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Grant Details

Grant Number: 2R01CA241410-06 Interpret this number
Primary Investigator: Witte, John
Organization: Stanford University
Project Title: Precision Prostate Cancer Screening with Genetically Adjusted Prostate-Specific Antigen Levels
Fiscal Year: 2025


Abstract

Abstract Prostate-specific antigen (PSA) screening is controversial because it can lead to overdiagnosis and overtreatment of prostate cancer when individuals have high PSA levels for reasons other than aggressive disease. It is thus important to ask the question how PSA screening can be improved. Preliminary evidence from our team suggests that the incorporation of genetic factors into PSA screening decisions has tremendous potential. During the initial funding period of this project, we have had great success showing that accounting for genetic factors that impact constitutive, non-cancer PSA levels results in a test that ascertains more clinically relevant, aggressive disease. In parallel, we have shown that genetic factors for PSA can also be used to improve polygenic risk scores (PRS) for prostate cancer. Existing PRS are strongly predictive of prostate cancer risk, but they do not specifically predict aggressive disease because they were largely developed in men with PSA screen- detected, lower-risk disease. We have initial results demonstrating that removing PSA genetic factors from prostate cancer PRS makes the PRS more predictive of aggressive disease. Additional studies are needed to clarify how best to adjust for PSA genetics to improve screening, to develop a prostate cancer PRS that is even more predictive of aggressive disease by removing additional PSA variants, and to assess the clinical utility of these tools. In this renewal, we propose to tackle these outstanding imperatives with a comprehensive project leveraging data from 13 studies ranging from large-scale biobanks to unique clinical populations (N > 500K). In Aim 1, we will further advance our understanding of PSA genetics by identifying novel rare and common PSA variants and undertaking functional studies of epigenomic features and single-cell expression quantitative loci. We will then use this information to develop more accurate and personalized genetic adjustment of PSA levels. In Aim 2, we will develop a new PRS for prostate cancer aggressiveness by filtering out PC risk variants that are also associated with non-cancer PSA. We will first remove PSA variants from the prostate cancer PRS based on statistical significance. Then we will develop and apply a novel hierarchical modeling genome-wide approach that incorporates PSA associations and functional information. In Aim 3, we will determine the clinical utility of incorporating genetically adjusted PSA levels and the PRS for aggressive prostate cancer into validated risk calculators for biopsy outcomes (higher grade disease) and prostate cancer active surveillance upgrading. We will also investigate the relationships between genetically adjusted PSA, the aggressive prostate cancer PRS, and lethal prostate cancer. These models will allow us to assess the benefit of incorporating genetic information into decisions about frequency of screening, escalation to prostate biopsy, and selection of active surveillance following diagnosis. Our renewal aims in aggregate are promising toward reducing PSA screening harms while improving screening benefits and predicting risk of clinically important disease. In translation, clinicians and patients could make more informed decisions, reducing unnecessary procedures and improving outcomes.



Publications

Genome-wide association study of prostate-specific antigen levels in 392,522 men identifies new loci and improves prediction across ancestry groups.
Authors: Hoffmann T.J. , Graff R.E. , Madduri R.K. , Rodriguez A.A. , Cario C.L. , Feng K. , Jiang Y. , Wang A. , Klein R.J. , Pierce B.L. , et al. .
Source: Nature Genetics, 2025 Feb; 57(2), p. 334-344.
EPub date: 2025-02-10 00:00:00.0.
PMID: 39930085
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Principles and methods for transferring polygenic risk scores across global populations.
Authors: Kachuri L. , Chatterjee N. , Hirbo J. , Schaid D.J. , Martin I. , Kullo I.J. , Kenny E.E. , Pasaniuc B. , Polygenic Risk Methods in Diverse Populations (PRIMED) Consortium Methods Working Group , Witte J.S. , et al. .
Source: Nature Reviews. Genetics, 2024 Jan; 25(1), p. 8-25.
EPub date: 2023-08-24 00:00:00.0.
PMID: 37620596
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Clinical consequences of a genetic predisposition toward higher benign prostate-specific antigen levels.
Authors: Shi M. , Shelley J.P. , Schaffer K.R. , Tosoian J.J. , Bagheri M. , Witte J.S. , Kachuri L. , Mosley J.D. .
Source: Ebiomedicine, 2023-10-19 00:00:00.0; 97, p. 104838.
EPub date: 2023-10-19 00:00:00.0.
PMID: 37865044
Related Citations

Genetically adjusted PSA levels for prostate cancer screening.
Authors: Kachuri L. , Hoffmann T.J. , Jiang Y. , Berndt S.I. , Shelley J.P. , Schaffer K.R. , Machiela M.J. , Freedman N.D. , Huang W.Y. , Li S.A. , et al. .
Source: Nature Medicine, 2023-06-01 00:00:00.0; , .
EPub date: 2023-06-01 00:00:00.0.
PMID: 37264206
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Transcriptome-Wide Association Analysis Identifies Novel Candidate Susceptibility Genes for Prostate-Specific Antigen Levels in Men Without Prostate Cancer.
Authors: Chen D.M. , Dong R. , Kachuri L. , Hoffmann T. , Jiang Y. , Berndt S.I. , Shelley J.P. , Schaffer K.R. , Machiela M.J. , Freedman N.D. , et al. .
Source: Medrxiv : The Preprint Server For Health Sciences, 2023-05-05 00:00:00.0; , .
EPub date: 2023-05-05 00:00:00.0.
PMID: 37205487
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A Polygenic Risk Score for Prostate Cancer Risk Prediction.
Authors: Schaffer K.R. , Shi M. , Shelley J.P. , Tosoian J.J. , Kachuri L. , Witte J.S. , Mosley J.D. .
Source: Jama Internal Medicine, 2023-04-01 00:00:00.0; 183(4), p. 386-388.
PMID: 36877498
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Association of Prostate-Specific Antigen Levels with Prostate Cancer Risk in a Multiethnic Population: Stability over Time and Comparison with Polygenic Risk Score.
Authors: Chou A. , Darst B.F. , Wilkens L.R. , Le Marchand L. , Lilja H. , Conti D.V. , Haiman C.A. .
Source: Cancer Epidemiology, Biomarkers & Prevention : A Publication Of The American Association For Cancer Research, Cosponsored By The American Society Of Preventive Oncology, 2022-09-20 00:00:00.0; , .
EPub date: 2022-09-20 00:00:00.0.
PMID: 36126957
Related Citations

Inclusion of variants discovered from diverse populations improves polygenic risk score transferability.
Authors: Cavazos T.B. , Witte J.S. .
Source: Hgg Advances, 2021-01-14 00:00:00.0; 2(1), .
EPub date: 2020-12-02 00:00:00.0.
PMID: 33564748
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Sign-based Shrinkage Based on an Asymmetric LASSO Penalty.
Authors: Kawaguchi E.S. , Darst B.F. , Wang K. , Conti D.V. .
Source: Journal Of Data Science : Jds, 2021; 19(3), p. 429-449.
EPub date: 2021-06-02 00:00:00.0.
PMID: 35222618
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A large-scale association study detects novel rare variants, risk genes, functional elements, and polygenic architecture of prostate cancer susceptibility.
Authors: Emami N.C. , Cavazos T.B. , Rashkin S.R. , Graff R.E. , Tai C.G. , Mefford J.A. , Kachuri L. , Cario C.L. , Wan E. , Wong S. , et al. .
Source: Cancer Research, 2020-12-08 00:00:00.0; , .
EPub date: 2020-12-08 00:00:00.0.
PMID: 33293427
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