Determination of pathogenicity of breast cancer 1 gene variants using the American college of medical genetics and genomics and the association for molecular pathology guidelines

OPEN JOURNAL SYSTEMS SCImago Journal & Country Rank ABOUT THE AUTHORS Angela Brown Wellington Regional Genetics Laboratory, Wellington Hospital, Wellington, New Zealand Mansour Zamanpoor Wellington Regional Genetics Laboratory, Wellington Hospital, Wellington, New Zealand Donald R. Love Diagnostic Genetics, LabPLUS, Auckland City Hospital, Auckland, New Zealand; Department of Pathology, Sidra Medicine, Doha, Qatar Debra O. Prosser Diagnostic Genetics, LabPLUS, Auckland City Hospital, Auckland, New Zealand; Department of Pathology, Sidra Medicine, Doha, Qatar USER Username Password Remember me JOURNAL CONTENT Search Search Scope All Browse By Issue By Author By Title By Sections Other Journals NOTIFICATIONS View Subscribe FONT SIZE Make font size smallerMake font size defaultMake font size larger INFORMATION For Readers For Authors For Librarians ARTICLE TOOLS Print this article Indexing metadata How to cite item Email this article (Login required) Email the author (Login required) Journal Help HOME ABOUT LOGIN REGISTER SEARCH CURRENT ARCHIVES AIM AND SCOPE AUTHOR GUIDELINES SUBMISSIONS REVIEWER GUIDELINES ABSTRACTING AND INDEXING ABOUT US CONTACT US Home > Vol 19, No 4 (2019) > Brown Determination of Pathogenicity of Breast Cancer 1 Gene Variants using the American College of Medical Genetics and Genomics and the Association for Molecular Pathology Guidelines Angela Brown, Mansour Zamanpoor, Donald R. Love, Debra O. Prosser Abstract Objectives: Molecular diagnostic laboratories screen for mutations in disease-causing genes in order to confirm a clinical diagnosis. The classification of DNA variants as ‘pathogenic’ or ‘likely pathogenic’ mutations creates a workflow bottleneck, which becomes increasingly challenging as greater number of genes are screened. The classification challenge is also acute if there are conflicting reports regarding pathogenicity and differing classification criteria between laboratories. This study aimed to compare two procedures for the classification of variants in the breast cancer (BRCA)1 gene. Methods: This bioinformatic study was conducted at LabPLUS, Auckland, New Zealand, from February to June 2017. DNA was extracted from peripheral blood samples of 30 patients and gene library construction was carried out using a commercially available targeted panel for the BRCA1 and BRCA2 genes. The genes were subsequently sequenced and the sequence data analysed. The guidelines published by the American College of Medical Genetics and G