It appears that all types of genomic nucleotide variations can be deleterious by affecting normal pre-mRNA splicing via disruption/creation of splice site consensus sequences. As it is neither pertinent nor realistic to perform functional testing for all of these variants, it is important to identify those that could lead to a splice defect in order to restrict transcript analyses to the most appropriate cases. Web-based tools designed to provide such predictions are available. We evaluated the performance of six of these tools (Splice Site Prediction by Neural Network [NNSplice], Splice-Site Finder [SSF], MaxEntScan [MES], Automated Splice-Site Analyses [ASSA], Exonic Splicing Enhancer [ESE] Finder, and Relative Enhancer and Silencer Classification by Unanimous Enrichment [RESCUE]-ESE) using 39 unrelated retinoblastoma patients carrying different RB1 variants (31 intronic and eight exonic). These 39 patients were screened for abnormal splicing using puromycin-treated cell lines and the results were compared to the predictions. As expected, 17 variants impacting canonical AG/GT splice sites were correctly predicted as deleterious. A total of 22 variations occurring at loosely defined positions (+/-60 nucleotides from an AG/GT site) led to a splice defect in 19 cases and 16 of them were classified as deleterious by at least one tool (84% sensitivity). In other words, three variants escaped in silico detection and the remaining three were correctly predicted as neutral. Overall our results suggest that a combination of complementary in silico tools is necessary to guide molecular geneticists (balance between the time and cost required by RNA analysis and the risk of missing a deleterious mutation) because the weaknesses of one in silico tool may be overcome by the results of another tool.

BackgroundMost currently known breast cancer predisposition genes play a role in DNA repair by homologous recombination. Recent studies conducted on RAD51 paralogs, involved in the same DNA repair pathway, have identified rare germline mutations conferring breast and/or ovarian cancer predisposition in the RAD51C, RAD51D and XRCC2 genes. The present study analysed the five RAD51 paralogs (RAD51B, RAD51C, RAD51D, XRCC2, XRCC3) to estimate their contribution to breast and ovarian cancer predisposition.MethodsThe study was conducted on 142 unrelated patients with breast and/or ovarian cancer either with early onset or with a breast/ovarian cancer family history. Patients were referred to a French family cancer clinic and had been previously tested negative for a BRCA1/2 mutation. Coding sequences of the five genes were analysed by EMMA (Enhanced Mismatch Mutation Analysis). Detected variants were characterized by Sanger sequencing analysis.ResultsThree splicing mutations and two likely deleterious missense variants were identified: RAD51B c.452 + 3A > G, RAD51C c.706-2A > G, RAD51C c.1026 + 5_1026 + 7del, RAD51B c.475C > T/p.Arg159Cys and XRCC3 c.448C > T/p.Arg150Cys. No RAD51D and XRCC2 gene mutations were detected. These mutations and variants were detected in families with both breast and ovarian cancers, except for the RAD51B c.475C > T/p.Arg159Cys variant that occurred in a family with 3 breast cancer cases.ConclusionsThis study identified the first RAD51B mutation in a breast and ovarian cancer family and is the first report of XRCC3 mutation analysis in breast and ovarian cancer. It confirms that RAD51 paralog mutations confer breast and ovarian cancer predisposition and are rare events. In view of the low frequency of RAD51 paralog mutations, international collaboration of family cancer clinics will be required to more accurately estimate their penetrance and establish clinical guidelines in carrier individuals.

Variability in the age of onset and number of tumors is occasionally described among retinoblastoma patients, and possible genetic modifiers might lie in the pRB or p53 pathways, both of which are involved in the development of retinoblastoma. MDM2, which increases p53 and pRB catabolism, is therefore a prominent candidate. The minor allele of MDM2 that includes a 309T>G transversion (single-nucleotide polymorphism rs2279744) in the MDM2 promoter is known to enhance MDM2 expression. Its genetic transmission was studied in 326 individuals including 212 RB1 mutation carriers in 70 retinoblastoma families, and the marker genotype was tested for association with age at diagnosis and disease phenotype. In family-based association analyses, the MDM2 309G allele was found to be statistically significantly associated with incidence of bilateral or unilateral retinoblastoma among members of retinoblastoma families (Z = 3.305, two-sided exact P = .001) under a recessive model (ie, affected patients tend to be homozygous for the G allele); in transmission disequilibrium analyses using the recessive model, the association was also observed (estimated odds ratio = 4.0, 95% confidence interval = 1.3 to 12.0). The strong association of this genotype with retinoblastoma development designates MDM2 as the first modifier gene to be identified among retinoblastoma patients and suggests that enhancement of pRB haploinsufficiency and/or resistance to p53-mediated apoptosis is critical to tumor formation.