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:

Proteomic studies of urinary biomarkers for prostate, bladder and kidney cancers

Nature Reviews Urology volume 10, pages 206–218 (2013)Cite this article

Subjects

Abstract

Urine is an ideal body fluid for the detection of protein markers produced by urological cancers as it can be sampled noninvasively and contains secreted and directly shed proteins from the prostate, bladder and kidney. Major challenges of working with urine include high inter-individual and intra-individual variability, low protein concentration, the presence of salts and the dynamic range of protein expression. Despite these challenges, significant progress is being made using modern proteomic methods to identify and characterize protein-based markers for urological cancers. The development of robust, easy-to-use clinical tests based on novel biomarkers has the potential to impact upon diagnosis, prognosis and monitoring and could revolutionize the treatment and management of these cancers.

Key Points

  • Urine is an accessible body fluid that can be utilized for the discovery of prognostic, diagnostic and monitoring biomarkers for urological cancers

  • Proteomics has the potential to identify the key molecules in urine that are involved in the development and spread of urological cancers and might have roles as biomarkers

  • Increasing numbers of potential biomarkers are being discovered for prostate cancer, bladder cancer and renal cell carcinoma using urine-based proteomic studies

  • Urinary exosomes are a promising source of biomarkers for cancer diagnosis

  • Consideration needs to be given to how biomarkers from laboratory-based studies are validated and evaluated to ensure effective and timely translation into clinical use

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

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

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

Figure 1: Proteomic analysis for discovery of biomarkers of urological cancers.
Figure 2: Biomarker validation—from discovery to clinical application.

Similar content being viewed by others

References

  1. Strong, K. J., Osicka, T. M. & Comper, W. D. Urinary-peptide excretion by patients with and volunteers without diabetes. J. Lab. Clin. Med. 145, 239–246 (2005).

    Article  CAS  PubMed  Google Scholar 

  2. Saraon, P., Jarvi, K. & Diamandis, E. P. Molecular alterations during progression of prostate cancer to androgen independence. Clin. Chem. 57, 1366–1375 (2011).

    Article  CAS  PubMed  Google Scholar 

  3. Oosterwijk, E. et al Basic research in kidney cancer. Eur. Urol., 60, 622–633 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  4. Castillo-Martin, M. et al. Molecular pathways of urothelial development and bladder tumorigenesis. Urol. Oncol. 28, 401–408 (2010).

    Article  CAS  PubMed  Google Scholar 

  5. Norden, A. G., Rodriguez-Cutillas, P. & Unwin, R. J. Clinical urinary peptidomics: learning to walk before we can run. Clin. Chem. 53, 375–376 (2007).

    Article  CAS  PubMed  Google Scholar 

  6. Nagaraj, N. & Mann, M. Quantitative analysis of the intra- and inter-individual variability of the normal urinary proteome. J. Proteome Res. 10, 637–645 (2011).

    Article  CAS  PubMed  Google Scholar 

  7. Mischak, H. et al. Comprehensive human urine standards for comparability and standardization in clinical proteome analysis. Proteomics Clin. Appl. 4, 464–478 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Weissinger, E. M. et al. Proteomic patterns established with capillary electrophoresis and mass spectrometry for diagnostic purposes. Kidney Int. 65, 2426–2434 (2004).

    Article  CAS  PubMed  Google Scholar 

  9. Ferguson, M. A. & Waikar, S. S. Established and emerging markers of kidney function. Clin. Chem. 58, 680–689 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Jackson, D. H. & Banks, R. E. Banking of clinical samples for proteomic biomarker studies: a consideration of logistical issues with a focus on pre-analytical variation. Proteomics Clin. Appl. 4, 250–270 (2010).

    Article  CAS  PubMed  Google Scholar 

  11. Molina, L. et al. Analysis of the variability of human normal urine by 2D-GE reveals a “public” and a “private” proteome. J. Proteomics 75, 70–80 (2011).

