Prostate cancer risk stratification based on conventional clinical and pathologic characteristics alone may misclassify a proportion of men at various stages of the disease process. Many gene-based assays have emerged in recent years that seek to improve the predictive accuracy in the prediagnostic and postdiagnostic settings. Following primary treatment failure, gene expression tests may offer improved stratification of individuals at risk for disease progression and inform refinements in the necessity of additional treatment. Unifying limitations among all novel gene-based tests are include clinical validation derived from historical cohorts and a dearth of empirical clinical effectiveness data.
Tissue-based gene expression tests have been developed to predict the occurrence of subsequent PCa events, including adverse characteristics, biochemical recurrence, metastatic progression, and PCa mortality.
Tissue-based gene expression tests have been developed to predict the occurrence of subsequent PCa events, including adverse characteristics, biochemical recurrence, metastatic progression, and PCa mortality.
On the heels of insights gained into PCa biology and technological advancements affording accessible, high throughput sequencing, assays have emerged that evaluate numerous junctures within the PCa disease process. Spanning the prediagnostic, initial detection and posttreatment settings, this expanding battery of risk-stratification tools seek to offer improved assessment of outcome and gain widespread implementation in clinical practice. In light of the novelty of such developments, the authors aim to critically review the current body of tools that have appeared in recent years and the details of their supporting evidence and offer a contextualization of the pipeline of emerging tests under development.
Most PCa detected worldwide are the result of biopsy undertaken in the setting of elevated PSA. Owing to the well-recognized deficiencies in specificity of PSA for the identification of clinically significant disease, a considerable number of individuals will undergo screening and biopsy to detect a single high-risk cancer. The development of accurate markers to better select those at greatest risk for harboring significant and actionable disease would, therefore, be impactful for men who may be spared unneeded biopsy or detection of low-grade tumors in whom treatment may offer little benefit to longevity or quality of life. In this setting, new markers have emerged that seek to offer improvements in the selection for initial or repeat biopsy.
References
- 1. Center M.M., Jemal A., Lortet-Tieulent J., et al: International variation in prostate cancer incidence and mortality rates. Eur Urol 2012; 61: pp. 1079-1092
- 2. Schröder F.H., Hugosson J., Roobol M.J., et al: Screening and prostate cancer mortality: results of the European Randomised Study of Screening for Prostate Cancer (ERSPC) at 13 years of follow-up. Lancet 2014; 384: pp. 2027-2035
- 3. Wang S.Y., Cowan J.E., Cary K.C., et al: Limited ability of existing nomograms to predict outcomes in men undergoing active surveillance for prostate cancer. BJU Int 2014; 114: pp. E18-E24
- 4. Womble P.R., Montie J.E., Ye Z., et al: Contemporary use of initial active surveillance among men in Michigan with low-risk prostate cancer. Eur Urol 2015; 67: pp. 44-50
- 5. Briganti A., Karnes R.J., Joniau S., et al: Prediction of outcome following early salvage radiotherapy among patients with biochemical recurrence after radical prostatectomy. Eur Urol 2014; 66: pp. 479-486
- 6. Brockman J.A., Alanee S., Vickers A.J., et al: Nomogram predicting prostate cancer-specific mortality for men with biochemical recurrence after radical prostatectomy. Eur Urol 2015; 67: pp. 1160-1167
- 7. Cooperberg M.R., Pasta D.J., Elkin E.P., et al: The University of California, San Francisco Cancer of the Prostate Risk Assessment score: a straightforward and reliable preoperative predictor of disease recurrence after radical prostatectomy. J Urol 2005; 173: pp. 1938-1942
- 8. Korets R., Motamedinia P., Yeshchina O., et al: Accuracy of the Kattan nomogram across prostate cancer risk-groups. BJU Int 2011; 108: pp. 56-60
- 9. Greene K.L., Meng M.V., Elkin E.P., et al: Validation of the Kattan preoperative nomogram for prostate cancer recurrence using a community based cohort: results from cancer of the prostate strategic urological research endeavor (capsure). J Urol 2004; 171: pp. 2255-2259
