Year: 2022
Type: article
Study design: Observational Study
Abstract: Polygenic risk scores (PRS) for prostate cancer incidence have been proposed to optimize prostate cancer screening. Prediction of lethal prostate cancer is key to any stratified screening program to avoid excessive overdiagnosis. Herein, PRS for incident prostate cancer was evaluated in two population-based cohorts of unscreened middle-aged men linked to cancer and death registries: the Västerbotten Intervention Project (VIP) and the Malmö Diet and Cancer study (MDC). SNP genotypes were measured by genome-wide SNP genotyping by array followed by imputation or genotyping of selected SNPs using mass spectrometry. The ability of PRS to predict lethal prostate cancer was compared to PSA and a commercialized pre-specified model based on four kallikrein markers. The PRS was associated with incident prostate cancer, replicating previously reported relative risks, and was also associated with prostate cancer death. However, unlike PSA, the PRS did not show stronger association with lethal disease: the hazard ratio for prostate cancer incidence vs. prostate cancer metastasis and death was 1.69 vs. 1.65 in VIP and 1.25 vs. 1.25 in MDC. PSA was a much stronger predictor of prostate cancer metastasis or death with an area-under-the-curve of 0.78 versus 0.63 for the PRS. Importantly, addition of PRS to PSA did not contribute additional risk stratification for lethal prostate cancer. We have shown that a PRS that predicts prostate cancer incidence does not have utility above and beyond that of PSA measured at baseline when applied to the clinically relevant endpoint of prostate cancer death. These findings have implications for public health policies for delivery of prostate cancer screening. Focusing polygenic risk scores on clinically significant endpoints such as prostate cancer metastasis or death would likely improve clinical utility.
Source: npj Precision Oncology
Institutions: Icahn School of Medicine at Mount Sinai, Memorial Sloan Kettering Cancer Center, University of California, Los Angeles, Broad Center, UCLA Jonsson Comprehensive Cancer Center, Karolinska University Hospital, Uppsala University, Umeå University, Lund University, Uppsala University Hospital, Skåne University Hospital
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,390
Funders: U.S. Department of Health and Human Services, Prostate Cancer Foundation, Memorial Sloan-Kettering Cancer Center, Icahn School of Medicine at Mount Sinai, Cancerfonden, Vetenskapsrådet, National Institutes of Health, Centers for Disease Control and Prevention, Sidney Kimmel Center for Prostate and Urologic Cancers, NIH Office of the Director, National Cancer Institute
Awards: G1007166040, G128850485, G1696708022, G1901299981, G1970601448, G2051006376, G2348840809, G2542880440, G2702338508, G2849661646, G289723095, G3159197574, Transforming Genomics with 5 PB Big Omics Data Engine Cray CS300-AC Supercomputer, G3407543945, G3606906554, G3807074232, G393989436, Big Omics Data Engine 2 Supercomputer, G4102770861, Genetic Predictors of Prostate Cancer Survival, G5374026869, Identification and validation of non-invasive biomarkers for prostate cancer progression, Improving prostate cancer screening by integration of SNPs with blood biomarkers, G6457718916, G6771167223, G7205063868, COVID and Translational Science supercomputer (CATS), G811166696, G861748693, G8635422303, G9000003249, Cancer Center Support Grant, SPORE in Prostate Cancer, G969222351
OpenAlex ID: W4223567842