Amanda B. Spurdle

A common coding variant in CASP8 is associated with breast cancer risk

The Breast Cancer Association Consortium (BCAC) has been established to conduct combined case-control analyses with augmented statistical power to try to confirm putative genetic associations with breast cancer. We genotyped nine SNPs for which there was some prior evidence of an association with breast cancer: CASP8 D302H (rs1045485), IGFBP3 −202 C → A (rs2854744), SOD2 V16A (rs1799725), TGFB1 L10P (rs1982073), ATM S49C (rs1800054), ADH1B 3′ UTR A → G (rs1042026), CDKN1A S31R (rs1801270), ICAM5 V301I (rs1056538) and NUMA1 A794G (rs3750913). We included data from 9–15 studies, comprising 11,391–18,290 cases and 14,753–22,670 controls. We found evidence of an association with breast cancer for CASP8 D302H (with odds ratios (OR) of 0.89 (95% confidence interval (c.i.): 0.85–0.94) and 0.74 (95% c.i.: 0.62–0.87) for heterozygotes and rare homozygotes, respectively, compared with common homozygotes; Ptrend = 1.1 × 10−7) and weaker evidence for TGFB1 L10P (OR = 1.07 (95% c.i.: 1.02–1.13) and 1.16 (95% c.i.: 1.08–1.25), respectively; Ptrend = 2.8 × 10−5). These results demonstrate that common breast cancer susceptibility alleles with small effects on risk can be identified, given sufficiently powerful studies.NOTE: In the version of this article initially published, there was an error that affected the calculations of the odds ratios, confidence intervals, between-study heterogeneity, trend test and test for association for SNP ICAM5 V301I in Table 1 (ICAM5 V301I); genotype counts in Supplementary Table 2 (ICAM5; ICR_FBCS and Kuopio studies) and minor allele frequencies, trend test and odds ratios for heterozygotes and rare homozygotes in Supplementary Table 3 (ICAM5; ICR_FBCS and Kuopio studies). The errors in Table 1 have been corrected in the PDF version of the article. The errors in supplementary information have been corrected online.

Sequence variant classification and reporting: recommendations for improving the interpretation of cancer susceptibility genetic test results

Genetic testing of cancer susceptibility genes is now widely applied in clinical practice to predict risk of developing cancer. In general, sequence‐based testing of germline DNA is used to determine whether an individual carries a change that is clearly likely to disrupt normal gene function. Genetic testing may detect changes that are clearly pathogenic, clearly neutral, or variants of unclear clinical significance. Such variants present a considerable challenge to the diagnostic laboratory and the receiving clinician in terms of interpretation and clear presentation of the implications of the result to the patient. There does not appear to be a consistent approach to interpreting and reporting the clinical significance of variants either among genes or among laboratories. The potential for confusion among clinicians and patients is considerable and misinterpretation may lead to inappropriate clinical consequences. In this article we review the current state of sequence‐based genetic testing, describe other standardized reporting systems used in oncology, and propose a standardized classification system for application to sequence‐based results for cancer predisposition genes. We suggest a system of five classes of variants based on the degree of likelihood of pathogenicity. Each class is associated with specific recommendations for clinical management of at‐risk relatives that will depend on the syndrome. We propose that panels of experts on each cancer predisposition syndrome facilitate the classification scheme and designate appropriate surveillance and cancer management guidelines. The international adoption of a standardized reporting system should improve the clinical utility of sequence‐based genetic tests to predict cancer risk. Hum Mutat 29(11), 1282–1291, 2008.

Type I and II Endometrial Cancers: Have They Different Risk Factors?

