Skip to main content

Advertisement

Log in

CANCER SCREENING

Improving breast cancer risk prediction with epigenetic risk factors

  • News & Views
  • Published:

From Nature Reviews Clinical Oncology

View current issue Sign up to alerts

Over the past decade, iterative improvements to models predicting breast cancer risk have primarily come from new information about genetic risk factors and improvements to mammogram-based risk scores. Epigenetic risk factors offer some potential to further improve risk stratification. However, the recently developed DNA methylation score (the WID-BC index) is not yet convincing for predicting breast cancer risk.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

References

  1. Mavaddat, N. et al. Polygenic risk scores for prediction of breast cancer and breast cancer subtypes. Am. J. Hum. Genet. 104, 21–34 (2019).

    Article  CAS  Google Scholar 

  2. Nguyen, T. L. et al. Novel mammogram-based measures improve breast cancer risk prediction beyond an established mammographic density measure. Int. J. Cancer 148, 2193–2202 (2021).

    Article  CAS  Google Scholar 

  3. Lee, A. et al. BOADICEA: a comprehensive breast cancer risk prediction model incorporating genetic and nongenetic risk factors. Genet. Med. 21, 1708–1718 (2019).

    Article  Google Scholar 

  4. Li, S. X. et al. Prospective evaluation of the addition of polygenic risk scores to breast cancer risk models. JNCI Cancer Spectr. 5, pkab021 (2021).

    Article  Google Scholar 

  5. Wong, E. M., Southey, M. C. & Terry, M. B. Integrating DNA methylation measures to improve clinical risk assessment: are we there yet? The case of BRCA1 methylation marks to improve clinical risk assessment of breast cancer. Br. J. Cancer 122, 1133–1140 (2020).

    Article  CAS  Google Scholar 

  6. Joo, J. E. et al. Heritable DNA methylation marks associated with susceptibility to breast cancer. Nat. Commun. 9, 867 (2018).

    Article  Google Scholar 

  7. Li, S., Ye, Z., kConFab Investigators, Hopper J. L. & Southey M. C. in Twin and Family Studies of Epigenetics (eds Li, S. & Hopper, J. L.) 67–83 (Academic, 2021).

  8. Kresovich, J. K. et al. Blood DNA methylation profiles improve breast cancer prediction. Mol. Oncol. 16, 42–53 (2022).

    Article  Google Scholar 

  9. Barrett, J. E. et al. The WID-BC-index identifies women with primary poor prognostic breast cancer based on DNA methylation in cervical samples. Nat. Commun. 13, 449 (2022).

    Article  CAS  Google Scholar 

  10. Hopper, J. L., Nguyen, T. L. & Li, S. Blood DNA methylation score predicts breast cancer risk: applying OPERA in molecular, environmental, genetic and analytic epidemiology. Mol. Oncol. 16, 8–10 (2022).

    Article  Google Scholar 

Download references

Acknowledgements

The authors thank J. Hopper and S. Li at the University of Melbourne for their helpful discussions whilst preparing this article.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Melissa C. Southey.

Ethics declarations

Competing interests

The authors declare no competing interests.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Southey, M.C., Dugué, PA. Improving breast cancer risk prediction with epigenetic risk factors. Nat Rev Clin Oncol 19, 363–364 (2022). https://doi.org/10.1038/s41571-022-00622-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41571-022-00622-4

  • Springer Nature Limited

Navigation