Role of Splicing Regulatory Elements and In Silico Tools Usage in the Identification of Deep Intronic Splicing Variants in Hereditary Breast/Ovarian Cancer Genes

Cancer hereditario de mama y ovario; Pseudoexones; Variantes intrónicas profundas spliceogénicasCàncer hereditari de mama i d'ovari; Pseudoexons; Variants intròniques profundes spliceogèniquesHereditary breast ovarian cancer; Pseudoexons; Spliceogenic deep intronic variantsThe contribution of deep intronic splice-altering variants to hereditary breast and ovarian cancer (HBOC) is unknown. Current computational in silico tools to predict spliceogenic variants leading to pseudoexons have limited efficiency. We assessed the performance of the SpliceAI tool combined with ESRseq scores to identify spliceogenic deep intronic variants by affecting cryptic sites or splicing regulatory elements (SREs) using literature and experimental datasets. Our results with 233 published deep intronic variants showed that SpliceAI, with a 0.05 threshold, predicts spliceogenic deep intronic variants affecting cryptic splice sites, but is less effective in detecting those affecting SREs. Next, we characterized the SRE profiles using ESRseq, showing that pseudoexons are significantly enriched in SRE-enhancers compared to adjacent intronic regions. Although the combination of SpliceAI with ESRseq scores (considering ∆ESRseq and SRE landscape) showed higher sensitivity, the global performance did not improve because of the higher number of false positives. The combination of both tools was tested in a tumor RNA dataset with 207 intronic variants disrupting splicing, showing a sensitivity of 86%. Following the pipeline, five spliceogenic deep intronic variants were experimentally identified from 33 variants in HBOC genes. Overall, our results provide a framework to detect deep intronic variants disrupting splicing.This research was funded by the Spanish Instituto de Salud Carlos III (ISCIII) funding an initiative of the Spanish Ministry of Economy and Innovation, partially supported by European Regional Development FEDER Funds, grant numbers PI16/01218 and PI19/01303. AM-F contract is supported by the award ERAPERMED2019-215 granted by AECC FC and by ISCIII thorough AES 2019, both within the ERAPerMed framework”. J.D.-V. contract is supported by the Secretariat for Universities and Research of the Ministry of Business and Knowledge of the Government of Catalonia and the European Social Fund