First application of next-generation sequencing in Moroccan breast/ovarian cancer families and report of a novel frameshift mutation of the BRCA1 gene

摘要

At present, breast cancer is the most common type of cancer in females. The majority of cases are sporadic, but 5-10% are due to an inherited predisposition to develop breast and ovarian cancers, which are transmitted as an autosomal dominant form with incomplete penetrance. The beneficial effects of clinical genetic testing, including next generation sequencing (NGS) for BRCA1/2 mutations, is major; in particular, it benefits the care of patients and the counseling of relatives that are at risk of breast cancer, in order to reduce breast cancer mortality. BRCA genetic testing was performed in 15 patients with breast cancer and a family with positivity for the heterozygous c.6428C>A mutation of the BRCA2 gene. Informed consent was obtained from all the subjects. Genomic DNAs were extracted and the NGS for genes was performed using the Ion Torrent Personal Genome Machine (PGM) with a 316 chip. The reads were aligned with the human reference HG19 genome to elucidate variants in the BRCA1 and BRCA2 genes. Mutations detected by the PGM platform were confirmed by target direct Sanger sequencing on a second patient DNA sample. In total, 4 BRCA variants were identified in 6 families by NGS. Of these, 3 mutations had been previously reported: c.2126insA of BRCA1, and c.1310_1313delAAGA and c.7235insG of BRCA2. The fourth variant, c.3453delT in BRCA1, has, to the best of our knowledge, never been previously reported. The present study is the first to apply NGS of the BRCA1 and BRCA2 genes to a Moroccan population, prompting additional investigation into local founder mutations and variant characteristics in the region. The variants with no clear clinical significance may present a diagnostic challenge when performing targeted resequencing. These results confirm that an NGS approach based on Ampliseq libraries and PGM sequencing is a highly efficient, speedy and high-throughput mutation detection method, which may be preferable in lower income countries.