Skip to main content
SpringerLink
Log in

Biomarkers of Potential Therapeutic Value

  • Chapter
  • First Online:
Prostate Cancer: A Comprehensive Perspective

  • 2964 Accesses

Abstract

Prostate cancer is shown to have a biologically heterogeneous nature, and the prognosis of patients after a diagnosis of this disease is extremely variable. Accordingly, despite the widespread use of the prostate-specific antigen test, it would be absolutely necessary to identify molecular biomarkers for exactly predicting the clinical course of this disease in an individual patient. Based on recent advance in characterizing molecular mechanism mediating progression of prostate cancer, intensive studies have been performed for identifying novel biomarkers for prostate cancer using newly developed attractive approaches, including microarray techniques and proteomic/metabolic profiling analyses. To date, there have been a number of candidate biological markers discovered that would be likely to be associated with cell-cycle regulation, apoptosis, signal transduction, cell adhesion, angiogenesis, and other pathophysiological functions. Then, the relevance of these candidate markers have been validated in clinical setting, and some of them showed promising outcomes. Furthermore, the integration of selected biomarkers with conventional clinicopathological variables has been reported to produce predictive models showing outcomes superior to standard predictive system, like a nomogram. Collectively, these findings suggest that despite several limitations to be overcome prior to the introduction of these biomarkers into clinical practice of prostate cancer, once strictly evaluated, such biomarkers may help provide variable information on clinical decision-making during treatment of patients with prostate cancer.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 229.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Jemal A, Siegel R, Xu J, Ward E. Cancer statistics, 2010. CA Cancer J Clin. 2010;60:277–300.

    Article  PubMed  Google Scholar 

  2. McDavid K, Lee J, Fulton JP, Tonita J, et al. Prostate cancer incidence and mortality rates and trends in the United States and Canada. Public Health Rep. 2004;119:174–86.

    PubMed  Google Scholar 

  3. Partin AW, Mangold LA, Lamm DM, et al. Contemporary update of prostate cancer staging nomograms (Partin tables) for the new millennium. Urology. 2001;58:843–8.

    Article  PubMed  CAS  Google Scholar 

  4. Kattan MW, Marasco J. What is a real nomogram? Semin Oncol. 2010;37:23–6.

    Article  PubMed  Google Scholar 

  5. Dutt SS, Gao AC. Molecular mechanisms of castration-resistant prostate cancer progression. Future Oncol. 2009;5:1403–13.

    Article  PubMed  CAS  Google Scholar 

  6. Clarke NW, Hart CA, Brown MD MD. Molecular mechanisms of metastasis in prostate cancer. Asian J Androl. 2009;11:57–67.

    Article  PubMed  CAS  Google Scholar 

  7. Shariat SF, Canto EI, Kattan MW, et al. Beyond prostate-specific antigen: new serologic biomarkers for improved diagnosis and management of prostate cancer. Rev Urol. 2004;6:58–72.

    PubMed  Google Scholar 

  8. Etzioni R, Penson DF, Legler JM, et al. Overdiagnosis due to prostate-specific antigen screening: lessons from U.S. prostate cancer incidence trends. J Natl Cancer Inst. 2002;94:981–90.

    Article  PubMed  Google Scholar 

  9. Makarov DV, Loeb S, Getzenberg RH, et al. Biomarkers for prostate cancer. Annu Rev Med. 2009;60:139–51.

    Article  PubMed  CAS  Google Scholar 

  10. Leman ES, Getzenberg RH. Biomarkers for prostate cancer. J Cell Biochem. 2009;108:3–9.

    Article  PubMed  CAS  Google Scholar 

  11. Gretzer MB, Partin AW. PSA markers in prostate cancer detection. Urol Clin North Am. 2003;30:677–86.

    Article  PubMed  Google Scholar 

  12. Schröder FH. Review of diagnostic markers for prostate cancer. Recent Results Cancer Res. 2009;181:173–82.

    Article  PubMed  Google Scholar 

  13. Charrier JP, Tournel C, Michel S, et al. Differential diagnosis of prostate cancer and benign prostate hyperplasia using two-dimensional electrophoresis. Electrophoresis. 2001;22:1861–6.

    Article  PubMed  CAS  Google Scholar 

  14. Stamey TA, Johnstone IM, McNeal JE, et al. Preoperative serum prostate specific antigen levels between 2 and 22 ng/ml correlate poorly with post-radical prostatectomy cancer morphology: prostate specific antigen cure rates appear constant between 2 and 9 ng/ml. J Urol. 2002;167:103–11.

