Next Article in Journal
Gut Microbiota and Non-Alcoholic Fatty Liver Disease Severity in Type 2 Diabetes Patients
Previous Article in Journal
A Review on the Value of Imaging in Differentiating between Large Vessel Vasculitis and Atherosclerosis
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
JPM
Volume 11
Issue 3
10.3390/jpm11030237
jpm-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Liquid Biopsy Biomarkers in Urine: A Route towards Molecular Diagnosis and Personalized Medicine of Bladder Cancer

by
Matteo Ferro
1,†,
Evelina La Civita
2,†,
Antonietta Liotti
2,
Michele Cennamo
2,
Fabiana Tortora
3,
Carlo Buonerba
4,5,
Felice Crocetto
6,
Giuseppe Lucarelli
7,
Gian Maria Busetto
8,
Francesco Del Giudice
9,
Ottavio de Cobelli
1,10,
Giuseppe Carrieri
9,
Angelo Porreca
11,
Amelia Cimmino
12,* and
Daniela Terracciano
2,*
1
Department of Urology of European Institute of Oncology (IEO), IRCCS, Via Ripamonti 435, 20141 Milan, Italy
2
Department of Translational Medical Sciences, University of Naples “Federico II”, 80131 Naples, Italy
3
Institute of Protein Biochemistry, National Research Council, 80131 Naples, Italy
4
CRTR Rare Tumors Reference Center, AOU Federico II, 80131 Naples, Italy
5
Environment & Health Operational Unit, Zoo-Prophylactic Institute of Southern Italy, 80055 Portici, Italy
6
Department of Neurosciences, Sciences of Reproduction and Odontostomatology, University of Naples Federico II, 80131 Naples, Italy
7
Department of Emergency and Organ Transplantation, Urology, Andrology and Kidney Transplantation Unit, University of Bari, 70124 Bari, Italy
8
Department of Urology and Organ Transplantation, University of Foggia, 71122 Foggia, Italy
9
Department of Urology, Sapienza University of Rome, 00185 Rome, Italy
10
Dipartimento di Oncologia ed Ematoncologia-DIPO-Università degli Studi di Milano, 20122 Milan, Italy
11
Department of Urology, Veneto Institute of Oncology, 31033 Padua, Italy
12
Institute of Genetics and Biophysics, National Research Council, 80131 Naples, Italy
 
add Show full affiliation list
 
remove Hide full affiliation list
*
Authors to whom correspondence should be addressed.
†
These authors equally contributed.
J. Pers. Med. 2021, 11(3), 237; https://doi.org/10.3390/jpm11030237
Submission received: 28 January 2021 / Revised: 10 March 2021 / Accepted: 19 March 2021 / Published: 23 March 2021
Browse Figures
Versions Notes

Abstract

:
Bladder cancer (BC) is characterized by high incidence and recurrence rates together with genomic instability and elevated mutation degree. Currently, cystoscopy combined with cytology is routinely used for diagnosis, prognosis and disease surveillance. Such an approach is often associated with several side effects, discomfort for the patient and high economic burden. Thus, there is an essential demand of non-invasive, sensitive, fast and inexpensive biomarkers for clinical management of BC patients. In this context, liquid biopsy represents a very promising tool that has been widely investigated over the last decade. Liquid biopsy will likely be at the basis of patient selection for precision medicine, both in terms of treatment choice and real-time monitoring of therapeutic effects. Several different urinary biomarkers have been proposed for liquid biopsy in BC, including DNA methylation and mutations, protein-based assays, non-coding RNAs and mRNA signatures. In this review, we summarized the state of the art on different available tests concerning their potential clinical applications for BC detection, prognosis, surveillance and response to therapy.

Graphical Abstract

1. Introduction

In the context of non-invasive methods in the diagnosis and follow-up of cancer, liquid biopsy is a valid alternative to tissue biopsy. Compared to the latter, in fact, liquid biopsy provides responses on tumor progression and therapeutic results in real time, as well as representing a non-invasive approach in disease diagnosis [1]. Liquid biopsy is also advantageous in terms of compatibility for real-time disease assessment [2]. For instance, radiological assessment approaches are unable to observe a low number of heterogeneous cancer cells. Therefore, a low sensitivity of evaluation is obtained, which results in a notable reduction in the chances of early diagnosis of the disease. Moreover, biopsy of tumor tissue, especially in the genitourinary (GU) system, can be inefficient and require invasive surgical options, especially for upper tract urothelial cancer. Liquid biopsy includes any non-tissue sample, especially body fluids, such as blood, feces, saliva, pleural fluid, peritoneal fluid, or brain spinal fluid, which may negate the need for costly, invasive, and sometimes painful tumor tissue biopsies for active surveillance of cancer. In particular, the discovery and characterization of some elements from urine, in recent years, has aroused considerable curiosity among scientific and clinical staff. Urine can turn out to be “liquid gold”, being the most abundant source of cancerous material [3]. Various methods are available for the isolation and characterization of these urinary components, which may involve genetic, and protein analyzes as well as microfluidic techniques. These are very specific and sensitive methods, advantageous from an operational point of view and in terms of processing speed and use of small sample volumes [4].
The three main used methods are ELISA to detect proteins, (rRT-PCR) for genetic material (DNA/RNA) and next-generation sequencing (NGS) which can assess the genomic sequence. Each of these diagnosis approaches has its own advantages and disadvantages. ELISA tests are sensitive and specific but can give false positive results. RT-PCR is a well-established methodology with high sensitivity, but it requires expensive consumables. NGS is highly repeatable and accurate, but it is expensive, and it needs high expertise and sophisticated laboratory equipment [5].
Scientific progress is undisputed in the use of urinary components as possible biomarkers for the diagnosis and surveillance of disease. These include exfoliated bladder cancer cells (EBCC), exosomes, and cell-free DNA (cfDNA).
Several types of cells are present in urine, namely epithelial cells, renal-derived cells, leukocytes, erythrocytes and urothelial cells, as well as genetic material, proteins, peptides and inorganic elements. Therefore, scientific and medical personnel prefer to use urinary biopsies for the potential diagnosis of diseases, such as colorectal cancer (CC) [4], bladder cancer [3], chronic renal disease [6], prostate cancer [7], cystic fibrosis [8] and chronic obstructive pulmonary disease [9]. Urine may be used in its entirety or divided into supernatant and pellet for biomarker analysis. The supernatant contains partially fragmented cell-free tumor nucleic acids and other cancer-derived materials, while the pellet mostly contains normal and exfoliated tumor cells, in addition to debris and possible bacteria. Recent studies have found that supernatant of urine is more useful than pellet for the analysis of genetic aberrations in patients with tumor of urothelial tract [10,11]. All biomarkers have their advantages and disadvantages, and their selection depends on the type of method available.
In the last few decades, cancer genetic profiles have been better characterized, providing potentially useful biomarkers for prognosis and prediction of drug response [12]. The use of urinary liquid biopsy in bladder cancer has gained growing attention [13]. In addition, molecular biology technologies have advanced to the point at which the application in clinical practice of technically demanding biomarkers will be soon even more possible. In this context, we provided an overview of the more recent studies regarding the emerging applications in clinical practice of the different biomarkers in urine-based liquid biopsy.

2. Methods

We performed an online search by PubMed/Medline using the terms “bladder cancer”, “non-muscle invasive bladder cancer” in combination with “urine biomarkers” and “liquid biopsy” limiting the search of articles published up to February 2021. This review included the original data of each clinical trial or observational study, which led to the development of urinary biomarkers. Two reviewers independently (M.F. and E.L.C.) selected articles, extracted data, removed duplicate publications. The inclusion criteria include: (1) urine-based biomarkers, (2) diagnostic biomarkers (3) biomarkers for the identification of disease recurrence. Only studies in English were included. The exclusion criteria include all conference abstracts, editorials, comments, letters to the editor and duplicates. The selection of literature is shown in Figure S1.

3. Biomarkers Used in Urinary Biopsy

The analytes that can be used for tumor diagnosis in the liquid biopsy in urine setting include cell-free DNA (cfDNA), non-coding-RNA, exfoliated tumor cells, proteins (Figure 1).
Both healthy and diseased cells can release cfDNA during tumor destruction therapies or during apoptotic and necrotic processes. The cfDNA fragments, in most cases, are 100–200 base pairs in length. Because in physiological conditions the phagocytic cells englobe cellular debris and necrotic cells, we will have a very low cfDNA level in the disease absence [14]. On the other hand, in case of diseases, phagocytosis is not total, DNA digestion is minimal, and the DNA fragments have a random dimension that can even exceed 10,000 base pairs. As a result, the cfDNA level in the sick patient is elevated. Furthermore, cfDNA mutations give very important indications for the disease prognosis and diagnosis. CfDNA can be a useful biomarker derived from a urine biopsy. Indeed, scientists have discovered that cfDNA released by cells into the bloodstream can also be filtered at renal level and released in urine [15]. CfDNA can be analyzed in urine samples by ultracentrifugation or by molecular weight-based DNA separation techniques [16]. However, such a cfDNA extraction approach presents obstacles, as large fragments of cfDNA can escape capture, with consequent target DNA molecules loss or decrease. This can be overcome by processing a high number of samples. The extracted cfDNA can be amplified and analyzed using the various procedures that involve the polymerase chain reaction (PCR) and subsequent gene sequencing. Nevertheless, the frequency of observed mutations of cfDNA in urine often relies on the analysis technique and sample font. In fact, recent analysis found that the cfDNA level in urine is greater than that in the bloodstream [17]. Additionally, urine may be a circulating tumor cells (CTCs) source richer than blood, particularly in the case of renal, prostate, and upper and lower urothelial tract carcinoma, because urine wets these genitourinary organs. Further advantages of urinary biopsy concern the ease of acquisition, in fact there is no need for qualified medical personnel, less inconvenience for the patient, the use of a very small sample volume and mostly the urine contains fewer contaminating proteins than blood. The proteins biodistribution in the human body is based on the protein’s hydrodynamic diameters. In case of renal filtration, proteins with a diameter of less than 5 nm will be excreted rapidly in the urine, while proteins with a diameter greater than 15 nm will be retained by kidney filtration [11]. Glomerular filtration rate was assessed by endogenous small molecule such as urea and creatinine or smaller (less than 66 kDa) as cystatin C and β2-microglobulin [18].
An abnormal increase in specific proteins in the patient’s urine can be a marker of disease and has been proposed as biomarker for molecular detection, surveillance and prediction of targeted therapy efficacy [19].
Recently, preliminary studies on urinary peptide profiles as part of prognostic model to assess the risk of disease recurrence were available [20,21]. However, the potential clinical impact of these models needs to be further assessed in clinical trials on larger population.
In addition, it has been currently characterized the association of urinary microbiome and bladder cancer as well as the different urinary microbial profiles between non-muscle invasive bladder cancer (NMIBC) and muscle invasive bladder cancer (MIBC) [22,23]. These findings will probably pave the way to the identification of new biomarkers.

