Genetically adjusted PSA levels for prostate cancer screening

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

doi:10.1038/s41591-023-02277-9

Genetically adjusted PSA levels for prostate cancer screening

Nat Med. 2023 Jun;29(6):1412-1423. doi: 10.1038/s41591-023-02277-9. Epub 2023 Jun 1.

Authors

Linda Kachuri^{1

2

3}, Thomas J Hoffmann^{1

4}, Yu Jiang², Sonja I Berndt⁵, John P Shelley⁶, Kerry R Schaffer⁷, Mitchell J Machiela⁵, Neal D Freedman⁵, Wen-Yi Huang⁵, Shengchao A Li⁵, Ryder Easterlin⁸, Phyllis J Goodman⁹, Cathee Till¹⁰, Ian Thompson¹¹, Hans Lilja^{12

13}, Stephen K Van Den Eeden¹⁴, Stephen J Chanock⁵, Christopher A Haiman^{15

16}, David V Conti^{15

16}, Robert J Klein¹⁷, Jonathan D Mosley^{6

18}, Rebecca E Graff¹⁹, John S Witte^{20

21

22

23}

Affiliations

¹ Department of Epidemiology & Biostatistics, University of California, San Francisco, San Francisco, CA, USA.
² Department of Epidemiology & Population Health, Stanford University School of Medicine, Stanford, CA, USA.
³ Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA.
⁴ Institute of Human Genetics, University of California, San Francisco, San Francisco, CA, USA.
⁵ Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA.
⁶ Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.
⁷ Vanderbilt-Ingram Cancer Center, Nashville, TN, USA.
⁸ Biological and Medical Informatics, University of California, San Francisco, San Francisco, CA, USA.
⁹ Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
¹⁰ SWOG Statistics and Data Management Center, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
¹¹ CHRISTUS Santa Rosa Medical Center Hospital, San Antonio, TX, USA.
¹² Departments of Laboratory Medicine, Surgery and Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
¹³ Department of Translational Medicine, Lund University, Skåne University Hospital, Malmö, Sweden.
¹⁴ Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA.
¹⁵ Center for Genetic Epidemiology, Department of Population and Preventive Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
¹⁶ Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
¹⁷ Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
¹⁸ Department of Internal Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
¹⁹ Department of Epidemiology & Biostatistics, University of California, San Francisco, San Francisco, CA, USA. Rebecca.Graff@ucsf.edu.
²⁰ Department of Epidemiology & Biostatistics, University of California, San Francisco, San Francisco, CA, USA. jswitte@stanford.edu.
²¹ Department of Epidemiology & Population Health, Stanford University School of Medicine, Stanford, CA, USA. jswitte@stanford.edu.
²² Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA. jswitte@stanford.edu.
²³ Departments of Biomedical Data Science and Genetics, Stanford University, Stanford, CA, USA. jswitte@stanford.edu.

Abstract

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 (PGS_PSA) 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.

Publication types

Meta-Analysis

MeSH terms

Biopsy
Early Detection of Cancer
Humans
Male
Neoplasm Grading
Prostate-Specific Antigen / genetics
Prostatic Neoplasms* / diagnosis
Prostatic Neoplasms* / genetics
Prostatic Neoplasms* / pathology

Substances

Prostate-Specific Antigen

Abstract

Publication types

MeSH terms

Substances

Grants and funding