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Urinary Biomarkers in Bladder Cancer: FDA-Approved Tests and Emerging Tools for Diagnosis and Surveillance

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Submitted:

30 September 2025

Posted:

08 October 2025

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Abstract
Bladder cancer is a prevalent malignancy with high mobility and mortality, particularly when diagnosed at an advanced stage. Early detection is critical, as it significantly improves prognosis and the patient's outcome. Bladder cancer also has a high recurrence rate, necessitating long-term surveillance. While cystoscopy remains the gold standard for diagnosis and monitoring. It is invasive and costly. Urine cytology, though widely used, has high specificity for detecting high-grade urothelial carcinoma but suffers from low sensitivity, limited its effectiveness as a stand-alone diagnostics tool. Urinary biomarkers offer a promising, noninvasive alternative for early detection and disease surveillance. This review examines FDA–approved urinary biomarkers tests, including NMP 22, UroVysion, and BTA, highlighting their clinical utility and limitations. Additionally, we explore emerging biomarkers such as DNA methylation assays, genomic alterations, and proteomic signatures. Along with advanced technologies like next-generation sequencing and machine learning-based platforms. These innovations have the potential to enhance diagnostic accuracy, risk stratification, and recurrent monitoring. Ultimately improving early detection and long-term disease management. By evaluating both established and emerging urinary biomarkers, this review aims to provide clinicians and researchers with insights into evolving tools for bladder cancer diagnosis and surveillance.
Keywords: 
bladder cancer
;  
urinary biomarkers
;  
urine cytology
;  
next-generation sequencing
;  
artificial intelligence
Subject: 
Medicine and Pharmacology  -   Urology and Nephrology

Introduction

Bladder cancer is one of the most common malignancies of the urinary tract, ranking among the top ten cancers worldwide in terms of incidence [1]. It is characterized by a high rate of recurrence and significant risk of progression making lifelong surveillance necessary for affected patients [2]. The gold standard for diagnosis and follow-up of bladder cancer has traditionally been cystoscopy, an endoscopic technique that allows direct visualization of the bladder mucosa [3]. Although cystoscopy is highly specific, it is invasive, costly, and often uncomfortable for patients, emphasizing the need for noninvasive diagnostic methods [4].
The earliest attempt to meet this need was urine cytology, introduced in 1945, which became the first widely used urinary biomarker for bladder cancer [5]. By examining exfoliated urothelial cells microscopically, cytology provided a noninvasive method of tumor detection. Although it remains a pivotal tool in clinical practice due to its high specificity for high-grade tumors, its limited sensitivity for low-grade disease pointed to the demand for more advanced biomarkers [6].
Beginning in the early 1990s, a new wave of urinary biomarker assays was developed. These included protein-based tests such as BTA Stat/TRAK and NMP22, which received FDA approval and introduced antigen detection into clinical practice [7,8]. Following that, ImmunoCyt/uCyt+ and UroVysion FISH were developed by targeting cell-surface antigens and chromosomal abnormalities, respectively [9,10].
The 2000s brought an era of molecular biomarkers focusing on telomerase activity, microsatellite instability, and DNA methylation patterns [11,12,13]. In the 2010s, multiparametric molecular platforms such as Cxbladder and AssureMDx integrated gene expression and mutational analyses into clinical testing [14,15].
Most recently, the field has moved toward next-generation approaches, including liquid biopsy panels detecting recurrent mutations (e.g., FGFR3, TERT promoter, TP53), exosomal cargo profiling, and multi-omics platforms incorporating transcriptomics, epigenomics, proteomics, and metabolomics that are enhanced by artificial intelligence [16,17,18,19]. These advances represent a remarkable evolution from simple cytological observation to complex molecular interrogation, reflecting both the challenges and the progress in developing reliable urinary biomarkers for bladder cancer.
In this review, we provide a chronological overview of bladder cancer biomarkers, from cytology to modern molecular platforms, with particular emphasis on emerging technologies such as next-generation sequencing and machine learning.

