ORCID Profile
0000-0003-2627-2154
Current Organisation
University of Oxford
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Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 06-2006
Publisher: Springer Science and Business Media LLC
Date: 06-10-2022
Publisher: Springer Science and Business Media LLC
Date: 13-09-2018
DOI: 10.1038/S41467-018-04989-W
Abstract: Genome-wide association studies (GWAS) have transformed our understanding of susceptibility to multiple myeloma (MM), but much of the heritability remains unexplained. We report a new GWAS, a meta-analysis with previous GWAS and a replication series, totalling 9974 MM cases and 247,556 controls of European ancestry. Collectively, these data provide evidence for six new MM risk loci, bringing the total number to 23. Integration of information from gene expression, epigenetic profiling and in situ Hi-C data for the 23 risk loci implicate disruption of developmental transcriptional regulators as a basis of MM susceptibility, compatible with altered B-cell differentiation as a key mechanism. Dysregulation of autophagy/apoptosis and cell cycle signalling feature as recurrently perturbed pathways. Our findings provide further insight into the biological basis of MM.
Publisher: Springer Science and Business Media LLC
Date: 10-01-2019
DOI: 10.1038/S41467-018-08107-8
Abstract: The original version of this Article contained an error in the spelling of a member of the PRACTICAL Consortium, Manuela Gago-Dominguez, which was incorrectly given as Manuela Gago Dominguez. This has now been corrected in both the PDF and HTML versions of the Article. Furthermore, in the original HTML version of this Article, the order of authors within the author list was incorrect. The PRACTICAL consortium was incorrectly listed after Richard S. Houlston and should have been listed after Nora Pashayan. This error has been corrected in the HTML version of the Article the PDF version was correct at the time of publication.
Publisher: Elsevier BV
Date: 03-2019
Publisher: American Association for Cancer Research (AACR)
Date: 04-2015
DOI: 10.1158/2159-8290.CD-14-1057
Abstract: Prostate cancer is the second most common malignancy among men worldwide. Genome-wide association studies have identified 100 risk variants for prostate cancer, which can explain approximately 33% of the familial risk of the disease. We hypothesized that a comprehensive analysis of genetic variations found within the 3′ untranslated region of genes predicted to affect miRNA binding (miRSNP) can identify additional prostate cancer risk variants. We investigated the association between 2,169 miRSNPs and prostate cancer risk in a large-scale analysis of 22,301 cases and 22,320 controls of European ancestry from 23 participating studies. Twenty-two miRSNPs were associated (P & 2.3 × 10−5) with risk of prostate cancer, 10 of which were within 7 genes previously not mapped by GWAS studies. Further, using miRNA mimics and reporter gene assays, we showed that miR-3162-5p has specific affinity for the KLK3 rs1058205 miRSNP T-allele, whereas miR-370 has greater affinity for the VAMP8 rs1010 miRSNP A-allele, validating their functional role. Significance: Findings from this large association study suggest that a focus on miRSNPs, including functional evaluation, can identify candidate risk loci below currently accepted statistical levels of genome-wide significance. Studies of miRNAs and their interactions with SNPs could provide further insights into the mechanisms of prostate cancer risk. Cancer Discov 5(4) 368–79. ©2015 AACR. See related commentary by Yousef, p. 351 This article is highlighted in the In This Issue feature, p. 333
Publisher: Wiley
Date: 14-09-2010
Publisher: Springer Science and Business Media LLC
Date: 05-11-2018
DOI: 10.1038/S41467-018-06863-1
Abstract: 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 4.28 × 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 ~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.
Publisher: Elsevier BV
Date: 11-2021
Publisher: Springer Science and Business Media LLC
Date: 14-09-2014
DOI: 10.1038/NG.3094
Publisher: Public Library of Science (PLoS)
Date: 11-10-2016
Publisher: Springer Science and Business Media LLC
Date: 08-06-2020
Publisher: Wiley
Date: 23-06-2016
DOI: 10.1002/IJC.30206
Publisher: Oxford University Press (OUP)
Date: 07-2008
DOI: 10.1093/JNCI/DJN190
Publisher: Wiley
Date: 18-09-2012
Publisher: Springer Science and Business Media LLC
Date: 14-05-2019
DOI: 10.1038/S41467-019-09775-W
Abstract: Colorectal cancer (CRC) is a leading cause of cancer-related death worldwide, and has a strong heritable basis. We report a genome-wide association analysis of 34,627 CRC cases and 71,379 controls of European ancestry that identifies SNPs at 31 new CRC risk loci. We also identify eight independent risk SNPs at the new and previously reported European CRC loci, and a further nine CRC SNPs at loci previously only identified in Asian populations. We use in situ promoter capture Hi-C (CHi-C), gene expression, and in silico annotation methods to identify likely target genes of CRC SNPs. Whilst these new SNP associations implicate target genes that are enriched for known CRC pathways such as Wnt and BMP, they also highlight novel pathways with no prior links to colorectal tumourigenesis. These findings provide further insight into CRC susceptibility and enhance the prospects of applying genetic risk scores to personalised screening and prevention.
Publisher: Springer Science and Business Media LLC
Date: 10-10-2014
DOI: 10.1038/NCOMMS5809
Publisher: Springer Science and Business Media LLC
Date: 20-01-2021
Publisher: Wiley
Date: 04-04-2019
DOI: 10.1002/IJC.32276
Publisher: Springer Science and Business Media LLC
Date: 10-02-2008
DOI: 10.1038/NG.90
Abstract: Prostate cancer is the most common cancer affecting males in developed countries. It shows consistent evidence of familial aggregation, but the causes of this aggregation are mostly unknown. To identify common alleles associated with prostate cancer risk, we conducted a genome-wide association study (GWAS) using blood DNA s les from 1,854 in iduals with clinically detected prostate cancer diagnosed at </=60 years or with a family history of disease, and 1,894 population-screened controls with a low prostate-specific antigen (PSA) concentration (<0.5 ng/ml). We analyzed these s les for 541,129 SNPs using the Illumina Infinium platform. Initial putative associations were confirmed using a further 3,268 cases and 3,366 controls. We identified seven loci associated with prostate cancer on chromosomes 3, 6, 7, 10, 11, 19 and X (P = 2.7 x 10(-8) to P = 8.7 x 10(-29)). We confirmed previous reports of common loci associated with prostate cancer at 8q24 and 17q. Moreover, we found that three of the newly identified loci contain candidate susceptibility genes: MSMB, LMTK2 and KLK3.
Publisher: Springer Science and Business Media LLC
Date: 26-06-2014
DOI: 10.1038/NCOMMS5264
Publisher: Public Library of Science (PLoS)
Date: 23-11-2011
Publisher: Springer Science and Business Media LLC
Date: 05-04-2011
Publisher: Public Library of Science (PLoS)
Date: 13-02-2014
Publisher: Oxford University Press (OUP)
Date: 27-03-2013
DOI: 10.1093/HMG/DDT086
Publisher: American Association for Cancer Research (AACR)
Date: 07-2015
DOI: 10.1158/1055-9965.EPI-14-0317
Abstract: Background: Genome-wide association studies have identified multiple genetic variants associated with prostate cancer risk which explain a substantial proportion of familial relative risk. These variants can be used to stratify in iduals by their risk of prostate cancer. Methods: We genotyped 25 prostate cancer susceptibility loci in 40,414 in iduals and derived a polygenic risk score (PRS). We estimated empirical odds ratios (OR) for prostate cancer associated with different risk strata defined by PRS and derived age-specific absolute risks of developing prostate cancer by PRS stratum and family history. Results: The prostate cancer risk for men in the top 1% of the PRS distribution was 30.6 (95% CI, 16.4–57.3) fold compared with men in the bottom 1%, and 4.2 (95% CI, 3.2–5.5) fold compared with the median risk. The absolute risk of prostate cancer by age of 85 years was 65.8% for a man with family history in the top 1% of the PRS distribution, compared with 3.7% for a man in the bottom 1%. The PRS was only weakly correlated with serum PSA level (correlation = 0.09). Conclusions: Risk profiling can identify men at substantially increased or reduced risk of prostate cancer. The effect size, measured by OR per unit PRS, was higher in men at younger ages and in men with family history of prostate cancer. Incorporating additional newly identified loci into a PRS should improve the predictive value of risk profiles. Impact: We demonstrate that the risk profiling based on SNPs can identify men at substantially increased or reduced risk that could have useful implications for targeted prevention and screening programs. Cancer Epidemiol Biomarkers Prev 24(7) 1121–9. ©2015 AACR.
Publisher: Public Library of Science (PLoS)
Date: 02-10-2015
Publisher: American Association for Cancer Research (AACR)
Date: 2019
DOI: 10.1158/0008-5472.CAN-18-2318
Abstract: This international collaboration comprises the largest prospective study on blood vitamin D and prostate cancer risk and shows no association with aggressive disease but some evidence of a higher risk of nonaggressive disease.
Publisher: Springer Science and Business Media LLC
Date: 04-04-2016
Publisher: Springer Science and Business Media LLC
Date: 30-11-2020
DOI: 10.1038/S41467-020-20128-W
Abstract: Correction to this paper has been published: 0.1038/s41467-020-20128-w
Publisher: Elsevier BV
Date: 03-2020
Publisher: National Institute for Health and Care Research
Date: 09-2021
DOI: 10.3310/HTA25530
Abstract: The use of placebo comparisons for randomised trials assessing the efficacy of surgical interventions is increasingly being considered. However, a placebo control is a complex type of comparison group in the surgical setting and, although powerful, presents many challenges. To provide a summary of knowledge on placebo controls in surgical trials and to summarise any recommendations for designers, evaluators and funders of placebo-controlled surgical trials. To carry out a state-of-the-art workshop and produce a corresponding report involving key stakeholders throughout. A workshop to discuss and summarise the existing knowledge and to develop the new guidelines. To assess what a placebo control entails and to assess the understanding of this tool in the context of surgery is considered, along with when placebo controls in surgery are acceptable (and when they are desirable). We have considered ethics arguments and regulatory requirements, how a placebo control should be designed, how to identify and mitigate risk for participants in these trials, and how such trials should be carried out and interpreted. The use of placebo controls is justified in randomised controlled trials of surgical interventions provided that there is a strong scientific and ethics rationale. Surgical placebos might be most appropriate when there is poor evidence for the efficacy of the procedure and a justified concern that results of a trial would be associated with a high risk of bias, particularly because of the placebo effect. The use of placebo controls is justified in randomised controlled trials of surgical interventions provided that there is a strong scientific and ethics rationale. Feasibility work is recommended to optimise the design and implementation of randomised controlled trials. An outline for best practice was produced in the form of the Applying Surgical Placebo in Randomised Evaluations (ASPIRE) guidelines for those considering the use of a placebo control in a surgical randomised controlled trial. