A whole germline BRCA2 gene deletion: How to learn from CNV in silico analysis

Maria Gabriella Ferrandina, Giovanni Scambia, Giovanni Luca Scaglione, Paola Concolino, Maria De Bonis, Elisa De Paolis, Angelo Minucci, Ettore Domenico Capoluongo

Risultato della ricerca: Contributo in rivistaArticolo in rivista

9 Citazioni (Scopus)

Abstract

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.
Lingua originaleEnglish
pagine (da-a)961-N/A
RivistaInternational Journal of Molecular Sciences
Volume19
DOI
Stato di pubblicazionePubblicato - 2018

Keywords

  • BRCA1/2
  • CNV
  • Catalysis
  • Computer Science Applications1707 Computer Vision and Pattern Recognition
  • Data analysis
  • HBOC
  • Inorganic Chemistry
  • MLPA
  • Molecular Biology
  • NGS
  • Organic Chemistry
  • Physical and Theoretical Chemistry
  • Spectroscopy

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