DNA methylation profiling to assess pathogenicity of BRCA1 unclassified variants in breast cancer

Germline pathogenic mutations in BRCA1 increase risk of developing breast cancer. Screening for mutations in BRCA1 frequently identifies sequence variants of unknown pathogenicity and recent work has aimed to develop methods for determining pathogenicity. We previously observed that tumor DNA methylation can differentiate BRCA1-mutated from BRCA1-wild type tumors. We hypothesized that we could predict pathogenicity of variants based on DNA methylation profiles of tumors that had arisen in carriers of unclassified variants. We selected 150 FFPE breast tumor DNA samples [47 BRCA1 pathogenic mutation carriers, 65 BRCAx (BRCA1-wild type), 38 BRCA1 test variants] and analyzed a subset (n=54) using the Illumina 450K methylation platform, using the remaining samples for bisulphite pyrosequencing validation. Three validated markers (BACH2, C8orf31, and LOC654342) were combined with sequence bioinformatics in a model to predict pathogenicity of 27 variants (independent test set). Predictions were compared with standard multifactorial likelihood analysis. Prediction was consistent for c.5194-12G>A (IVS 19-12 G>A) (P>0.99); 13 variants were considered not pathogenic or likely not pathogenic using both approaches. We conclude that tumor DNA methylation data alone has potential to be used in prediction of BRCA1 variant pathogenicity but is not independent of estrogen receptor status and grade, which are used in current multifactorial models to predict pathogenicity

Genotypic and phenotypic analysis of familial male breast cancer shows under representation of the HER2 and basal subtypes in BRCA-associated carcinomas

BACKGROUND: Male breast cancer (MBC) is an uncommon and relatively uncharacterised disease accounting for <1% of all breast cancers. A significant proportion occurs in families with a history of breast cancer and in particular those carrying BRCA2 mutations. Here we describe clinicopathological features and genomic BRCA1 and BRCA2 mutation status in a large cohort of familial MBCs. METHODS: Cases (n=60) included 3 BRCA1 and 25 BRCA2 mutation carries, and 32 non-BRCA1/2 (BRCAX) carriers with strong family histories of breast cancer. The cohort was examined with respect to mutation status, clinicopathological parameters including TNM staging, grade, histological subtype and intrinsic phenotype. RESULTS: Compared to the general population, MBC incidence was higher in all subgroups. In contrast to female breast cancer (FBC) there was greater representation of BRCA2 tumours (41.7% vs 8.3%, p=0.0008) and underrepresentation of BRCA1 tumours (5.0% vs 14.4%, p=0.0001). There was no correlation between mutation status and age of onset, disease specific survival (DSS) or other clincopathological factors. Comparison with sporadic MBC studies showed similar clinicopathological features. Prognostic variables affecting DSS included primary tumour size (p=0.003, HR:4.26 95%CI 1.63-11.11), age (p=0.002, HR:4.09 95%CI 1.65-10.12), lymphovascular (p=0.019, HR:3.25 95%CI 1.21-8.74) and perineural invasion (p=0.027, HR:2.82 95%CI 1.13-7.06). Unlike familial FBC, the histological subtypes seen in familial MBC were more similar to those seen in sporadic MBC with 46 (76.7%) pure invasive ductal carcinoma of no special type (IDC-NST), 2 (3.3%) invasive lobular carcinomas and 4 (6.7%) invasive papillary carcinoma. A further 8 (13.3%) IDC-NST had foci of micropapillary differentiation, with a strong trend for co-occurrence in BRCA2 carriers (p=0.058). Most tumours were of the luminal phenotype (89.7%), with infrequent HER2 (8.6%) and basal (1.7%) phenotype tumours seen. CONCLUSION: MBC in BRCA1/2 carriers and BRCAX families is different to females. Unlike FBC, a clear BRCA1 phenotype is not seen but a possible BRCA2 phenotype of micropapillary histological subtype is suggested. Comparison with sporadic MBCs shows this to be a high-risk population making further recruitment and investigation of this cohort of value in further understanding these uncommon tumours

The androgen receptor CAG repeat polymorphism and modification of breast cancer risk in BRCA1 and BRCA2 mutation carriers.

INTRODUCTION: The androgen receptor (AR) gene exon 1 CAG repeat polymorphism encodes a string of 9-32 glutamines. Women with germline BRCA1 mutations who carry at least one AR allele with 28 or more repeats have been reported to have an earlier age at onset of breast cancer. METHODS: A total of 604 living female Australian and British BRCA1 and/or BRCA2 mutation carriers from 376 families were genotyped for the AR CAG repeat polymorphism. The association between AR genotype and disease risk was assessed using Cox regression. AR genotype was analyzed as a dichotomous covariate using cut-points previously reported to be associated with increased risk among BRCA1 mutation carriers, and as a continuous variable considering smaller allele, larger allele and average allele size. RESULTS: There was no evidence that the AR CAG repeat polymorphism modified disease risk in the 376 BRCA1 or 219 BRCA2 mutation carriers screened successfully. The rate ratio associated with possession of at least one allele with 28 or more CAG repeats was 0.74 (95% confidence interval 0.42-1.29; P = 0.3) for BRCA1 carriers, and 1.12 (95% confidence interval 0.55-2.25; P = 0.8) for BRCA2 carriers. CONCLUSION: The AR exon 1 CAG repeat polymorphism does not appear to have an effect on breast cancer risk in BRCA1 or BRCA2 mutation carriers

Breast cancer risk prediction using a polygenic risk score in the familial setting: a prospective study from the Breast Cancer Family Registry and kConFab.

PURPOSE: This study examined the utility of sets of single-nucleotide polymorphisms (SNPs) in familial but non-BRCA-associated breast cancer (BC). METHODS: We derived a polygenic risk score (PRS) based on 24 known BC risk SNPs for 4,365 women from the Breast Cancer Family Registry and Kathleen Cuningham Consortium Foundation for Research into Familial Breast Cancer familial BC cohorts. We compared scores for women based on cancer status at baseline; 2,599 women unaffected at enrollment were followed-up for an average of 7.4 years. Cox proportional hazards regression was used to analyze the association of PRS with BC risk. The BOADICEA risk prediction algorithm was used to measure risk based on family history alone. RESULTS: The mean PRS at baseline was 2.25 (SD, 0.35) for affected women and was 2.17 (SD, 0.35) for unaffected women from combined cohorts (P < 10-6). During follow-up, 205 BC cases occurred. The hazard ratios for continuous PRS (per SD) and upper versus lower quintiles were 1.38 (95% confidence interval: 1.22-1.56) and 3.18 (95% confidence interval: 1.84-5.23) respectively. Based on their PRS-based predicted risk, management for up to 23% of women could be altered. CONCLUSION: Including BC-associated SNPs in risk assessment can provide more accurate risk prediction than family history alone and can influence recommendations for cancer screening and prevention modalities for high-risk women.Genet Med 19 1, 30-35.National Institutes of HealthThis is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/gim.2016.4

High-throughput automated scoring of Ki67 in breast cancer tissue microarrays from the Breast Cancer Association Consortium.

Automated methods are needed to facilitate high-throughput and reproducible scoring of Ki67 and other markers in breast cancer tissue microarrays (TMAs) in large-scale studies. To address this need, we developed an automated protocol for Ki67 scoring and evaluated its performance in studies from the Breast Cancer Association Consortium. We utilized 166 TMAs containing 16,953 tumour cores representing 9,059 breast cancer cases, from 13 studies, with information on other clinical and pathological characteristics. TMAs were stained for Ki67 using standard immunohistochemical procedures, and scanned and digitized using the Ariol system. An automated algorithm was developed for the scoring of Ki67, and scores were compared to computer assisted visual (CAV) scores in a subset of 15 TMAs in a training set. We also assessed the correlation between automated Ki67 scores and other clinical and pathological characteristics. Overall, we observed good discriminatory accuracy (AUC = 85%) and good agreement (kappa = 0.64) between the automated and CAV scoring methods in the training set. The performance of the automated method varied by TMA (kappa range= 0.37-0.87) and study (kappa range = 0.39-0.69). The automated method performed better in satisfactory cores (kappa = 0.68) than suboptimal (kappa = 0.51) cores (p-value for comparison = 0.005); and among cores with higher total nuclei counted by the machine (4,000-4,500 cells: kappa = 0.78) than those with lower counts (50-500 cells: kappa = 0.41; p-value = 0.010). Among the 9,059 cases in this study, the correlations between automated Ki67 and clinical and pathological characteristics were found to be in the expected directions. Our findings indicate that automated scoring of Ki67 can be an efficient method to obtain good quality data across large numbers of TMAs from multicentre studies. However, robust algorithm development and rigorous pre- and post-analytical quality control procedures are necessary in order to ensure satisfactory performance.ABCS was supported by the Dutch Cancer Society [grants NKI 2007-3839; 2009-4363]; BBMRI-NL, which is a Research Infrastructure financed by the Dutch government (NWO 184.021.007); and the Dutch National Genomics Initiative. CNIO-BCS was supported by the Genome Spain Foundation, the Red Tematica de Investigacion Cooperativa en Cancer and grants from the Asociacion Espaola Contra el Cancer and the Fondo de Investigacion Sanitario (PI11/00923 and PI081120). The Human Genotyping-CEGEN Unit (CNIO) is supported by the Instituto de Salud Carlos III. The ESTHER study was supported by a grant from the Baden Wurttemberg Ministry of Science, Research and Arts. Additional cases were recruited in the context of the VERDI study, which was supported by a grant from the German Cancer Aid (Deutsche Krebshilfe). The KBCP was financially supported by the special Government Funding (EVO) of Kuopio University Hospital grants, Cancer Fund of North Savo, the Finnish Cancer Organizations, the Academy of Finland and by the strategic funding of the University of Eastern Finland. We wish to thank Heather Thorne, Eveline Niedermayr, all the kConFab research nurses and staff, the heads and staff of the Family Cancer Clinics, and the Clinical Follow Up Study (which has received funding from the NHMRC, the National Breast Cancer Foundation, Cancer Australia, and the National Institute of Health (USA)) for their contributions to this resource, and the many families who contribute to kConFab. kConFab is supported by a grant from the National Breast Cancer Foundation, and previously by the National Health and Medical Research Council (NHMRC), the Queensland Cancer Fund, the Cancer Councils of New South Wales, Victoria, Tasmania and South Australia, and the Cancer Foundation of Western Australia. The MARIE study was supported by the Deutsche Krebshilfe e.V. [70-2892-BR I, 106332, 108253, 108419], the Hamburg Cancer Society, the German Cancer Research Center (DKFZ) and the Federal Ministry of Education and Research (BMBF) Germany [01KH0402]. The MCBCS was supported by an NIH Specialized Program of Research Excellence (SPORE) in Breast Cancer [CA116201], the Breast Cancer Research Foundation, the Mayo Clinic Breast Cancer Registry and a generous gift from the David F. and Margaret T. Grohne Family Foundation and the Ting Tsung and Wei Fong Chao Foundation. ORIGO authors thank E. Krol-Warmerdam, and J. Blom; The contributing studies were funded by grants from the Dutch Cancer Society (UL1997-1505) and the Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL CP16). PBCS was funded by Intramural Research Funds of the National Cancer Institute, Department of Health and Human Services, USA. The RBCS was funded by the Dutch Cancer Society (DDHK 2004-3124, DDHK 2009-4318). SEARCH is funded by programme grant from Cancer Research UK [C490/A10124. C490/A16561] and supported by the UK National Institute for Health Research Biomedical Research Centre at the University of Cambridge. Part of this work was supported by the European Community’s Seventh Framework Programme under grant agreement number 223175 (grant number HEALTH-F2-2009223175) (COGS). The UKBGS is funded by Breakthrough Breast Cancer and the Institute of Cancer Research (ICR), London. ICR acknowledges NHS funding to the NIHR Biomedical Research Centre. We acknowledge funds from Breakthrough Breast Cancer, UK, in support of MGC at the time this work was carried out and funds from the Cancer Research, UK, in support of MA.This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1002/cjp2.4

Ассоциативно-семантическая группа как языковая основа концепта

Статья посвящена описанию особой лексико-семантической парадигмы ассоциативно-семантической группы, которая является частью ассоциативно- семантического комплекса и рассматривается как языковая основа концепта. Исследование проведено с применением описательного, структурного и функционального методов.Статтю присвячено опису особливої лексико-семантичної парадигми асоціативно-семантичної групи, яка є частиною асоціативно-семантичного комплексу і являє собою мовну основу концепту. Дослідження проведено із застосуванням описового, структурного та функціонального методів.The particular lexico-semantic paradigm – associative-semantic group (ASG) which is the part of associative-semantic complex (ASC) – is investigated in the article as a linguistic base of concept. Descriptive, structural, and functional methods were used

Ovarian and Breast Cancer Risks Associated With Pathogenic Variants in RAD51C and RAD51D

Background: The purpose of this study was to estimate precise age-specific tubo-ovarian carcinoma (TOC) and breast cancer (BC) risks for carriers of pathogenic variants in RAD51C and RAD51D. Methods: We analyzed data from 6178 families, 125 with pathogenic variants in RAD51C, and 6690 families, 60 with pathogenic variants in RAD51D. TOC and BC relative and cumulative risks were estimated using complex segregation analysis to model the cancer inheritance patterns in families while adjusting for the mode of ascertainment of each family. All statistical tests were two-sided. Results: Pathogenic variants in both RAD51C and RAD51D were associated with TOC (RAD51C: relative risk [RR] = 7.55, 95% confidence interval [CI] = 5.60 to 10.19; P = 5 x 10(-40); RAD51D: RR = 7.60, 95% CI = 5.61 to 10.30; P = 5 x 10(-39)) and BC (RAD51C: RR =1.99, 95% CI = 1.39 to 2.85; P = 1.55 x 10(-4); RAD51D: RR = 1.83, 95% CI = 1.24 to 2.72; P = .002). For both RAD51C and RAD51D, there was a suggestion that the TOC relative risks increased with age until around age 60 years and decreased thereafter. The estimated cumulative risks of developing TOC to age 80 years were 11% (95% CI = 6% to 21%) for RAD51C and 13% (95% CI = 7% to 23%) for RAD51D pathogenic variant carriers. The estimated cumulative risks of developing BC to 80 years were 21% (95% CI = 15% to 29%) for RAD51C and 20% (95% CI = 14% to 28%) for RAD51D pathogenic variant carriers. Both TOC and BC risks for RAD51C and RAD51D pathogenic variant carriers varied by cancer family history and could be as high as 32-36% for TOC, for carriers with two first-degree relatives diagnosed with TOC, or 44-46% for BC, for carriers with two first-degree relatives diagnosed with BC. Conclusions: These estimates will facilitate the genetic counseling of RAD51C and RAD51D pathogenic variant carriers and justify the incorporation of RAD51C and RAD51D into cancer risk prediction models.Peer reviewe