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2.
  • Michailidou, Kyriaki, et al. (författare)
  • Association analysis identifies 65 new breast cancer risk loci.
  • 2017
  • Ingår i: Nature. - : Nature Publishing Group. - 0028-0836 .- 1476-4687. ; 551:7678, s. 92-94
  • Tidskriftsartikel (refereegranskat)abstract
    • Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P < 5 × 10-8. The majority of credible risk single-nucleotide polymorphisms in these loci fall in distal regulatory elements, and by integrating in silico data to predict target genes in breast cells at each locus, we demonstrate a strong overlap between candidate target genes and somatic driver genes in breast tumours. We also find that heritability of breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the use of genetic risk scores for individualized screening and prevention.
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3.
  • Michailidou, Kyriaki, et al. (författare)
  • Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer
  • 2015
  • Ingår i: Nature Genetics. - 1061-4036 .- 1546-1718. ; 47:4, s. 373-U127
  • Tidskriftsartikel (refereegranskat)abstract
    • Genome-wide association studies (GWAS) and large-scale replication studies have identified common variants in 79 loci associated with breast cancer, explaining similar to 14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS, comprising 15,748 breast cancer cases and 18,084 controls together with 46,785 cases and 42,892 controls from 41 studies genotyped on a 211,155-marker custom array (iCOGS). Analyses were restricted to women of European ancestry. We generated genotypes for more than 11 million SNPs by imputation using the 1000 Genomes Project reference panel, and we identified 15 new loci associated with breast cancer at P < 5 x 10(-8). Combining association analysis with ChIP-seq chromatin binding data in mammary cell lines and ChIA-PET chromatin interaction data from ENCODE, we identified likely target genes in two regions: SETBP1 at 18q12.3 and RNF115 and PDZK1 at 1q21.1. One association appears to be driven by an amino acid substitution encoded in EXO1.
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5.
  • 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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7.
  • 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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8.
  • Aad, G., et al. (författare)
  • A measurement of the ratio of the production cross sections for W and Z bosons in association with jets with the ATLAS detector
  • 2014
  • Ingår i: European Physical Journal C. Particles and Fields. - : Springer. - 1434-6044 .- 1434-6052. ; 74:12
  • Tidskriftsartikel (refereegranskat)abstract
    • The ratio of the production cross sections for W and Z bosons in association with jets has been measured in proton-proton collisions at root s = 7 TeV with the ATLAS experiment at the Large Hadron Collider. The measurement is based on the entire 2011 dataset, corresponding to an integrated luminosity of 4.6 fb(-1). Inclusive and differential cross-section ratios for massive vector bosons decaying to electrons and muons are measured in association with jets with transverse momentum p(T) > 30 GeV and jet rapidity vertical bar y vertical bar < 4.4. The measurements are compared to next-to-leading-order perturbative QCD calculations and to predictions from different Monte Carlo generators implementing leading-order matrix elements supplemented by parton showers.
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9.
  • Aad, G., et al. (författare)
  • A neural network clustering algorithm for the ATLAS silicon pixel detector
  • 2014
  • Ingår i: Journal of Instrumentation. - : IOP Publishing. - 1748-0221. ; 9
  • Tidskriftsartikel (refereegranskat)abstract
    • A novel technique to identify and split clusters created by multiple charged particles in the ATLAS pixel detector using a set of artificial neural networks is presented. Such merged clusters are a common feature of tracks originating from highly energetic objects, such as jets. Neural networks are trained using Monte Carlo samples produced with a detailed detector simulation. This technique replaces the former clustering approach based on a connected component analysis and charge interpolation. The performance of the neural network splitting technique is quantified using data from proton-proton collisions at the LHC collected by the ATLAS detector in 2011 and from Monte Carlo simulations. This technique reduces the number of clusters shared between tracks in highly energetic jets by up to a factor of three. It also provides more precise position and error estimates of the clusters in both the transverse and longitudinal impact parameter resolution.
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10.
  • Aad, G., et al. (författare)
  • A search for flavour changing neutral currents in top-quark decays in pp collision data collected with the ATLAS detector at root s=7 TeV
  • 2012
  • Ingår i: Journal of High Energy Physics. - : Springer. - 1029-8479 .- 1126-6708. ; :9
  • Tidskriftsartikel (refereegranskat)abstract
    • A search for flavour changing neutral current (FCNC) processes in top-quark decays by the ATLAS Collaboration is presented. Data collected from pp collisions at the LHC at a centre-of-mass energy of root s = 7 TeV during 2011, corresponding to an integrated luminosity of 2.1 fb(-1), were used. A search was performed for top-quark pair-production events, with one top quark decaying through the t -> Zq FCNC (q = u, c) channel, and the other through the Standard Model dominant mode t -> Wb. Only the decays of the Z boson to charged leptons and leptonic W-boson decays were considered as signal. Consequently, the final-state topology is characterised by the presence of three isolated charged leptons, at least two jets and missing transverse momentum from the undetected neutrino. No evidence for an FCNC signal was found. An upper limit on the t -> Zq branching ratio of BR(t -> Zq) < 0.73% is set at the 95% confidence level.
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