PURPOSE Endometrial cancers have long been divided into estrogen-dependent type I and the less common clinically aggressive estrogen-independent type II. Little is known about risk factors for type II tumors because most studies lack sufficient cases to study these much less common tumors separately. We examined whether so-called classical endometrial cancer risk factors also influence the risk of type II tumors. PATIENTS AND METHODS Individual-level data from 10 cohort and 14 case-control studies from the Epidemiology of Endometrial Cancer Consortium were pooled. A total of 14,069 endometrial cancer cases and 35,312 controls were included. We classified endometrioid (n = 7,246), adenocarcinoma not otherwise specified (n = 4,830), and adenocarcinoma with squamous differentiation (n = 777) as type I tumors and serous (n = 508) and mixed cell (n = 346) as type II tumors. RESULTS Parity, oral contraceptive use, cigarette smoking, age at menarche, and diabetes were associated with type I and type II tumors to similar extents. Body mass index, however, had a greater effect on type I tumors than on type II tumors: odds ratio (OR) per 2 kg/m(2) increase was 1.20 (95% CI, 1.19 to 1.21) for type I and 1.12 (95% CI, 1.09 to 1.14) for type II tumors (P heterogeneity < .0001). Risk factor patterns for high-grade endometrioid tumors and type II tumors were similar. CONCLUSION The results of this pooled analysis suggest that the two endometrial cancer types share many common etiologic factors. The etiology of type II tumors may, therefore, not be completely estrogen independent, as previously believed.

Common Breast Cancer-Predisposition Alleles Are Associated with Breast Cancer Risk in BRCA1 and BRCA2 Mutation Carriers

Germline mutations in BRCA1 and BRCA2 confer high risks of breast cancer. However, evidence suggests that these risks are modified by other genetic or environmental factors that cluster in families. A recent genome-wide association study has shown that common alleles at single nucleotide polymorphisms (SNPs) in FGFR2 (rs2981582), TNRC9 (rs3803662), and MAP3K1 (rs889312) are associated with increased breast cancer risks in the general population. To investigate whether these loci are also associated with breast cancer risk in BRCA1 and BRCA2 mutation carriers, we genotyped these SNPs in a sample of 10,358 mutation carriers from 23 studies. The minor alleles of SNP rs2981582 and rs889312 were each associated with increased breast cancer risk in BRCA2 mutation carriers (per-allele hazard ratio [HR] = 1.32, 95% CI: 1.20-1.45, p(trend) = 1.7 x 10(-8) and HR = 1.12, 95% CI: 1.02-1.24, p(trend) = 0.02) but not in BRCA1 carriers. rs3803662 was associated with increased breast cancer risk in both BRCA1 and BRCA2 mutation carriers (per-allele HR = 1.13, 95% CI: 1.06-1.20, p(trend) = 5 x 10(-5) in BRCA1 and BRCA2 combined). These loci appear to interact multiplicatively on breast cancer risk in BRCA2 mutation carriers. The differences in the effects of the FGFR2 and MAP3K1 SNPs between BRCA1 and BRCA2 carriers point to differences in the biology of BRCA1 and BRCA2 breast cancer tumors and confirm the distinct nature of breast cancer in BRCA1 mutation carriers.

Correlation of tumour BRAF mutations and MLH1 methylation with germline mismatch repair (MMR) gene mutation status: a literature review assessing utility of tumour features for MMR variant classification

Colorectal cancer (CRC) that demonstrates microsatellite instability (MSI) is caused by either germline mismatch repair (MMR) gene mutations, or ‘sporadic’ somatic tumour MLH1 promoter methylation. MLH1 promoter methylation is reportedly correlated with tumour BRAF V600E mutation status. No systematic review has been undertaken to assess the value of BRAF V600E mutation and MLH1 promoter methylation tumour markers as negative predictors of germline MMR mutation status. A literature review of CRC cohorts tested for MMR mutations, and tumour BRAF V600E mutation and/or MLH1 promoter methylation was conducted using PubMed. Studies were assessed for tumour features, stratified by tumour MMR status based on immunohistochemistry or MSI where possible. Pooled frequencies and 95% CIs were calculated using a random effects model. BRAF V600E results for 4562 tumours from 35 studies, and MLH1 promoter methylation results for 2975 tumours from 43 studies, were assessed. In 550 MMR mutation carriers, the BRAF V600E mutation frequency was 1.40% (95% CI 0.06% to 3%). In MMR mutation-negative cases, the BRAF V600E mutation frequency was 5.00% (95% CI 4% to 7%) in 1623 microsatellite stable (MSS) cases and 63.50% (95% CI 47% to 79%) in 332 cases demonstrating MLH1 methylation or MLH1 expression loss. MLH1 promoter methylation of the ‘A region’ was reported more frequently than the ‘C region’ in MSS CRCs (17% vs 0.06%, p<0.0001) and in MLH1 mutation carriers (42% vs 6%, p<0.0001), but not in MMR mutation-negative MSI-H CRCs (40% vs 47%, p=0.12). Methylation of the ‘C region’ was a predictor of MMR mutation-negative status in MSI-H CRC cases (47% vs 6% in MLH1 mutation carriers, p<0.0001). This review demonstrates that tumour BRAF V600E mutation, and MLH1 promoter ‘C region’ methylation specifically, are strong predictors of negative MMR mutation status. It is important to incorporate these features in multifactorial models aimed at predicting MMR mutation status.

