International Journal of

Molecular Sciences

Review
Extracellular Vesicles as Potential Bladder Cancer Biomarkers:
Take It or Leave It?
Ana Teixeira-Marques 1,† , Catarina Lourenço 1,2,3,4,† , Miguel Carlos Oliveira 1 , Rui Henrique 1,5,6
and Carmen Jerónimo 1,6, *

1 Cancer Biology and Epigenetics Group, Research Center of IPO Porto (CI-IPOP)/RISE@CI-IPOP
(Health Research Network), Portuguese Oncology Institute of Porto (IPO Porto)/Porto Comprehensive
Cancer Center Raquel Seruca (Porto.CCC Raquel Seruca), 4200-072 Porto, Portugal
2 i3S-Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135 Porto, Portugal
3 INEB—Instituto Nacional de Engenharia Biomédica, Universidade do Porto, 4200-135 Porto, Portugal
4 Doctoral Programme in Biomedical Sciences, School Medicine and Biomedical Sciences,
University of Porto (ICBAS-UP), 4050-313 Porto, Portugal
5 Department of Pathology, Portuguese Oncology Institute of Porto (IPOPorto), 4200-072 Porto, Portugal
6 Department of Pathology and Molecular Immunology, School of Medicine & Biomedical Sciences,
University of Porto (ICBAS-UP), 4050-313 Porto, Portugal
* Correspondence: carmenjeronimo@ipoporto.min-saude.pt
† These authors contributed equally to this work.

Abstract: Bladder cancer (BC) is the 10th most frequently diagnosed cancer worldwide. Although urine
cytology and cystoscopy are current standards for BC diagnosis, both have limited sensitivity to detect
low-grade and small tumors. Moreover, effective prognostic biomarkers are lacking. Extracellular
vesicles (EVs) are lipidic particles that contain nucleic acids, proteins, and metabolites, which are
released by cells into the extracellular space, being crucial effectors in intercellular communication.
These particles have emerged as potential tools carrying biomarkers for either diagnosis or prognosis
in liquid biopsies namely urine, plasma, and serum. Herein, we review the potential of liquid
Citation: Teixeira-Marques, A.;
biopsies EVs’ cargo as BC diagnosis and prognosis biomarkers. Additionally, we address the emerging
Lourenço, C.; Oliveira, M.C.;
advantages and downsides of using EVs within this framework.
Henrique, R.; Jerónimo, C.
Extracellular Vesicles as Potential
Bladder Cancer Biomarkers: Take It
Keywords: bladder cancer; liquid biopsies; extracellular vesicles; biomarkers; lncRNA; protein; miRNA
or Leave It? Int. J. Mol. Sci. 2023, 24,
6757. https://doi.org/10.3390/
ijms24076757
1. Introduction
Academic Editors:
1.1. Bladder Cancer
Francesca Diomede,
Jacopo Pizzicanella and
1.1.1. Epidemiology and Biology
Oriana Trubiani Bladder cancer (BC) ranks as the 10th most common malignancy worldwide, showing
a high incidence in regions with a high human development index, such as Europe and
Received: 22 February 2023
North America, in which it constitutes the fourth most common cancer in men and ninth
Revised: 22 March 2023
most common in women [1,2]. Because life expectancy has risen globally and BC mostly
Accepted: 29 March 2023
afflicts the elderly, the incidence has increased over the last 20 years [3]. Furthermore,
Published: 4 April 2023
given such demographic trends, its global health burden is likely to further grow in
the near future [1]. BC diagnosis depends on the transurethral resection of the bladder
tumor (TURBT), enabling the complete removal of visible lesions under direct cystoscopic
Copyright: © 2023 by the authors. examination [4]. This technique may be complemented with urine cytology, often used as
Licensee MDPI, Basel, Switzerland. an ancillary procedure for BC detection.
This article is an open access article Most BCs originate in the urothelium, the epithelial tissue that lines the lumen of
distributed under the terms and bladder and urinary organs, making urothelial carcinoma the most common type of BC
conditions of the Creative Commons (90% of all cases) [5]. The disease may be further stratified based on the tumor’s ability to
Attribution (CC BY) license (https:// invade the muscle layer. Non-muscle-invasive BC (NMIBC) comprises about 70% of newly
creativecommons.org/licenses/by/ diagnosed tumors, while the remaining 30% are muscle-invasive BC (MIBC). Importantly,
4.0/).

Int. J. Mol. Sci. 2023, 24, 6757. https://doi.org/10.3390/ijms24076757 https://www.mdpi.com/journal/ijms

Int. J. Mol. Sci. 2023, 24, 6757 2 of 19

BC has long been recognized as a heterogenous and complex disease, presenting multiple
features that challenge clinicians and researchers.

1.1.2. Current Hurdles and Disease Management

Concerning NMIBC, frequent recurrence and progression (up to 50–70% and 10–30%,
respectively) constitute the major clinical problems [6–8]. Because patients enduring relapse
and/or progression cannot be prospectively identified, rigorous and, in many cases long-
term, surveillance is required [8–12]. Indeed, currently available patient risk stratification
parameters, solely reliant on clinicopathological variables, are imperfect and incapable of
portraying the true heterogeneity and complexity of BC [8,9,13]. Consequently, BC is the
costliest cancer to treat on a per-patient basis, particularly driven by periodic and invasive
cystoscopies, leading to a significant financial burden to healthcare systems [8,14–18].
Furthermore, there is considerable patient morbidity, as cystoscopies frequently originate
anxiety, pain, hematuria, and even urinary tract infections [19,20]. Urine cytology, although
noninvasive and reliable (90–95% specificity), shows low sensitivity (30–50%) for BC
detection, and, consequently, cystoscopy cannot be spared to check for recurrences during
patients’ follow-up [21–23]. Whereas alternative urine tests have been developed, such as
bladder tumor antigen (BTA) and Nuclear Matrix Protein 22 (NMP22) assessment, showing
higher sensitivity (50–70%), the specificity remains suboptimal (60–90%); therefore, these
are not recommended at present since they do not obviate the need for cystoscopy [21,23,24].
The identification of novel, accurate, cost-effective, and noninvasive cancer biomarkers
has, thus, become a fundamental goal of research on NMIBC [17]. In addition to addressing
the aforementioned shortcomings, the implementation of novel biomarkers in clinical
practice might also provide improved risk stratification, identifying which patients might
benefit from further therapeutic interventions, as well as those with low-risk disease who
should be spared excessive interventions. Overall, these should allow for the design of
more effective follow-up strategies, enabling the earlier detection of disease recurrence and
progression, and simultaneously reducing morbidity due to frequent monitoring.
MIBC lies on the opposite side of the spectrum. This is an aggressively invasive and
rapidly metastatic disease, carrying a high mortality risk (40–60% 5-year survival) [25]. The
major clinical problem is treatment failure due to inaccurate patient selection, prompting
unnecessary costs to the patient and the healthcare system [9]. This may be attributed to the
lack of adequate tools for patient selection and, consequently, treatment is mostly offered
as “one size fits all” [9,26]. Similar to NMIBC, the identification of accurate and predictive
biomarkers for therapy response would improve patient outcome and avoid ineffective
treatment in probable nonresponders [9].

1.2. Extracellular Vesicles (EVs): A New Source of BC Biomarkers in Liquid Biopsy

Liquid biopsies have been gaining increasing attention in recent years. They encom-
pass the minimally or noninvasive sampling of biological fluids, such as plasma, serum, or
urine, and their contents are a potential source of biomarkers. Importantly, they are a mini-
mally or noninvasive, fast, and affordable means of acquiring relevant clinical information,
enabling earlier diagnosis as well as real-time disease monitoring, and granting a person-
alized snapshot of disease evolution—a core prerequisite of precision medicine [27–32].
Compared to tumor tissue samples, the gold standard for diagnosis and prognostication,
liquid biopsies may be performed in a serial manner, providing a better understanding of
disease evolution over time, more accurately reflecting the diversity of tumor subclones,
and providing a wider and more complete picture of the tumor, an attribute of particular
relevance in heterogenous cancers such as BC [29,31].