4. Molecular Detection and Surveillance

Urine can be collected at the time of the onset of symptoms related to urothelial carcinoma such as micro- and macro-hematuria or low-urinary tract manifestations.
European Association of Urology (EAU) guidelines recommend execute cystoscopy in patients presenting with hematuria [24], however, bladder cancer (BC) was found in a percentage of cases lower than 30% [25]. Therefore, a lot of unnecessary cystoscopies were performed with an increase of the cost of the whole diagnostic-therapeutic pathway and a relevant impact for the patient undergone to invasive procedure [26]. Urinary biopsies allow to avoid invasive cystoscopy or defer it. Several different new tests have been developed with a clear tendency towards the use of combination of biomarkers (Table 1).

5. DNA Methylation

5.1. Bladder EpiCheck

DNA methylation pattern changed during progression from NMIBC to MIBC [27]. Changes in DNA methylation pattern of a panel of 15 genomic biomarkers detected by RT-PCR was used in the Bladder EpiCheck (Nucleix, Rehovot, Israel) [28]. The test provides a score, which is considered positive for values higher than 60 [29]. Several reports were available on the diagnostic performance of Bladder Epicheck. Collectively, these studies indicated that Bladder Epicheck showed higher sensitivity particularly for low-grade cancer compared to cytology, whereas specificity was higher for cytology [29,30,31,32].

5.2. Urodiag

Since it has been demonstrated that high-risk tumors in general have high amount of hypermethylated genes than low-risk tumors [33], Roperch and Hennion [34] proposed a model combining a panel of FGFR3 mutations and a set of epigenetic markers (hypermethylation of the HS3ST2, SEPTIN9 and SLIT2). Such a model in a study population including 263 subjects showed a very high diagnostic accuracy for the monitoring of BC patients with sensitivity/specificity/Negative predictive value (NPV)higher than 95%/76%/99%, respectively [35]. On this basis, the authors designed the Urodiag® PCR Kit that includes an easy-to perform, fast and low-cost (~$100 per sample) tool for molecular detection and personalized surveillance of NMIBC.

5.3. AssureMDX

AssureMDX is a urinary combining DNA methylation and mutations. The test is based on the study of methylation of OTX1, ONECUT2 and TWIST1 genes and mutations in FGFR3, TERT, and HRAS genes [36]. Two different multicenter studies (including 154 and 977 patients respectively) showed a potential diagnostic utility of the test with a pooled sensitivity of 0.95 [95% CI 0.87–0.98] and specificity of 0.85 [95% CI 0.79–0.89] [26,37].

6. DNA Mutations

6.1. UroMuTERT

Telomerase reverse transcriptase (TERT) promoter mutations (C228T and C250T) occur in about 60–90% BC [38,39]. It is possible to detect these mutations in the urine of BC patients, providing a great opportunity for an easy diagnostic test for detection and surveillance of BC patients.
Avogbe et al. developed a test based on Next-Generation Sequencing called UroMuTERT for the comprehensive analysis of urine cell pellet and cell-free DNA in BC patients [40]. The authors demonstrated that the detection of TERT promoter mutations in urine have high diagnostic accuracy and excellent diagnostic specificity for BC [40,41]. More recently, Hosen et al. reported the development of test based on droplet digital PCR able to detect TERT promoter mutations in urine with an easy, inexpensive, non-invasive procedure [42]. Such an assay showed comparable performance with previously developed NGS-based test [40] but has the potential to be implemented in large-scale clinical application. Furthermore, TERT promoter mutations were revealed in urine 10 years before BC diagnosis and were not detected in healthy subjects in a recently published prospective study [41]. These findings suggested that urinary TERT promoter mutations could be a promising non-invasive biomarker for BC detection and surveillance.

6.2. Uromonitor

Mutations in fibroblast growth factor receptor 3 (FGFR3) are reported in about 35% BC [88]. The mutations G372C, R248C, S249C, and Y375C were analyzed in the urine and then evaluated as a tool for the diagnosis and monitoring of BC patients [89,90]. Unfortunately, two clinical studies including 772 and 97 patients respectively showed low sensitivity on the detection of high-grade tumors [43,91].
Recently, a new urine test called Uromonitor-V2® (U-monitor, Porto, Portugal) was developed [44]. This test combines a group of hotspot mutations in three genes (TERT, FGFR3, and KRAS), among the most common genetic alterations in BC by RT qPCR.
Uromonitor-V2® is based on a widely used technology and equipment and represent a low-cost and short time response test. However, this test was evaluated in a small number of patients with histologically confirmed recurrence and needs further studies on larger population of high-grade NMIBC patients.

6.3. Urovysion

Several authors showed that a test based on the fluorescence in situ hybridizations called UroVysion® can help to detect urothelial carcinoma of the upper urinary tract better than urine cytology [45,46,47,48]. This test relies upon the analysis of chromosome aneuploidy on exfoliated urothelial cells collected from urine and allows to detect disease progression in Bacillus Calmette-Guérin (BCG)-treated patients [49]. However, genetic alterations can be detected in urinary cfDNA by droplet digital PCR and NGS methods with a significantly higher sensitivity [92].

6.4. Uroseek

Uroseek® is an assay designed to reveal common alterations in BC of the following 11 genes: CDKN2A, HRAS, ERBB2, MET, FGFR3, PI3K, TP53, TERT, KRAS, MLL and VHL [50]. Eich et al. analyzed 527 cases and reported that the majority of studied cancers have at least one of the mutations of the panel, suggesting the strengthen and potential clinical benefits of the test [51].

6.5. uCAPP-Seq

Recently, a study from Stanford University including 118 BC patients and 67 healthy subjects demonstrated that a sequencing-based method for urinary tumor DNA detection, uCAPP-Seq, had a sensitivity of 84% and a specificity of 96–100% in BC detection [52].

7. Protein-Based Assays

NMP22 and Basement Membrane-Derived Antigen (BTA)

The only two protein-based urinary assays FDA-approved and CE-marked are NMP22® and BTA®, recommended in combination with cystoscopy for surveillance, but not for initial diagnosis because of false positive results due to hematuria, stones, and infectious disease and endoscopic procedures [93].
NMP22 is a nuclear matrix protein, abundantly expressed in malignant urothelial cells and released in urine by dead cells [53]. Both a quantitative ELISA assay and a qualitative test were available targeting NMP22. In a systematic review of the clinical benefit of urinary biomarkers, NMP22 assays showed a pooled sensitivity of 69% (CI 50–85%) and pooled specificity of 81% (46–93%) [54]. More recently, it has been highlighted a significant variation among studies and in some cases very low sensitivity values [55]. At present, NMP22 test is not widespread adopted in clinical practice even if still recommended in EAU guidelines in case of negative cystoscopy for patients at high-risk of recurrence [94].
BTA is a basement membrane-derived antigen released by cancer cells [56]. Two BTA assays are available: the ELISA BTA-TRAK-assay (Bard Diagnostics, Redmont, USA) and the qualitative test BTA-STAT (Bard Diagnostics, Redmont, USA) [57,58].
As NMP22, BTA assays are approved for surveillance in addition to cystoscopy, but not for diagnostic scope. Unfortunately, despite sensitivity values higher than cytology [55], BTA tests are not routinely used in clinical practice because of the high rate of false positive results [59].

8. Adxbladder

ADXBLADDER is an ELISA test measuring the urinary level of MCM5 (minichromosome maintenance protein 5). MCM5 belongs to a family of proteins playing a prominent role in DNA replication [60]. These proteins are overexpressed in highly proliferating cancer cells compared to healthy urothelial cells [61]. There is evidence that MCM5 amount was significantly associated with bladder tumor aggressiveness [62]. Several authors evaluated the potential clinical benefit of MCM5 as urinary biomarker [63,64,65,66,67]. ADXBLADDER is an easy to perform and cheap ELISA test, but still few data were available on the clinical benefit of its use in clinical practice. Dudderidge e al [65] in a prospective study including 856 subjects with hematuria showed a sensitivity of 73% (CI 61–83%) and a NPV of 96% (95–98%) for all cases, 86% and 99% for high grade cancers, 55% and 98% for low grade cancers, respectively. The findings suggested that ADXBLADDDER could be more sensitive than cytology at initial diagnosis of BC in patients with hematuria. In a smaller set of patients (n = 91, with 40 confirmed cancer cases) lower values of sensitivity (60%) and NPV (74%) was reported [66]. In a series of 1431 patients with NMIBC undergoing cystoscopic surveillance, Roupret et al. demonstrated a sensitivity of 45% (CI 36–54%) and a NPV of 93% (CI 91–95%). These results suggested that a negative ADXBLADDER result during surveillance was significantly associated with the absence of recurrence, conversely a positive result was not diagnostic.

Oncuria

Furuya et al. identified 10 protein biomarkers (APOE, ANG, A1AT, CA9, IL8, MMP9, MMP10, PAI1, SDC1 VEGA) establishing a diagnostic signature (Oncuria™) for BC, which in a study including 44 subjects showed a sensitivity of 85% and specificity of 81% [68]. This test is currently under evaluation in several multicenter prospective study (NCT03193541, NCT03193528 and NCT03193515) and needs further extensive validation.

9. Non-Coding RNA

Non-coding RNA have been recognized as driver of BC carcinogenesis and progression [95,96,97,98,99], suggesting their potential uses as biomarkers for diagnosis and prognosis of bladder tumors [69,100,101]. Several mi-RNAs were reported as deregulated in BC and most of the studies investigated tissue samples [98,101]. However, Parizi et al. in a study including 157 subjects showed that miRNAs expression profile was different among urine samples from BC and healthy patients [70].
Hanke et al. for the first time reported the presence of miRNAs in urine in 2010 [71]. Since then, a lot of studies focused on the role miRNAs as urinary biomarkers, showing a potential prognostic ability for miR-200, miR-145, and miR-214 [70]. However, further studies on large population are needed to validate these findings.
LncRNAs affects cellular biology and are often deregulated in BC, suggesting their potential use as biomarkers in liquid biopsy samples for early diagnosis as well as for risk stratification [72]. As lncRNAs can be detected in urine and can resist to degradation by ribonuclease, several authors investigated their ability to detect or provide prognostic information in BC patients [73,74].
UCA1 is the most studied among lncRNAs as urinary biomarkers. A meta-analysis including seven studies showed that UCA1 has a good sensitivity (0.84) and specificity (0.87) for the detection of BC [75]. The combination of UCA1 with miR-210 and miR-96, and the mRNA, HYAL1 achieved the ideal sensitivity of 100% with a specificity of 89.5 for BC detection [102]. Yazarlou et al. [69] measured the expression levels of four lncRNAs in urinary exosomes: UCA1-203, UCA1-201, MALAT1 and LINC00355 and the combined model showed a 92% sensitivity and a 91.7% specificity in a study population including 108 subjects. Based on their high sensitivity and specificity, lncRNAs seems to be extremely promising as urinary biomarkers. Further studies are encouraged to validate their clinical use and implement these assays into routine practice.

