Prediction of Breast Cancer Risk Based on Flow-variant Analysis of Circulating Peripheral Blood B Cells

Overview

Journal Genet Med

Publisher Elsevier

Specialty Genetics

Date 2017 Mar 17

PMID 28301456

Citations 4

Authors

Mahrukh M Syeda

Kinnari Upadhyay

Johnny Loke

Alexander Pearlman

Susan Klugman

Yongzhao Shao

Harry Ostrer

Affiliations

Soon will be listed here.

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.Genet Med advance online publication 16 March 2017.

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Prediction of breast cancer risk based on flow variant analysis of circulating peripheral blood mononuclear cells.

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