1.2.1. EVs’ Biogenesis

EVs are a heterogenous population of lipid enclosed structures abundantly present
in body fluids [33]. According to their mechanism of assembly, they may be classified
into three main categories: exosomes (30–150 nm, formed by the fusion of multivesicular
Int. J. Mol. Sci. 2023, 24, 6757 3 of 19

bodies with the plasma membrane); microvesicles (100–1000 nm, generated by direct
budding from the cell membrane); and apoptotic bodies (50–5000 nm, released during
programmed cell death) [34–36]. EVs found in liquid biopsies likely represent a mixture of
vesicles originating from all three biogenesis pathways, with considerable size and density
overlap among them [36]. As currently available purification methods are incapable of fully
discriminating according to their biogenesis, the use of the generic term EV is recommended
by the Minimal Information for Studies of Extracellular Vesicles (MISEV) guidelines [37].

1.2.2. EVs’ Physiological and Pathological Role

EVs have emerged in recent years as key mediators of paracrine and endocrine inter-
cellular communication in both physiological and pathological processes. They serve as
vehicles for the transfer and delivery of proteins, lipids, DNA, RNA, and metabolites to
recipient cells, shielded from degradation by the lipid bilayer membrane [28,34,36,38,39].
This mechanism is acknowledged to play a leading role in tumorigenesis. Specifically,
through the transfer of protumoral cargo, EVs may stimulate cell proliferation, promote
angiogenesis, induce drug resistance, modulate the microenvironment, and support the
establishment of premetastatic niches [28,36,40–44]. For instance, EVs from BC cells internal-
ized by macrophages promote their polarization into protumoral macrophages, enhancing
the release of immunosuppressive cytokines, which facilitates tumor progression [45]. Ad-
ditionally, the transfer of EVs’ lncRNAs and miRNAs from cancer-associated fibroblasts to
BC cells showed chemotherapy resistance modulation [46,47]. Moreover, proteins derived
from EVs of BC cells increased angiogenesis and the migration of BC cells as well as en-
dothelial cells, also facilitating cancer progression [48,49]. These studies provide evidence
of EVs and its cargo’s protumoral influence in BC.
Considering the aforementioned mentioned challenges in the management of BC
patients, especially the lack of accurate biomarkers for early detection and prognostication,
we explore in this review the published literature on the potential of BC-EV-derived
biomarkers as a noninvasive tool to assist in the clinical management of BC patients, as
well as the limitations of such studies.

2. Methods
For this review, a PubMed database search was performed on 15 January 2023, using
the query: (Extracellular vesicles OR Exosomes OR Microparticle) AND (Bladder Cancer
OR Bladder Neoplasm) AND (Biomarkers OR Transcriptome OR Molecular Markers)
AND (Blood OR Plasma OR Serum OR Urine), with no time interval restraints. Only
original records published in English were considered (reviews were excluded). Records
were first screened through critical abstract evaluation, followed by full-text read-outs
and the selection of those providing meaningful information regarding the topic to be
included in the final analysis. A flow chart summarizing the methodology is provided
in Figure 1. Information regarding the biomarkers depicted in the different studies is
illustrated in Tables 1–4, with Figure 2 summarizing the candidate biomarkers’ distribution
among different biofluids. Moreover, Figure 3 presents an overview regarding the isolation
methods used in the review studies. Regarding the tables, the patient cohorts’ designation
given by the authors was, when possible, maintained, regardless of its size or goal. If the
cohort’s name was not defined by the authors, we considered cohort 1, 2, or 3 depending
on the number of independent cohorts used in the study. Furthermore, the term healthy
control (HC) comprises the denominations “healthy control”, “healthy”, “control”, or
“healthy donor” used by the original authors. The designation “benign lesions” was used
whenever a patient had a lesion suspected to be cancerous that, upon initial assessment,
turned out to be a nonmalignant condition. Benign urological diseases comprise benign
pathologies such as urinary lithiasis, benign prostate hyperplasia, obstructive uropathy,
and nonspecified benign conditions of urologic origin. Only the best outcomes are shown,
except when multiple markers and/or panels are worth mentioning owing to different
 study. Furthermore, the term healthy control (HC) comprises the denominations “healthy
control”, “healthy”, “control”, or “healthy donor” used by the original authors. The
designation “benign lesions” was used whenever a patient had a lesion suspected to be
cancerous that, upon initial assessment, turned out to be a nonmalignant condition.
Int. J. Mol. Sci. 2023, 24, 6757
Benign urological diseases comprise benign pathologies such as urinary lithiasis, benign4 of 19
prostate hyperplasia, obstructive uropathy, and nonspecified benign conditions of
urologic origin. Only the best outcomes are shown, except when multiple markers and/or
panels are worth mentioning owing to different advantages/benefits in performance
advantages/benefits
measures. in performance
Finally, regardless measures. Finally,
of the denomination usedregardless of the in
by the authors denomination
the original
used by the authors in the original manuscripts,
manuscripts, the term EV was used in this review. the term EV was used in this review.

Int. J. Mol. Sci. 2023, 24, x FOR PEER REVIEW 10 of 19

Figure 1. Flow
Figure 1. Flow diagram
diagram summarizing the methodology
summarizing the methodology used
used in
in this
this review.
review.

Figure 2.
Figure 2. Distribution
Distribution of
of extracellular-vesicle-derived
extracellular-vesicle-derived bladder
bladder cancer
cancer biomarkers
biomarkers within
within urine
urine and
and
plasma/serum biofluids. Numbers represent the number of BC-EV biomarker studies. Created
plasma/serum biofluids. Numbers represent the number of BC-EV biomarker studies. Created with with
BioRender.com.
BioRender.com.
Int. J. Mol. Sci. 2023, 24, 6757 5 of 19

Table 1. miRNAs with potential in the management of bladder cancer patients.

Study Cohort miRNA Levels SN (%) SP (%) AUC Clinical Significance

Urine
Strømme et al. miR-486-5p Prognosis:
41 NMIBCs and 15 HCs ↑ - - -
2021 [50] miR-451a pre- vs. postsurgery
Discovery: miR-516a-5p 72.9 89.9 0.79 Diagnosis:
6 NMIBCs, 6 MIBC, and 4 HCs ↑ BC vs. HC
Lin et al. 74.1 90.2 0.838
2021 [51]
Validation: miR-93-5p Diagnosis:
90.5 60.6 0.769
32 NMIBCs, 21 MIBCs, and 51 HCs MIBC vs. NMIBC
miR-96-5p 80.4 91.8 0.85
El-Shal et al. 22 NMIBCs, 29 MIBCs, miR-183-5p 78.4 81.6 0.83 Diagnosis:
↑
2021 [52] 21 benign lesions, and 28 HCs BC vs. HC
Combined panel:
88.2 87.8 0.878
miR-96-5p and miR-183-5p
Baumgart et al. Validation: Diagnosis:
miR-146b-5p ↑ - - -
2019 [53] 17 NMIBCs and 20 MIBCs MIBC vs. NMIBC
6 BC and 3 HCs
Matsuzaki et al. Diagnosis:
Validation: miR-21-5p ↑ 75.0 95.8 0.90
2017 [54] BC vs. HC
18 NMIBCs, 18 MIBCs, and 24 HCs
Detection: Diagnosis:
miR-146a ↑ - - -
Andreu et al. 4 BCs and 4 HCs low-grade NMIBC vs. HC
2016 [55] Validation: Diagnosis:
miR-375 ↓ - - -
27 NMIBCs, 7 MIBCs, and 9 HCs high-grade NMIBC vs. HC
Plasma/Serum
Diagnosis:
- - -
Cohort 1: BC vs. HC
miR-4644 ↑
Yan et al. 3 BCs and 3 HCs Prognosis:
- - -
2020 [56] ↑ with tumor stage
Cohort 2: miR-4298 - - - Diagnosis:
↓
25 NMIBCs, 32 MIBCs, and 25 HCs BC vs. HC
miR-4669
Yin et al. Diagnosis:
3 NMIBCs, 60 MIBCs, and 59 HCs miR-663b ↑ - - -
2019 [57] BC vs. HC
Abbreviations: AUC—area under the curve; BC—bladder cancer; EAU—European Association of Urology; HC—healthy control; NMIBC—non-muscle-invasive bladder cancer;
MIBC—muscle-invasive bladder cancer; miRNA—microRNA; RFS—recurrence-free survival; PFS—progression-free survival; SN—sensitivity; SP—specificity; vs.— versus; ↑—higher;
↓—lower.
Int. J. Mol. Sci. 2023, 24, 6757 6 of 19

Table 2. lncRNAs with potential in the management of bladder cancer patients.

