Gene-based urinary biomarkers for bladder cancer: An unfulfilled promise?

Urologic Oncology: Seminars and Original Investigations ] (2013) 1–9

Review article

Gene-based urinary biomarkers for bladder cancer: An unfulfilled promise?$ Nikhil Sapre, M.B.Ch.B.a,b,*, Paul D. Anderson, M.B.B.S., F.R.A.C.S.a,b, Anthony J. Costello, M.B.B.S., M.D., F.R.A.C.S., F.R.C.S.I. (Hon)a,b, Christopher M. Hovens, Ph.D.a,b, Niall M. Corcoran, M.B.B.Ch., B.A.O., Ph.D., F.R.A.C.S.a,b a

Department of Urology, Royal Melbourne Hospital, Parkville, Victoria, Australia Department of Surgery, University of Melbourne, Parkville, Victoria, Australia

b

Received 22 May 2013; received in revised form 1 July 2013; accepted 1 July 2013

Abstract Objective: Noninvasive biomarkers are used routinely in the clinical management of several cancers but bladder cancer detection and surveillance remains dependent on invasive procedures such as cystoscopy. No validated biomarker currently exists in routine clinical practice other than cytology. Gene-based testing has shown great promise for biomarker profiling and this review addresses the current state of biomarker research in bladder cancer. Materials and methods: A comprehensive review of all published literature on urinary biomarkers from 1970 - 2012 was conducted in PubMed. Keywords used alone or in combination were bladder cancer, diagnosis, surveillance, urinary biomarker, molecular biomarkers, methylation, gene expression, single nucleotide polymorphism and microRNA. The cited references of the manuscripts included in the review were also screened. Results: We have reviewed various strategies currently used for gene-based biomarker profiling of bladder cancer. We have comprehensively summarized the performance of several biomarkers in the diagnosis and surveillance of bladder cancer. Finally we have identified biomarkers that have shown potential and now deserve the opportunity to be validated in the clinical setting. Conclusion: Several gene-based urinary biomarkers have demonstrated promise in initial studies, which now need to be rigorously validated in the clinical setting for them to be translated into clinically useful tests in diagnosis, surveillance or risk-stratification of bladder cancer. Crown Copyright r 2013 Published by Elsevier Inc. All rights reserved. Keywords: Bladder cancer; Urinary biomarker; Recurrence; Molecular biomarkers; microRNA

1. Introduction Modern developments in genomics offer new approaches to biomarker screening, which has led to a plethora of biomarker research over the past decade. Although molecular profiling of tumors has resulted in clinically useful biomarkers in selected cancers such as breast and melanoma, no biomarker is used routinely in the clinical management of bladder cancer (BCa) other than cytology. This coupled with the high recurrence rate of BCa has led to the reliance on invasive procedures such as cystoscopy for detection and surveillance of BCa. The morbidity of cystoscopy is often underestimated, and patient ☆

N.S. is supported by postgraduate scholarships from the Royal Australasian College of Surgeons, Cancer Council Victoria, and the Cybec Cancer Research Foundation. * Corresponding author: Tel.: þ613-9342-7294; fax: þ613-9342-8928. E-mail address: [email protected] (N. Sapre).

adherence with surveillance is as low as 40% [1]. It is also an expensive and resource-intensive procedure, making BCa the single most expensive cancer to treat per incident case from diagnosis to death [2]. Finally, flexible cystoscopy has a definite false-negative rate, particularly for carcinoma in situ. There is a pressing need for an accurate noninvasive test to assist diagnosis and surveillance of BCa. Urine is in direct contact with BCa cells, and hence is an ideal source for investigation of noninvasive biomarkers of BCa. Why is it that despite several promising reports of urinary biomarkers over the past decade that we still lack a urinary biomarker for clinical management of BCa? The answer lies in the lack of adherence by researchers in the discovery phase of biomarker development to a formal validation structure to guide the clinical development of a biomarker. To address this, the National Cancer Institute has recently proposed a framework for guiding biomarker development [3]. This starts with preclinical testing to identify potentially useful biomarkers

1078-1439/$ – see front matter Crown Copyright r 2013 Published by Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.urolonc.2013.07.002

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(Phase 1—hypothesis generation). This is then followed by the development of the assay on patient samples (Phase 2— optimization) before the ability of the assay to detect cancer in a potential clinical setting, then tested on a group of patient samples (Phase 3—discovery). The next phase involves retrospective validation of these results in a larger patient sample cohort, after which the biomarker is tested prospectively in a clinical setting to quantify its performance and efficacy (Phase 4—validation). Finally, the biomarker must be rigorously tested to assess its cost-effectiveness and effect on cancer mortality (Phase 5—cancer control). In this review, we use this framework to discuss the urinary genetic, transcriptomic, and epigenetic biomarkers that have emerged from recent evidence for the management of BCa and highlight those that now are worthy of further validation and clinical translation.

