Background Inactivating germline mutations in the tumour suppressor gene BRCA1 are associated with a significantly increased risk of developing breast and ovarian cancer. A large number (>1500) of unique BRCA1 variants have been identified in the population and can be classified as pathogenic, non-pathogenic or as variants of unknown significance (VUS). Many VUS are rare missense variants leading to single amino acid changes. Their impact on protein function cannot be directly inferred from sequence information, precluding assessment of their pathogenicity. Thus, functional assays are critical to assess the impact of these VUS on protein activity. BRCA1 is a multifunctional protein and different assays have been used to assess the impact of variants on different biochemical activities and biological processes. Methods and results To facilitate VUS analysis, we have developed a visualisation resource that compiles and displays functional data on all documented BRCA1 missense variants. BRCA1 Circos is a web-based visualisation tool based on the freely available Circos software package. The BRCA1 Circos web tool (http://research.nhgri.nih.gov/bic/circos/) aggregates data from all published BRCA1 missense variants for functional studies, harmonises their results and presents various functionalities to search and interpret individual-level functional information for each BRCA1 missense variant. Conclusions This research visualisation tool will serve as a quick one-stop publically available reference for all the BRCA1 missense variants that have been functionally assessed. It will facilitate meta-analysis of functional data and improve assessment of pathogenicity of VUS.
Fine-mapping of the HNF1B multicancer locus identifies candidate variants that mediate endometrial cancer risk
A large genotyping project within the Breast Cancer Association Consortium (BCAC) recently identified 41 associations between single nucleotide polymorphisms (SNPs) and overall breast cancer (BC) risk. We investigated whether the effects of these 41 SNPs, as well as six SNPs associated with estrogen receptor (ER) negative BC risk are modified by 13 environmental risk factors for BC. Data from 22 studies participating in BCAC were pooled, comprising up to 26,633 cases and 30,119 controls. Interactions between SNPs and environmental factors were evaluated using an empirical Bayes‐type shrinkage estimator. Six SNPs showed interactions with associated p ‐values ( p int ) <1.1 × 10 −3 . None of the observed interactions was significant after accounting for multiple testing. The Bayesian False Discovery Probability was used to rank the findings, which indicated three interactions as being noteworthy at 1% prior probability of interaction. SNP rs6828523 was associated with increased ER‐negative BC risk in women ≥170 cm (OR = 1.22, p = 0.017), but inversely associated with ER‐negative BC risk in women <160 cm (OR = 0.83, p = 0.039, p int = 1.9 × 10 −4 ). The inverse association between rs4808801 and overall BC risk was stronger for women who had had four or more pregnancies (OR = 0.85, p = 2.0 × 10 −4 ), and absent in women who had had just one (OR = 0.96, p = 0.19, p int = 6.1 × 10 −4 ). SNP rs11242675 was inversely associated with overall BC risk in never/former smokers (OR = 0.93, p = 2.8 × 10 −5 ), but no association was observed in current smokers (OR = 1.07, p = 0.14, p int = 3.4 × 10 −4 ). In conclusion, recently identified BC susceptibility loci are not strongly modified by established risk factors and the observed potential interactions require confirmation in independent studies.
Identification of New Genetic Susceptibility Loci for Breast Cancer Through Consideration of Gene‐Environment Interactions
ABSTRACTGenes that alter disease risk only in combination with certain environmental exposures may not be detected in genetic association analysis. By using methods accounting for gene‐environment (G × E) interaction, we aimed to identify novel genetic loci associated with breast cancer risk. Up to 34,475 cases and 34,786 controls of European ancestry from up to 23 studies in the Breast Cancer Association Consortium were included. Overall, 71,527 single nucleotide polymorphisms (SNPs), enriched for association with breast cancer, were tested for interaction with 10 environmental risk factors using three recently proposed hybrid methods and a joint test of association and interaction. Analyses were adjusted for age, study, population stratification, and confounding factors as applicable. Three SNPs in two independent loci showed statistically significant association: SNPs rs10483028 and rs2242714 in perfect linkage disequilibrium on chromosome 21 and rs12197388 in ARID1B on chromosome 6. While rs12197388 was identified using the joint test with parity and with age at menarche (P‐values = 3 × 10−07), the variants on chromosome 21 q22.12, which showed interaction with adult body mass index (BMI) in 8,891 postmenopausal women, were identified by all methods applied. SNP rs10483028 was associated with breast cancer in women with a BMI below 25 kg/m2 (OR = 1.26, 95% CI 1.15–1.38) but not in women with a BMI of 30 kg/m2 or higher (OR = 0.89, 95% CI 0.72–1.11, P for interaction = 3.2 × 10−05). Our findings confirm comparable power of the recent methods for detecting G × E interaction and the utility of using G × E interaction analyses to identify new susceptibility loci.