10. mRNA Signatures

10.1. Cxbladder Detect and Monitor

Cxbladder® is a reverse transcription quantitative PCR assay designed to detect and quantify urinary mRNA levels of CDK1, MDK, HOXA13, IGFBP5 and CXCR2 [103]. Two versions of the assay are available: Cxbladder® Detect and Cxbladder® Monitor. The first showed high sensitivity and specificity (82% and 85%, respectively) in the detection of BC in subjects with hematuria [76]. Cxbladder® Monitor showed high sensitivity and NPV to select patients at low risk of recurrence who would not benefit from repeated cystoscopy [77,78].
Koya et al. demonstrated that Cxbladder® Monitor addition in clinical guidelines allowed to safely select patients who can be monitored by a cystoscopy every 2 years [79]. Lowering the number of cystoscopies, this test potentially showed the ability of decrease the economic burden of BC patient’s surveillance and increase patient compliance.

10.2. Xpert Bladder Cancer Detect and Monitor

The Xpert® Bladder Cancer is a urinary test, which combines the values of five mRNA (ABL1, ANXA10, CRH, IGF2 and UPK1B) that may be overexpressed in BC by RT-PCR [80]. The test is performed using the Gene Xpert System (Cepheid) with an easy and fast assay, which automates nucleic acid amplification and the detection of mRNAs targets [80]. Two kind of assays have been developed: the first, detection, for first diagnosis, the second, monitor, for surveillance [81]. Xpert Detection showed a NPV of 99% (CI 98–100%) for high-grade cancers [81]. Several authors showed that active surveillance is a safe and cost-effective alternative therapeutic strategy in patients with recurrent NMIBC [82,83]. D’Elia et al. in a prospective study including 230 patients and 52 recurrences demonstrated that Xpert BC Monitor has a sensitivity of 85.7% for high-grade tumors [84]. Pichler et al. reported a high sensitivity (77%) also in low-grade disease [85]. In a recently published study, Xpert Bladder Monitor had an overall sensitivity of 74% with a specificity of 80%, and a sensitivity of 83% for high grade and 63% for low-grade cancers [86]. Interestingly, Hurle et al. reported the ability of Xpert Bladder Monitor to avoid unnecessary cystoscopies without missing high-grade cancers in a set of 106 patients underwent active surveillance when a cutoff value <0.4 was chosen [87].

11. Predict Targeted Therapy Efficacy

Urine can be collected after treatment as a source of biomarkers useful to assess residual disease or recurrence of BC. The staging of residual disease after neoadjuvant chemotherapy (NAC) might be ameliorated by sensitive detection of cancer genetic derivative. The staging allows us to select patients who achieve ypT0 for radical cystectomy avoidance. Unfortunately, no urine biomarkers are currently available to address this issue and the assessment of the minimal residual disease after NAC is still challenging.
The clinical scenario of BC is characterized by a high degree of heterogeneity high rate of recurrence and the limited treatment options [104], thus liquid biopsy in urine might represent a valuable source of predictive biomarkers for personalized medicine [105].
A panel of nine cytokines (tumor necrosis factor-a, tumor necrosis factor-related apoptosis-inducing ligand, IL-18, IL-12[p70], IL-12[p40], IL-8, IL-6, IL-2, IL-1ra) measured in urine has been used to build a nomogram (CyPRIT) able to predict recurrence after intravesical BCG with 85.5% accuracy [106]. More recently, Salmasi et al. demonstrated that SHGB, IP10 and resistin urinary levels were significantly associated with time-to-treatment failure in a prospective study including 50 patients receiving BCG (15 developed recurrence and 4 experienced disease progression) [107].
The test Uroseek [50] detect mutations in 11 genes, including PIK3CA, FGFR3 and ERBB2, which are target of drugs. Thus, this urinary test has the potential to guide treatment decision. FGFR3 mutations are preponderant in BC [91], thus FGFR3 inhibitors could be a desirable treatment option in patients who could be selected by urine biopsy.
Similarly, to what has been described in lung cancer [108], patients may be selected for kinase inhibitors treatment based on urine biopsy. Choudhury et al. demonstrated the efficacy of Afatinib in metastatic patients with cancers platinum-refractory presenting ERBB2 and ERBB3 mutations [109]. This drug could be given only in selected patients, potentially improving treatment outcome.

12. Conclusions and Future Perspective

Early identification of BC is a relevant goal. The five-year survival rate is about 94% when BC was early detected, but dramatically drops at 50% when the disease is muscle-invasive and at 20% in metastatic patients [110,111].
The currently used procedure for diagnosis and follow-up of BC relies on cystoscopy and urine cytology with substantial discomfort for the patient and high economic burden. Unfortunately, cytology has high specificity, but low sensitivity, so it is far from ideal for cystoscopy replacement. In this clinical scenario, a non-invasive and inexpensive biomarker could be useful. A biomarker with good sensitivity could replace cytology for the diagnosis, as well as a biomarker with high NPV could reduce repeated invasive cystoscopic procedures during the follow-up. In addition, a desirable outcome might be the availability of specific biomarkers to predict the response to targeted therapy.
For diagnostic purpose, few biomarkers are currently available with higher sensitivity, but lower specificity compared to cytology. In addition, some of them are not easy-to perform, making more complex to implement them in clinical practice [112]. The first biomarkers proposed were NMP22 [113] and BTA [114]. Unfortunately, since bladder tumors harbor different molecular changes, single biomarkers are far from ideal for BC detection. High-throughput technologies prompted new biomarkers discovery and panels building and several groups investigated the clinical benefit of multiplex assays (i.e., methylation of several genes and RNA signatures) [52,71,115,116,117,118].
For the follow-up, a restricted number of biomarkers are at present used in clinic. Only NMP22 and UroVysion are cited in EAU and AUA guidelines, but not widespread used in clinical settings.
To date, no biomarker is available to predict therapy response. However, considering that immunotherapeutic agents against programmed cell death protein 1 (PD-1) and programmed cell death ligand-1 (PD-L1) are emerging therapeutic options, predictive biomarkers could be particularly helpful.
The bladder is naturally pointed towards urine, which provides a source for liquid biopsy. Liquid biopsy has the potential to provide biomarkers for detection, prognosis, surveillance, monitoring the clinical outcome after treatment. Growing evidence suggest the need of clinical validation for the new discovered urinary biomarkers, potentially filling a relevant request for patient evaluation. Several challenges need to be addressed, such as low mutant allele fraction, tumor DNA stability in urine, the need of new technologies and correct storage and the transport of samples. Moreover, sequencing and detection of tumor DNA is still an expensive procedure and it could be cost-effective only if it can allow a change in therapy or the identification of druggable targets.
NMIBC shows high recurrence rate and cystoscopy currently is still the gold-standard diagnostic procedure, so clinical management of BC is one of the most expensive [119]. In the last ten years, assays based on panel of biomarkers were developed most of all for the follow-up. Several test, such as Urovysion, BTA and NMP22 are FDA-approved, but not widely used in clinical practice because of low NPV [55]. Xpert Bladder Monitor, Bladder EpiCheck and CxBladder Monitor showed more promising results with NPV higher than 98% [32,77,86].
Bladder tumors show cellular and molecular inter- and intra-tumoral heterogeneity [120,121]. Urine corresponds to a framework of the tumor heterogeneity, so mutations not detected by a biopsy procedure may be captured in urine. Thus, it is critical to develop urinary test able to address specific clinical need. The clinical validation has to focus only on test able to impact on clinical decision making process both in terms of improvement of patient survival and quality of life. Urine biopsy may represent a non-invasive test with the potential of significantly improve the whole diagnostic and therapeutic pathway of BC patient. Ideally, a multiplex assay could help to select which patients need invasive, expensive and time-consuming procedure such as cystoscopy, should predict disease recurrence and might envision the best treatment option for each single patient.

Supplementary Materials

The following are available online at https://www.mdpi.com/2075-4426/11/3/237/s1, Figure S1: Study selection flow chart.

Author Contributions

Conceptualization, M.F., E.L.C., A.C., D.T., methodology, M.F., E.L.C., A.C., D.T.; software, none; validation, M.F., E.L.C., A.C., D.T.; formal analysis, E.L.C., A.L., M.C., F.T.; investigation, M.F.; resources, A.C., D.T.; data curation, C.B., F.C., G.L., G.M.B., F.D.G.; writing—original draft preparation, D.T.; writing—review and editing, A.C., D.T.; visualization, O.d.C., G.C., A.P.; supervision, A.C., D.T.; project administration, D.T., funding acquisition, none. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by SATIN-POR CAMPANIA FESR 2014/2020 to A.C.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

Abbreviations

FDA: food and drugs administration; CE: Conformitè Europëenne; FGFR3: Fibroblast Growth Factor Receptor 3; HS3ST2: Heparan Sulfate-Glucosamine 3-Sulfotransferase 2; SLIT2: Slit Guidance Ligand 2; TERT: Telomerase reverse transcriptase; KRAS: Kirsten RAt Sarcoma virus; NMIBC: nonmuscle-invasive bladder cancer; ELISA: Enzyme-linked immunosorbent assay; MCM5: Minichromosome Maintenance Complex Component 5; APOE: Apolipoprotein E; ANG: Angiogenin; A1AT: Alpha-1 antitrypsin: CA9: Carbonic anhydrase IX; IL8: Interleukin-8, MMP9: metalloprotease-9, MMP10: metalloprotease-10, PAI1: plasminogen activator inhibitor 1, SDC1: Syndecan 1; VEGFA: Vascular endothelial growth factor A; bps: base-pairs; RT-qPCR; real time quantitative polymerase chain reaction; NGS: next generation sequencing; CDK1: Cyclin-dependent kinase 1, MDK: Midkine, HOXA13: Homeobox A13, IGFBP5: Insulin Like Growth Factor Binding Protein 5; CXCR2: CXC chemokine receptor 2; ABL1: Tyrosine-protein kinase; ANXA10: Annexin A10; CRH: Corticotropin-releasing hormone, IGF2: Insulin Like Growth Factor 2; UPK1B:Uroplakin 1B, NA: not available. BC: bladder cancer; NMIBC, non-muscle invasive bladder cancer; MIBC, muscle-invasive bladder cancer; RT-PCR, real-time polymerase chain reaction; miRNA, micro-RNA; LncRNA, long-non coding-RNA.

