Polygenic hazard score to guide screening for aggressive prostate cancer: development and validation in large scale cohorts

Tyler M Seibert, Chun Chieh Fan, Yunpeng Wang, Verena Zuber, Roshan Karunamuni, J Kellogg Parsons, Rosalind A Eeles, Douglas F Easton, ZSofia Kote-Jarai, Ali Amin Al Olama, Sara Benlloch Garcia, Kenneth Muir, Henrik Grönberg, Fredrik Wiklund, Markus Aly, Johanna Schleutker, Csilla Sipeky, Teuvo Lj Tammela, Børge G Nordestgaard, Sune F Nielsen, Maren Weischer, Rasmus Bisbjerg, M Andreas Røder, Peter Iversen, Tim J Key, Ruth C Travis, David E Neal, Jenny L Donovan, Freddie C Hamdy, Paul Pharoah, Nora Pashayan, Kay-Tee Khaw, Christiane Maier, Walther Vogel, Manuel Luedeke, Kathleen Herkommer, Adam S Kibel, Cezary Cybulski, Dominika Wokolorczyk, Wojciech Kluzniak, Lisa Cannon-Albright, Hermann Brenner, Katarina Cuk, Kai-Uwe Saum, Jong Y Park, Thomas A Sellers, Chavdar Slavov, Radka Kaneva, Vanio Mitev, Jyotsna Batra, Judith A Clements, Amanda Spurdle, Manuel R Teixeira, Paula Paulo, Sofia Maia, Hardev Pandha, Agnieszka Michael, Andrzej Kierzek, David S Karow, Ian G Mills, Ole A Andreassen, Anders M Dale, PRACTICAL Consortium*, Tyler M Seibert, Chun Chieh Fan, Yunpeng Wang, Verena Zuber, Roshan Karunamuni, J Kellogg Parsons, Rosalind A Eeles, Douglas F Easton, ZSofia Kote-Jarai, Ali Amin Al Olama, Sara Benlloch Garcia, Kenneth Muir, Henrik Grönberg, Fredrik Wiklund, Markus Aly, Johanna Schleutker, Csilla Sipeky, Teuvo Lj Tammela, Børge G Nordestgaard, Sune F Nielsen, Maren Weischer, Rasmus Bisbjerg, M Andreas Røder, Peter Iversen, Tim J Key, Ruth C Travis, David E Neal, Jenny L Donovan, Freddie C Hamdy, Paul Pharoah, Nora Pashayan, Kay-Tee Khaw, Christiane Maier, Walther Vogel, Manuel Luedeke, Kathleen Herkommer, Adam S Kibel, Cezary Cybulski, Dominika Wokolorczyk, Wojciech Kluzniak, Lisa Cannon-Albright, Hermann Brenner, Katarina Cuk, Kai-Uwe Saum, Jong Y Park, Thomas A Sellers, Chavdar Slavov, Radka Kaneva, Vanio Mitev, Jyotsna Batra, Judith A Clements, Amanda Spurdle, Manuel R Teixeira, Paula Paulo, Sofia Maia, Hardev Pandha, Agnieszka Michael, Andrzej Kierzek, David S Karow, Ian G Mills, Ole A Andreassen, Anders M Dale, PRACTICAL Consortium*

Abstract

Objectives: To develop and validate a genetic tool to predict age of onset of aggressive prostate cancer (PCa) and to guide decisions of who to screen and at what age.

Design: Analysis of genotype, PCa status, and age to select single nucleotide polymorphisms (SNPs) associated with diagnosis. These polymorphisms were incorporated into a survival analysis to estimate their effects on age at diagnosis of aggressive PCa (that is, not eligible for surveillance according to National Comprehensive Cancer Network guidelines; any of Gleason score ≥7, stage T3-T4, PSA (prostate specific antigen) concentration ≥10 ng/L, nodal metastasis, distant metastasis). The resulting polygenic hazard score is an assessment of individual genetic risk. The final model was applied to an independent dataset containing genotype and PSA screening data. The hazard score was calculated for these men to test prediction of survival free from PCa.