Study Cohort lncRNA Levels SN (%) SP (%) AUC Clinical Significance

Urine
Cohort 1:
Chen et al. 4 BCs and 3 HCs Diagnosis:
TERC ↑ 78.65 77.78 0.836
2022 [58] Validation: BC vs. HC
105 NMIBCs, 23 MIBCs, 46 benign lesions, and 94 HCs
Abbastabar ANRIL 46.67 87.5 0.7229 Diagnosis:
et al. 20 NMIBCs, 10 MIBCs, and 10 HCs ↑
PCAT-1 43.33 87.5 0.7292 BC vs. HC
2019 [59]
Combined panel: Diagnosis:
Screening: ↑ 62.5 85.0 0.813
MALAT1, PCAT-1, and SPRY4-IT1 BC vs. HC
61 NMIBCs, 43 MIBCs, and 104 HCs
Zhan et al.
2018 [60] PCAT-1 ↑ - - -
Prognosis:
Validation:
↓ RFS in NMIBC
50 NIMBCs, 30 MIBCs, and 80 HCs
MALAT1 ↑ - - -
Plasma/Serum
Training: Combined panel: Diagnosis:
↑ 80.0 75.0 0.826
Zhang et al. 56 NMIBCs, 44 MIBCs, and 100 HCs PCAT-1, SNHG16, and UBC1 BC vs. HC
2019 [61] Validation: Prognosis:
UBC1 ↑ - - -
84 NMIBCs, 76 MIBCs, and 160 HCs ↓ RFS
Diagnosis:
74.07 78.08 0.851 BC vs. HC and benign
Wang et al. 52 BCs, 52 benign H19 ↑ urologic diseases
2018 [62] urologic diseases, and 52 HCs
Prognosis:
- - -
↑ survival
Zheng et al. Diagnosis:
41 NMIBCs, 9 MIBCs, and 50 HCs PTENP1 ↓ 65.4 84.2 0.743
2018 [63] BC vs. HC
Xue et al. Diagnosis:
15 NMIBCs, 15 MIBCs, and 30 HCs UCA1 ↑ 80.0 83.33 0.878
2017 [64] BC vs. HC
Abbreviations: AUC—area under the curve; BC—bladder cancer; HC—healthy control; lncRNA—long noncoding RNA; NMIBC—non-muscle-invasive bladder cancer; MIBC—muscle-
invasive bladder cancer; RFS—recurrence-free survival; SN—sensitivity; SP—specificity; vs.— versus; ↑—higher; ↓—lower.
Int. J. Mol. Sci. 2023, 24, 6757 7 of 19

Table 3. Proteins with potential in the management of bladder cancer patients.

Study Cohort Protein Levels SN (%) SP (%) AUC Clinical Significance

Urine
Discovery:
Suh et al. 19 NMIBCs, 5 MIBCs, and 12 HCs Combined panel: Diagnosis:
↑ 88.0 81.3 0.845
2022 [65] Validation: Cofilin-1, ITIH2, and Afamin BC vs. HC
75 NMIBCs, 20 MIBCs, and 25 HCs
Discovery:
4 BCs pre- and postsurgery Diagnosis:
Lee et al. a2M ↑ 93.3 34.8 0.809 BC vs. benign urologic
2022 [66] Validation: diseases
57 NMIBCs, 2 MIBCs, and 22 benign urologic diseases
Cohort 1:
9 BCs and 4 HCs Diagnosis:
Igami et al. Combined panel: ↑ 81.82 97.87 0.907 BC vs. HC andBenign
2022 [67] Cohort 2: CEACAM1, CEACAM5, and CEACAM6 urologic diseases
31 BCs, 18 benign urologic diseases, and 29 HCs

