Myriad’s myRisk Hereditary Cancer test includes analysis of several well-known breast cancer genes. However, 10% or fewer of breast cancers in women are hereditary.1,2,3 While hereditary breast cancers are due to a mutation in a specific gene, many other breast cancers are the result of a combination of small genetic factors, environment, lifestyle, and other unknown factors. Consequently, women without a mutation in a breast cancer susceptibility gene could still be at an increased risk for breast cancer due to these other genetic and non-genetic factors. Myriad developed riskScore, a polygenic risk score (PRS) and clinically validated precision medicine tool, to account for these factors.4 riskScore is part of the myRisk Hereditary Cancer test and predicts a woman’s 5-year and lifetime risks of developing breast cancer using clinical risk factors and genetic markers called single nucleotide polymorphisms (SNPs). SNPs are a common form of genetic variation and the breast cancer risk conferred by a single SNP is not high enough to significantly impact a woman’s risk of breast cancer. However, when the effect of multiple SNPs is combined, the risk can be large enough to significantly alter medical management.

Previously, a woman’s breast cancer risk would be estimated using various models that account for her family history and/or hormonal/reproductive factors. The Tyrer-Cuzick model accounts for a woman’s family history of breast and ovarian cancer; her age at menarche, parity, age at first childbirth, age at menopause, height, BMI, and personal history of atypical hyperplasia or LCIS.5 Myriad’s riskScore tool modifies a women’s Tyrer-Cuzick risk estimate by combining it with a weighted analysis of 86 SNPs. riskScore helps to refine a woman’s risk of breast cancer, with or without a family history of breast cancer. In doing so, riskScore can help identify which women may benefit from enhanced breast cancer screening and/or preventative measures.

Currently, there are no specific medical management guidelines for breast cancer based on riskScore. However, an estimated remaining lifetime risk at or above the 20% threshold may warrant consideration of risk-reduction strategies similar to those recommended for women with an estimated lifetime risk greater than 20% based on other risk prediction methods. NCCN recommends women with a breast cancer lifetime risk that is estimated to be 20% or greater based on models that are largely dependent on family history (e.g. Claus, BRCAPRO, Tyrer-Cuzick) consider annual screening with mammograms and breast MRIs at earlier ages.6

Currently, riskScore is only calculated for women of solely European ancestry, under the age of 85, and without a personal history of breast cancer, LCIS, hyperplasia, or a breast biopsy with unknown result. At the present time, riskScore is not calculated for women with a pathogenic mutation in a breast cancer risk gene. However, at the recent 2019 San Antonio Breast Cancer Symposium, Myriad presented data from a validation study using an 86-SNP PRS to refine the breast cancer risk estimates for women with a pathogenic mutation in the following genes: BRCA1, BRCA2, ATM, CHEK2, and PALB2.7 This study showed that the PRS was able to better refine the breast cancer risk for these mutation carriers, but it was strongest for CHEK2 mutation carriers. A comprehensive risk assessment that combines the 86-SNP PRS with other risk factors may improve the accuracy of risk estimates and facilitate medical decision-making, especially for women with pathogenic mutations in the moderate penetrance breast cancer genes. Myriad is currently researching this topic further and may incorporate PRS-based risk estimates for carriers of certain gene mutations in the future.

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References

1. Couch FJ, et al. Associations between cancer predisposition testing panel genes and breast cancer. JAMA Oncol. 2017;3(9):1190-1196.
2. Buys SS, et al. A study of over 35,000 women with breast cancer tested with a 25-gene panel of hereditary cancer genes. Cancer. 2017;123(10):1721-1730.
3. Siegel RL, et al. Cancer statistics, 2019. CA Cancer J Clin. 2019;69(1):7-34.
4. Hughes, E. et al. SABCS (2017 presentation).
5. Tyrer J, Duffy SW, & Cuzick J. A breast cancer prediction model incorporating familial and personal risk factors. Stat Med. 2004;23(7):1111-1130.
6. NCCN Clinical Practice Guidelines in Oncology. Breast Cancer Screening and Diagnosis (Version 1.2019). https://www.nccn.org/professionals/physician_gls/pdf/breast-screening.pdf. Accessed April 27, 2020.
7. Hughes, E. et al. SABCS (2019 presentation).