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Sökning: WFRF:(Dörk Thilo)

  • Resultat 21-27 av 27
  • Föregående 12[3]
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21.
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22.
  • Purrington, Kristen S, et al. (författare)
  • Genetic variation in mitotic regulatory pathway genes is associated with breast tumor grade.
  • 2014
  • Ingår i: Human Molecular Genetics. - : Oxford University Press. - 0964-6906 .- 1460-2083. ; 23:22, s. 6034-6046
  • Tidskriftsartikel (refereegranskat)abstract
    • Mitotic index is an important component of histologic grade and has an etiologic role in breast tumorigenesis. Several small candidate gene studies have reported associations between variation in mitotic genes and breast cancer risk. We measured associations between 2,156 single nucleotide polymorphisms (SNPs) from 194 mitotic genes and breast cancer risk, overall and by histologic grade, in the Breast Cancer Association Consortium (BCAC) iCOGS study (n=39,067 cases; n=42,106 controls). SNPs in TACC2 (rs17550038: odds ratio (OR)=1.24, 95% CI 1.16-1.33, p=4.2x10(-10)) and EIF3H (rs799890: OR=1.07, 95% confidence interval (CI) 1.04-1.11, p=8.7x10(-6)) were significantly associated with risk of low grade breast cancer. The TACC2 signal was retained (rs17550038: OR=1.15, 95% CI 1.07-1.23, p=7.9x10(-5)) after adjustment for breast cancer risk SNPs in the nearby FGFR2 gene, suggesting that TACC2 is a novel, independent genome-wide significant genetic risk locus for low grade breast cancer. While no SNPs were individually associated with high-grade disease, a pathway-level gene set analysis showed that variation across the 194 mitotic genes was associated with high grade breast cancer risk (p=2.1x10(-3)). These observations will provide insight into the contribution of mitotic defects to histological grade and the etiology of breast cancer.
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23.
  • Schmidt, Marjanka K, et al. (författare)
  • Do MDM2 SNP309 and TP53 R72P interact in breast cancer susceptibility? A large pooled series from the breast cancer association consortium
  • 2007
  • Ingår i: Cancer Research. - 0008-5472 .- 1538-7445. ; 67:19, s. 9584-9590
  • Tidskriftsartikel (refereegranskat)abstract
    • Association studies in large series of breast cancer patients can be used to identify single-nucleotide polymorphisms (SNP) contributing to breast cancer susceptibility. Previous studies have suggested associations between variants in TP53 (R72P) and MDM2 (SNP309) and cancer risk. Data from molecular studies suggest a functional interaction between these genes. We therefore investigated the effect of TP53 R72P and MDM2 SNP309 on breast cancer risk and age at onset of breast cancer in a pooled series of 5,191 cases and 3,834 controls from the Breast Cancer Association Consortium (BCAC). Breast cancer risk was not found to be associated with the combined variant alleles [odds ratio (OR), 1.00; 95% confidence interval (95% CI), 0.81–1.23]. Estimated ORs were 1.01 (95% CI, 0.93–1.09) per MDM2 SNP309 allele and 0.98 (95% CI, 0.91–1.04) for TP53 R72P. Although we did find evidence for a 4-year earlier age at onset for carriers of both variant alleles in one of the breast cancer patient series of the BCAC (the German series), we were not able to confirm this effect in the pooled analysis. Even so, carriers of both variant alleles did not have different risk estimates for bilateral or estrogen receptor–positive breast cancer. In conclusion, in this large collaborative study, we did not find an association of MDM2 SNP309 and TP53 R72P, separately or in interaction, with breast cancer. This suggests that any effect of these two variants would be very small and possibly confined to subgroups that were not assessed in our present study.
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24.
