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Published on: October 11, 2019
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Polygenic scores in cancer.
Xin Yang1, Siddhartha Kar2,3, Antonis C Antoniou1
1Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Nature Reviews. Cancer
|July 21, 2023
Summary
Polygenic scores (PGSs) combine many common genetic variants to improve cancer risk prediction. Research shows PGSs can be clinically useful for stratifying cancer risk, despite current challenges.
Area of Science:
- Genetics
- Oncology
- Biostatistics
Background:
- Thousands of common cancer risk alleles identified since 2007.
- Individual genetic variants offer small, clinically insignificant cancer risk.
- Polygenic scores (PGSs) aggregate effects of multiple variants for greater risk discrimination.
Purpose of the Study:
- Review 15 years of research on PGS development for cancer.
- Evaluate statistical methods and applications in genome-wide association studies.
- Assess predictive performance and clinical utility challenges of cancer PGSs.
Main Methods:
- Review of statistical methods for PGS development.
- Application of PGSs in large-scale genome-wide association studies for various cancers.
- Analysis of predictive performance and limitations of existing cancer PGSs.
Main Results:
- PGSs demonstrate potential for clinically useful cancer risk stratification.
- Significant research efforts have advanced PGS methodology over 15 years.
- Challenges remain for widespread clinical integration of cancer PGSs.
Conclusions:
- PGSs are emerging as valuable tools for cancer risk prediction.
- Integration into multifactorial models is beginning for clinical trials and implementation.
- Continued research is needed to overcome limitations and enhance clinical application.
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