but these proteins have not yet been fully confirmed as reliable biomarkers for the diagnosis of RCC. Studies comparing the miRNA expres- sion profiles of normal and RCC tissue specimens have shown that miRNAs that target tumour suppressors are upregulated, whereas those that target oncogenes are downregulated in RCC, as has been reviewed previ- ously.138 The dysregulation of miRNAs has profound biological implications, as they target molecules impli- cated in RCC progression, such as PTEN, VHL, HIF, vascular endothelial growth factor (VEGF) and mam- malian target of rapamycin (mTOR). These observations have prompted studies aimed at identifying miRNAs within the circulation and urine of patients with RCC, which have been reviewed elsewhere.138 An analysis of
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Table 4 | Candidate biomarkers for kidney cancer derived from extracellular vesicles
VEGF, FGF, angiopoietin 1, ephrin‐A3, MMP‐2, MMP‐9
Cancer stem cells
Ultracentrifugation, flow cytometry, immunohistochemistry
Grange et al. (2011)14
miR‐200c, miR‐92, miR‐141, miR‐19b, miR‐29a, miR‐29c, miR‐650, miR‐151
Cancer stem cells
Ultracentrifugation, microarray analysis, qRT‐PCR
Grange et al. (2011)14
Fas ligand, Bcl2‐L‐4
RCC cells
Centrifugation, filtration, flow cytometry, Western blot, ELISA
Yang et al. (2013)145
Lysophosphatidylethanolamine metabolite
Ultracentrifugation, mass spectrometry (LC–MS/MS)
Del Boccio et al. (2012)146
MMP‐9, ceruloplasmin, PODXL, DKK4, CAIX
Ultracentrifugation, OptiprepTM density gradient, mass spectrometry (LC–MS/MS), Western blot
Raimondo et al. (2013)147
Abbreviations: Bcl2‐L‐4, apoptosis regulator BAX; CAIX, carbonic anhydrase IX; DKK, Dickkopf‐related protein; FGF, fibroblast growth factor; LC–MS/MS, liquid chromatography–mass spectrometry; miR, microRNA; MMP, matrix metalloproteinase; PODXL, podocalyxin; qRT‐PCR, quantitative reverse transcription PCR; RCC, renal cell carcinoma; VEGF, vascular endothelial growth factor.
circulating serum miRNAs revealed that a small subset of 36 miRNAs were upregulated not only in the serum, but also in tissue samples of patients with RCC.139 As miR-378 is overexpressed in RCC serum, it has been proposed as a potential biomarker,140 but with conflict- ing results.141 Another miRNA that is highly expressed in the serum of patients with RCC, the levels of which have been shown to decrease after surgery, is miR-210, which is directly upregulated by HIF.142 The levels of miR-15a are upregulated in the urine of patients with ccRCC, but downregulated in patients with oncocytoma, suggesting that this biomarker shows tumour-subtype specificity.143
Extracellular vesicles in RCC
The pathogenic role of extracellular vesicles has been extensively investigated in several cancers, but few studies have addressed their role in RCC. Extracellular vesicles released from renal cancer stem cells were shown to influ- ence the tumour microenvironment, thereby promoting angiogenesis, tumour invasion and premetastatic niche formation in the lungs,14 whereas those from differen- tiated tumour cells did not display these properties. Comparative studies of RNA species from these two dif- ferent extracellular vesicle sources revealed that those from cancer stem cells were enriched in mRNAs encod- ing proteins involved in angiogenesis, such as fibroblast growth factor, VEGF, ephrin-A3, angiopoietin 1 and matrix metalloproteinase (MMP)-2 and MMP-9; addi- tionally, 24 miRNAs were significantly upregulated and 33 miRNAs were downregulated in extracellular vesi- cles from these cells compared with extracellular vesicles from differentiated tumour cells.14 The targets of these miRNAs, as predicted by gene ontology analysis, have been implicated in the regulation of cell proliferation, transcription, nucleic-acid binding, expression of adhe- sion molecules and metabolic processes. In particular, extracellular vesicles derived from renal stem cells were enriched in miR-29c, miR-19b and miR-151, which are also overexpressed in RCC, miR-92, miR-141 and miR-200c, which are significantly upregulated in several cancers, and miR-29a, miR-151 and miR-650, which are associated with tumour invasion and metastases.138,144 Extracellular vesicles derived from RCC have been
proposed to favour immune evasion as they contain Fas ligand, and induce apoptosis of T cells by increasing the levels of caspases and apoptosis regulator BAX (Bcl2-L-4), and decreasing the levels of apoptosis regulator Bcl-2.145
Few studies have addressed the potential use of uri- nary extracellular vesicles as a diagnostic tool for RCC. A comparative analysis of urinary extracellular vesicles performed using a hyphenated microLC-Q-TOF-MS (capillary liquid chromatography, quadrupole, time-of- flight mass spectrometry) platform demonstrated a differ- ential lipid composition between the exosomes of patients with RCC and those of healthy control subjects.146 Pro- teomic analysis of urinary extracellular vesicles has facilitated the identification of an RCC-specific ‘finger- print’, containing proteins such as MMP-9, podocalyxin (PODXL), Dickkopf-related protein 4 (DKK4), carbonic anhydrase IX (CAIX) and ceruloplasmin (Table 4).147 These preliminary studies suggest that urinary extra- cellular vesicles could provide a tool for identifying new biomarkers for RCC, although further studies are needed.