2. Urinary biomarkers for BCa Cytology, the only urinary test that currently aids cystoscopy in routine follow-up of patients has high interobserver variability and poor sensitivity especially for low-grade tumors [4]. Several studies now support the costeffectiveness of incorporating noninvasive urinary biomarkers in the surveillance of BCa [2]. An ideal noninvasive test for BCa should give a bedside result, be cheap, easy to use, reliable and accurate, and not be affected by inflammation and infection. Most importantly, it must have a high negative predictive value (sensitivity) to avoid missing tumors. Over the past 2 decades, several important genetic changes in BCa have been identified. Technology allowing rapid nucleic acid extraction, various panels of biomarkers to be multiplexed in parallel in a high-throughput fashion at affordable costs combined with the proven stability of DNA and RNA in urine make urinary genomic markers a rich source of noninvasive biomarkers for BCa.

3. Protein- and cell-based urinary biomarkers There are several protein- and cell-based commercial and investigational markers that have been the subject of much research, such as nuclear matrix protein 22, bladder tumor antigen, ImmunoCyt, BLCA, and hyaluronic acid/hyaluronidase, which have been extensively reviewed previously and are not discussed further here. Table 1 summarizes the current commercial and investigational urinary biomarkers in BCa. However, the performance of such cell- and protein-based tests has been too inadequate to incorporate them into routine clinical practice, primarily because they are affected by other bladder conditions such as infection, inflammation, and intravesical therapy, and this has given a way for gene-based biomarker testing in more recent times. The high-throughput technologies that characterize modern genomics are still lagging in proteomics, and it is likely that,

Table 1 Established/commercial and investigational urinary biomarkers for detection and surveillance of bladder cancer Protein- and cell-based detection Established/commercialized  Cytology  ImmunoCyt  BTA stat/TRAK  NMP22 Investigational  Telomerase  BLCA-4  Hyaluronic acid (HA/HAse)  Lewis X antigen  Survivin Gene-based detection Established/commercialized  FISH (UroVysion)  Cxbladder (uRNA-2) Investigational  FISH (Aurora kinase A)  Microsatellite/LOH detection  DNA methylation  miRNA  mRNA (e.g., UCA-1) BTA ¼ bladder tumor antigen; NMP ¼ nuclear matrix protein; UCA ¼ urothelial carcinoma–associated gene.

in the future, advances in these would give a further impetus to proteomic molecular profiling.

4. Fluorescence in situ hybridization (FISH) 4.1. UroVysion BCa has a number of well-defined genetic changes. UroVysion FISH is an assay that relies on the detection of the most common chromosomal changes in the BCa in exfoliated cells in urine. It uses 2 types of probes—centromeric enumeration probes that detect the aneuploidy of chromosome 3, 7, and 17 and locus-specific probes that detect the loss of tumor suppressor genes (TSGs) in malignant urothelial cells. A positive result for BCa is usually defined as a finding of more than 5 urothelial cells with a gain of more than 2 chromosomes, or 10 cells with a gain of a single chromosome, or 12 or more cells with homozygous loss of the 9p21 locus; however, these values differ amongst institutions [5]. The sensitivity of this test in detection of BCa ranges from 69% to 85% with a specificity of 78% to 92% [4–8]. In patients undergoing surveillance for non–muscle invasive bladder cancer (NMIBC), the test sensitivity is 71% and the specificity is 94.5% [8]. The potential of UroVysion in risk stratification of BCa first came from the study by Bollman et al. [9] who found that in the

