Citations

ABSTRACTIntroduction: Valosin‐containing protein (VCP) is a ubiquitously expressed, multifunctional AAA‐ATPase protein. Its dominant mutations cause hereditary inclusion body myopathy associated with Paget disease of bone and frontotemporal dementia (IBMPFD) or amyotrophic lateral sclerosis. The pattern of muscle weakness in IBMPFD patients is variable and includes limb‐girdle, scapuloperoneal, distal, or axial distributions. Case Report: We report a 63‐year‐old man with progressive scapuloperoneal weakness, head drop, and hyperCKemia since age 40 years. Electromyography showed myopathic changes and rare myotonic discharges. Muscle biopsy revealed numerous lobulated fibers, few fibers with glycogen accumulation, and rare fibers with polyglucosan bodies. Rimmed vacuoles and congophilic inclusions, often seen in IBMPFD, were absent. VCP sequencing identified a novel heterozygous c. 1160G>A mutation resulting in p.Asn387Ser substitution. Conclusions: Our patient broadens the pathological spectrum of VCP‐myopathy and emphasizes the importance of VCP analysis in patients with scapuloperoneal muscular dystrophy despite the absence of Paget disease, dementia, rimmed vacuoles, or intracellular amyloid deposition. Muscle Nerve 50:295–299, 2014

The cloning of the breast cancer susceptibility genes BRCA1 and BRCA2 nearly two decades ago helped set in motion an avalanche of research exploring how genomic information can be optimally applied to identify and clinically care for individuals with a high risk of developing cancer. Genetic testing for mutations in BRCA1 , BRCA2 , and other breast cancer susceptibility genes has since proved to be a valuable tool for determining eligibility for enhanced screening and prevention strategies, as well as for identifying patients most likely to benefit from a targeted therapy. Here, we discuss the landscape of inherited mutations and sequence variants in BRCA1 and BRCA2 , the complexities of determining disease risk when the pathogenicity of sequence variants is uncertain, and current strategies for clinical management of women who carry BRCA1/2 mutations.

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.

Abstract Part of the substantial unexplained familial aggregation of breast cancer may be due to interactions between common variants, but few studies have had adequate statistical power to detect interactions of realistic magnitude. We aimed to assess all two-way interactions in breast cancer susceptibility between 70 917 single nucleotide polymorphisms (SNPs) selected primarily based on prior evidence of a marginal effect. Thirty-eight international studies contributed data for 46 450 breast cancer cases and 42 461 controls of European origin as part of a multi-consortium project (COGS). First, SNPs were preselected based on evidence (P < 0.01) of a per-allele main effect, and all two-way combinations of those were evaluated by a per-allele (1 d.f.) test for interaction using logistic regression. Second, all 2.5 billion possible two-SNP combinations were evaluated using Boolean operation-based screening and testing, and SNP pairs with the strongest evidence of interaction (P < 10−4) were selected for more careful assessment by logistic regression. Under the first approach, 3277 SNPs were preselected, but an evaluation of all possible two-SNP combinations (1 d.f.) identified no interactions at P < 10−8. Results from the second analytic approach were consistent with those from the first (P > 10−10). In summary, we observed little evidence of two-way SNP interactions in breast cancer susceptibility, despite the large number of SNPs with potential marginal effects considered and the very large sample size. This finding may have important implications for risk prediction, simplifying the modelling required. Further comprehensive, large-scale genome-wide interaction studies may identify novel interacting loci if the inherent logistic and computational challenges can be overcome.

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.

Abstract Initial genome wide association studies (GWAS) of common cancers focused on combining all available cases in order to maximize the statistical power of the studies. While many genome wide significant associations (p < 5 × 10−8) were observed, this approach overlooked the possibility that certain genetic risk factors might have greater effects in specific populations. With this in mind more recent studies have focused on associations between common genetic variants and disease in populations other than those of northern European ancestry. In addition, GWAS of predisposed individuals, such as carriers of BRCA1 and BRCA2 mutations, have been conducted based on the hypothesis that unique modifiers of breast and ovarian cancer risk might influence disease in these populations. More recently, associations with histological subtypes of tumors have been observed for a number of different cancer types. In the setting of breast cancer, specific associations with estrogen receptor status of tumors and even triple negative tumors (estrogen receptor, progesterone receptor, and HER2 negative) have been reported. Ongoing studies further suggest that specific associations with histochemical markers and tumor grade may also exist in the general population. Here we will discuss recent associations between genetic variants and subpopulations of disease using breast cancer as a model, and consider the importance of these findings for an improved understanding of the etiology of breast cancer and enhanced cancer risk assessment. Citation Format: Fergus J. Couch. Tumor heterogeneity: Making the most of diversity. [abstract]. In: Proceedings of the AACR Special Conference on Post-GWAS Horizons in Molecular Epidemiology: Digging Deeper into the Environment; 2012 Nov 11-14; Hollywood, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2012;21(11 Suppl):Abstract nr IA11A.

The cytochrome P450 2B6 (CYP2B6) is involved in the metabolism of testosterone. Functional changes in this enzyme may influence endogenous hormone exposure, which has been associated with risk of breast cancer. To assess potential associations between two functional polymorphisms CYP2B6_516_G>T (rs3745274) and CYP2B6_785_A>G (rs2279343) and breast cancer risk, we established a specific matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry assay. The GENICA breast cancer case–control study showed associations between the variant genotypes CYP2B6_516_TT and CYP2B6_785_GG and breast cancer risk with odds ratios (ORs) of 1.34 (p = 0.001) and 1.31 (p = 0.002), respectively. A similar effect was observed for carriers of the CYP2B6_516_T allele in a validation study including four independent studies from Germany, Sweden and USA. In a pooled analysis of all five studies involving 4,638 breast cancer cases and 3,594 controls of European ancestry, carriers of the CYP2B6_516_G and the CYP2B6_785_G variant had an increased breast cancer risk with ORs of 1.10 (p = 0.027) and 1.10 (p = 0.031), respectively. We conclude that the genetic variants CYP2B6_516_G and CYP2B6_785_G (designated CYP2B6*6), which are known to decrease activity of the CYP2B6 enzyme, contribute to an increased breast cancer risk.

AbstractIntroduction.DNA variants of uncertain significance (VUS) are common outcomes of clinical genetic testing for susceptibility to cancer. A statistically rigorous model that provides a pathogenicity score for each variant has been developed to aid in the clinical management of patients undergoing genetic testing.Methods.The information in this article is derived from multiple publications on VUS in BRCA genes, distilled for communicating with clinicians who may encounter VUS in their practice.Results.The posterior probability scores for BRCA1 or BRCA2 VUS, calculated from a multifactorial likelihood model, are explained, and links for looking up specific VUS are provided. The International Agency on Cancer Research (IARC) of the World Health Organization has proposed a simple five-tier system for clinical management that is not widely known to clinicians. Classes 1 and 2 in this system are managed as neutral variants, classes 4 and 5 are managed as pathogenic variants, and class 3 variants still have insufficient evidence to move to either end of this scale and, thus, cannot be used in medical management.Conclusions.Development of models that integrate multiple independent lines of evidence has allowed classification of a growing number of VUS in the BRCA1 and BRCA2 genes. The pathogenicity score that is generated by this model maps to the IARC system for clinical management, which will assist clinicians in the medical management of those patients who obtain a VUS result upon testing.