281 research outputs found

    Understanding Gene Panel Testing for Breast Cancer Risk

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    Polygenic tests such as genome-wide small nucleotide polymorphism (SNP) risk testing, exome or genome sequencing are currently on the horizon for genetic testing for inherited cancer risk. We are unsure of how patients would accept this future genetic testing and the best way to fully understand the experience of undergoing a polygenic test for breast cancer risk is to explore the experience of women who have already undergone the process. In Ontario, these individuals are those who have already had gene panel testing (GPT). This group’s opinions and experiences will be directly related to the refinement and modification of the existing GPT process and will provide guidance for polygenic testing offered in the future. Methods: Fourteen women who have undergone GPT in the past year were interviewed in a semi-structured manner regarding their GPT experience. Interviews were recorded and transcribed, then qualitatively coded to identify key words, phrases, and expressed concepts surrounding GPT. Results: Participants had an overall favourable opinion regarding their GPT experience, with minor changes to be considered in future provision of GPT. In general, GPT appears to be well-tolerated within the context of a traditional genetics assessment and participants that did not receive a clinically significant result through GPT felt that they would be open to pursuing other forms of genetic testing in the future such as polygenic testing, despite the possibility of receiving an uncertain result

    Worry Is Good for Breast Cancer Screening: A Study of Female Relatives from the Ontario Site of the Breast Cancer Family Registry

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    Background. Few prospective studies have examined associations between breast cancer worry and screening behaviours in women with elevated breast cancer risks based on family history. Methods. This study included 901 high familial risk women, aged 23–71 years, from the Ontario site of the Breast Cancer Family Registry. Self-reported breast screening behaviours at year-one followup were compared between women at low (N=305), medium (N=433), and high (N=163) levels of baseline breast cancer worry using logistic regression. Nonlinear relationships were assessed using likelihood ratio tests. Results. A significant non-linear inverted “U” relationship was observed between breast cancer worry and mammography screening (P=0.034) for all women, where women at either low or high worry levels were less likely than those at medium to have a screening mammogram. A similar significant non-linear inverted “U” relationship was also found among all women and women at low familial risk for worry and screening clinical breast examinations (CBEs). Conclusions. Medium levels of cancer worries predicted higher rates of screening mammography and CBE among high-risk women

    Accuracy of Risk Estimates from the iPrevent Breast Cancer Risk Assessment and Management Tool.

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    BACKGROUND: iPrevent is an online breast cancer (BC) risk management decision support tool. It uses an internal switching algorithm, based on a woman's risk factor data, to estimate her absolute BC risk using either the International Breast Cancer Intervention Study (IBIS) version 7.02, or Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm version 3 models, and then provides tailored risk management information. This study assessed the accuracy of the 10-year risk estimates using prospective data. METHODS: iPrevent-assigned 10-year invasive BC risk was calculated for 15 732 women aged 20-70 years and without BC at recruitment to the Prospective Family Study Cohort. Calibration, the ratio of the expected (E) number of BCs to the observed (O) number and discriminatory accuracy were assessed. RESULTS: During the 10 years of follow-up, 619 women (3.9%) developed BC compared with 702 expected (E/O = 1.13; 95% confidence interval [CI] =1.05 to 1.23). For women younger than 50 years, 50 years and older, and BRCA1/2-mutation carriers and noncarriers, E/O was 1.04 (95% CI = 0.93 to 1.16), 1.24 (95% CI = 1.11 to 1.39), 1.13 (95% CI = 0.96 to 1.34), and 1.13 (95% CI = 1.04 to 1.24), respectively. The C-statistic was 0.70 (95% CI = 0.68 to 0.73) overall and 0.74 (95% CI = 0.71 to 0.77), 0.63 (95% CI = 0.59 to 0.66), 0.59 (95% CI = 0.53 to 0.64), and 0.65 (95% CI = 0.63 to 0.68), respectively, for the subgroups above. Applying the newer IBIS version 8.0b in the iPrevent switching algorithm improved calibration overall (E/O = 1.06, 95% CI = 0.98 to 1.15) and in all subgroups, without changing discriminatory accuracy. CONCLUSIONS: For 10-year BC risk, iPrevent had good discriminatory accuracy overall and was well calibrated for women aged younger than 50 years. Calibration may be improved in the future by incorporating IBIS version 8.0b

    Evaluation of polygenic risk scores for breast and ovarian cancer risk prediction in BRCA1 and BRCA2 mutation carriers

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    Background: Genome-wide association studies (GWAS) have identified 94 common single-nucleotide polymorphisms (SNPs) associated with breast cancer (BC) risk and 18 associated with ovarian cancer (OC) risk. Several of these are also associated with risk of BC or OC for women who carry a pathogenic mutation in the high-risk BC and OC genes BRCA1 or BRCA2. The combined effects of these variants on BC or OC risk for BRCA1 and BRCA2 mutation carriers have not yet been assessed while their clinical management could benefit from improved personalized risk estimates. Methods: We constructed polygenic risk scores (PRS) using BC and OC susceptibility SNPs identified through population-based GWAS: for BC (overall, estrogen receptor [ER]-positive, and ER-negative) and for OC. Using data from 15 252 female BRCA1 and 8211 BRCA2 carriers, the association of each PRS with BC or OC risk was evaluated using a weighted cohort approach, with time to diagnosis as the outcome and estimation of the hazard ratios (HRs) per standard deviation increase in the PRS. Results: The PRS for ER-negative BC displayed the strongest association with BC risk in BRCA1 carriers (HR = 1.27, 95% confidence interval [CI] = 1.23 to 1.31, P = 8.2 x 10(53)). In BRCA2 carriers, the strongest association with BC risk was seen for the overall BC PRS (HR = 1.22, 95% CI = 1.17 to 1.28, P = 7.2 x 10(-20)). The OC PRS was strongly associated with OC risk for both BRCA1 and BRCA2 carriers. These translate to differences in absolute risks (more than 10% in each case) between the top and bottom deciles of the PRS distribution; for example, the OC risk was 6% by age 80 years for BRCA2 carriers at the 10th percentile of the OC PRS compared with 19% risk for those at the 90th percentile of PRS. Conclusions: BC and OC PRS are predictive of cancer risk in BRCA1 and BRCA2 carriers. Incorporation of the PRS into risk prediction models has promise to better inform decisions on cancer risk management

    Breast cancer risks associated with missense variants in breast cancer susceptibility genes

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    BACKGROUND: Protein truncating variants in ATM, BRCA1, BRCA2, CHEK2, and PALB2 are associated with increased breast cancer risk, but risks associated with missense variants in these genes are uncertain. METHODS: We analyzed data on 59,639 breast cancer cases and 53,165 controls from studies participating in the Breast Cancer Association Consortium BRIDGES project. We sampled training (80%) and validation (20%) sets to analyze rare missense variants in ATM (1146 training variants), BRCA1 (644), BRCA2 (1425), CHEK2 (325), and PALB2 (472). We evaluated breast cancer risks according to five in silico prediction-of-deleteriousness algorithms, functional protein domain, and frequency, using logistic regression models and also mixture models in which a subset of variants was assumed to be risk-associated. RESULTS: The most predictive in silico algorithms were Helix (BRCA1, BRCA2 and CHEK2) and CADD (ATM). Increased risks appeared restricted to functional protein domains for ATM (FAT and PIK domains) and BRCA1 (RING and BRCT domains). For ATM, BRCA1, and BRCA2, data were compatible with small subsets (approximately 7%, 2%, and 0.6%, respectively) of rare missense variants giving similar risk to those of protein truncating variants in the same gene. For CHEK2, data were more consistent with a large fraction (approximately 60%) of rare missense variants giving a lower risk (OR 1.75, 95% CI (1.47-2.08)) than CHEK2 protein truncating variants. There was little evidence for an association with risk for missense variants in PALB2. The best fitting models were well calibrated in the validation set. CONCLUSIONS: These results will inform risk prediction models and the selection of candidate variants for functional assays and could contribute to the clinical reporting of gene panel testing for breast cancer susceptibility

    Common variants in LSP1, 2q35 and 8q24 and breast cancer risk for BRCA1 and BRCA2 mutation carriers

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    Genome-wide association studies of breast cancer have identified multiple single nucleotide polymorphisms (SNPs) that are associated with increased breast cancer risks in the general population. In a previous study, we demonstrated that the minor alleles at three of these SNPs, in FGFR2, TNRC9 and MAP3K1, also confer increased risks of breast cancer for BRCA1 or BRCA2 mutation carriers. Three additional SNPs rs3817198 at LSP1, rs13387042 at 2q35 and rs13281615 at 8q24 have since been reported to be associated with breast cancer in the general population, and in this study we evaluated their association with breast cancer risk in 9442 BRCA1 and 5665 BRCA2 mutation carriers from 33 study centres. The minor allele of rs3817198 was associated with increased breast cancer risk only for BRCA2 mutation carriers [hazard ratio (HR) = 1.16, 95% CI: 1.07–1.25, P-trend = 2.8 × 10−4]. The best fit for the association of SNP rs13387042 at 2q35 with breast cancer risk was a dominant model for both BRCA1 and BRCA2 mutation carriers (BRCA1: HR = 1.14, 95% CI: 1.04–1.25, P = 0.0047; BRCA2: HR = 1.18 95% CI: 1.04–1.33, P = 0.0079). SNP rs13281615 at 8q24 was not associated with breast cancer for either BRCA1 or BRCA2 mutation carriers, but the estimated association for BRCA2 mutation carriers (per-allele HR = 1.06, 95% CI: 0.98–1.14) was consistent with odds ratio estimates derived from population-based case–control studies. The LSP1 and 2q35 SNPs appear to interact multiplicatively on breast cancer risk for BRCA2 mutation carriers. There was no evidence that the associations vary by mutation type depending on whether the mutated protein is predicted to be stable or not

    Identification of new genetic susceptibility loci for breast cancer through consideration of gene-environment interactions

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    Genes 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/m(2) (OR = 1.26, 95% CI 1.15–1.38) but not in women with a BMI of 30 kg/m(2) 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

    Spectrum and Frequency of Germline FANCM Protein-Truncating Variants in 44,803 European Female Breast Cancer Cases

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