Literature DB >> 27886673

In silico, in vitro and case-control analyses as an effective combination for analyzing BRCA1 and BRCA2 unclassified variants in a population-based sample.

Marta Rodríguez-Balada1, Bàrbara Roig1, Lourdes Martorell2, Mireia Melé1, Mònica Salvat1, Elisabet Vilella2, Joan Borràs1, Josep Gumà3.   

Abstract

Ascertaining the clinical consequences of BRCA1 and BRCA2 variants of uncertain significance (VUS) is currently indispensable for providing effective genetic counseling and preventive actions for families with hereditary breast and ovarian cancer (HBOC). To this end, we conducted a combination of in silico prediction and cDNA splicing analyses of 13 BRCA1 and 10 BRCA2 VUS identified in our cohort as well as a case-control analysis in a population-based sample of 10 recurrent VUS. We observed consistent results between the in silico predictions and sequencing analyses for all analyzed VUS. An abnormal cDNA pattern was observed for variants c.212+1G>A and c.5278-1G>A in BRCA1 and c.516+2T>A and c.8168A>G in BRCA2 according to in silico splicing prediction. A case-control study of VUS confirmed the polymorphisms of the c.67+62A>G, c.7008-62A>G and c.8851G>A BRCA2 variants previously published. c.4068G>A in the BRCA2 gene can also be considered a polymorphism due to its occurrence at a frequency greater than 1% in our population. Our study shows that employing population-based analysis and a combination of several in silico methods yields highly accurate information, resulting in a reliable tool for selecting variants for cDNA sequencing analysis in routine cancer genetic counseling units. Copyright Â
© 2016 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  BRCA1; BRCA2; cDNA; cancer genetic counseling; splicing; variants of unknown significance

Mesh:

Substances:

Year:  2016        PMID: 27886673     DOI: 10.1016/j.cancergen.2016.09.003

Source DB:  PubMed          Journal:  Cancer Genet


  2 in total

1.  A plugin for the Ensembl Variant Effect Predictor that uses MaxEntScan to predict variant spliceogenicity.

Authors:  Jannah Shamsani; Stephen H Kazakoff; Irina M Armean; Will McLaren; Michael T Parsons; Bryony A Thompson; Tracy A O'Mara; Sarah E Hunt; Nicola Waddell; Amanda B Spurdle
Journal:  Bioinformatics       Date:  2019-07-01       Impact factor: 6.937

2.  Prioritizing variants of uncertain significance for reclassification using a rule-based algorithm in inherited retinal dystrophies.

Authors:  Ionut-Florin Iancu; Almudena Avila-Fernandez; Ana Arteche; Maria Jose Trujillo-Tiebas; Rosa Riveiro-Alvarez; Berta Almoguera; Inmaculada Martin-Merida; Marta Del Pozo-Valero; Irene Perea-Romero; Marta Corton; Pablo Minguez; Carmen Ayuso
Journal:  NPJ Genom Med       Date:  2021-02-23       Impact factor: 8.617

  2 in total

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