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Incorporation of tissue-based genomic biomarkers into localized prostate cancer clinics


Localized prostate cancer (PCa) is a clinically heterogeneous disease, which presents with variability in patient outcomes within the same risk stratification (low, intermediate or high) and even within the same Gleason scores. Genomic tools have been developed with the purpose of stratifying patients affected by this disease to help physicians personalize therapies and follow-up schemes. This review focuses on these tissue-based tools. At present, four genomic tools are commercially available: Decipher™, Oncotype DX®, Prolaris® and ProMark®. Decipher™ is a tool based on 22 genes and evaluates the risk of adverse outcomes (metastasis) after radical prostatectomy (RP). Oncotype DX® is based on 17 genes and focuses on the ability to predict outcomes (adverse pathology) in very low-low and low-intermediate PCa patients, while Prolaris® is built on a panel of 46 genes and is validated to evaluate outcomes for patients at low risk as well as patients who are affected by high risk PCa and post-RP. Finally, ProMark® is based on a multiplexed proteomics assay and predicts PCa aggressiveness in patients found with similar features to Oncotype DX®. These biomarkers can be helpful for post-biopsy decision-making in low risk patients and post-radical prostatectomy in selected risk groups. Further studies are needed to investigate the clinical benefit of these new technologies, the financial ramifications and how they should be utilized in clinics.

Keywords:
Prostate cancer, Radical prostatectomy, Genetic tools, Decipher, Oncotype DX, Prolaris


Autoři: Marco Moschini 1;  Martin Spahn 2;  Agostino Mattei 3;  John Cheville 4;  R. Jeffrey Karnes 1*
Působiště autorů: Department of Urology, Mayo Clinic, Rochester, MN, USA. 1;  Department of Urology, University Hospital of Bern, Inselspital, Bern, Switzerland. 2;  Klinik für Urologie, Luzerner Kantonsspital, Luzern, Switzerland. 3;  Department of Laboratory Medicine and Pathology, Mayo Clinic , Rochester, MN, USA. 4
Vyšlo v časopise: BMC Medicine 2016, 14:67
Kategorie: Review
prolekare.web.journal.doi_sk: https://doi.org/10.1186/s12916-016-0613-7

© 2016 Moschini et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
The electronic version of this article is the complete one and can be found online at: https://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-016-0613-7

Souhrn

Localized prostate cancer (PCa) is a clinically heterogeneous disease, which presents with variability in patient outcomes within the same risk stratification (low, intermediate or high) and even within the same Gleason scores. Genomic tools have been developed with the purpose of stratifying patients affected by this disease to help physicians personalize therapies and follow-up schemes. This review focuses on these tissue-based tools. At present, four genomic tools are commercially available: Decipher™, Oncotype DX®, Prolaris® and ProMark®. Decipher™ is a tool based on 22 genes and evaluates the risk of adverse outcomes (metastasis) after radical prostatectomy (RP). Oncotype DX® is based on 17 genes and focuses on the ability to predict outcomes (adverse pathology) in very low-low and low-intermediate PCa patients, while Prolaris® is built on a panel of 46 genes and is validated to evaluate outcomes for patients at low risk as well as patients who are affected by high risk PCa and post-RP. Finally, ProMark® is based on a multiplexed proteomics assay and predicts PCa aggressiveness in patients found with similar features to Oncotype DX®. These biomarkers can be helpful for post-biopsy decision-making in low risk patients and post-radical prostatectomy in selected risk groups. Further studies are needed to investigate the clinical benefit of these new technologies, the financial ramifications and how they should be utilized in clinics.

Keywords:
Prostate cancer, Radical prostatectomy, Genetic tools, Decipher, Oncotype DX, Prolaris


Zdroje

1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2015. CA Cancer J Clin. 2015;65:5–29. doi:10.3322/caac.21254.

2. Shao YH, Demissie K, Shih W, Mehta AR, Stein MN, Roberts CB, et al. Contemporary risk profile of prostate cancer in the United States. J Natl Cancer Inst. 2009;101:1280–3. doi:10.1093/jnci/djp262.

3. Budäus L, Spethmann J, Isbarn H, Schmitges J, Beesch L, Haese A, et al. Inverse stage migration in patients undergoing radical prostatectomy: results of 8916 European patients treated within the last decade. BJU Int. 2011;108:1256–61. doi:10.1111/j.1464-410X.2010.09982.x.

4. Silberstein JL, Vickers AJ, Power NE, Fine SW, Scardino PT, Eastham JA, et al. Reverse stage shift at a tertiary care center: escalating risk in men undergoing radical prostatectomy. Cancer. 2011;117:4855–60. doi:10.1002/cncr.26132.

5. Barbieri CE, Bangma CH, Bjartell A, Catto JWF, Culig Z, Grönberg H, et al. The mutational landscape of prostate cancer. Eur Urol. 2013;64:567–76. doi:10.1016/j.eururo.2013.05.029.

6. Haffner MC, Mosbruger T, Esopi DM, Fedor H, Heaphy CM, Walker DA, et al. Tracking the clonal origin of lethal prostate cancer. J Clin Invest. 2013;123:4918–22. doi:10.1172/JCI70354.

7. Kumar A, White TA, MacKenzie AP, Clegg N, Lee C, Dumpit RF, et al. Exome sequencing identifies a spectrum of mutation frequencies in advanced and lethal prostate cancers. Proc Natl Acad Sci U S A. 2011;108:17087–92. doi:10.1073/pnas.1108745108.

8. Grasso CS, Wu YM, Robinson DR, Cao X, Dhanasekaran SM, Khan AP, et al. The mutational landscape of lethal castration-resistant prostate cancer. Nature. 2012;487:239–43. doi:10.1038/nature11125.

9. Taylor BS, Schultz N, Hieronymus H, Gopalan A, Xiao Y, Carver BS, et al. Integrative genomic profiling of human prostate cancer. Cancer Cell. 2010;18:11–22. doi:10.1016/j.ccr.2010.05.026.

10. Fizazi K, Scher HI, Molina A, Logothetis CJ, Chi KN, Jones RJ, et al. Abiraterone acetate for treatment of metastatic castration-resistant prostate cancer: final overall survival analysis of the COU-AA-301 randomised, double-blind, placebocontrolled phase 3 study. Lancet Oncol. 2012;13:983–92. doi:10.1016/S1470-2045(12)70379-0.

11. Scher HI, Fizazi K, Saad F, Taplin ME, Sternberg CN, Miller K, et al. Increased survival with enzalutamide in prostate cancer after chemotherapy. N Engl J Med. 2012;367:1187–97. doi:10.1056/NEJMoa1207506.

12. Beer TM, Tombal B. Enzalutamide in metastatic prostate cancer before chemotherapy. N Engl J Med. 2014;371:1755–6. doi:10.1056/NEJMc1410239.

13. Tannock IF, de Wit R, Berry WR, Horti J, Pluzanska A, Chi KN, et al. Docetaxel plus prednisone or mitoxantrone plus prednisone for advanced prostate cancer. N Engl J Med. 2004;351:1502–12. doi:10.1056/NEJMoa040720.

14. de Bono JS, Oudard S, Ozguroglu M, Hansen S, MacHiels JP, Kocak I, et al. Prednisone plus cabazitaxel or mitoxantrone for metastatic castrationresistant prostate cancer progressing after docetaxel treatment: a randomised open-label trial. Lancet. 2010;376:1147–54. doi:10.1016/S0140-6736(10)61389-X.

15. Sternberg IA, Vela I, Scardino PT. Molecular profiles of prostate cancer: to treat or not to treat. Annu Rev Med. 2015;67:119–35. doi:10.1146/annurevmed-060413-112226.

16. Boström PJ, Bjartell AS, Catto JWF, Eggener SE, Lilja H, Loeb S, et al. Genomic predictors of outcome in prostate cancer. Eur Urol. 2015;68:1033–44. doi:10.1016/j.eururo.2015.04.008.

17. Sartori DA, Chan DW. Biomarkers in prostate cancer: what’s new? Curr Opin Oncol. 2014;26:259–64. doi:10.1097/CCO.0000000000000065.

18. Spahn M, Boxler S, Joniau S, Moschini M, Tombal B, Karnes RJ. What is the need for prostatic biomarkers in prostate cancer management? Curr Urol Rep. 2015;16:70. doi:10.1007/s11934-015-0545-3.

19. Erho N, Crisan A, Vergara IA, Mitra AP, Ghadessi M, Buerki C, et al. Discovery and validation of a prostate cancer genomic classifier that predicts early metastasis following radical prostatectomy. PLoS One. 2013;8, e66855. doi:10.1371/journal.pone.0066855.

20. Mohler JL, Armstrong AJ, Bahnson RR, D’Amico AV, Davis BJ, Eastham JA, et al. Prostate Cancer, Version 1.2016. J Natl Compr Canc Netw. 2016;14:19–30.

21. Alshalalfa M, Crisan A, Vergara IA, Ghadessi M, Buerki C, Erho N, et al. Clinical and genomic analysis of metastatic prostate cancer progression with a background of postoperative biochemical recurrence. BJU Int. 2015;116:556–67. doi:10.1111/bju.13013.

22. Karnes RJ, Bergstralh EJ, Davicioni E, Ghadessi M, Buerki C, Mitra AP, et al. Validation of a genomic classifier that predicts metastasis following radical prostatectomy in an at risk patient population. J Urol. 2013;190: 2047–53. doi:10.1016/j.juro.2013.06.017.

23. Ross AE, Feng FY, Ghadessi M, Erho N, Crisan A, Buerki C, et al. A genomic classifier predicting metastatic disease progression in men with biochemical recurrence after prostatectomy. Prostate Cancer Prostatic Dis. 2014;17:64–9. doi:10.1038/pcan.2013.49.

24. Den RB, Feng FY, Showalter TN, Mishra MV, Trabulsi EJ, Lallas CD, et al. Genomic prostate cancer classifier predicts biochemical failure and metastases in patients after postoperative radiation therapy. Int J Radiat Oncol. 2014;89:1038–46. doi:10.1016/j.ijrobp.2014.04.052.

25. Den RB, Yousefi K, Trabulsi EJ, Abdollah F, Choeurng V, Feng FY, et al. Genomic classifier identifies men with adverse pathology after radical prostatectomy who benefit from adjuvant radiation therapy. J Clin Oncol. 2015;33:944–51. doi:10.1200/JCO.2014.59.0026.

26. Lobo JM, Dicker AP, Buerki C, Daviconi E, Karnes RJ, Jenkins RB, et al. Evaluating the clinical impact of a genomic classifier in prostate cancer using individualized decision analysis. PLoS One. 2015;10, e0116866. doi:10.1371/journal.pone.0116866.

27. Klein EA, Yousefi K, Haddad Z, Choeurng V, Buerki C, Stephenson AJ, 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. 2014;67:778–86. doi:10.1016/j.eururo.2014.10.036.

28. 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;67:326–33. doi:10.1016/j.eururo.2014.05.039.

29. Knezevic D, Goddard AD, Natraj N, Cherbavaz DB, Clark-Langone KM, Snable J, 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. doi:10.1186/1471-2164-14-690.

30. Klein EA, Cooperberg MR, Magi-Galluzzi C, Simko JP, Falzarano SM, Maddala T, 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;66:550–60. doi:10.1016/j.eururo.2014.05.004.

31. Cullen J, Rosner IL, Brand TC, Zhang N, Tsiatis AC, Moncur J, et al. A biopsybased 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;68:123–31. doi:10.1016/j.eururo.2014.11.030.

32. Cuzick J, Swanson GP, Fisher G, Brothman AR, Berney DM, Reid JE, 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;12:245–55. doi:10.1016/S1470-2045(10)70295-3.

33. Cuzick J, Berney DM, Fisher G, Mesher D, Møller H, Reid JE, 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;106:1095–9. doi:10.1038/bjc.2012.39.

34. Bishoff JT, Freedland SJ, Gerber L, Tennstedt P, Reid J, Welbourn W, et al. Prognostic utility of the cell cycle progression score generated from biopsy in men treated with prostatectomy. J Urol. 2014;192:409–14. doi:10.1016/j.juro.2014.02.003.

35. Freedland SJ, Gerber L, Reid J, Welbourn W, Tikishvili E, Park 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;86:848–53. doi:10.1016/j.ijrobp.2013.04.043.

36. Cooperberg MR, Simko JP, Cowan JE, Reid JE, Djalilvand A, Bhatnagar S, et al. Validation of a cell-cycle progression gene panel to improve risk stratification in a contemporary prostatectomy cohort. J Clin Oncol. 2013;31:1428–34. doi:10.1200/JCO.2012.46.4396.

37. Shipitsin M, Small C, Choudhury S, Giladi E, Friedlander S, Nardone J, et al. Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error. Br J Cancer. 2014;111:1201–12. doi:10.1038/bjc.2014.396.

38. Blume-Jensen P, Berman DM, Rimm DL, Shipitsin M, Putzi M, Nifong TP, et al. Development and clinical validation of an in situ biopsy-based multimarker assay for risk stratification in prostate cancer. Clin Cancer Res. 2015;21:2591–600. doi:10.1158/1078-0432.CCR-14-2603.

39. Partin AW, Van Neste L, Klein EA, Marks LS, Gee JR, Troyer DA, et al. Clinical validation of an epigenetic assay to predict negative histopathological results in repeat prostate biopsies. J Urol. 2014;192:1081–7. doi:10.1016/j.juro.2014.04.013.

40. Wojno KJ, Costa FJ, Cornell RJ, Small JD, Pasin E, Van Criekinge W, et al. Reduced rate of repeated prostate biopsies observed in ConfirmMDx clinical utility field study. Am Heal Drug Benefits. 2014;7:129–34.

41. Fisher G, Yang ZH, Kudahetti S, Møller H, Scardino P, Cuzick J, et al. Prognostic value of Ki-67 for prostate cancer death in a conservatively managed cohort. Br J Cancer. 2013;108:271–7. doi:10.1038/bjc.2012.598.

42. Rubio J, Ramos D, López-Guerrero JA, Iborra I, Collado A, Solsona E, et al. Immunohistochemical expression of Ki-67 antigen, cox-2 and Bax/Bcl-2 in prostate cancer; prognostic value in biopsies and radical prostatectomy specimens. Eur Urol. 2005;48:745–51. doi:10.1016/j.eururo.2005.06.014.

43. Jhavar S, Bartlett J, Kovacs G, Corbishley C, Dearnaley D, Eeles R, et al. Biopsy tissue microarray study of Ki-67 expression in untreated, localized prostate cancer managed by active surveillance. Prostate Cancer Prostatic Dis. 2009;12:143–7. doi:10.1038/pcan.2008.47.

44. Tollefson MK, Karnes RJ, Kwon ED, Lohse CM, Rangel LJ, Mynderse LA, et al. Prostate cancer Ki-67 (MIB-1) expression, perineural invasion, and gleason score as biopsy-based predictors of prostate cancer mortality: the Mayo model. Mayo Clin Proc. 2014;89:308–18. doi:10.1016/j.mayocp.2013.12.001.

45. Pollack A, DeSilvio M, Khor LY, Li R, Al-Saleem TI, Hammond ME, et al. Ki-67 staining is a strong predictor of distant metastasis and mortality for men with prostate cancer treated with radiotherapy plus androgen deprivation: Radiation Therapy Oncology Group Trial 92-02. J Clin Oncol. 2004;22:2133–40. doi:10.1200/JCO.2004.09.150.

46. Khatami A, Hugosson J, Wang W, Damber JE. Ki-67 in screen-detected, low-grade, low-stage prostate cancer, relation to prostate-specific antigen doubling time, Gleason score and prostate-specific antigen relapse after radical prostatectomy. Scand J Urol Nephrol. 2009;43:12–8. doi:10.1080/00365590802469543.

47. Aaltomaa S, Kärjä V, Lipponen P, Isotalo T, Kankkunen JP, Talja M, et al. Expression of Ki-67, cyclin D1 and apoptosis markers correlated with survival in prostate cancer patients treated by radical prostatectomy. Anticancer Res. 2006;26:4873–8.

48. Mathieu R, Shariat SF, Seitz C, Karakiewicz PI, Fajkovic H, Sun M, et al. Multiinstitutional validation of the prognostic value of Ki-67 labeling index in patients treated with radical prostatectomy. World J Urol. 2015;33:1165–71. doi:10.1007/s00345-014-1421-3.

49. Leinonen KA, Saramäki OR, Furusato B, Kimura T, Takahashi H, Egawa S, et al. Loss of PTEN is associated with aggressive behavior in ERG-positive prostate cancer. Cancer Epidemiol Biomarkers Prev. 2013;22:2333–44. doi:10.1158/1055-9965.EPI-13-0333-T.

50. Yoshimoto M, Joshua AM, Cunha IW, Coudry RA, Fonseca FP, Ludkovski O, et al. Absence of TMPRSS2:ERG fusions and PTEN losses in prostate cancer is associated with a favorable outcome. Mod Pathol. 2008;21:1451–60. doi:10.1038/modpathol.2008.96.

51. Krohn A, Diedler T, Burkhardt L, Mayer PS, De Silva C, Meyer-Kornblum M, et al. Genomic deletion of PTEN is associated with tumor progression and early PSA recurrence in ERG fusion-positive and fusion-negative prostate cancer. Am J Pathol. 2012;181:401–12. doi:10.1016/j.ajpath.2012.04.026.

52. McCall P, Witton CJ, Grimsley S, Nielsen KV, Edwards J. Is PTEN loss associated with clinical outcome measures in human prostate cancer? Br J Cancer. 2008;99:1296–301. doi:10.1038/sj.bjc.6604680.

53. Cairns P, Okami K, Halachmi S, Halachmi N, Esteller M, Herman JG, et al. Frequent inactivation of PTEN/MMAC1 in primary prostate cancer. Cancer Res. 1997;57:4997–5000.

54. Feilotter HE, Nagai MA, Boag AH, Eng C, Mulligan LM. Analysis of PTEN and the 10q23 region in primary prostate carcinomas. Oncogene. 1998;16:1743–8. doi:10.1038/sj.onc.1200205.

55. Pesche S, Latil A, Muzeau F, Cussenot O, Fournier G, Longy M, et al. PTEN/MMAC1/TEP1 involvement in primary prostate cancers. Oncogene. 1998;16:2879–83. doi:10.1038/sj.onc.1202081.

56. Wang SI, Parsons R, Ittmann M. Homozygous deletion of the PTEN tumor suppressor gene in a subset of prostate adenocarcinomas. Clin Cancer Res. 1998;4:811–5.

57. Whang YE, Wu X, Suzuki H, Reiter RE, Tran C, Vessella RL, et al. Inactivation of the tumor suppressor PTEN/MMAC1 in advanced human prostate cancer through loss of expression. Proc Natl Acad Sci U S A. 1998;95:5246–50.

58. Murphy SJ, Karnes RJ, Kosari F, Castellar BE, Kipp BR, Johnson SH, et al. Integrated analysis of the genomic instability of PTEN in clinically insignificant and significant prostate cancer. Mod Pathol. 2016;29:143–56. doi:10.1038/modpathol.2015.136.

59. Mithal P, Allott E, Gerber L, Reid J, Welbourn W, Tikishvili E, et al. PTEN loss in biopsy tissue predicts poor clinical outcomes in prostate cancer. Int J Urol. 2014;21:1209–14. doi:10.1111/iju.12571.

60. Lotan TL, Carvalho FLF, Peskoe SB, Hicks JL, Good J, Fedor HL, et al. PTEN loss is associated with upgrading of prostate cancer from biopsy to radical prostatectomy. Mod Pathol. 2015;28:128–37. doi:10.1038/modpathol.2014.85.

61. Lotan TL, Gurel B, Sutcliffe S, Esopi D, Liu W, Xu J, et al. PTEN protein loss by immunostaining: analytic validation and prognostic indicator for a high risk surgical cohort of prostate cancer patients. Clin Cancer Res. 2011;17:6563–73. doi:10.1158/1078-0432.CCR-11-1244.

62. Ferraldeschi R, Nava Rodrigues D, Riisnaes R, Miranda S, Figueiredo I, Rescigno P, et al. PTEN protein loss and clinical outcome from castrationresistant prostate cancer treated with abiraterone acetate. Eur Urol. 2015;67:795–802. doi:10.1016/j.eururo.2014.10.027.

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