Abstract
Purpose:Identifying women at high risk for breast cancer can trigger a personal program of annual mammograms and magnetic resonance imaging scans for early detection, prophylactic surgery, or chemoprevention to reduce the risk of cancer. Yet, current strategies to identify high-risk mutations based on sequencing panels of genes have significant false-positive and false-negative results, suggesting the need for alternative approaches.Methods:Flow-variant assays (FVAs) that assess the effects of mutations in the double-strand break (DSB) repair genetic pathway in lymphoblastoid cells in response to treatment with radiomimetic agents were assessed for sensitivity, specificity, and accuracy both alone and as part of a logistic regression classification score. In turn, these assays were validated in circulating B cells and applied to individuals with personal and/or family history of breast and/or ovarian cancer.Results:A three-FVA classification score based on logistic regression had 95% accuracy. Individuals from a breast cancer-positive cohort with affected family members had high-risk FVA classification scores.Conclusion:Application of a classification score based on multiple FVAs could represent an alternative to panel sequencing for identifying women at high risk for cancer.
Original language | English (US) |
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Pages (from-to) | 1071-1077 |
Number of pages | 7 |
Journal | Genetics in Medicine |
Volume | 19 |
Issue number | 9 |
DOIs | |
State | Published - Sep 1 2017 |
Keywords
- breast cancer
- functional genomics
- genetic testing
- high risk
- panel sequencing
ASJC Scopus subject areas
- Genetics(clinical)