Genetic and Histopathologic Evaluation of BRCA1 and BRCA2 DNA Sequence Variants of Unknown Clinical Significance

Classification of rare missense variants as neutral or disease causing is a challenge and has important implications for genetic counseling. A multifactorial likelihood model for classification of unclassified variants in BRCA1 and BRCA2 has previously been developed, which uses data on co-occurrence of the unclassified variant with pathogenic mutations in the same gene, cosegregation of the unclassified variant with affected status, and Grantham analysis of the fit between the missense substitution and the evolutionary range of variation observed at its position in the protein. We have further developed this model to take into account relevant features of BRCA1- and BRCA2-associated tumors, such as the characteristic histopathology and immunochemical profiles associated with pathogenic mutations in BRCA1, and the fact that approximately 80% of tumors from BRCA1 and BRCA2 carriers undergo inactivation of the wild-type allele by loss of heterozygosity. We examined 10 BRCA1 and 15 BRCA2 unclassified variants identified in Australian, multiple-case breast cancer families. By a combination of genetic, in silico, and histopathologic analyses, we were able to classify one BRCA1 variant as pathogenic and six BRCA1 and seven BRCA2 variants as neutral. Five of these neutral variants were also found in at least 1 of 180 healthy controls, suggesting that screening a large number of appropriate controls might be a useful adjunct to other methods for evaluation of unclassified variants.

Multiple Novel Prostate Cancer Predisposition Loci Confirmed by an International Study: The PRACTICAL Consortium

A recent genome-wide association study found that genetic variants on chromosomes 3, 6, 7, 10, 11, 19 and X were associated with prostate cancer risk. We evaluated the most significant single-nucleotide polymorphisms (SNP) in these loci using a worldwide consortium of 13 groups (PRACTICAL). Blood DNA from 7,370 prostate cancer cases and 5,742 male controls was analyzed by genotyping assays. Odds ratios (OR) associated with each genotype were estimated using unconditional logistic regression. Six of the seven SNPs showed clear evidence of association with prostate cancer (P = 0.0007-P = 10−17). For each of these six SNPs, the estimated per-allele OR was similar to those previously reported and ranged from 1.12 to 1.29. One SNP on 3p12 (rs2660753) showed a weaker association than previously reported [per-allele OR, 1.08 (95% confidence interval, 1.00-1.16; P = 0.06) versus 1.18 (95% confidence interval, 1.06-1.31)]. The combined risks associated with each pair of SNPs were consistent with a multiplicative risk model. Under this model, and in combination with previously reported SNPs on 8q and 17q, these loci explain 16% of the familial risk of the disease, and men in the top 10% of the risk distribution have a 2.1-fold increased risk relative to general population rates. This study provides strong confirmation of these susceptibility loci in multiple populations and shows that they make an important contribution to prostate cancer risk prediction. (Cancer Epidemiol Biomarkers Prev 2008;17(8):2052–61)

ENIGMA-Evidence-based network for the interpretation of germline mutant alleles: An international initiative to evaluate risk and clinical significance associated with sequence variation in BRCA1 and BRCA2 genes

As genetic testing for predisposition to human diseases has become an increasingly common practice in medicine, the need for clear interpretation of the test results is apparent. However, for many disease genes, including the breast cancer susceptibility genes BRCA1 and BRCA2, a significant fraction of tests results in the detection of a genetic variant for which disease association is not known. The finding of an “unclassified” variant (UV)/variant of uncertain significance (VUS) complicates genetic test reporting and counseling. As these variants are individually rare, a large collaboration of researchers and clinicians will facilitate studies to assess their association with cancer predisposition. It was with this in mind that the ENIGMA consortium (www.enigmaconsortium.org) was initiated in 2009. The membership is both international and interdisciplinary, and currently includes more than 100 research scientists and clinicians from 19 countries. Within ENIGMA, there are presently six working groups focused on the following topics: analysis, clinical, database, functional, tumor histopathology, and mRNA splicing. ENIGMA provides a mechanism to pool resources, exchange methods and data, and coordinately develop and apply algorithms for classification of variants in BRCA1 and BRCA2. It is envisaged that the research and clinical application of models developed by ENIGMA will be relevant to the interpretation of sequence variants in other disease genes. Hum Mutat 33:2–7, 2012.

Genetic evidence and integration of various data sources for classifying uncertain variants into a single model.

Genetic testing often results in the finding of a variant whose clinical significance is unknown. A number of different approaches have been employed in the attempt to classify such variants. For some variants, case‐control, segregation, family history, or other statistical studies can provide strong evidence of direct association with cancer risk. For most variants, other evidence is available that relates to properties of the protein or gene sequence. In this work we propose a Bayesian method for assessing the likelihood that a variant is pathogenic. We discuss the assessment of prior probability, and how to combine the various sources of data into a statistically valid integrated assessment with a posterior probability of pathogenicity. In particular, we propose the use of a two‐component mixture model to integrate these various sources of data and to estimate the parameters related to sensitivity and specificity of specific kinds of evidence. Further, we discuss some of the issues involved in this process and the assumptions that underpin many of the methods used in the evaluation process. Hum Mutat 29(11), 1265–1272, 2008.

Analysis of cancer risk and BRCA1 and BRCA2 mutation prevalence in the kConFab familial breast cancer resource.

IntroductionThe Kathleen Cuningham Foundation Consortium for Research into Familial Breast Cancer (kConFab) is a multidisciplinary, collaborative framework for the investigation of familial breast cancer. Based in Australia, the primary aim of kConFab is to facilitate high-quality research by amassing a large and comprehensive resource of epidemiological and clinical data with biospecimens from individuals at high risk of breast and/or ovarian cancer, and from their close relatives.MethodsEpidemiological, family history and lifestyle data, as well as biospecimens, are collected from multiple-case breast cancer families ascertained through family cancer clinics in Australia and New Zealand. We used the Tyrer-Cuzick algorithms to assess the prospective risk of breast cancer in women in the kConFab cohort who were unaffected with breast cancer at the time of enrolment in the study.ResultsOf kConFabs first 822 families, 518 families had multiple cases of female breast cancer alone, 239 had cases of female breast and ovarian cancer, 37 had cases of female and male breast cancer, and 14 had both ovarian cancer as well as male and female breast cancer. Data are currently held for 11,422 people and germline DNAs for 7,389. Among the 812 families with at least one germline sample collected, the mean number of germline DNA samples collected per family is nine. Of the 747 families that have undergone some form of mutation screening, 229 (31%) carry a pathogenic or splice-site mutation in BRCA1 or BRCA2. Germline DNAs and data are stored from 773 proven carriers of BRCA1 or BRCA1 mutations. kConFabs fresh tissue bank includes 253 specimens of breast or ovarian tissue – both normal and malignant – including 126 from carriers of BRCA1 or BRCA2 mutations.ConclusionThese kConFab resources are available to researchers anywhere in the world, who may apply to kConFab for biospecimens and data for use in ethically approved, peer-reviewed projects. A high calculated risk from the Tyrer-Cuzick algorithms correlated closely with the subsequent occurrence of breast cancer in BRCA1 and BRCA2 mutation positive families, but this was less evident in families in which no pathogenic BRCA1 or BRCA2 mutation has been detected.