Skip to main content

Prostate cancer and the role of biomarkers

Abdominal Radiology volume 45, pages 2120–2132 (2020)Cite this article

Abstract

Purpose

To review available prostate cancer biomarkers and their performance in a clinical order, from prostate cancer detection, to treatment of localized and advanced disease.

Methods

We used an electronic literature search of the PubMed database using the key words “prostate biomarkers,” “genomic markers,” and “prostate cancer screening,” as well as specific biomarkers, until March 2019.

Results

Prostate-specific antigen (PSA) lacks sensitivity for prostate cancer detection, and PSA derivatives have slightly improved its specificity, but have not resolved the limitations of PSA screening. Prostate cancer biomarkers have emerged as an ancillary tool to guide the clinical decision-making in different clinical scenarios. Urine-based tests can identify patients who may benefit from a prostate biopsy, and issue-based markers are helpful in guiding the decision regarding a second biopsy, stratifying patient with newly diagnosed prostate cancer to active surveillance or treatment, and identifying patients who may benefit from adjuvant treatment after surgery.

Conclusions

New biomarkers have improved risk stratification in diagnosing and treating prostate cancer. Many of these markers are still considered experimental, and their efficacy and cost utility have not been determined.

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

Access options

Buy single article

Instant access to the full article PDF.

43,34 €

Price includes VAT (Finland)
Tax calculation will be finalised during checkout.

Fig. 1

References

  1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2019. CA Cancer J Clin. 2019;69(1):7-34. https://doi.org/10.3322/caac.21551

    Article  PubMed  Google Scholar 

  2. Horner MJ. SEER Cancer Statistics Review 1975-2006 National Cancer Institute SEER Cancer Statistics Review 1975-2006 National Cancer Institute. Cancer. 2011.

  3. Bell KJL, Del Mar C, Wright G, Dickinson J, Glasziou P. Prevalence of incidental prostate cancer: A systematic review of autopsy studies. Int J Cancer. 2015;137(7):1749-1757. https://doi.org/10.1002/ijc.29538

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  4. Kessler B, Albertsen P. The natural history of prostate cancer. Urol Clin. 2003;30(2):219-226. https://doi.org/10.1016/s0094-0143(02)00182-9

    Article  Google Scholar 

  5. Howlader N, Noone AM, Krapcho M, Miller D, Bishop K, Altekruse SF, Kosary CL, Yu M, Ruhl J, Tatalovich Z, Mariotto A, Lewis DR, Chen HS, Feuer EJ CK (eds). SEER Cancer Statistics Review 1975-2013 National Cancer Institute SEER Cancer Statistics Review 1975-2013 National Cancer Institute. SEER Cancer Stat Rev 1975-2013, Natl Cancer Institute Bethesda, MD, http//seer.cancer.gov/csr/1975_2013/, based Novemb 2015 SEER data submission, posted to SEER web site, April 2016. 2016:1992-2013. doi:https://seer.cancer.gov/csr/1975_2014/

  6. Newcomer LM, Stanford JL, Blumenstein BA, Brawer MK. Temporal trends in rates of prostate cancer: Declining incidence of advanced stage disease, 1974 to 1994. J Urol. 1997;158(4):1427-1430. https://doi.org/10.1016/s0022-5347(01)64231-9

    CAS  Article  PubMed  Google Scholar 

  7. Thompson IM, Pauler DK, Goodman PJ, et al. Prevalence of Prostate Cancer among Men with a Prostate-Specific Antigen Level ≤ 4.0 ng per Milliliter. N Engl J Med. 2004;350(22):2239-2246. https://doi.org/10.1056/nejmoa031918

  8. Moyer V U. Clinical Guideline OF AND. 2012;157(2).

  9. Kramer BS, Prorok PC, Chia D, et al. Mortality Results from a Randomized Prostate-Cancer Screening Trial. N Engl J Med. 2009;360(13):1310-1319. https://doi.org/10.1056/nejmoa0810696

    Article  PubMed  PubMed Central  Google Scholar 

  10. Aus G, Hugosson J, Berenguer A, et al. Screening and Prostate-Cancer Mortality in a Randomized European Study. N Engl J Med. 2009;360(13):1320-1328. https://doi.org/10.1056/nejmoa0810084

    Article  PubMed  Google Scholar 

  11. Brajtbord JS, Leapman MS, Cooperberg MR. The CAPRA Score at 10 Years: Contemporary Perspectives and Analysis of Supporting Studies. Eur Urol. 2017;71(5):705-709. https://doi.org/10.1016/j.eururo.2016.08.065

    Article  PubMed  Google Scholar 

  12. Catalona WJ, Hudson MA, Scardino PT, et al. Selection of Optimal Prostate Specific Antigen Cutoffs for Early Detection of Prostate Cancer: Receiver Operating Characteristic Curves. J Urol. 1994;152(6):2037-2042. https://doi.org/10.1016/s0022-5347(17)32300-5

    Article  PubMed  Google Scholar 

  13. Lilja H, Cronin AM, Dahlin A, et al. Prediction of significant prostate cancer diagnosed 20 to 30 years later with a single measure of prostate-specific antigen at or before age 50. Cancer. 2011;117(6):1210-1219. https://doi.org/10.1002/cncr.25568

    Article  PubMed  Google Scholar 

  14. Loeb S, Roehl KA, Antenor JA V., Catalona WJ, Suarez BK, Nadler RB. Baseline prostate-specific antigen compared with median prostate-specific antigen for age group as predictor of prostate cancer risk in men younger than 60 years old. Urology. 2006;67(2):316-320. https://doi.org/10.1016/j.urology.2005.08.040

    Article  PubMed  Google Scholar 

  15. POLASCIK TJ, OESTERLING JE, PARTIN AW. PROSTATE SPECIFIC ANTIGEN: A DECADE OF DISCOVERY-WHAT WE HAVE LEARNED AND WHERE WE ARE GOING. J Urol. 1999;162(2):293-306. https://doi.org/10.1016/s0022-5347(05)68543-6

    CAS  Article  PubMed  Google Scholar 

  16. Vessella RL, Lange PH, Partin AW, et al. Probability of prostate cancer detection based on results of a multicenter study using the AxSYM free PSA and total PSA assays. Urology. 2000;55(6):909-914. https://doi.org/10.1016/s0090-4295(00)00461-1

    CAS  Article  PubMed  Google Scholar 

  17. Partin A, Brawer M, Subong E, et al. Prospective evaluation of percent free-PSA and complexed-PSA for early detection of prostate cancer. Prostate Cancer Prostatic Dis. 1998;1(4):197-203. https://doi.org/10.1038/sj.pcan.4500232

    CAS  Article  PubMed  Google Scholar 

  18. Catalona WJ, Partin AW, Slawin KM, et al. Use of the Percentage of Free Prostate-Specific Antigen to Enhance Differentiation of Prostate Cancer From Benign Prostatic Disease. JAMA. 1998;279(19):1542. https://doi.org/10.1001/jama.279.19.1542

    CAS  Article  PubMed  Google Scholar 

  19. Auprich M, Augustin H, Budäus L, et al. A comparative performance analysis of total prostate‐specific antigen, percentage free prostate‐specific antigen, prostate‐specific antigen velocity and urinary prostate cancer gene 3 in the first, second and third repeat prostate biopsy. BJU Int. 2012;109(11):1627-1635. https://doi.org/10.1111/j.1464-410x.2011.10584.x

    CAS  Article  PubMed  Google Scholar 

  20. Shariat SF, Abdel-Aziz KF, Roehrborn CG, Lotan Y. Pre-operative Percent Free PSA Predicts Clinical Outcomes in Patients Treated with Radical Prostatectomy with Total PSA Levels below 10 ng/ml. Eur Urol. 2006;49(2):293-302. https://doi.org/10.1016/j.eururo.2005.10.027

    Article  PubMed  Google Scholar 

  21. Morote J, Encabo G, de Torres IM. Use of Percent Free Prostate–Specific Antigen as a Predictor of the Pathological Features of Clinically Localized Prostate Cancer. Eur Urol. 2000;38(2):225-229. https://doi.org/10.1159/000020283

    CAS  Article  PubMed  Google Scholar 

  22. Nordström T, Akre O, Aly M, Grönberg H, Eklund M. Prostate-specific antigen (PSA) density in the diagnostic algorithm of prostate cancer. Prostate Cancer Prostatic Dis. 2018;21(1):57-63. https://doi.org/10.1038/s41391-017-0024-7

    Article  PubMed  Google Scholar 

  23. Presti JC, Hovey R, Carroll PR, Shinohara K. Prospective evaluation of prostate specific antigen and prostate specific antigen density in the detection of nonpalpable and stage T1C carcinoma of the prostate. J Urol. 1996;156(5):1685-1690. http://www.ncbi.nlm.nih.gov/pubmed/8863571. Accessed April 1, 2019.

  24. Catalona WJ, Southwick PC, Slawin KM, et al. Comparison of percent free PSA, PSA density, and age-specific PSA cutoffs for prostate cancer detection and staging. Urology. 2000;56(2):255-260. https://doi.org/10.1016/s0090-4295(00)00637-3

    CAS  Article  PubMed  Google Scholar 

  25. Kundu SD, Roehl KA, Yu X, Antenor JA V., Suarez BK, Catalona WJ. Prostate Specific Antigen Density Correlates With Features of Prostate Cancer Aggressiveness. J Urol. 2007;177(2):505-509. https://doi.org/10.1016/j.juro.2006.09.039

    CAS  Article  PubMed  Google Scholar 

  26. Distler FA, Radtke JP, Bonekamp D, et al. The Value of PSA Density in Combination with PI-RADSTM for the Accuracy of Prostate Cancer Prediction. J Urol. 2017;198(3):575-582. https://doi.org/10.1016/j.juro.2017.03.130

    Article  PubMed  Google Scholar 

  27. Washington SL, Baskin AL, Ameli N, et al. MRI-based prostate specific antigen density predicts Gleason score upgrade in an active surveillance cohort. J Clin Oncol. 2019;37(7_suppl):107-107. https://doi.org/10.1200/jco.2019.37.7_suppl.107

  28. Loeb S, Roehl KA, Catalona WJ, Nadler RB. Is the utility of prostate-specific antigen velocity for prostate cancer detection affected by age? BJU Int. 2008;101(7):817-821. https://doi.org/10.1111/j.1464-410x.2008.07501.x

    CAS  Article  PubMed  Google Scholar 

  29. D’Amico A V., Chen M-H, Roehl KA, Catalona WJ. Preoperative PSA Velocity and the Risk of Death from Prostate Cancer after Radical Prostatectomy. N Engl J Med. 2004;351(2):125-135. https://doi.org/10.1056/nejmoa032975

    Article  PubMed  Google Scholar 

  30. Schröder FH, Roobol MJ, van der Kwast TH, Kranse R, Bangma CH. Does PSA Velocity Predict Prostate Cancer in Pre-Screened Populations? Eur Urol. 2006;49(3):460-465. https://doi.org/10.1016/j.eururo.2005.12.026

    Article  PubMed  Google Scholar 

  31. Ulmert D, Serio AM, O’Brien MF, et al. Long-term prediction of prostate cancer: Prostate-specific antigen (PSA) velocity is predictive but does not improve the predictive accuracy of a single PSA measurement 15 years or more before cancer diagnosis in a large, representative, unscreened population. J Clin Oncol. 2008;26(6):835-841. https://doi.org/10.1200/jco.2007.13.1490

    Article  PubMed  Google Scholar 

  32. Thompson IM, Goodman PJ, Tangen CM, et al. The Influence of Finasteride on the Development of Prostate Cancer. N Engl J Med. 2003;349(3):215-224. https://doi.org/10.1056/nejmoa030660

    CAS  Article  PubMed  Google Scholar 

  33. 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):1650-1655. https://doi.org/10.1016/j.juro.2010.12.032

  34. 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. BJU Int. 2013;112(3):313-321. https://doi.org/10.1111/bju.12217

    CAS  Article  PubMed  Google Scholar 

  35. Lughezzani G, Lazzeri M, Haese A, et al. Multicenter European External Validation of a Prostate Health Index–based Nomogram for Predicting Prostate Cancer at Extended Biopsy. Eur Urol. 2014;66(5):906-912. https://doi.org/10.1016/j.eururo.2013.12.005

    CAS  Article  PubMed  Google Scholar 

  36. 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):255-261. https://doi.org/10.1158/1055-9965.epi-10-1003

    CAS  Article  PubMed  Google Scholar 

  37. Russo GI, Regis F, Castelli T, et al. A Systematic Review and Meta-analysis of the Diagnostic Accuracy of Prostate Health Index and 4-Kallikrein Panel Score in Predicting Overall and High-grade Prostate Cancer. Clin Genitourin Cancer. 2017;15(4):429-439.e1. https://doi.org/10.1016/j.clgc.2016.12.022

    Article  PubMed  Google Scholar 

  38. Nordström T, Vickers A, Assel M, Lilja H, Grönberg H, Eklund M. Comparison Between the Four-kallikrein Panel and Prostate Health Index for Predicting Prostate Cancer. Eur Urol. 2015;68(1):139-146. https://doi.org/10.1016/j.eururo.2014.08.010

    CAS  Article  PubMed  Google Scholar 

  39. Tomlins SA, Rhodes DR, Perner S, et al. Recurrent fusion of TMPRSS2 and ETS transcription factor genes in prostate cancer. Science. 2005;310(5748):644-648. https://doi.org/10.1126/science.1117679

    CAS  Article  PubMed  Google Scholar 

  40. Salami SS, Schmidt F, Laxman B, et al. Combining urinary detection of TMPRSS2:ERG and PCA3 with serum PSA to predict diagnosis of prostate cancer. Urol Oncol Semin Orig Investig. 2013;31(5):566-571. https://doi.org/10.1016/j.urolonc.2011.04.001

    CAS  Article  Google Scholar 

  41. Tomlins SA, Day JR, Lonigro RJ, et al. Urine TMPRSS2:ERG Plus PCA3 for Individualized Prostate Cancer Risk Assessment. Eur Urol. 2016;70(1):45-53. https://doi.org/10.1016/j.eururo.2015.04.039

    CAS  Article  PubMed  Google Scholar 

  42. Sanda MG, Feng Z, Howard DH, et al. Association Between Combined TMPRSS2:ERG and PCA3 RNA Urinary Testing and Detection of Aggressive Prostate Cancer. JAMA Oncol. 2017;3(8):1085-1093. https://doi.org/10.1001/jamaoncol.2017.0177

    Article  PubMed  PubMed Central  Google Scholar 

  43. Zhou CK, Young D, Yeboah ED, et al. TMPRSS2:ERG Gene Fusions in Prostate Cancer of West African Men and a Meta-Analysis of Racial Differences. Am J Epidemiol. 2017;186(12):1352-1361. https://doi.org/10.1093/aje/kwx235

    Article  PubMed  PubMed Central  Google Scholar 

  44. Leyten GHJM, Hessels D, Smit FP, et al. Identification of a candidate gene panel for the early diagnosis of prostate cancer. Clin Cancer Res. 2015;21(13):3061-3070. https://doi.org/10.1158/1078-0432.ccr-14-3334

    CAS  Article  PubMed  Google Scholar 

  45. Van Neste L, Hendriks RJ, Dijkstra S, et al. Detection of High-grade Prostate Cancer Using a Urinary Molecular Biomarker–Based Risk Score. Eur Urol. 2016;70(5):740-748. https://doi.org/10.1016/j.eururo.2016.04.012

    Article  PubMed  Google Scholar 

  46. Dijkstra S, Govers TM, Hendriks RJ, et al. Cost-effectiveness of a new urinary biomarker-based risk score compared to standard of care in prostate cancer diagnostics - a decision analytical model. BJU Int. 2017;120(5):659-665. https://doi.org/10.1111/bju.13861

    Article  PubMed  Google Scholar 

  47. Cochran JS, Bentink S, Skog J, et al. A molecular signature of PCA3 and ERG exosomal RNA from non-DRE urine is predictive of initial prostate biopsy result. Prostate Cancer Prostatic Dis. 2015;18(4):370-375. https://doi.org/10.1038/pcan.2015.40

    CAS  Article  PubMed  Google Scholar 

  48. Carroll P, Brown G, Belzer S, et al. A Novel Urine Exosome Gene Expression Assay to Predict High-grade Prostate Cancer at Initial Biopsy. JAMA Oncol. 2016;2(7):882. https://doi.org/10.1001/jamaoncol.2016.0097

    Article  PubMed  Google Scholar 

  49. Sathianathen NJ, Kuntz KM, Alarid-Escudero F, et al. Incorporating Biomarkers into the Primary Prostate Biopsy Setting: A Cost-Effectiveness Analysis. J Urol. 2018;200(6):1215-1220. https://doi.org/10.1016/j.juro.2018.06.016

    Article  PubMed  Google Scholar 

  50. Jones JS, Patel A, Schoenfield L, Rabets JC, Zippe CD, Magi-Galluzzi C. Saturation Technique Does Not Improve Cancer Detection as an Initial Prostate Biopsy Strategy. J Urol. 2006;175(2):485-488. https://doi.org/10.1016/s0022-5347(05)00211-9

    Article  PubMed  Google Scholar 

  51. Djavan B, Ravery V, Zlotta A, et al. Prospective evaluation of prostate cancer detected on biopsies 1, 2, 3 and 4: when should we stop? J Urol. 2001;166(5):1679-1683. http://www.ncbi.nlm.nih.gov/pubmed/11586201. Accessed March 31, 2019.

  52. van Oort I, Witjes JA, Kiemeney LA, et al. DD3PCA3-based Molecular Urine Analysis for the Diagnosis of Prostate Cancer. Eur Urol. 2003;44(1):8-16. https://doi.org/10.1016/s0302-2838(03)00201-x

    Article  PubMed  Google Scholar 

  53. Schalken JA, Jannink SA, Hanssen SLJ, et al. The Time-Resolved Fluorescence-Based PCA3 Test on Urinary Sediments after Digital Rectal Examination; a Dutch Multicenter Validation of the Diagnostic Performance. Clin Cancer Res. 2007;13(3):939-943. https://doi.org/10.1158/1078-0432.ccr-06-2679

    Article  PubMed  Google Scholar 

  54. André J, Paparel P, Devonec M, Vlaeminck-Guillem V, Ruffion A. Urinary Prostate Cancer 3 Test: Toward the Age of Reason? Urology. 2009;75(2):447-453. https://doi.org/10.1016/j.urology.2009.03.046

    Article  PubMed  Google Scholar 

  55. Cucchiara V, Cooperberg MR, Dall’Era M, et al. Genomic Markers in Prostate Cancer Decision Making. Eur Urol. 2018;73(4):572-582. https://doi.org/10.1016/j.eururo.2017.10.036

  56. Nicholson A, Mahon J, Boland A, et al. The clinical effectiveness and cost-effectiveness of the PROGENSA® prostate cancer antigen 3 assay and the Prostate Health Index in the diagnosis of prostate cancer: a systematic review and economic evaluation. Health Technol Assess (Rockv). 2015;19(87):1-192. https://doi.org/10.3310/hta19870

    Article  Google Scholar 

  57. 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):1110-1116. https://doi.org/10.1016/j.juro.2012.08.219

    Article  PubMed  Google Scholar 

  58. 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):1081-1087. https://doi.org/10.1016/j.juro.2014.04.013

    Article  PubMed  PubMed Central  Google Scholar 

  59. Van Neste L, Partin AW, Stewart GD, Epstein JI, Harrison DJ, Van Criekinge W. Risk score predicts high-grade prostate cancer in DNA-methylation positive, histopathologically negative biopsies. Prostate. 2016;76(12):1078-1087. https://doi.org/10.1002/pros.23191

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  60. Aubry WM, Lieberthal RD, Willis A, Bagley G, Willis SM, Layton AJ. Budget impact model: epigenetic assay can help avoid unnecessary repeated prostate biopsies and reduce healthcare spending. undefined. 2013. https://www.semanticscholar.org/paper/Budget-impact-model%3A-epigenetic-assay-can-help-and-Aubry-Lieberthal/dbba7a1f7538da276925d1613fb0103cff35e111. Accessed October 9, 2019.

  61. Klotz L, Zhang L, Lam A, Nam R, Mamedov A, Loblaw A. Clinical Results of Long-Term Follow-Up of a Large, Active Surveillance Cohort With Localized Prostate Cancer. J Clin Oncol. 2009;28:126-131. https://doi.org/10.1200/jco.2009.24.2180

    Article  PubMed  Google Scholar 

  62. 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(1):690. https://doi.org/10.1186/1471-2164-14-690

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  63. 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):550-560. https://doi.org/10.1016/j.eururo.2014.05.004

    Article  PubMed  Google Scholar 

  64. 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):123-131. https://doi.org/10.1016/j.eururo.2014.11.030

    Article  PubMed  Google Scholar 

  65. Albala D, Kemeter MJ, Febbo PG, et al. Health Economic Impact and Prospective Clinical Utility of Oncotype DX® Genomic Prostate Score. Rev Urol. 2016;18(3):123-132. https://doi.org/10.3909/riu0725

    Article  PubMed  PubMed Central  Google Scholar 

  66. Warf MB, Reid JE, Brown KL, Kimbrell H, Kolquist KA. Analytical Validation of a Cell Cycle Progression Signature Used as a Prognostic Marker in Prostate Cancer. J Mol Biomark Diagn. 2015;6(4):239. https://doi.org/10.4172/2155-9929.1000239

    CAS  Article  Google Scholar 

  67. 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):245-255. https://doi.org/10.1016/s1470-2045(10)70295-3

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  68. 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):1428-1434. https://doi.org/10.1200/jco.2012.46.4396

    CAS  Article  PubMed  Google Scholar 

  69. 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. 2013;86(5):848-853. https://doi.org/10.1016/j.ijrobp.2013.04.043

    Article  Google Scholar 

  70. Health Quality Ontario. Prolaris Cell Cycle Progression Test for Localized Prostate Cancer: A Health Technology Assessment. Ont Health Technol Assess Ser. 2017;17(6):1-75. http://www.ncbi.nlm.nih.gov/pubmed/28572867. Accessed October 9, 2019.

  71. Erho N, Crisan A, Vergara IA, et al. Discovery and validation of a prostate cancer genomic classifier that predicts early metastasis following radical prostatectomy. PLoS One. 2013;8(6):e66855. https://doi.org/10.1371/journal.pone.0066855

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  72. Spratt DE, Yousefi K, Deheshi S, et al. Individual Patient-Level Meta-Analysis of the Performance of the Decipher Genomic Classifier in High-Risk Men After Prostatectomy to Predict Development of Metastatic Disease. J Clin Oncol. 2017;35(18):1991-1998. https://doi.org/10.1200/jco.2016.70.2811

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  73. Taneja SS. Re: Impact of a Genomic Classifier of Metastatic Risk on Postprostatectomy Treatment Recommendations by Radiation Oncologists and Urologists. J Urol. 2016;195(5):1472-1472. https://doi.org/10.1016/j.juro.2016.02.023

    CAS  Article  PubMed  Google Scholar 

  74. Klein EA, Haddad Z, Yousefi K, et al. Decipher Genomic Classifier Measured on Prostate Biopsy Predicts Metastasis Risk. Urology. 2016;90:148-152. https://doi.org/10.1016/j.urology.2016.01.012

    Article  PubMed  Google Scholar 

  75. Lobo JM, Trifiletti DM, Sturz VN, et al. Cost-effectiveness of the Decipher Genomic Classifier to Guide Individualized Decisions for Early Radiation Therapy After Prostatectomy for Prostate Cancer. Clin Genitourin Cancer. 2017;15(3):e299-e309. https://doi.org/10.1016/j.clgc.2016.08.012

    Article  PubMed  Google Scholar 

  76. Le JD, Tan N, Shkolyar E, et al. Multifocality and Prostate Cancer Detection by Multiparametric Magnetic Resonance Imaging: Correlation with Whole-mount Histopathology. Eur Urol. 2015;67(3):569-576. https://doi.org/10.1016/j.eururo.2014.08.079

    Article  PubMed  Google Scholar 

  77. Li P, You S, Nguyen C, et al. Genes involved in prostate cancer progression determine MRI visibility. Theranostics. 2018;8(7):1752-1765. https://doi.org/10.7150/thno.23180

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  78. Leapman MS, Westphalen AC, Ameli N, et al. Association between a 17-gene genomic prostate score and multi-parametric prostate MRI in men with low and intermediate risk prostate cancer (PCa). PLoS One. 2017;12(10):1-13. https://doi.org/10.1371/journal.pone.0185535

    CAS  Article  Google Scholar 

  79. Salmasi A, Said J, Shindel AW, et al. A 17-Gene Genomic Prostate Score Assay Provides Independent Information on Adverse Pathology in the Setting of Combined Multiparametric Magnetic Resonance Imaging Fusion Targeted and Systematic Prostate Biopsy. J Urol. 2018;200(3):564-572. https://doi.org/10.1016/j.juro.2018.03.004

    Article  PubMed  Google Scholar 

Download references

Author information

Affiliations

  1. Department of Urology, Mayo Clinic, 5777 East Mayo Blvd, Phoenix, AZ, 85054, USA

    Amihay Nevo, Anojan Navaratnam & Paul Andrews

Authors
  1. Amihay Nevo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Anojan Navaratnam
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Paul Andrews
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Amihay Nevo.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Nevo, A., Navaratnam, A. & Andrews, P. Prostate cancer and the role of biomarkers. Abdom Radiol 45, 2120–2132 (2020). https://doi.org/10.1007/s00261-019-02305-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00261-019-02305-8

Keywords

  • Prostate cancer
  • Biomarkers
  • Prognosis