    Article  CAS  PubMed  Google Scholar 

  12. Jantos-Siwy, J. et al. Quantitative urinary proteome analysis for biomarker evaluation in chronic kidney disease. J. Proteome Res. 8, 268–281 (2009).

    Article  CAS  PubMed  Google Scholar 

  13. Kentsis, A. et al. Urine proteomics for profiling of human disease using high accuracy mass spectrometry. Proteomics Clin. Appl. 3, 1052–1061 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Adachi, J. et al. The human urinary proteome contains more than 1500 proteins, including a large proportion of membrane proteins. Genome Biol. 7, R80 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Castagna, A. et al. Exploring the hidden human urinary proteome via ligand library beads. J. Proteome Res. 4, 1917–1930 (2005).

    Article  CAS  PubMed  Google Scholar 

  16. Pieper, R. et al. Characterization of the human urinary proteome: a method for high-resolution display of urinary proteins on two-dimensional electrophoresis gels with a yield of nearly 1400 distinct protein spots. Proteomics 4, 1159–1174 (2004).

    Article  CAS  PubMed  Google Scholar 

  17. Marimuthu, A. et al. A comprehensive map of the human urinary proteome. J. Proteome Res. 10, 2734–2743 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Pan, B. T. et al. Electron microscopic evidence for externalization of the transferrin receptor in vesicular form in sheep reticulocytes. J. Cell. Biol. 101, 942–948 (1985).

    Article  CAS  PubMed  Google Scholar 

  19. Pisitkun, T., Shen, R. F. & Knepper, M. A. Identification and proteomic profiling of exosomes in human urine. Proc. Natl Acad. Sci. USA 101, 13368–13373 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Gonzalez-Begne, M. et al. Proteomic analysis of human parotid gland exosomes by multidimensional protein identification technology (MudPIT). J. Proteome Res. 8, 1304–1314 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Vlassov, A. V. et al. Exosomes: current knowledge of their composition, biological functions, and diagnostic and therapeutic potentials. Biochim. Biophys. Acta 1820, 940–948 (2012).

    Article  CAS  PubMed  Google Scholar 

  22. Wang, Z. et al. Proteomic analysis of urine exosomes by multidimensional protein identification technology (MudPIT). Proteomics 12, 329–338 (2012).

    Article  CAS  PubMed  Google Scholar 

  23. Zhou, H. et al. Collection, storage, preservation, and normalization of human urinary exosomes for biomarker discovery. Kidney Int. 69, 1471–1476 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Tran, J. C. et al. Mapping intact protein isoforms in discovery mode using top-down proteomics. Nature 480, 254–258 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Bakry, R. et al. Protein profiling for cancer biomarker discovery using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and infrared imaging: a review. Anal. Chim. Acta 690, 26–34 (2011).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  27. Jemal, A. et al. Cancer statistics, 2008. CA Cancer J. Clin. 58, 71–96 (2008).

    Article  PubMed  Google Scholar 

  28. Catto, J. W. Health care spending, social policy, public health, and life expectancy: what cancer outcomes can tell us beyond treatment efficacy. Eur. Urol. 60, 16–18 (2011).

    Article  PubMed  Google Scholar 

  29. Lilja, H., Ulmert, D. & Vickers, A. J. Prostate-specific antigen and prostate cancer: prediction, detection and monitoring. Nature Rev. Cancer 8, 268–278 (2008).

    Article  CAS  Google Scholar 

  30. Brawer, M. K. et al. Screening for prostatic carcinoma with prostate specific antigen. J. Urol. 147, 841–845 (1992).

    Article  CAS  PubMed  Google Scholar 

  31. Krumholtz, J. S. et al. Prostate-specific antigen cutoff of 2.6 ng/mL for prostate cancer screening is associated with favorable pathologic tumor features. Urology 60, 469–473 (2002).

    Article  PubMed  Google Scholar 

  32. Lin, K. et al. Benefits and harms of prostate-specific antigen screening for prostate cancer: an evidence update for the, U. S. Preventive Services Task Force. Ann. Intern. Med. 149, 192–199 (2008).

    Article  PubMed  Google Scholar 

  33. Loberg, R. D. et al. Pathogenesis and treatment of prostate cancer bone metastases: targeting the lethal phenotype. J. Clin. Oncol. 23, 8232–8241 (2005).

    Article  CAS  PubMed  Google Scholar 

  34. Horwich, A. Prostate cancer management. Ann. Oncol. 15 (Suppl. 4), iv307–iv312 (2004).

    PubMed  Google Scholar 

  35. Merrimen, J. L., Jones, G. & Srigley, J. R. Is high grade prostatic intraepithelial neoplasia still a risk factor for adenocarcinoma in the era of extended biopsy sampling? Pathology 42, 325–329 (2010).

    Article  PubMed  Google Scholar 

  36. Ploussard, G. & de la Taille, A. Urine biomarkers in prostate cancer. Nat. Rev. Urol. 7, 101–109 (2010).

    Article  CAS  PubMed  Google Scholar 

  37. True, L. D. et al. CD90/THY1 is overexpressed in prostate cancer-associated fibroblasts and could serve as a cancer biomarker. Mod. Pathol. 23, 1346–1356 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Cheng, H. L. et al. Urinary CD14 as a potential biomarker for benign prostatic hyperplasia—discovery by combining MALDI-TOF-based biostatistics and ESI-MS/MS-based stable-isotope labeling. Proteomics Clin. Appl. 5, 121–132 (2011).

    Article  CAS  PubMed  Google Scholar 

  39. Principe, S. et al. Identification of prostate-enriched proteins by in-depth proteomic analyses of expressed prostatic secretions in urine. J. Proteome Res. 11, 2386–2396 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Drake, R. R. et al. Clinical collection and protein properties of expressed prostatic secretions as a source for biomarkers of prostatic disease. J. Proteomics 72, 907–917 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Reis, S. T. et al. MMP-9 overexpression due to TIMP-1 and RECK underexpression is associated with prognosis in prostate cancer. Int. J. Biol. Markers 26, 255–261 (2011).

    Article  CAS  PubMed  Google Scholar 

  42. Liu, A. Y. Zhang, H., Sorensen, C. M. & Diamond, D. L. Analysis of prostate cancer by proteomics using tissue specimens. J. Urol. 173, 73–78 (2005).

  43. Mhawech, P., Greloz, V., Assaly, M. & Herrmann, F. Immunohistochemical expression of 14-3-3 sigma protein in human urological and gynecological tumors using a multi-tumor microarray analysis. Pathol. Int. 55, 77–82 (2005).

    Article  CAS  PubMed  Google Scholar 

  44. Lehmann, B. D. et al. Senescence-associated exosome release from human prostate cancer cells. Cancer Res. 68, 7864–7871 (2008).

    Article  CAS  PubMed  Google Scholar 

  45. Ronquist, K. G. et al. Proteomic analysis of prostate cancer metastasis-derived prostasomes. Anticancer Res. 30, 285–290 (2010).

    CAS  PubMed  Google Scholar 

  46. Theodorescu, D. et al. Pilot study of capillary electrophoresis coupled to mass spectrometry as a tool to define potential prostate cancer biomarkers in urine. Electrophoresis 26, 2797–2808 (2005).

    Article  CAS  PubMed  Google Scholar 

  47. Theodorescu, D. et al. Discovery and validation of urinary biomarkers for prostate cancer. Proteomics Clin. Appl. 2, 556–570 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Schiffer, E. et al. Urinary proteome analysis for prostate cancer diagnosis: cost-effective application in routine clinical practice in Germany. Int. J. Urol. 19, 118–125 (2012).

    Article  CAS  PubMed  Google Scholar 

  49. Okamoto, A. et al. Protein profiling of post-prostatic massage urine specimens by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry to discriminate between prostate cancer and benign lesions. Oncol. Rep. 21, 73–79 (2009).

    Article  CAS  PubMed  Google Scholar 

  50. M'Koma, A. E. et al. Detection of pre-neoplastic and neoplastic prostate disease by MALDI profiling of urine. Biochem. Biophys. Res. Commun. 353, 829–834 (2007).

    Article  CAS  PubMed  Google Scholar 

  51. Schostak, M. et al. Annexin A3 in urine: a highly specific noninvasive marker for prostate cancer early detection. J. Urol. 181, 343–353 (2009).

    Article  CAS  PubMed  Google Scholar 

  52. Morgan, R. et al. Engrailed-2 (EN2): a tumor specific urinary biomarker for the early diagnosis of prostate cancer. Clin. Cancer Res. 17, 1090–1098 (2011).

    Article  CAS  PubMed  Google Scholar 

  53. Pandha, H. et al. Urinary engrailed-2 (EN2) levels predict tumour volume in men undergoing radical prostatectomy for prostate cancer. BJU Int. 110, E287–E292 (2012).

    Article  CAS  PubMed  Google Scholar 

  54. Ferlay, J. et al. Declining mortality from bladder cancer in Europe. BJU Int. 101, 11–19 (2008).

    PubMed  Google Scholar 

  55. Kaufman, D. S., Shipley, W. U. & Feldman, A. S. Bladder cancer. Lancet 374, 239–249 (2009).

    Article  CAS  PubMed  Google Scholar 

  56. Messing, E. M. et al. Grade and stage at presentation do not predict mortality in patients with bladder cancer who survive their disease. J. Clin. Oncol. 27, 2443–2449 (2009).

    Article  PubMed  Google Scholar 

  57. Mitra, A. P. & Cote, R. J. Molecular screening for bladder cancer: progress and potential. Nat. Rev. Urol. 7, 11–20 (2010).

    Article  CAS  PubMed  Google Scholar 

  58. 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).

    Article  CAS  PubMed  Google Scholar 

  59. Saito, M. et al. Proteome analysis of gelatin-bound urinary proteins from patients with bladder cancers. Eur. Urol. 48, 865–871 (2005).

    Article  CAS  PubMed  Google Scholar 

  60. 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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Hwa, J. S. et al. Identification of proteins differentially expressed in the conventional renal cell carcinoma by proteomic analysis. J. Korean Med. Sci. 20, 450–455 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  63. 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).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  65. Tan, L. B. et al. Identification of urine PLK2 as a marker of bladder tumors by proteomic analysis. World J. Urol. 28, 117–122 (2010).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  67. Pollard, C. et al. Genoproteomic mining of urothelial cancer suggests {gamma}-glutamyl hydrolase and diazepam-binding inhibitor as putative urinary markers of outcome after chemotherapy. Am. J. Pathol. 175, 1824–1830 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Lin, C. Y. et al. Searching cell-secreted proteomes for potential urinary bladder tumor markers. Proteomics 6, 4381–4389 (2006).

    Article  CAS  PubMed  Google Scholar 

  69. Kawanishi, H. et al. Secreted CXCL1 is a potential mediator and marker of the tumor invasion of bladder cancer. Clin. Cancer Res. 14, 2579–2587 (2008).

    Article  CAS  PubMed  Google Scholar 

  70. Selevsek, N. et al. Systematic quantification of peptides/proteins in urine using selected reaction monitoring. Proteomics 11, 1135–1147 (2011).

    Article  CAS  PubMed  Google Scholar 

  71. Welton, J. L. et al. Proteomics analysis of bladder cancer exosomes. Mol. Cell Proteomics 9, 1324–1338 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Vlahou, A. et al. Development of a novel proteomic approach for the detection of transitional cell carcinoma of the bladder in urine. Am. J. Pathol. 158, 1491–1502 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Zhang, Y. F. et al. Tree analysis of mass spectral urine profiles discriminates transitional cell carcinoma of the bladder from noncancer patient. Clin. Biochem. 37, 772–779 (2004).

    Article  CAS  PubMed  Google Scholar 

  74. Munro, N. P. et al. Urinary biomarker profiling in transitional cell carcinoma. Int. J. Cancer 119, 2642–2650 (2006).

