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Clinical Utility of Biomarkers in Localized Prostate Cancer

  • Genitourinary Cancers (DP Petrylak and JW Kim, Section Editors)
  • Published:
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Abstract

A new generation of prostate cancer (PCa) biomarkers has emerged, including diagnostic serum and urine markers aimed at refining the identification high-grade tumors and tissue-based gene expression assays offering prognostic and predictive clinical information. Such tests seek to improve treatment-related decisions at multiple decision points, including initial diagnosis and following initial primary therapy. In this review, we aim to contextualize the body of evidence surrounding these emerging tests, with attention on studies addressing clinical utility.

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References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2015. CA Cancer J Clin. 2015;65(1):5–29.

    Article  PubMed  Google Scholar 

  2. Cooperberg MR, Carroll PR. Trends in management for patients with localized prostate cancer, 1990-2013. JAMA. 2015;314(1):80–2.

    Article  CAS  PubMed  Google Scholar 

  3. Harvey P, Basuita A, Endersby D, Curtis B, Iacovidou A, Walker M. A systematic review of the diagnostic accuracy of prostate specific antigen. BMC Urol. 2009;9:14.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Wang SY, Cowan JE, Cary KC, Chan JM, Carroll PR, Cooperberg MR. Limited ability of existing nomograms to predict outcomes in men undergoing active surveillance for prostate cancer. BJU Int. 2014;114(6b):E18–24.

    Article  PubMed  Google Scholar 

  5. Bostrom PJ, Bjartell AS. Catto JW, et al. Eur Urol: Genomic predictors of outcome in prostate cancer; 2015.

    Google Scholar 

  6. McShane LM, Altman DG, Sauerbrei W, et al. Reporting recommendations for tumor marker prognostic studies. J Clin Oncol. 2005;23(36):9067–72.

    Article  PubMed  Google Scholar 

  7. Febbo PG, Ladanyi M, Aldape KD, et al. NCCN Task Force report: evaluating the clinical utility of tumor markers in oncology. J Natl Compr Canc Netw. 2011;9 Suppl 5:S1–32. quiz S33.

    PubMed  Google Scholar 

  8. Cooperberg MR, Broering JM, Carroll PR. Risk assessment for prostate cancer metastasis and mortality at the time of diagnosis. J Natl Cancer Inst. 2009;101(12):878–87.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Stephenson AJ, Scardino PT, Eastham JA, et al. Postoperative nomogram predicting the 10-year probability of prostate cancer recurrence after radical prostatectomy. J Clin Oncol. 2005;23(28):7005–12.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Vickers AJ, Elkin EB. Decision curve analysis: a novel method for evaluating prediction models. Med Decis Making. 2006;26(6):565–74.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Fitzgerald M, Saville BR, Lewis RJ. Decision curve analysis. JAMA. 2015;313(4):409–10.

    Article  CAS  PubMed  Google Scholar 

  12. Ng CF, Chiu PK, Lam NY, Lam HC, Lee KW, Hou SS. The Prostate Health Index in predicting initial prostate biopsy outcomes in Asian men with prostate-specific antigen levels of 4-10 ng/mL. Int Urol Nephrol. 2014;46(4):711–7.

    Article  CAS  PubMed  Google Scholar 

  13. Boegemann M, Stephan C, Cammann H, et al. The percentage of prostate-specific antigen (PSA) isoform [-2]proPSA and the Prostate Health Index improve the diagnostic accuracy for clinically relevant prostate cancer at initial and repeat biopsy compared with total PSA and percentage free PSA in men aged </=65 years. BJU Int. 2015

  14. Lazzeri M, Haese A, de la Taille A, et al. Serum isoform [-2]proPSA derivatives significantly improve prediction of prostate cancer at initial biopsy in a total PSA range of 2-10 ng/ml: a multicentric European study. Eur Urol. 2013;63(6):986–94.

    Article  CAS  PubMed  Google Scholar 

  15. de la Calle C, Patil D, Wei JT, et al. Multicenter evaluation of the prostate health index to detect aggressive prostate cancer in biopsy naive men. J Urol. 2015;194(1):65–72.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Catalona WJ, Partin AW, Sanda MG, et al. A multicenter study of [-2]pro-prostate specific antigen combined with prostate specific antigen and free prostate specific antigen for prostate cancer detection in the 2.0 to 10.0 ng/ml prostate specific antigen range. J Urol. 2011;185(5):1650–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Wang W, Wang M, Wang L, Adams TS, Tian Y, Xu J. Diagnostic ability of %p2PSA and prostate health index for aggressive prostate cancer: a meta-analysis. Sci Rep. 2014;4:5012.

    CAS  PubMed  Google Scholar 

  18. Fossati N, Buffi NM, Haese A, et al. Preoperative prostate-specific antigen isoform p2PSA and its derivatives, %p2PSA and Prostate Health Index, predict pathologic outcomes in patients undergoing radical prostatectomy for prostate cancer: results from a Multicentric European Prospective Study. Eur Urol. 2015;68(1):132–8.

    Article  CAS  PubMed  Google Scholar 

  19. Vickers AJ, Cronin AM, Aus G, et al. A panel of kallikrein markers can reduce unnecessary biopsy for prostate cancer: data from the European Randomized Study of Prostate Cancer Screening in Goteborg, Sweden. BMC Med. 2008;6:19.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Benchikh A, Savage C, Cronin A, et al. A panel of kallikrein markers can predict outcome of prostate biopsy following clinical work-up: an independent validation study from the European Randomized Study of Prostate Cancer screening, France. BMC Cancer. 2010;10:635.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Vickers AJ, Cronin AM, Roobol MJ, et al. A four-kallikrein panel predicts prostate cancer in men with recent screening: data from the European Randomized Study of Screening for Prostate Cancer, Rotterdam. Clin Cancer Res. 2010;16(12):3232–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Vickers AJ, Cronin AM, Aus G, et al. Impact of recent screening on predicting the outcome of prostate cancer biopsy in men with elevated prostate-specific antigen: data from the European Randomized Study of Prostate Cancer Screening in Gothenburg, Sweden. Cancer. 2010;116(11):2612–20.

    PubMed  PubMed Central  Google Scholar 

  23. Vickers A, Cronin A, Roobol M, et al. Reducing unnecessary biopsy during prostate cancer screening using a four-kallikrein panel: an independent replication. J Clin Oncol. 2010;28(15):2493–8.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Parekh DJ, Punnen S, Sjoberg DD, et al. A multi-institutional prospective trial in the USA confirms that the 4Kscore accurately identifies men with high-grade prostate cancer. Eur Urol. 2015;68(3):464–70. Multi-institutional U.S. validation study addressing utility of the 4Kscore assay in detection of clinically significant PCa, as well as comparison with Prostate Cancer Prevention Trial Risk Calculator.

    Article  PubMed  Google Scholar 

  25. Nordstrom T, Vickers A, Assel M, Lilja H, Gronberg H, Eklund M. Comparison between the four-kallikrein panel and Prostate Health Index for predicting prostate cancer. Eur Urol. 2015;68(1):139–46. Direct comparison of four kallikrein panel and prostate health index for the prediction of prostate cancer at biopsy.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Trock BJ, Brotzman MJ, Mangold LA, et al. Evaluation of GSTP1 and APC methylation as indicators for repeat biopsy in a high-risk cohort of men with negative initial prostate biopsies. BJU Int. 2012;110(1):56–62.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Van Neste L, Herman JG, Otto G, Bigley JW, Epstein JI, Van Criekinge W. The epigenetic promise for prostate cancer diagnosis. Prostate. 2012;72(11):1248–61.

    Article  PubMed  Google Scholar 

  28. Stewart GD, Van Neste L, Delvenne P, et al. Clinical utility of an epigenetic assay to detect occult prostate cancer in histopathologically negative biopsies: results of the MATLOC study. J Urol. 2013;189(3):1110–6.

    Article  PubMed  Google Scholar 

  29. Partin AW, Van Neste L, Klein EA, et al. Clinical validation of an epigenetic assay to predict negative histopathological results in repeat prostate biopsies. J Urol. 2014;192(4):1081–7.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Wojno KJ, Costa FJ, Cornell RJ, et al. Reduced rate of repeated prostate biopsies observed in ConfirmMDx Clinical Utility Field Study. Am Health Drug Benefits. 2014;7(3):129–34.

    PubMed  PubMed Central  Google Scholar 

  31. Cuzick J, Swanson GP, Fisher G, et al. Prognostic value of an RNA expression signature derived from cell cycle proliferation genes in patients with prostate cancer: a retrospective study. Lancet Oncol. 2011;12(3):245–55.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Freedland SJ, Gerber L, Reid J, et al. Prognostic utility of cell cycle progression score in men with prostate cancer after primary external beam radiation therapy. Int J Radiat Oncol Biol Phys. 2013;86(5):848–53.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Bishoff JT, Freedland SJ, Gerber L, et al. Prognostic utility of the cell cycle progression score generated from biopsy in men treated with prostatectomy. J Urol. 2014;192(2):409–14.

    Article  PubMed  Google Scholar 

  34. Cuzick J, Stone S, Fisher G, et al. Validation of an RNA cell cycle progression score for predicting death from prostate cancer in a conservatively managed needle biopsy cohort. Br J Cancer. 2015;113(3):382–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Cooperberg MR, Simko JP, Cowan JE, et al. Validation of a cell-cycle progression gene panel to improve risk stratification in a contemporary prostatectomy cohort. J Clin Oncol. 2013;31(11):1428–34. Validation study of cell-cycle progression assay for risk stratification among post-prostatectomy cohort. Estimation of clinical utility compared with clinical risk stratification models.

    Article  CAS  PubMed  Google Scholar 

  36. Crawford ED, Scholz MC, Kar AJ, et al. Cell cycle progression score and treatment decisions in prostate cancer: results from an ongoing registry. Curr Med Res Opin. 2014;30(6):1025–31.

    Article  PubMed  Google Scholar 

  37. Shore N, Concepcion R, Saltzstein D, et al. Clinical utility of a biopsy-based cell cycle gene expression assay in localized prostate cancer. Curr Med Res Opin. 2014;30(4):547–53.

    Article  PubMed  Google Scholar 

  38. Knezevic D, Goddard AD, Natraj N, et al. Analytical validation of the Oncotype DX prostate cancer assay—a clinical RT-PCR assay optimized for prostate needle biopsies. BMC Genomics. 2013;14:690.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Klein EA, Cooperberg MR, Magi-Galluzzi C, et al. A 17-gene assay to predict prostate cancer aggressiveness in the context of Gleason grade heterogeneity, tumor multifocality, and biopsy undersampling. Eur Urol. 2014;66(3):550–60.

    Article  PubMed  Google Scholar 

  40. Cullen J, Rosner IL, Brand TC, et al. A biopsy-based 17-gene genomic prostate score predicts recurrence after radical prostatectomy and adverse surgical pathology in a racially diverse population of men with clinically low- and intermediate-risk prostate cancer. Eur Urol. 2015;68(1):123–31.

    Article  PubMed  Google Scholar 

  41. Nakagawa T, Kollmeyer TM, Morlan BW, et al. A tissue biomarker panel predicting systemic progression after PSA recurrence post-definitive prostate cancer therapy. PLoS ONE. 2008;3(5):e2318.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Karnes RJ, Bergstralh EJ, Davicioni E, et al. Validation of a genomic classifier that predicts metastasis following radical prostatectomy in an at risk patient population. J Urol. 2013;190(6):2047–53.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Cooperberg MR, Davicioni E, Crisan A, Jenkins RB, Ghadessi M, Karnes RJ. Combined value of validated clinical and genomic risk stratification tools for predicting prostate cancer mortality in a high-risk prostatectomy cohort. Eur Urol. 2015;67(2):326–33.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Den RB, Feng FY, Showalter TN, et al. Genomic prostate cancer classifier predicts biochemical failure and metastases in patients after postoperative radiation therapy. Int J Radiat Oncol Biol Phys. 2014;89(5):1038–46.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Den RB, Yousefi K, Trabulsi EJ, et al. Genomic classifier identifies men with adverse pathology after radical prostatectomy who benefit from adjuvant radiation therapy. J Clin Oncol. 2015;33(8):944–51. Use of 22-feature genomic classifier to add prognostic information in the timing of post-operative radiotherapy following radical prostatectomy.

    Article  PubMed  Google Scholar 

  46. Le BV, Griffin CR, Loeb S, et al. [-2]Proenzyme prostate specific antigen is more accurate than total and free prostate specific antigen in differentiating prostate cancer from benign disease in a prospective prostate cancer screening study. J Urol. 2010;183(4):1355–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Jansen FH, van Schaik RH, Kurstjens J, et al. Prostate-specific antigen (PSA) isoform p2PSA in combination with total PSA and free PSA improves diagnostic accuracy in prostate cancer detection. Eur Urol. 2010;57(6):921–7.

    Article  CAS  PubMed  Google Scholar 

  48. Loeb S, Sokoll LJ, Broyles DL, et al. Prospective multicenter evaluation of the Beckman Coulter Prostate Health Index using WHO calibration. J Urol. 2013;189(5):1702–6.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Guazzoni G, Nava L, Lazzeri M, et al. Prostate-specific antigen (PSA) isoform p2PSA significantly improves the prediction of prostate cancer at initial extended prostate biopsies in patients with total PSA between 2.0 and 10 ng/ml: results of a prospective study in a clinical setting. Eur Urol. 2011;60(2):214–22.

    Article  CAS  PubMed  Google Scholar 

  50. Lazzeri M, Briganti A, Scattoni V, et al. Serum index test %[-2]proPSA and Prostate Health Index are more accurate than prostate specific antigen and %fPSA in predicting a positive repeat prostate biopsy. J Urol. 2012;188(4):1137–43.

    Article  CAS  PubMed  Google Scholar 

  51. Lazzeri M, Haese A, Abrate A, et al. Clinical performance of serum prostate-specific antigen isoform [-2]proPSA (p2PSA) and its derivatives, %p2PSA and the prostate health index (PHI), in men with a family history of prostate cancer: results from a multicentre European study, the PROMEtheuS project. BJU Int. 2013;112(3):313–21.

    Article  CAS  PubMed  Google Scholar 

  52. Stephan C, Vincendeau S, Houlgatte A, Cammann H, Jung K, Semjonow A. Multicenter evaluation of [-2]proprostate-specific antigen and the prostate health index for detecting prostate cancer. Clin Chem. 2013;59(1):306–14.

    Article  CAS  PubMed  Google Scholar 

  53. Loeb S, Sanda MG, Broyles DL, et al. The prostate health index selectively identifies clinically significant prostate cancer. J Urol. 2015;193(4):1163–9.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Fossati N, Lazzeri M, Haese A, et al. Clinical performance of serum isoform [-2]proPSA (p2PSA), and its derivatives %p2PSA and the Prostate Health Index, in men aged <60 years: results from a multicentric European study. BJU Int. 2015;115(6):913–20.

    Article  CAS  PubMed  Google Scholar 

  55. Braun K, Sjoberg DD, Vickers AJ, Lilja H, Bjartell AS. A four-kallikrein panel predicts high-grade cancer on biopsy: independent validation in a community cohort. Eur Urol. 2016;69(3):505–11. doi: 10.1016/j.eururo.2015.04.028

  56. Gupta A, Roobol MJ, Savage CJ, et al. A four-kallikrein panel for the prediction of repeat prostate biopsy: data from the European Randomized Study of Prostate Cancer screening in Rotterdam, Netherlands. Br J Cancer. 2010;103(5):708–14.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Carlsson S, Maschino A, Schroder F, et al. Predictive value of four kallikrein markers for pathologically insignificant compared with aggressive prostate cancer in radical prostatectomy specimens: results from the European Randomized Study of Screening for Prostate Cancer section Rotterdam. Eur Urol. 2013;64(5):693–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Vickers AJ, Gupta A, Savage CJ, et al. A panel of kallikrein marker predicts prostate cancer in a large, population-based cohort followed for 15 years without screening. Cancer Epidemiol Biomarkers Prev. 2011;20(2):255–61.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Bryant RJ, Sjoberg DD, Vickers AJ, et al. Predicting high-grade cancer at ten-core prostate biopsy using four kallikrein markers measured in blood in the ProtecT study. J Natl Cancer Inst. 2015;107:7.

    Article  Google Scholar 

  60. Cuzick J, Berney DM, Fisher G, et al. Prognostic value of a cell cycle progression signature for prostate cancer death in a conservatively managed needle biopsy cohort. Br J Cancer. 2012;106(6):1095–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Ross AE, Feng FY, Ghadessi M, et al. A genomic classifier predicting metastatic disease progression in men with biochemical recurrence after prostatectomy. Prostate Cancer Prostatic Dis. 2014;17(1):64–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Klein EA, Yousefi K, Haddad Z, et al. A genomic classifier improves prediction of metastatic disease within 5 years after surgery in node-negative high-risk prostate cancer patients managed by radical prostatectomy without adjuvant therapy. Eur Urol. 2015;67(4):778–86.

    Article  PubMed  Google Scholar 

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Authors and Affiliations

  1. Department of Urology, Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA, USA

    Michael S. Leapman, Hao G. Nguyen & Matthew R. Cooperberg

  2. Department of Epidemiology and Biostatistics, Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA, USA

    Matthew R. Cooperberg

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  1. Michael S. Leapman
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  2. Hao G. Nguyen
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  3. Matthew R. Cooperberg
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Correspondence to Michael S. Leapman.

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Conflict of Interest

Michael S. Leapman declares that he has no conflict of interest.

Hao G. Nguyen declares that he has no conflict of interest.

Matthew R. Cooperberg has received financial support through institutional grants from Genomic Health, GenomeDx, and Myriad Genetics and has received compensation from Myriad Genetics, Janssen, Dendreon, AbbVie, and Astellas for service as a consultant.

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This article does not contain any studies with human or animal subjects performed by any of the authors.

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This article is part of the Topical Collection on Genitourinary Cancers

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Leapman, M.S., Nguyen, H.G. & Cooperberg, M.R. Clinical Utility of Biomarkers in Localized Prostate Cancer. Curr Oncol Rep 18, 30 (2016). https://doi.org/10.1007/s11912-016-0513-1

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