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surveillance of patients with NMIBC, the ones with a negative cystoscopy but positive FISH results have a significantly higher risk of recurrence compared with those with negative cystoscopy and FISH results. This suggests that it may have the ability to predict small cancers not visible at cystoscopy or detect subclinical genetic changes before cancers progress to large papillary tumors. Kipp et al. [10] demonstrated the utility of UroVysion in predicting response to intravesical therapy with bacillus Calmette-Guerin. Patients with a negative FISH results at biopsy after bacillus Calmette-Guerin had significantly lower recurrence rates and progression to muscle-invasive disease than those with positive FISH results. However, owing to lack of standardization of testing, need for expensive laboratory equipment, specificity lower than cytology, and sensitivity lower than cystoscopy, UroVysion FISH is currently not used in routine clinical practice despite being well studied at several centers. 4.2. Aurora kinase A (AURKA) AURKA gene is an important regulator of mitosis and is overexpressed in several cancer cells. Using FISH, Park et al. [11] examined AURKA gene amplification in exfoliated cells in urine samples as a biomarker for the detection of BCa. Using distinct training (23 cancers and 7 healthy controls) and validation (100 BCa and 148 controls) sets, the FISH test was able to differentiate between urine from patients with BCa and healthy controls with a specificity of 96.6% and sensitivity of 87% and had an area under the receiver operating characteristic curve of 0.94. The degree of gene amplification was also associated with higher grade. Based on these results, this biomarker merits further validation in independent prospective multicenter studies. However, its use in the surveillance setting for tumor recurrence as opposed to diagnosis remains unexplored.

5. Microsatellites and single nucleotide polymorphisms (SNPs) Microsatellites are highly polymorphic, short tandem repeats that result from failure in DNA mismatch repair and are important players in carcinogenesis [12]. Microsatellite analysis (MSA) targets such tandem repeats in genomic DNA to evaluate loss of heterozygosity (LOH) that occurs with tumor cell transformation. Several studies have shown that these microsatellite changes can be profiled in urine for the detection of BCa cells [13–20] and are more sensitive than conventional cytology especially for low-grade tumors. Despite numerous studies identifying several potential microsatellite markers linked to BCa, contrasting conclusions amongst studies and lack of validation of positive results has tempered interest in this area recently.

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Steiner et al. [20] first reported the potential of MSA in BCa by testing serial urine samples from 21 patients undergoing surveillance for BCa for 20 polymorphic satellite markers with a sensitivity of 91% and a specificity of 100%. Evidence that mutations in tissue are detectable in urine came from another study [19], where in voided-urine samples of 119 patients, the combination of cytology with LOH analysis detected BCa with sensitivity of 88.2% and specificity of 97.1% and performed significantly better than cytology alone. Seripa et al. [13] also highlighted the ability of MSA to detect low-grade and lowstage tumors much better than cytology with a sensitivity of 95% for grades G1–G2 and 100% for pTis and pTa tumors compared with a sensitivity of 79% of cytology. This test also correctly identified the absence of BCa in healthy controls with 100% accuracy. However, this was a small study of 34 patients and a heterogeneous patient population of primary and recurrent tumors without a validation cohort. Similarly, a prospective study of 91 patients undergoing surveillance [14] showed that microsatellite LOH analysis was superior to UroVysion FISH and conventional cytology especially for the detection of low-grade (G1 60%; G2 52%) tumors. Urine LOH combined with cytology identified 93% of all patients with a recurrence, showing the potential utility of such analyses in surveillance regimens. Roupret et al. [21] found that MSA using 6 marker panel was significantly more sensitive than an 11-gene DNA methylation panel in noninvasive detection of recurrence in patients undergoing surveillance for BCa (area under the curve [AUC] 0.92 vs. 0.45). However, this study also lacked a validation arm and enrolled only 40 patients, of which, only 14 showed positive results for recurrence. However, other studies have contradicted these findings and suggested that MSA has insufficient sensitivity and is not costeffective enough to replace cystoscopy in the management of BCa. Van der Aa et al. [17] found that although MSA of voided-urine samples in 815 episodes showed that patients with positive MA results had a higher risk of recurrence, sensitivity of MSA for detection of a recurrence was quite low at 58% with a specificity of 73%. Similarly, in a cost-effectiveness study, de Bekker-Grob et al. [16] concluded that replacing 3monthly cystoscopy with 3-monthly MSA of voided urine with cystoscopy at 3, 12, and 24 months was not cost-effective owing to MSA being not sensitive enough (58%) and more expensive compared with routine cystoscopy. Few studies have examined urinary SNP profiling to detect BCa and with contrasting results. Evidence for the utility of high-throughput platforms for urinary SNP profiling in BCa came from Hoque et al. [15] who studied the allelic imbalance in voided urine from 31 patients with BCa using SNP arrays in parallel with microsatellite instability. They found that SNP alternations were more common in higher stage and grade tumors and detected BCa with 100% sensitivity compared with healthy controls. However, these findings were contrasted by another study by Coenen et al. [18] who used Affymetrix SNP arrays to analyze copy number changes in voided urine from 158 patients with BCa undergoing surveillance. They found that patients with

