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BRCA1 is a high-risk susceptibility gene for breast and ovarian cancer. Pathogenic protein-truncating variants are scattered across the open reading frame, but all known missense substitutions that are pathogenic because of missense dysfunction are located in either the amino-terminal RING domain or the carboxy-terminal BRCT domain. Heterodimerization of the BRCA1 and BARD1 RING domains is a molecularly defined obligate activity. Hence, we tested every BRCA1 RING domain missense substitution that can be created by a single nucleotide change for heterodimerization with BARD1 in a mammalian two-hybrid assay. Downstream of the laboratory assay, we addressed three additional challenges: assay calibration, validation thereof, and integration of the calibrated results with other available data, such as computational evidence and patient/population observational data to achieve clinically applicable classification. Overall, we found that 15%-20% of BRCA1 RING domain missense substitutions are pathogenic. Using a Bayesian point system for data integration and variant classification, we achieved clinical classification of 89% of observed missense substitutions. Moreover, among missense substitutions not present in the human observational data used here, we find an additional 45 with concordant computational and functional assay evidence in favor of pathogenicity plus 223 with concordant evidence in favor of benignity; these are particularly likely to be classified as likely pathogenic and likely benign, respectively, once human observational data become available.

The main aim of this study was to screen epigenetic modifier genes and known breast cancer driver genes for germline mutations in non-BRCA1/2 (BRCAx) breast cancer families in order to identify novel susceptibility genes of moderate–high penetrance. We screened 264 candidate susceptibility genes in 656 index cases from non-BRCA1/2 families. Potentially pathogenic candidate mutations were then genotyped in all available family members for the assessment of co-segregation of the variant with disease in the family in order to estimate the breast cancer risks associated with these mutations. For 11 of the candidate susceptibility genes, we screened an additional 800 non-BRCA1/2 breast cancer cases and 787 controls. Only two genes, CHD8 and USH2A showed any evidence of an increased risk of breast cancer (RR = 2.40 (95% CI 1.0–7.32) and 2.48 (95% CI 1.11–6.67), respectively). We found no convincing evidence that epigenetic modifier and known breast cancer driver genes carry germline mutations that increase breast cancer risk. USH2A is no longer regarded as a breast cancer driver gene and seems an implausible candidate given its association with Usher syndrome. However, somatic mutations in CHD8 have been recently reported, making it an even more promising candidate, but further analysis of CHD8 in very large cohorts of families or case–control studies would be required to determine if it is a moderate-risk breast cancer susceptibility gene.

Approximately half of the familial aggregation of breast cancer remains unexplained. A multiple-case breast cancer family exome-sequencing study identified three likely pathogenic mutations in RINT1 (NM_021930.4) not present in public sequencing databases: RINT1 c.343C>T (p.Q115X), c.1132_1134del (p.M378del), and c.1207G>T (p.D403Y). On the basis of this finding, a population-based case–control mutation-screening study was conducted that identified 29 carriers of rare (minor allele frequency < 0.5%), likely pathogenic variants: 23 in 1,313 early-onset breast cancer cases and six in 1,123 frequency-matched controls [OR, 3.24; 95% confidence interval (CI), 1.29–8.17; P = 0.013]. RINT1 mutation screening of probands from 798 multiple-case breast cancer families identified four additional carriers of rare genetic variants. Analysis of the incidence of first primary cancers in families of women carrying RINT1 mutations estimated that carriers were at increased risk of Lynch syndrome–spectrum cancers [standardized incidence ratio (SIR), 3.35; 95% CI, 1.7–6.0; P = 0.005], particularly for relatives diagnosed with cancer under the age of 60 years (SIR, 10.9; 95% CI, 4.7–21; P = 0.0003). Significance: The work described in this study adds RINT1 to the growing list of genes in which rare sequence variants are associated with intermediate levels of breast cancer risk. Given that RINT1 is also associated with a spectrum of cancers with mismatch repair defects, these findings have clinical applications and raise interesting biological questions. Cancer Discov; 4(7); 804–15. ©2014 AACR. See related commentary by Ngeow and Eng, p. 762 This article is highlighted in the In This Issue feature, p. 745

Background Characterising genetic diversity through the analysis of massively parallel sequencing (MPS) data offers enormous potential to significantly improve our understanding of the genetic basis for observed phenotypes, including predisposition to and progression of complex human disease. Great challenges remain in resolving genetic variants that are genuine from the millions of artefactual signals. Results FAVR is a suite of new methods designed to work with commonly used MPS analysis pipelines to assist in the resolution of some of the issues related to the analysis of the vast amount of resulting data, with a focus on relatively rare genetic variants. To the best of our knowledge, no equivalent method has previously been described. The most important and novel aspect of FAVR is the use of signatures in comparator sequence alignment files during variant filtering, and annotation of variants potentially shared between individuals. The FAVR methods use these signatures to facilitate filtering of (i) platform and/or mapping-specific artefacts, (ii) common genetic variants, and, where relevant, (iii) artefacts derived from imbalanced paired-end sequencing, as well as annotation of genetic variants based on evidence of co-occurrence in individuals. We applied conventional variant calling applied to whole-exome sequencing datasets, produced using both SOLiD and TruSeq chemistries, with or without downstream processing by FAVR methods. We demonstrate a 3-fold smaller rare single nucleotide variant shortlist with no detected reduction in sensitivity. This analysis included Sanger sequencing of rare variant signals not evident in dbSNP131, assessment of known variant signal preservation, and comparison of observed and expected rare variant numbers across a range of first cousin pairs. The principles described herein were applied in our recent publication identifying XRCC2 as a new breast cancer risk gene and have been made publically available as a suite of software tools. Conclusions FAVR is a platform-agnostic suite of methods that significantly enhances the analysis of large volumes of sequencing data for the study of rare genetic variants and their influence on phenotypes.

Objective:The primary aim of this study was to investigate the association of polymorphisms of TRAF1-C5, a newly identified rheumatoid arthritis (RA) risk locus in Caucasians, with susceptibility to RA and systemic lupus erythematosus (SLE) in Japanese populations. Gene expression levels of TRAF1 and C5 to assess the functional significance of genotypes were also analysed.Methods:A multicentre association study consisting of 4 RA case-control series (4397 cases and 2857 controls) and 3 SLE case-control series (591 cases and 2199 shared controls) was conducted. Genotyping was performed using TaqMan genotyping assay for two single nucleotide polymorphisms (SNPs) that showed the best evidence of association in the previous Caucasian studies. Quantifications of TRAF1 and C5 expression were performed with TaqMan expression assay.Results:Significant differences in allele frequency for both SNPs were observed between RA and control subjects (combined odds ratio = 1.09), while no significant difference was detected between patients with SLE and controls. Interestingly, alleles rs3761847 A and rs10818488 G had increased the risk for RA in the present study, while they decreased the risk in the original studies. A significant difference was found between risk allele carriers and non-carriers of rs10818488 for the expression level of TRAF1 in phorbol myristate acetate-stimulated lymphoblastoid cell lines (p = 0.04).Conclusion:Association of TRAF1-C5 locus with RA susceptibility was detected in the Japanese populations with modest magnitude, while no significant association was observed for SLE. Significant positive effect of genotype on the expression of TRAF1 might support the genetic association between TRAF1 and RA.

Objective STAT4 encodes a transcriptional factor that transmits signals induced by several key cytokines, and it might be a key molecule in the development of autoimmune diseases. Recently, a STAT4 haplotype was reported to be associated with rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) in Caucasian populations. This was replicated in a Korean RA population. Interestingly, the degree of risk of RA susceptibility with the STAT4 haplotype was similar in the Caucasian and Korean populations. The present study was undertaken to investigate the effect of STAT4 on susceptibility to RA and SLE in the Japanese. Methods We performed an association study using 3 independent Japanese RA case–control populations (total 3,567 cases and 2,199 controls) and 3 independent Japanese SLE populations (total 591 cases). All samples were genotyped using the TaqMan fluorogenic 5′ nuclease assay for single-nucleotide polymorphism (SNP) rs7574865, which tags the susceptibility haplotype. The association of the SNP with disease susceptibility in each case–control study was calculated using Fisher's exact test, and the results were combined, using the Mantel-Haenszel method, to obtain combined odds ratios (ORs). Results We observed a significant association of the STAT4 polymorphism with susceptibility to both RA and SLE. The combined ORs for RA and SLE, respectively, were 1.27 (P = 8.4 × 10−9) and 1.61 (P = 2.1 × 10−11) for allele frequency distribution; these ORs were quite similar to those previously observed in the Caucasian population. Conclusion We conclude that STAT4 is associated with RA and SLE in the Japanese. Our results indicate that STAT4 is a common genetic risk factor for autoimmune diseases, with similar strength across major racial groups.