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Sökning: WFRF:(West Catharine)

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1.
  • Hedman, Mattias, et al. (författare)
  • Comparison of predicted and clinical response to radiotherapy: a radiobiology modelling study.
  • 2009
  • Ingår i: Acta oncologica (Stockholm, Sweden). - 1651-226X. ; 48:4, s. 584-90
  • Tidskriftsartikel (refereegranskat)abstract
    • INTRODUCTION: A model to predict clinical outcome after radiation therapy would be a valuable aid in the effort of developing more tailored treatment regimes for different patients. In this work we evaluate the clinical utility of a model that incorporates the following individually measured radiobiology parameters: intrinsic radiosensitivity, proliferation and number of clonogenic cells. The hypothesis underlying the study was that the incorporation of individually measured tumour parameters in a model would increase its reliability in predicting treatment outcome compared with the use of average population derived data. MATERIAL AND METHODS: Forty-six patients with head and neck tumours were analyzed, the majority of whom received both external beam radiotherapy and brachytherapy. Eighteen patients received external beam treatment alone and statistical analyses were carried out on this subgroup. RESULTS: Four of the 18 patients had a >95% calculated probability of cure and none developed a local recurrence resulting in a negative predictive value of 100% (compared with 67% for population-derived data). The sensitivity of the model in predicting local recurrence was 75% (compared with 38% for population-derived data). Using a model that incorporated individually measured radiobiology data, there was a statistically significant difference in local control levels for patients with >95% and <5% predicted probability of local control (chi(2), p = 0.04). DISCUSSION: This study suggests, therefore, that incorporation of measured biological data within a radiobiological model improves its ability to predict radiation therapy outcome compared with the use of population-derived data.
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2.
  • 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
    • <p><strong>BACKGROUND:</strong> 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).</p><p><strong>MATERIALS AND METHODS:</strong> 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.</p><p><strong>RESULTS:</strong> Thirty-five metabolites were strongly associated with prostate cancer (p &lt;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.</p><p><strong>CONCLUSIONS:</strong> 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.</p><p><strong>IMPACT:</strong> The metabolome provides a promising set of biomarkers that may aid prostate cancer classification.</p>
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3.
  • 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
    • <p>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.</p>
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4.
  • Hall, Janet, et al. (författare)
  • Ionizing radiation biomarkers in epidemiological studies - An update
  • 2017
  • Ingår i: Mutation Research. - 1383-5742 .- 1388-2139. ; 771, s. 59-84
  • Forskningsöversikt (refereegranskat)abstract
    • <p>Recent epidemiology studies highlighted the detrimental health effects of exposure to low dose and low dose rate ionizing radiation (IR): nuclear industry workers studies have shown increased leukaemia and solid tumour risks following cumulative doses of &lt; 100 mSv and dose rates of &lt; 10 mGy per year; paediatric patients studies have reported increased leukaemia and brain tumours risks after doses of 30-60 mGy from computed tomography scans. Questions arise, however, about the impact of even lower doses and dose rates where classical epidemiological studies have limited power but where subsets within the large cohorts are expected to have an increased risk. Further progress requires integration of biomarkers or bioassays of individual exposure, effects and susceptibility to IR. The European DoReMi (Low Dose Research towards Multidisciplinary Integration) consortium previously reviewed biomarkers for potential use in IR epidemiological studies. Given the increased mechanistic understanding of responses to low dose radiation the current review provides an update covering technical advances and recent studies. A key issue identified is deciding which biomarkers to progress. A roadmap is provided for biomarker development from discovery to implementation and used to summarise the current status of proposed biomarkers for epidemiological studies. Most potential biomarkers remain at the discovery stage and for some there is sufficient evidence that further development is not warranted. One biomarker identified in the final stages of development and as a priority for further research is radiation specific mRNA transcript profiles.</p>
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5.
  • Hedman, Mattias, et al. (författare)
  • Comparison of predicted and clinical response to radiotherapy : A radiobiology modelling study
  • 2009
  • Ingår i: Acta Oncologica. - 0284-186X .- 1651-226X. ; 48:4, s. 584-590
  • Tidskriftsartikel (refereegranskat)abstract
    • <p>Introduction. A model to predict clinical outcome after radiation therapy would be a valuable aid in the effort of developing more tailored treatment regimes for different patients. In this work we evaluate the clinical utility of a model that incorporates the following individually measured radiobiology parameters: intrinsic radiosensitivity, proliferation and number of clonogenic cells. The hypothesis underlying the study was that the incorporation of individually measured tumour parameters in a model would increase its reliability in predicting treatment outcome compared with the use of average population derived data. Material and methods. Forty-six patients with head and neck tumours were analyzed, the majority of whom received both external beam radiotherapy and brachytherapy. Eighteen patients received external beam treatment alone and statistical analyses were carried out on this subgroup. Results. Four of the 18 patients had a 95% calculated probability of cure and none developed a local recurrence resulting in a negative predictive value of 100% (compared with 67% for population-derived data). The sensitivity of the model in predicting local recurrence was 75% (compared with 38% for population-derived data). Using a model that incorporated individually measured radiobiology data, there was a statistically significant difference in local control levels for patients with 95% and 5% predicted probability of local control (2, p = 0.04). Discussion. This study suggests, therefore, that incorporation of measured biological data within a radiobiological model improves its ability to predict radiation therapy outcome compared with the use of population-derived data.</p>
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6.
  • Jiang, Xia, et al. (författare)
  • Shared heritability and functional enrichment across six solid cancers
  • 2019
  • Ingår i: Nature Communications. - Nature Publishing Group. - 2041-1723 .- 2041-1723. ; 10
  • Tidskriftsartikel (refereegranskat)abstract
    • <p>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 (<em>r</em><em>g</em> = 0.57, <em>p</em> = 4.6 × 10−8), breast and ovarian cancer (<em>r</em><em>g</em> = 0.24, <em>p</em> = 7 × 10−5), breast and lung cancer (<em>r</em><em>g</em> = 0.18, <em>p </em>=1.5 × 10−6) and breast and colorectal cancer (<em>r</em><em>g</em> = 0.15, <em>p</em> = 1.1 × 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.</p>
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7.
  • Jiang, Xia, et al. (författare)
  • Shared heritability and functional enrichment across six solid cancers
  • 2019
  • Ingår i: Nature Communications. - 2041-1723 .- 2041-1723. ; 10
  • Tidskriftsartikel (refereegranskat)abstract
    • <p>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.</p>
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8.
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9.
  • Matejcic, Marco, et al. (författare)
  • Germline variation at 8q24 and prostate cancer risk in men of European ancestry
  • 2018
  • Ingår i: Nature Communications. - 2041-1723 .- 2041-1723. ; 9
  • Tidskriftsartikel (refereegranskat)abstract
    • <p>Chromosome 8q24 is a susceptibility locus for multiple cancers, including prostate cancer. Here we combine genetic data across the 8q24 susceptibility region from 71,535 prostate cancer cases and 52,935 controls of European ancestry to define the overall contribution of germline variation at 8q24 to prostate cancer risk. We identify 12 independent risk signals for prostate cancer (p &lt; 4.28 x 10(-15)), including three risk variants that have yet to be reported. From a polygenic risk score (PRS) model, derived to assess the cumulative effect of risk variants at 8q24, men in the top 1% of the PRS have a 4-fold (95% CI = 3.62-4.40) greater risk compared to the population average. These 12 variants account for similar to 25% of what can be currently explained of the familial risk of prostate cancer by known genetic risk factors. These findings highlight the overwhelming contribution of germline variation at 8q24 on prostate cancer risk which has implications for population risk stratification.</p>
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10.
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