    Article  PubMed  CAS  Google Scholar 

  15. Djavan B, Eckersberger E, Finkelstein J, et al. Prostate-specific antigen testing and prostate cancer screening. Prim Care. 2010;37:441–59.

    Article  PubMed  Google Scholar 

  16. Steuber T, O’Brien MF, Lilja H. Serum markers for prostate cancer: a rational approach to the literature. Eur Urol. 2008;54:31–40.

    Article  PubMed  CAS  Google Scholar 

  17. Loeb S, Catalona WJ. Prostate-specific antigen in clinical practice. Cancer Lett. 2007;249:30–9.

    Article  PubMed  CAS  Google Scholar 

  18. Haese A, Graefen M, Huland H, et al. Prostate-specific antigen and related isoforms in the diagnosis and management of prostate cancer. Curr Urol Rep. 2004;5:231–40.

    Article  PubMed  Google Scholar 

  19. Southwick PC, Catalona WJ, Partin AW, et al. Prediction of post-radical prostatectomy pathological outcome for stage T1c prostate cancer with percent free prostate specific antigen: a prospective multicenter clinical trial. J Urol. 1999;162:1346–51.

    Article  PubMed  CAS  Google Scholar 

  20. Graefen M, Karakiewicz PI, Cagiannos I, et al. Percent free prostate specific antigen is not an independent predictor of organ confinement or prostate specific antigen recurrence in unscreened patients with localized prostate cancer treated with radical prostatectomy. J Urol. 2002;167:1306–9.

    Article  PubMed  Google Scholar 

  21. Jansen FH, Roobol M, Jenster G, et al. Screening for prostate cancer in 2008 II: the importance of molecular subforms of prostate-specific antigen and tissue kallikreins. Eur Urol. 2009;55:563–74.

    Article  PubMed  CAS  Google Scholar 

  22. Ulmert D, O’Brien MF, Bjartell AS, et al. Prostate kallikrein markers in diagnosis, risk stratification and prognosis. Nat Rev Urol. 2009;6:384–91.

    Article  PubMed  CAS  Google Scholar 

  23. Steuber T, Vickers AJ, Haese A, et al. Risk assessment for biochemical recurrence prior to radical prostatectomy: significant enhancement contributed by human glandular kallikrein 2 (hK2) and free prostate specific antigen (PSA) in men with moderate PSA-elevation in serum. Int J Cancer. 2006;118:1234–40.

    Article  PubMed  CAS  Google Scholar 

  24. Hessels D, Klein Gunnewiek JM, et al. DD3(PCA3)-based molecular urine analysis for the diagnosis of prostate cancer. Eur Urol. 2003;44:8–15.

    Article  PubMed  CAS  Google Scholar 

  25. Whitman EJ, Groskopf J, Ali A, et al. PCA3 score before radical prostatectomy predicts extracapsular extension and tumor volume. J Urol. 2008;180:1975–8.

    Article  PubMed  Google Scholar 

  26. Lopergolo A, Zaffaroni N. Biomolecular markers of outcome prediction in prostate cancer. Cancer. 2009;115:3058–67.

    Article  PubMed  CAS  Google Scholar 

  27. Karnak D, Xu L, et al. Chemosensitization of prostate cancer by modulating Bcl-2 family proteins. Curr Drug Targets. 2010;11:699–707.

    Article  PubMed  CAS  Google Scholar 

  28. Miyake H, Tolcher A, Gleave ME. Chemosensitization and delayed androgen-independent recurrence of prostate cancer with the use of antisense Bcl-2 oligodeoxynucleotides. J Natl Cancer Inst. 2000;92:34–41.

    Article  Google Scholar 

  29. Oxley JD, Winkler MH, Parry K, et al. p53 and bcl-2 immunohistochemistry in preoperative biopsies as predictors of biochemical recurrence after radical prostatectomy. BJU Int. 2002;89:27–32.

    Article  PubMed  CAS  Google Scholar 

  30. Pollack A, Cowen D, Troncoso P, et al. Molecular markers of outcome after radiotherapy in patients with prostate carcinoma: Ki-67, bcl-2, bax, and bcl-x. Cancer. 2003;97:1630–8.

    Article  PubMed  Google Scholar 

  31. So A, Hadaschik B, Sowery R, et al. The role of stress proteins in prostate cancer. Curr Genomics. 2007;8(4):252–61.

    Article  PubMed  CAS  Google Scholar 

  32. Miyake H, Hara I, Gleave ME. Antisense oligodeoxynucleotide therapy targeting clusterin gene for prostate cancer: Vancouver experience from discovery to clinic. Int J Urol. 2005;12:785–94.