Setting: Multiple institutions that were members of international PRACTICAL consortium.

Participants: All consortium participants of European ancestry with known age, PCa status, and quality assured custom (iCOGS) array genotype data. The development dataset comprised 31 747 men; the validation dataset comprised 6411 men.

Main outcome measures: Prediction with hazard score of age of onset of aggressive cancer in validation set.

Results: In the independent validation set, the hazard score calculated from 54 single nucleotide polymorphisms was a highly significant predictor of age at diagnosis of aggressive cancer (z=11.2, P<10-16). When men in the validation set with high scores (>98th centile) were compared with those with average scores (30th-70th centile), the hazard ratio for aggressive cancer was 2.9 (95% confidence interval 2.4 to 3.4). Inclusion of family history in a combined model did not improve prediction of onset of aggressive PCa (P=0.59), and polygenic hazard score performance remained high when family history was accounted for. Additionally, the positive predictive value of PSA screening for aggressive PCa was increased with increasing polygenic hazard score.

Conclusions: Polygenic hazard scores can be used for personalised genetic risk estimates that can predict for age at onset of aggressive PCa.

Conflict of interest statement

Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare no support from any organisation for the submitted work except as follows: DSK and AMD report a research grant from the US Department of Defense, OAA reports research grants from KG Jebsen Stiftelsen, Research Council of Norway, and South East Norway Health Authority, TMS reports honoraria from WebMD for educational content, as well as a research grant from Varian Medical Systems, ASK reports advisory board memberships for Sanofi-Aventis, Dendreon, and Profound, AK reports paid work for Certara Quantitative Systems Pharmacology, DSK reports paid work for Human Longevity, OAA has a patent application (US 20150356243) pending, AMD also applied for this patent application and assigned it to UC San Diego. AMD has additional disclosures outside the present work: founder, equity holder, and advisory board member for CorTechs Labs, advisory board member of Human Longevity, recipient of non-financial research support from General Electric Healthcare; no financial relationships with any companies that might have an interest in the submitted work in the previous 3 years; no other relationships or activities that could appear to have influenced the submitted work.

Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Figures

Fig 1
Fig 1
Kaplan-Meier and Cox estimates of prostate cancer-free survival for patients in development set by centile ranges of polygenic hazard score. Centiles are in reference to distribution of score within 11 190 controls aged under 70 in development set. Time of “failure” is age at any diagnosis of prostate cancer. Controls were censored at age of observation. Formal testing of proportionality is described in appendix 1
Fig 2
Fig 2
Positive predictive value of PSA testing for aggressive PCa in validation set. Centiles refer to distribution of polygenic hazard score among young controls in development set. 95% confidence intervals are from random samples of cases in validation set (see methods)
https://www.ncbi.nlm.nih.gov/pmc/articles/instance/5759091/bin/seit038395.f3.jpg