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a tumor recurrence had more copy number changes compared with the ones with nonrecurrence; however, the inadequate performance of this test (sensitivity 78%, specificity 47%, and AUC 0.67) led them to conclude that SNP profiling was not suitable as a replacement for cystoscopy in BCa surveillance. Small number of studies with no validation and conflicting results mean that neither MSA nor SNP profiling are currently suitable alternatives for replacing cystoscopy.

6. DNA methylation DNA methylation in urine is the most-studied epigenetic marker in BCa with several promising markers worthy of validation in the clinical setting. Several studies on bladder tumor tissue have shown that hypermethylation of gene promoters especially in TSGs leading to transcriptional silencing of TSGs is a very important mechanism of carcinogenesis [22]. Methylomic alterations are thought to occur early in BCa with a presence of DNA hypermethylation field effect [23] and may progressively drive BCa to become invasive [24]. It has now been shown that these methylomic changes are detectable in urine [25–48]. This has translated to several candidate-driven investigations using qualitative or quantitative methylation-specific polymerase chain reaction (PCR) in urine. Low-throughput approaches are making way for multiplexed techniques such as methylation-specific multiplex ligation-dependent probe amplification and MethylCap sequencing. Table 2 summarizes the markers investigated for studying DNA methylation in urine for BCa. There has been a large variation in the sensitivity of the reports with the number varying from 50% to 94%. Improvement in technology, selection of candidate markers, and profiling for a panel of multiple markers have resulted in enhancement of performance of such assays. Although the potential of DNA methylation as a urinary biomarkers in the diagnostic setting was first reported by Chan et al. [25] and since been replicated by many, only a handful of groups have recently reported the results for a search of a DNA methylation biomarker for the surveillance of BCa [21,44,46]. In a small study of 40 patients, Roupret et al. [21] reported the sensitivity of an 11-gene panel to be 86%, with the specificity of 8% (AUC 0.45). Zuiverloon et al. [44] found that a panel of 4 gene markers predicted recurrence in the surveillance of 94 patients with BCa with a sensitivity of 72% and specificity of 55%. Most recently Reinert et al. [46] analyzed 206 voided-urine samples from patients undergoing surveillance for BCa using 6 methylation markers previously shown to differentiate BCa from healthy controls. When compared with cystoscopy, they achieved a test sensitivity and specificity of 87% to 94% and 28% to 47%, respectively. Methylation of POU4F2 and ZNF154 showed an anticipatory effect with 63% to 68% of patients with methylation-positive results recurring at 12

months compared with 8% to 12% of patients with methylation-negative results. The methylation status of ZNF154, HOXA9, POU4F2, TWIST1, and VIM was significantly associated with recurrence-free survival. Several markers such as APC [29,30,41,44,48], RARβ [25,40,47,48], RASSF1 [26,29,33,34,37,41], E-cadherin [25,33,37], BRCA1 [34,40], SFRP [32,41,43], human telomerase reverse transcriptase [27,42,44], and bcl2 [27,34,42] have been shown to have a high sensitivity across multiple studies and merit independent validation in prospective studies. Such studies should now consist of a panel of multiple markers, ideally be multiinstitutional, have robust study design in a specific clinical setting, and be sufficiently powered to draw conclusions about whether the panel would provide additional benefit over current clinicopathological models.

7. Gene expression Many have studied mRNA gene expression using highthroughput as well as candidate-driven approaches. The largest impediment to clinical translation of these has been a lack of standardization of assays and validation of results, which is especially important in a dynamic entity like gene expression. The most promising new biomarker and the closest to clinical translation is the uRNA2 assay (Cxbladder; Pacific Edge, New Zealand). In the discovery phase, they [49] used microarray data from BCa and healthy tissue to generate a panel of genes that was differentially expressed in various stages and grades of BCa compared with normal urothelium. After excluding the markers overexpressed in blood and inflammatory cells, candidate urine markers were selected and tested in voided-urine samples from 75 patients with transitional cell carcinoma (TCC) and 77 control samples to generate a mRNA panel (CDC2, MDK, IGFBP5, and HOXA3) that predicted the presence of cancer in the bladder with a sensitivity of 48% (Ta), 90% (T1), and 100% (4T1) and specificity of 85%. These markers were then used to develop an optimized commercial test, which was significantly better than cytology as well as nuclear matrix protein 22 BladderChek and enzyme-linked immunosorbent assay tests, with an overall sensitivity of 82% and specificity (fixed) of 85% in assessing patients with hematuria in a following study [50]. Furthermore, it was also able to distinguish between Ta low-grade and other cancers with a sensitivity and specificity of 90% and 91%, respectively, indicating a role in risk stratification of patients. Clinical trials testing the performance of this test in the surveillance setting are currently ongoing. This assay is current awaiting Food and Drug Administration approval pending results from large multicenter validation studies. Urquidi et al. [51] used Affymetrix arrays to predict presence of cancer in the exfoliated urothelia of 92 patients (training set 52 BCa and 40 controls). Using computational analyses and leave-one-out cross-validation approach, they

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Table 2 Studies investigating the potential of DNA methylation status of genes in urine as biomarkers of bladder cancer References

Cohort size 39 24 57 77

Clinical Setting

Methodology

Sensitivity (%)

Specificity (%)

Genes profiled

Diagnostic Diagnostic Diagnostic Diagnostic

MSP MSP MSP qMSP

91 50 78 49

77 100 100 100

DAPK, RARβ, E-cadherin, and p16 RASSF1 DAPK, BCL2, and hTERT Laminin

87 93 (invasive) 69 61 69 92 65 94 83 90 85 88–100 62 76 87 63–72 89

100 NA 100 93 60 87 80 90 100 93 95 34–65 100 98 95 55–58 87

APC, RASSF1A, and p14 APC and cyclinD2 CDKN2A, ARF, MGMT, and GSTP1 SFRP1, SFRP2, SFRP4, SFRP5, WIF1, and DKK3 RASSF1A, E-cad, and APC multiplea Myopodin GDF15, TMEFF2, and VIM E-cadherin, p14, and RASSF1A TWIST1 and NID2 MYO3A, CA10, SOX11, PENK, and DBC1 BRCA1, WT1, and RARβ FGFR3, APC, RASSF1A, and SFRP2 BCL2 and hTERT IRF8, p14, and SFRP1 APC, TERT_a, TERT_b, and EPNRB VAX1, KCNV1, TAC1, PPOX1, and CFTR

82–89

94–100

65 94

89.7 NA

EOMES, HOXA9, POU4F2, TWIST1, VIM, and ZNF154 RARβ2 APC, RARβ, and Survivin

Chan et al. [25] Chan et al. [26] Friedrich et al. [27] Sathynarayana et al. [28] Duliami et al. [29] Pu et al. [30] Hoque et al. [31] Urakami et al. [32] Yates et al. [33] Yu et al. [34] Cebrian et al. [35] Costa et al. [36] Lin et al. [37] Renard et al. [38] Chung et al. [39] Cabello et al. [40] Serizawa et al. [41] Vinci et al. [42] Chen et al. [43] Zuiverloon et al. [44] Zhao et al. [45]

6 55 269 44 104 168 164 110 66 466 228 146 146 213 49 208 238

Diagnostic Diagnostic Diagnostic Diagnostic Diagnostic Diagnostic Diagnostic Diagnostic Diagnostic Diagnostic Diagnostic Diagnostic Diagnostic Diagnostic Diagnostic Surveillance Diagnostic

Reinert et al. [46]

184

Surveillance

qMSP MSP qMSP qMSP qMSP MSP MSP qMSP MSP qMSP qMSP MS-MLPA qMSP qMSP qMSP MS-MLPA MethylCap/ Seq MS-HRM

Eissa et al. [47] Berrada et al. [48]

216 48

Diagnostic Diagnostic

qMSP MSP

MSP ¼ methylation-specific polymerase chain reaction; qMSP ¼ quantitative methylation-specific polymerase chain reaction; MS-HRM ¼ methylationspecific high-resolution melting; MS-MLPA ¼ methylation-specific multiplex ligation-dependent probe amplification. a SALL3, CFTR, ABCC6, HPR1, RASSF1A, MT1A, RUNX3, ITGA4, BCL2, ALX4, MYOD1, DRM, CDH13, BMP3B, CCNA1, RPRM, MINT1, and BRCA1.

derived a 14-gene panel that could predict the presence of cancer in the bladder with 90% sensitivity and 100% specificity and AUC of 0.98 which validated well in an independent cohort of 81 patients (44 BCa and 37 controls) using quantitative reverse transcriptase (qRT)-PCR (AUC 0.93). Bongiovanni et al. [52] showed that expression levels of SEPT4, a ubiquitously expressed cell cycle regulator, were up-regulated in urine of patients with BCa (41 BCa and 17 healthy controls) and classified these correctly with sensitivity and specificity of 93% and 65%, respectively (AUC 0.798). Similarly, Wang et al. [53], using qRT-PCR, showed that urothelial carcinoma–associated gene 1 was upregulated in urine of patients with upper and lower tract TCC and detected TCC with a sensitivity of 81% (91% in patients with high-grade disease) and specificity of 92% in a cohort of 127 patients with TCC and 85 control patients. Neither of the latter 2 studies had validation arms. All these studies have shown promise, and these gene signatures represent good candidates for further validation. Other markers such as fibroblast growth factor receptor 3 (FGFR3), survivin, and telomerase have shown much less promise despite several independent studies. Two large studies [54,55] have shown that the sensitivity of FGFR3 in

detection of BCa is 58% to 62%, which is better than cytology but largely inadequate to challenge cystoscopy. Zuiverloon et al. [55] also showed that in 463 patients undergoing surveillance, presence of FGFR3 mutation in urine was associated with a 3.8-fold risk of recurrence at a mean of 3.5-year of follow-up. Measuring the overexpression of telomerase by telomeric repeat amplification protocol or human telomerase reverse transcriptase assays has shown extremely variable performance but most report sensitivities of approximately 60% to 90% and specificities of 40% to 70% [56,57]. 7.1. MicroRNAs (miRNAs) miRNAs are known to be regulators of epigenetic processes, are central to carcinogenesis, exhibit tissuespecific expression, and have been investigated as tissue biomarkers in various cancers [58] including BCa. Recognition that miRNAs are stable even in the cell-free fraction in body fluids makes urinary profiling for miRNAs a novel avenue for the development of a biomarker that may be used in a diagnostic or surveillance setting in BCa. To date, most studies have used qRT-PCR for miRNA profiling, but

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Table 3 Studies investigating the potential of urinary microRNAs (miRs) as biomarkers of bladder cancer References

Sample size

Sensitivity (%)

Specificity (%)

miRs profiled/ significant miRs

Platform

Key findings Ratio of miR-126:miR-152 in urine enabled the detection of BCa compared with controls (AUC 0.77) miR-452 (AUC 0.848) and miR-222 (AUC 0.718) in urine provided accurately distinguished between patients with BCa and controls miR 96 (71%) and 183 (74%) had good sensitivity in distinguishing BCa from controls as well as correlation of tumor stage/grade. miR 96 when used with cytology increased sensitivity of cytology from 43%–78%. miR-200 family, miR-192, and miR-155 down-regulated in bladder cancer patients of which the former 2 correlated with urinary expression of EMT markers. Predicts BCa with sensitivity and specificity of 100% and 52.6%, respectively miR-145 levels were able to distinguish patients with BCa from noncancer controls (AUC 0.73 and 0.79 and sensitivity of 77.8% and 84.1% for NMIBC and MIBC, respectively). miR-200a was an independent predictor of NMIBC recurrence (OR 0.45) miRs-135b/15b/1224-3p detected bladder cancer with a high sensitivity and sufficient specificity and was correct in 86% of patients

Hanke et al. [59]

83

82

72

157 miRs 126 and 152

qRT-PCR

Puerta-Gil et al. [60]

94

–

–

3 miR-143, 222, and 452

qRT-PCR

Yamada et al. [61]

174

71.0 (miR96) 74.0 (miR183)

89.2 (miR96) 77.3 (miR183)

2 miR 96 and 183

qRT-PCR

Wang et al. [62]

75

100

52.6

miR-200 family, 205, 192, miR155, and 146a

qRT-PCR

Yun et al. [63]

354

77.8 (NMIBC) 84.1 (MIBC)

61.1 (NMIBC) 61.1 (MIBC)

2 miR 145 and 200a

qRT-PCR

Miah et al. [64]

121

94.1

51

15 miRs-15a/15b/241/27b/100/ 135b/203/212/ 328/1224

qRT-PCR

MIBC ¼ muscle-invasive bladder cancer; EMT ¼ epithelial-mesenchymal transition; OR ¼ odds ratio.

in the future, we are likely to see the use of microarrays as well as miRNA sequencing allowing for rapid profiling of miRNAs. Only a few groups [59–64] have investigated urinary miRNAs as biomarkers of BCa and these are summarized in Table 3. Hanke et al. [59] were the first group to report a robust methodology to study miRNAs in urine as tumor markers. Puerta-Gil et al. [60] selected miR-143, 222, and 452 from a previous tissue microarray study and showed that urinary miR expression was concordant with tissue expression. They also reported that these miRs could predict recurrence (miR-222 and miR-143), progression (miR-222 and miR-143), disease-specific survival (miR222), and overall survival (miR-222). Similarly Yun et al. [63] also found that urinary levels of miR 200a predicted recurrence of NMIBC. Yamada et al. [61] also show that miR expression in urine and tissue are concordant when they found that miR 96 and 183 were overexpressed in BCa urine, mirroring their expression in tissue from a previous study [65]. The levels of miR 96 and 183

dropped in the urine collected after transurethral resection of bladder tumor, again suggesting the BCa specificity of these miRNAs. Although the majority of miRs across studies were up-regulated in BCa, some miRs such as the miR-200 family [62], miR-155 [62], miR-192 [62], miR-205 [62], and miR-143 [60] were found to be down-regulated in studies. Preliminary studies have shown mixed results about the utility of miRNAs as urinary biomarkers of cancer. The low specificity of several studies [59,62–64] may be owing to heterogeneous control groups, which include patients with hematuria and other benign urologic conditions as well as a possibility that miRNA levels in urine may be responsive to benign inflammatory and infective changes. There is variation in methodology, minimal overlap in miRNAs across studies, and no validation of results in most studies, and hence an inability to draw broad conclusions on the utility of urinary miRNAs in the detection of BCa. Furthermore, none of the studies have looked at the utility of urinary miRNAs in the surveillance setting.

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8. Conclusion

References

As our insights into the molecular mechanisms of BCa deepen, urinary biomarkers have evolved over the past decade. The lack of clinical benefit of protein- and cellbased urinary biomarkers and the emergence of highthroughput genomic platforms have given way to pursuit of gene-based profiling of biomarkers. However, the majority of these studies remain in the discovery phase, and what is now needed for clinical translation of these markers is multicenter prospective validation studies in large clinical settings with adequate scientific and statistical rigor. Bioinformatics approaches continue to evolve but computer modeling methods that take into account natural behavior of the cancer and biomarker, treatment effects, cost, and population information can often be useful for deciding sample size in a setting where traditional power calculations are often invalid [3]. For clinical translation, biomarkers must add significant benefit over the current clinical models in a cost-effective manner. The National Cancer Institute biomarker development recommendations form a useful guiding tool for future biomarker studies. Limitations of exploratory studies of urinary markers for BCa in the discovery phase also need to be addressed. Almost all studies are done retrospectively on stored samples using differing methodology for biomarker profiling. Patient populations are often heterogeneous—test groups often contain an admixture of patients with hematuria, surveillance patients, and controls, a mix of healthy volunteers and patients with benign urologic conditions, making comparison and extrapolation of results difficult. In addition, there are inherent problems with urinary testing. As volume and stage/grade of bladder tumors can vary vastly, test should be able to deal with a small amount of exfoliated cells in urine. Another disadvantage of urinary markers is that urine is a very dynamic fluid and its composition can be affected by fluid status, renal disease, infection, and urinary tract instrumentation. Gene-based urinary biomarkers are more sensitive and specific as they detect cancer-specific changes and are less likely to be affected by inflammatory and other benign conditions compared with protein-based detection. They can also be easily multiplexed to test for several markers simultaneously. This is important because it is unlikely that a single urinary biomarker would provide satisfactory performance to predict disease states and outcomes owing to complex interactions and cross talk between molecular pathways and tumor heterogeneity. Currently, the majority of biomarker profiling is based on candidate-driven approaches. As the use of next generation sequencing increases, we are likely to see a shift to high-throughput approaches for screening of novel biomarkers. At present, cystoscopy continues to be the gold standard for detection of recurrences in the diagnostic and surveillance setting. Although several biomarkers have shown promise, most remain to be validated in large multicenter clinical studies before their routine use in the clinic.

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