    Article  CAS  PubMed  Google Scholar 

  75. Bryan, R. T. et al. Assessment of high-throughput high-resolution MALDI-TOF-MS of urinary peptides for the detection of muscle-invasive bladder cancer. Proteomics Clin. Appl. 5, 493–503 (2011).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  78. Motzer, R. J., Bander, N. H. & Nanus, D. M. Renal-cell carcinoma. N. Engl. J. Med. 335, 865–875 (1996).

    Article  CAS  PubMed  Google Scholar 

  79. Najjar, Y. G. & Rini, B. I. Novel agents in renal carcinoma: a reality check. Ther. Adv. Med. Oncol. 4, 183–194 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Minamida, S. et al. 14-3-3 protein beta/alpha as a urinary biomarker for renal cell carcinoma: proteomic analysis of cyst fluid. Anal. Bioanal. Chem. 401, 245–252 (2011).

    Article  CAS  PubMed  Google Scholar 

  81. Gardino, A. K. & Yaffe, M. B. 14-3-3 proteins as signaling integration points for cell cycle control and apoptosis. Semin. Cell Dev. Biol. 22, 688–695 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Masui, O. et al. Quantitative proteomic analysis in metastatic renal cell carcinoma reveals a unique set of proteins with potential prognostic significance. Mol. Cell Proteomics 12, 132–144 (2013).

    Article  CAS  PubMed  Google Scholar 

  83. Vasudev, N. S. et al. Pre-operative urinary cathepsin D is associated with survival in patients with renal cell carcinoma. Br. J. Cancer 101, 1175–1182 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Beasley, N. J. et al. Carbonic anhydrase IX, an endogenous hypoxia marker, expression in head and neck squamous cell carcinoma and its relationship to hypoxia, necrosis, and microvessel density. Cancer Res. 61, 5262–5267 (2001).

    CAS  PubMed  Google Scholar 

  85. Zavada, J. et al. Soluble form of carbonic anhydrase IX (CA IX) in the serum and urine of renal carcinoma patients. Br. J. Cancer 89, 1067–1071 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. Bonventre, J. V. Kidney Injury Molecule-1 (KIM-1): a specific and sensitive biomarker of kidney injury. Scand. J. Clin. Lab. Invest. Suppl. 241, 78–83 (2008).

    Article  CAS  PubMed  Google Scholar 

  87. Morrissey, J. J. et al. Sensitivity and specificity of urinary neutrophil gelatinase-associated lipocalin and kidney injury molecule-1 for the diagnosis of renal cell carcinoma. Am. J. Nephrol. 34, 391–398 (2011).

    Article  CAS  PubMed  Google Scholar 

  88. Morrissey, J. J. et al. Urinary biomarkers for the early diagnosis of kidney cancer. Mayo Clin. Proc. 85, 413–421 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Kaya, K. et al. Urinary nuclear matrix protein 22 for diagnosis of renal cell carcinoma. Scand. J. Urol. Nephrol. 39, 25–29 (2005).

    Article  CAS  PubMed  Google Scholar 

  90. Zhang, Y. et al. Exosomes derived from IL-12-anchored renal cancer cells increase induction of specific antitumor response in vitro: a novel vaccine for renal cell carcinoma. Int. J. Oncol. 36, 133–140 (2010).

    PubMed  Google Scholar 

  91. Del Boccio, P. et al. A hyphenated microLC-Q-TOF-MS platform for exosomal lipidomics investigations: application to RCC urinary exosomes. Electrophoresis 33, 689–696 (2012).

    Article  CAS  PubMed  Google Scholar 

  92. Bosso, N. et al. Human urine biomarkers of renal cell carcinoma evaluated by ClinProt. Proteomics Clin. Appl. 2, 1036–1046 (2008).

    Article  CAS  PubMed  Google Scholar 

  93. Wu, D. L. et al. Proteomic evaluation of urine from renal cell carcinoma using SELDI-TOF-MS and tree analysis pattern. Technol. Cancer Res. Treat. 7, 155–160 (2008).

