Full in-frame exon 3 skipping of BRCA2 confers high risk of breast and/or ovarian cancer Full in-frame exon 3 skipping of BRCA2 confers high risk of breast and/or ovarian cancer

Retinoblastoma (RB) is the most common pediatric intraocular neoplasm and occurs in 1 of every 20 000 births.¹ It results from biallelic inactivation of the RB1 tumor-suppressor gene (OMIM 180200), located on 13q14.² The RB1 gene encodes the nuclear phosphoprotein RB protein, which plays a prominent role during the G1/S phase transition.³ Both RB1 alleles can be inactivated in tumors via diverse loss of function mechanisms including point pathogenic variants, large rearrangements (ie, large deletions or duplications from a single exon to the entire gene), promoter hypermethylation, and loss of the second allele by loss of heterozygosity. In nonhereditary RB, both RB1 pathogenic variants are somatic and occur in the same retinal cell that develops into a tumor. In contrast, in hereditary RB, the germline pathogenic variant of 1 allele is associated with RB. The germline pathogenic variant is either inherited from an affected parent or acquired during fetal development (de novo), whereas the second pathogenic variant on the other allele is somatic, usually acquired during early childhood.

Understanding the medical effect of an ever-growing number of human variants detected is a long term challenge in genetic counseling. Functional assays, based on in vitro or in vivo evaluations of the variant effects, provide essential information, but they require robust statistical validation, as well as adapted outputs, to be implemented in the clinical decision-making process. Here, we assessed 25 pathogenic and 15 neutral missense variants of the BRCA1 breast/ovarian cancer susceptibility gene in four BRCA1 functional assays. Next, we developed a novel approach that refines the variant ranking in these functional assays. Lastly, we developed a computational system that provides a probabilistic classification of variants, adapted to clinical interpretation. Using this system, the best functional assay exhibits a variant classification accuracy estimated at 93%. Additional theoretical simulations highlight the benefit of this ready-to-use system in the classification of variants after functional assessment, which should facilitate the consideration of functional evidences in the decision-making process after genetic testing. Finally, we demonstrate the versatility of the system with the classification of siRNAs tested for human cell growth inhibition in high throughput screening. Human genetics has entered a new age with the advent of next generation sequencing. However, this great advance also comes with new concerns. Currently, the extensive use of multi-gene panels, whole exome and whole genome sequencing, is generating an ever-growing number of new DNA sequence variations detected in the disease-predisposing genes of human patients. The pathogenic or neutral status of these variants needs to be known before planning any medical act or follow-up. We show here that the status of the variants identified in the BRCA1 breast/ovarian cancer susceptibility gene can be estimated thanks to experimental systems using yeast cells and a novel computational model. Importantly, this model provides a probabilistic classification of variants, opening the possibility to integrate results from functional assays into clinical decision-making. Moreover, our computational model is directly compatible with all kinds of experimental system without any requirement for skills in statistics thanks to ready-to-use online tools. We believe that this work is a step forward in the clinical interpretation of human genetic variants.