A Whole Germline BRCA2 Gene Deletion: How to Learn from CNV In Silico Analysis
1
Fondazione di Ricerca e Cura Giovanni Paolo II, Laboratorio di Oncologia Molecolare, Molipharma a spin-off of Fondazione di Ricerca e Cura Giovanni Paolo II, Contrada Tappino, 86100 Campobasso, Italy
2
Istituto Dermopatico dell’Immacolata—Istituto di Ricovero e Cura a Carattere Scientifico, Dipartimento di Diagnostica di Laboratorio e Biologia Molecolare Clinica, 00168 Roma, Italy
3
Università Cattolica del Sacro Cuore, Fondazione Policlinico Universitario Agostino Gemelli, Polo Scienze delle Immagini, di Laboratorio ed Infettivologiche, 00168 Rome, Italy
4
Università Cattolica del Sacro Cuore, Fondazione Policlinico Universitario Agostino Gemelli, Polo Scienze della Salute della Donna e del Bambino, 00168 Rome, Italy
5
Laboratory of Molecular Genomics XBiogem, Catholic University of Rome, 00168 Rome, Italy
*
Author to whom correspondence should be addressed.
Int. J. Mol. Sci. 2018, 19(4), 961; https://doi.org/10.3390/ijms19040961
Received: 12 February 2018 / Revised: 19 March 2018 / Accepted: 21 March 2018 / Published: 23 March 2018
(This article belongs to the Special Issue Ovarian Cancer: Pathogenesis, Diagnosis, and Treatment)
BRCA1/2 screening in Hereditary Breast and Ovarian Syndrome (HBOC) is an essential step for effective patients’ management. Next-Generation Sequencing (NGS) can rapidly provide high throughput and reliable information about the qualitative and quantitative status of tumor-associated genes. Straightforwardly, bioinformatics methods play a key role in molecular diagnostics pipelines. BRCA1/2 genes were evaluated with our NGS workflow, coupled with Multiplex Amplicon Quantification (MAQ) and Multiplex Ligation-dependent Probe Amplification (MLPA) assays. Variant calling was performed on Amplicon Suite, while Copy Number Variant (CNV) prediction by in house and commercial CNV tools, before confirmatory MAQ/MLPA testing. The germline profile of BRCA genes revealed a unique HBOC pattern. Although variant calling analysis pinpointed heterozygote and homozygote polymorphisms on BRCA1 and BRCA2, respectively, the CNV predicted by our script suggested two conflicting interpretations: BRCA1 duplication and/or BRCA2 deletion. Our commercial software reported a BRCA1 duplication, in contrast with variant calling results. Finally, the MAQ/MLPA assays assessed a whole BRCA2 copy loss. In silico CNV analysis is a time and cost-saving procedure to powerfully identify possible Large Rearrangements using robust and efficient NGS pipelines. Our layout shows as bioinformatics algorithms alone cannot completely and correctly identify whole BRCA1/2 deletions/duplications. In particular, the complete deletion of an entire gene, like in our case, cannot be solved without alternative strategies as MLPA/MAQ. These findings support the crucial role of bioinformatics in deciphering pitfalls within NGS data analysis.