Bladder cancer
Bladder cancer is one of the five most frequent malignan- cies in developed countries and, among genitourinary tract malignancies, is second only to prostate cancer.1 Early diagnosis of non-muscle-invasive papillary tumours fol- lowed by early treatment significantly improves prognosis, whereas prognosis is less favourable when muscle invasion is present at the time of diagnosis. Invasive bladder carci- nomas show elevated resistance to chemotherapy, and, therefore, have a high recurrence rate, with high patient mortality.148 Constant surveillance of these patients is required, and is carried out by combining cystoscopy, an invasive and costly, but very sensitive technique, with urinary cytology, which is specific, but less sensitive. As early diagnosis and monitoring of bladder cancer is critical, the discovery of new, sensitive biomarkers is of paramount importance. Cytology can be improved by combination with either an immunofluorescence assay that detects mucins associated with exfoliated bladder cells,149 or with in situ hybridization, which can detect aneuploidy in chromosomes 3, 7 and 17, and loss of the 9p21 locus of the tumour suppressor gene p16.150
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Table 5 | Candidate biomarkers for bladder cancer derived from extracellular vesicles
Resistin, GTPase NRas, MUC4, EPS8L1, EPS8L2,EHD4,G3BP,RAI3,GSA
Ultracentrifugation, in‐gel digestion, mass spectrometry (LC–MS/MS)
Smalley et al. (2008)30
TACSTD2 (one of 107 candidates, 24 validated)
Ultracentrifugation, flow cytometry, mass spectrometry (LC–MS/MS, MRM‐MS), ELISA
Chen et al. 2012)25
β1 and α6 integrins, CD36, CD44, CD73, CD10, MUC1, basigin, 5T4
Ultracentrifugation, flow cytometry, in‐gel digestion, mass spectrometry (MALDI–TOF/TOF)
Welton et al. (2010)157
Ultracentrifugation, sucrose/D2O cushion, mass spectrometry (LC–MS/MS)
Beckhan et al. (2014)158
Ultracentrifugation, NanoSight, microarray, PCR
Perez et al. (2014)159
Abbreviations: 5T4, trophoblast glycoprotein; D20, deuterium oxide; EDIL‐3, epidermal growth factor (EGF)‐like repeat and discoidin I‐like domain‐containing protein 3; EHD4, EH domain‐containing protein 4; EPS8L, epidermal growth factor receptor kinase substrate 8‐like protein; G3BP, galectin 3‐binding protein; GALNT, N‐acetylgalactosaminyltransferase; GSA, α subunit of GsGTP binding protein; LASS2, LAG1 longevity assurance homolog 2; MALDI–TOF, matrix‐assisted laser desorption/ionization–time‐of‐flight mass spectrometry; MRM‐MS, multiple reaction monitoring‐mass spectrometry; MUC, mucin; RA13, retinoic acid 13; TACSTD2, tumour‐associated calcium‐signal transducer 2.