References

  1. Murtaza, M.; Dawson, S.J.; Tsui, D.W.; Gale, D.; Forshew, T.; Piskorz, A.M.; Parkinson, C.; Chin, S.F.; Kingsbury, Z.; Wong, A.S.; et al. Non-invasive analysis of acquired resistance to cancer therapy by sequencing of plasma DNA. Nature 2013, 497, 108–112. [Google Scholar] [CrossRef]
  2. Chen, L.; Bode, A.M.; Dong, Z. Circulating tumor cells: Moving biological insights into detection. Theranostics 2017, 7, 2606–2619. [Google Scholar] [CrossRef]
  3. Satyal, U.; Srivastava, A.; Abbosh, P.H. Urine biopsy-liquid gold for molecular detection and surveillance of bladder cancer. Front. Oncol. 2019, 9, 1266. [Google Scholar] [CrossRef] [Green Version]
  4. Normanno, N.; Cervantes, A.; Ciardiello, F.; De Luca, A.; Pinto, C. The liquid biopsy in the management of colorectal cancer patients: Current applications and future scenarios. Cancer Treat. Rev. 2018, 70, 1–8. [Google Scholar] [CrossRef]
  5. Boonham, N.; Kreuze, J.; Winter, S.; van der Vlugt, R.; Bergervoet, J.; Tomlinson, J.; Mumford, R. Methods in virus diagnostics: From ELISA to next generation sequencing. Virus Res. 2014, 186, 20–31. [Google Scholar] [CrossRef] [PubMed]
  6. Mischak, H.; Delles, C.; Vlahou, A.; Vanholder, R. Proteomic biomarkers in kidney disease: Issues in development and implementation. Nat. Rev. Nephrol. 2015, 11, 221–232. [Google Scholar] [CrossRef] [PubMed]
  7. Rzhevskiy, A.S.; Razavi Bazaz, S.; Ding, L.; Kapitannikova, A.; Sayyadi, N.; Campbell, D.; Walsh, B.; Gillatt, D.; Ebrahimi Warkiani, M.; Zvyagin, A.V. Rapid and label-free isolation of tumour cells from the urine of patients with localised prostate cancer using inertial microfluidics. Cancers 2019, 12, 81. [Google Scholar] [CrossRef] [Green Version]
  8. Laguna, T.A.; Wagner, B.D.; Starcher, B.; Luckey Tarro, H.K.; Mann, S.A.; Sagel, S.D.; Accurso, F.J. Urinary desmosine: A biomarker of structural lung injury during CF pulmonary exacerbation. Pediatr. Pulmonol. 2012, 47, 856–863. [Google Scholar] [CrossRef] [Green Version]
  9. Ongay, S.; Sikma, M.; Horvatovich, P.; Hermans, J.; Miller, B.E.; Ten Hacken, N.H.T.; Bischoff, R. Free urinary desmosine and isodesmosine as COPD biomarkers: The relevance of confounding factors. Chronic Obstr. Pulm. Dis. 2016, 3, 560–569. [Google Scholar] [CrossRef] [PubMed]
  10. Togneri, F.S.; Ward, D.G.; Foster, J.M.; Devall, A.J.; Wojtowicz, P.; Alyas, S.; Vasques, F.R.; Oumie, A.; James, N.D.; Cheng, K.K.; et al. Genomic complexity of urothelial bladder cancer revealed in urinary cfDNA. Eur. J. Hum. Genet. 2016, 24, 1167–1174. [Google Scholar] [CrossRef] [Green Version]
  11. Choi, H.S.; Liu, W.; Misra, P.; Tanaka, E.; Zimmer, J.P.; Itty Ipe, B.; Bawendi, M.G.; Frangioni, J.V. Renal clearance of quantum dots. Nat. Biotechnol. 2007, 25, 1165–1170. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Crowley, E.; Di Nicolantonio, F.; Loupakis, F.; Bardelli, A. Liquid biopsy: Monitoring cancer-genetics in the blood. Nat. Rev. Clin. Oncol. 2013, 10, 472–484. [Google Scholar] [CrossRef]
  13. Lodewijk, I.; Duenas, M.; Rubio, C.; Munera-Maravilla, E.; Segovia, C.; Bernardini, A.; Teijeira, A.; Paramio, J.M.; Suarez-Cabrera, C. Liquid biopsy biomarkers in bladder cancer: A current need for patient diagnosis and monitoring. Int. J. Mol. Sci. 2018, 19, 2514. [Google Scholar] [CrossRef] [Green Version]
  14. Choi, J.J.; Reich, C.F., 3rd; Pisetsky, D.S. The role of macrophages in the in vitro generation of extracellular DNA from apoptotic and necrotic cells. Immunology 2005, 115, 55–62. [Google Scholar] [CrossRef] [PubMed]
  15. Bryzgunova, O.E.; Skvortsova, T.E.; Kolesnikova, E.V.; Starikov, A.V.; Rykova, E.Y.; Vlassov, V.V.; Laktionov, P.P. Isolation and comparative study of cell-free nucleic acids from human urine. Ann. N. Y. Acad. Sci. 2006, 1075, 334–340. [Google Scholar] [CrossRef]
  16. Phallen, J.; Sausen, M.; Adleff, V.; Leal, A.; Hruban, C.; White, J.; Anagnostou, V.; Fiksel, J.; Cristiano, S.; Papp, E.; et al. Direct detection of early-stage cancers using circulating tumor DNA. Sci. Transl. Med. 2017, 9. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  17. Hirotsu, Y.; Yokoyama, H.; Amemiya, K.; Hagimoto, T.; Daimon, H.; Hosaka, K.; Oyama, T.; Mochizuki, H.; Omata, M. Genomic profile of urine has high diagnostic sensitivity compared to cytology in non-invasive urothelial bladder cancer. Cancer Sci. 2019, 110, 3235–3243. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  18. Price, C.P.; Finney, H. Developments in the assessment of glomerular filtration rate. Clin. Chim. Acta 2000, 297, 55–66. [Google Scholar] [CrossRef]
  19. D’Costa, J.J.; Goldsmith, J.C.; Wilson, J.S.; Bryan, R.T.; Ward, D.G. A systematic review of the diagnostic and prognostic value of urinary protein biomarkers in urothelial bladder cancer. Bladder Cancer 2016, 2, 301–317. [Google Scholar] [CrossRef] [Green Version]
  20. Krochmal, M.; van Kessel, K.E.M.; Zwarthoff, E.C.; Belczacka, I.; Pejchinovski, M.; Vlahou, A.; Mischak, H.; Frantzi, M. Urinary peptide panel for prognostic assessment of bladder cancer relapse. Sci. Rep. 2019, 9, 7635. [Google Scholar] [CrossRef] [Green Version]
  21. Frantzi, M.; van Kessel, K.E.; Zwarthoff, E.C.; Marquez, M.; Rava, M.; Malats, N.; Merseburger, A.S.; Katafigiotis, I.; Stravodimos, K.; Mullen, W.; et al. Development and validation of urine-based peptide biomarker panels for detecting bladder cancer in a multi-center study. Clin. Cancer Res. 2016, 22, 4077–4086. [Google Scholar] [CrossRef] [Green Version]
  22. Hussein, A.A.; Elsayed, A.S.; Durrani, M.; Jing, Z.; Iqbal, U.; Gomez, E.C.; Singh, P.K.; Liu, S.; Smith, G.; Tang, L.; et al. Investigating the association between the urinary microbiome and bladder cancer: An exploratory study. Urol. Oncol. 2021. [Google Scholar] [CrossRef]
  23. Wu, P.; Zhang, G.; Zhao, J.; Chen, J.; Chen, Y.; Huang, W.; Zhong, J.; Zeng, J. Profiling the urinary microbiota in male patients with bladder cancer in China. Front. Cell Infect. Microbiol. 2018, 8, 167. [Google Scholar] [CrossRef] [PubMed]
  24. Roupret, M.; Babjuk, M.; Burger, M.; Capoun, O.; Cohen, D.; Comperat, E.M.; Cowan, N.C.; Dominguez-Escrig, J.L.; Gontero, P.; Hugh Mostafid, A.; et al. European Association of Urology Guidelines on upper urinary tract urothelial carcinoma: 2020 update. Eur. Urol. 2021, 79, 62–79. [Google Scholar] [CrossRef] [PubMed]
  25. Burger, M.; Catto, J.W.; Dalbagni, G.; Grossman, H.B.; Herr, H.; Karakiewicz, P.; Kassouf, W.; Kiemeney, L.A.; La Vecchia, C.; Shariat, S.; et al. Epidemiology and risk factors of urothelial bladder cancer. Eur. Urol. 2013, 63, 234–241. [Google Scholar] [CrossRef]
  26. Van Kessel, K.E.; Beukers, W.; Lurkin, I.; Ziel-van der Made, A.; van der Keur, K.A.; Boormans, J.L.; Dyrskjot, L.; Marquez, M.; Orntoft, T.F.; Real, F.X.; et al. Validation of a DNA methylation-mutation urine assay to select patients with hematuria for cystoscopy. J. Urol. 2017, 197, 590–595. [Google Scholar] [CrossRef]
  27. Beukers, W.; Kandimalla, R.; Masius, R.G.; Vermeij, M.; Kranse, R.; van Leenders, G.J.; Zwarthoff, E.C. Stratification based on methylation of TBX2 and TBX3 into three molecular grades predicts progression in patients with pTa-bladder cancer. Mod. Pathol. 2015, 28, 515–522. [Google Scholar] [CrossRef] [Green Version]
  28. Mancini, M.; Righetto, M.; Zumerle, S.; Montopoli, M.; Zattoni, F. The Bladder EpiCheck Test as a non-invasive tool based on the identification of DNA methylation in bladder cancer cells in the urine: A review of published evidence. Int. J. Mol. Sci. 2020, 21, 6542. [Google Scholar] [CrossRef] [PubMed]
  29. Trenti, E.; D’Elia, C.; Mian, C.; Schwienbacher, C.; Hanspeter, E.; Pycha, A.; Kafka, M.; Degener, S.; Danuser, H.; Roth, S.; et al. Diagnostic predictive value of the Bladder EpiCheck test in the follow-up of patients with non-muscle-invasive bladder cancer. Cancer Cytopathol. 2019, 127, 465–469. [Google Scholar] [CrossRef]
