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Development and validation of a variant detection workflow for BRCA1 and BRCA2 genes and its clinical application based on the Ion Torrent technology

Authors :
Caio Robledo D'Angioli Costa Quaio
Caroline Monaco Moreira
David Santos Marco Antonio
Miguel Mitne-Neto
Ana Lígia Buzolin
Patricia Rossi Sacramento
Alexandre Ricardo dos Santos Fornari
Andre Yuji Oku
Wagner A.R. Baratela
Source :
Human Genomics, Vol 11, Iss 1, Pp 1-9 (2017), Human Genomics
Publication Year :
2017
Publisher :
BMC, 2017.

Abstract

Background Breast cancer is the most common among women worldwide, and ovarian cancer is the most difficult gynecological tumor to diagnose and with the lowest chance of cure. Mutations in BRCA1 and BRCA2 genes increase the risk of ovarian cancer by 60% and breast cancer by up to 80% in women. Molecular tests allow a better orientation for patients carrying these mutations, affecting prophylaxis, treatment, and genetic counseling. Results Here, we evaluated the performance of a panel for BRCA1 and BRCA2, using the Ion Torrent PGM (Life Technologies) platform in a customized workflow and multiplex ligation-dependent probe amplification for detection of mutations, insertions, and deletions in these genes. We validated the panel with 26 samples previously analyzed by Myriad Genetics Laboratory, and our workflow showed 95.6% sensitivity and 100% agreement with Myriad reports, with 85% sensitivity on the positive control sample from NIST. We also screened 68 clinical samples and found 22 distinct mutations. Conclusions The selection of a robust methodology for sample preparation and sequencing, together with bioinformatics tools optimized for the data analysis, enabled the development of a very sensitive test with high reproducibility. We also highlight the need to explore the limitations of the NGS technique and the strategies to overcome them in a clinically confident manner. Electronic supplementary material The online version of this article (doi:10.1186/s40246-017-0110-x) contains supplementary material, which is available to authorized users.

Details

Language :
English
ISSN :
14797364
Volume :
11
Issue :
1
Database :
OpenAIRE
Journal :
Human Genomics
Accession number :
edsair.doi.dedup.....c4668f2cebeef6dcada9d8191cabc8d5
Full Text :
https://doi.org/10.1186/s40246-017-0110-x