References

    1. Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A. Global cancer statistics, 2012. CA Cancer J Clin 2015;65:87-108. 10.3322/caac.21262
    1. Schröder FH, Hugosson J, Roobol MJ, et al. ERSPC Investigators 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;384:2027-35. 10.1016/S0140-6736(14)60525-0
    1. Wolf AMD, Wender RC, Etzioni RB, et al. American Cancer Society Prostate Cancer Advisory Committee American Cancer Society guideline for the early detection of prostate cancer: update 2010. CA Cancer J Clin 2010;60:70-98. 10.3322/caac.20066
    1. Horwich A, Hugosson J, de Reijke T, Wiegel T, Fizazi K, Kataja V, Panel Members. European Society for Medical Oncology Prostate cancer: ESMO Consensus Conference Guidelines 2012. Ann Oncol 2013;24:1141-62. 10.1093/annonc/mds624
    1. Qaseem A, Barry MJ, Denberg TD, Owens DK, Shekelle P, Clinical Guidelines Committee of the American College of Physicians Screening for prostate cancer: a guidance statement from the Clinical Guidelines Committee of the American College of Physicians. Ann Intern Med 2013;158:761-9. 10.7326/0003-4819-158-10-201305210-00633
    1. Eeles RA, Olama AAA, Benlloch S, et al. COGS–Cancer Research UK GWAS–ELLIPSE (part of GAME-ON) Initiative. Australian Prostate Cancer Bioresource. UK Genetic Prostate Cancer Study Collaborators/British Association of Urological Surgeons’ Section of Oncology. UK ProtecT (Prostate testing for cancer and Treatment) Study Collaborators. PRACTICAL (Prostate Cancer Association Group to Investigate Cancer-Associated Alterations in the Genome) Consortium Identification of 23 new prostate cancer susceptibility loci using the iCOGS custom genotyping array. Nat Genet 2013;45:385-91, e1-2. 10.1038/ng.2560
    1. Goh CL, Schumacher FR, Easton D, et al. Genetic variants associated with predisposition to prostate cancer and potential clinical implications. J Intern Med 2012;271:353-65. 10.1111/j.1365-2796.2012.02511.x
    1. Witte JS. Personalized prostate cancer screening: improving PSA tests with genomic information. Sci Transl Med 2010;2:62ps55. 10.1126/scitranslmed.3001861
    1. Chatterjee N, Shi J, García-Closas M. Developing and evaluating polygenic risk prediction models for stratified disease prevention. Nat Rev Genet 2016;17:392-406.. 10.1038/nrg.2016.27
    1. Pharoah PDP, Antoniou AC, Easton DF, Ponder BAJ. Polygenes, risk prediction, and targeted prevention of breast cancer. N Engl J Med 2008;358:2796-803. 10.1056/NEJMsa0708739
    1. Pashayan N, Duffy SW, Chowdhury S, et al. Polygenic susceptibility to prostate and breast cancer: implications for personalised screening. Br J Cancer 2011;104:1656-63. 10.1038/bjc.2011.118
    1. Lane JA, Donovan JL, Davis M, et al. ProtecT study group Active monitoring, radical prostatectomy, or radiotherapy for localised prostate cancer: study design and diagnostic and baseline results of the ProtecT randomised phase 3 trial. Lancet Oncol 2014;15:1109-18. 10.1016/S1470-2045(14)70361-4
    1. Loeb S, Bjurlin MA, Nicholson J, et al. Overdiagnosis and overtreatment of prostate cancer. Eur Urol 2014;65:1046-55. 10.1016/j.eururo.2013.12.062
    1. Mohler JL, Armstrong AJ, Bahnson RR, et al. Prostate Cancer, Version 1.2016. J Natl Compr Canc Netw 2016;14:19-30. 10.6004/jnccn.2016.0004
    1. Desikan RS, Fan CC, Wang Y, et al. Personalized genetic assessment of age associated Alzheimers disease risk: Development and validation of a polygenic hazard score. PLoS Med 2016;14:e1002289 10.1371/journal.pmed.1002258
    1. Eeles R, Goh C, Castro E, et al. The genetic epidemiology of prostate cancer and its clinical implications. Nat Rev Urol 2014;11:18-31. 10.1038/nrurol.2013.266
    1. Fleshner NE, Lucia MS, Egerdie B, et al. Dutasteride in localised prostate cancer management: the REDEEM randomised, double-blind, placebo-controlled trial. Lancet 2012;379:1103-11. 10.1016/S0140-6736(11)61619-X
