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Sökning: WFRF:(Ulmer HU)

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1.
  • Stevens, Kristen N, et al. (författare)
  • 19p13.1 is a triple negative-specific breast cancer susceptibility locus
  • 2012
  • Ingår i: Cancer Research. - 0008-5472 .- 1538-7445. ; 72, s. 1795
  • Tidskriftsartikel (refereegranskat)abstract
    • The 19p13.1 breast cancer susceptibility locus is a modifier of breast cancer risk in BRCA1 mutation carriers and is also associated with risk of ovarian cancer. Here we investigated 19p13.1 variation and risk of breast cancer subtypes, defined by estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2) status, using 48,869 breast cancer cases and 49,787 controls from the Breast Cancer Association Consortium (BCAC). Variants from 19p13.1 were not associated with breast cancer overall or with ER-positive breast cancer but were significantly associated with ER-negative breast cancer risk [rs8170 Odds Ratio (OR)=1.10, 95% Confidence Interval (CI) 1.05 - 1.15, p=3.49 x 10-5] and triple negative (TN) (ER, PR and HER2 negative) breast cancer [rs8170 OR=1.22, 95% CI 1.13 - 1.31, p=2.22 x 10-7]. However, rs8170 was no longer associated with ER-negative breast cancer risk when TN cases were excluded [OR=0.98, 95% CI 0.89 - 1.07, p=0.62]. In addition, a combined analysis of TN cases from BCAC and the Triple Negative Breast Cancer Consortium (TNBCC) (n=3,566) identified a genome-wide significant association between rs8170 and TN breast cancer risk [OR=1.25, 95% CI 1.18 - 1.33, p=3.31 x 10-13]. Thus, 19p13.1 is the first triple negative-specific breast cancer risk locus and the first locus specific to a histological subtype defined by ER, PR, and HER2 to be identified. These findings provide convincing evidence that genetic susceptibility to breast cancer varies by tumor subtype and that triple negative tumors and other subtypes likely arise through distinct etiologic pathways.
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  • Kar, Siddhartha P, et al. (författare)
  • Genome-Wide Meta-Analyses of Breast, Ovarian, and Prostate Cancer Association Studies Identify Multiple New Susceptibility Loci Shared by at Least Two Cancer Types
  • 2016
  • Ingår i: Cancer discovery. - 2159-8290. ; 6:9, s. 1052-1067
  • Tidskriftsartikel (refereegranskat)abstract
    • UNLABELLED: Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P < 10(-8) seven new cross-cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type-specific expression quantitative trait locus and enhancer-gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P < 10(-5) in the three-cancer meta-analysis.SIGNIFICANCE: We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052-67. ©2016 AACR.This article is highlighted in the In This Issue feature, p. 932.
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  • Mavaddat, Nasim, et al. (författare)
  • Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes
  • 2019
  • Ingår i: American journal of human genetics. - 1537-6605. ; 104:1, s. 21-34
  • Tidskriftsartikel (refereegranskat)abstract
    • Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57–1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628–0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs. © 2018 The Authors
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