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In silico tools for splicing defect prediction have a key role to assess the impact of variants of uncertain significance. Our aim was to evaluate the performance of a set of commonly used splicing in silico tools comparing the predictions against RNA in vitro results. This was done for natural splice sites of clinically relevant genes in hereditary breast/ovarian cancer (HBOC) and Lynch syndrome. A study divided into two stages was used to evaluate SSF-like, MaxEntScan, NNSplice, HSF, SPANR, and dbscSNV tools. A discovery dataset of 99 variants with unequivocal results of RNA in vitro studies, located in the 10 exonic and 20 intronic nucleotides adjacent to exon–intron boundaries of BRCA1, BRCA2, MLH1, MSH2, MSH6, PMS2, ATM, BRIP1, CDH1, PALB2, PTEN, RAD51D, STK11, and TP53, was collected from four Spanish cancer genetic laboratories. The best stand-alone predictors or combinations were validated with a set of 346 variants in the same genes with clear splicing outcomes reported in the literature. Sensitivity, specificity, accuracy, negative predictive value (NPV) and Mathews Coefficient Correlation (MCC) scores were used to measure the performance. The discovery stage showed that HSF and SSF-like were the most accurate for variants at the donor and acceptor region, respectively. The further combination analysis revealed that HSF, HSF+SSF-like or HSF+SSF-like+MES achieved a high performance for predicting the disruption of donor sites, and SSF-like or a sequential combination of MES and SSF-like for predicting disruption of acceptor sites. The performance confirmation of these last results with the validation dataset, indicated that the highest sensitivity, accuracy, and NPV (99.44%, 99.44%, and 96.88, respectively) were attained with HSF+SSF-like or HSF+SSF-like+MES for donor sites and SSF-like (92.63%, 92.65%, and 84.44, respectively) for acceptor sites.We provide recommendations for combining algorithms to conduct in silico splicing analysis that achieved a high performance. The high NPV obtained allows to select the variants in which the study by in vitro RNA analysis is mandatory against those with a negligible probability of being spliceogenic. Our study also shows that the performance of each specific predictor varies depending on whether the natural splicing sites are donors or acceptors.

In the Iberian Peninsula, which includes mainly Spain and Portugal, large genomic rearrangements (LGRs) of BRCA1 and BRCA2 have respectively been found in up to 2.33% and 8.4% of families with hereditary breast and/or ovarian cancer (HBOC) that lack point mutations and small indels. In Galicia (Northwest Spain), the spectrum and frequency of BRCA1/BRCA2 point mutations differs from the rest of the Iberian populations. However, to date there are no Galician frequency reports of BRCA1/BRCA2 LGRs. Here we used multiplex ligation-dependent probe amplification (MLPA) to screen 651 Galician index cases (out of the 830 individuals referred for genetic analysis) without point mutations or small indels. We identified three different BRCA1 LGRs in four families. Two of them have been previously classified as pathogenic LGRs: the complete deletion of BRCA1 (identified in two unrelated families) and the deletion of exons 1 to 13. We also identified the duplication of exons 1 and 2 that is a LGR with unknown pathogenicity. Determination of the breakpoints of the BRCA1 LGRs using CNV/SNP arrays and sequencing identified them as NG_005905.2:g.70536_180359del, NG_005905.2:g.90012_97270dup, and NC_000017.10:g.41230935_41399840delinsAluSx1, respectively; previous observations of BRCA1 exon1-24del, exon1-2dup, and exon1-13del LGRs have not characterized them in such detail. All the BRCA1 LGRs arose from unequal homologous recombination events involving Alu elements. We also detected, by sequencing, one BRCA2 LGR, the Portuguese founder mutation c.156_157insAluYa5. The low frequency of BRCA1 LGRs within BRCA1 mutation carriers in Galicia (2.34%, 95% CI: 0.61-7.22) seems to differ from the Spanish population (9.93%, 95% CI: 6.76-14.27, P-value = 0.013) and from the rest of the Iberian population (9.76%, 95% CI: 6.69-13.94, P-value = 0.014).