Discovery: HSP90 82.5 70.0 0.813

Tomiyama et al. 3 NMIBCs, 4 MIBCs, and 4 HCs Diagnosis:
SDC1 ↑ 82.5 63.3 0.785
2021 [68] BC vs. HC
Validation:
20 NMIBCs, 20 MIBCs, and 30 HCs
MARCKS 65.0 80.0 0.772
Cohort 1:
Lee J. et al. 5 NMIBCs, 4 MIBCs, and 8 HCs MUC1, CEACAM-5, - - - Diagnosis:
↑
2018 [69] Validation: EPS8L2, and Moesin BC vs. HC
4 NMIBCs, 2 MIBCs, and 6 HCs
Diagnosis:
- - - BC vs. HC and other
Lin et al. 70 BCs, 59 ureter or renal pelvis cancers, 17 UTIs, 25 PCas, and H2B1K ↑ urologic diseases
2016 [70] 20 HCs α1AT
Prognosis:
- - -
↑ with grade and stage
Discovery:
Chen et al. 9 BCs and 9 hernias Diagnosis:
TACSTD2 ↑ 73.6 76.5 0.80
2012 [71] Validation: BC vs. hernia
28 BCs, 12 hernias, 5 hematurias, and 3 UTIs
Resistin, GTPase Nras,
Smalley et al. EPS8L1, EPS8L2, RAI3, Diagnosis:
4 BCs and 5 HCs ↑ - - -
2008 [72] Mucin 4, EHC4EH, and BC vs. HC
α subunit of GsGTP-binding protein
Abbreviations: A2M—alpha-2 macroglobulin; AFM—afamin; APOA1—apolipoprotein A-I; AUC—area under the curve; BC—bladder cancer; CD5L—CD5 antigen-like protein;
CDC5L—cell division cycle 5-like protein; CEACAM—carcinoembryonic-antigen-related cell adhesion molecules; CFL1—cofilin-1; EPS8L2—Epidermal growth factor receptor kinase
substrate 8-like protein 2; FGB—fibrinogen beta chain; HC—healthy control; ITIH2—inter-alpha-trypsin inhibitor heavy chain H2; NMIBC—non-muscle-invasive bladder cancer;
MIBC—muscle-invasive bladder cancer; PCa—prostate cancer; TACSTD2—tumor-associated calcium signal transducer 2; SN—sensitivity; SP—specificity; UTI—urinary tract infection;
vs.— versus; ↑—higher; ↓—lower.
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Table 4. Other and/or combined biomarker studies with potential in the management of bladder cancer patients.
4. Other and/or combined Table
biomarker 4. Other
studies withand/or combined
potential inwith
the biomarker
management studies with potential
of bladder cancer in the management of bladder cancer patients.
Table
Table 4. Other
Table
and/or
4. Other
combined
and/or
biomarker
combined studies
biomarker
with studies
potential in the
potential
management
in the management
of bladder ofpatients.
cancer
bladder
patients.
cancer patients.
Study Cohort Biomarker Levels SN (%) SP (%) AUC Clinical Significance
Study Cohort Biomarker Levels SN (%) SP (%) AUC Clinical S
Study Study Study Cohort
Cohort Cohort Biomarker
Biomarker Biomarker Levels
Levels SNLevels (%) SN (%)
Urine SP
SN(%) (%) SP
AUC
SP(%) (%) AUC Clinical
AUC Significance Clinical
ClinicalSignificance
Significance
Urine
UrineUrine Urine mRNA
mRNA
mRNA Combined mRNA
panel:
mRNA Combined panel: ↑
Combined panel: Combined panel:
STARD3NL, RPLP0, SF3A1, DDX17, RPL19, ↑
Zhu et al. Combined panel: STARD3NL, RPLP0, ↑ SF3A1,↑DDX17, RPL19, Diagnosis:
Zhu et 11 al.NMIBCs, 24STARD3NL,
MIBCs, and RPLP0,
35STARD3NL,
HCs SF3A1,AUP1,
RPLP0,
DDX17, SF3A1,
RPL19,
CIT, PWP1,DDX17, RPL19,
SLC46A3, ↑ SNX27, BICD2, - - 0.898 Diag
Zhu et al. Zhu et al. 2021 [73] STARD3NL,
11 NMIBCs, RPLP0, SF3A1,and
24 MIBCs, DDX17, RPL19, AUP1,
35 HCs AUP1, CIT, PWP1, SLC46A3, SNX27, BICD2, - Diagnosis:
- Diagnosis: BC vs. HC
0.898
Zhu et al. 11 NMIBCs, 11 NMIBCs,
2411MIBCs, 24
NMIBCs, MIBCs,
and
2021 [73] 24
35 MIBCs,
HCs and AUP1,
35 HCs CIT, PWP1,
AUP1, SLC46A3,
CIT, PWP1,
SNX27,
ARL4C, SLC46A3,
BICD2, SNX27, BICD2,
PNMA5, EIF3CL, PPP2R2A, MT-ATP8, - - -- 0.898- 0.898 Diagnosis: BC v
2021 [73] 2021 [73] CIT, PWP1, SLC46A3, SNX27, BICD2, ARL4C, ↓ - 0.898 BC vs. HC BC
BCvs.
vs.HC
ARL4C, PNMA5, EIF3CL, PPP2R2A, MT-ATP8, Ⴕ
2021 [73] and 35 HCs ARL4C, PNMA5,ARL4C,
EIF3CL,PNMA5,
PPP2R2A,
EIF3CL,
MT-ATP8,
COL1A1 PPP2R2A,
Ⴕ, CD248 MT-ATP8,
Ⴕ, and PCGF5 Ⴕ Ⴕ↓ HC
Int. J. Mol. Sci. 2023, Int.
24, xJ.FOR
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Sci. 2023, 24,
REVIEW x FOR
PNMA5, PEER
EIF3CL,REVIEW
PPP2R2A, MT-ATP8, COL1A1 , COL1A1 Ⴕ↓ Ⴕ, CD248 Ⴕ, andႵ↓
PCGF5 Ⴕ 8 o
CD248 Ⴕ,, CD248
COL1A1 CD248ႵႵ, and PCGF5 Ⴕ ↓
Ⴕ, andႵ,PCGF5
andCOL1A1
PCGF5
Yazarlou et al. 59 BCs, 24 HCs, and 25 benign Diagnosis:
Yazarlou et al. 59 BCs, 24 HCs, and 25 benign MAGE-B4 ↑ 71.7 66.7 0.67 Diag
Yazarlou et al. Yazarlou et 59al.
BCs, 5924
2018 HCs,
BCs, 59and
24
[74] BCs,25and
HCs, 24benign
HCs,
25 andurologic
25 benign diseases MAGE-B4 ↑ 71.7 Diagnosis: 0.67
66.7 Diagnosis: BC vs. HC
Yazarlou et al. 2018 [74] MAGE-B4
urologic diseases MAGE-B4 ↑ 71.7↑ 66.7
71.7 0.67
66.7 0.67 Diagnosis: BC v
2018 [74] 2018 [74] benigndiseases
urologic urologic
urologic diseases MAGE-B4 ↑ 71.7 66.7 0.67 BC vs. HC BC vs. HC
2018 [74] Cohort4.1:Other and/or BC vs. HC
diseases Table Table
Cohort 1: 4. Other
combined and/or
biomarker combined
studies biomarker
with studies
potential in thewith potential
management in the
of management
bladder cancer of bladder
patients. cancer patients.
PerezCohort
et al. 1: Cohort 1: 5 BCs and 6 HCs GALNT1, LASS2, Diagnosis:
Cohort Perez
1: et al. 5 BCs and 6 HCs GALNT1, LASS2, ↑ - - - Diag
Perez et al. Perez etStudy
al. 5 BCs[75]
2014 and 6 HCs 5 BCs and Cohort
Study 6 HCsValidation: GALNT1, LASS2,
Cohort GALNT1,Biomarker
LASS2,
ARHGEF39, and↑ FOXO3Biomarker Levels ↑ SP (%)SN-(%) AUC SP Diagnosis:
SN (%) Levels -(%) AUC-Diagnosis:
Clinical Significance Clinical S
BC vs. HC
5 BCs and2014 6 HCs [75] Validation: ARHGEF39, and- FOXO3 ↑ -- -- - BC v
2014 [75]
Perez et 2014
al. [75] Validation: Validation:3 BCs and 3 HCs GALNT1,
ARHGEF39, LASS2,
and
ARHGEF39,
FOXO3 and FOXO3 ↑ Urine - Urine - - BC vs. HC Diagnosis:
BC vs. HC
2014 [75] 3 BCs and 3 HCs
ARHGEF39, and FOXO3 BC vs. HC
3 BCsValidation:
and 3 HCs 3 BCs and 3 HCs mRNA mRNA
3 BCs and 3 HCs Combined biomarker
Combined biomarker
Combined
Combined panel:
biomarker
Combined Combined
biomarker panel:
Combined biomarker ↑ ↑ Diagnosis:
STARD3NL, RPLP0, STARD3NL,
SF3A1,
Combined DDX17, RPLP0,
panel: SF3A1, DDX17, RPL19,
RPL19, ↑ 88.5 83.3 0.924 Diag
Zhu et al. Zhu et al. Training: Combined panel: ↑ 88.5 Diagnosis: 0.924
83.3 Diagnosis:
Diagnosis: BC vs. HC Diag
11
Training: NMIBCs, 24 11
MIBCs, NMIBCs,
and 35 24
HCs MIBCs,
CombinedAUP1,
and 35CIT,
HCs
panel: PWP1,
Combined AUP1,
SLC46A3,
panel:
Training: panel: mRNA—KLHCC7B, CASP14,
Combined
CIT, ↑
PWP1,
SNX27,
↑ and 88.5
SLC46A3,
BICD2, PRSS1 ↑ SNX27, 83.3
88.5
BICD2, - 0.924
83.3 - 0.924
- 0.898 - 0.898Diagnosis: BC v
2021 [73] Training:2021 [73] Training:
9 NMIBCs, 1 MIBC, and 10 HCsARL4C, PNMA5, EIF3CL, mRNA—KLHCC7B, CASP14, 88.5PRSS1
and 83.3 0.924 BC vs. HC BC vs.BC HCvs. HCDiagnosis: BC v
Huang
9 NMIBCs,et al.1Huang
MIBC, 9 mRNA—KLHCC7B,
NMIBCs, 1 mRNA—KLHCC7B,
MIBC, andCASP14,
10 HCs and ARL4C,
PRSS1
CASP14,
lncRNA—MIR205HG PNMA5,
PPP2R2A,
and PRSS1 EIF3CL,
MT-ATP8,
and GAS5 PPP2R2A,
Ⴕ Ⴕ↓
MT-ATP8, 87.2 83.3 0.91 BC vs. HC Diag
Huang et al. Huang et 9 NMIBCs,
al. 20211[76] MIBC,
9 NMIBCs,
and 10 1and
et al.
HCs
MIBC, and 10mRNA—KLHCC7B,
HCs CASP14, and PRSS1
Ⴕ,lncRNA—MIR205HG
Ⴕ↓ Ⴕand
Ⴕ↓
GAS5 Ⴕ Ⴕ↓
87.2 Diagnosis: 0.91
83.3 Diagnosis:MIBC vs. NMIBC
Huang et al. 10 HCs lncRNA—MIR205HG
lncRNA—MIR205HG andCOL1A1
lncRNA—MIR205HG
and
GAS5GAS5 Ⴕ
Ⴕ, CD248 and COL1A1
and
GAS5 PCGF5 Ⴕ, CD248
↓Ⴕ Ⴕ, and
87.2 ↓ PCGF5 Ⴕ
83.3
87.2 0.91
83.3 0.91 Diagnosis: MIBC v
2021 [76] 87.2 - 83.3 - 0.91 - vs. NMIBC
MIBC MIBC vs. NMIBC
2021 [76] 2021 [76]
2021 [76] Yazarlou et al. Validation: MIR205HG - - MIBC
- vs. NMIBC Prognosis:
Yazarlou
59 BCs, et 24
al. HCs, and 59 25 BCs,
benign24Validation:
HCs, and 25 benign MIR205HG - -- ↓ 71.7 -- - 0.67 66.7 Diagnosis: Diag
Prog
Validation: Validation: MIR205HG MIR205HG MAGE-B4GAS5 MAGE-B4 ↑ -↓↑ - 66.7 71.7- Prognosis: 0.67 Prognosis:
2018 [74] Validation:
2018 [74] 64urologic
NMIBCs, 16 MIBCs,
diseases
64 NMIBCs,
and 80 diseases
urologic HCs
16 MIR205HG
MIBCs, and 80 HCs ↓ GAS5 ↓ - - - -- BC vs. HC↓ PFS
- Prognosis: BC↓v
64 NMIBCs, 1664MIBCs,
64 NMIBCs, NMIBCs,
16and 16
MIBCs,80MIBCs,
HCs and 80 HCs GAS5 GAS5 ↓ - -- -- - ↓ PFS ↓ PFS
GAS5 ↓ PFS Diagnosis:
and 80 HCs Cohort 1: Cohort 1: Combined panel: - 80.0- 86.4 - 0.899 Diag
Combined panel: 80.0 Diagnosis: 0.899
86.4 Diagnosis: BC vs. HC
Perez etAmuran
al. et al. Perez et al. 5 BCs and 6 HCs Combined
5 BCs and 6 HCs panel: Combined EVs
GALNT1,panel:
miRNA—miR-139-5p,
LASS2, GALNT1, LASS2, 80.0 86.4
80.0 0.899
86.4 0.899 Diagnosis: Diag
BC v
Amuran 43 et al.
NMIBCs, 16 MIBCs, and Combined
34 HCs panel: EVs miRNA—miR-139-5p, ↑ ↑ - ↑ - - - - - Diagnosis:
Amuran et al. Amuran2014 et al.[75]
2020 [77] 43 NMIBCs,EVs 16 miRNA—miR-139-5p,
MIBCs, and EVs34miRNA—miR-139-5p,
HCs miR-136-3p, and miR-19b1-5p 80.0 ↑86.4 0.899 BC vs. HC BC vs. HC
Amuran et al. 43 NMIBCs, 43 NMIBCs,
1643MIBCs, 2014
16
NMIBCs, [75]
MIBCs,
and 16
34 Validation:
MIBCs,
HCs and 34 HCs EVs Validation:
miRNA—miR-139-5p, ARHGEF39, and FOXO3 ARHGEF39,
↑ and FOXO3
↑ BC BCHC
vs. vs. HCDiagnosis: BC v
2020 [77] miR-136-3p,↑ and miR-19b1-5p 93.3 95.5 0.976 Diag
2020 [77]
2020 [77]2020 [77] and 34 HCs 3 BCs and 3 HCs miR-136-3p,
3 BCs and 3 and
HCsmiR-136-3p,
miR-19b1-5p
miR-136-3p, and miR-19b1-5p and
Circulating miR-19b1-5p
Protein—ApeRef1, BC4, and CRK 93.3 Diagnosis:
95.5 Diagnosis:
0.976 low-risk patients vs. HC
Circulating Protein—ApeRef1, 93.3 BC4, and CRK Diagnosis:
Circulating
Circulating Protein—ApeRef1,
Circulating Protein—ApeRef1,
Protein—ApeRef1, BC4,
BC4, andand
CRK CRK BC4, and CRK 93.3 95.5
93.3 0.976
95.595.5 0.976 0.976 patients
low-risk low-risk
vs. HCpatients vs. HC
low-risk pa
Cohort 1: Combined
HOTAIR, HOX-AS-2, biomarker Combined biomarker low-risk patients vs.Diagnosis:
HC
Cohort 1: HOTAIR, HOX-AS-2, ↑ - - - Diag
Cohort
Cohort 1: 1: Cohort 1:8 MIBCs and 5 HCs HOTAIR,
HOTAIR, HOX-AS-2,
HOX-AS-2,HOTAIR, HOX-AS-2,
MALAT, SOX2, and ↑ - Diagnosis:
- -Diagnosis:
Diagnosis:
8 MIBCs and 5 HCs MALAT, ↑ ↑ OCT4 - ↑ OCT4-
SOX2, panel:
and -- 88.5 -- - 83.3 88.5- 0.924 - 83.3 Diagnosis: BC vs. HC Diag
BC v
8 MIBCs
8 MIBCs
Berrondo etandand
al. 5MIBCs
58HCs HCs and 5 HCs MALAT,
MALAT, SOX2, and
SOX2, OCT4
MALAT,
and OCT4 Combined
SOX2, and OCT4 panel: Combined ↑ ↑ BC vs. HC 0.924BCvs.
BC vs.HCHC
Berrondo et al.Training: Cohort 2: Training: BC vs. HC BC v
Berrondo et al.Berrondo Cohort 2: mRNA—KLHCC7B, mRNA—KLHCC7B,
CASP14, and PRSS1 CASP14, and PRSS1
Berrondo et al. et al. 2016Cohort [78]
Cohort 2:2016
9 2:
NMIBCs,Cohort 2:8 MIBCs and
10 5HCs
HCs
2016Huang
[78] et8 al. Huang et al. 1 MIBC,
[78] 9 NMIBCs,
and 1 MIBC, and 10 HCs HYMA1, LINC00477, Ⴕ↓ Ⴕ ↑ Ⴕ↓ Diagnosis: Diagnosis: Diag
2016 [78]
2016 [78] 8 MIBCs
MIBCs andand58HCs HCs and 5 HCsCohort 83:MIBCs
5MIBCs and 5 HCslncRNA—MIR205HG
HYMA1, LINC00477,
HYMA1, LINC00477,
LOC100506688,
and HYMA1,
GAS5 Ⴕ LINC00477,
lncRNA—MIR205HG
and OTX2- AS1
and GAS5 87.2 -
↑
83.3 87.2-
-
0.91 83.3 -
Diagnosis:
-
0.91
-Diagnosis:
Diag
2021 [76] 2021 [76] HYMA1,
CohortLINC00477,
3: ↑↑
LOC100506688, ↑
and- OTX2- -
AS1 -- -- - - - Diagnosis: BC vs. HC
MIBC vs. NMIBC MIBC v
BC v
Cohort
Cohort 3: 3: Cohort 3: 10 MIBCs and LOC100506688,
7 HCs
LOC100506688, LOC100506688,
and and OTX2-
OTX2- AS1AS1 and OTX2- AS1 - - - - BC
- vs. HC -BC
BCvs.
vs. HC
HC
Validation: Validation:
10 MIBCs and 7 HCs MIR205HG MIR205HG Prognosis: Prog
1010MIBCs
MIBCs and and10
7 HCs
7MIBCs
HCs and 7 HCs ↓ ↓
64 NMIBCs, 16 MIBCs, 64 NMIBCs,
and 80 HCs 16 MIBCs, and 80 HCs GAS5 GAS5Plasma Plasma - - - - - - ↓ PFS ↓
Plasma PlasmamiRNA and piRNA
miRNA and piRNA Diagnosis:
Sabo et al. miRNA
Combinedand piRNA
miRNA Combined
panel: and piRNApanel: Diagnosis: Diag
Sabo et 39 al. NMIBCs, 8 MIBCs, and 46 HCs miR-126-3p ↑ 80.0 - 86.4 80.0- 0.899 86.4- 0.899
BC vs. HC Diag
BC v
Sabo et al. SaboAmuran
et al. et2020al. [79] Amuran et al. 39 NMIBCs, 8 MIBCs, and 46 HCs EVs miRNA—miR-139-5p, miR-126-3p
EVs miRNA—miR-139-5p, ↑ - Diagnosis:
- -Diagnosis: G3 tumors vs. HC
39 NMIBCs, 8 MIBCs,39 NMIBCs, and
432020 46
8 MIBCs,
[79]
NMIBCs, HCs and4346NMIBCs,
16 MIBCs, HCs34 HCs
and miR-126-3p
16 MIBCs, and 34 HCs miR-126-3p ↑ - ↑ ↑ -- -↑- - G3 tumo
2020 [79] 2020 [79]
2020 [77] 2020 [77] miR-136-3p, and miR-19b1-5p
miR-136-3p, and miR-19b1-5p G3 tumors vs. G3
HC tumors vs. HC
Diagnosis: Diag
CirculatingBC4,
Circulating Protein—ApeRef1, Protein—ApeRef1,
and CRK BC4, and CRK93.3 95.5 93.3 0.976 95.5 0.976
low-risk patients vs.low-risk
HC pa
Cohort 1: Cohort 1: HOTAIR, HOX-AS-2,HOTAIR, HOX-AS-2, Diagnosis: Diag
↑ - ↑ - - - - -
8 MIBCs and 5 HCs 8 MIBCs and 5 HCs MALAT, SOX2, and MALAT,
OCT4 SOX2, and OCT4 BC vs. HC BC v
Berrondo et al. Berrondo et al.Cohort 2: Cohort 2:
Int. J. Mol. Sci. 2023, 24, 6757 9 of 19

