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
Related Citations
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
Related Citations
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
Related Citations
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
Related Citations
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
Related Citations
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
Related Citations
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
Related Citations
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
Related Citations