  • Shu, Xiang, et al. (författare)
  • Evaluation of associations between genetically predicted circulating protein biomarkers and breast cancer risk
  • Ingår i: International Journal of Cancer. - : John Wiley and Sons. - 0020-7136. ; 146:8, s. 2130-2138
  • Tidskriftsartikel (refereegranskat)abstract
    • A small number of circulating proteins have been reported to be associated with breast cancer risk, with inconsistent results. Herein, we attempted to identify novel protein biomarkers for breast cancer via the integration of genomics and proteomics data. In the Breast Cancer Association Consortium (BCAC), with 122,977 cases and 105,974 controls of European descendants, we evaluated the associations of the genetically predicted concentrations of >1,400 circulating proteins with breast cancer risk. We used data from a large-scale protein quantitative trait loci (pQTL) analysis as our study instrument. Summary statistics for these pQTL variants related to breast cancer risk were obtained from the BCAC and used to estimate odds ratios (OR) for each protein using the inverse-variance weighted method. We identified 56 proteins significantly associated with breast cancer risk by instrumental analysis (false discovery rate <0.05). Of these, the concentrations of 32 were influenced by variants close to a breast cancer susceptibility locus (ABO, 9q34.2). Many of these proteins, such as insulin receptor, insulin-like growth factor receptor 1 and other membrane receptors (OR: 0.82–1.18, p values: 6.96 × 10−4–3.28 × 10−8), are linked to insulin resistance and estrogen receptor signaling pathways. Proteins identified at other loci include those involved in biological processes such as alcohol and lipid metabolism, proteolysis, apoptosis, immune regulation and cell motility and proliferation. Consistent associations were observed for 22 proteins in the UK Biobank data (p < 0.05). The study identifies potential novel biomarkers for breast cancer, but further investigation is needed to replicate our findings.
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25.
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26.
  • Yang, Yaohua, et al. (författare)
  • Genetically Predicted Levels of DNA Methylation Biomarkers and Breast Cancer Risk : Data From 228 951 Women of European Descent
  • 2020
  • Ingår i: Journal of the National Cancer Institute. - : Oxford University Press. - 1460-2105. ; 112:3, s. 295-304
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND: DNA methylation plays a critical role in breast cancer development. Previous studies have identified DNA methylation marks in white blood cells as promising biomarkers for breast cancer. However, these studies were limited by low statistical power and potential biases. Using a new methodology, we investigated DNA methylation marks for their associations with breast cancer risk. METHODS: Statistical models were built to predict levels of DNA methylation marks using genetic data and DNA methylation data from HumanMethylation450 BeadChip from the Framingham Heart Study (n = 1595). The prediction models were validated using data from the Women's Health Initiative (n = 883). We applied these models to genomewide association study (GWAS) data of 122 977 breast cancer patients and 105 974 controls to evaluate if the genetically predicted DNA methylation levels at CpG sites (CpGs) are associated with breast cancer risk. All statistical tests were two-sided. RESULTS: Of the 62 938 CpG sites CpGs investigated, statistically significant associations with breast cancer risk were observed for 450 CpGs at a Bonferroni-corrected threshold of P less than 7.94 × 10-7, including 45 CpGs residing in 18 genomic regions, that have not previously been associated with breast cancer risk. Of the remaining 405 CpGs located within 500 kilobase flaking regions of 70 GWAS-identified breast cancer risk variants, the associations for 11 CpGs were independent of GWAS-identified variants. Integrative analyses of genetic, DNA methylation, and gene expression data found that 38 CpGs may affect breast cancer risk through regulating expression of 21 genes. CONCLUSION: Our new methodology can identify novel DNA methylation biomarkers for breast cancer risk and can be applied to other diseases.
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27.
  • Zhan, Haoyu, et al. (författare)
  • Genome-wide association study identifies 32 novel breast cancer susceptibility loci from overall and subtype-specific analyses
  • 2020
  • Ingår i: Nature Genetics. - : NATURE PUBLISHING GROUP. - 1061-4036 .- 1546-1718. ; 52:6, s. 572-
  • Tidskriftsartikel (refereegranskat)abstract
    • Genome-wide analysis identifies 32 loci associated with breast cancer susceptibility, accounting for estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade. Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype(1-3). To identify novel loci, we performed a genome-wide association study including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade. We identified 32 novel susceptibility loci (P < 5.0 x 10(-8)), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate < 0.05). Five loci showed associations (P < 0.05) in opposite directions between luminal and non-luminal subtypes. In silico analyses showed that these five loci contained cell-specific enhancers that differed between normal luminal and basal mammary cells. The genetic correlations between five intrinsic-like subtypes ranged from 0.35 to 0.80. The proportion of genome-wide chip heritability explained by all known susceptibility loci was 54.2% for luminal A-like disease and 37.6% for triple-negative disease. The odds ratios of polygenic risk scores, which included 330 variants, for the highest 1% of quantiles compared with middle quantiles were 5.63 and 3.02 for luminal A-like and triple-negative disease, respectively. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores.
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  • Föregående 12[3]
 
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