Table 4. Cont.

Study Cohort Biomarker Levels SN (%) SP (%) AUC Clinical Significance

Plasma
miRNA and piRNA
Diagnosis:
miR-126-3p ↑ - - -
G3 tumors vs. HC
Diagnosis:
- - -
MIBC vs. HC
miR-4508 ↓ Diagnosis:
- - - ↑ according to EAU risk
Sabo et al. 39 NMIBCs, 8 MIBCs, class
2020 [79] and 46 HCs
Diagnosis:
piR-5936 ↑ - - - ↑ according to EAU risk
class
miR-185-5p - - -
↓ Prognosis:
miR-106a-5p ↓ survival
miR-10b-5p ↑ - - -
Urine and Serum
Urine
- - -
18 BCs and 14 HCs
Chen et al.
PRMT5 ↑ Diagnosis:
2018 [80] Serum
BC vs. HC
23 NMIBCs, 48 MIBCs, - - -
and 36 HCs
Abbreviations: AUC—area under the curve; BC—bladder cancer; EAU—European Association of Urology; HC—healthy control; NMIBC—non-muscle-invasive bladder cancer;
MIBC—muscle-invasive bladder cancer; miRNA—microRNA; piRNA—piwi-interacting RNA; PFS—progression-free survival PCa—prostate cancer; SN—sensitivity; SP—specificity;
vs—versus; ↑—higher; ↓—lower.
 Figure 2. Distribution of extracellular-vesicle-derived bladder cancer biomarkers within urine and
plasma/serum biofluids. Numbers represent the number of BC-EV biomarker studies. Created with
Int. J. Mol. Sci. 2023, 24, 6757 10 of 19
BioRender.com.

Figure 3. Summary of extracellular vesicle isolation methods that were used in BC articles, con-
Figure 3. Summary of extracellular vesicle isolation methods that were used in BC articles,
cerning urine, plasma, and serum. Numbers represent the number of BC-EV biomarker studies.
concerning urine, plasma, and serum. Numbers represent the number of BC-EV biomarker studies.
Abbreviations:
Abbreviations: BC—Bladder
BC—Bladder cancer;
cancer; EVs—extracellular
EVs—extracellular vesicles.
vesicles. Created
Created with
with BioRender.com.
BioRender.com.
3. EVs in BC
3. EVs in BC Biomarkers in BC
3.1. miRNA
3.1. miRNA
AfterBiomarkers
performingin BC
a miRNA array and qRT-PCR analysis in urinary EVs (uEVs),
After et
Andreu performing a miRNA
al. highlighted arrayand
miR-375 andmiR-146a
qRT-PCR asanalysis
diagnosticin markers
urinary EVs (uEVs),
of high-grade
Andreu et al. highlighted
and low-grade miR-375 and
BC, respectively [55].miR-146a as diagnostic
Moreover, Matsukazimarkers of high-grade
et al. identified and
miR-21-5p
low-grade BC,valuable
as a highly respectively [55]. Moreover,
biomarker Matsukazi
for BC diagnosis et al. identified
(sensitivity, miR-21-5p 95.8%),
75.0%; specificity, as a
highly valuable biomarker
also disclosing for in
higher levels BCuEVs
diagnosis (sensitivity,
from BC 75.0%;
patients with specificity,
negative urine95.8%), also
cytology [54].
El-Shal et al. chose up-regulated EV-derived miRNAs previously reported in the literature
to develop a diagnostic panel for BC, with high specificity (87.8%) and sensitivity (88.2%)
for detecting BC using combined levels of miR-96-5p and miR-183-5p, which also correlated
with clinicopathological features [52].
Combining high-throughput sequencing and miRNA BC tissue levels from the TCGA
database, uEV-derived miRNA candidates were validated with qRT-PCR in an independent
cohort, resulting in the identification of both miR-93-5p and miR-516a-5p as potential BC
diagnostic biomarkers. Interestingly, miR-93-5p also discriminated MIBC from NMIBC [51].
Using the next-generation sequencing of matched urine and serum-EV-derived miRNA
from BC patients pre- and postsurgery, Strømme et al. identified two miRNAs in uEVs
(miR-451a and miR-486-5p) that were significantly up-regulated in presurgery samples from
T1 patients compared to postsurgery check-up samples. Moreover, no differential miRNA
levels were found in the serum of these patients. This study suggests that uEV-derived
miR-451a and miR-486-5p are potential biomarkers of recurrence-free survival in T1 BC [50].
Baumghart et al. sought to refine MIBC patient selection for radical surgical treatment.
Thus, uEVs were isolated and the results were compared with those of formalin-fixed
paraffin-embedded (FFPE) tumor tissues. MiR-146b-5p and miR-155-5p were up-regulated
in MIBC patients compared to NMIBC, indicating that they discriminate MIBC from
NMIBC [53].
Concerning studies exploring plasma, Yin et al. showed that miR-663b levels assessed
with qRT-PCR were elevated in BC patients [57]. Additionally, Yan et al. isolated EVs with
size exclusion chromatography (SEC) and demonstrated that miR-4644 was up-regulated
in BC compared to HC [56].
Int. J. Mol. Sci. 2023, 24, 6757 11 of 19