  30. D’Andrea, D.; Soria, F.; Zehetmayer, S.; Gust, K.M.; Korn, S.; Witjes, J.A.; Shariat, S.F. Diagnostic accuracy, clinical utility and influence on decision-making of a methylation urine biomarker test in the surveillance of non-muscle-invasive bladder cancer. BJU Int. 2019, 123, 959–967. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  31. Trenti, E.; Pycha, S.; Mian, C.; Schwienbacher, C.; Hanspeter, E.; Kafka, M.; Spedicato, G.A.; Vjaters, E.; Degener, S.; Pycha, A.; et al. Comparison of 2 new real-time polymerase chain reaction-based urinary markers in the follow-up of patients with non-muscle-invasive bladder cancer. Cancer Cytopathol. 2020, 128, 341–347. [Google Scholar] [CrossRef]
  32. Witjes, J.A.; Morote, J.; Cornel, E.B.; Gakis, G.; van Valenberg, F.J.P.; Lozano, F.; Sternberg, I.A.; Willemsen, E.; Hegemann, M.L.; Paitan, Y.; et al. Performance of the bladder EpiCheck methylation test for patients under surveillance for non-muscle-invasive bladder cancer: Results of a multicenter, prospective, blinded clinical trial. Eur. Urol. Oncol. 2018, 1, 307–313. [Google Scholar] [CrossRef]
  33. Brait, M.; Begum, S.; Carvalho, A.L.; Dasgupta, S.; Vettore, A.L.; Czerniak, B.; Caballero, O.L.; Westra, W.H.; Sidransky, D.; Hoque, M.O. Aberrant promoter methylation of multiple genes during pathogenesis of bladder cancer. Cancer Epidemiol. Biomark. Prev. 2008, 17, 2786–2794. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Roperch, J.P.; Hennion, C. A novel ultra-sensitive method for the detection of FGFR3 mutations in urine of bladder cancer patients—Design of the Urodiag(R) PCR kit for surveillance of patients with non-muscle-invasive bladder cancer (NMIBC). BMC Med. Genet. 2020, 21, 112. [Google Scholar] [CrossRef] [PubMed]
  35. Roperch, J.P.; Grandchamp, B.; Desgrandchamps, F.; Mongiat-Artus, P.; Ravery, V.; Ouzaid, I.; Roupret, M.; Phe, V.; Ciofu, C.; Tubach, F.; et al. Promoter hypermethylation of HS3ST2, SEPTIN9 and SLIT2 combined with FGFR3 mutations as a sensitive/specific urinary assay for diagnosis and surveillance in patients with low or high-risk non-muscle-invasive bladder cancer. BMC Cancer 2016, 16, 704. [Google Scholar] [CrossRef]
  36. Van Kessel, K.E.; Van Neste, L.; Lurkin, I.; Zwarthoff, E.C.; Van Criekinge, W. Evaluation of an epigenetic profile for the detection of bladder cancer in patients with hematuria. J. Urol. 2016, 195, 601–607. [Google Scholar] [CrossRef] [PubMed]
  37. Beukers, W.; van der Keur, K.A.; Kandimalla, R.; Vergouwe, Y.; Steyerberg, E.W.; Boormans, J.L.; Jensen, J.B.; Lorente, J.A.; Real, F.X.; Segersten, U.; et al. FGFR3, TERT and OTX1 as a urinary biomarker combination for surveillance of patients with bladder cancer in a large prospective multicenter study. J. Urol. 2017, 197, 1410–1418. [Google Scholar] [CrossRef] [PubMed]
  38. Hosen, I.; Rachakonda, P.S.; Heidenreich, B.; de Verdier, P.J.; Ryk, C.; Steineck, G.; Hemminki, K.; Kumar, R. Mutations in TERT promoter and FGFR3 and telomere length in bladder cancer. Int. J. Cancer 2015, 137, 1621–1629. [Google Scholar] [CrossRef] [PubMed]
  39. Kinde, I.; Munari, E.; Faraj, S.F.; Hruban, R.H.; Schoenberg, M.; Bivalacqua, T.; Allaf, M.; Springer, S.; Wang, Y.; Diaz, L.A., Jr.; et al. TERT promoter mutations occur early in urothelial neoplasia and are biomarkers of early disease and disease recurrence in urine. Cancer Res. 2013, 73, 7162–7167. [Google Scholar] [CrossRef] [Green Version]
  40. Avogbe, P.H.; Manel, A.; Vian, E.; Durand, G.; Forey, N.; Voegele, C.; Zvereva, M.; Hosen, M.I.; Meziani, S.; De Tilly, B.; et al. Urinary TERT promoter mutations as non-invasive biomarkers for the comprehensive detection of urothelial cancer. EBioMedicine 2019, 44, 431–438. [Google Scholar] [CrossRef] [Green Version]
  41. Hosen, M.I.; Sheikh, M.; Zvereva, M.; Scelo, G.; Forey, N.; Durand, G.; Voegele, C.; Poustchi, H.; Khoshnia, M.; Roshandel, G.; et al. Urinary TERT promoter mutations are detectable up to 10 years prior to clinical diagnosis of bladder cancer: Evidence from the Golestan Cohort Study. EBioMedicine 2020, 53, 102643. [Google Scholar] [CrossRef]
  42. Hosen, M.I.; Forey, N.; Durand, G.; Voegele, C.; Bilici, S.; Avogbe, P.H.; Delhomme, T.M.; Foll, M.; Manel, A.; Vian, E.; et al. Development of sensitive droplet digital PCR assays for detecting urinary TERT promoter mutations as non-invasive biomarkers for detection of urothelial cancer. Cancers 2020, 12, 3541. [Google Scholar] [CrossRef]
  43. Hernandez, S.; Lopez-Knowles, E.; Lloreta, J.; Kogevinas, M.; Amoros, A.; Tardon, A.; Carrato, A.; Serra, C.; Malats, N.; Real, F.X. Prospective study of FGFR3 mutations as a prognostic factor in nonmuscle invasive urothelial bladder carcinomas. J. Clin. Oncol. 2006, 24, 3664–3671. [Google Scholar] [CrossRef]
  44. Sieverink, C.A.; Batista, R.P.M.; Prazeres, H.J.M.; Vinagre, J.; Sampaio, C.; Leao, R.R.; Maximo, V.; Witjes, J.A.; Soares, P. Clinical validation of a urine test (uromonitor-V2((R))) for the surveillance of non-muscle-invasive bladder cancer patients. Diagnostics 2020, 10, 745. [Google Scholar] [CrossRef] [PubMed]
  45. Hajdinjak, T. UroVysion FISH test for detecting urothelial cancers: Meta-analysis of diagnostic accuracy and comparison with urinary cytology testing. Urol. Oncol. 2008, 26, 646–651. [Google Scholar] [CrossRef]
  46. Dimashkieh, H.; Wolff, D.J.; Smith, T.M.; Houser, P.M.; Nietert, P.J.; Yang, J. Evaluation of urovysion and cytology for bladder cancer detection: A study of 1835 paired urine samples with clinical and histologic correlation. Cancer Cytopathol. 2013, 121, 591–597. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  47. Halling, K.C.; Kipp, B.R. Bladder cancer detection using FISH (UroVysion assay). Adv. Anat. Pathol. 2008, 15, 279–286. [Google Scholar] [CrossRef]
  48. Whitson, J.; Berry, A.; Carroll, P.; Konety, B. A multicolour fluorescence in situ hybridization test predicts recurrence in patients with high-risk superficial bladder tumours undergoing intravesical therapy. BJU Int. 2009, 104, 336–339. [Google Scholar] [CrossRef]
  49. Savic, S.; Zlobec, I.; Thalmann, G.N.; Engeler, D.; Schmauss, M.; Lehmann, K.; Mattarelli, G.; Eichenberger, T.; Dalquen, P.; Spieler, P.; et al. The prognostic value of cytology and fluorescence in situ hybridization in the follow-up of nonmuscle-invasive bladder cancer after intravesical Bacillus Calmette-Guerin therapy. Int. J. Cancer 2009, 124, 2899–2904. [Google Scholar] [CrossRef] [PubMed]
  50. Wong, R.; Rosser, C.J. UroSEEK gene panel for bladder cancer surveillance. Transl. Androl. Urol. 2019, 8, S546–S549. [Google Scholar] [CrossRef]
  51. Eich, M.L.; Rodriguez Pena, M.D.C.; Springer, S.U.; Taheri, D.; Tregnago, A.C.; Salles, D.C.; Bezerra, S.M.; Cunha, I.W.; Fujita, K.; Ertoy, D.; et al. Incidence and distribution of UroSEEK gene panel in a multi-institutional cohort of bladder urothelial carcinoma. Mod. Pathol. 2019, 32, 1544–1550. [Google Scholar] [CrossRef]
  52. Dudley, J.C.; Schroers-Martin, J.; Lazzareschi, D.V.; Shi, W.Y.; Chen, S.B.; Esfahani, M.S.; Trivedi, D.; Chabon, J.J.; Chaudhuri, A.A.; Stehr, H.; et al. Detection and surveillance of bladder cancer using urine tumor DNA. Cancer Discov 2019, 9, 500–509. [Google Scholar] [CrossRef] [PubMed]
  53. Carpinito, G.A.; Stadler, W.M.; Briggman, J.V.; Chodak, G.W.; Church, P.A.; Lamm, D.L.; Lange, P.H.; Messing, E.M.; Pasciak, R.M.; Reservitz, G.B.; et al. Urinary nuclear matrix protein as a marker for transitional cell carcinoma of the urinary tract. J. Urol. 1996, 156, 1280–1285. [Google Scholar] [CrossRef]
  54. Mowatt, G.; Zhu, S.; Kilonzo, M.; Boachie, C.; Fraser, C.; Griffiths, T.R.; N’Dow, J.; Nabi, G.; Cook, J.; Vale, L. Systematic review of the clinical effectiveness and cost-effectiveness of photodynamic diagnosis and urine biomarkers (FISH, ImmunoCyt, NMP22) and cytology for the detection and follow-up of bladder cancer. Health Technol. Assess. 2010, 14, 3–4. [Google Scholar] [CrossRef] [Green Version]