A number of urinary biomarkers have been investi- gated. Proteomic analysis has revealed that levels of the nuclear mitotic apparatus protein 1 (NUMA1) are significantly elevated in the urine of patients with bladder cancer compared with normal subjects.151 Several studies have found that the immunoassay used to detect NUMA1 is more sensitive than cytologic evaluation, ranging from 60% to 90%, as previously reviewed.152 However, the specificity is significantly lower, owing to a number of interfering conditions, such as haematuria, inflammation and infections, which might give rise to false-positive results.153 Another extensively studied urinary biomarker is bladder tumour antigen (BTA, identified as human complement factor H-related protein), the test for which has been used in the screening of a population of patients with suspected bladder cancers, as well as in surveillance for recurrence, but which should not be used as absolute evidence for the presence of bladder cancer, as several conditions not related to tumours might generate false- positive results. Fragments of cytokeratins 8, 18 and 19 released into the urine and detected by ELISA have also been evaluated as biomarkers of bladder cancer, but the specificity and sensitivity of the results have been discordant, as reviewed elsewhere.152 Elevated urinary levels of the antiapoptotic protein survivin and the nuclear transcription factors BLCA-1 and BLCA-4 have also been detected with high sensitivity and speci- ficity in patients with bladder cancer. However, these assays all require a more precise definition of the cut-off values, and better standardization, before entering into clinical use.
Profiling of gene mutations could also provide diag- nostic and/or prognostic information for bladder cancer. Mutation of TP53 (which encodes p53) in bladder cancer cells has been associated with a highly aggres- sive phenotype,154 whereas mutation of FGFR3 (which encodes the fibroblast growth factor receptor 3) has been associated with a low tumour grade and low risk of recurrence.155 Another promising marker is the gene encoding the mitosis regulator Aurora kinase A—a high degree of amplification of this gene has been associated with high tumour grade.156
Diagnostic potential of extracellular vesicles
In bladder cancer, extracellular vesicles released into urine from the bladder carry the signature of the tumour cells of origin, and can, therefore, be exploited as diagnostic factors. The proteomic profiles of extra- cellular vesicles in the urine of patients with bladder cancer have previously been characterized. Smalley et al.30 identified several proteins that were present at elevated levels in extracellular vesicles that are poten- tially involved in tumour progression, including com- ponents of the epidermal growth factor (EGF) pathway, the α subunit of the G protein Gs, resistin and retinoic acid protein 3. Welton et al.157 extended the proteomic studies of urinary extracellular vesicles with gene onto- logy analysis, as well as demonstrating a strong associ- ation of the identified proteome with exosomes derived from a bladder cancer cell line (Table 5). On the basis of proteomic analysis in extracellular vesicles, Chen et al.25 proposed that tumour-associated calcium-signal transducer 2 (TACSTD2) has diagnostic value as a bio- marker owing to its presence at high levels in patients with bladder cancer.
Tumour cells release extracellular vesicles that influ- ence surrounding or distant cells, and that might, therefore, transfer cargo that can modify the pheno- types of recipient cells.13 Extracellular vesicles derived from bladder cancer might promote cancer progres- sion by delivering the protein EGF-like repeat and discoidin I-like domain-containing protein-3 (EDIL-3), an integrin ligand implicated in angiogenesis.158 Extra- cellular vesicles have been shown to transfer genetic information between cells, as they carry functional RNA transcripts, implying that the extracellular vesicle tran- scriptome might contain markers for the cell of origin. In 2014, Perez et al.159 investigated the potential applica- tion of the RNA content of urinary extracellular vesicles (Table 5) in the diagnosis of bladder cancer. Using micro- array technology followed by PCR validation, they gener- ated a list of differentially expressed genes in urinary extracellular vesicles from patients with cancer com- pared with those from cancer-free controls. LASS2 and GALNT1, which encode proteins involved in cancer pro- gression and metastasis, were found only in extracellular
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    This work was supported by a Movember Discovery grant from Prostate Cancer Canada (D2013‐21) and by the Canada Research Chair Program to T. Kislinger. M. Nawaz, F. Fatima and L. Neder acknowledge funding from FAPESP (Sao Paulo Research Foundation, Proc. No. 12/24574‐3) and CAPES (Coordination for the Improvement of Higher Education Personnel). K. Ekström and X. Wang are supported by The Swedish Research Council (K2012‐52X‐09495‐25‐3), the BIOMATCELL VINN Excellence Center of Biomaterials and Cell Therapy, the Stiftelsen Handlanden Hjalmar Svensson Foundation and the Magnus Bergvalls Foundation.
    G. Camussi acknowledges funding from
    Associazione Italiana per la Ricerca sul Cancro (AIRC) IG2012 n. 12890.
    Author contributions
    All authors contributed equally to discussions of content, writing the article and reviewing and editing the manuscript before submission.
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