The validation and clinical implementation of BRCAplus: a comprehensive high-risk breast cancer diagnostic assay.
Breast cancer is the most commonly diagnosed cancer in women, with 10% of disease attributed to hereditary factors. Although BRCA1 and BRCA2 account for a high percentage of hereditary cases, there are more than 25 susceptibility genes that differentially impact the risk for breast cancer. Traditionally, germline testing for breast cancer was performed by Sanger dideoxy terminator sequencing in a reflexive manner, beginning with BRCA1 and BRCA2. The introduction of next-generation sequencing (NGS) has enabled the simultaneous testing of all genes implicated in breast cancer resulting in diagnostic labs offering large, comprehensive gene panels. However, some physicians prefer to only test for those genes in which established surveillance and treatment protocol exists. The NGS based BRCAplus test utilizes a custom tiled PCR based target enrichment design and bioinformatics pipeline coupled with array comparative genomic hybridization (aCGH) to identify mutations in the six high-risk genes: BRCA1, BRCA2, PTEN, TP53, CDH1, and STK11. Validation of the assay with 250 previously characterized samples resulted in 100% detection of 3,025 known variants and analytical specificity of 99.99%. Analysis of the clinical performance of the first 3,000 BRCAplus samples referred for testing revealed an average coverage greater than 9,000X per target base pair resulting in excellent specificity and the sensitivity to detect low level mosaicism and allele-drop out. The unique design of the assay enabled the detection of pathogenic mutations missed by previous testing. With the abundance of NGS diagnostic tests being released, it is essential that clinicians understand the advantages and limitations of different test designs.
Department of Research and Development, Ambry Genetics, Aliso Viejo, California, United States of America.
Hansook Kim
HK
Chong
Department of Bioinformatics, Ambry Genetics, Aliso Viejo, California, United States of America.
Tao
T
Wang
Department of Bioinformatics, Ambry Genetics, Aliso Viejo, California, United States of America.
Hsiao-Mei
HM
Lu
Department of Research and Development, Ambry Genetics, Aliso Viejo, California, United States of America.
Sara
S
Seidler
Department of Bioinformatics, Ambry Genetics, Aliso Viejo, California, United States of America.
Hong
H
Lu
Department of Clinical Genetics, Ambry Genetics, Aliso Viejo, California, United States of America.
Steven
S
Keiles
Department of Clinical Genetics, Ambry Genetics, Aliso Viejo, California, United States of America.
Elizabeth C
EC
Chao
Department of Clinical Genetics, Ambry Genetics, Aliso Viejo, California, United States of America.
A J
AJ
Stuenkel
Department of Bioinformatics, Ambry Genetics, Aliso Viejo, California, United States of America.
Xiang
X
Li
Department of Research and Development, Ambry Genetics, Aliso Viejo, California, United States of America.
Aaron M
AM
Elliott
D000465:Algorithms; D000483:Alleles; D024682:BRCA2 Protein / Q000235:genetics*; D001943:Breast Neoplasms / Q000175:diagnosis / Q000235:genetics*; D055028:Comparative Genomic Hybridization; D019295:Computational Biology / Q000379:methods*; D017931:DNA Primers; D055088:Early Detection of Cancer; D005260:Female; D024522:Genes, BRCA2; D020022:Genetic Predisposition to Disease; D006801:Humans; D009154:Mutation; D016133:Polymerase Chain Reaction; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
D024682:BRCA2 Protein; C551750:BRCA2 protein, human; D017931:DNA Primers