Next-generation sequencing of BRCA1 and BRCA2 genes for rapid detection of germline mutations in hereditary breast/ovarian cancer

Background Conventional methods used to identify BRCA1 and BRCA2 germline mutations in hereditary cancers, such as Sanger sequencing/multiplex ligation-dependent probe amplification (MLPA), are time-consuming and expensive, due to the large size of the genes. The recent introduction of next-generation sequencing (NGS) benchtop platforms offered a powerful alternative for mutation detection, dramatically improving the speed and the efficiency of DNA testing. Here we tested the performance of the Ion Torrent PGM platform with the Ion AmpliSeq BRCA1 and BRCA2 Panel in our clinical routine of breast/ovarian hereditary cancer syndrome assessment. Methods We first tested the NGS approach in a cohort of 11 patients (training set) who had previously undergone genetic diagnosis in our laboratory by conventional methods. Then, we applied the optimized pipeline to the consecutive cohort of 136 uncharacterized probands (validation set). Results By minimal adjustments in the analytical pipeline of Torrent Suite Software we obtained a 100% concordance with Sanger results regarding the identification of single nucleotide alterations, insertions, and deletions with the exception of three large genomic rearrangements (LGRs) contained in the training set. The optimized pipeline applied to the validation set (VS), identified pathogenic and polymorphic variants, including a novel BRCA2 pathogenic variant at exon 3, 100% of which were confirmed by Sanger in their correct zygosity status. To identify LGRs, all negative samples of the VS were subjected to MLPA analysis. Discussion Our experience strongly supports that the Ion Torrent PGM technology in BRCA1 and BRCA2 germline variant identification, combined with MLPA analysis, is highly sensitive, easy to use, faster, and cheaper than traditional (Sanger sequencing/MLPA) approaches

Clinical Multigene Panel Sequencing Identifies Distinct Mutational Association Patterns in Metastatic Colorectal Cancer

Extensive molecular characterization of human colorectal cancer (CRC) via Next Generation Sequencing (NGS) indicated that genetic or epigenetic dysregulation of a relevant, but limited, number of molecular pathways typically occurs in this tumor. The molecular picture of the disease is significantly complicated by the frequent occurrence of individually rare genetic aberrations, which expand tumor heterogeneity. Inter- and intratumor molecular heterogeneity is very likely responsible for the remarkable individual variability in the response to conventional and target-driven first-line therapies, in metastatic CRC (mCRC) patients, whose median overall survival remains unsatisfactory. Implementation of an extensive molecular characterization of mCRC in the clinical routine does not yet appear feasible on a large scale, while multigene panel sequencing of most commonly mutated oncogene/oncosuppressor hotspots is more easily achievable. Here, we report that clinical multigene panel sequencing performed for anti-EGFR therapy predictive purposes in 639 formalin-fixed paraffin-embedded (FFPE) mCRC specimens revealed previously unknown pairwise mutation associations and a high proportion of cases carrying actionable gene mutations. Most importantly, a simple principal component analysis directed the delineation of a new molecular stratification of mCRC patients in eight groups characterized by non-random, specific mutational association patterns (MAPs), aggregating samples with similar biology. These data were validated on a The Cancer Genome Atlas (TCGA) CRC dataset. The proposed stratification may provide great opportunities to direct more informed therapeutic decisions in the majority of mCRC cases

Identification of novel BRCA1 large genomic rearrangements by a computational algorithm of amplicon-based Next-Generation Sequencing data

Genetic testing for BRCA1/2 germline mutations in hereditary breast/ovarian cancer patients requires screening for single nucleotide variants, small insertions/deletions and large genomic rearrangements (LGRs). These studies have long been run by Sanger sequencing and multiplex ligation-dependent probe amplification (MLPA). The recent introduction of next-generation sequencing (NGS) platforms dramatically improved the speed and the efficiency of DNA testing for nucleotide variants, while the possibility to correctly detect LGRs by this mean is still debated. The purpose of this study was to establish whether and to which extent the development of an analytical algorithm could help us translating NGS sequencing via an Ion Torrent PGM platform into a tool suitable to identify LGRs in hereditary breast-ovarian cancer patients