  55. Soria, F.; Droller, M.J.; Lotan, Y.; Gontero, P.; D’Andrea, D.; Gust, K.M.; Roupret, M.; Babjuk, M.; Palou, J.; Shariat, S.F. An up-to-date catalog of available urinary biomarkers for the surveillance of non-muscle invasive bladder cancer. World J. Urol. 2018, 36, 1981–1995. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  56. Miyake, M.; Goodison, S.; Rizwani, W.; Ross, S.; Bart Grossman, H.; Rosser, C.J. Urinary BTA: Indicator of bladder cancer or of hematuria. World J. Urol. 2012, 30, 869–873. [Google Scholar] [CrossRef] [Green Version]
  57. Lokeshwar, V.B.; Soloway, M.S. Current bladder tumor tests: Does their projected utility fulfill clinical necessity? J. Urol. 2001, 165, 1067–1077. [Google Scholar] [CrossRef]
  58. Kinders, R.; Jones, T.; Root, R.; Bruce, C.; Murchison, H.; Corey, M.; Williams, L.; Enfield, D.; Hass, G.M. Complement factor H or a related protein is a marker for transitional cell cancer of the bladder. Clin. Cancer Res. 1998, 4, 2511–2520. [Google Scholar]
  59. Sarosdy, M.F.; deVere White, R.W.; Soloway, M.S.; Sheinfeld, J.; Hudson, M.A.; Schellhammer, P.F.; Jarowenko, M.V.; Adams, G.; Blumenstein, B.A. Results of a multicenter trial using the BTA test to monitor for and diagnose recurrent bladder cancer. J. Urol. 1995, 154, 379–383. [Google Scholar] [CrossRef]
  60. Tye, B.K. MCM proteins in DNA replication. Ann. Rev. Biochem. 1999, 68, 649–686. [Google Scholar] [CrossRef]
  61. Stoeber, K.; Tlsty, T.D.; Happerfield, L.; Thomas, G.A.; Romanov, S.; Bobrow, L.; Williams, E.D.; Williams, G.H. DNA replication licensing and human cell proliferation. J. Cell Sci. 2001, 114, 2027–2041. [Google Scholar]
  62. Stoeber, K.; Halsall, I.; Freeman, A.; Swinn, R.; Doble, A.; Morris, L.; Coleman, N.; Bullock, N.; Laskey, R.A.; Hales, C.N.; et al. Immunoassay for urothelial cancers that detects DNA replication protein Mcm5 in urine. Lancet 1999, 354, 1524–1525. [Google Scholar] [CrossRef]
  63. Stoeber, K.; Swinn, R.; Prevost, A.T.; de Clive-Lowe, P.; Halsall, I.; Dilworth, S.M.; Marr, J.; Turner, W.H.; Bullock, N.; Doble, A.; et al. Diagnosis of genito-urinary tract cancer by detection of minichromosome maintenance 5 protein in urine sediments. J. Natl. Cancer Inst. 2002, 94, 1071–1079. [Google Scholar] [CrossRef] [PubMed]
  64. Kelly, J.D.; Dudderidge, T.J.; Wollenschlaeger, A.; Okoturo, O.; Burling, K.; Tulloch, F.; Halsall, I.; Prevost, T.; Prevost, A.T.; Vasconcelos, J.C.; et al. Bladder cancer diagnosis and identification of clinically significant disease by combined urinary detection of Mcm5 and nuclear matrix protein 22. PLoS ONE 2012, 7, e40305. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  65. Dudderidge, T.; Stockley, J.; Nabi, G.; Mom, J.; Umez-Eronini, N.; Hrouda, D.; Cresswell, J.; McCracken, S.R.C. A Novel, non-invasive test enabling bladder cancer detection in urine sediment of patients presenting with haematuria-A prospective multicentre performance evaluation of ADXBLADDER. Eur. Urol. Oncol. 2020, 3, 42–46. [Google Scholar] [CrossRef] [PubMed]
  66. Anastasi, E.; Maggi, M.; Tartaglione, S.; Angeloni, A.; Gennarini, G.; Leoncini, P.P.; Sperduti, I.; Di Lascio, G.; De Stefano, V.; Di Pierro, G.B.; et al. Predictive value of MCM5 (ADXBLADDER) analysis in urine of men evaluated for the initial diagnosis of bladder cancer: A comparative prospective study. Diagn. Cytopathol. 2020. [Google Scholar] [CrossRef] [PubMed]
  67. Roupret, M.; Gontero, P.; McCracken, S.R.C.; Dudderidge, T.; Stockley, J.; Kennedy, A.; Rodriguez, O.; Sieverink, C.; Vanie, F.; Allasia, M.; et al. Diagnostic accuracy of MCM5 for the detection of recurrence in nonmuscle invasive bladder cancer followup: A blinded, prospective cohort, multicenter European Study. J. Urol. 2020, 204, 685–690. [Google Scholar] [CrossRef]
  68. Furuya, H.; Tabula, L.; Lee, R.; Kralovec, P.; Ramsden, M.; Wong, R.; Rosser, C.J. Analytical validation of ONCURIA a multiplex bead-based immunoassay for the non-invasive bladder cancer detection. Pract. Lab. Med. 2020, 22, e00189. [Google Scholar] [CrossRef]
  69. Yazarlou, F.; Modarressi, M.H.; Mowla, S.J.; Oskooei, V.K.; Motevaseli, E.; Tooli, L.F.; Nekoohesh, L.; Eghbali, M.; Ghafouri-Fard, S.; Afsharpad, M. Urinary exosomal expression of long non-coding RNAs as diagnostic marker in bladder cancer. Cancer Manag. Res. 2018, 10, 6357–6365. [Google Scholar] [CrossRef] [Green Version]
  70. Parizi, P.K.; Yarahmadi, F.; Tabar, H.M.; Hosseini, Z.; Sarli, A.; Kia, N.; Tafazoli, A.; Esmaeili, S.A. MicroRNAs and target molecules in bladder cancer. Med. Oncol. 2020, 37, 118. [Google Scholar] [CrossRef]
  71. Hanke, M.; Hoefig, K.; Merz, H.; Feller, A.C.; Kausch, I.; Jocham, D.; Warnecke, J.M.; Sczakiel, G. A robust methodology to study urine microRNA as tumor marker: MicroRNA-126 and microRNA-182 are related to urinary bladder cancer. Urol. Oncol. 2010, 28, 655–661. [Google Scholar] [CrossRef]
  72. Flippot, R.; Beinse, G.; Boileve, A.; Vibert, J.; Malouf, G.G. Long non-coding RNAs in genitourinary malignancies: A whole new world. Nat. Rev. Urol. 2019, 16, 484–504. [Google Scholar] [CrossRef]
  73. Srivastava, A.K.; Singh, P.K.; Rath, S.K.; Dalela, D.; Goel, M.M.; Bhatt, M.L. Appraisal of diagnostic ability of UCA1 as a biomarker of carcinoma of the urinary bladder. Tumour Biol. 2014, 35, 11435–11442. [Google Scholar] [CrossRef]
  74. Wang, X.S.; Zhang, Z.; Wang, H.C.; Cai, J.L.; Xu, Q.W.; Li, M.Q.; Chen, Y.C.; Qian, X.P.; Lu, T.J.; Yu, L.Z.; et al. Rapid identification of UCA1 as a very sensitive and specific unique marker for human bladder carcinoma. Clin. Cancer Res. 2006, 12, 4851–4858. [Google Scholar] [CrossRef] [Green Version]
  75. Wang, Z.; Wang, X.; Zhang, D.; Yu, Y.; Cai, L.; Zhang, C. Long non-coding RNA urothelial carcinoma-associated 1 as a tumor biomarker for the diagnosis of urinary bladder cancer. Tumour Biol. 2017, 39, 1010428317709990. [Google Scholar] [CrossRef] [Green Version]
  76. O’Sullivan, P.; Sharples, K.; Dalphin, M.; Davidson, P.; Gilling, P.; Cambridge, L.; Harvey, J.; Toro, T.; Giles, N.; Luxmanan, C.; et al. A multigene urine test for the detection and stratification of bladder cancer in patients presenting with hematuria. J. Urol. 2012, 188, 741–747. [Google Scholar] [CrossRef] [PubMed]
  77. Kavalieris, L.; O’Sullivan, P.; Frampton, C.; Guilford, P.; Darling, D.; Jacobson, E.; Suttie, J.; Raman, J.D.; Shariat, S.F.; Lotan, Y. Performance characteristics of a multigene urine biomarker test for monitoring for recurrent urothelial carcinoma in a multicenter study. J. Urol. 2017, 197, 1419–1426. [Google Scholar] [CrossRef] [PubMed]
  78. Lotan, Y.; O’Sullivan, P.; Raman, J.D.; Shariat, S.F.; Kavalieris, L.; Frampton, C.; Guilford, P.; Luxmanan, C.; Suttie, J.; Crist, H.; et al. Clinical comparison of noninvasive urine tests for ruling out recurrent urothelial carcinoma. Urol. Oncol. 2017, 35, e515–e531. [Google Scholar] [CrossRef]
  79. Koya, M.; Osborne, S.; Chemasle, C.; Porten, S.; Schuckman, A.; Kennedy-Smith, A. An evaluation of the real world use and clinical utility of the Cxbladder Monitor assay in the follow-up of patients previously treated for bladder cancer. BMC Urol. 2020, 20, 12. [Google Scholar] [CrossRef] [PubMed]
  80. Wallace, E.; Higuchi, R.; Satya, M.; McCann, L.; Sin, M.L.Y.; Bridge, J.A.; Wei, H.; Zhang, J.; Wong, E.; Hiar, A.; et al. Development of a 90-minute integrated noninvasive urinary assay for bladder cancer detection. J. Urol. 2018, 199, 655–662. [Google Scholar] [CrossRef]
  81. Valenberg, F.; Hiar, A.M.; Wallace, E.; Bridge, J.A.; Mayne, D.J.; Beqaj, S.; Sexton, W.J.; Lotan, Y.; Weizer, A.Z.; Jansz, G.K.; et al. Validation of an mRNA-based urine test for the detection of bladder cancer in patients with haematuria. Eur. Urol. Oncol. 2020. [Google Scholar] [CrossRef]
  82. Hurle, R.; Lazzeri, M.; Vanni, E.; Lughezzani, G.; Buffi, N.; Casale, P.; Saita, A.; Morenghi, E.; Forni, G.; Cardone, P.; et al. Active surveillance for low risk nonmuscle invasive bladder cancer: A confirmatory and resource consumption study from the BIAS project. J. Urol. 2018, 199, 401–406. [Google Scholar] [CrossRef] [PubMed]
