Urologic Oncology: Seminars and Original Investigations ] (2014) ∎∎∎–∎∎∎

Seminar article

Molecular markers for urothelial bladder cancer prognosis: Toward implementation in clinical practice Bas W.G. van Rhijn, M.D., Ph.D., F.E.B.U.a,*, James W. Catto, M.B., Ch.B., Ph.D.b, Peter J. Goebell, M.D.c, Ruth Knüchel, M.D.d, Shahrokh F. Shariat, M.D., Ph.D.e, Henk G. van der Poel, M.D., Ph.D.a, Marta Sanchez-Carbayo, M.D., Ph.D.f, George N. Thalmann, M.D.g, Bernd J. Schmitz-Dräger, M.D., Ph.D.h, Lambertus A. Kiemeney, Ph.D.i,j a

Division of Urology, Department of Surgical Oncology, Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands b Institute for Cancer Studies and Academic Urology Unit, University of Sheffield, Sheffield, United Kingdom c Department of Urology, University Clinic of Erlangen, Erlangen, Germany d Institute of Pathology, RWTH Aachen University, Aachen, Germany e Department of Urology, Medical University of Vienna, Vienna General Hospital, Vienna, Austria f CIC bioGUNE, Bizkaia Technology Park, Derio, Spain g Department of Urology, University of Berne, Inselspital, Berne, Switzerland h Department of Urology, Schön-Klinik, Nürnberg/Fürth, Germany i Department for Health Evidence, Radboud University Medical Centre, Nijmegen, The Netherlands j Department of Urology, Radboud University Medical Centre, Nijmegen, The Netherlands Received 3 January 2014; received in revised form 2 July 2014; accepted 3 July 2014

Abstract Objectives: To summarize the current status of clinicopathological and molecular markers for the prediction of recurrence or progression or both in non–muscle-invasive and survival in muscle-invasive urothelial bladder cancer, to address the reproducibility of pathology and molecular markers, and to provide directions toward implementation of molecular markers in future clinical decision making. Methods and materials: Immunohistochemistry, gene signatures, and FGFR3-based molecular grading were used as molecular examples focussing on prognostics and issues related to robustness of pathological and molecular assays. Results: The role of molecular markers to predict recurrence is limited, as clinical variables are currently more important. The prediction of progression and survival using molecular markers holds considerable promise. Despite a plethora of prognostic (clinical and molecular) marker studies, reproducibility of pathology and molecular assays has been understudied, and lack of reproducibility is probably the main reason that individual prediction of disease outcome is currently not reliable. Conclusions: Molecular markers are promising to predict progression and survival, but not recurrence. However, none of these are used in the daily clinical routine because of reproducibility issues. Future studies should focus on reproducibility of marker assessment and consistency of study results by incorporating scoring systems to reduce heterogeneity of reporting. This may ultimately lead to incorporation of molecular markers in clinical practice. r 2014 Elsevier Inc. All rights reserved.

Keywords: Urothelial; Bladder; Cancer; Molecular; Marker; Reproducibility

Introduction

Corresponding author. Tel.: þ31-20-5122553; fax: þ31-20-5122459. E-mail addresses: [email protected], [email protected] (B.W.G. van Rhijn). *

http://dx.doi.org/10.1016/j.urolonc.2014.07.002 1078-1439/r 2014 Elsevier Inc. All rights reserved.

The global incidence of urinary bladder cancer (BC) was approximately 429,200 cases in 2012 [1]. Most (75%) BCs are non–muscle invasive (NMI) at first diagnosis (Ta, T1, and carcinoma in situ [CIS]) and generally have a good

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prognosis. Between 30% and 80% will recur as NMI tumors and 1% and 45% will progress to muscle invasion (MI) within 5 years [2–4]. NMI-BC is a chronic disease that requires frequent bladder surveillance and repeated treatments over many years. Consequently, BC is the most expensive cancer per patient [5]. By contrast, MI-BC (T2–T4) has a poor prognosis. Treatment requires a multidisciplinary approach with radical surgery, radiotherapy, and chemotherapy. Despite these treatments, roughly half of these patients develop metastases and die within 3 years [6]. Although response rates of systemic chemotherapy are high (up to 50%), the prognosis of BC with overt (organ) metastasis is poor with cures rarely achieved [6,7]. Decision making and the prognosis of BC relies heavily on TNM stage and pathological grade. However, the reproducibility of pathology assessments is modest [3,4,8,9]. Therefore, intense research efforts are being made to identify and characterize robust molecular markers. Currently, the value of molecular markers over clinicopathological parameters is unclear, and their clinical use is limited. This review summarizes the current status of clinicopathological and molecular markers for prediction of recurrence and progression of NMI-BC and survival in MI-BC. Reproducibility of pathology and molecular markers was also addressed. In addition, statistical considerations and phases of marker development are discussed in the section Phases of biomarker development. We focused on immunohistochemistry (IHC), gene signatures, and FGFR3-based molecular grade (mG) as molecular marker examples, because reproducibility of study results is available for these markers. The aim of this review was not to provide a comprehensive survey/long list of molecular markers and their prognostic performance. Instead, we focussed on issues related to robustness of pathological and molecular assays and provided directions toward implementation of molecular markers in clinical practice.

as examples because reproducibility/consistency of study results was available for these markers. The authors acknowledge that most of the molecular data are on IHC staining because this method has most commonly been used. Results Prognostic factors for recurrence of NMI-BC Prediction of recurrence with clinical and pathological variables Clinical and pathology factors that may predict NMI-BC recurrence have been studied extensively over the years [2–4,10–15]. Sylvester et al. [2] calculated the probability of recurrence using data of 2,596 patients. Different variables were important for recurrence and progression of NMI-BC. Each variable was assigned a weighted score per end point (recurrence or progression). The total score was based on 6 variables, i.e., grade, category, CIS, multiplicity, size, and prior recurrence rate. The EAU adopted this in their guidelines and determined scores for patients at low, intermediate, and high risk of recurrence [2,4]. FernandezGomez et al. [15] reported prognostic factors from 4 Club Urológico Español de Tratamiento Oncológico (CUETO) trials, in which 1,062 patients received BCG. Multiplicity, prior tumor, female sex, and CIS were significant predictors for recurrence in multivariable analysis [15]. Although studies vary in the number of patients, follow-up, the variables analyzed, and statistical analysis, the most important variables for prediction of NMI-BC recurrence are multiplicity, tumor size, and prior recurrence rate [2–4,10–16]. An earlier review concluded that the chances of definitive cure of a patient with primary NMI-BC rely on a highquality transurethral resection (TUR) removing all (pre) malignant lesions [3]. However, multiple tumors probably have more small (pre)malignant lesions than we are able to visualize with regular white light [3]. A possible step forward has been made with photodynamic diagnosis [3].

Methods and materials Relevant articles and reports on epidemiology, recurrence, and progression of NMI-BC and survival in MI-BC were selected for the clinical paragraphs on prognostic factors for recurrence, progression, and survival using the European Association of Urology (EAU) guidelines [4,7]. A literature search in English was performed using PubMed. We selected abstracts on PubMed between 1992 and 2012 with the terms “biomarker/molecular marker” and “bladder cancer” (4,129 hits). We found an increasing number of reports per year (95 in 1992 to more than 300 in 2012). These abstracts were briefly screened to select original (tissue-based) research dealing with issues related to robustness of pathological and molecular assays. In the subsequent assessment of the molecular markers, we focused on IHC, gene signatures, and FGFR3-based mG

Prediction of recurrence with molecular markers Numerous molecular biomarkers have been investigated to predict NMI-BC recurrence [14,16–18]. However, most molecular markers show a relation to grade, category, and progression but not to recurrence of NMI-BC [14,16–18]. For example, presence of an activating FGFR3 (fibroblast growth factor receptor 3) mutation was linked to a lower percentage of progression but not to recurrence in 2 sufficiently sized studies either alone or in combination with other molecular markers [19,20]. Multiplicity was the only significant predictor for recurrence in multivariable analysis [19]. For p53, conflicting results are found. For example, Shariat et al. [21] found the mutant genotype to be a predictor for recurrence, whereas Moonen et al. [22] found more recurrence in patients with wild-type tumors. A combination of multiple biomarkers or analyses of multiple

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genes may be of interest to identify specific markers (survivin [23] and minichromosome maintenance complex component 2 [24]) or gene classifiers to discern recurrent from nonrecurrent NMI-BC [21–25]. However, validation with 404 patients from 5 European countries of the previously published 26-gene signature for recurrence was not successful [26]. At present, the role of molecular markers to predict recurrence seems limited because the tumor biology behind multiplicity remains unknown, and incomplete treatment by TUR contributes to recurrence as well [3].

Prognostic factors for progression of NMI-BC Prediction of progression with clinical and pathological variables As for recurrence, clinical and pathology factors predicting progression have been studied extensively [2,10–15]. Five-year probabilities range from less than 1% to 45%, depending on prognostic factors [2–4]. The most important variables for prediction of progression in NMI-BC are presence of CIS, tumor grade, and invasion of the lamina propria (T1 category) [2,12,13]. Based on the study by Sylvester et al. [2], a weighted progression risk score [4] to stratify patients into low, intermediate, and high risk of progression to MI-BC was proposed [2,4]. Recurrence at first cystoscopy, category, grade, and prior tumor were the prognostic variables in the multivariable analysis for progression in the CUETO studies [15]. However, one has to bear in mind that the end point progression suffers from heterogeneity because different definitions are used [27]. Additional factors associated with progression were reviewed earlier and are, among others, micropapillary or solid growth patterns, tumor at the bladder neck or prostatic urethra, extensive lamina propria invasion and lymphovascular invasion (LVI) [3,4]. If LVI is present in a NMI-BC specimen at TUR, it indicates understaging and possible lymph node involvement [28].

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Prediction of progression with molecular markers Many molecular alterations are associated with pathology variables that predict progression of NMI-BC (i.e., CIS, grade 3, and T1 category). By contrast, molecular alterations are usually not linked to multiplicity and size, which are the clinical variables predicting recurrence. A wide variety of molecular alterations (oncogene activation, tumor suppressor gene loss, epigenetic changes, chromosomal alterations and up- or down-regulation of cell cycle regulators, proliferation antigens, cell adhesion molecules, and signaling proteins, etc.) have been investigated for a better assessment of NMI-BC prognosis [14,16,18,19,29–32]. Some of these markers have been shown to be associated with biologically aggressive disease and hold promise to predict progression [14,16,18,19,30–32], but in many cases a lack of replication studies prohibits implementation into clinical practice. The most frequently investigated marker to predict progression is p53 [19,21,22,33]. Most, but not all, studies found that a p53 mutation or p53 overexpression is associated with progression. The number of patients and especially methods of analyses may be the major cause of discrepancy between studies [33,34]. Two genetic events (loss of parts of chromosome 9 and FGFR3 mutations) in NMI-BC are frequent and present in early NMI-BC. Loss of heterozygosity of chromosome 9 has been found in up to 60% of cases [18,29,31]. However, no association between clinical parameters and progression has been found [18,31]. Conversely, the FGFR3 mutation has been found to be a selective marker for favorable disease in several reports [19,20,32,35]. In pTaG1, 88% of tumors had a mutation as opposed to 19% of pT1G3 tumors [19]. Moreover, in several independent studies, presence of the FGFR3 mutation protected against progression [19,20,32,35]. This led to the proposal of the FGFR3 mutation as the genetic event responsible for the favorable pathway in BC (Fig. 1) [19]. Furthermore, based on FGFR3 mutation status and the expression of the proliferation

MOLECULAR AND CLINICAL PATHWAYS OF BLADDER CANCER

FGFR3 mutation

T2 G2/3

Ta G1/2

Normal Urothelium

Metastasis

Progression p53 ↑ Ki-67 ↑

Ta/1 G2/3 CIS

T2 G3

INCREASING NUMBER OF GENETIC EVENTS Fig. 1. Simplified 2-pathway model for disease pathogenesis of bladder cancer (BC). This figure shows the combination of molecular and pathological data in non–muscle-invasive BC. Arrow thickness is indicative of the percentage of tumors. The FGFR3 mutation is largely responsible for the favorable molecular pathway in NMI-BC. Among many others, overexpression of p53 and Ki-67 is an example of unfavorable NMI-BC. Molecular alterations, not included in the figure in the interest of clarity, are represented by the bottom arrow. FGFR3, fibroblast growth factor receptor 3 gene; mt, mutation; ↑, elevated expression (Ki67, p53); CIS, carcinoma in situ.

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marker Ki-67, mG1–3 was introduced as a highly reproducible and prognostic tool in BC progression. The first prospective data confirmed the prognostic value of mG for progression [20]. Moreover, in a study with long-term (median ¼ 8.6 y) follow-up, the addition of mG to the multivariable model for progression significantly increased its discrimination, and mG provided valuable extra prognostic information over the European Organization for Research and Treatment of Cancer (EORTC) risk scores for progression [32]. Given the similar molecular backgrounds, these findings were also seen in upper tract urothelial carcinomas [36]. A combination of molecular markers is necessary to better predict progression [16,18,19,33,34]. As discussed earlier, mG is an example of this. Another example is the differential expression of multiple IHC markers from 1 tissue sample using tissue microarray (TMA) technology (Fig. 2). Shariat et al. [21] investigated p53, pRB, p21, and p27 and found that not a particular marker but the number of altered markers was independently associated with an increased risk of progression. The TMA technique and analysis have been automated, are possible in any pathology laboratory, and may improve prediction of progression [21,37]. Nevertheless, routine use is not advocated because results have so far not been confirmed in prospective studies, and the TMA technology is mainly for research purposes. Another example of combining genetic information is the construction of a gene classifier using microarrays [25]. This approach has the potential of individual prediction of outcome. In an international validation study, which is currently the largest study on gene-expression microarrays,

2 classifiers, one based on 52 genes and another on 88 genes, were significant in multivariable analysis of progression [26]. Although these gene classifiers enhanced prediction of progression next to clinicopathological indices, the sensitivity and specificity to predict progression were both only 66%. Hence, a gene classifier on its own is not enough to predict progression in individual cases. Prospective data using well-defined patient cohorts and end points will give us valuable information on mG [19,32], TMA [21,37], and gene classifier technology [25,26] in the future. In addition, more work is needed on reproducibility (refer to the section Reproducibility), easy access to these technologies, and simplification and combination of methods. Until then, the value of molecular markers over traditional histopathology is limited in NMI-BC. Prognostic factors for survival in MI-BC Prediction of survival with clinical and pathological variables Radical cystectomy (RC) has been the standard treatment for patients with MI-BC without (radiological) signs of metastasis since the 1960s [6,7,38]. Cisplatin containing neoadjuvant chemotherapy should be considered in patients with MI-BC, as it is associated with an increase in overall survival from 30% to 36% at 10 years [39,40]. Chemoradiotherapy with curative intent is an alternative to RC, particularly for patients with low volume, cT2 MI-BC [41]. Clinical outcome of MI-BC is dependent on TNM stage [6,7,38,42–44]. The chances on subsequent metastatic spread after RC are higher in nonorgan-confined (4pT2)

Fig. 2. The tissue microarray (TMA) technology. It allows simultaneous immunohistochemical (IHC) analysis of 50 to 100 tumor tissue specimens. The donor block (not shown) is the regular formalin-fixed paraffin-embedded block with tumor tissue. The acceptor block contains cylinder punches from different donor blocks. This particular example shows a fragment of FGFR3 IHC analyses. On the left side, a TMA slide stained for FGFR3 is shown generated from the acceptor block. The right side shows the view of this TMA under the microscope. References for more details on the TMA technology [21,37,42–44] and for the other methods described in this review, i.e., FGFR3 mutation analysis [32,35,36,60] and gene-expression profiling to construct a genetic signature [17,25,26,52–55,59,60] are shown in the reference list. (Color version of figure is available online.)

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and node-positive BC. For example, a 5-year recurrencefree survival after RC was found to be 85% in organconfined/node-negative BC and 35% in node-positive BC [38]. After RC, extranodal extension, age, and LVI are important variables for prognosis next to pT category and lymph node status [42–45]. Understaging before RC [46–48] and the inability to accurately point out who will develop metastasis after RC are critical issues in MI-BC management. The heterogeneity of the patient population undergoing RC is obvious and better (individual) risk assessment, as well as better treatment modalities, is urgently needed. Prediction of survival with molecular markers The outcome of NMI-BC is affected strongly by the onset of progression to invasion. Many molecular markers associated with progression are also prognostic of cancerspecific survival for both NMI-BC and MI-BC [14,16,18,19,31,49]. Two examples of IHC markers that have frequently been investigated as prognostic markers in RC series are p53 and Ki-67 [42,49]. A meta-analysis of p53 in BC found 117 studies (10,026 patients), with sample sizes ranging from 12 to 270 patients (mean = 86, SD = 53) [34]. IHC was used in 96% of the 117 studies for assessment of p53 status. The overall hazard ratio from this metaanalysis for which 17 studies qualified was 1.43 (1.21–1.69) for p53 to predict mortality. These findings could be overestimates because of publication and reporting biases [34]. Furthermore, IHC as the method to assess p53 status is probably not as good as polymerase chain reaction-based methods [50]. The only molecular marker that has been investigated in a phase III study is p53 [51]. Patients with pT1/2 pN0 M0 (RC) and altered p53 (410% nuclear immunoreactivity) were randomized to 3 cycles of adjuvant chemotherapy (MVAC [methotrexate, vinblastine, adriamycin, and cisplatin]) vs. observation. Neither the prognostic value of p53 nor the benefit of adjuvant chemotherapy was confirmed. The event rate was lower than expected, and only 67% (39/58) of patients assigned to receive MVAC completed their adjuvant treatment, thereby severely compromising the power of the study [51]. The largest study on Ki-67 IHC used the expression of this protein to predict outcomes in 713 patients after RC [42]. It showed that the addition of Ki-67 to the multivariable base model, marginally improved the discrimination of this model by 2.4% for disease-specific survival [42]. The authors suggest that altered Ki-67 may be used in addition to established predictors to identify patients who may benefit from adjuvant treatment after RC. Taken together, the relevance of a single IHC marker (p53) varies between studies and is therefore insufficient to assess outcome of MI-BC. As for NMI-BC, a combination of IHC markers has been associated with improved clinical outcome prediction after RC for MI-BC [37,43,44]. In 692 patients with locally advanced (4pT2) BC or node positivity or both at RC, the number of altered markers among p53, p27, p21, and pRb

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improved the discrimination of the multivariable base model to predict disease-specific mortality by 4.3% [43]. In another article using the same markers in organ-confined (opT3), node-negative BC at RC (n ¼ 324), this percentage was calculated at 14.8% [44]. Although the status of individual molecular markers did not add sufficient value to outcome prediction after RC, combinations may improve prognostication and possibly prediction of response to therapy [43,44]. A multimarker IHC prospective evaluation, which was recently published, confirmed earlier retrospective data to identify patients who may benefit from neoadjuvant [47] and adjuvant [48] systemic treatment. Some studies that separately analyzed survival in MI-BC with gene-expression signatures deserve attention [52–55]. Sanchez-Carbayo et al. [52] developed a 100-gene set associated with poor survival in MI-BC. Their set of tumors was subsequently used by others [53,54] for validation purposes. Lindgren et al. [53] successfully used geneexpression analysis to distinguish specific molecular subtypes of BC and defined gene signatures that can classify BC by grade as well as MI status. Furthermore, they reported a gene-expression signature with an independent prognostic effect on metastasis and survival [53]. Smith et al. [54] reported a 20-gene-expression model from 3 cohorts of patients (n ¼ 275) that independently predicted lymph node status at RC. This model identified patients at high relative risk (1.74, 95% CI: 1.03–2.93) and low relative risk (0.70, 95% CI: 0.51–0.96) of nodal metastasis at RC [54]. The authors suggested that the high-risk patients in this model may benefit from neoadjuvant chemotherapy. Lauss et al. [55] investigated 6 published signatures for BC survival. The overlap of genes was only 0.6%. More important, these authors calculated that 4150 genes are needed in a signature to obtain robust accuracy [55]. Independent replication of these results using comparable study objectives and patient groups is needed. Furthermore, the complexity of the molecular analyses and the reproducibility of these gene signatures (refer to the section Reproducibility) make transition to clinical practice difficult. In addition, it has not been shown that a gene classifier is associated with a higher increase in prognostic discrimination than, e.g., a combination of IHC markers [56]. Reproducibility Observer variability and prognosis in pathology Reproducibility of pathology assessment has not been studied as extensively as clinicopathological prediction of recurrence and progression [3]. Nevertheless, reproducibility is of utmost importance to compare clinical results between institutes and for the assessment of the prognostic value of BC grade and category. The largest study on stage review in NMI-BC was published in 2000 [8]. Local pathology and review pathology were compared in 1,400 patients who participated in 5 EORTC trials. Agreement between pathologists varied from

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36% to 90%, and the authors recommended pathology review in high-risk NMI-BC. This conclusion was confirmed by a study with 164 patients with T1 (high risk) NMI-BC whose original slides were reviewed. Approximately 20% of T1 tumors were upstaged or downstaged, and the reviewed stage strongly predicted patient's prognosis [57]. Hence, pathology review in the high-risk NMI-BC category identifies patients with different prognoses who may benefit from other treatment strategies than BCG. Pathological grade carries significant prognostic information (NMI-BC), especially for prediction of progression [2–4,6,8–15]. However, its poor reproducibility is a recognized problem and a major concern. Concordance of grade assessment (World Health Organization [WHO] 1973) varied from 42% to 73% between local and review pathologists in the 5 EORTC studies mentioned earlier [8]. A new classification system for grade was adopted by the WHO in 2004 [3]. Next to high observer variability, the main reasons to propose a new system were the lack of clear definitions for the 3 WHO 1973 grades and the high percentage of NMI-BC classified as G2 (the default diagnosis). Although the new system contains detailed histological criteria to decrease interobserver variability, direct comparison of both classification systems for grade did not result in a better prediction of progression or better reproducibility or both [3,9]. The main criticism to the new system is that it has been accepted in spite of lack of clinical evidence and proper studies with long-term follow-up to assess its reproducibility and prognostic value compared with the “old” WHO 1973 system [3]. Therefore, the EAU guidelines advocate the use of both systems until the 2004 system has been properly validated [4]. The advantage of the new system over the WHO 1973 system will probably be limited, as interobserver variability remains high in both systems. Recently, the mean grade as assessed by a pathologist was found to be constant for 1 pathologist but highly variable between different pathologists (up to 0.7 grade), irrespective of the classification system used [9]. Mean grade distinguished low and high graders among the pathologists and this knowledge was strongly linked with the risk of progression for each grade category [9]. This new mean grade concept allows a better assessment of the prognostic value of grading. Mean grade has the potential to become a tool for quality assurance in pathology and clinical trials [9]. Category and grade are the gold standards on which treatment decisions in BC are based. The poor reproducibility of pathological category and grade is a recognized problem and a major concern for clinicians. It is probably the main reason that clinical decision making based on grade and category is troublesome in individual cases. Reproducibility of molecular markers Studies on reproducibility of molecular markers are rare. Hereunder, some aspects of reproducibility of IHC, gene

signatures, and mG for NMI-BC are discussed. We have focussed on 2 aspects, i.e., reproducibility of marker assessment and consistency of study results. The NCI conducted a well-designed study on the reproducibility of p53 IHC [58]. In total, 50 high-grade, primary BCs were subjected to several sources of variability, i.e., the scorer, the staining laboratory, and another tumor block. The percentage agreement ranged from 83% (2 observers, 2 slides, and 2 laboratories) to 95% (1 observer, 2 slides, and 1 laboratory). In another study, the percentages of agreement (2 observers, 1 slide, and 1 laboratory) for Ki67, p53, and p27 were 91%, 88%, and 85%, respectively [19]. These values are higher than the percentages of agreement for pathological grade, but it should be noted that IHC is either positive or negative (2-tier system) and pathological grade usually is a 3-tier system. In the new WHO 2004 classification system for grade, the first 2 categories are sometimes lumped together resulting in a 2-tier system. Using such an approach, the percentages of agreement for pathological grade ranged from 68% to 87% (4 pathologists, 1 slide, and 1 laboratory) [32]. These values come close to but do not reach the reproducibility of IHC. Several groups have constructed a gene classifier using microarrays to predict clinical outcome [25,26,52–54,59,60]. The classification performances show very similar accuracies to predict NMI-BC progression or survival in MI-BC. However, the studies show only little overlap in the identified genes that are part of the classifier itself [25,26,52–54,59,60]. Some explanations for this phenomenon may include heterogeneity between the analyzed tumors, use of manual instead of laser-capture microdissection of tumor tissue, poor reproducibility of this method, and a cutoff-value issue when scaling down from expression profiles of ⫾20,000 genes to less than 100 genes to construct the gene classifier. The most logical explanation, however, is false-positive findings (with 20,000 genes studied, 1,000 genes are expected to significantly associate with outcome just by chance). mG, based on FGFR3 mutation status and Ki-67 expression, has been proposed as an alternative to predict progression [19,32]. A recent study compared the reproducibility of pathological grading and mG on the same series of patients [32]. The reproducibility of mG was almost perfect (κ ¼ 0.76), whereas reproducibility for pathological grade was only fair to substantial (κ: 0.17–0.58) [32]. Taken together, mG (composed of 3 mGs) proved more reproducible than pathological grade assessment making it a more reliable and robust tool to assess progression in NMI-BC than pathological grade. Although testing the reproducibility of a molecular marker is part of the earliest phase in discovery, evaluation, and validation protocols [49], the number of reported studies on molecular reproducibility is low. Another aspect of reproducibility, beyond the scope of this article because it particularly relates to personalized treatment, is tumor heterogeneity in relation to molecular makers. In conclusion,

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the reproducibility of molecular markers in BC is an understudied subject, which deserves more attention if molecular markers are to become important in clinical practice.

Phases of biomarker development Despite a plethora of molecular markers reported to be clinically “promising,” there is currently no single prognostic molecular marker in routine clinical use. To determine the value of a new molecular marker, it is not sufficient to show that it is significantly related to prognosis or outcome, statistically significant in a multivariable model that includes the standard clinical and pathologic factors, or more significant than standard clinical and pathologic factors. Rather, for a molecular marker to be clinically useful, it is necessary to show that adding the molecular marker to an existing model based on the most important clinical and pathologic factors substantially improves the discrimination of the model. In fact, statistical significance in prognostic research has little meaning, as the question is how well you can discriminate different groups of patients, not just that you can discriminate. The next step is to assess whether the increase in discrimination and risk assessment

translates into improved individualized, evidence-based treatment recommendations with eventual superior patient outcomes. However, many researchers publish early “promising” observations of possible relevant marker(s) but are reluctant to perform the clinical studies to confirm or deny the role of the putative marker. Moreover, molecular marker research is usually done in the context of standard clinical care, rather than clinical trials. Consequently, molecular markers that appear biologically and statistically significant are not confirmed by studies at other centers [26,34,49,61]. This prompted the development of guidelines intended to ensure that molecular marker studies conform to some basic standards in design and reporting [61]. Hereunder, we discuss 3 of these guideline systems that have the purpose to improve the consistency of study results. In 2002, the National Cancer Institute's Early Detection Research Network developed a 5-phase approach to systematic discovery and evaluation of molecular markers (Fig. 3) and has been adopted and modified for BC research through the International Bladder Cancer Network in 2003 and 2007 [49,61,62]. These phases of research are generally ordered in a sequence from discovery to validation and ultimately to assessment of benefit according to the strength of evidence that each provides. This approach provides a clear scale by which researchers, patients, reviewers, and investors can

Phase

Goals/aims

Experimentation

Sample details

Preclinical

Exploratory; nominate

Preclinical study

Possible bias: small size

Testing

and rank candidate

for hypothesis

and

biomarker profiles

generation

convenience sampling

0

I

Develop an assay with

Reproducibility and

clinically reproducible

robustness of assay; No

results

assessment of benefit

Test on small sample to

Marker optimization,

Sample population

determine benefit

7

establish prediction

assay developed from

rules, determine cut-offs

candidate biomarker

Retrospective design

Sample population

profile II

III

Determine operating characteristics & internal

should be the target

validation

population

External validation

Retrospective or

Multi-institutional, large

prospective,

study

Generaliziability, Impact on clinical decisionmaking IV

Assess whether biomarker reduces the burden of disease

Post-approval reporting and testing for other disease processes or disease stages

Fig. 3. Modification of the structured 5-phase approach to the systematic discovery, evaluation, and validation of biomarkers developed by the National Cancer Institute's Early Detection Research Network [49,61,62].

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evaluate the status of a molecular marker in its development process. The phases of research are generally ordered according to the strength of evidence that each provides in favor of the biomarker. The results from earlier phases are generally necessary to design later phases. This classification of studies into a sequence of phases, from discovery to validation, and assessment of benefit has been adapted by several BC groups [49,61,62]. In an effort to address the pervasive problem of inadequacies in the design, analysis, and reporting of molecular marker prognostic studies, a set of reporting recommendations, such as the reporting recommendations for tumor marker prognostic studies (REMARK), has been developed and adopted by many prominent journals [49,61,63]. The goal of these guidelines is to encourage transparent and complete reporting and to help readers judge the data and understand the context in which the conclusions apply. The REMARK lists 20 items that investigators should attempt to report in any molecular marker study. Another tool aimed at standardizing the quality of molecular marker research is the tumor marker utility grading system [49,61,64]. This is a scale of levels of evidence, designed to help place molecular marker studies into a context of validity. Although testing the consistency of study results for a molecular marker is part of the earliest phase in discovery, evaluation, and validation protocols [49], the number of reported studies on molecular reproducibility is low (refer to the section Reproducibility). These structured systems may be a step forward to standardize molecular marker research but their use in original reports is currently limited and the systems themselves have so far not been tested for reproducibility or consistency or both. Moreover, these systems do not indicate how much of an improvement in discrimination (c-index) is needed to justify the use of a molecular marker. Nevertheless, the implementation of standards and conventions is crucial before a conclusive recommendation for the introduction of new markers to the clinical routine because replication and independent confirmation are hallmarks of any scientific method. Conclusions The prognosis of NMI-BC heavily relies on clinical variables (multiplicity, size, and prior recurrence rate) to predict recurrence and pathological variables (TNM category, grade, and CIS) and to predict progression. Clinical outcome of MI-BC is dependent on TNM. The role of molecular markers to predict NMI-BC recurrence seems limited. Prediction of progression (NMI-BC) and survival (MI-BC) with molecular markers holds considerable promise. The currently available data together with the current paradigm that BC develops along multiple molecular pathways suggest that including multiple molecular markers in

models designed to predict outcomes could enhance their discriminative power. Therefore, use of multiple molecular markers likely represents the future of risk stratification on which optimal management to prevent progression of NMI-BC and metastasis of MI-BC may be based. The reproducibility of marker assessment is understudied and replication studies are rare. Nevertheless, reproducibility and consistency of these markers are important and recommended by several guidelines on molecular markers even before prognostic analyses of these markers. Moreover, the fair to substantial reproducibility of pathology in BC may be an obstacle for the introduction of molecular markers in clinical practice. Prospective data using welldefined patient cohorts and end points will give us valuable information on mG and the (tissue/gene) microarray technologies in the near future to predict patient's prognosis. Next to prediction of prognosis, research into actionable genomic alterations may serve as a platform for therapeutic drug discovery [65]. This type of studies requires pretreatment genomic characterization. The MAGNOLIA trial [66] is an example of this approach, and this and future studies will assess the value of actionable genomic alterations for our patients. References [1] GLOBOCAN. Cancer incidence, mortality and prevalence worldwide in 2012. Lyon, France: International Agency for Research on Cancer, 2012. Available at: http://globocan.iarc.fr. [2] Sylvester RJ, van der Meijden AP, Oosterlinck W, et al. Predicting recurrence and progression in individual patients with stage Ta T1 bladder cancer using EORTC risk tables: a combined analysis of 2596 patients from seven EORTC trials. Eur Urol 2006;49:466–77. [3] Van Rhijn BW, Burger M, Lotan Y, et al. Recurrence and progression of disease in non–muscle-invasive bladder cancer: from epidemiology to treatment strategy. Eur Urol 2009;56:430–42. [4] Babjuk M, Burger M, Zigeuner R, et al. EAU guidelines on non– muscle invasive urothelial carcinoma of the bladder—update 2013. Eur Urol 2013;64:639–53. [5] Botteman MF, Pashos CL, Redaelli A, Laskin B, Hauser R. The health economics of bladder cancer. Pharmacoeconomics 2003;21: 1315–30. [6] Kaufman DS, Shipley WU, Feldman AS. Bladder cancer. Lancet 2009;374:239–49. [7] Stenzl A, Cowan NC, De Santis M, et al. Treatment of muscleinvasive and metastatic bladder cancer: update of the EAU guidelines. Eur Urol 2011;59:1009–18. [8] Van der Meijden A, Sylvester R, Collette L, Bono A, Ten Kate F. The role and impact of pathology review on stage and grade assessment of stages Ta and T1 bladder tumors: a combined analysis of 5 European Organization for Research and Treatment of Cancer Trials. J Urol 2000;164:1533–7. [9] van Rhijn BW, van Leenders GJLH, ECM Ooms, et al. The pathologist's mean grade is constant and individualizes the prognostic value of bladder cancer grading. Eur Urol 2010;57:1052–7. [10] Zieger K, Wolf H, Olsen PR, Hojgaard K. Long-term follow-up of non-invasive bladder tumours (stage Ta): recurrence and progression. BJU Int 2000;85:824–8. [11] Millán-Rodríguez F, Chéchile-Toniolo G, Salvador-Bayarri J, Palou J, Vicente-Rodríguez J. Multivariate analysis of the prognostic factors of primary superficial bladder cancer. J Urol 2000;163:73–8.

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