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Updated: Sep 4, 2025
13:19
Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer
Published on: November 2, 2013
16.7K
Polygenic risk score in prostate cancer.
Jong Jin Oh1,2, Sung Kyu Hong1,2
1Department of Urology, Seoul National University Bundang Hospital, Seongnam.
Current Opinion in Urology
|July 20, 2022
Summary
Polygenic risk score (PRS) shows promise for predicting prostate cancer (PCa) risk. Combining PRS with clinical markers significantly improves accuracy, suggesting a valuable tool for early detection.
Area of Science:
- Genetics
- Oncology
- Biostatistics
Background:
- Polygenic risk scores (PRS) leverage genetic analysis to predict disease risk.
- Numerous studies have assessed PRS for prostate cancer (PCa) prediction.
- Development of comprehensive genetic risk models for PCa is ongoing.
Purpose of the Study:
- To review the outcomes of polygenic risk score (PRS) in predicting prostate cancer (PCa).
- To examine the clinical utility of PRS for PCa risk estimation.
Main Methods:
- Review of current literature on PRS in prostate cancer.
- Analysis of accuracy rates for PRS alone and in combination with clinical markers.
- Comparison of PRS performance across different populations (Asian vs. Western).
Main Results:
- PRS alone achieved PCa detection rates from 0.56 to 0.67.
- Models combining PRS with clinical markers showed higher accuracy (0.866-0.880).
- Initial lower accuracy in Asian populations is improving, with recent cohorts showing comparable results to Western populations.
Conclusions:
- PRS offers potential for enhanced PCa risk prediction.
- Integration of PRS with clinical markers improves predictive accuracy.
- Further development and validation of large-scale PRS models are needed for clinical application.
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