  83. Hernandez, V.; Llorente, C.; de la Pena, E.; Perez-Fernandez, E.; Guijarro, A.; Sola, I. Long-term oncological outcomes of an active surveillance program in recurrent low grade Ta bladder cancer. Urol. Oncol. 2016, 34, 165.e119–165.e123. [Google Scholar] [CrossRef]
  84. D´Elia, C.; Pycha, A.; Folchini, D.M.; Mian, C.; Hanspeter, E.; Schwienbacher, C.; Vjaters, E.; Pycha, A.; Trenti, E. Diagnostic predictive value of Xpert Bladder Cancer Monitor in the follow-up of patients affected by non-muscle invasive bladder cancer. J. Clin. Pathol. 2018, 72, 140–144. [Google Scholar] [CrossRef]
  85. Pichler, R.; Fritz, J.; Tulchiner, G.; Klinglmair, G.; Soleiman, A.; Horninger, W.; Klocker, H.; Heidegger, I. Increased accuracy of a novel mRNA-based urine test for bladder cancer surveillance. BJU Int. 2018, 121, 29–37. [Google Scholar] [CrossRef] [Green Version]
  86. Valenberg, F.; Hiar, A.M.; Wallace, E.; Bridge, J.A.; Mayne, D.J.; Beqaj, S.; Sexton, W.J.; Lotan, Y.; Weizer, A.Z.; Jansz, G.K.; et al. Prospective validation of an mRNA-based urine test for surveillance of patients with bladder cancer. Eur. Urol. 2019, 75, 853–860. [Google Scholar] [CrossRef]
  87. Hurle, R.; Casale, P.; Saita, A.; Colombo, P.; Elefante, G.M.; Lughezzani, G.; Fasulo, V.; Paciotti, M.; Domanico, L.; Bevilacqua, G.; et al. Clinical performance of Xpert Bladder Cancer (BC) Monitor, a mRNA-based urine test, in active surveillance (AS) patients with recurrent non-muscle-invasive bladder cancer (NMIBC): Results from the Bladder Cancer Italian Active Surveillance (BIAS) project. World J. Urol. 2020, 38, 2215–2220. [Google Scholar] [CrossRef]
  88. Cappellen, D.; De Oliveira, C.; Ricol, D.; de Medina, S.; Bourdin, J.; Sastre-Garau, X.; Chopin, D.; Thiery, J.P.; Radvanyi, F. Frequent activating mutations of FGFR3 in human bladder and cervix carcinomas. Nat. Genet. 1999, 23, 18–20. [Google Scholar] [CrossRef] [PubMed]
  89. Couffignal, C.; Desgrandchamps, F.; Mongiat-Artus, P.; Ravery, V.; Ouzaid, I.; Roupret, M.; Phe, V.; Ciofu, C.; Tubach, F.; Mentre, F.; et al. The diagnostic and prognostic performance of urinary FGFR3 mutation analysis in bladder cancer surveillance: A prospective multicenter study. Urology 2015, 86, 1185–1190. [Google Scholar] [CrossRef]
  90. Knowles, M.A. Role of FGFR3 in urothelial cell carcinoma: Biomarker and potential therapeutic target. World J. Urol. 2007, 25, 581–593. [Google Scholar] [CrossRef] [Green Version]
  91. Billerey, C.; Chopin, D.; Aubriot-Lorton, M.H.; Ricol, D.; Gil Diez de Medina, S.; Van Rhijn, B.; Bralet, M.P.; Lefrere-Belda, M.A.; Lahaye, J.B.; Abbou, C.C.; et al. Frequent FGFR3 mutations in papillary non-invasive bladder (pTa) tumors. Am. J. Pathol. 2001, 158, 1955–1959. [Google Scholar] [CrossRef] [Green Version]
  92. Hayashi, Y.; Fujita, K.; Matsuzaki, K.; Eich, M.L.; Tomiyama, E.; Matsushita, M.; Koh, Y.; Nakano, K.; Wang, C.; Ishizuya, Y.; et al. Clinical significance of hotspot mutation analysis of urinary cell-free DNA in urothelial bladder cancer. Front. Oncol. 2020, 10, 755. [Google Scholar] [CrossRef]
  93. Chou, R.; Buckley, D.; Fu, R.; Gore, J.L.; Gustafson, K.; Griffin, J.; Grusing, S.; Selph, S. Emerging Approaches to Diagnosis and Treatment of Non-Muscle-Invasive Bladder Cancer; Agency for Healthcare Research and Quality: Rockville, MD, USA, 2015. [Google Scholar]
  94. Babjuk, M.; Bohle, A.; Burger, M.; Capoun, O.; Cohen, D.; Comperat, E.M.; Hernandez, V.; Kaasinen, E.; Palou, J.; Roupret, M.; et al. EAU Guidelines on non-muscle-invasive urothelial carcinoma of the bladder: Update 2016. Eur. Urol. 2017, 71, 447–461. [Google Scholar] [CrossRef]
  95. Lenherr, S.M.; Tsai, S.; Silva Neto, B.; Sullivan, T.B.; Cimmino, C.B.; Logvinenko, T.; Gee, J.; Huang, W.; Libertino, J.A.; Summerhayes, I.C.; et al. MicroRNA expression profile identifies high grade, non-muscle-invasive bladder tumors at elevated risk to progress to an invasive phenotype. Genes 2017, 8, 77. [Google Scholar] [CrossRef] [Green Version]
  96. Olivieri, M.; Ferro, M.; Terreri, S.; Durso, M.; Romanelli, A.; Avitabile, C.; De Cobelli, O.; Messere, A.; Bruzzese, D.; Vannini, I.; et al. Long non-coding RNA containing ultraconserved genomic region 8 promotes bladder cancer tumorigenesis. Oncotarget 2016, 7, 20636–20654. [Google Scholar] [CrossRef] [PubMed]
  97. Terreri, S.; Durso, M.; Colonna, V.; Romanelli, A.; Terracciano, D.; Ferro, M.; Perdona, S.; Castaldo, L.; Febbraio, F.; de Nigris, F.; et al. New cross-talk layer between ultraconserved non-coding RNAs, MicroRNAs and polycomb protein YY1 in bladder cancer. Genes 2016, 7, 127. [Google Scholar] [CrossRef] [PubMed]
  98. Pop-Bica, C.; Gulei, D.; Cojocneanu-Petric, R.; Braicu, C.; Petrut, B.; Berindan-Neagoe, I. Understanding the role of non-coding RNAs in bladder cancer: From dark matter to valuable therapeutic targets. Int. J. Mol. Sci. 2017, 18, 1514. [Google Scholar] [CrossRef] [PubMed]
  99. Seitz, A.K.; Christensen, L.L.; Christensen, E.; Faarkrog, K.; Ostenfeld, M.S.; Hedegaard, J.; Nordentoft, I.; Nielsen, M.M.; Palmfeldt, J.; Thomson, M.; et al. Profiling of long non-coding RNAs identifies LINC00958 and LINC01296 as candidate oncogenes in bladder cancer. Sci. Rep. 2017, 7, 395. [Google Scholar] [CrossRef] [Green Version]
  100. Terracciano, D.; Ferro, M.; Terreri, S.; Lucarelli, G.; D’Elia, C.; Musi, G.; de Cobelli, O.; Mirone, V.; Cimmino, A. Urinary long noncoding RNAs in nonmuscle-invasive bladder cancer: New architects in cancer prognostic biomarkers. Transl. Res. 2017, 184, 108–117. [Google Scholar] [CrossRef]
  101. Berindan-Neagoe, I.; Monroig Pdel, C.; Pasculli, B.; Calin, G.A. MicroRNAome genome: A treasure for cancer diagnosis and therapy. CA Cancer J. Clin. 2014, 64, 311–336. [Google Scholar] [CrossRef] [PubMed]
  102. Eissa, S.; Matboli, M.; Essawy, N.O.; Kotb, Y.M. Integrative functional genetic-epigenetic approach for selecting genes as urine biomarkers for bladder cancer diagnosis. Tumour Biol. 2015, 36, 9545–9552. [Google Scholar] [CrossRef]
  103. Breen, V.; Kasabov, N.; Kamat, A.M.; Jacobson, E.; Suttie, J.M.; O’Sullivan, P.J.; Kavalieris, L.; Darling, D.G. A holistic comparative analysis of diagnostic tests for urothelial carcinoma: A study of Cxbladder Detect, UroVysion(R) FISH, NMP22(R) and cytology based on imputation of multiple datasets. BMC Med. Res. Methodol. 2015, 15, 45. [Google Scholar] [CrossRef] [Green Version]
  104. Zuiverloon, T.C.; Nieuweboer, A.J.; Vekony, H.; Kirkels, W.J.; Bangma, C.H.; Zwarthoff, E.C. Markers predicting response to bacillus Calmette-Guerin immunotherapy in high-risk bladder cancer patients: A systematic review. Eur. Urol. 2012, 61, 128–145. [Google Scholar] [CrossRef] [PubMed]
  105. Huang, H.M.; Li, H.X. Tumor heterogeneity and the potential role of liquid biopsy in bladder cancer. Cancer Commun. 2020. [Google Scholar] [CrossRef]
  106. Kamat, A.M.; Briggman, J.; Urbauer, D.L.; Svatek, R.; Nogueras Gonzalez, G.M.; Anderson, R.; Grossman, H.B.; Prat, F.; Dinney, C.P. Cytokine panel for response to Intravesical therapy (CyPRIT): Nomogram of changes in urinary cytokine levels predicts patient response to bacillus calmette-guerin. Eur. Urol. 2016, 69, 197–200. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  107. Salmasi, A.; Elashoff, D.A.; Guo, R.; Upfill-Brown, A.; Rosser, C.J.; Rose, J.M.; Giffin, L.C.; Gonzalez, L.E.; Chamie, K. Urinary cytokine profile to predict response to intravesical BCG with or without HS-410 therapy in patients with non-muscle-invasive bladder cancer. Cancer Epidemiol. Biomark. Prev. 2019, 28, 1036–1044. [Google Scholar] [CrossRef] [PubMed]
  108. Franovic, A.; Raymond, V.M.; Erlander, M.G.; Reckamp, K.L. Urine test for EGFR analysis in patients with non-small cell lung cancer. J. Thorac Dis. 2017, 9, S1323–S1331. [Google Scholar] [CrossRef] [Green Version]
