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    From BRCA1to polygenic risk scores: mutation-associated risks in breast cancer-related genes

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    Authors
    Woodward, E. R.
    van Veen, E. M
    Evans, D Gareth R
    Affiliation
    Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester
    Issue Date
    2021
    
    Metadata
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    Abstract
    Background: There has been huge progress over the last 30 years in identifying the familial component of breast cancer. Summary: Currently around 20% is explained by the high-risk genes BRCA1 and BRCA2, a further 2% by other high-penetrance genes, and around 5% by the moderate risk genes ATM and CHEK2. In contrast, the more than 300 low-penetrance single-nucleotide polymorphisms (SNP) now account for around 28% and they are predicted to account for most of the remaining 45% yet to be found. Even for high-risk genes which confer a 40-90% risk of breast cancer, these SNP can substantially affect the level of breast cancer risk. Indeed, the strength of family history and hormonal and reproductive factors is very important in assessing risk even for a BRCA carrier. The risks of contralateral breast cancer are also affected by SNP as well as by the presence of high or moderate risk genes. Genetic testing using gene panels is now commonplace. Key-messages: There is a need for a more parsimonious approach to panels only testing those genes with a definite 2-fold increased risk and only testing those genes with challenging management implications, such as CDH1 and TP53, when there is strong clinical indication to do so. Testing of SNP alongside genes is likely to provide a more accurate risk assessment.
    Citation
    Woodward ER, van Veen EM, Evans DG. From BRCA1 to Polygenic Risk Scores: Mutation-Associated Risks in Breast Cancer-Related Genes. Breast Care. 2021;16(3):202–13.
    Journal
    Breast Care
    URI
    http://hdl.handle.net/10541/624440
    DOI
    10.1159/000515319
    PubMed ID
    34248461
    Additional Links
    https://dx.doi.org/10.1159/000515319
    Type
    Article
    Language
    en
    ae974a485f413a2113503eed53cd6c53
    10.1159/000515319
    Scopus Count
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