15 research outputs found

    A role for XRCC2 gene polymorphisms in breast cancer risk and survival

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    Background The XRCC2 gene is a key mediator in the homologous recombination repair of DNA double strand breaks. It is hypothesised that inherited variants in the XRCC2 gene might also affect susceptibility to, and survival from, breast cancer. Methods The study genotyped 12 XRCC2 tagging single nucleotide polymorphisms (SNPs) in 1131 breast cancer cases and 1148 controls from the Sheffield Breast Cancer Study (SBCS), and examined their associations with breast cancer risk and survival by estimating ORs and HRs, and their corresponding 95% CIs. Positive findings were further investigated in 860 cases and 869 controls from the Utah Breast Cancer Study (UBCS) and jointly analysed together with available published data for breast cancer risk. The survival findings were further confirmed in studies (8074 cases) from the Breast Cancer Association Consortium (BCAC). Results The most significant association with breast cancer risk in the SBCS dataset was the XRCC2 rs3218408 SNP (recessive model p=2.3×10−4, minor allele frequency (MAF)=0.23). This SNP yielded an ORrec of 1.64 (95% CI 1.25 to 2.16) in a two-site analysis of SBCS and UBCS, and a meta-ORrec of 1.33 (95% CI 1.12 to 1.57) when all published data were included. This SNP may mark a rare risk haplotype carried by two in 1000 of the control population. Furthermore, the XRCC2 coding R188H SNP (rs3218536, MAF=0.08) was significantly associated with poor survival, with an increased per-allele HR of 1.58 (95% CI 1.01 to 2.49) in a multivariate analysis. This effect was still evident in a pooled meta-analysis of 8781 breast cancer patients from the BCAC (HR 1.19, 95% CI 1.05 to 1.36; p=0.01). Conclusions These findings suggest that XRCC2 SNPs may influence breast cancer risk and survival

    Selected single-nucleotide polymorphisms in <em>FOXE1, SERPINA5, FTO, EVPL, TICAM1</em> and <em>SCARB1</em> are associated with papillary and follicular thyroid cancer risk: Replication study in a German population.

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    Several single-nucleotide polymorphisms (SNPs) have been associated with papillary and follicular thyroid cancer (PTC and FTC, respectively) risk, but few have replicated. After analyzing 17525 tag SNPs in 1129 candidate genes, we found associations with PTC risk in SERPINA5, FTO, HEMGN (near FOXE1) and other genes. Here, we report results from a replication effort in a large independent PTC/FTC case-control study conducted in Germany. We evaluated the best tagging SNPs from our previous PTC study and additionally included SNPs in or near FOXE1 and NKX2-1 genes, known susceptibility loci for thyroid cancer. We genotyped 422 PTC and 130 FTC cases and 752 controls recruited from three German clinical centers. We used polytomous logistic regression to simultaneously estimate PTC and FTC associations for 79 SNPs based on log-additive models. We assessed effect modification by body mass index (BMI), gender and age for all SNPs, and selected SNP by SNP interactions. We confirmed associations with PTC and SNPs in FOXE1/HEMGN, SERPINA5 (rs2069974), FTO (rs8047395), EVPL (rs2071194), TICAM1 (rs8120) and SCARB1 (rs11057820) genes. We found associations with SNPs in FOXE1, SERPINA5, FTO, TICAM1 and HSPA6 and FTC. We found two significant interactions between FTO (rs8047395) and BMI (P = 0.0321) and between TICAM1 (rs8120) and FOXE1 (rs10984377) (P = 0.0006). Besides the known associations with FOXE1 SNPs, we confirmed additional PTC SNP associations reported previously. We also found several new associations with FTC risk and noteworthy interactions. We conclude that multiple variants and host factors might interact in complex ways to increase risk of PTC and FTC

    International study of factors affecting human chromosome translocations

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    Chromosome translocations in peripheral blood lymphocytes of normal, healthy humans increase with age, but the effects of gender, race, and cigarette smoking on background translocation yields have not been examined systematically. Further, the shape of the relationship between age and translocation frequency (TF) has not been definitively determined. We collected existing data from 16 laboratories in North America, Europe, and Asia on TFs measured in peripheral blood lymphocytes by fluorescence in situ hybridization whole chromosome painting among 1933 individuals. In Poisson regression models, age, ranging from newborns (cord blood) to 85 years, was strongly associated with TF and this relationship showed significant upward curvature at older ages versus a linear relationship (p < 0.001). Ever smokers had significantly higher TFs than non-smokers (rate ratio (RR) = 1.19, 95% confidence interval (CI), 1.09-1.30) and smoking modified the effect of age on TFs with a steeper age-related increase among ever smokers compared to non-smokers (p < 0.001). TFs did not differ by gender. Interpreting an independent effect of race was difficult owing to laboratory variation. Our study is three times larger than any pooled effort to date, confirming a suspected curvilinear relationship of TF with age. The significant effect of cigarette smoking has not been observed with previous pooled studies of TF in humans. Our data provide stable estimates of background TF by age, gender, race, and smoking status and suggest an acceleration of chromosome damage above age 60 and among those with a history of smoking cigarettes. © 2008 Elsevier B.V. All rights reserved

    Prediction of Breast Cancer Risk Based on Profiling With Common Genetic Variants

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    Background: Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is lacking. Methods: We investigated the value of using 77 breast cancer-associated single nucleotide polymorphisms (SNPs) for risk stratification, in a study of 33 673 breast cancer cases and 33 381 control women of European origin. We tested all possible pair-wise multiplicative interactions and constructed a 77-SNP polygenic risk score (PRS) for breast cancer overall and by estrogen receptor (ER) status. Absolute risks of breast cancer by PRS were derived from relative risk estimates and UK incidence and mortality rates. Results: There was no strong evidence for departure from a multiplicative model for any SNP pair. Women in the highest 1% of the PRS had a three-fold increased risk of developing breast cancer compared with women in the middle quintile (odds ratio [OR] = 3.36, 95% confidence interval [CI] = 2.95 to 3.83). The ORs for ER-positive and ER-negative disease were 3.73 (95% CI = 3.24 to 4.30) and 2.80 (95% CI = 2.26 to 3.46), respectively. Lifetime risk of breast cancer for women in the lowest and highest quintiles of the PRS were 5.2% and 16.6% for a woman without family history, and 8.6% and 24.4% for a woman with a first-degree family history of breast cancer. Conclusions: The PRS stratifies breast cancer risk in women both with and without a family history of breast cancer. The observed level of risk discrimination could inform targeted screening and prevention strategies. Further discrimination may be achievable through combining the PRS with lifestyle/environmental factors, although these were not considered in this report.Peer reviewe
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