title: Prediction of breast cancer risk based on flow-variant analysis of circulating peripheral blood B cells.
abstract: 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.
  
  
  
  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.
  
  
  
  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.
  
  
  
  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.
authors.affiliation: Department of Pathology, Albert Einstein College of Medicine, Bronx, New York, USA.
authors.forename: Mahrukh M
authors.identifier: 0000-0002-4081-2068
authors.initials: MM
authors.lastname: Syeda
authors.affiliation: Department of Pathology, Albert Einstein College of Medicine, Bronx, New York, USA.
authors.forename: Kinnari
authors.initials: K
authors.lastname: Upadhyay
authors.affiliation: Department of Pathology, Albert Einstein College of Medicine, Bronx, New York, USA.
authors.forename: Johnny
authors.initials: J
authors.lastname: Loke
authors.affiliation: Department of Pathology, Albert Einstein College of Medicine, Bronx, New York, USA.
authors.forename: Alexander
authors.initials: A
authors.lastname: Pearlman
authors.affiliation: Department of Obstetrics and Gynecology, Albert Einstein College of Medicine, Bronx, New York, USA.
authors.forename: Susan
authors.initials: S
authors.lastname: Klugman
authors.affiliation: Department of Population Health, Division of Biostatistics, New York University School of Medicine, New York, New York, USA.
authors.forename: Yongzhao
authors.initials: Y
authors.lastname: Shao
authors.affiliation: Department of Pathology, Albert Einstein College of Medicine, Bronx, New York, USA.
authors.forename: Harry
authors.identifier: 0000-0002-2209-5376
authors.initials: H
authors.lastname: Ostrer
mesh_terms: D001402:B-Lymphocytes / Q000378:metabolism*; D019313:BRCA1 Protein / Q000235:genetics / Q000378:metabolism; D024682:BRCA2 Protein / Q000235:genetics / Q000378:metabolism; D014408:Biomarkers, Tumor; D001943:Breast Neoplasms / Q000175:diagnosis / Q000453:epidemiology* / Q000235:genetics*; D045744:Cell Line, Tumor; D053903:DNA Breaks, Double-Stranded; D004252:DNA Mutational Analysis; D055088:Early Detection of Cancer / Q000379:methods / Q000592:standards; D005260:Female; D016158:Genes, p53; D006801:Humans; D009154:Mutation; D010766:Phosphorylation; D021381:Protein Transport; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D017422:Sequence Analysis, DNA; D000073359:Exome Sequencing; D000073336:Whole Genome Sequencing
chemical_list: D019313:BRCA1 Protein; D024682:BRCA2 Protein; D014408:Biomarkers, Tumor