3.2. lncRNA Biomarkers in BC

Contrarily to the studies on EVs’ proteins and miRNAs, that usually carried out
cargo profiling, EV-derived lncRNA studies focused mostly on evaluating the potential
of preselected candidates. For instance, Zhan et al. isolated uEVs using the Exosomal
RNA Isolation Kit (Norgen), and by performing RT-qPCR, they assessed the levels of eight
lncRNAs in a training set. A final panel for BC detection comprising the lncRNAs MALAT1,
PCAT-1, and SPRY4-IT1 showed a superior AUC (0.813) compared to urine cytology (0.619)
in a validation set. Furthermore, PCAT-1 and MALAT1 levels were associated with shorter
recurrence-free survival in NMIBC patients [60]. Using a commercial RT-qPCR precipitation,
Abbastabar et al. found that T1 and T2 BC patients displayed higher ANRIL and PCAT-1
levels in uEVs compared to HC, achieving 46.67 % sensitivity and 87.5% specificity for
ANRIL and 43.3% sensitivity and 87.5% specificity for PCAT-1 [59]. In another study,
using sequencing for RNA profiling, Chen et al. found that uEVs’ TERC levels were
higher in BC patients than in HC, with a diagnostic performance of 78.65% sensitivity and
77.78% specificity, which is considerably higher than that of the NMP22 (FDA-approved)
test and urine cytology. Additionally, the TERC levels discriminated low-grade from
high-grade disease [58].
Zhang et al. selected and quantified 11 candidates in a training set of BC and HC
serum samples to predict and detect BC recurrence. Among those, three lncRNAs were
up-regulated in patients compared to HC. Subsequently, in a validation set, the three-
lncRNA panel (PCAT-1, UBC1, and SNHG16) detected BC with 80% sensitivity and 75%
specificity, outperforming urine cytology. UBC1 and SNHG16 were also up-regulated in
MIBC vs. NMIBC, thus associating with deep bladder wall invasion. Moreover, UBC1
was also suggested to serve as a prognostic marker, since higher levels associated with
poor recurrence-free survival in NMIBC [61]. Wang et al. explored serum-EV-derived
H19 as a BC biomarker. After ensuring that measured H19 derived only from inside EVs,
the authors observed that H19 levels were increased in BC patients compared to HC and
benign disease, further correlating with tumor stage. Moreover, the postoperative samples
presented decreased lncRNA levels compared to the preoperative samples. Interestingly,
BC patients with higher H19 levels endured shorter overall survival [62]. In another
study, PTENP1 was found to be decreased in plasma EV from BC patients and paired BC
tissues. Biologically, PTENP1 expression increased cell apoptosis and reduced invasion
and migration [63]. Finally, released lncRNAs may induce tumor growth and progression
during hypoxia. Xue et al. reported that UCA1 promoted BC cell proliferation, migration,
and invasion. After assessing the relevance of this lncRNA in cell lines, the authors
confirmed that UCA1 was elevated in the serum of BC patients, compared to HC [64].

3.3. Protein Biomarkers in BC

Urine has been the fluid of choice for assessing free proteins as biomarkers for BC,
and the study of uEV proteins has followed the same trend. Proteomic analysis using
liquid chromatography–tandem mass spectrometry (LC-MS) demonstrated an enrichment
of several proteins in the uEVs of BC patients compared to HC [69–72]. However, only
Chen et al. confirmed the potential of the tumor-associated calcium signal transducer 2
(TACSTD2) in uEVs for BC diagnosis [71]. Furthermore, Tomiyama et al. used density
gradient ultracentrifugation (DUC) to isolate uEVs and carried out a combined proteomic
analysis of uEVs and EVs derived from tissue exudate. After performing tandem mass
tag (TMT)-LC-MS/MS analysis, 22 membrane proteins were selected as BC candidate
biomarkers for validation, using selected reaction monitoring/multiple reaction monitoring
(SRM/MRM) analysis on an independent cohort of 70 individuals. Heat-shock protein 90,
syndecan-1, and myristoylated alanine-rich C-kinase substrate (MARCKS) were validated
as significantly up-regulated in BC patients [68].
Surprisingly, and despite plasma being widely used for biomarker research, there are
no studies on BC-EV-derived proteins in this biofluid, to the best of our knowledge.
Int. J. Mol. Sci. 2023, 24, 6757 12 of 19

3.4. Other Molecules as BC Biomarkers

Yazarlou et al. analyzed the MAGE-B4 profile in uEVs, highlighting its potential
for BC diagnosis. Its expression, however, was higher in patients with benign prostate
hyperplasia (BPH) than in BC patients [74]. Moreover, Amuran et al., after uEV isolation
using the Norgen kit, combined EV-derived miR-139-5p, miR-136-3p, miR-19b1-5p, and
miR-210-3p with the urinary proteins Ape1/Ref1, BLCA4, CRK, and VIM into a panel
able to discriminate BC (especially low-risk) patients from HC with 93.3% sensitivity and
95.5% specificity and 80.0% sensitivity and 86.4% specificity, respectively [77]. Lastly, us-
ing high-throughput RNA-Seq in uEVs, Huang et al. established and validated a panel
combining the mRNAs KLHDC7B, CASP14, and PRSS1 and the lncRNAs MIR205HG and
GAS5, which discriminated BC patients from HCs with excellent performance (88.5% sensi-
tivity and 83.3% specificity). Additionally, RNA levels were associated with tumor stage
and grade [76].

4. Discussion
Presently, cytology is the only test implemented for assisting in BC patient manage-
ment, used in complementarity with cystoscopy [9]. The FDA-approved urine-sediment-
based tests for BC diagnosis and follow-up, mostly assessing proteins, metabolites, DNA,
or mRNA, have not gained wide acceptance in clinical routine due to its low sensitivity
for detecting early disease and its limited reproducibility [81]. Thus, novel molecular
biomarkers are required to fill this gap. In this scenario, EVs have shown potential as a
source of biomarkers, with interest growing exponentially over the years. The clinical
drive for studying EVs lies in their critical role in a comprehensive range of pathological
processes in several cancers [38].

4.1. The Potential of EVs as BC Biomarkers

EVs may be found in almost all biofluids, each containing different information that
may potentially answer different questions concerning BC management. Whereas urine,
collected in a noninvasive manner, may be more informative for detecting early-stage BC,
plasma provides the advantage of being less influenced by bladder inflammation and may
even allow for detecting premetastatic signals. Due to EVs’ presence in these biofluids and
their potential as minimally invasive biomarkers, the role of EVs as BC biomarkers has
been extensively explored (Figure 2).
Thus far, most studies have focused on BC diagnosis and most disclose biomarker per-
formance parameters, generally reporting higher sensitivity than cytology for BC detection
(Tables 1 and 2), underscoring the promising value of EV-derived biomarkers as diagnostic
tools [58,60-68,71,74,76,77]. Moreover, specific serum lncRNAs and miRNAs’ levels have
been associated with recurrence-free survival and overall survival, suggesting that EVs
may be useful for prognostication [50,60,62]. Additionally, EV-derived biomolecules were
found to be differentially regulated according to clinicopathological features such as the
tumor grade and the level of bladder wall invasion, unveiling an interconnection between
biomarker levels and disease aggressiveness [52,53,55,56,70,76]. Importantly, two clinical
trials using EVs as BC biomarkers are ongoing: miR Sentinel BC uses uEV-derived miRNAs
for BC detection and monitoring in patients with hematuria (NCT04155359), whereas uEV
lncRNAs are used at diagnosis to stratify patients according to lymph node metastatic
status (NCT05270174).

