Skipping of BRCA2 exon 3 ( increment E3) is a naturally occurring splicing event, complicating clinical classification of variants that may alter increment E3 expression. This study used multiple... Show moreSkipping of BRCA2 exon 3 ( increment E3) is a naturally occurring splicing event, complicating clinical classification of variants that may alter increment E3 expression. This study used multiple evidence types to assess pathogenicity of 85 variants in/near BRCA2 exon 3. Bioinformatically predicted spliceogenic variants underwent mRNA splicing analysis using minigenes and/or patient samples. increment E3 was measured using quantitative analysis. A mouse embryonic stem cell (mESC) based assay was used to determine the impact of 18 variants on mRNA splicing and protein function. For each variant, population frequency, bioinformatic predictions, clinical data, and existing mRNA splicing and functional results were collated. Variant class was assigned using a gene-specific adaptation of ACMG/AMP guidelines, following a recently proposed points-based system. mRNA and mESC analysis combined identified six variants with transcript and/or functional profiles interpreted as loss of function. Cryptic splice site use for acceptor site variants generated a transcript encoding a shorter protein that retains activity. Overall, 69/85 (81%) variants were classified using the points-based approach. Our analysis shows the value of applying gene-specific ACMG/AMP guidelines using a points-based approach and highlights the consideration of cryptic splice site usage to appropriately assign PVS1 code strength. Show less
Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could... Show morePolygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, "select and shrink for summary statistics" (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28-1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08-1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21-1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29-1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35-1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs. Show less
Fine-mapping of causal variants and integration of epigenetic and chromatin conformation data identify likely target genes for 150 breast cancer risk regions.Genome-wide association studies have... Show moreFine-mapping of causal variants and integration of epigenetic and chromatin conformation data identify likely target genes for 150 breast cancer risk regions.Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes. Show less
Figlioli, G.; Bogliolo, M.; Catucci, I.; Caleca, L.; Lasheras, S.V.; Pujol, R.; ... ; Marsh, D. 2019
Breast cancer is a common disease partially caused by genetic risk factors. Germline pathogenic variants in DNA repair genes BRCA1, BRCA2, PAM, ATM, and CHEK2 are associated with breast cancer risk... Show moreBreast cancer is a common disease partially caused by genetic risk factors. Germline pathogenic variants in DNA repair genes BRCA1, BRCA2, PAM, ATM, and CHEK2 are associated with breast cancer risk. FANCM, which encodes for a DNA translocase, has been proposed as a breast cancer predisposition gene, with greater effects for the ER-negative and triple-negative breast cancer (TNBC) subtypes. We tested the three recurrent protein-truncating variants FANCM:p.Arg658*, p.Gln1701*, and pArg1931* for association with breast cancer risk in 67,112 cases, 53,766 controls, and 26,662 carriers of pathogenic variants of BRCA1 or BRCA2. These three variants were also studied functionally by measuring survival and chromosome fragility in FANCM(-/-) patient-derived immortalized fibroblasts treated with diepoxybutane or olaparib. We observed that FANCM:p.Arg658* was associated with increased risk of ER-negative disease and TNBC (OR = 2.44, P = 0.034 and OR = 3.79; P = 0.009, respectively). In a country-restricted analysis, we confirmed the associations detected for FANCM:p.Arg658* and found that also FANCM:p.Arg1931* was associated with ER-negative breast cancer risk (OR = 1.96; P = 0.006). The functional results indicated that all three variants were deleterious affecting cell survival and chromosome stability with FANCM:p.Arg658* causing more severe phenotypes. In conclusion, we confirmed that the two rare FANCM deleterious variants p.Arg658* and p.Arg1931* are risk factors for ER-negative and TNBC subtypes. Overall our data suggest that the effect of truncating variants on breast cancer risk may depend on their position in the gene. Cell sensitivity to olaparib exposure, identifies a possible therapeutic option to treat FANCM-associated tumors. Show less
Hoya, M. de la; Soukarieh, O.; Lopez-Perolio, I.; Vega, A.; Walker, L.C.; Ierland, Y. van; ... ; KConFaB Investigators 2016
![Combined genetic and splicing analysis of BRCA1 c.[594-2A > C; 641A > G] highlights the relevance of naturally occurring in-frame transcripts for developing disease gene variant classification algorithms](/sites/all/modules/custom/islandora_solr_search/images/defaultimg.png?solr_nav%5Bid%5D=fd1add46a48d6fd216fe&solr_nav%5Bpage%5D=0&solr_nav%5Boffset%5D=4)