    1. Hamdy FC, Donovan JL, Lane JA, et al. ProtecT Study Group 10-Year Outcomes after Monitoring, Surgery, or Radiotherapy for Localized Prostate Cancer. N Engl J Med 2016;375:1415-24. 10.1056/NEJMoa1606220
    1. Pashayan N, Pharoah P, Neal DE, et al. PSA-detected prostate cancer and the potential for dedifferentiation--estimating the proportion capable of progression. Int J Cancer 2011;128:1462-70. 10.1002/ijc.25471
    1. Gastwirth JL. A General Definition of the Lorenz Curve. Econometrica 1971;39:1037-9 10.2307/1909675.
    1. Vickers AJ, Cronin AM, Björk T, et al. Prostate specific antigen concentration at age 60 and death or metastasis from prostate cancer: case-control study. BMJ 2010;341:c4521. 10.1136/bmj.c4521
    1. Vickers AJ, Ulmert D, Sjoberg DD, et al. Strategy for detection of prostate cancer based on relation between prostate specific antigen at age 40-55 and long term risk of metastasis: case-control study. BMJ 2013;346:f2023. 10.1136/bmj.f2023
    1. Amin Al Olama A, Benlloch S, Antoniou AC, et al. UK Genetic Prostate Cancer Study Collaborators/British Association of Urological Surgeons’ Section of Oncology. UK ProtecT Study Collaborators. PRACTICAL Consortium Risk Analysis of Prostate Cancer in PRACTICAL, a Multinational Consortium, Using 25 Known Prostate Cancer Susceptibility Loci. Cancer Epidemiol Biomarkers Prev 2015;24:1121-9. 10.1158/1055-9965.EPI-14-0317
    1. Pashayan N, Duffy SW, Neal DE, et al. Implications of polygenic risk-stratified screening for prostate cancer on overdiagnosis. Genet Med 2015;17:789-95. 10.1038/gim.2014.192
    1. Mikropoulos C, Goh C, Leongamornlert D, Kote-Jarai Z, Eeles R. Translating genetic risk factors for prostate cancer to the clinic: 2013 and beyond. Future Oncol 2014;10:1679-94. 10.2217/fon.14.72
    1. Thompson IM, Ankerst DP, Chi C, et al. Assessing prostate cancer risk: results from the Prostate Cancer Prevention Trial. J Natl Cancer Inst 2006;98:529-34. 10.1093/jnci/djj131
    1. Kranse R, Roobol M, Schröder FH. A graphical device to represent the outcomes of a logistic regression analysis. Prostate 2008;68:1674-80. 10.1002/pros.20840
    1. Kader AK, Sun J, Reck BH, et al. Potential impact of adding genetic markers to clinical parameters in predicting prostate biopsy outcomes in men following an initial negative biopsy: findings from the REDUCE trial. Eur Urol 2012;62:953-61. 10.1016/j.eururo.2012.05.006
    1. Lilja H, Ulmert D, Björk T, et al. Long-term prediction of prostate cancer up to 25 years before diagnosis of prostate cancer using prostate kallikreins measured at age 44 to 50 years. J Clin Oncol 2007;25:431-6. 10.1200/JCO.2006.06.9351
    1. Loeb S, Carter HB, Catalona WJ, Moul JW, Schroder FH. Baseline prostate-specific antigen testing at a young age. Eur Urol 2012;61:1-7. 10.1016/j.eururo.2011.07.067
    1. Preston MA, Batista JL, Wilson KM, et al. Baseline Prostate-Specific Antigen Levels in Midlife Predict Lethal Prostate Cancer. J Clin Oncol 2016;34:2705-11. 10.1200/JCO.2016.66.7527
    1. Carroll PR, Parsons JK, Andriole G, et al. NCCN Guidelines Insights: Prostate Cancer Early Detection, Version 2.2016. J Natl Compr Canc Netw 2016;14:509-19. 10.6004/jnccn.2016.0060
    1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2016. CA Cancer J Clin 2016;66:7-30. 10.3322/caac.21332
    1. Siegel R, Ward E, Brawley O, Jemal A. Cancer statistics, 2011: the impact of eliminating socioeconomic and racial disparities on premature cancer deaths. CA Cancer J Clin 2011;61:212-36. 10.3322/caac.20121
    1. Jemal A, Siegel R, Ward E, et al. Cancer statistics, 2006. CA Cancer J Clin 2006;56:106-30. 10.3322/canjclin.56.2.106
    1. Greenlee RT, Hill-Harmon MB, Murray T, Thun M. Cancer statistics, 2001. CA Cancer J Clin 2001;51:15-36. 10.3322/canjclin.51.1.15

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