| 1. |
- Aad, G., et al.
(author)
-
- 2011
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swepub:Mat__t (peer-reviewed)
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| 2. |
- Aad, G., et al.
(author)
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- 2012
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Journal article (peer-reviewed)
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| 3. |
- Aad, G., et al.
(author)
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- 2011
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swepub:Mat__t (peer-reviewed)
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| 4. |
- Aad, G., et al.
(author)
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- 2011
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swepub:Mat__t (peer-reviewed)
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| 5. |
- Aad, G., et al.
(author)
-
- 2011
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swepub:Mat__t (peer-reviewed)
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| 6. |
- Aad, G., et al.
(author)
-
- 2011
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swepub:Mat__t (peer-reviewed)
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| 7. |
- Aad, G., et al.
(author)
-
- 2011
-
swepub:Mat__t (peer-reviewed)
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| 8. |
- Aad, G., et al.
(author)
-
- 2010
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swepub:Mat__t (peer-reviewed)
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| 9. |
- Aad, G., et al.
(author)
-
- 2011
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swepub:Mat__t (peer-reviewed)
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| 10. |
- Aad, G., et al.
(author)
-
- 2011
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swepub:Mat__t (peer-reviewed)
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| 11. |
- Aad, G., et al.
(author)
-
- 2011
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swepub:Mat__t (peer-reviewed)
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| 12. |
- Aad, G., et al.
(author)
-
- 2011
-
swepub:Mat__t (peer-reviewed)
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| 13. |
- Aad, G., et al.
(author)
-
- 2011
-
swepub:Mat__t (peer-reviewed)
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| 14. |
- Aad, G., et al.
(author)
-
- 2011
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swepub:Mat__t (peer-reviewed)
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| 15. |
- Aad, G., et al.
(author)
-
- 2011
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swepub:Mat__t (peer-reviewed)
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| 16. |
- Aad, G., et al.
(author)
-
- 2011
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swepub:Mat__t (peer-reviewed)
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| 17. |
- Aad, G., et al.
(author)
-
- 2011
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swepub:Mat__t (peer-reviewed)
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| 18. |
- Aad, G., et al.
(author)
-
- 2011
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swepub:Mat__t (peer-reviewed)
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| 19. |
- Aad, G., et al.
(author)
-
- 2011
-
swepub:Mat__t (peer-reviewed)
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| 20. |
- Aad, G., et al.
(author)
-
- 2011
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swepub:Mat__t (peer-reviewed)
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| 21. |
- Aad, G., et al.
(author)
-
- 2011
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swepub:Mat__t (peer-reviewed)
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| 22. |
- Aad, G., et al.
(author)
-
- 2011
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swepub:Mat__t (peer-reviewed)
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| 23. |
- Aad, G., et al.
(author)
-
- 2011
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swepub:Mat__t (peer-reviewed)
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| 24. |
- Aad, G., et al.
(author)
-
- 2011
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swepub:Mat__t (peer-reviewed)
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| 25. |
- Aad, G., et al.
(author)
-
- 2011
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swepub:Mat__t (peer-reviewed)
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| 26. |
- Aad, G., et al.
(author)
-
- 2011
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swepub:Mat__t (peer-reviewed)
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| 27. |
- Aad, G., et al.
(author)
-
- 2011
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swepub:Mat__t (peer-reviewed)
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| 28. |
- Aad, G., et al.
(author)
-
- 2011
-
swepub:Mat__t (peer-reviewed)
|
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| 29. |
- Aad, G., et al.
(author)
-
- 2011
-
swepub:Mat__t
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| 30. |
|
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| 31. |
- Aad, G., et al.
(author)
-
- 2010
-
swepub:Mat__t
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| 32. |
- Aad, G., et al.
(author)
-
- 2010
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swepub:Mat__t
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| 33. |
- Jiang, X., et al.
