Peter J Boström1, Anders S Bjartell2, James W F Catto3, Scott E Eggener4, Hans Lilja5, Stacy Loeb6, Jack Schalken7, Thorsten Schlomm8, Matthew R Cooperberg9. 1. Department of Urology, Turku University Hospital, Turku, Finland. Electronic address: peter.j.bostrom@gmail.com. 2. Department of Urology, Skåne University Hospital Malmö, Lund University, Lund Sweden. 3. Academic Urology Unit, University of Sheffield, Sheffield, UK. 4. Section of Urology, University of Chicago, Chicago, IL, USA. 5. Departments of Laboratory Medicine, Surgery (Urology), and Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK; Institute of Biomedical Technology, University of Tampere, Tampere, Finland. 6. Department of Urology and Population Health, New York University and Manhattan Veterans Affairs Medical Center, New York, NY, USA. 7. Department of Urology, Radboud University Medical Center, Nijmegen, the Netherlands. 8. Martini-Clinic, Prostate Cancer Center, University Medical Center Hamburg-Eppendorf, Hamburg, Germany. 9. Departments of Urology and Epidemiology and Biostatistics, UCSF Helen Diller Family Comprehensive Cancer Center, San Francisco, CA, USA.
Abstract
CONTEXT: Given the highly variable behavior and clinical course of prostate cancer (PCa) and the multiple available treatment options, a personalized approach to oncologic risk stratification is important. Novel genetic approaches offer additional information to improve clinical decision making. OBJECTIVE: To review the use of genomic biomarkers in the prognostication of PCa outcome and prediction of therapeutic response. EVIDENCE ACQUISITION: Systematic literature review focused on human clinical studies reporting outcome measures with external validation. The literature search included all Medline, Embase, and Scopus articles from inception through July 2014. EVIDENCE SYNTHESIS: An improved understanding of the genetic basis of prostate carcinogenesis has produced an increasing number of potential prognostic and predictive tools, such as transmembrane protease, serine2:v-ets avian erythroblastosis virus E26 oncogene homolog (TMPRSS2:ERG) gene fusion status, loss of the phosphatase and tensin homolog (PTEN) gene, and gene expression signatures utilizing messenger RNA from tumor tissue. Several commercially available gene panels with external validation are now available, although most have yet to be widely used. The most studied commercially available gene panels, Prolaris, Oncotype DX Genomic Prostate Score, and Decipher, may be used to estimate disease outcome in addition to clinical parameters or clinical nomograms. ConfirmMDx is an epigenetic test used to predict the results of repeat prostate biopsy after an initial negative biopsy. Additional future strategies include using genetic information from circulating tumor cells in the peripheral blood to guide treatment decisions at the initial diagnosis and at subsequent decision points. CONCLUSIONS: Major advances have been made in our understanding of PCa biology in recent years. Our field is currently exploring the early stages of a personalized approach to augment traditional clinical decision making using commercially available genomic tools. A more comprehensive appreciation of value, limitations, and cost is important. PATIENT SUMMARY: We summarized current advances in genomic testing in prostate cancer with a special focus on the estimation of disease outcome. Several commercial tests are currently available, but further understanding is needed to appreciate the potential benefits and limitations of these novel tests.
CONTEXT: Given the highly variable behavior and clinical course of prostate cancer (PCa) and the multiple available treatment options, a personalized approach to oncologic risk stratification is important. Novel genetic approaches offer additional information to improve clinical decision making. OBJECTIVE: To review the use of genomic biomarkers in the prognostication of PCa outcome and prediction of therapeutic response. EVIDENCE ACQUISITION: Systematic literature review focused on human clinical studies reporting outcome measures with external validation. The literature search included all Medline, Embase, and Scopus articles from inception through July 2014. EVIDENCE SYNTHESIS: An improved understanding of the genetic basis of prostate carcinogenesis has produced an increasing number of potential prognostic and predictive tools, such as transmembrane protease, serine2:v-ets avian erythroblastosis virus E26 oncogene homolog (TMPRSS2:ERG) gene fusion status, loss of the phosphatase and tensin homolog (PTEN) gene, and gene expression signatures utilizing messenger RNA from tumor tissue. Several commercially available gene panels with external validation are now available, although most have yet to be widely used. The most studied commercially available gene panels, Prolaris, Oncotype DX Genomic Prostate Score, and Decipher, may be used to estimate disease outcome in addition to clinical parameters or clinical nomograms. ConfirmMDx is an epigenetic test used to predict the results of repeat prostate biopsy after an initial negative biopsy. Additional future strategies include using genetic information from circulating tumor cells in the peripheral blood to guide treatment decisions at the initial diagnosis and at subsequent decision points. CONCLUSIONS: Major advances have been made in our understanding of PCa biology in recent years. Our field is currently exploring the early stages of a personalized approach to augment traditional clinical decision making using commercially available genomic tools. A more comprehensive appreciation of value, limitations, and cost is important. PATIENT SUMMARY: We summarized current advances in genomic testing in prostate cancer with a special focus on the estimation of disease outcome. Several commercial tests are currently available, but further understanding is needed to appreciate the potential benefits and limitations of these novel tests.
Authors: C G Picanço-Albuquerque; C L Morais; F L F Carvalho; S B Peskoe; J L Hicks; O Ludkovski; T Vidotto; H Fedor; E Humphreys; M Han; E A Platz; A M De Marzo; D M Berman; T L Lotan; J A Squire Journal: Virchows Arch Date: 2016-02-09 Impact factor: 4.064
Authors: Shanshan Zhao; Milan S Geybels; Amy Leonardson; Rohina Rubicz; Suzanne Kolb; Qingxiang Yan; Brandy Klotzle; Marina Bibikova; Antonio Hurtado-Coll; Dean Troyer; Raymond Lance; Daniel W Lin; Jonathan L Wright; Elaine A Ostrander; Jian-Bing Fan; Ziding Feng; Janet L Stanford Journal: Clin Cancer Res Date: 2016-06-29 Impact factor: 12.531
Authors: Primo N Lara; Andreas M Heilmann; Julia A Elvin; Mamta Parikh; Ralph de Vere White; Regina Gandour-Edwards; Christopher P Evans; Chong-Xian Pan; Alexa B Schrock; Rachel Erlich; Jeffrey S Ross; Philip J Stephens; John McPherson; Vincent A Miller; Siraj M Ali Journal: JCO Precis Oncol Date: 2017-11-02
Authors: Michael Kongnyuy; Daniel M Halpern; Corinne C Liu; Kaitlin E Kosinski; David J Habibian; Anthony T Corcoran; Aaron E Katz Journal: Int Urol Nephrol Date: 2017-08-10 Impact factor: 2.370
Authors: William S Chen; Rahul Aggarwal; Li Zhang; Shuang G Zhao; George V Thomas; Tomasz M Beer; David A Quigley; Adam Foye; Denise Playdle; Jiaoti Huang; Paul Lloyd; Eric Lu; Duanchen Sun; Xiangnan Guan; Matthew Rettig; Martin Gleave; Christopher P Evans; Jack Youngren; Lawrence True; Primo Lara; Vishal Kothari; Zheng Xia; Kim N Chi; Robert E Reiter; Christopher A Maher; Felix Y Feng; Eric J Small; Joshi J Alumkal Journal: Eur Urol Date: 2019-03-28 Impact factor: 20.096
Authors: Jennifer A Freedman; Yanru Wang; Xuechan Li; Hongliang Liu; Patricia G Moorman; Daniel J George; Norman H Lee; Terry Hyslop; Qingyi Wei; Steven R Patierno Journal: Carcinogenesis Date: 2018-07-03 Impact factor: 4.944
Authors: Anqi Cheng; Shanshan Zhao; Liesel M FitzGerald; Jonathan L Wright; Suzanne Kolb; R Jeffrey Karnes; Robert B Jenkins; Elai Davicioni; Elaine A Ostrander; Ziding Feng; Jian-Bing Fan; James Y Dai; Janet L Stanford Journal: Prostate Date: 2019-08-02 Impact factor: 4.104
Authors: Kanerva Lahdensuo; Andrew Erickson; Irena Saarinen; Heikki Seikkula; Johan Lundin; Mikael Lundin; Stig Nordling; Anna Bützow; Hanna Vasarainen; Peter J Boström; Pekka Taimen; Antti Rannikko; Tuomas Mirtti Journal: Mod Pathol Date: 2016-08-26 Impact factor: 7.842