    Article  PubMed  CAS  Google Scholar 

  33. Gleave M, Miyake H, Chi K. Beyond simple castration: targeting the molecular basis of treatment resistance in advanced prostate cancer. Cancer Chemother Pharmacol. 2005;56:47–57.

    Article  PubMed  Google Scholar 

  34. July LV, Akbari M, Zellweger T, et al. Clusterin expression is significantly enhanced in prostate cancer cells following androgen withdrawal therapy. Prostate. 2002;50:179–88.

    Article  PubMed  CAS  Google Scholar 

  35. Pins MR, Fiadjoe JE, Korley F, et al. Clusterin as a possible predictor for biochemical recurrence of prostate cancer following radical prostatectomy with intermediate Gleason scores: a preliminary report. Prostate Cancer Prostatic Dis. 2004;7:243–8.

    Article  PubMed  CAS  Google Scholar 

  36. Miyake H, Yamanaka K, Muramaki M, et al. Enhanced expression of the secreted form of clusterin following neoadjuvant hormonal therapy as a prognostic predictor in patients undergoing radical prostatectomy for prostate cancer. Oncol Rep. 2005;14:1371–5.

    PubMed  CAS  Google Scholar 

  37. Miyake H, Muramaki M, Kurahashi T, et al. Expression of clusterin in prostate cancer correlates with Gleason score but not with prognosis in patients undergoing radical prostatectomy without neoadjuvant hormonal therapy. Urology. 2006;68:609–14.

    Article  PubMed  Google Scholar 

  38. Miyake H, Muramaki M, Furukawa J, et al. Serum level of clusterin and its density in men with prostate cancer as novel biomarkers reflecting disease extension. Urology. 2010;75:454–9.

    Article  PubMed  Google Scholar 

  39. Ciocca DR, Calderwood SK. Heat shock proteins in cancer: diagnostic, prognostic, predictive, and treatment implications. Cell Stress Chaperones. 2005;10:86–103.

    Article  PubMed  CAS  Google Scholar 

  40. Miyake H, Muramaki M, Kurahashi T, et al. Enhanced expression of heat shock protein 27 following neoadjuvant hormonal therapy is associated with poor clinical outcome in patients undergoing radical prostatectomy for prostate cancer. Anticancer Res. 2006;26:1583–7.

    PubMed  CAS  Google Scholar 

  41. Rosenberg ME, Silkensen J. Clusterin: physiologic and pathophysiologic considerations. Int J Biochem Cell Biol. 1995;27:633–45.

    Article  PubMed  CAS  Google Scholar 

  42. Gleave M, Chi KN. Knock-down of the cytoprotective gene, clusterin, to enhance hormone and chemosensitivity in prostate and other cancers. Ann N Y Acad Sci. 2005;1058:1–15.

    Article  PubMed  CAS  Google Scholar 

  43. Arrigo AP. The cellular “networking” of mammalian Hsp27 and its functions in the control of protein folding, redox state and apoptosis. Adv Exp Med Biol. 2007;594:14–26.

    Article  PubMed  Google Scholar 

  44. Rocchi P, So A, Kojima S, et al. Heat shock protein 27 increases after androgen ablation and plays a cytoprotective role in hormone-refractory prostate cancer. Cancer Res. 2004;64:6595–602.

    Article  PubMed  CAS  Google Scholar 

  45. de Cárcer G, de Pérez Castro I, Malumbres M. Targeting cell cycle kinases for cancer therapy. Curr Med Chem. 2007;14:969–85.

    Article  PubMed  Google Scholar 

  46. Henshall SM, Quinn DI, Lee CS, et al. Overexpression of the cell cycle inhibitor p16INK4A in high-grade prostatic intraepithelial neoplasia predicts early relapse in prostate cancer patients. Clin Cancer Res. 2001;7:544–50.

    PubMed  CAS  Google Scholar 

  47. Cordon-Cardo C, Koff A, Drobnjak M, et al. Distinct altered patterns of p27KIP1 gene expression in benign prostatic hyperplasia and prostatic carcinoma. J Natl Cancer Inst. 1998;90:1284–91.

    Article  PubMed  CAS  Google Scholar 

  48. Freedland SJ, deGregorio F, Sacoolidge JC, et al. Preoperative p27 status is an independent predictor of prostate specific antigen failure following radical prostatectomy. J Urol. 2003;169:1325–30.

    Article  PubMed  CAS  Google Scholar 

  49. Rigaud J, Tiguert R, Decobert M, et al. Expression of p21 cell cycle protein is an independent predictor of response to salvage radiotherapy after radical prostatectomy. Prostate. 2004;58:269–76.

    Article  PubMed  CAS  Google Scholar 

  50. Furukawa J, Miyake H, Takenaka A, et al. Persistent expression of Aurora-A after neoadjuvant hormonal therapy as a predictor of a poor clinical outcome in patients undergoing radical prostatectomy for prostate cancer. BJU Int. 2007;100:310–4.

    Article  PubMed  CAS  Google Scholar 

  51. Miyake H, Muramaki M, Kurahashi T, et al. Expression of potential molecular markers in prostate cancer: correlation with clinicopathological outcomes in patients undergoing radical prostatectomy. Urol Oncol. 2010;28:145–51.

    Article  PubMed  CAS  Google Scholar 

  52. Warner SL, Bearss DJ, Han H, et al. Targeting aurora-2 kinase in cancer. Mol Cancer Ther. 2003;2:589–95.

    PubMed  CAS  Google Scholar 

  53. Faivre S, Djelloul S, Raymond E. New paradigms in anticancer therapy: targeting multiple signaling pathways with kinase inhibitors. Semin Oncol. 2006;33:407–20.

    Article  PubMed  CAS  Google Scholar 

  54. Wegiel B, Evans S, Hellsten R, et al. Molecular pathways in the progression of hormone-independent and metastatic prostate cancer. Curr Cancer Drug Targets. 2010;10:392–401.

    Article  PubMed  CAS  Google Scholar 

  55. McCall P, Gemmell LK, Mukherjee R, et al. Phosphorylation of the androgen receptor is associated with reduced survival in hormone-refractory prostate cancer patients. Br J Cancer. 2008;98: 1094–101.

    Article  PubMed  CAS  Google Scholar 

  56. Dai B, Kong YY, Ye DW, et al. Activation of the mammalian target of rapamycin signalling pathway in prostate cancer and its association with patient clinicopathological characteristics. BJU Int. 2009;104:1009–16.

    Article  PubMed  CAS  Google Scholar 

  57. Karam JA, Lotan Y, Roehrborn CG, et al. Caveolin-1 overexpression is associated with aggressive prostate cancer recurrence. Prostate. 2007;67:614–22.

    Article  PubMed  Google Scholar 

  58. Gravdal K, Halvorsen OJ, Haukaas SA, et al. A switch from E-cadherin to N-cadherin expression indicates epithelial to mesenchymal transition and is of strong and independent importance for the progress of prostate cancer. Clin Cancer Res. 2007;13:7003–11.

    Article  PubMed  CAS  Google Scholar 

  59. Strohmeyer D, Rössing C, Strauss F, et al. Tumor angiogenesis is associated with progression after radical prostatectomy in pT2/pT3 prostate cancer. Prostate. 2000;42:26–33.

    Article  PubMed  CAS  Google Scholar 

  60. Shariat SF, Andrews B, Kattan MW, et al. Plasma levels of interleukin-6 and its soluble receptor are associated with prostate cancer progression and metastasis. Urology. 2001;58:1008–15.

    Article  PubMed  CAS  Google Scholar 

  61. Gohji K, Fujimoto N, Hara I, et al. Serum matrix metalloproteinase-2 and its density in men with prostate cancer as a new predictor of disease extension. Int J Cancer. 1998;79:96–101.

    Article  PubMed  CAS  Google Scholar 

  62. Ellinger J, Haan K, Heukamp LC, et al. CpG island hypermethylation in cell-free serum DNA identifies patients with localized prostate cancer. Prostate. 2008;68:42–9.

    Article  PubMed  CAS  Google Scholar 

  63. Mantovani A, Savino B, Locati M, et al. The chemokine system in cancer biology and therapy. Cytokine Growth Factor Rev. 2010;21:27–39.

    Article  PubMed  CAS  Google Scholar 

  64. Ara T, Declerck YA. Interleukin-6 in bone metastasis and cancer progression. Eur J Cancer. 2010;46:1223–31.

    Article  PubMed  CAS  Google Scholar 

  65. Golub TR, Slonim DK, Tamayo P, et al. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science. 1999;286:531–7.

    Article  PubMed  CAS  Google Scholar 

  66. Sørensen KD, Ørntoft TF. Discovery of prostate cancer biomarkers by microarray gene expression profiling. Expert Rev Mol Diagn. 2010;10:49–64.

    Article  PubMed  Google Scholar 

  67. LaTulippe E, Satagopan J, Smith A, et al. Comprehensive gene expression analysis of prostate cancer reveals distinct transcriptional programs associated with metastatic disease. Cancer Res. 2002;62:4499–506.

    PubMed  CAS  Google Scholar 

  68. Ferdinandusse S, Denis S, IJlst L, et al. Subcellular localization and physiological role of α-methylacyl-CoA racemase. J Lipid Res. 2000;41:1890–6.

    PubMed  CAS  Google Scholar 

  69. Rubin MA, Bismar TA, Andrén O, et al. Decreased α-methylacyl CoA racemase expression in localized prostate cancer is associated with an increased rate of biochemical recurrence and cancer-specific death. Cancer Epidemiol Biomarkers Prev. 2005;14:1424–32.

    Article  PubMed  CAS  Google Scholar 

  70. Demichelis F, Fall K, Perner S, et al. TMPRSS2:ERG gene fusion associated with lethal prostate cancer in a watchful waiting cohort. Oncogene. 2007;26:4596–9.

    Article  PubMed  CAS  Google Scholar 

  71. Ploussard G, de la Taille A. Urine biomarkers in prostate cancer. Nat Rev Urol. 2010;7:101–9.

    Article  PubMed  CAS  Google Scholar 

  72. Jamaspishvili T, Kral M, Khomeriki I, et al. Urine markers in monitoring for prostate cancer. Prostate Cancer Prostatic Dis. 2010;13:12–9.

    Article  PubMed  CAS  Google Scholar 

  73. Russo AL, Jedlicka K, Wernick M, et al. Urine analysis and protein networking identify met as a marker of metastatic prostate cancer. Clin Cancer Res. 2009;15:4292–8.

    Article  PubMed  CAS  Google Scholar 

  74. Harden SV, Sanderson H, Goodman SN, et al. Quantitative GSTP1 methylation and the detection of prostate adenocarcinoma in sextant biopsies. J Natl Cancer Inst. 2003;95:1634–7.

    Article  PubMed  CAS  Google Scholar 

  75. Woodson K, O’Reilly KJ, Hanson JC, et al. The usefulness of the detection of GSTP1 methylation in urine as a biomarker in the diagnosis of prostate cancer. J Urol. 2008;179:508–11.

    Article  PubMed  CAS  Google Scholar 

  76. Sreekumar A, Poisson LM, Rajendiran TM, et al. Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression. Nature. 2009;457:910–4.

    Article  PubMed  CAS  Google Scholar 

  77. Kattan MW, Shariat SF, Andrews B, et al. The addition of interleukin-6 soluble receptor and transforming growth factor beta1 improves a preoperative nomogram for predicting biochemical progression in patients with clinically localized prostate cancer. J Clin Oncol. 2003;21:3573–9.

    Article  PubMed  CAS  Google Scholar 

  78. Shariat SF, Park S, Trinh QD, et al. Plasminogen activation inhibitor-1 improves the predictive accuracy of prostate cancer nomograms. J Urol. 2007;178:1229–36.

    Article  PubMed  CAS  Google Scholar 

  79. Stephenson AJ, Smith A, Kattan MW, et al. Integration of gene expression profiling and clinical variables to predict prostate carcinoma recurrence after radical prostatectomy. Cancer. 2005;104:290–8.

    Article  PubMed  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Division of Urology, Department of Surgery, Kobe University Graduate School of Medicine, 7-5-1 Kusunoki-cho, Chuo-ku, Kobe, Hyogo, 650-0017, Japan

    Hideaki Miyake M.D., Ph.D. & Masato Fujisawa M.D., Ph.D.

  2. Division of Urology, Department of Surgery, Faculty of Medicine, Tottori University, 36-1 Nishi-cho, Yonago, 683-8504, Japan

    Atsushi Takenaka M.D., Ph.D.

Authors
  1. Hideaki Miyake M.D., Ph.D.
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Atsushi Takenaka M.D., Ph.D.
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Masato Fujisawa M.D., Ph.D.
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hideaki Miyake M.D., Ph.D. .

Editor information

Editors and Affiliations

  1. New York Presbyterian Hospital, Brady Urologic Health Center, Weill Cornell Medical Center, East 68th Street 525, New York, 10021, New York, USA

    Ashutosh Tewari

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag London

About this chapter

Cite this chapter

Miyake, H., Takenaka, A., Fujisawa, M. (2013). Biomarkers of Potential Therapeutic Value. In: Tewari, A. (eds) Prostate Cancer: A Comprehensive Perspective. Springer, London. https://doi.org/10.1007/978-1-4471-2864-9_15

Download citation

  • DOI: https://doi.org/10.1007/978-1-4471-2864-9_15

  • Published:

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-2863-2

  • Online ISBN: 978-1-4471-2864-9

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics

Search

Navigation