- 10. Parker P.A., Davis J.W., Latini D.M., et al: Relationship between illness uncertainty, anxiety, fear of progression and quality of life in men with favourable-risk prostate cancer undergoing active surveillance. BJU Int 2015; undefined:
- 11. Boutros P.C., Fraser M., Harding N.J., et al: Spatial genomic heterogeneity within localized, multifocal prostate cancer. Nat Genet 2015; 47: pp. 736-745
- 12. McShane L.M., Altman D.G., Sauerbrei W., et al: Reporting recommendations for tumor marker prognostic studies. J Clin Oncol 2005; 23: pp. 9067-9072
- 13. Simon R.: Clinical trial designs for evaluating the medical utility of prognostic and predictive biomarkers in oncology. Per Med 2010; 7: pp. 33-47
- 14. Pepe M.S., Feng Z., Janes H., et al: Pivotal evaluation of the accuracy of a biomarker used for classification or prediction: standards for study design. J Natl Cancer Inst 2008; 100: pp. 1432-1438
- 15. Loeb S., Vonesh E.F., Metter E.J., et al: What is the true number needed to screen and treat to save a life with prostate-specific antigen testing? J Clin Oncol 2011; 29: pp. 464-467
- 16. Fradet Y., Saad F., Aprikian A., et al: uPM3, a new molecular urine test for the detection of prostate cancer. Urology 2004; 64: pp. 311-315
- 17. Wei J.T., Feng Z., Partin A.W., et al: Can urinary PCA3 supplement PSA in the early detection of prostate cancer? J Clin Oncol 2014; 32: pp. 4066-4072
- 18. Deras I.L., Aubin S.M., Blase A., et al: PCA3: a molecular urine assay for predicting prostate biopsy outcome. J Urol 2008; 179: pp. 1587-1592
- 19. Marks L.S., Fradet Y., Deras I.L., et al: PCA3 molecular urine assay for prostate cancer in men undergoing repeat biopsy. Urology 2007; 69: pp. 532-535
- 20. Haese A., de la Taille A., van Poppel H., et al: Clinical utility of the PCA3 urine assay in European men scheduled for repeat biopsy. Eur Urol 2008; 54: pp. 1081-1088
- 21. de la Taille A., Irani J., Graefen M., et al: Clinical evaluation of the PCA3 assay in guiding initial biopsy decisions. J Urol 2011; 185: pp. 2119-2125
- 22. Roobol M.J., Schroder F.H., van Leeuwen P., et al: Performance of the prostate cancer antigen 3 (PCA3) gene and prostate-specific antigen in prescreened men: exploring the value of PCA3 for a first-line diagnostic test. Eur Urol 2010; 58: pp. 475-481
- 23. Auprich M., Chun F.K., Ward J.F., et al: Critical assessment of preoperative urinary prostate cancer antigen 3 on the accuracy of prostate cancer staging. Eur Urol 2011; 59: pp. 96-105
- 24. Nakanishi H., Groskopf J., Fritsche H.A., et al: PCA3 molecular urine assay correlates with prostate cancer tumor volume: implication in selecting candidates for active surveillance. J Urol 2008; 179: pp. 1804-1809
- 25. Ploussard G., Durand X., Xylinas E., et al: Prostate cancer antigen 3 score accurately predicts tumour volume and might help in selecting prostate cancer patients for active surveillance. Eur Urol 2011; 59: pp. 422-429
- 26. Tomlins S.A., Rhodes D.R., Perner S., et al: Recurrent fusion of TMPRSS2 and ETS transcription factor genes in prostate cancer. Science 2005; 310: pp. 644-648
- 27. Salami S.S., 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 2013; 31: pp. 566-571
- 28. Hessels D., Smit F.P., Verhaegh G.W., et al: Detection of TMPRSS2-ERG fusion transcripts and prostate cancer antigen 3 in urinary sediments may improve diagnosis of prostate cancer. Clin Cancer Res 2007; 13: pp. 5103-5108
- 29. Leyten G.H., Hessels D., Jannink S.A., et al: Prospective multicentre evaluation of PCA3 and TMPRSS2-ERG gene fusions as diagnostic and prognostic urinary biomarkers for prostate cancer. Eur Urol 2014; 65: pp. 534-542
- 30. Tallon L., Luangphakdy D., Ruffion A., et al: Comparative evaluation of urinary PCA3 and TMPRSS2: ERG scores and serum PHI in predicting prostate cancer aggressiveness. Int J Mol Sci 2014; 15: pp. 13299-13316
- 31. Duijvesz D., Luider T., Bangma C.H., et al: Exosomes as biomarker treasure chests for prostate cancer. Eur Urol 2011; 59: pp. 823-831
- 32. Nilsson J., Skog J., Nordstrand A., et al: Prostate cancer-derived urine exosomes: a novel approach to biomarkers for prostate cancer. Br J Cancer 2009; 100: pp. 1603-1607
- 33. Donovan MJ, Noerholm M, Bentink S, et al. A first catch, non-DRE urine exosome gene signature to predict Gleason 7 prostate cancer on an initial prostate needle biopsy. Abstract #45/Poster#C12 2015 Genitourinary Cancers Symposium. Orlando, FL, 2015.
- 34. Lughezzani G., Budaus L., Isbarn H., et al: Head-to-head comparison of the three most commonly used preoperative models for prediction of biochemical recurrence after radical prostatectomy. Eur Urol 2010; 57: pp. 562-568
- 35. Van Neste L., Herman J.G., Otto G., et al: The epigenetic promise for prostate cancer diagnosis. Prostate 2012; 72: pp. 1248-1261
- 36. Mehrotra J., Varde S., Wang H., et al: Quantitative, spatial resolution of the epigenetic field effect in prostate cancer. Prostate 2008; 68: pp. 152-160
- 37. Trock B.J., Brotzman M.J., Mangold L.A., 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: pp. 56-62
- 38. Stewart G.D., 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: pp. 1110-1116
- 39. Partin A.W., Van Neste L., Klein E.A., et al: Clinical validation of an epigenetic assay to predict negative histopathological results in repeat prostate biopsies. J Urol 2014; 192: pp. 1081-1087
- 40. Siddiqui M.M., Rais-Bahrami S., Turkbey B., et al: Comparison of MR/ultrasound fusion-guided biopsy with ultrasound-guided biopsy for the diagnosis of prostate cancer. JAMA 2015; 313: pp. 390-397
- 41. Whitfield M.L., Sherlock G., Saldanha A.J., et al: Identification of genes periodically expressed in the human cell cycle and their expression in tumors. Mol Biol Cell 2002; 13: pp. 1977-2000
- 42. Cuzick J., Swanson G.P., 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: pp. 245-255
- 43. Cooperberg M.R., Carroll P.R., and Klotz L.: Active surveillance for prostate cancer: progress and promise. J Clin Oncol 2011; 29: pp. 3669-3676
- 44. Dall’era M.A., Cooperberg M.R., Chan J.M., et al: Active surveillance for early-stage prostate cancer: review of the current literature. Cancer 2008; 112: pp. 1650-1659
- 45. Freedland S.J., 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: pp. 848-853
- 46. Bishoff J.T., Freedland S.J., Gerber L., et al: Prognostic utility of the cell cycle progression score generated from biopsy in men treated with prostatectomy. J Urol 2014; 192: pp. 409-414
- 47. Knezevic D., Goddard A.D., 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: pp. 690
- 48. Klein E.A., Cooperberg M.R., 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: pp. 550-560
- 49. Cullen J., Rosner I.L., Brand T.C., 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: pp. 123-131
- 50. Nakagawa T., Kollmeyer T.M., Morlan B.W., et al: A tissue biomarker panel predicting systemic progression after PSA recurrence post-definitive prostate cancer therapy. PLoS One 2008; 3: pp. e2318
- 51. Karnes R.J., Bergstralh E.J., 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: pp. 2047-2053
- 52. Cooperberg M.R., Davicioni E., Crisan A., et al: 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: pp. 326-333
- 53. Den R.B., Feng F.Y., Showalter T.N., 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: pp. 1038-1046
- 54. Antonarakis E.S., Feng Z., Trock B.J., et al: The natural history of metastatic progression in men with prostate-specific antigen recurrence after radical prostatectomy: long-term follow-up. BJU Int 2012; 109: pp. 32-39
- 55. Simmons M.N., Stephenson A.J., and Klein E.A.: Natural history of biochemical recurrence after radical prostatectomy: risk assessment for secondary therapy. Eur Urol 2007; 51: pp. 1175-1184
- 56. Ross A.E., Feng F.Y., Ghadessi M., et al: A genomic classifier predicting metastatic disease progression in men with biochemical recurrence after prostatectomy. Prostate Cancer Prostatic Dis 2014; 17: pp. 64-69
- 57. Brett S.I., Kim Y., Biggs C.N., et al: Extracellular vesicles such as prostate cancer cell fragments as a fluid biopsy for prostate cancer. Prostate Cancer Prostatic Dis 2015; 18: pp. 213-220
- 58. Zheng Q., Peskoe S.B., Ribas J., et al: Investigation of miR-21, miR-141, and miR-221 expression levels in prostate adenocarcinoma for associated risk of recurrence after radical prostatectomy. Prostate 2014; 74: pp. 1655-1662
- 59. Wang S.Y., Shiboski S., Belair C.D., et al: miR-19, miR-345, miR-519c-5p serum levels predict adverse pathology in prostate cancer patients eligible for active surveillance. PLoS One 2014; 9: pp. e98597