1945:. Urine Cytology

Urine cytology, first described in 1945 by Papanicolaou and Marshall [5], represents the earliest and most widely used noninvasive urinary biomarker for bladder cancer. The method rapidly gained clinical traction and was further established in the mid-20th century through studies that characterized the cytologic features of bladder tumors [20]. By examining exfoliated urothelial cells microscopically, cytology provided a noninvasive means of tumor detection, with malignant cells recognized by abnormal nuclear morphology, high nuclear-to-cytoplasmic ratios, and irregular chromatin patterns [21,22].
The major strength of urine cytology lies in its high specificity, particularly for high-grade urothelial carcinoma and carcinoma in situ, where diagnostic accuracy approaches 90–100% in some series [6,23]. However, its sensitivity is markedly limited for low-grade tumors, since these cells often resemble normal urothelium and shed less frequently into urine [24]. Additional drawbacks include inter-observer variability, dependence on pathologist expertise, and reduced performance in cases with inflammation or atypical findings [25].
Despite these limitations, urine cytology remains an essential adjunct to cystoscopy in bladder cancer diagnosis and follow-up, and it continues to serve as the benchmark against which newer urinary biomarkers are compared [6,26].

1990s: FDA-Approved Urinary Biomarker Assays

In the early 1990s, several urinary biomarker assays were developed to address the limitations of cytology. Among them, BTA Stat and BTA TRAK were first developed, which detect human complement factor H–related proteins released by bladder tumor cells [7,8]. These tests provided a rapid, point-of-care approach, and although they improved sensitivity compared to cytology, their specificity was reduced due to false positives from hematuria and inflammation [27].
Another milestone was the introduction of NMP22, a nuclear matrix protein released during urothelial cell apoptosis and necrosis [28]. Both an ELISA-based format (NMP22 Test Kit) and a point-of-care version (NMP22 BladderChek) were FDA-approved. These assays demonstrated higher sensitivity than cytology, particularly for recurrent disease [29]. However, like BTA, specificity was compromised in patients with benign urological conditions such as urinary tract infections and stones [30].
To enhance detection accuracy, ImmunoCyt/uCyt+ was developed in the late 1990s. This assay uses fluorescently labeled monoclonal antibodies to detect bladder cancer–associated antigens such as CEA and mucin-like glycoproteins in exfoliated urothelial cells [9]. It demonstrated significantly higher sensitivity than cytology, especially for low-grade tumors, though its requirement for specialized fluorescence microscopy limited widespread adoption [31].
UroVysion fluorescence in situ hybridization (FISH) was introduced around 2000, targeting chromosomal abnormalities commonly seen in bladder cancer (e.g., aneuploidy of chromosomes 3, 7, 17, and deletion of 9p21) [10]. FDA-approved for use in both diagnosis and surveillance, UroVysion offered strong sensitivity for detecting recurrent high-grade disease, though false positives and high costs restricted routine use [32].
Table 1 summarizes the first clinically adopted urinary biomarker assays of the 1990s. These were largely protein-based tests (BTA, NMP22) or immunocytochemical assays (ImmunoCyt).
Collectively, these FDA-approved tests represented a paradigm shift in bladder cancer diagnostics, introducing antigen and chromosomal marker–based detection into clinical practice. While none replaced cystoscopy, they laid the foundation for molecular assays that would emerge in the 2000s and beyond.

2000s: Molecular Biomarkers

The 2000s marked a transition from antigen-based assays toward molecular biomarker approaches that leveraged advances in genomics and molecular biology. Among the earliest investigated was telomerase activity, an enzyme upregulated in most cancers to maintain replicative potential. Several studies demonstrated that telomerase activity in urine and bladder washings had high sensitivity for urothelial carcinoma, particularly in detecting early-stage and recurrent tumors [33,34].
Microsatellite instability (MSI) and loss of heterozygosity (LOH) was one of the important categories. These genomic alterations, especially at chromosome 9p21 and other loci, were detectable in exfoliated urinary cells and showed promise as markers for recurrence monitoring [35,36]. Although highly informative in research, technical complexity and cost limit their translation to routine practice.
DNA methylation–based assays emerged as particularly promising in this decade. Aberrant promoter methylation of tumor suppressor genes such as RASSF1A, APC, and CDKN2A was shown to be frequent in bladder cancer and detectable in voided urine [37,38]. Early clinical studies demonstrated high sensitivity and specificity, positioning methylation as a leading candidate for noninvasive surveillance [39,40,41].
These molecular biomarkers (summarized in Table 2) represented a conceptual leap, shifting bladder cancer diagnostics toward genomic and epigenetic profiling. While not yet widely adopted clinically at the time, they laid the foundation for the multi-gene methylation panels and integrated molecular assays that became prominent in the 2010s.

2010s: Multiparametric Molecular Panels (RNA, DNA, and Methylation Assays)

The 2010s saw the rise of multiparametric molecular platforms for non-invasive bladder cancer detection, leveraging RNA expression, DNA mutations, and epigenetic modifications (summarized in Table 3). These assays aimed to improve sensitivity and specificity over traditional protein- or cytology-based tests while capturing molecular heterogeneity of tumors [42,43,44,45,46,47,48].
Cxbladder, a urine-based mRNA panel, integrates five gene targets (IGFBP5, HOXA13, MDK, CDK1, CXCR2) implicated in tumorigenesis, cell cycle regulation, and inflammation. Clinical studies demonstrated that Cxbladder could stratify patients into high- and low-risk groups, improving evaluation of hematuria and monitoring for recurrence [42,43,44]. Its sensitivity for low-grade tumors is higher than urine cytology, although specificity can be reduced in patients with benign urinary conditions [43,45].
AssureMDx combines mutation analysis (FGFR3, HRAS, TERT promoter) with DNA methylation markers (OTX1, ONECUT2, TWIST1) to detect bladder cancer with high accuracy. This multi-layered approach leverages both genetic and epigenetic alterations, improving detection of primary and recurrent disease [46,47,48]. While not FDA-approved, it has been increasingly adopted as a laboratory-developed test in specialized centers under CLIA-certified protocols [47].
DNA methylation panels gained prominence in this decade, as promoter hypermethylation is a common epigenetic event in bladder cancer [49,50,51,52]. Markers such as TWIST1, NID2, OTX1, and SIM2 were repeatedly validated to distinguish malignant from benign urinary samples, providing a non-invasive alternative to cystoscopy for surveillance and early detection [50,51,52]. Streamlined assays, such as the EarlyTect BCD PENK methylation test, exemplify how DNA methylation diagnostics have evolved from initial research into clinically viable tests [51,53].
Additionally, combined multi-gene panels and RNA expression signatures have been explored for risk stratification and predicting recurrence or progression [2,19,54,55]. These platforms represent a shift from single analyte testing toward integrative molecular diagnostics, paving the way for multi-omics strategies that further enhance diagnostic power in the following decade [2,19,55].

2020s: Advancements in Bladder Cancer Biomarkers (NGS, Exosome-Based, and AI Integration)

