Prostate-specific antigen (PSA) screening for prostate cancer remains controversial because it increases overdiagnosis and overtreatment of clinically insignificant tumors. Accounting for genetic determinants of constitutive, non-cancer-related PSA variation has potential to improve screening utility. In this study, we discovered 128 genome-wide significant associations (P < 5 × 10-8) in a multi-ancestry meta-analysis of 95,768 men and developed a PSA polygenic score (PGSPSA) that explains 9.61% of constitutive PSA variation. We found that, in men of European ancestry, using PGS-adjusted PSA would avoid up to 31% of negative prostate biopsies but also result in 12% fewer biopsies in patients with prostate cancer, mostly with Gleason score <7 tumors. Genetically adjusted PSA was more predictive of aggressive prostate cancer (odds ratio (OR) = 3.44, P = 6.2 × 10-14, area under the curve (AUC) = 0.755) than unadjusted PSA (OR = 3.31, P = 1.1 × 10-12, AUC = 0.738) in 106 cases and 23,667 controls. Compared to a prostate cancer PGS alone (AUC = 0.712), including genetically adjusted PSA improved detection of aggressive disease (AUC = 0.786, P = 7.2 × 10-4). Our findings highlight the potential utility of incorporating PGS for personalized biomarkers in prostate cancer screening.
Nature medicine. 2023 Jun 01 [Epub ahead of print]
Linda Kachuri, Thomas J Hoffmann, Yu Jiang, Sonja I Berndt, John P Shelley, Kerry R Schaffer, Mitchell J Machiela, Neal D Freedman, Wen-Yi Huang, Shengchao A Li, Ryder Easterlin, Phyllis J Goodman, Cathee Till, Ian Thompson, Hans Lilja, Stephen K Van Den Eeden, Stephen J Chanock, Christopher A Haiman, David V Conti, Robert J Klein, Jonathan D Mosley, Rebecca E Graff, John S Witte
Department of Epidemiology & Biostatistics, University of California, San Francisco, San Francisco, CA, USA., Department of Epidemiology & Population Health, Stanford University School of Medicine, Stanford, CA, USA., Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA., Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA., Vanderbilt-Ingram Cancer Center, Nashville, TN, USA., Biological and Medical Informatics, University of California, San Francisco, San Francisco, CA, USA., Fred Hutchinson Cancer Research Center, Seattle, WA, USA., SWOG Statistics and Data Management Center, Fred Hutchinson Cancer Research Center, Seattle, WA, USA., CHRISTUS Santa Rosa Medical Center Hospital, San Antonio, TX, USA., Departments of Laboratory Medicine, Surgery and Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA., Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA., Center for Genetic Epidemiology, Department of Population and Preventive Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA., Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA., Department of Epidemiology & Biostatistics, University of California, San Francisco, San Francisco, CA, USA. ., Department of Epidemiology & Biostatistics, University of California, San Francisco, San Francisco, CA, USA. .