Comparison of mRNA Splicing Assay Protocols across Multiple Laboratories: Recommendations for Best Practice in Standardized Clinical Testing
Abstract BACKGROUND Accurate evaluation of unclassified sequence variants in cancer predisposition genes is essential for clinical management and depends on a multifactorial analysis of clinical, genetic, pathologic, and bioinformatic variables and assays of transcript length and abundance. The integrity of assay data in turn relies on appropriate assay design, interpretation, and reporting. METHODS We conducted a multicenter investigation to compare mRNA splicing assay protocols used by members of the ENIGMA (Evidence-Based Network for the Interpretation of Germline Mutant Alleles) consortium. We compared similarities and differences in results derived from analysis of a panel of breast cancer 1, early onset (BRCA1) and breast cancer 2, early onset (BRCA2) gene variants known to alter splicing (BRCA1: c.135-1G>T, c.591C>T, c.594-2A>C, c.671-2A>G, and c.5467+5G>C and BRCA2: c.426-12_8delGTTTT, c.7988A>T, c.8632+1G>A, and c.9501+3A>T). Differences in protocols were then assessed to determine which elements were critical in reliable assay design. RESULTS PCR primer design strategies, PCR conditions, and product detection methods, combined with a prior knowledge of expected alternative transcripts, were the key factors for accurate splicing assay results. For example, because of the position of primers and PCR extension times, several isoforms associated with BRCA1, c.594-2A>C and c.671-2A>G, were not detected by many sites. Variation was most evident for the detection of low-abundance transcripts (e.g., BRCA2 c.8632+1G>A Δ19,20 and BRCA1 c.135-1G>T Δ5q and Δ3). Detection of low-abundance transcripts was sometimes addressed by using more analytically sensitive detection methods (e.g., BRCA2 c.426-12_8delGTTTT ins18bp). CONCLUSIONS We provide recommendations for best practice and raise key issues to consider when designing mRNA assays for evaluation of unclassified sequence variants.
A Multifactorial Likelihood Model for MMR Gene Variant Classification Incorporating Probabilities Based on Sequence Bioinformatics and Tumor Characteristics: A Report from the Colon Cancer Family Registry
Background Clinical classification of rare sequence changes identified in the breast cancer susceptibility genes BRCA1 and BRCA2 is essential for appropriate genetic counselling of individuals carrying these variants. We previously showed that variant BRCA1 c.5096G>A p.Arg1699Gln in the BRCA1 transcriptional transactivation domain demonstrated equivocal results from a series of functional assays, and proposed that this variant may confer low to moderate risk of cancer. Methods Measures of genetic risk (report of family history, segregation) were assessed for 68 BRCA1 c.5096G>A p.Arg1699Gln (R1699Q) families recruited through family cancer clinics, comparing results with 34 families carrying the previously classified pathogenic BRCA1 c.5095C>T p.Arg1699Trp (R1699W) mutation at the same residue, and to 243 breast cancer families with no BRCA1 pathogenic mutation (BRCA-X). Results Comparison of BRCA1 carrier prediction scores of probands using the BOADICEA risk prediction tool revealed that BRCA1 c.5096G>A p.Arg1699Gln variant carriers had family histories that were less ‘ BRCA1 -like’ than BRCA1 c.5095C>T p.Arg1699Trp mutation carriers (p<0.00001), but more ‘ BRCA1 -like’ than BRCA-X families (p=0.0004). Further, modified segregation analysis of the subset of 30 families with additional genotyping showed that BRCA1 c.5096G >A p.Arg1699Gln had reduced penetrance compared with the average truncating BRCA1 mutation penetrance (p=0.0002), with estimated cumulative risks to age 70 of breast or ovarian cancer of 24%. Conclusions Our results provide substantial evidence that the BRCA1 c.5096G>A p.Arg1699Gln (R1699Q) variant, demonstrating ambiguous functional deficiency across multiple assays, is associated with intermediate risk of breast and ovarian cancer, highlighting challenges for risk modelling and clinical management of patients of this and other potential moderate-risk variants.
Abstract 1900: Age at last birth and endometrial cancer risk: Pooled analysis in the Epidemiology of Endometrial Cancer Consortium
Abstract Some studies show that childbearing at older age is associated with lower risk of endometrial cancer, but whether the association is independent of number of children or other factors still requires clarification. We pooled individual-level data from epidemiologic studies in the Epidemiology of Endometrial Cancer Consortium (E2C2). Data on age at last birth and/or last pregnancy were available from 14 studies: 11 case-control studies and 3 cohort studies; the latter were analyzed using a nested case-control design. A total of 9,613 endometrial cancer cases and 17,112 controls were included in the analysis. The majority of women were White (82%) and older than 55 years (69%). We estimated the effects of age at last birth using data from 12 studies and age at last pregnancy using data from 10 studies on the risk of endometrial cancer by calculating odds ratios (OR) and 95% confidence intervals (95% CI) using logistic regression models. Potential confounders included in the analysis were race, body mass index, parity, age at menarche, age at first birth, oral contraceptive use, postmenopausal hormone use, smoking status, and report of diabetes. After adjusting for potential confounders, a reduction in endometrial cancer risk was observed in women with increasing age at last birth (P trend <0.0001) and age at last pregnancy (P trend <0.0001). The OR per five-year increase in age at last birth and age at last pregnancy was 0.90 (95%CI: 0.86, 0.94) and 0.91 (95% CI: 0.87, 0.95), respectively. Women who had their last child at an age >40 years were at a 34% decreased risk compared with women who had their last child at an age <25 years (95% CI: 0.52, 0.82). Compared to women with age at last pregnancy <25 years, those with age at last pregnancy >40 years had a 30% decreased risk of endometrial cancer (95%CI: 0.57, 0.86). Inverse associations were observed for Whites and Asians in race-specific analysis and also in analysis restricted to women with at least 2 births. In this large pooled analysis, we show that late age at last birth or last pregnancy is a strong and independent protective factor for endometrial cancer. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 1900. doi:10.1158/1538-7445.AM2011-1900