(author)
-
Shared heritability and functional enrichment across six solid cancers
- 2019
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In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10
-
Journal article (peer-reviewed)abstract
- Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (r(g) = 0.57, p = 4.6 x 10(-8)), breast and ovarian cancer (r(g) = 0.24, p = 7 x 10(-5)), breast and lung cancer (r(g) = 0.18, p = 1.5 x 10(-6)) and breast and colorectal cancer (r(g) = 0.15, p = 1.1 x 10(-4)). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.
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| 34. |
- Abate, E., et al.
(author)
-
Combined performance tests before installation of the ATLAS Semiconductor and Transition Radiation Tracking Detectors
- 2008
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In: Journal of Instrumentation. - 1748-0221. ; 3
-
Journal article (peer-reviewed)abstract
- The ATLAS (A Toroidal LHC ApparatuS) Inner Detector provides charged particle tracking in the centre of the ATLAS experiment at the Large Hadron Collider (LHC). The Inner Detector consists of three subdetectors: the Pixel Detector, the Semiconductor Tracker (SCT), and the Transition Radiation Tracker (TRT). This paper summarizes the tests that were carried out at the final stage of SCT+TRT integration prior to their installation in ATLAS. The combined operation and performance of the SCT and TRT barrel and endcap detectors was investigated through a series of noise tests, and by recording the tracks of cosmic rays. This was a crucial test of hardware and software of the combined tracker detector systems. The results of noise and cross-talk tests on the SCT and TRT in their final assembled configuration, using final readout and supply hardware and software, are reported. The reconstruction and analysis of the recorded cosmic tracks allowed testing of the offline analysis chain and verification of basic tracker performance parameters, such as efficiency and spatial resolution, in combined operation before installation.
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| 35. |
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| 36. |
- Abdesselam, A., et al.
(author)
-
Engineering for the ATLAS SemiConductor Tracker (SCT) end-cap
- 2008
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In: Journal of Instrumentation. - 1748-0221. ; 3
-
Journal article (peer-reviewed)abstract
- The ATLAS SemiConductor Tracker (SCT) is a silicon-strip tracking detector which forms part of the ATLAS inner detector. The SCT is designed to track charged particles produced in proton-proton collisions at the Large Hadron Collider (LHC) at CERN at an energy of 14 TeV. The tracker is made up of a central barrel and two identical end-caps. The barrel contains 2112 silicon modules, while each end-cap contains 988 modules. The overall tracking performance depends not only on the intrinsic measurement precision of the modules but also on the characteristics of the whole assembly, in particular, the stability and the total material budget. This paper describes the engineering design and construction of the SCT end-caps, which are required to support mechanically the silicon modules, supply services to them and provide a suitable environment within the inner detector. Critical engineering choices are highlighted and innovative solutions are presented - these will be of interest to other builders of large-scale tracking detectors. The SCT end-caps will be fully connected at the start of 2008. Further commissioning will continue, to be ready for proton-proton collision data in 2008.
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| 37. |
- Figlioli, G, et al.
(author)
-
The FANCM:p.Arg658* truncating variant is associated with risk of triple-negative breast cancer
- 2019
-
In: NPJ breast cancer. - : Springer Science and Business Media LLC. - 2374-4677. ; 5, s. 38-
-
Journal article (peer-reviewed)abstract
- Breast cancer is a common disease partially caused by genetic risk factors. Germline pathogenic variants in DNA repair genes BRCA1, BRCA2, PALB2, ATM, and CHEK2 are associated with breast cancer risk. FANCM, which encodes for a DNA translocase, has been proposed as a breast cancer predisposition gene, with greater effects for the ER-negative and triple-negative breast cancer (TNBC) subtypes. We tested the three recurrent protein-truncating variants FANCM:p.Arg658*, p.Gln1701*, and p.Arg1931* for association with breast cancer risk in 67,112 cases, 53,766 controls, and 26,662 carriers of pathogenic variants of BRCA1 or BRCA2. These three variants were also studied functionally by measuring survival and chromosome fragility in FANCM−/− patient-derived immortalized fibroblasts treated with diepoxybutane or olaparib. We observed that FANCM:p.Arg658* was associated with increased risk of ER-negative disease and TNBC (OR = 2.44, P = 0.034 and OR = 3.79; P = 0.009, respectively). In a country-restricted analysis, we confirmed the associations detected for FANCM:p.Arg658* and found that also FANCM:p.Arg1931* was associated with ER-negative breast cancer risk (OR = 1.96; P = 0.006). The functional results indicated that all three variants were deleterious affecting cell survival and chromosome stability with FANCM:p.Arg658* causing more severe phenotypes. In conclusion, we confirmed that the two rare FANCM deleterious variants p.Arg658* and p.Arg1931* are risk factors for ER-negative and TNBC subtypes. Overall our data suggest that the effect of truncating variants on breast cancer risk may depend on their position in the gene. Cell sensitivity to olaparib exposure, identifies a possible therapeutic option to treat FANCM-associated tumors.
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| 38. |
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| 39. |
- Dareng, EO, et al.
(author)
-
Polygenic risk modeling for prediction of epithelial ovarian cancer risk
- 2022
-
In: European journal of human genetics : EJHG. - : Springer Science and Business Media LLC. - 1476-5438 .- 1018-4813. ; 30:3, s. 349-362
-
Journal article (peer-reviewed)abstract
- Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, “select and shrink for summary statistics” (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28–1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08–1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21–1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29–1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35–1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.
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| 40. |
- Lawrenson, Kate, et al.
(author)
-
Functional mechanisms underlying pleiotropic risk alleles at the 19p13.1 breast-ovarian cancer susceptibility locus
- 2016
-
In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 7
-
Journal article (peer-reviewed)abstract
- A locus at 19p13 is associated with breast cancer (BC) and ovarian cancer (OC) risk. Here we analyse 438 SNPs in this region in 46,451 BC and 15,438 OC cases, 15,252 BRCA1 mutation carriers and 73,444 controls and identify 13 candidate causal SNPs associated with serous OC (P=9.2 × 10-20), ER-negative BC (P=1.1 × 10-13), BRCA1-associated BC (P=7.7 × 10-16) and triple negative BC (P-diff=2 × 10-5). Genotype-gene expression associations are identified for candidate target genes ANKLE1 (P=2 × 10-3) and ABHD8 (P<2 × 10-3). Chromosome conformation capture identifies interactions between four candidate SNPs and ABHD8, and luciferase assays indicate six risk alleles increased transactivation of the ADHD8 promoter. Targeted deletion of a region containing risk SNP rs56069439 in a putative enhancer induces ANKLE1 downregulation; and mRNA stability assays indicate functional effects for an ANKLE1 3′-UTR SNP. Altogether, these data suggest that multiple SNPs at 19p13 regulate ABHD8 and perhaps ANKLE1 expression, and indicate common mechanisms underlying breast and ovarian cancer risk.
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| 41. |
- Abdesselam, A., et al.
(author)
-
The ATLAS semiconductor tracker end-cap module
- 2007
-
In: Nuclear Instruments and Methods in Physics Research Section A. - : Elsevier BV. - 0168-9002 .- 1872-9576. ; 575:3, s. 353-389
-
Journal article (peer-reviewed)abstract
- The challenges for the tracking detector systems at the LHC are unprecedented in terms of the number of channels, the required read-out speed and the expected radiation levels. The ATLAS Semiconductor Tracker. (SCT) end-caps have a total of about 3 million electronics channels each reading out every 25 ns into its own on-chip 3.3 mu s buffer. The highest anticipated dose after 10 years operation is 1.4x10(14) cm(-2) in units of 1 MeV neutron equivalent (assuming the damage factors scale with the non-ionising energy loss). The forward tracker has 1976 double-sided modules, mostly of area similar to 70 cm(2), each having 2 x 768 strips read out by six ASICs per side. The requirement to achieve an average perpendicular radiation length of 1.5% X-0, while coping with up to 7 W dissipation per module (after irradiation), leads to stringent constraints on the thermal design. The additional requirement of 1500e(-) equivalent noise charge (ENC) rising to only 1800e(-) ENC after irradiation, provides stringent design constraints on both the high-density Cu/Polyimide flex read-out circuit and the ABCD3TA read-out ASICs. Finally, the accuracy of module assembly must not compromise the 16 mu m (r phi) resolution perpendicular to the strip directions or 580 mu m radial resolution coming from the 40 mrad front-back stereo angle. A total of 2210 modules were built to the tight tolerances and specifications required for the SCT. This was 234 more than the 1976 required and represents a yield of 93%. The component flow was at times tight, but the module production rate of 40-50 per week was maintained despite this. The distributed production was not found to be a major logistical problem and it allowed additional flexibility to take advantage of where the effort was available, including any spare capacity, for building the end-cap modules. The collaboration that produced the ATLAS SCT end-cap modules kept in close contact at all times so that the effects of shortages or stoppages at different sites could be rapidly resolved.
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| 42. |
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| 43. |
- Ferreira, MA, et al.
(author)
-
Genome-wide association and transcriptome studies identify target genes and risk loci for breast cancer
- 2019
-
In: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10:1, s. 1741-
-
Journal article (peer-reviewed)abstract
- Genome-wide association studies (GWAS) have identified more than 170 breast cancer susceptibility loci. Here we hypothesize that some risk-associated variants might act in non-breast tissues, specifically adipose tissue and immune cells from blood and spleen. Using expression quantitative trait loci (eQTL) reported in these tissues, we identify 26 previously unreported, likely target genes of overall breast cancer risk variants, and 17 for estrogen receptor (ER)-negative breast cancer, several with a known immune function. We determine the directional effect of gene expression on disease risk measured based on single and multiple eQTL. In addition, using a gene-based test of association that considers eQTL from multiple tissues, we identify seven (and four) regions with variants associated with overall (and ER-negative) breast cancer risk, which were not reported in previous GWAS. Further investigation of the function of the implicated genes in breast and immune cells may provide insights into the etiology of breast cancer.
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| 44. |
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| 45. |
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| 46. |
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| 47. |
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| 48. |
- Kang, E. Y., et al.
(author)
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CCNE1 and survival of patients with tubo-ovarian high-grade serous carcinoma: An Ovarian Tumor Tissue Analysis consortium study
- 2023
-
In: Cancer. - : Wiley. - 0008-543X .- 1097-0142. ; 129:5, s. 697-713
-
Journal article (peer-reviewed)abstract
- Background: Cyclin E1 (CCNE1) is a potential predictive marker and therapeutic target in tubo-ovarian high-grade serous carcinoma (HGSC). Smaller studies have revealed unfavorable associations for CCNE1 amplification and CCNE1 overexpression with survival, but to date no large-scale, histotype-specific validation has been performed. The hypothesis was that high-level amplification of CCNE1 and CCNE1 overexpression, as well as a combination of the two, are linked to shorter overall survival in HGSC. Methods: Within the Ovarian Tumor Tissue Analysis consortium, amplification status and protein level in 3029 HGSC cases and mRNA expression in 2419 samples were investigated. Results: High-level amplification (>8 copies by chromogenic in situ hybridization) was found in 8.6% of HGSC and overexpression (>60% with at least 5% demonstrating strong intensity by immunohistochemistry) was found in 22.4%. CCNE1 high-level amplification and overexpression both were linked to shorter overall survival in multivariate survival analysis adjusted for age and stage, with hazard stratification by study (hazard ratio [HR], 1.26; 95% CI, 1.08-1.47, p = .034, and HR, 1.18; 95% CI, 1.05-1.32, p = .015, respectively). This was also true for cases with combined high-level amplification/overexpression (HR, 1.26; 95% CI, 1.09-1.47, p = .033). CCNE1 mRNA expression was not associated with overall survival (HR, 1.00 per 1-SD increase; 95% CI, 0.94-1.06; p = .58). CCNE1 high-level amplification is mutually exclusive with the presence of germline BRCA1/2 pathogenic variants and shows an inverse association to RB1 loss. Conclusion: This study provides large-scale validation that CCNE1 high-level amplification is associated with shorter survival, supporting its utility as a prognostic biomarker in HGSC.
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| 49. |
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| 50. |
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