    Article  CAS  PubMed  Google Scholar 

  94. Rogers, M. A. et al. Proteomic profiling of urinary proteins in renal cancer by surface enhanced laser desorption ionization and neural-network analysis: identification of key issues affecting potential clinical utility. Cancer Res. 63, 6971–6983 (2003).

    CAS  PubMed  Google Scholar 

  95. Wood, S. L. et al. Association of serum amyloid A protein and peptide fragments with prognosis in renal cancer. Br. J. Cancer 103, 101–111 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Shao, C. et al. A tool for biomarker discovery in the urinary proteome: a manually curated human and animal urine protein biomarker database. Mol. Cell Proteomics 10, M111 010975 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  97. Sturgeon, C. et al. Taking a new biomarker into routine use--a perspective from the routine clinical biochemistry laboratory. Proteomics Clin. Appl. 4, 892–903 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Ablin, R. J. et al. Precipitating antigens of the normal human prostate. J. Reprod. Fertil. 22, 573–574 (1970).

    Article  CAS  PubMed  Google Scholar 

  99. Stamey, T. A. et al. Prostate-specific antigen as a serum marker for adenocarcinoma of the prostate. N. Engl. J. Med. 317, 909–916 (1987).

    Article  CAS  PubMed  Google Scholar 

  100. Rafferty, B. et al. Reference reagents for prostate-specific antigen (PSA): establishment of the first international standards for free PSA and PSA (90:10). Clin. Chem. 46, 1310–1317 (2000).

    CAS  PubMed  Google Scholar 

  101. Fung, E. T. A recipe for proteomics diagnostic test development: the OVA1 test, from biomarker discovery to FDA clearance. Clin. Chem. 56, 327–329 (2010).

    Article  CAS  PubMed  Google Scholar 

  102. Hoofnagle, A. N. Quantitative clinical proteomics by liquid chromatography-tandem mass spectrometry: assessing the platform. Clin. Chem. 56, 161–164 (2010).

    Article  CAS  PubMed  Google Scholar 

  103. Makawita, S. & Diamandis, E. P. The bottleneck in the cancer biomarker pipeline and protein quantification through mass spectrometry-based approaches: current strategies for candidate verification. Clin. Chem. 56, 212–222 (2010).

    Article  CAS  PubMed  Google Scholar 

  104. Carr, S. A. & Anderson, L. Protein quantitation through targeted mass spectrometry: the way out of biomarker purgatory? Clin. Chem. 54, 1749–1752 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Hüttenhain, R. et al. Reproducible quantification of cancer-associated proteins in body fluids using targeted proteomics. Sci. Transl. Med. 4, 142ra94 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  106. Abogunrin, F. et al. The impact of biomarkers in multivariate algorithms for bladder cancer diagnosis in patients with hematuria. Cancer 118, 2641–2650 (2012).

    Article  CAS  PubMed  Google Scholar 

  107. Rifai, N., Watson, I. D. & Miller, W. G. Commercial Immunoassays in Biomarkers Studies: Researchers Beware! Clin. Chem. 58, 1387–1388 (2012).

    Article  CAS  PubMed  Google Scholar 

  108. Sim, S. H. et al. Prognostic utility of pre-operative circulating osteopontin, carbonic anhydrase IX and CRP in renal cell carcinoma. Br. J. Cancer 107, 131–1137 (2012).

    Article  CAS  Google Scholar 

  109. Li, J., Kelm, K. B. & Tezak, Z. Regulatory perspective on translating proteomic biomarkers to clinical diagnostics. J. Proteomics 74, 2682–2690 (2011).

    Article  CAS  PubMed  Google Scholar 

  110. Regnier, F. E. et al. Protein-based multiplex assays: mock presubmissions to the US Food and Drug Administration. Clin. Chem. 56, 165–171 (2010).

