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Träfflista för sökning "WFRF:(Muir Kenneth) srt2:(2015-2019)"

Sökning: WFRF:(Muir Kenneth) > (2015-2019)

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1.
  • Tidskriftsartikel (refereegranskat)
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2.
  • Dörk, Thilo, et al. (författare)
  • Two truncating variants in FANCC and breast cancer risk
  • 2019
  • Ingår i: Scientific Reports. - : Nature Publishing Group. - 2045-2322 .- 2045-2322. ; 9
  • Tidskriftsartikel (refereegranskat)abstract
    • Fanconi anemia (FA) is a genetically heterogeneous disorder with 22 disease-causing genes reported to date. In some FA genes, monoallelic mutations have been found to be associated with breast cancer risk, while the risk associations of others remain unknown. The gene for FA type C, FANCC, has been proposed as a breast cancer susceptibility gene based on epidemiological and sequencing studies. We used the Oncoarray project to genotype two truncating FANCC variants (p.R185X and p.R548X) in 64,760 breast cancer cases and 49,793 controls of European descent. FANCC mutations were observed in 25 cases (14 with p.R185X, 11 with p.R548X) and 26 controls (18 with p.R185X, 8 with p.R548X). There was no evidence of an association with the risk of breast cancer, neither overall (odds ratio 0.77, 95% CI 0.44-1.33, p = 0.4) nor by histology, hormone receptor status, age or family history. We conclude that the breast cancer risk association of these two FANCC variants, if any, is much smaller than for BRCA1, BRCA2 or PALB2 mutations. If this applies to all truncating variants in FANCC it would suggest there are differences between FA genes in their roles on breast cancer risk and demonstrates the merit of large consortia for clarifying risk associations of rare variants.
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3.
  • 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. - : AMER ASSOC CANCER RESEARCH. - 2159-8274 .- 2159-8290. ; 6:9, s. 1052-1067
  • Tidskriftsartikel (refereegranskat)abstract
    • 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. (C) 2016 AACR.
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5.
  • Zeng, Chenjie, et al. (författare)
  • Identification of independent association signals and putative functional variants for breast cancer risk through fine-scale mapping of the 12p11 locus
  • 2016
  • Ingår i: Breast Cancer Research. - 1465-5411 .- 1465-542X. ; 18
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Multiple recent genome-wide association studies (GWAS) have identified a single nucleotide polymorphism (SNP), rs10771399, at 12p11 that is associated with breast cancer risk. Method: We performed a fine-scale mapping study of a 700 kb region including 441 genotyped and more than 1300 imputed genetic variants in 48,155 cases and 43,612 controls of European descent, 6269 cases and 6624 controls of East Asian descent and 1116 cases and 932 controls of African descent in the Breast Cancer Association Consortium (BCAC; http://bcac.ccge.medschl.cam.ac.uk/), and in 15,252 BRCA1 mutation carriers in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Stepwise regression analyses were performed to identify independent association signals. Data from the Encyclopedia of DNA Elements project (ENCODE) and the Cancer Genome Atlas (TCGA) were used for functional annotation. Results: Analysis of data from European descendants found evidence for four independent association signals at 12p11, represented by rs7297051 (odds ratio (OR) = 1.09, 95 % confidence interval (CI) = 1.06-1.12; P = 3 x 10(-9)), rs805510 (OR = 1.08, 95 % CI = 1.04-1.12, P = 2 x 10(-5)), and rs1871152 (OR = 1.04, 95 % CI = 1.02-1.06; P = 2 x 10(-4)) identified in the general populations, and rs113824616 (P = 7 x 10(-5)) identified in the meta-analysis of BCAC ER-negative cases and BRCA1 mutation carriers. SNPs rs7297051, rs805510 and rs113824616 were also associated with breast cancer risk at P < 0.05 in East Asians, but none of the associations were statistically significant in African descendants. Multiple candidate functional variants are located in putative enhancer sequences. Chromatin interaction data suggested that PTHLH was the likely target gene of these enhancers. Of the six variants with the strongest evidence of potential functionality, rs11049453 was statistically significantly associated with the expression of PTHLH and its nearby gene CCDC91 at P < 0.05. Conclusion: This study identified four independent association signals at 12p11 and revealed potentially functional variants, providing additional insights into the underlying biological mechanism(s) for the association observed between variants at 12p11 and breast cancer risk.
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6.
  • Adams, Charleen, et al. (författare)
  • Circulating Metabolic Biomarkers of Screen-Detected Prostate Cancer in the ProtecT Study.
  • 2018
  • Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - 1055-9965 .- 1538-7755.
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND: Whether associations between circulating metabolites and prostate cancer are causal is unknown. We report on the largest study of metabolites and prostate cancer (2,291 cases and 2,661 controls) and appraise causality for a subset of the prostate cancer-metabolite associations using two-sample Mendelian randomization (MR).MATERIALS AND METHODS: The case-control portion of the study was conducted in nine UK centres with men aged 50-69 years who underwent prostate-specific antigen (PSA) screening for prostate cancer within the Prostate testing for cancer and Treatment (ProtecT) trial. Two data sources were used to appraise causality: a genome-wide association study (GWAS) of metabolites in 24,925 participants and a GWAS of prostate cancer in 44,825 cases and 27,904 controls within the Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium.RESULTS: Thirty-five metabolites were strongly associated with prostate cancer (p <0.0014, multiple-testing threshold). These fell into four classes: i) lipids and lipoprotein subclass characteristics (total cholesterol and ratios, cholesterol esters and ratios, free cholesterol and ratios, phospholipids and ratios, and triglyceride ratios); ii) fatty acids and ratios; iii) amino acids; iv) and fluid balance. Fourteen top metabolites were proxied by genetic variables, but MR indicated these were not causal.CONCLUSIONS: We identified 35 circulating metabolites associated with prostate cancer presence, but found no evidence of causality for those 14 testable with MR. Thus, the 14 MR-tested metabolites are unlikely to be mechanistically important in prostate cancer risk.IMPACT: The metabolome provides a promising set of biomarkers that may aid prostate cancer classification.
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7.
  • Dadaev, Tokhir, et al. (författare)
  • Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants.
  • 2018
  • Ingår i: Nature Communications. - 2041-1723 .- 2041-1723. ; 9:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.
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9.
  • Gnanapragasam, V. J., et al. (författare)
  • Using prognosis to guide inclusion criteria, define standardised endpoints and stratify follow-up in active surveillance for prostate cancer
  • 2019
  • Ingår i: Bju International. - : WILEY. - 1464-4096 .- 1464-410X. ; 124:5, s. 758-767
  • Tidskriftsartikel (refereegranskat)abstract
    • Objectives: To test whether using disease prognosis can inform a rational approach to active surveillance (AS) for early prostate cancer. Patients and methods: We previously developed the Cambridge Prognostics Groups (CPG) classification, a five-tiered model that uses prostate-specific antigen (PSA), Grade Group and Stage to predict cancer survival outcomes. We applied the CPG model to a UK and a Swedish prostate cancer cohort to test differences in prostate cancer mortality (PCM) in men managed conservatively or by upfront treatment in CPG2 and 3 (which subdivides the intermediate-risk classification) vs CPG1 (low-risk). We then applied the CPG model to a contemporary UK AS cohort, which was optimally characterised at baseline for disease burden, to identify predictors of true prognostic progression. Results were re-tested in an external AS cohort from Spain. Results: In a UK cohort (n = 3659) the 10-year PCM was 2.3% in CPG1, 1.5%/3.5% in treated/untreated CPG2, and 1.9%/8.6% in treated/untreated CPG3. In the Swedish cohort (n = 27 942) the10-year PCM was 1.0% in CPG1, 2.2%/2.7% in treated/untreated CPG2, and 6.1%/12.5% in treated/untreated CPG3. We then tested using progression to CPG3 as a hard endpoint in a modern AS cohort (n = 133). During follow-up (median 3.5 years) only 6% (eight of 133) progressed to CPG3. Predictors of progression were a PSA density ≥0.15 ng/mL/mL and CPG2 at diagnosis. Progression occurred in 1%, 8% and 21% of men with neither factor, only one, or both, respectively. In an independent Spanish AS cohort (n = 143) the corresponding rates were 3%, 10% and 14%, respectively. Conclusion: Using disease prognosis allows a rational approach to inclusion criteria, discontinuation triggers and risk-stratified management in AS. © 2019 The Authors. BJU International © 2019 BJU International Published by John Wiley & Sons Ltd
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