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Breast cancer polygenic risk scores are associated with short-term risk of poor prognosis breast cancer

Breast Cancer Research and Treatment volume 196, pages 389–398 (2022)Cite this article

Abstract

Purpose

Polygenic risk scores (PRS) for breast cancer may help guide screening decisions. However, few studies have examined whether PRS are associated with risk of short-term or poor prognosis breast cancers. The study purpose was to evaluate the association of the 313 SNP breast cancer PRS with 2-year risk of poor prognosis breast cancer.

Methods

We evaluated the association of breast cancer PRS with breast cancer overall, ER + and ER- breast cancer, and poor prognosis breast cancer diagnosed within 2 years of a negative mammogram among a cohort of 3657 women using logistic regression adjusted for age, breast density, race/ethnicity, year of screening, and genetic ancestry principal components. Breast cancers were considered poor prognosis if they were metastatic, positive lymph nodes, ER/PR + HER2− and > 2 cm, ER/PR/HER2−, or HER2 + and > 1 cm.

Results

Of the 308 breast cancers, 137 (44%) were poor prognosis. The overall breast cancer PRS was significantly associated with breast cancer diagnosis within 2 years (OR 1.39, 95% CI 1.23–1.57, p < 0.001). The breast cancer PRS was also associated specifically with diagnosis of poor prognosis disease (OR 1.24, 95% CI 1.03–1.49, p = 0.018), but was more strongly associated with good prognosis cancer (OR 1.52 95% CI 1.29–1.80 p = 3.60 × 10–7) The ER + PRS was significantly associated with ER/PR + breast cancer (OR 1.41, 95% CI 1.24–1.61, p < 0.001) and the ER− PRS was significantly associated with ER− breast cancer (OR 1.48, 95% CI 1.08–2.02, p = 0.015).

Conclusion

Breast cancer PRS was independently and significantly associated with diagnosis of both breast cancer overall and poor prognosis breast cancer within 2 years of a negative mammogram, suggesting PRS may help guide decisions about screening intervals and supplemental screening.

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Fig.1

Data availability

The datasets generated during and/or analyzed during the current study are not publicly available due to patient privacy protections, but de-identified data are available from the corresponding author on reasonable request and with institutional approval.

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Funding

This work was supported by the Susan G. Komen Foundation (PI McCarthy CCR17480662).

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Authors and Affiliations

  1. Department of Biostatistics Epidemiology and Informatics, University of Pennsylvania School of Medicine, 423 Guardian Drive, Philadelphia, PA, 19104, USA

    Anne Marie McCarthy

  2. Massachusetts General Hospital, Boston, MA, USA

    Alisa K. Manning, Sarah Hsu, Beverly Moy & Constance D. Lehman

  3. Metabolism Program, Broad Institute, Cambridge, MA, USA

    Alisa K. Manning

  4. Department of Medicine, Harvard Medical School, Boston, MA, USA

    Alisa K. Manning

  5. Draper Laboratory, Cambridge, MA, USA

    Michaela Welch

  6. Columbia University Irving Medical Center, New York, NY, USA

    Katrina Armstrong

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  1. Anne Marie McCarthy
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Correspondence to Anne Marie McCarthy.

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Conflict of interest

Dr. Lehman reports that her institution, Massachusetts General Hospital, receives research support from GE Healthcare and Hologic, Inc. and that she is a co-founder and serves as a consultant to Clairity, Inc. The other authors report no conflicts of interest.

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The authors confirm that human research participants provided informed consent for their genetic information and data to be used for research purposes.

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Appendix

Appendix

See Tables 5, 6, 7, 8, and 9.

Table 5 Recruitment of breast cancer cases for DNA analysis
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Table 6 Comparison of full cohort and analytic sample by case status
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Table 7 Sensitivity analyses: logistic regression of PRS and cancer diagnosis within 2 years of a negative mammogram, overall, by prognosis, and by ER status among women aged 40–74
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Table 8 Comparison of models additionally adjusted for body mass index (BMI) as a continuous or categorical variable
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Table 9 Comparison of models adjusting for race/ethnicity and PCs
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McCarthy, A.M., Manning, A.K., Hsu, S. et al. Breast cancer polygenic risk scores are associated with short-term risk of poor prognosis breast cancer. Breast Cancer Res Treat 196, 389–398 (2022). https://doi.org/10.1007/s10549-022-06739-5

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Keywords

  • Breast cancer
  • Polygenic risk score
  • Poor prognosis