    Article  CAS  PubMed  Google Scholar 

  111. Boja, E. S. et al. The journey to regulation of protein-based multiplex quantitative assays. Clin. Chem. 57, 560–567 (2011).

    Article  CAS  PubMed  Google Scholar 

  112. Freidlin, B., McShane, L. M. & Korn, E. L. Randomized clinical trials with biomarkers: design issues. J. Natl Cancer Inst. 102, 152–160 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  113. Subramanian, J. & Simon, R. Gene expression-based prognostic signatures in lung cancer: ready for clinical use? J. Natl Cancer Inst. 102, 464–474 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  114. Moons, K. G. et al. Quantifying the added value of a diagnostic test or marker. Clin. Chem. 58, 1408–1417 (2012).

    Article  PubMed  Google Scholar 

  115. Linnet, K. et al. Quantifying the accuracy of a diagnostic test or marker. Clin. Chem. 58, 1292–1301 (2012).

    Article  CAS  PubMed  Google Scholar 

  116. Boyd, J. C., Rifai, N. & Annesley, T. Statistical methods for test and biomarker evaluation studies: a clinical chemistry series. Clin. Chem. 58, 1273–1274 (2012).

    Article  CAS  PubMed  Google Scholar 

  117. 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).

    Article  CAS  PubMed  Google Scholar 

  118. Yossepowitch, O., Herr, H. W. & Donat, S. M. Use of urinary biomarkers for bladder cancer surveillance: patient perspectives. J. Urol. 177, 1277–1282 (2007).

    Article  PubMed  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  120. 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).

    Article  CAS  PubMed  Google Scholar 

  121. Orenes-Pinero, E. et al. Searching urinary tumor markers for bladder cancer using a two-dimensional differential gel electrophoresis (2D-DIGE) approach. J. Proteome Res. 6, 4440–4448 (2007).

    Article  CAS  PubMed  Google Scholar 

  122. Iwaki, H. et al. Diagnostic potential in bladder cancer of a panel of tumor markers (calreticulin, gamma -synuclein, and catechol-o-methyltransferase) identified by proteomic analysis. Cancer Sci. 95, 955–961 (2004).

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

S. L. Wood was supported by an Experimental Cancer Medical Centre grant (Leeds) and a Clinical Research Initiative and Experimental Cancer Medical Centre grant (Manchester) from Cancer Research UK. R. E. Banks was supported by Cancer Research UK.

Author information

Authors and Affiliations

  1. Wolfson Molecular Imaging Centre, 27 Palatine Road, Withington, M20 3LJ, Manchester, UK

    Steven L. Wood

  2. Clinical and Biomedical Proteomics Group, Cancer Research Centre, Leeds Institute of Molecular Medicine, St James' University Hospital, Beckett Street, Leeds, LS9 7TF, UK

    Margaret A. Knowles, Peter J. Selby & Rosamonde E. Banks

  3. Blood Sciences Department, The General Infirmary, Leeds, LS1 3EX, UK

    Douglas Thompson

Authors
  1. Steven L. Wood
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Margaret A. Knowles
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Douglas Thompson
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Peter J. Selby
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Rosamonde E. Banks
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

S. L. Wood, M. A. Knowles and R. E. Banks researched data for the article. S. L. Wood wrote the article. All authors made a substantial contribution to the discussion of content and reviewed the manuscript before submission.

Corresponding author

Correspondence to Steven L. Wood.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Table 1

Non-proteomic studies to discover biomarkers of prostate cancer (DOC 37 kb)

Supplementary Table 2

Non-proteomic studies to discover biomarkers of bladder cancer (DOC 46 kb)

Supplementary Table 3

Non-proteomic-studies to discover biomarkers of renal cell carcinoma (RCC) (DOC 26 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Wood, S., Knowles, M., Thompson, D. et al. Proteomic studies of urinary biomarkers for prostate, bladder and kidney cancers. Nat Rev Urol 10, 206–218 (2013). https://doi.org/10.1038/nrurol.2013.24

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nrurol.2013.24

This article is cited by

Search

Advanced 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