Multigene assessment of genetic risk for women for two or more breast cancers

Abstract

Purpose

The prevalence, penetrance, and spectrum of pathogenic variants that predispose women to two or more breast cancers is largely unknown.

Methods

We queried clinical and genetic data from women with one or more breast cancer diagnosis who received multigene panel testing between 2013 and 2018. Clinical data were obtained from provider-completed test request forms. For each gene on the panel, a multivariable logistic regression model was constructed to test for association with risk of multiple breast cancer diagnoses. Models accounted for age of diagnosis, personal and family cancer history, and ancestry. Results are reported as odds ratios (ORs) with 95% confidence intervals (CIs).

Results

This study included 98,979 patients: 88,759 (89.7%) with a single breast cancer and 10,220 (10.3%) with ≥ 2 breast cancers. Of women with two or more breast cancers, 13.2% had a pathogenic variant in a cancer predisposition gene compared to 9.4% with a single breast cancer. BRCA1, BRCA2, CDH1, CHEK2, MSH6, PALB2, PTEN, and TP53 were significantly associated with two or more breast cancers, with ORs ranging from 1.35 for CHEK2 to 3.80 for PTEN. Overall, pathogenic variants in all breast cancer risk genes combined were associated with both metachronous (OR 1.65, 95% CI 1.53–1.79, p = 7.2 × 10–33) and synchronous (OR 1.33, 95% CI 1.19–1.50, p = 2.4 × 10–6) breast cancers.

Conclusions

This study demonstrated that several high and moderate penetrance breast cancer susceptibility genes are associated with ≥ 2 breast cancers, affirming the association of two or more breast cancers with diverse genetic etiologies.

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Data availability

The data generated during clinical testing and analyzed during the current study are not publicly available in order to protect the privacy of patients/tested individuals, but are available from the corresponding author on reasonable request.

Code Availability

All analyses were conducted using R version 3.5.2. or SAS version 9.2 or higher. Request for code availability can be made to the authors and will be provided upon reasonable request.

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Acknowledgements

The authors would like to thank Kevin Tsang for his assistance with manuscript preparation, Brenda Rubalcaba for figure development, and Eric Rosenthal for his editorial contributions.

Funding

Dr. Weitzel was supported in part by the Breast Cancer Research Foundation, the American Society of Clinical Oncology Conquer Cancer® Research Professorship in Breast Cancer Disparities, the Dr. Norman & Melinda Payson Professorship in Medical Oncology, and NCI grant R01CA242218. Dr. Slavin was supported in part by NCI grant K08CA234394. The research reported in this publication also included work performed in the Biostatistical Core supported by the National Cancer Institute of the National Institutes of Health (NIH) under grant number P30CA033572. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

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Contributions

All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by John Kidd, Ryan Bernhisel, and Elisha Hughes. The first draft of the manuscript was written by Jeffrey Weitzel and all authors commented on subsequent versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Jeffrey N. Weitzel.

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Conflict of interest

Authors JK, RB, DT, KM, KS, KB, AG, EH, SC, JS and TS were employees of Myriad Genetics at the time of manuscript preparation and had stock options. JNW received speaker fees from AstraZeneca. No other authors have any conflict of interest to disclose.

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All individuals provided consent for clinical testing, and testing data were de-identified for analysis.

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All individuals provided consent for clinical testing, and testing data were de-identified for analysis.

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All authors have provided consent for the manuscript to be submitted for review and publication in the journal Breast Cancer Research and Treatment.

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Weitzel, J.N., Kidd, J., Bernhisel, R. et al. Multigene assessment of genetic risk for women for two or more breast cancers. Breast Cancer Res Treat (2021). https://doi.org/10.1007/s10549-021-06201-y

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Keywords

  • Breast cancer
  • BRCA1
  • BRCA2
  • Second breast cancer
  • Multiple breast cancers
  • Hereditary breast cancer