The 2020s have been accompanied by significant advancements in bladder cancer diagnostics, propelled by innovations in next-generation sequencing (NGS), exosome-based analyses, and artificial intelligence (AI). These technologies aim to enhance diagnostic accuracy, enable early detection, and support personalized treatment strategies [56,57,58,59,60,61,62,63,64,65,66,67,68].
Next-Generation Sequencing (NGS) has transformed non-invasive bladder cancer diagnostics by enabling comprehensive analysis of multiple genetic alterations in urine-derived DNA. Urinary NGS panels can simultaneously detect mutations in genes commonly altered in bladder tumors, including TERT promoter, FGFR3, TP53, PIK3CA, and ERBB2 [56,57]. TERT promoter mutations are present in approximately 55% of bladder cancers across all stages, while FGFR3 mutations are found in 30–50% of cases, often in low-grade, non-muscle-invasive tumors [56,57]. PIK3CA mutations occur in roughly 35% of cases, TP53 in 24%, and ERBB2 amplifications in a smaller subset typically associated with aggressive disease [56,57,58]. By capturing these alterations in urine, NGS offers a non-invasive method for early diagnosis, tumor monitoring, and longitudinal tracking of clonal evolution [56,57,58].
NGS-based urinary assays have demonstrated high sensitivity and specificity, with some studies reporting diagnostic accuracies above 90% [57,58]. Multi-gene panels outperform single-gene approaches by improving the detection of low-grade tumors and capturing tumor heterogeneity [57,58].
Urinary exosomes, nanoscale extracellular vesicles secreted by tumor cells, have emerged as a rich source of bladder cancer biomarkers. Exosomes carry proteins, DNA fragments, and RNA species, including microRNAs (miRNAs), that reflect the molecular characteristics of the tumor. Studies have identified exosomal miRNAs such as miR-21 and members of the miR-200 family, as well as proteins like survivin, with high diagnostic accuracy for bladder cancer [56,59]. Exosomes are particularly attractive because their contents are stable in urine, allowing non-invasive sampling and repeated monitoring [56,59]. Preliminary studies suggest that exosomal assays may detect early-stage disease with higher sensitivity than conventional protein- or cytology-based tests and may also provide insights into tumor aggressiveness and recurrence risk [56,59].
The integration of Artificial Intelligence (AI) into bladder cancer diagnostics has seen significant advancements in the 2020s, particularly in the analysis of urinary biomarkers and cystoscopic imaging [58,59,60,61,62,63,64,65]. These developments aim to enhance diagnostic accuracy, predict disease progression, and personalize treatment strategies [58,59,60,61,62,63,64,65].
AI algorithms have been applied to analyze complex datasets derived from urinary biomarkers, including miRNA profiles and clinical data [58,61]. For instance, a study by Moisoiu et al. utilized machine learning models—Random Forest, Support Vector Machine (SVM), and XGBoost—to integrate miRNA expression levels with demographic and clinical data, demonstrating improved diagnostic accuracy for bladder cancer [58,61].
Furthermore, AI has been employed to process droplet patterns in blood and urine samples [62]. A study by Demir et al. developed a deep learning model using ResNet-18 architecture, achieving diagnostic accuracies of 97.3% for blood samples and 95.3% for urine samples [62].
AI has also been integrated into cystoscopic imaging to improve the detection and classification of bladder tumors [64]. A study by Amaouche et al. proposed a hybrid convolutional neural network (CNN)-transformer model for bladder cancer detection and segmentation, demonstrating high diagnostic accuracy [64].
Additionally, a multi-task deep learning framework developed by Yu et al. combined EfficientNet-B0 for classification, ResNet34-UNet++ for segmentation, and ConvNeXt-Tiny for molecular subtyping, achieving an accuracy of 93.28%, F1-score of 82.05%, and AUC of 96.41% [63].
AI models have been utilized to predict the recurrence and progression of non-muscle-invasive bladder cancer (NMIBC) [65]. A study by Abbas et al. employed the Tsetlin Machine, an interpretable AI model, to analyze clinical features and predict NMIBC recurrence, achieving an F1-score of 0.80 [65].
In summary, the 2020s have witnessed a rapid evolution in bladder cancer diagnostics, driven by the integration of next-generation sequencing, exosome-based analyses, and artificial intelligence (summarized in Table 4) [56,57,58,59,60,61,62,63,64,65,66,67,68]. These approaches enable highly sensitive and non-invasive detection of genetic mutations, epigenetic changes, and tumor-derived extracellular vesicles, capturing the molecular heterogeneity of bladder cancer more comprehensively than ever before [56,57,58,59,60,61,62,63,64,65,66,67,68]. AI-powered models further enhance diagnostic performance by integrating complex datasets from urinary biomarkers, clinical features, and imaging, allowing for accurate tumor classification, risk prediction, and monitoring of disease recurrence or progression [56,57,58,59,60,61,62,63,64,65,66,67,68]. Collectively, these innovations provide a multi-dimensional, personalized framework that holds promise for improving early detection, guiding treatment decisions, and enabling precision surveillance, ultimately transforming the management and long-term outcomes of bladder cancer patients [56,57,58,59,60,61,62,63,64,65,66,67,68].

Discussion

Current Status of Bladder Cancer Biomarkers

Urinary biomarkers have become an increasingly valuable tool in the non-invasive detection and surveillance of bladder cancer. They offer several advantages, including the potential to identify tumors that may be missed by standard urine cytology, reduce reliance on invasive cystoscopy, and enable repeated, convenient monitoring through simple urine collection. Many biomarkers detect molecular or cellular alterations associated with malignancy, including proteins shed into the urine, genetic mutations, epigenetic changes, and extracellular vesicles such as exosomes. These assays can provide insights not only into the presence of disease but, in some cases, also into tumor biology and risk of recurrence [56,69].
Urinary biomarkers also have important limitations. Sensitivity and specificity can vary depending on tumor grade, stage, and the presence of benign urological conditions such as infection, inflammation, or hematuria, which may cause false-positive or false-negative results. Some assays require specialized laboratory equipment or technical expertise, limiting accessibility in routine clinical practice. Variability in assay performance across different laboratories and platforms can affect reliability, and many tests still require further clinical validation to establish consistent accuracy and predictive value. Cost and reimbursement considerations may also influence their practical implementation, especially for complex multi-analyte or omics-based platforms. Despite these challenges, urinary biomarkers represent a promising adjunct to conventional diagnostic methods, offering the potential to improve early detection, risk stratification, and longitudinal monitoring of bladder cancer patients [60,70].

FDA-Approved Versus Non–FDA-Approved Biomarkers in Clinical Adoption

The development of urinary biomarkers for bladder cancer has been driven by the need for non-invasive tools to complement or reduce reliance on cystoscopy and urine cytology. Several assays have received regulatory approval from the U.S. Food and Drug Administration (FDA), yet their translation into routine practice has been inconsistent. At the same time, a few non–FDA-approved assays are currently in clinical use, underscoring the complex interplay between regulatory designation, payer reimbursement, and clinical adoption.
Among the FDA-approved assays are BTA Stat and BTA TRAK, which detect complement factor H–related proteins; NMP22 and its point-of-care version, NMP22 BladderChek, which measure elevated nuclear matrix protein; ImmunoCyt/uCyt+, which uses fluorescent antibodies to detect tumor-associated antigens in exfoliated cells; and UroVysion FISH, a cytogenetic assay for chromosomal aneuploidies and 9p21 deletion. Although FDA approval confirms safety and analytical validity, these tests demonstrate variable sensitivity and specificity, particularly across tumor grades, and none have displaced cystoscopy as the gold standard for surveillance [56,58,70].
In parallel, non–FDA-approved biomarkers have gained traction, often as laboratory-developed tests performed in CLIA-certified laboratories. These include detection of TERT promoter, and FGFR3 mutations, urine-based methylation panels, and RNA expression signatures derived from both mRNA and microRNA profiling. More advanced platforms such as next-generation sequencing and exosome-based assays are increasingly employed, offering greater sensitivity for low-grade tumors and a more comprehensive molecular characterization than older FDA-approved tests. Despite lacking formal FDA clearance, these assays are frequently integrated into practice at both academic and community levels because of their diagnostic performance and clinical relevance [71,72].
A key factor explaining this apparent paradox is that insurance reimbursement, rather than FDA approval, is the primary determinant of clinical uptake. Several FDA-approved tests have struggled to gain widespread use due to inconsistent coverage by Medicare and private payers. Conversely, non–FDA-approved assays often achieve clinical adoption when supported by real-world evidence of utility and when reimbursed by insurers. Payer decisions, clinical guidelines, and cost-effectiveness analyses therefore exert greater influence on practice patterns than regulatory status alone [58,70,74].
Taken together, the current landscape of bladder cancer biomarkers reflects a divergence between FDA approval and clinical adoption. While FDA-cleared assays provide a regulatory foundation, non–FDA-approved platforms have reshaped the field by offering enhanced diagnostic accuracy and molecular insights. Ultimately, reimbursement policies are the decisive factor for integration into clinical workflows, emphasizing the need for new essays to demonstrate both clinical value and economic justification [59,69,71].

Traditional Versus Emerging Biomarkers in Bladder Cancer Diagnosis

The search for reliable urinary biomarkers in bladder cancer has evolved significantly over the past three decades. Traditional assays were largely designed around the detection of single molecules or cellular alterations, whereas contemporary approaches increasingly employ multi-target platforms and omics-based technologies. This transition reflects a shift from narrow, single-parameter diagnostics to integrative molecular profiling capable of capturing the biological complexity of urothelial carcinoma [56,60].
Early biomarker development focused on individual proteins or cytogenetic changes. Examples include the detection of nuclear matrix protein 22 (NMP22), elevated in urothelial tumors due to increased nuclear turnover; bladder tumor antigen (BTA) assays, which identify complement factor H–related proteins; and ImmunoCyt/uCyt+, which uses antibodies against single antigens such as CEA and mucin-like glycoproteins. Similarly, UroVysion FISH targets a limited set of chromosomal abnormalities (aneuploidies of chromosomes 3, 7, 17, and 9p21 deletion). While these assays represented important advances, their performance has been constrained by moderate sensitivity and specificity, particularly for low-grade tumors, and none have replaced cystoscopy in standard surveillance protocols [58,70].
In contrast, recent biomarker platforms have moved beyond single-molecule detection toward multi-analyte panels and omics integration. Advances in genomics, transcriptomics, epigenomics, proteomics, and metabolomics have enabled assays that capture the heterogeneity of bladder cancer at multiple molecular levels. Multi-gene panels that assess common mutations such as TERT promoter and FGFR3, DNA methylation signatures involving dozens of loci, and RNA expression profiles of mRNA and microRNAs illustrate this expanded scope. Moreover, next-generation sequencing (NGS)–based urine assays can provide comprehensive mutational landscapes, while proteomic and exosome-based platforms analyze complex molecular cargo released from tumor cells. These approaches leverage bioinformatics and, increasingly, machine learning algorithms to integrate multi-dimensional data, offering both improved diagnostic accuracy and prognostic stratification [71,72,73].
This progression from single-protein or cytogenetic markers to multi-complex, system-level assays represent a paradigm shift. Traditional biomarkers laid the foundation for non-invasive testing but proved too limited to capture the biological variability of bladder cancer. Omics-driven approaches, while still undergoing clinical validation, hold promises for greater sensitivity, specificity, and potential integration into precision oncology frameworks. Their ultimate adoption, however, will depend on not only technical performance but also on demonstration of cost-effectiveness and reimbursement feasibility [56,60,74].

Continuity of Biomarker Development

Although we have described urinary biomarkers in a chronological framework, from cytology in the 1940s to multi-omics and AI integration in the 2020s. It is important to recognize that biomarker development is a continuous and evolving process rather than a series of discrete eras. Innovations from the 2000s and 2010s have not become obsolete; rather, they provide the foundation for current and emerging technologies. For example, DNA methylation assays, which first gained attention in the 2010s, continue to evolve with improved sensitivity, streamlined workflows, and broader clinical applicability. The EarlyTect BCD PENK methylation test exemplifies this progression, integrating lessons from earlier methylation studies into a simplified, highly sensitive urine-based assay that achieves excellent performance across diverse populations [75]. This demonstrates how foundational research in previous decades seamlessly extends into modern diagnostics, highlighting a continuum of innovation with ongoing potential to enhance early detection, monitoring, and personalized management of bladder cancer [56,71,76].

Conclusion

Urinary biomarkers have become an increasingly important component of bladder cancer diagnosis and surveillance, offering a non-invasive alternative to cystoscopy and complementing traditional urine cytology [69,70]. They provide the ability to detect tumors earlier, monitor disease recurrence, and gain molecular insights into tumor biology, which can guide personalized patient management [56,60,71]. Traditional biomarkers, such as NMP22, BTA, ImmunoCyt, and UroVysion FISH, established the foundation for non-invasive testing by targeting single proteins or chromosomal abnormalities [58,70]. Emerging platforms, including multi-gene panels, DNA methylation assays, exosome profiling, and integrated multi-omics approaches enhanced by artificial intelligence, now allow for more comprehensive molecular characterization, higher sensitivity, and improved detection across tumor grades [71,72,73,76].
Despite these advantages, urinary biomarkers still face important limitations. Sensitivity and specificity can vary depending on tumor stage, grade, and the presence of benign urological conditions, while technical complexity, cost, and variability across laboratories can limit widespread clinical implementation [56,58,70]. Many emerging assays also require further validation before routine adoption, and reimbursement policies continue to influence their practical use [59,74].
Nonetheless, the future of urinary biomarker research is highly promising. Advances in multi-omics integration, liquid biopsy technologies, and AI-driven predictive modeling have the potential to transform bladder cancer care by enabling precision diagnostics, real-time risk stratification, and personalized surveillance strategies [71,72,75,76]. As these technologies mature, they are expected to reduce reliance on invasive procedures, improve early detection, and ultimately enhance patient outcomes, representing a significant step forward in the management of bladder cancer [56,60,71].

Author Contributions

Conceptualization, Z.Y., J.Z.; writing (original draft preparation), Z.Y., J.Z.; writing (review and editing), F.S. All authors have read and agreed F.to the published version of the manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

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Table 1. Urinary Biomarker Assays in the 1990s – First Generation Protein-Based and Cell-Based Tests.
Table 1. Urinary Biomarker Assays in the 1990s – First Generation Protein-Based and Cell-Based Tests.
Assay Year Introduced / Approved Principle FDA Status Key Notes
BTA Stat Early 1990s Detects complement factor H–related proteins in urine FDA-approved (point-of-care) Rapid immunoassay; higher sensitivity than cytology, but false positives with hematuria/inflammation.
BTA TRAK Early 1990s ELISA detecting complement factor H–related proteins FDA-approved (lab-based) Quantitative version of BTA Stat; improved sensitivity but limited specificity.
NMP22 (ELISA) 1996 Detects nuclear mitotic apparatus protein released during cell death FDA-approved (lab-based) Useful for recurrence monitoring; false positives with benign urological conditions.
NMP22 BladderChek Late 1990s Point-of-care immunoassay detecting NMP22 FDA-approved (POC) Quick test; widely studied in follow-up surveillance.
ImmunoCyt/uCyt+ Late 1990s Fluorescent monoclonal antibodies against bladder tumor–associated antigens (CEA, mucin-like glycoproteins) FDA-approved (adjunct to cytology) Improved sensitivity for low-grade tumors; require fluorescence microscopy.
Cytokeratin 20 (CK20) Assay Late 1990s (research) Immunocytochemistry detecting CK20 expression in urothelial cells Research only Early attempt to integrate cytokeratin markers into urine cytology.
Table 2. Urinary Biomarker Assays in the 2000s – Genetic and Chromosomal Marker Era.
Table 2. Urinary Biomarker Assays in the 2000s – Genetic and Chromosomal Marker Era.
Assay Year Introduced Principle FDA Status Key Notes
UroVysion FISH 2001 Multicolor FISH detecting aneuploidy of chromosomes 3, 7, 17, and 9p21 deletion FDA-approved Gold standard molecular cytogenetics assay; strong for high-grade and equivocal cytology.
Microsatellite Analysis Early 2000s (research) Detects loss of heterozygosity (LOH) in urine DNA Research only Pioneered DNA-based urinary diagnostics; labor intensive.
hTERT Promoter Mutations Early 2000s (research) PCR-based detection of telomerase reverse transcriptase mutations Research only One of the most frequent alterations in bladder cancer.
FGFR3 Mutation Assays 2000s (research) Detects FGFR3 hotspot mutations in urine Research only Associated with low-grade, non-muscle-invasive bladder cancers.
Survivin Assay 2000s (research) Detects survivin protein/mRNA in urine Research only Marker of apoptosis inhibition; promising but variable performance.
CYFRA 21-1 2000s Detects soluble cytokeratin 19 fragments in urine Research only Evaluated in several studies; modest diagnostic accuracy.
Table 3. Urinary Biomarker Assays in the 2010s – Multi-Marker Panels and Methylation Signatures.
Table 3. Urinary Biomarker Assays in the 2010s – Multi-Marker Panels and Methylation Signatures.
Assay Year Introduced Principle FDA/CE Status Key Notes
Cxbladder 2013 Measures expression of 5 mRNA genes (MDK, HOXA13, CDC2, IGFBP5, CXCR2) LDT (NZ, US) High sensitivity; used for both diagnosis and surveillance.
Bladder EpiCheck 2016 DNA methylation panel of 15 genomic loci CE-marked (EU) Robust negative predictive value for recurrence.
Xpert Bladder Cancer Monitor 2017 qRT-PCR detecting 5 bladder cancer mRNAs CE-marked (EU) Cartridge-based, automated, rapid workflow.
AssureMDx 2017 Detects FGFR3, HRAS, TERT mutations plus methylation markers LDT High NPV in hematuria patients; used to triage cystoscopy.
UroMark 2010s (UK research) High-throughput methylation panel (>150 loci) Research only Developed as a large-scale epigenetic screening assay.
ADx Bladder Test 2010s (France) Detects specific mRNA biomarkers in urine CE-marked Used in Europe for surveillance and follow-up.
Table 4. Urinary Biomarker Assays in the 2020s – Advanced Genomics, Exosomes, and AI Integration.
Table 4. Urinary Biomarker Assays in the 2020s – Advanced Genomics, Exosomes, and AI Integration.
Assay Year Introduced Principle FDA/CE Status Key Notes
UroSEEK 2020s NGS detecting mutations (TERT, FGFR3, TP53, others) and aneuploidy Clinical trials High sensitivity; integrates multiple molecular alterations.
ExoDx (ExosomeDx) Bladder Test 2020s Exosomal RNA and protein profiling Research/LDT Leverages extracellular vesicles as tumor carriers.
OncoUrine 2020s Targeted NGS + urine cfDNA analysis CE-marked (China/EU) Provides recurrence monitoring; expanding global use.
AI-enhanced Digital Cytology 2020s Deep learning applied to cytology slides + molecular inputs Research/early adoption Improves accuracy of urine cytology; integrated workflows emerging.
EarlyTect BCD 2024 PENK gene methylation assay in urine DNA CE-marked (Korea) Single-gene streamlined test; validated in hematuria patients.
miRNA Panels (e.g., miR-126, miR-146a, miR-200 family) 2020s (research) Urinary exosomal or free miRNA profiling Research only Promising biomarkers, under clinical validation.
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