  109. Choudhury, N.J.; Campanile, A.; Antic, T.; Yap, K.L.; Fitzpatrick, C.A.; Wade, J.L., 3rd; Karrison, T.; Stadler, W.M.; Nakamura, Y.; O’Donnell, P.H. Afatinib activity in platinum-refractory metastatic urothelial carcinoma in patients with ERBB alterations. J. Clin. Oncol. 2016, 34, 2165–2171. [Google Scholar] [CrossRef] [Green Version]
  110. Messing, E. Markers of detection. Urol. Oncol. 2007, 25, 344–347. [Google Scholar] [CrossRef] [PubMed]
  111. Hall, M.C.; Chang, S.S.; Dalbagni, G.; Pruthi, R.S.; Seigne, J.D.; Skinner, E.C.; Wolf, J.S., Jr.; Schellhammer, P.F. Guideline for the management of nonmuscle invasive bladder cancer (stages Ta, T1, and Tis): 2007 update. J. Urol. 2007, 178, 2314–2330. [Google Scholar] [CrossRef]
  112. Shariat, S.F.; Karam, J.A.; Lotan, Y.; Karakiewizc, P.I. Critical evaluation of urinary markers for bladder cancer detection and monitoring. Rev. Urol. 2008, 10, 120–135. [Google Scholar] [PubMed]
  113. Ponsky, L.E.; Sharma, S.; Pandrangi, L.; Kedia, S.; Nelson, D.; Agarwal, A.; Zippe, C.D. Screening and monitoring for bladder cancer: Refining the use of NMP22. J. Urol. 2001, 166, 75–78. [Google Scholar] [CrossRef]
  114. Thomas, L.; Leyh, H.; Marberger, M.; Bombardieri, E.; Bassi, P.; Pagano, F.; Pansadoro, V.; Sternberg, C.N.; Boccon-Gibod, L.; Ravery, V.; et al. Multicenter trial of the quantitative BTA TRAK assay in the detection of bladder cancer. Clin. Chem. 1999, 45, 472–477. [Google Scholar]
  115. Goodison, S.; Ogawa, O.; Matsui, Y.; Kobayashi, T.; Miyake, M.; Ohnishi, S.; Fujimoto, K.; Dai, Y.; Shimizu, Y.; Tsukikawa, K.; et al. A multiplex urinary immunoassay for bladder cancer detection: Analysis of a Japanese cohort. J. Transl. Med. 2016, 14, 287. [Google Scholar] [CrossRef] [Green Version]
  116. Chung, W.; Bondaruk, J.; Jelinek, J.; Lotan, Y.; Liang, S.; Czerniak, B.; Issa, J.P. Detection of bladder cancer using novel DNA methylation biomarkers in urine sediments. Cancer Epidemiol. Biomark. Prev. 2011, 20, 1483–1491. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  117. Mengual, L.; Burset, M.; Ribal, M.J.; Ars, E.; Marin-Aguilera, M.; Fernandez, M.; Ingelmo-Torres, M.; Villavicencio, H.; Alcaraz, A. Gene expression signature in urine for diagnosing and assessing aggressiveness of bladder urothelial carcinoma. Clin. Cancer Res. 2010, 16, 2624–2633. [Google Scholar] [CrossRef] [Green Version]
  118. Holyoake, A.; O’Sullivan, P.; Pollock, R.; Best, T.; Watanabe, J.; Kajita, Y.; Matsui, Y.; Ito, M.; Nishiyama, H.; Kerr, N.; et al. Development of a multiplex RNA urine test for the detection and stratification of transitional cell carcinoma of the bladder. Clin. Cancer Res. 2008, 14, 742–749. [Google Scholar] [CrossRef] [Green Version]
  119. Yeung, C.; Dinh, T.; Lee, J. The health economics of bladder cancer: An updated review of the published literature. Pharmacoeconomics 2014, 32, 1093–1104. [Google Scholar] [CrossRef]
  120. Meeks, J.J.; Al-Ahmadie, H.; Faltas, B.M.; Taylor, J.A., 3rd; Flaig, T.W.; DeGraff, D.J.; Christensen, E.; Woolbright, B.L.; McConkey, D.J.; Dyrskjot, L. Genomic heterogeneity in bladder cancer: Challenges and possible solutions to improve outcomes. Nat. Rev. Urol. 2020, 17, 259–270. [Google Scholar] [CrossRef]
  121. Warrick, J.I.; Sjodahl, G.; Kaag, M.; Raman, J.D.; Merrill, S.; Shuman, L.; Chen, G.; Walter, V.; DeGraff, D.J. Intratumoral heterogeneity of bladder cancer by molecular subtypes and histologic variants. Eur. Urol. 2019, 75, 18–22. [Google Scholar] [CrossRef]
Jpm 11 00237 g001 550
Figure 1. Overview of the liquid biopsy biomarkers in urine.
Figure 1. Overview of the liquid biopsy biomarkers in urine.
Jpm 11 00237 g001
Table
Table 1. Current and upcoming liquid biopsy urinary tests.
Table 1. Current and upcoming liquid biopsy urinary tests.
TestVariablesMethodUse in Clinical PracticeCostApprovalReference
Bladder EpiCheckDNA methylation pattern
(15 genomic biomarkers)		RT-PCRDiagnosisNAYes (FDA/CE)[27,28,29,30,31,32]
UrodiagFGFR3 mutations and epigenetic markers (hypermethylation of HS3ST2, SEPTIN9 and SLIT2)PCRDiagnosisNAYes (CE)[33,34,35]
AssureMDXFGFR3, TERT, HRAS mutations, methylation of OTX1, ONECUT2, TWIST1PCRDiagnosisNANo[36,37]
UroMuTERTTERT promoter mutations
(C228T and C250T)		PCRDiagnosisNANo[38,39,40,41,42]
Uromonitor-V2FGFR3, TERT and KRAS hotspot mutationsqPCRDetection of NMIBC recurrenceNAYes (FDA/CE)[43,44]
Urovysion3,7,17 chromosome aneuploidy and loss of 9p21 locusFISHDiagnosis200$/testYes (FDA/CE)[45,46,47,48,49]
Uroseek®Mutations in 11 genes and aneuploidyNGS/SANGERDiagnosis1000$/testNo[50,51]
uCAPP-SeqUrine ctDNA determination NGSDiagnosisNANo[52]
NMP22Nuclear matrix protein released by dead cells in urineELISASurveillance in combination with cystoscopy25$/testYes (FDA/CE)[53,54,55]
BTABasement membrane-derived antigen released by cancer cellsELISASurveillance in combination with cystoscopy40$/testYes (FDA/CE)[56,57,58,59]
ADXBLADDERMCM5 proteinELISASurveillance; prognosis52$/testYes (CE)[60,61,62,63,64,65,66,67]
Oncuria10 protein biomarkers (APOE, ANG, A1AT, CA9, IL8, MMP9, MMP10, PAI1, SDC1, VEGFA)ELISADiagnosisNANo[68]
miRNAsmiR-200, miR-145, and miR-214RT-qPCRPrognosisNANo[69,70,71]
LncRNAUCA-1, UCA1-203, UCA1-201, MALAT1 and LINC00355RT-qPCRDiagnosisNANo[72,73,74,75]
Cxbladder detect and monitormRNA signature in urine
(CDK1, MDK, HOXA13, IGFBP5 and CXCR2)		RT-qPCRDiagnosis, surveillanceNAYes (CE)[76,77,78,79]
Xpert Bladder cancer detect and monitormRNA signature in urine
(ABL1, ANXA10, CRH, IGF2 and UPK1B)		RT-qPCRDiagnosis, surveillance165$/testYes (CE)[80,81,82,83,84,85,86,87]
Abbreviations: FDA: Food and Drug Administration; CE: Conformitè Europëenne; FGFR3: fibroblast growth factor receptor 3; HS3ST2: heparan sulfate-glucosamine 3-sulfotransferase 2; SLIT2: slit guidance ligand 2; TERT: telomerase reverse transcriptase; KRAS: Kirsten RAt sarcoma virus; NMIBC: non-muscle-invasive bladder cancer; ELISA: enzyme-linked immunosorbent assay; MCM5: minichromosome maintenance complex component 5; APOE: apolipoprotein E; ANG: angiogenin; A1AT: alpha-1 antitrypsin: CA9: carbonic anhydrase IX; IL8: interleukin-8, MMP9: metalloprotease-9, MMP10: metalloprotease-10, PAI1: plasminogen activator inhibitor 1, SDC1: Syndecan 1; VEGFA: vascular endothelial growth factor A; bps: base-pairs; RT-qPCR; real time quantitative polymerase chain reaction; NGS: next generation sequencing; CDK1: cyclin-dependent kinase 1, MDK: midkine, HOXA13: homeobox A13, IGFBP5: insulin like growth factor binding protein 5; CXCR2: CXC chemokine receptor 2; ABL1: tyrosine-protein kinase; ANXA10: annexin A10; CRH: corticotropin-releasing hormone, IGF2: insulin like growth factor 2; UPK1B: uroplakin 1B, NA: not available.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Ferro, M.; La Civita, E.; Liotti, A.; Cennamo, M.; Tortora, F.; Buonerba, C.; Crocetto, F.; Lucarelli, G.; Busetto, G.M.; Del Giudice, F.; et al. Liquid Biopsy Biomarkers in Urine: A Route towards Molecular Diagnosis and Personalized Medicine of Bladder Cancer. J. Pers. Med. 2021, 11, 237. https://doi.org/10.3390/jpm11030237

AMA Style

Ferro M, La Civita E, Liotti A, Cennamo M, Tortora F, Buonerba C, Crocetto F, Lucarelli G, Busetto GM, Del Giudice F, et al. Liquid Biopsy Biomarkers in Urine: A Route towards Molecular Diagnosis and Personalized Medicine of Bladder Cancer. Journal of Personalized Medicine. 2021; 11(3):237. https://doi.org/10.3390/jpm11030237

Chicago/Turabian Style

Ferro, Matteo, Evelina La Civita, Antonietta Liotti, Michele Cennamo, Fabiana Tortora, Carlo Buonerba, Felice Crocetto, Giuseppe Lucarelli, Gian Maria Busetto, Francesco Del Giudice, and et al. 2021. "Liquid Biopsy Biomarkers in Urine: A Route towards Molecular Diagnosis and Personalized Medicine of Bladder Cancer" Journal of Personalized Medicine 11, no. 3: 237. https://doi.org/10.3390/jpm11030237

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop