Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

Developing proteomic biomarkers for bladder cancer: towards clinical application

Key Points

  • An unmet clinical need exists for accurate, noninvasive assays, which enable the accurate diagnosis of bladder cancer and monitoring of patients for recurrence

  • Urine is the most appropriate bodily fluid for biomarker research owing to its noninvasive and easy collection, stability of samples and proximity to bladder tumours

  • Proteomics platforms have the advantages of providing large datasets with numerous putative biomarker candidates at high resolution; these technologies might also potentially enable validation of biomarker candidates

  • Multiple biomarker panels are likely to be more effective than single biomarkers, owing to the high level of disease heterogeneity observed among patients with bladder cancer

  • Multiple proteomic biomarkers for bladder cancer have already been discovered; however, a lack of validation in the appropriate patient populations and in specific contexts of use precludes clinical implementation

Abstract

Clinical use of proteomic biomarkers has the potential to substantially improve the outcomes of patients with bladder cancer. An unmet clinical need evidently exists for noninvasive biomarkers, which might enable improvements in both the diagnosis and prognosis of patients with bladder cancer, as well as improved monitoring of patients for the presence of recurrence. Urine is considered the optimal noninvasive source of proteomic biomarkers in patients with bladder cancer. Currently, a number of single-protein biomarkers have been detected in urine and tissue using a variety of proteomic techniques, each having specific conceptual considerations and technical implications. Promising preclinical data are available for several of these proteins; however, the combination of single urinary proteins into multimarker panels might better encompass the molecular heterogeneity of bladder cancer within this patient population, and prove more effective in clinical use.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Overview of the biomarker development workflow.

Similar content being viewed by others

References

  1. Ferlay, J. et al. Cancer incidence and mortality worldwide: Sources, methods and major patterns in GLOBOCAN 2012. Int. J. Cancer 136, E359–E386 (2014).

    PubMed  Google Scholar 

  2. Ferlay, J. et al. Estimates of worldwide burden of cancer in 2008: GLOBOCAN 2008. Int. J. Cancer 127, 2893–2917 (2010).

    CAS  PubMed  Google Scholar 

  3. Burger, M. et al. Epidemiology and risk factors of urothelial bladder cancer. Eur. Urol. 63, 234–241 (2013).

    PubMed  Google Scholar 

  4. Nielsen, M. E. et al. Trends in stage-specific incidence rates for urothelial carcinoma of the bladder in the United States: 1988 to 2006. Cancer 120, 86–95 (2014).

    PubMed  Google Scholar 

  5. Mak, R. H. et al. Long-term outcomes in patients with muscle-invasive bladder cancer after selective bladder-preserving combined-modality therapy: a pooled analysis of radiation therapy Oncology Group Protocols 8802, 8903, 9506, 9706, 9906, and 0233. J. Clin. Oncol. 32, 3801–3809 (2014).

    PubMed  PubMed Central  Google Scholar 

  6. Babjuk, M. et al. EAU guidelines on non-muscle-invasive urothelial carcinoma of the bladder: update 2013. Eur. Urol. 64, 639–653 (2013).

    PubMed  Google Scholar 

  7. Donat, S. M. Evaluation and follow-up strategies for superficial bladder cancer. Urol. Clin. North Am. 30, 765–76 (2003).

    PubMed  Google Scholar 

  8. Sylvester, R. J. 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. 49, 466–475 (2006).

    PubMed  Google Scholar 

  9. Yafi, F. A. et al. Prospective analysis of sensitivity and specificity of urinary cytology and other urinary biomarkers for bladder cancer. Urol. Oncol. 33, e25–e31 (2015).

    Google Scholar 

  10. Grossman, H. B. et al. A phase III, multicenter comparison of hexaminolevulinate fluorescence cystoscopy and white light cystoscopy for the detection of superficial papillary lesions in patients with bladder cancer. J. Urol. 178, 62–67 (2007).

    PubMed  Google Scholar 

  11. Fradet, Y. et al. A comparison of hexaminolevulinate fluorescence cystoscopy and white light cystoscopy for the detection of carcinoma in situ in patients with bladder cancer: a phase III, multicenter study. J. Urol. 178, 68–73 (2007).

    PubMed  Google Scholar 

  12. Mowatt, G. et al. Systematic review of the clinical effectiveness and cost-effectiveness of photodynamic diagnosis and urine biomarkers (FISH, ImmunoCyt, NMP22) and cytology for the detection and follow-up of bladder cancer. Health. Technol. Assess. 14, 1–331 (2010).

    CAS  PubMed  Google Scholar 

  13. Mayer, E. K., Bottle, A., Darzi, A. W., Athanasiou, T. & Vale, J. A. Provision of radical pelvic urological surgery in England, and compliance with improving outcomes guidance. BJU Int. 104, 1446–1451 (2009).

    PubMed  Google Scholar 

  14. Lokeshwar, V. B. et al. Bladder tumor markers beyond cytology: International Consensus Panel on bladder tumor markers. Urology 66, 35–63 (2005).

    PubMed  Google Scholar 

  15. Kamat, A. M. et al. Considerations on the use of urine markers in the management of patients with high-grade non-muscle-invasive bladder cancer. Urol. Oncol. 32, 1069–1077 (2014).

    PubMed  Google Scholar 

  16. Schmitz-Drager, B. J. et al. Considerations on the use of urine markers in the management of patients with low-/intermediate-risk non-muscle invasive bladder cancer. Urol. Oncol. 32, 1061–1068 (2014).

    PubMed  Google Scholar 

  17. Lotan, Y. et al. Considerations on implementing diagnostic markers into clinical decision making in bladder cancer. Urol. Oncol. 28, 441–448 (2010).

    PubMed  Google Scholar 

  18. Habuchi, T. et al. Prognostic markers for bladder cancer: International Consensus Panel on bladder tumor markers. Urology 66, S64–S74 (2005).

    Google Scholar 

  19. van Rhijn, B. W. et al. Molecular markers for urothelial bladder cancer prognosis: Toward implementation in clinical practice. Urol. Oncol. 32, 1078–1087 (2014).

    CAS  PubMed  Google Scholar 

  20. Zuiverloon, T. C. et al. Markers predicting response to bacillus Calmette-Guerin immunotherapy in high-risk bladder cancer patients: a systematic review. Eur. Urol. 61, 128–145 (2012).

    PubMed  Google Scholar 

  21. BTA (Bladder Tumor Antigen) stat® Test, Polymedco [online], (2003).

  22. NMP22® (Nuclear Matrix Protein 22) Test. Alere [online], (2010).

  23. ImmunoCyt/uCyt+ Test, Scimedx [online], (2006).

  24. UroVysion®Test. UroVysion®Test. Abbott Laboratories [online], (2014).

  25. Huber, S. et al. Nuclear matrix protein-22: a prospective evaluation in a population at risk for bladder cancer. Results from the UroScreen study. BJU Int. 110, 699–708 (2012).

    CAS  PubMed  Google Scholar 

  26. Banek, S. et al. Prospective evaluation of fluorescence-in situ-hybridization to detect bladder cancer: results from the UroScreen-Study. Urol. Oncol. 31, 1656–1662 (2013).

    PubMed  Google Scholar 

  27. Odisho, A. Y. et al. Reflex ImmunoCyt testing for the diagnosis of bladder cancer in patients with atypical urine cytology. Eur. Urol. 63, 936–940 (2013).

    PubMed  Google Scholar 

  28. Bantscheff, M., Schirle, M., Sweetman, G., Rick, J. & Kuster, B. Quantitative mass spectrometry in proteomics: a critical review. Anal. Bioanal. Chem. 389, 1017–1031 (2007).

    CAS  PubMed  Google Scholar 

  29. Gingras, A. C., Gstaiger, M., Raught, B. & Aebersold, R. Analysis of protein complexes using mass spectrometry. Nat. Rev. Mol. Cell. Biol. 8, 645–654 (2007).

    CAS  PubMed  Google Scholar 

  30. Wyttenbach, T. & Bowers, M. T. Intermolecular interactions in biomolecular systems examined by mass spectrometry. Annu. Rev. Phys. Chem. 58, 511–533 (2007).

    CAS  PubMed  Google Scholar 

  31. Witze, E. S., Old, W. M., Resing, K. A. & Ahn, N. G. Mapping protein post-translational modifications with mass spectrometry. Nat. Methods 4, 798–806 (2007).

    CAS  PubMed  Google Scholar 

  32. Mischak, H. et al. Epidemiological design and analysis for proteomic studies: a primer on -omic technologies. Am. J. Epidemiol. 181, 635–647 (2015).

    PubMed  Google Scholar 

  33. Mischak, H., Delles, C., Vlahou, A. & Vanholder, R. Proteomic biomarkers in kidney disease: issues in development and implementation Nat. Rev. Nephrol. 11, 221–232 (2015).

    CAS  PubMed  Google Scholar 

  34. Mischak, H. et al. Recommendations for biomarker identification and qualification in clinical proteomics. Sci. Transl. Med. 2, 46ps42 (2010).

    PubMed  Google Scholar 

  35. Minami, S. et al. Proteomic study of sera from patients with bladder cancer: usefulness of S100A8 and S100A9 proteins. Cancer Genomics Proteomics 7, 181–189 (2010).

    CAS  PubMed  Google Scholar 

  36. Ongay, S., Martin-Alvarez, P. J., Neususs, C. & de Frutos, M. Statistical evaluation of CZE-UV and CZE-ESI-MS data of intact α-1-acid glycoprotein isoforms for their use as potential biomarkers in bladder cancer. Electrophoresis 31, 3314–3325 (2010).

    CAS  PubMed  Google Scholar 

  37. Lee, Y. R., Chen, Y. W., Tsai, M. C., Chou, H. C. & Chan, H. L. Redox- and expression-proteomic analysis of plasma biomarkers in bladder transitional cell carcinoma. Mol. Biosyst. 8, 3314–3324 (2012).

    CAS  PubMed  Google Scholar 

  38. Schwamborn, K. et al. Serum proteomic profiling in patients with bladder cancer. Eur. Urol. 56, 989–996 (2009).

    CAS  PubMed  Google Scholar 

  39. Lotan, Y. Editorial comment on: serum proteomic profiling in patients with bladder cancer. Eur. Urol. 56, 996–997 (2009).

    PubMed  Google Scholar 

  40. Decramer, S. et al. Urine in clinical proteomics. Mol. Cell. Proteomics 7, 1850–1862 (2008).

    CAS  PubMed  Google Scholar 

  41. Feldman, A. S., Banyard, J., Wu, C. L., McDougal, W. S. & Zetter, B. R. Cystatin B as a tissue and urinary biomarker of bladder cancer recurrence and disease progression. Clin. Cancer Res. 15, 1024–1031 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Lei, T. et al. Discovery of potential bladder cancer biomarkers by comparative urine proteomics and analysis. Clin. Genitourin. Cancer 11, 56–62 (2013).

    PubMed  Google Scholar 

  43. Li, C. et al. Discovery of Apo-A1 as a potential bladder cancer biomarker by urine proteomics and analysis. Biochem. Biophys. Res. Commun. 446, 1047–1052 (2014).

    CAS  PubMed  Google Scholar 

  44. Tsui, K. H. et al. Bikunin loss in urine as useful marker for bladder carcinoma. J. Urol. 183, 339–344 (2010).

    CAS  PubMed  Google Scholar 

  45. Li, H. et al. Identification of Apo-A1 as a biomarker for early diagnosis of bladder transitional cell carcinoma. Proteome Sci. 9, 21 (2011).

    PubMed  PubMed Central  Google Scholar 

  46. Li, F. et al. Identification of urinary Gc-globulin as a novel biomarker for bladder cancer by two-dimensional fluorescent differential gel electrophoresis (2D-DIGE). J. Proteomics 77, 225–236 (2012).

    CAS  PubMed  Google Scholar 

  47. Zoidakis, J. et al. Profilin 1 is a potential biomarker for bladder cancer aggressiveness. Mol. Cell. Proteomics 11, M111 009449 (2012).

    PubMed  Google Scholar 

  48. Schiffer, E. et al. Prediction of muscle-invasive bladder cancer using urinary proteomics. Clin. Cancer Res. 15, 4935–4943 (2009).

    CAS  PubMed  Google Scholar 

  49. Theodorescu, D. et al. Discovery and validation of new protein biomarkers for urothelial cancer: a prospective analysis. Lancet Oncol. 7, 230–240 (2006).

    CAS  PubMed  Google Scholar 

  50. Chen, C. L. et al. Identification of potential bladder cancer markers in urine by abundant-protein depletion coupled with quantitative proteomics. J. Proteomics 85, 28–43 (2013).

    CAS  PubMed  Google Scholar 

  51. Chen, Y. T. et al. Discovery of novel bladder cancer biomarkers by comparative urine proteomics using iTRAQ technology. J. Proteome Res. 9, 5803–5815 (2010).

    CAS  PubMed  Google Scholar 

  52. Tan, L. B., Chen, K. T., Yuan, Y. C., Liao, P. C. & Guo, H. R. Identification of urine PLK2 as a marker of bladder tumors by proteomic analysis. World J. Urol. 28, 117–122 (2010).

    CAS  PubMed  Google Scholar 

  53. Tyan, Y. C. et al. Urinary protein profiling by liquid chromatography/tandem mass spectrometry: ADAM28 is overexpressed in bladder transitional cell carcinoma. Rapid Commun. Mass Spectrom. 25, 2851–2862 (2011).

    CAS  PubMed  Google Scholar 

  54. Yang, M. H. et al. Characterization of ADAM28 as a biomarker of bladder transitional cell carcinomas by urinary proteome analysis. Biochem. Biophys. Res. Commun. 411, 714–720 (2011).

    CAS  PubMed  Google Scholar 

  55. Yang, N. et al. Urinary glycoprotein biomarker discovery for bladder cancer detection using LC/MS-MS and label-free quantification. Clin. Cancer Res. 17, 3349–3359 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  56. Chen, Y. T. et al. Multiplexed quantification of 63 proteins in human urine by multiple reaction monitoring-based mass spectrometry for discovery of potential bladder cancer biomarkers. J. Proteomics 75, 3529–3545 (2012).

    CAS  PubMed  Google Scholar 

  57. Feng, J. et al. Platelet-derived growth factor receptor β: a novel urinary biomarker for recurrence of non-muscle-invasive bladder cancer. PLoS ONE 9, e96671 (2014).

    PubMed  PubMed Central  Google Scholar 

  58. Frantzi, M. et al. IMAC fractionation in combination with LC-MS reveals H2B and NIF-1 peptides as potential bladder cancer biomarkers. J. Proteome Res. 12, 3969–3979 (2013).

    CAS  PubMed  Google Scholar 

  59. Linden, M. et al. Proteomic analysis of urinary biomarker candidates for nonmuscle invasive bladder cancer. Proteomics 12, 135–144 (2012).

    CAS  PubMed  Google Scholar 

  60. Chen, C. L. et al. Comparative and targeted proteomic analyses of urinary microparticles from bladder cancer and hernia patients. J. Proteome Res. 11, 5611–5629 (2012).

    CAS  PubMed  Google Scholar 

  61. Wood, S. L., Knowles, M. A., Thompson, D., Selby, P. J. & Banks, R. E. Proteomic studies of urinary biomarkers for prostate, bladder and kidney cancers. Nat. Rev. Urol. 10, 206–218 (2013).

    CAS  PubMed  Google Scholar 

  62. Delles, C. et al. Urinary proteomic diagnosis of coronary artery disease: identification and clinical validation in 623 individuals. J. Hypertens 28, 2316–2322 (2010).

    CAS  PubMed  Google Scholar 

  63. Metzger, J. et al. Urinary excretion of twenty peptides forms an early and accurate diagnostic pattern of acute kidney injury. Kidney Int. 78, 1252–1262 (2010).

    PubMed  Google Scholar 

  64. Navarro-Munoz, M. et al. Uromodulin and α(1)-antitrypsin urinary peptide analysis to differentiate glomerular kidney diseases. Kidney Blood Press. Res. 35, 314–325 (2012).

    CAS  PubMed  Google Scholar 

  65. Nawaz, M. et al. The emerging role of extracellular vesicles as biomarkers for urogenital cancers. Nat. Rev. Urol. 11, 688–701 (2014).

    PubMed  Google Scholar 

  66. Dyrskjot, L. et al. Gene expression in the urinary bladder: a common carcinoma in situ gene expression signature exists disregarding histopathological classification. Cancer Res. 64, 4040–4048 (2004).

    CAS  PubMed  Google Scholar 

  67. Mengual, L. et al. DNA microarray expression profiling of bladder cancer allows identification of noninvasive diagnostic markers. J. Urol. 182, 741–748 (2009).

    CAS  PubMed  Google Scholar 

  68. Shimwell, N. J. et al. Combined proteome and transcriptome analyses for the discovery of urinary biomarkers for urothelial carcinoma. Br. J. Cancer 108, 1854–1861 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  69. Chen, L. M. et al. External validation of a multiplex urinary protein panel for the detection of bladder cancer in a multicenter cohort. Cancer Epidemiol. Biomarkers Prev. 23, 1804–1812 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  70. Goodison, S., Chang, M., Dai, Y., Urquidi, V. & Rosser, C. J. A multi-analyte assay for the non-invasive detection of bladder cancer. PLoS ONE 7, e47469 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  71. Rosser, C. J. et al. Urinary protein biomarker panel for the detection of recurrent bladder cancer. Cancer Epidemiol. Biomarkers Prev. 23, 1340–1345 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  72. Rosser, C. J. et al. Bladder cancer-associated gene expression signatures identified by profiling of exfoliated urothelia. Cancer Epidemiol. Biomarkers Prev. 18, 444–453 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  73. Rosser, C. J. et al. Multiplex protein signature for the detection of bladder cancer in voided urine samples. J. Urol. 190, 2257–2262 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  74. Urquidi, V. et al. IL-8 as a urinary biomarker for the detection of bladder cancer. BMC Urol. 12, 12 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  75. Urquidi, V., Goodison, S., Cai, Y., Sun, Y. & Rosser, C. J. A candidate molecular biomarker panel for the detection of bladder cancer. Cancer Epidemiol. Biomarkers Prev. 21, 2149–2158 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  76. Urquidi, V. et al. Vascular endothelial growth factor, carbonic anhydrase 9, and angiogenin as urinary biomarkers for bladder cancer detection. Urology 79, e1–e6 (2012).

    Google Scholar 

  77. Urquidi, V. et al. Diagnostic potential of urinary α-1-antitrypsin and apolipoprotein E in the detection of bladder cancer. J. Urol. 188, 2377–2383 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  78. Urquidi, V. et al. CCL18 in a multiplex urine-based assay for the detection of bladder cancer. PLoS ONE 7, e37797 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  79. Byeon, J. Y. et al. Determination of zolpidem in human plasma by liquid chromatography-tandem mass spectrometry for clinical application. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. 986–987, 129–134 (2015).

    PubMed  Google Scholar 

  80. Robandt, P. P., Reda, L. J. & Klette, K. L. Complete automation of solid-phase extraction with subsequent liquid chromatography-tandem mass spectrometry for the quantification of benzoylecgonine, m-hydroxybenzoylecgonine, p-hydroxybenzoylecgonine, and norbenzoylecgonine in urine—application to a high-throughput urine analysis laboratory. J. Anal. Toxicol. 32, 577–585 (2008).

    CAS  PubMed  Google Scholar 

  81. Tacker, D. H., Topardo, J., Mahaffey, C. & Perrotta, P. L. Workflow analysis comparing manual and automated specimen processing for mass spectrometry-based vitamin d testing. Lab. Med. 45, 361–367 (2014).

    PubMed  Google Scholar 

  82. Wood, P. L. Mass spectrometry strategies for clinical metabolomics and lipidomics in psychiatry, neurology, and neuro-oncology. Neuropsychopharmacology 39, 24–33 (2014).

    PubMed  Google Scholar 

  83. Sauer, S. & Kliem, M. Mass spectrometry tools for the classification and identification of bacteria. Nat. Rev. Microbiol. 8, 74–82 (2010).

    CAS  PubMed  Google Scholar 

  84. Kato, M. et al. DDX39 acts as a suppressor of invasion for bladder cancer. Cancer Sci. 103, 1363–1369 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  85. Niu, H. T. et al. Differences in shotgun protein expression profile between superficial bladder transitional cell carcinoma and normal urothelium. Urol. Oncol. 27, 400–406 (2009).

    CAS  PubMed  Google Scholar 

  86. Niu, H. T. et al. Cancer stroma proteome expression profile of superficial bladder transitional cell carcinoma and biomarker discovery. J. Cancer Res. Clin. Oncol. 137, 1273–1282 (2011).

    CAS  PubMed  Google Scholar 

  87. Niu, H. et al. Stromal proteome expression profile and muscle-invasive bladder cancer research. Cancer Cell Int. 12, 39 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  88. Niu, H. T. et al. Parallel proteomic analysis in muscle-invasive bladder transitional cell carcinoma and cancer-related stroma. Genet. Mol. Res. 12, 4251–4263 (2013).

    CAS  PubMed  Google Scholar 

  89. Liu, P. F. et al. Heterogeneity research in muscle-invasive bladder cancer based on differential protein expression analysis. Med. Oncol. 31, 21 (2014).

    PubMed  Google Scholar 

  90. Liu, P. F. et al. Far from resolved: stromal cell-based iTRAQ research of muscle-invasive bladder cancer regarding heterogeneity. Oncol. Rep. 32, 1489–1496 (2014).

    CAS  PubMed  Google Scholar 

  91. Frantzi, M., Makridakis, M. & Vlahou, A. Biomarkers for bladder cancer aggressiveness. Curr. Opin. Urol. 22, 390–396 (2012).

    PubMed  Google Scholar 

  92. Gakis, G., Schwentner, C., Todenhofer, T. & Stenzl, A. Current status of molecular markers for prognostication and outcome in invasive bladder cancer. BJU Int. 110, 233–237 (2012).

    CAS  PubMed  Google Scholar 

  93. Ru, Y., Dancik, G. M. & Theodorescu, D. Biomarkers for prognosis and treatment selection in advanced bladder cancer patients. Curr. Opin. Urol. 21, 420–427 (2011).

    PubMed  PubMed Central  Google Scholar 

  94. Sanguedolce, F., Bufo, P., Carrieri, G. & Cormio, L. Predictive markers in bladder cancer: do we have molecular markers ready for clinical use? Crit. Rev. Clin. Lab. Sci. 51, 291–304 (2014).

    CAS  PubMed  Google Scholar 

  95. Moreira, J. M. et al. Bladder cancer-associated protein, a potential prognostic biomarker in human bladder cancer. Mol. Cell. Proteomics. 9, 161–177 (2010).

    CAS  PubMed  Google Scholar 

  96. Fristrup, N. et al. Multicenter validation of cyclin D1, MCM7, TRIM29, and UBE2C as prognostic protein markers in non-muscle-invasive bladder cancer. Am. J. Pathol. 182, 339–349 (2013).

    CAS  PubMed  Google Scholar 

  97. Fristrup, N. et al. Cathepsin E, maspin, Plk1, and survivin are promising prognostic protein markers for progression in non-muscle invasive bladder cancer. Am. J. Pathol. 180, 1824–1834 (2012).

    CAS  PubMed  Google Scholar 

  98. Laurberg, J. R. et al. Expression of TIP60 (tat-interactive protein) and MRE11 (meiotic recombination 11 homolog) predict treatment-specific outcome of localised invasive bladder cancer. BJU Int. 110, E1228–E1236 (2012).

    CAS  PubMed  Google Scholar 

  99. Ajili, F. et al. Prognostic value of Bcl-2 and Bax tumor cell expression in patients with non muscle-invasive bladder cancer receiving bacillus Calmette-Guerin immunotherapy. Ultrastruct. Pathol. 36, 31–39 (2012).

    PubMed  Google Scholar 

  100. Shariat, S. F. et al. Risk stratification of organ confined bladder cancer after radical cystectomy using cell cycle related biomarkers. J. Urol. 187, 457–462 (2012).

    PubMed  Google Scholar 

  101. Kramer, M. W. et al. Decreased galectin-8 is a strong marker for recurrence in urothelial carcinoma of the bladder. Urol. Int. 87, 143–150 (2011).

    CAS  PubMed  Google Scholar 

  102. Kramer, M. W. et al. Maspin protein expression correlates with tumor progression in non-muscle invasive bladder cancer. Oncol. Lett. 1, 621–626 (2010).

    PubMed  PubMed Central  Google Scholar 

  103. Seiler, R., Thalmann, G. N., Rotzer, D., Perren, A. & Fleischmann, A. CCND1/CyclinD1 status in metastasizing bladder cancer: a prognosticator and predictor of chemotherapeutic response. Mod. Pathol. 27, 87–95 (2014).

    CAS  PubMed  Google Scholar 

  104. Choudhury, A. et al. MRE11 expression is predictive of cause-specific survival following radical radiotherapy for muscle-invasive bladder cancer. Cancer Res. 70, 7017–7026 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  105. Klatte, T. et al. Carbonic anhydrase IX in bladder cancer: a diagnostic, prognostic, and therapeutic molecular marker. Cancer 115, 1448–1458 (2009).

    PubMed  Google Scholar 

  106. Czachorowski, M. J. et al. Cyclooxygenase-2 expression in bladder cancer and patient prognosis: results from a large clinical cohort and meta-analysis. PLoS ONE 7, e45025 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  107. The TransBioBC project. TransBioBC - Translation of novel biomarkers for bladder cancer for clinical outcome prediction [online], (2015).

  108. McShane, L. M. et al. Reporting recommendations for tumor marker prognostic studies (REMARK). J. Natl Cancer Inst. 97, 1180–1184 (2005).

    CAS  PubMed  Google Scholar 

  109. Pepe, M. S., Feng, Z., Janes, H., Bossuyt, P. M. & Potter, J. D. Pivotal evaluation of the accuracy of a biomarker used for classification or prediction: standards for study design. J. Natl Cancer Inst. 100, 1432–1438 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  110. von Elm, E. et al. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. BMJ 335, 806–808 (2007).

    PubMed  PubMed Central  Google Scholar 

  111. Winget, M. D. et al. Development of common data elements: the experience of and recommendations from the early detection research network. Int. J. Med. Inform. 70, 41–48 (2003).

    PubMed  Google Scholar 

  112. Vlahou, A. Network views for personalized medicine. Proteomics Clin. Appl. 7, 384–387 (2013).

    CAS  PubMed  Google Scholar 

  113. Chen, J. et al. Shikonin and its analogs inhibit cancer cell glycolysis by targeting tumor pyruvate kinase-M2. Oncogene 30, 4297–4306 (2011).

    CAS  PubMed  Google Scholar 

  114. Christofk, H. R. et al. The M2 splice isoform of pyruvate kinase is important for cancer metabolism and tumour growth. Nature 452, 230–233 (2008).

    CAS  PubMed  Google Scholar 

  115. Stadler, W. M. et al. Phase III study of molecularly targeted adjuvant therapy in locally advanced urothelial cancer of the bladder based on p53 status. J. Clin. Oncol. 29, 3443–3449 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  116. Mischak, H., Vlahou, A., Righetti, P. G. & Calvete, J. J. Putting value in biomarker research and reporting. J. Proteomics 96, A1–A3 (2014).

    CAS  PubMed  Google Scholar 

  117. Guo, A. et al. Bladder tumour antigen (BTA stat) test compared to the urine cytology in the diagnosis of bladder cancer: A meta-analysis. Can. Urol. Assoc. J. 8, E347–E352 (2014).

    PubMed  PubMed Central  Google Scholar 

  118. van Rhijn, B. W., van der Poel, H. G. & van der Kwast, T. H. Urine markers for bladder cancer surveillance: a systematic review. Eur. Urol. 47, 736–748 (2005).

    CAS  PubMed  Google Scholar 

  119. Lotan, Y. & Roehrborn, C. G. Sensitivity and specificity of commonly available bladder tumor markers versus cytology: results of a comprehensive literature review and meta-analyses. Urology 61, 109–118 (2003).

    PubMed  Google Scholar 

  120. Raitanen, M. P. & FinnBladder, G. The role of BTA stat test in follow-up of patients with bladder cancer: results from FinnBladder studies. World J. Urol. 26, 45–50 (2008).

    PubMed  Google Scholar 

  121. Cha, E. K. et al. Immunocytology is a strong predictor of bladder cancer presence in patients with painless hematuria: a multicentre study. Eur. Urol. 61, 185–192 (2012).

    PubMed  Google Scholar 

  122. Bonberg, N. et al. Chromosomal instability and bladder cancer: the UroVysion(TM) test in the UroScreen study. BJU Int 112, E372–E382 (2013).

    CAS  PubMed  Google Scholar 

  123. Dimashkieh, H. et al. Evaluation of urovysion and cytology for bladder cancer detection: a study of 1835 paired urine samples with clinical and histologic correlation. Cancer Cytopathol. 121, 591–597 (2013).

    PubMed  PubMed Central  Google Scholar 

  124. Kauffman, E. C. et al. Role of androgen receptor and associated lysine-demethylase coregulators, LSD1 and JMJD2A, in localized and advanced human bladder cancer. Mol. Carcinog. 50, 931–944 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  125. Kramer, M. W. et al. HYAL-1 hyaluronidase: a potential prognostic indicator for progression to muscle invasion and recurrence in bladder cancer. Eur. Urol. 57, 86–93 (2010).

    CAS  PubMed  Google Scholar 

Download references

Acknowledgements

The work is supported in part by the BCMolMed grant (PITN-GA-2012-317,450) from the FP7–PEOPLE–2012–ITN programme and TransBioBC grant (601,933) from the FP7-Health project funded by the European Commission.

Author information

Authors and Affiliations

Authors

Contributions

M.F., A.L. and L.F. researched data for the article, M.F. and A.L. wrote the article, M.C.H., M.W.K., A.S.M., H.M. and A.V. made a substantial contribution to discussions of content, M.F., A.L., E.C., H.M. and A.V. reviewed and/or edited the manuscript before submission. M.F. and A.L. contributed equally, and should be considered equal first authors.

Corresponding author

Correspondence to Maria Frantzi.

Ethics declarations

Competing interests

H.M. is the founder and co-owner of Mosaiques Diagnostics. M.F. is employed by Mosaiques Diagnostics as part of an EID (Industrial-Academia) Marie Curie Action. L.F. is employed by Mosaiques Diagnostics. The other authors declare no competing interests.

PowerPoint slides

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Frantzi, M., Latosinska, A., Flühe, L. et al. Developing proteomic biomarkers for bladder cancer: towards clinical application. Nat Rev Urol 12, 317–330 (2015). https://doi.org/10.1038/nrurol.2015.100

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nrurol.2015.100

This article is cited by

Search

Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer