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Genetische Marker und Prognosefaktoren beim Prostatakarzinom

Molecular biomarkers and prognostic factors for prostate cancer

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Zusammenfassung

In der Ära der personalisierten Medizin werden große Hoffnungen in neu etablierte genetische Biomarker gesetzt, um die prognostische Lücke aus klinischen und histopathologischen Parametern bei der Therapie und Risikostratifizierung des Prostatakarzinoms zu schließen. In der vorliegenden Arbeit werden prognostische und prädiktive genetische Biomarker vorgestellt, die klinische Relevanz bei Diagnosestellung und nach einer definitiven Therapie des Prostatakarzinoms haben. Hierbei werden Grundsätze der Biomarkerforschung erläutert und die aktuelle Studienlage bezüglich des Progensa-PCA3-Tests, der TMPRSS2:ERG-Genfusion sowie des ConfirmMDx- und des Prolaris-Tests, des OncotypeDX Genomic Prostate Score und des Decipher Classifier präsentiert. Die Evidenz hat sich in den vergangenen Jahren stark verbessert. Nichtsdestotrotz besteht weiterhin ein Mangel an großen, multizentrischen und v. a. prospektiven Validierungsstudien. Darüber hinaus existieren keine komparativen Studien.

Abstract

In the era of personalized medicine and precision oncology, innovative genetic biomarkers are of emerging interest to close the diagnostic and prognostic gap that is left by current clinicopathologic risk classifiers. The current review article summarizes evidence regarding prognostic and predictive genetic biomarkers that are currently in widespread clinical use at initial diagnosis as well as following definitive treatment of prostate cancer. We give a brief summary about basic principles of biomarker research studies and present current data for the Progensa PC3 test, TMPRSS2:ERG gene fusion, ConfirmMDx, Prolaris gene panel, OncotypeDX Genomic Prostate score, and Decipher classifier. Evidence regarding those genetic biomarkers has heavily increased recently. However, there is still a lack of large, multicentric and prospective clinical validation studies. Furthermore, comparative studies that investigate the prognostic value of various genetic biomarkers are needed.

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Literatur

  1. Ferlay J, Soerjomataram I, Dikshit R, Eser S, Mathers C, Rebelo M et al (2015) Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer 136(5):E359–386. doi:10.1002/ijc.29210

    Article  CAS  PubMed  Google Scholar 

  2. Wang SY, Cowan JE, Cary KC, Chan JM, Carroll PR, Cooperberg MR (2014) Limited ability of existing nomograms to predict outcomes in men undergoing active surveillance for prostate cancer. BJU Int 114(6b):E18–24. doi:10.1111/bju.12554

    Article  PubMed  Google Scholar 

  3. Schroder FH, Hugosson J, Roobol MJ, Tammela TL, Zappa M, Nelen V et al (2014) Screening and prostate cancer mortality: results of the European Randomised Study of Screening for Prostate Cancer (ERSPC) at 13 years of follow-up. Lancet 384(9959):2027–2035. doi:10.1016/S0140-6736(14)60525-0

    Article  PubMed  PubMed Central  Google Scholar 

  4. Gordetsky J, Epstein J (2016) Grading of prostatic adenocarcinoma: current state and prognostic implications. Diagn Pathol 11:25. doi:10.1186/s13000-016-0478-2

    Article  PubMed  PubMed Central  Google Scholar 

  5. Antonarakis ES, Lu C, Wang H, Luber B, Nakazawa M, Roeser JC et al (2014) AR-V7 and resistance to enzalutamide and abiraterone in prostate cancer. N Engl J Med 371(11):1028–1038. doi:10.1056/NEJMoa1315815

    Article  PubMed  PubMed Central  Google Scholar 

  6. Bernemann C, Schnoeller TJ, Luedeke M, Steinestel K, Boegemann M, Schrader AJ et al (2016) Expression of AR-V7 in circulating tumour cells does not preclude response to next generation androgen deprivation therapy in patients with castration resistant prostate cancer. Eur Urol. doi:10.1016/j.eururo.2016.07.021

    Google Scholar 

  7. McShane LM, Altman DG, Sauerbrei W, Taube SE, Gion M, Clark GM et al (2005) Reporting recommendations for tumor marker prognostic studies. J Clin Oncol 23(36):9067–9072. doi:10.1200/JCO.2004.01.0454

    Article  PubMed  Google Scholar 

  8. Simon R (2010) Clinical trial designs for evaluating the medical utility of prognostic and predictive biomarkers in oncology. Per Med 7(1):33–47. doi:10.2217/pme.09.49

    Article  PubMed  PubMed Central  Google Scholar 

  9. Pepe MS, Feng Z, Janes H, Bossuyt PM, Potter JD (2008) Pivotal evaluation of the accuracy of a biomarker used for classification or prediction: standards for study design. J Natl Cancer Inst 100(20):1432–1438. doi:10.1093/jnci/djn326

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Leapman MS, Carroll PR (2016) New genetic markers for prostate cancer. Urol Clin North Am 43(1):7–15. doi:10.1016/j.ucl.2015.08.002

    Article  PubMed  Google Scholar 

  11. Fradet Y, Saad F, Aprikian A, Dessureault J, Elhilali M, Trudel C et al (2004) uPM3, a new molecular urine test for the detection of prostate cancer. Urology 64(2):311–315. doi:10.1016/j.urology.2004.03.052 (discussion 315–316)

    Article  PubMed  Google Scholar 

  12. Wei JT, Feng Z, Partin AW, Brown E, Thompson I, Sokoll L et al (2014) Can urinary PCA3 supplement PSA in the early detection of prostate cancer? J Clin Oncol 32(36):4066–4072. doi:10.1200/JCO.2013.52.8505

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. de la Taille A, Irani J, Graefen M, Chun F, de Reijke T, Kil P et al (2011) Clinical evaluation of the PCA3 assay in guiding initial biopsy decisions. J Urol 185(6):2119–2125. doi:10.1016/j.juro.2011.01.075

    Article  PubMed  Google Scholar 

  14. Haese A, de la Taille A, van Poppel H, Marberger M, Stenzl A, Mulders PF et al (2008) Clinical utility of the PCA3 urine assay in European men scheduled for repeat biopsy. Eur Urol 54(5):1081–1088. doi:10.1016/j.eururo.2008.06.071

    Article  PubMed  Google Scholar 

  15. Ploussard G, Durand X, Xylinas E, Moutereau S, Radulescu C, Forgue A et al (2011) Prostate cancer antigen 3 score accurately predicts tumour volume and might help in selecting prostate cancer patients for active surveillance. Eur Urol 59(3):422–429. doi:10.1016/j.eururo.2010.11.044

    Article  PubMed  Google Scholar 

  16. Tomlins SA, Rhodes DR, Perner S, Dhanasekaran SM, Mehra R, Sun XW et al (2005) Recurrent fusion of TMPRSS2 and ETS transcription factor genes in prostate cancer. Science 310(5748):644–648. doi:10.1126/science.1117679

    Article  CAS  PubMed  Google Scholar 

  17. Attard G, Clark J, Ambroisine L, Fisher G, Kovacs G, Flohr P et al (2008) Duplication of the fusion of TMPRSS2 to ERG sequences identifies fatal human prostate cancer. Oncogene 27(3):253–263. doi:10.1038/sj.onc.1210640

    Article  CAS  PubMed  Google Scholar 

  18. Demichelis F, Fall K, Perner S, Andren O, Schmidt F, Setlur SR et al (2007) TMPRSS2:ERG gene fusion associated with lethal prostate cancer in a watchful waiting cohort. Oncogene 26(31):4596–4599. doi:10.1038/sj.onc.1210237

    Article  CAS  PubMed  Google Scholar 

  19. Pettersson A, Graff RE, Bauer SR, Pitt MJ, Lis RT, Stack EC et al (2012) The TMPRSS2:ERG rearrangement, ERG expression, and prostate cancer outcomes: a cohort study and meta-analysis. Cancer Epidemiol Biomarkers Prev 21(9):1497–1509. doi:10.1158/1055-9965.epi-12-0042

    Article  PubMed  PubMed Central  Google Scholar 

  20. Leyten GHJM, Hessels D, Jannink SA, Smit FP, de Jong H, Cornel EB et al (2014) Prospective multicentre evaluation of PCA3 and TMPRSS2-ERG gene fusions as diagnostic and prognostic urinary biomarkers for prostate cancer. Eur Urol 65(3):534–542. doi:10.1016/j.eururo.2012.11.014

    Article  CAS  PubMed  Google Scholar 

  21. Tomlins SA, Day JR, Lonigro RJ, Hovelson DH, Siddiqui J, Kunju LP et al (2016) Urine TMPRSS2:ERG Plus PCA3 for Individualized Prostate Cancer Risk Assessment. Eur Urol 70(1):45–53. doi:10.1016/j.eururo.2015.04.039

    Article  CAS  PubMed  Google Scholar 

  22. Tomlins SA, Groskopf J, Chinnaiyan AM (2015) Reply to Carsten Stephan, Henning Cammann, and Klaus Jung’s Letter to the Editor re: Scott A. Tomlins, John R. Day, Robert J. Lonigro, et al Urine TMPRSS2:ERG Plus PCA3 for Individualized Prostate Cancer Risk Assessment. Eur Urol. In press. doi:10.1016/j.eururo.2015.04.039. Eur Urol 68(5):e108. doi:10.1016/j.eururo.2015.07.027

    Article  PubMed  Google Scholar 

  23. Stephan C, Cammann H, Jung K (2015) Re: Scott A. Tomlins, John R. Day, Robert J. Lonigro, et al Urine TMPRSS2:ERG Plus PCA3 for Individualized Prostate Cancer Risk Assessment. Eur Urol. In press. doi:10.1016/j.eururo.2015.04.039. Eur Urol 68(5):e106–107. doi:10.1016/j.eururo.2015.07.028

    Article  PubMed  Google Scholar 

  24. Chan TA, Glockner S, Yi JM, Chen W, Van Neste L, Cope L et al (2008) Convergence of mutation and epigenetic alterations identifies common genes in cancer that predict for poor prognosis. PloS Med Libr Sci 5(5):e114

    Article  Google Scholar 

  25. Van Neste L, Herman JG, Otto G, Bigley JW, Epstein JI, Van Criekinge W (2012) The epigenetic promise for prostate cancer diagnosis. Prostate 72(11):1248–1261

    Article  PubMed  Google Scholar 

  26. Trock BJ, Brotzman MJ, Mangold LA, Bigley JW, Epstein JI, McLeod D et al (2012) 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 110(1):56–62

    Article  CAS  PubMed  Google Scholar 

  27. Stewart GD, Van Neste L, Delvenne P, Delree P, Delga A, McNeill SA et al (2013) Clinical utility of an epigenetic assay to detect occult prostate cancer in histopathologically negative biopsies: results of the MATLOC study. J Urol 189(3):1110–1116. doi:10.1016/j.juro.2012.08.219

    Article  PubMed  Google Scholar 

  28. Partin AW, Van Neste L, Klein EA, Marks LS, Gee JR, Troyer DA et al (2014) Clinical validation of an epigenetic assay to predict negative histopathological results in repeat prostate biopsies. J Urol 192(4):1081–1087. doi:10.1016/j.juro.2014.04.013

    Article  PubMed  PubMed Central  Google Scholar 

  29. Weiss G, Cottrell S, Distler J, Schatz P, Kristiansen G, Ittmann M et al (2009) DNA methylation of the PITX2 gene promoter region is a strong independent prognostic marker of biochemical recurrence in patients with prostate cancer after radical prostatectomy. J Urol 181(4):1678–1685. doi:10.1016/j.juro.2008.11.120

    Article  CAS  PubMed  Google Scholar 

  30. Schatz P, Dietrich D, Koenig T, Burger M, Lukas A, Fuhrmann I et al (2010) Development of a diagnostic microarray assay to assess the risk of recurrence of prostate cancer based on PITX2 DNA methylation. J Mol Diagn 12(3):345–353. doi:10.2353/jmoldx.2010.090088

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Dietrich D, Hasinger O, Banez LL, Sun L, van Leenders GJ, Wheeler TM et al (2013) Development and clinical validation of a real-time PCR assay for PITX2 DNA methylation to predict prostate-specific antigen recurrence in prostate cancer patients following radical prostatectomy. J Mol Diagn 15(2):270–279. doi:10.1016/j.jmoldx.2012.11.002

    Article  CAS  PubMed  Google Scholar 

  32. Vasiljevic N, Ahmad AS, Carter PD, Fisher G, Berney DM, Foster CS et al (2014) DNA methylation of PITX2 predicts poor survival in men with prostate cancer. Biomark Med 8(9):1143–1150. doi:10.2217/bmm.14.41

    Article  CAS  PubMed  Google Scholar 

  33. Uhl B, Gevensleben H, Tolkach Y, Sailer V, Majores M, Jung M et al (2016) PITX2 DNA Methylation as Biomarker for Individualized Risk Assessment of Prostate Cancer in Core Biopsies. J Mol Diagn. doi:10.1016/j.jmoldx.2016.08.008

    PubMed  Google Scholar 

  34. Whitfield ML, Sherlock G, Saldanha AJ, Murray JI, Ball CA, Alexander KE et al (2002) Identification of genes periodically expressed in the human cell cycle and their expression in tumors. Mol Biol Cell 13(6):1977–2000. doi:10.1091/mbc.02-02-0030

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Freedland SJ, Gerber L, Reid J, Welbourn W, Tikishvili E, Park J et al (2013) Prognostic utility of cell cycle progression score in men with prostate cancer after primary external beam radiation therapy. Int J Radiat Oncol Biol Phys 86(5):848–853. doi:10.1016/j.ijrobp.2013.04.043

    Article  PubMed  PubMed Central  Google Scholar 

  36. Bishoff JT, Freedland SJ, Gerber L, Tennstedt P, Reid J, Welbourn W et al (2014) Prognostic utility of the cell cycle progression score generated from biopsy in men treated with prostatectomy. J Urol 192(2):409–414. doi:10.1016/j.juro.2014.02.003

    Article  PubMed  Google Scholar 

  37. Cuzick J, Stone S, Fisher G, Yang ZH, North BV, Berney DM et al (2015) Validation of an RNA cell cycle progression score for predicting death from prostate cancer in a conservatively managed needle biopsy cohort. Br J Cancer 113(3):382–389. doi:10.1038/bjc.2015.223

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Ross AE, D’Amico AV, Freedland SJ (2016) Which, when and why? Rational use of tissue-based molecular testing in localized prostate cancer. Prostate Cancer Prostatic Dis 19(1):1–6. doi:10.1038/pcan.2015.31

    Article  CAS  PubMed  Google Scholar 

  39. Davis JW (2015) Use of genomic markers to risk stratify men with prostate cancer. Trends Urol Mens Health 6(3):36–39. doi:10.1002/tre.461

    Article  Google Scholar 

  40. Harris L, Fritsche H, Mennel R, Norton L, Ravdin P, Taube S et al (2007) American Society of Clinical Oncology 2007 update of recommendations for the use of tumor markers in breast cancer. J Clin Oncol 25(33):5287–5312. doi:10.1200/JCO.2007.14.2364

    Article  CAS  PubMed  Google Scholar 

  41. Knezevic D, Goddard AD, Natraj N, Cherbavaz DB, Clark-Langone KM, Snable J et al (2013) Analytical validation of the Oncotype DX prostate cancer assay – a clinical RT-PCR assay optimized for prostate needle biopsies. BMC Genomics 14:690. doi:10.1186/1471-2164-14-690

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Klein EA, Cooperberg MR, Magi-Galluzzi C, Simko JP, Falzarano SM, Maddala T et al (2014) A 17-gene assay to predict prostate cancer aggressiveness in the context of Gleason grade heterogeneity, tumor multifocality, and biopsy undersampling. Eur Urol 66(3):550–560. doi:10.1016/j.eururo.2014.05.004

    Article  PubMed  Google Scholar 

  43. Cullen J, Rosner IL, Brand TC, Zhang N, Tsiatis AC, Moncur J et al (2015) 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 68(1):123–131. doi:10.1016/j.eururo.2014.11.030

    Article  PubMed  Google Scholar 

  44. Nakagawa T, Kollmeyer TM, Morlan BW, Anderson SK, Bergstralh EJ, Davis BJ et al (2008) A tissue biomarker panel predicting systemic progression after PSA recurrence post-definitive prostate cancer therapy. PLOS ONE 3(5):e2318. doi:10.1371/journal.pone.0002318

    Article  PubMed  PubMed Central  Google Scholar 

  45. Den RB, Feng FY, Showalter TN, Mishra MV, Trabulsi EJ, Lallas CD et al (2014) Genomic prostate cancer classifier predicts biochemical failure and metastases in patients after postoperative radiation therapy. Int J Radiat Oncol Biol Phys 89(5):1038–1046. doi:10.1016/j.ijrobp.2014.04.052

    Article  PubMed  PubMed Central  Google Scholar 

  46. Ross AE, Feng FY, Ghadessi M, Erho N, Crisan A, Buerki C et al (2014) A genomic classifier predicting metastatic disease progression in men with biochemical recurrence after prostatectomy. Prostate Cancer Prostatic Dis 17(1):64–69

    Article  CAS  PubMed  Google Scholar 

  47. Badani KK, Thompson DJ, Brown G, Holmes D, Kella N, Albala D et al (2015) Effect of a genomic classifier test on clinical practice decisions for patients with high-risk prostate cancer after surgery. BJU Int 115(3):419–429. doi:10.1111/bju.12789

    Article  PubMed  Google Scholar 

  48. Klein EA, Haddad Z, Yousefi K, Lam LL, Wang Q, Choeurng V et al (2016) Decipher genomic classifier measured on prostate biopsy predicts metastasis risk. Urology 90:148–152

    Article  PubMed  Google Scholar 

  49. Shipitsin M, Small C, Choudhury S, Giladi E, Friedlander S, Nardone J et al (2014) Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error. Br J Cancer 111(6):1201–1212. doi:10.1038/bjc.2014.396

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Blume-Jensen P, Berman DM, Rimm DL, Shipitsin M, Putzi M, Nifong TP et al (2015) Development and clinical validation of an in situ biopsy-based multimarker assay for risk stratification in prostate cancer. Clin Cancer Res 21(11):2591–2600. doi:10.1158/1078-0432.CCR-14-2603

    Article  CAS  PubMed  Google Scholar 

  51. Danielsen HE, Pradhan M, Novelli M (2016) Revisiting tumour aneuploidy – the place of ploidy assessment in the molecular era. Nat Rev Clin Oncol 13(5):291–304. doi:10.1038/nrclinonc.2015.208

    Article  CAS  PubMed  Google Scholar 

  52. Böcking A, Tils M, Schramm M, Dietz J, Biesterfeld S (2014) DNA-cytometric grading of prostate cancer systematic review with descriptive data analysis. Pathol Discov 2(1):7. doi:10.7243/2052-7896-2-7

    Article  Google Scholar 

  53. Sebo TJ, Cheville JC, Riehle DL, Lohse CM, Pankratz VS, Myers RP et al (2001) Predicting prostate carcinoma volume and stage at radical prostatectomy by assessing needle biopsy specimens for percent surface area and cores positive for carcinoma, perineural invasion, Gleason score, DNA ploidy and proliferation, and preoperative serum prostate specific antigen: a report of 454 cases. Cancer 91(11):2196–2204

    Article  CAS  PubMed  Google Scholar 

  54. Lorenzato M, Rey D, Durlach A, Bouttens D, Birembaut P, Staerman F (2004) DNA image cytometry on biopsies can help the detection of localized Gleason 3+3 prostate cancers. J Urol 172(4 Pt 1):1311–1313

    Article  CAS  PubMed  Google Scholar 

  55. Isharwal S, Miller MC, Epstein JI, Mangold LA, Humphreys E, Partin AW et al (2009) DNA Ploidy as surrogate for biopsy gleason score for preoperative organ versus nonorgan-confined prostate cancer prediction. Urology 73(5):1092–1097. doi:10.1016/j.urology.2008.09.060

    Article  PubMed  PubMed Central  Google Scholar 

  56. Pretorius ME, Waehre H, Abeler VM, Davidson B, Vlatkovic L, Lothe RA et al (2009) Large scale genomic instability as an additive prognostic marker in early prostate cancer. Cell Oncol 31(4):251–259. doi:10.3233/CLO-2009-0463

    CAS  PubMed  PubMed Central  Google Scholar 

  57. Tollefson MK, Karnes RJ, Kwon ED, Lohse CM, Rangel LJ, Mynderse LA et al (2014) 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 89(3):308–318. doi:10.1016/j.mayocp.2013.12.001

    Article  CAS  PubMed  Google Scholar 

  58. Lennartz M, Minner S, Brasch S, Wittmann H, Paterna L, Angermeier K et al (2016) The combination of DNA ploidy status and PTEN/6q15 deletions provides strong and independent prognostic information in prostate cancer. Clin Cancer Res 22(11):2802–2811. doi:10.1158/1078-0432.CCR-15-0635

    Article  CAS  PubMed  Google Scholar 

  59. Wei L, Wang J, Lampert E, Schlanger S, DePriest AD, Hu Q et al (2016) Intratumoral and intertumoral genomic heterogeneity of multifocal localized prostate cancer impacts molecular classifications and genomic prognosticators. Eur Urol. doi:10.1016/j.eururo.2016.07.008

    Google Scholar 

  60. Davis JW (2014) Novel commercially available genomic tests for prostate cancer: a roadmap to understanding their clinical impact. BJU Int 114(3):320–322. doi:10.1111/bju.12695

    PubMed  Google Scholar 

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Correspondence to A. Kretschmer.

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A. Kretschmer, Y. Tolkach, J. Ellinger und G. Kristiansen geben an, dass kein Interessenkonflikt besteht.

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Additional information

Redaktion

M.-O. Grimm, Jena

A. Gross, Hamburg

C.-G. Stief, München

J.-U. Stolzenburg, Leipzig

in Zusammenarbeit mit

der Akademie

der Deutschen Urologen

CME-Fragebogen

CME-Fragebogen

Welche Antwort ist richtig? Welcher der folgenden Tests ist ein Urintest?

ConfirmMDx (MDx Health, Irvine, USA)

Oncotype DX Genomic Prostate Score (Genomic Health, Redwood City, USA)

Decipher (GenomeDX, Vancouver, Kanada)

Prostate Cancer Antigen 3 (Progensa, Bedford, USA)

Prolaris (Myriad Genetics Inc., Salt Lake City, USA)

Welche Antwort ist richtig? Der Prolaris-Test (Myriad Genetics Inc., Salt Lake City, USA) beruht auf der Messung einer Gensignatur, die für welchen der folgenden zellbiologischen Prozesse bedeutsam ist?

Glukosemetabolismus

Lipolyse

Zellzyklusregulation

Phosphotidyl-3-Kinase/AKT-System

Chemotaxis

Welche Antwort ist richtig? Welcher der folgenden Gewebetests basiert auf Proteomics?

ConfirmMDx (MDx Health, Irvine, USA)

Oncotype DX Genomic Prostate Score (Genomic Health, Redwood City, USA)

Decipher (GenomeDX, Vancouver, Kanada)

ProMark (Metamark, Cambridge, USA)

Prolaris (Myriad Genetics Inc., Salt Lake City, USA)

Die Interpretation von welchem der folgenden molekularen Biomarkertests basiert auf dem sog. GPS-Score?

ConfirmMDx (MDx Health, Irvine, USA)

Oncotype DX Genomic Prostate Score (Genomic Health, Redwood City, USA)

Decipher (GenomeDX, Vancouver, Kanada)

Prostate Cancer Antigen 3 (Progensa, Bedford, USA)

Prolaris (Myriad Genetics Inc., Salt Lake City, USA)

Welche Antwort ist richtig? Welcher Biomarker beruht auf der Detektion von Deletionen oder Additionen einzelner Chromosomen?

ConfirmMDx (MDx Health, Irvine, USA)

Oncotype DX Genomic Prostate Score (Genomic Health, Redwood City, USA)

Decipher (GenomeDX, Vancouver, Kanada)

DNA-Ploidie

Prolaris (Myriad Genetics Inc., Salt Lake City, USA)

Welche Antwort ist richtig? Eine Aneuploidie wird heutzutage in der Regel mittels welcher Methode detektiert?

Polymerasekettenreaktion (PCR)

Southern Blot

Durchflusszytometrie

Cellsearch®-System

Hämatoxylin-Eosin(HE)-Färbung

Welche Antwort ist richtig? Der ConfirmMDx (MDx Health, Irvine, USA) untersucht welche molekulare Veränderung?

Hypermethylierung

Deletion

Punktmutation

Addition

Frameshift-Mutation

Welche Antwort ist richtig? Wie häufig tritt die TMPRSS2:ERG-Genfusion bei Prostatakarzinomen auf?

Ca. 5 %

Ca. 20 %

Ca. 50 %

Ca. 80 %

Ca. 100 %

Welche Antwort ist richtig? Bei welchem molekularen Biomarkertest handelt es sich um ein molekulares Korrelat einer Proliferationsmessung am Tumorgewebe?

ConfirmMDx (MDx Health, Irvine, USA)

Oncotype DX Genomic Prostate Score (Genomic Health, Redwood City, USA)

Decipher (GenomeDX, Vancouver, Kanada)

Prostate Cancer Antigen 3 (Progensa, Bedford, USA)

Prolaris (Myriad Genetics Inc., Salt Lake City, USA)

Welche Antwort ist richtig? Vor welchem molekularen Biomarkertest ist eine digital-rektale Prostatamassage obligat?

ConfirmMDx (MDx Health, Irvine, USA)

Oncotype DX Genomic Prostate Score (Genomic Health, Redwood City, USA)

Decipher (GenomeDX, Vancouver, Kanada)

Prostate Cancer Antigen 3 (Progensa, Bedford, USA)

Prolaris (Myriad Genetics Inc., Salt Lake City, USA)

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Kretschmer, A., Tolkach, Y., Ellinger, J. et al. Genetische Marker und Prognosefaktoren beim Prostatakarzinom. Urologe 56, 933–944 (2017). https://doi.org/10.1007/s00120-017-0418-0

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