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

Arianna Nicolussi; Francesca Belardinilli; Valentina Silvestri; Yasaman Mahdavian; Virginia Valentini; Sonia D'Inzeo; Marialaura Petroni; Massimo Zani; Sergio Ferraro; Stefano Di Giulio; Francesca Fabretti; Beatrice Fratini; Angela Gradilone; Laura Ottini; Giuseppe Giannini; Anna Coppa; Carlo Capalbo

doi:10.7717/peerj.7972

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

PeerJ. 2019 Nov 15:7:e7972. doi: 10.7717/peerj.7972. eCollection 2019.

Authors

Arianna Nicolussi¹, Francesca Belardinilli², Valentina Silvestri², Yasaman Mahdavian², Virginia Valentini², Sonia D'Inzeo³, Marialaura Petroni⁴, Massimo Zani², Sergio Ferraro², Stefano Di Giulio², Francesca Fabretti², Beatrice Fratini¹, Angela Gradilone², Laura Ottini², Giuseppe Giannini^{2

5}, Anna Coppa¹, Carlo Capalbo²

Affiliations

¹ Department of Experimental Medicine, University of Roma "La Sapienza", Roma, Italy.
² Department of Molecular Medicine, University of Roma "La Sapienza", Roma, Italy.
³ U.O.C. Microbiology and Virology Laboratory, A.O. San Camillo Forlanini, Roma, Italy.
⁴ Istituto Italiano di Tecnologia, Center for Life Nano Science @ Sapienza, Roma, Italy.
⁵ Istituto Pasteur-Fondazione Cenci Bolognetti, Roma, Italy.

Abstract

Background: 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.

Methods: We first used NGS data of a group of three patients (training set), previously screened in our laboratory by conventional methods, to develop an algorithm for the calculation of the dosage quotient (DQ) to be compared with the Ion Reporter (IR) analysis. Then, we tested the optimized pipeline with a consecutive cohort of 85 uncharacterized probands (validation set) also subjected to MLPA analysis. Characterization of the breakpoints of three novel BRCA1 LGRs was obtained via long-range PCR and direct sequencing of the DNA products.

Results: In our cohort, the newly defined DQ-based algorithm detected 3/3 BRCA1 LGRs, demonstrating 100% sensitivity and 100% negative predictive value (NPV) (95% CI [87.6-99.9]) compared to 2/3 cases detected by IR (66.7% sensitivity and 98.2% NPV (95% CI [85.6-99.9])). Interestingly, DQ and IR shared 12 positive results, but exons deletion calls matched only in five cases, two of which confirmed by MLPA. The breakpoints of the 3 novel BRCA1 deletions, involving exons 16-17, 21-22 and 20, have been characterized.

Conclusions: Our study defined a DQ-based algorithm to identify BRCA1 LGRs using NGS data. Whether confirmed on larger data sets, this tool could guide the selection of samples to be subjected to MLPA analysis, leading to significant savings in time and money.

Keywords: Analytical validation; BRCA1 LGRs; DQ analysis; Deep coverage; MLPA; NGS.

Grants and funding

This work was supported by the Italian Ministry of Education, Universities and Research—Dipartimenti di Eccellenza—L. 232/2016; Associazione Italiana per la Ricerca sul Cancro (AIRC) grant IG17734, Italian Ministry of University and Research, PRIN projects, and Istituto Pasteur-Fondazione Cenci Bolognetti (to Giuseppe Giannini); Francesca Fabretti is the recipient of a fellowship of the PhD Programme in Tecnologie Biomediche in Medicina Clinica, University La Sapienza. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.