4.2. Challenges and Drawbacks in BC-Derived EV Research

Although there is a plethora of studies proposing EV-derived biomarkers and eluci-
dating their potential, very few have made their way into clinical trials due to preanalytical
issues and a lack of standardized reporting. For instance, the published studies focusing
on the discovery of EV-based biomarkers in BC report different candidates. Neverthe-
less, PCAT-1 and PRMT5 were shown to be present both in serum and urine [59–61,80].
Additionally, uEV-derived PCAT-1, MALAT-1, and EPS8L2 are represented in different
Int. J. Mol. Sci. 2023, 24, 6757 13 of 19

studies [59–61,69,72,78]. The lack of overlapping may be explained by differences in experi-

mental design, such as the preprocessing conditions or the EV isolation method, as well as
the dissimilar composition and size of the patient cohorts [82–84].

4.2.1. Study Design Constraints

Some of these studies use small cohorts of patients and controls. Thus, after unveiling
and testing potential candidates, validation in larger studies from different institutions is
needed to disclose the real clinical value of these biomarkers. Importantly, the proportion of
MIBC and NMIBC stated in most reports does not mirror the real-world patient distribution,
which may bias the biomarker’s performance results.

4.2.2. Limitations of EVs’ Isolation

Another major shortcoming is the type of EV isolation method. Despite advances in
the EV field, the challenge of efficient EV isolation is far from being overcome, particularly
in biofluids, owing to their complexity and variability [85]. Although several different
methods have been developed, such as differential ultracentrifugation (UC) and polymer
precipitation, method standardization is lacking, and each may be performed in a variety
of ways [38].
UC stands as the most widely used method for uEV isolation for BC biomarker
discovery (Figure 3). Although UC provides EV samples with adequate recovery, most
protocols remain time-consuming, on top of requiring a large volume of each sample,
limiting clinical application. Moreover, commercial kits, mainly ExoQuick, are often
used in plasma and serum EV studies (Figure 3). These are usually costly and pro-
vide EV samples of low purity. Thus, the variety and complexity of these protocols
hinder a comprehensive profiling of EV cargo. Thus, developing a cost-effective protocol
that requires lower runtimes and volume inputs, more amenable for clinical use, is of
utmost importance.

4.3. Constraints in EVs’ Cargo Analysis

Full EV characterization and/or the presence of contaminants is often not reported in
several studies. Consequently, concerns about the intravesicular origin of the identified
candidates cannot be disregarded. Furthermore, treatments such as RNAse and proteinase,
that may affect biomarker results, are often not performed. For instance, when targeting a
nucleic acid, authors should consider DNAse and RNAse treatments before extraction to
assure that the biomarker of interest is, in fact, EV-derived. This is particularly relevant
concerning EV-derived-protein studies. Indeed, some authors sought to perform protease
treatments before the analysis of EV-derived proteins to ensure that the cargo originated
from EVs. However, treatment may partially damage EV membranes and, consequently,
degrade EVs’ internal molecules [86].
Finally, whereas EV-derived-protein analysis methods, such as ELISA, have the ad-
vantage of not requiring normalization, studies on RNA used RT-qPCR to evaluate and
quantitate RNA levels in a relative manner (Tables 1 and 2). Nonetheless, housekeeping
biomolecules for EV cargo normalization are not consensual, limiting unbiased assessment,
and further leading to non-reproducible results [87]. Thus, it is of vital importance to
uncover and validate housekeeping molecules within EVs and/or apply techniques that
evaluate levels in an absolute manner, such as droplet digital PCR.

4.4. Future Perspectives

Considering the drawbacks of available biomarkers for BC detection and prognos-
tication, novel biomarkers are urgently needed. Indeed, EVs’ derived cargo has been
shown to be powerful tools as BC biomarkers. Additionally, several reports have already
suggested EVs and their cargo as potential cancer vaccines in different cancer models [88].
Because therapeutic options are very limited in BC, it is of utmost importance to unveil
alternative therapies, eventually using EVs as a therapeutic option. Indeed, a clinical trial
Int. J. Mol. Sci. 2023, 24, 6757 14 of 19

is ongoing focusing on chimeric EVs vaccine administration to treat patients with recurrent
or metastatic BC (NCT05559177).
Although promising, EV-related methodological hurdles are considerable. In the
next few years, research must focus on addressing the technical shortcomings of EVs
isolation, not only by developing and standardizing techniques that might be easily (and
reproducibly) implemented in clinical practice, but also by using methods that allow for
accurate EV cargo quantification (e.g., ddPCR or the large-scale validation of housekeeping
molecules for RT-qPCR analysis). The clinical validity issues must be also solved by
increasing patient cohorts as well as by performing multicenter validation to ascertain the
real value of EVs as BC biomarkers.

5. Conclusions
EV-derived miRNAs, lncRNAs, mRNAs, and proteins may serve as biomarkers for
both BC diagnosis and prognostication. Not only might they improve patient care through
a more precise and minimally invasive strategy, but they might aid in overcoming con-
temporary challenges in the field. Importantly, technical issues still hamper their use
in a clinical setting. Nonetheless, research on EVs is advancing at a fast pace, showing
their great potential as a source of biomarkers, which further emphasizes the value that
EV-derived molecules may have in the clinical management of BC patients.

Author Contributions: Conceptualization, A.T.-M., C.L. and M.C.O.; writing—A.T.-M., C.L. and
M.C.O.; writing—review and editing, A.T.-M., C.L., M.C.O., R.H. and C.J.; supervision, R.H. and C.J.
All authors have read and agreed to the published version of the manuscript.
Funding: This research was funded by research grants from the Research Center of the Portuguese
Oncology Institute of Porto (PI 27-CI- IPOP-27-2016 and PI 160-CI-IPOP-153-2021) and the Pro-
grama Operacional Regional do Norte, and cofunded by the European Regional Development
Fund under the project “The Porto Comprehensive Cancer Center Raquel Seruca” with the ref-
erence NORTE-01-0145-FEDER-072678—Consorcio PORTO.CCC—Porto.Comprehensive Cancer
Center Raquel Seruca. A.T.-M. holds a fellowship from FCT—Fundação para a Ciência e Tecnologia
(PTDC/MEC-ONC/0491/2021). C.L. is a recipient of a PhD fellowship from FCT—Fundação para a
Ciência e Tecnologia (2021.06731.BD).
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: No new data was created or analyzed in this study. Data sharing is not
applicable to this article.
Conflicts of Interest: The authors declare no conflict of interest.

Abbreviations

A2M Alpha-2 macroglobulin

AFM Afamin
APOA1 Apolipoprotein A-I
AUC Area under the curve
BC Bladder cancer
CD5L CD5 antigen-like protein
CDC5L Cell division cycle 5-like protein
CEACAM Carcinoembryonic-antigen-related cell adhesion molecule
CFL1 Cofilin-1
EAU European Association of Urology
EPS8L2 Epidermal growth factor receptor kinase substrate 8-like protein 2
EV Extracellular vesicle
FGB Fibrinogen beta chain
HC Healthy control
ITIH2 Inter-Alpha-Trypsin Inhibitor Heavy Chain H2
Int. J. Mol. Sci. 2023, 24, 6757 15 of 19

LC-MS Liquid Chromatography-Tandem Mass Spectrometry

lncRNA Long noncoding RNA
MARCKS Myristoylated alanine-rich C-kinase substrate
MIBC Muscle-invasive bladder cancer
miRNA microRNA
MISEV Minimal Information for Studies of Extracellular Vesicles
NMIBC Non-muscle-invasive bladder cancer
NMP22 Nuclear Matrix Protein 22
PCa Prostate cancer
PFS Progression-free survival
piRNA Piwi-interacting RNA
RFS Recurrence-free survival
SEC Size exclusion chromatography
SN Sensitivity
SP Specificity
TACSTD2 Tumor-associated calcium signal transducer 2
TMT Tandem mass tag
UC Differential ultracentrifugation
UTI Urinary tract infection
Vs Versus
↑ Higher
↓ Lower

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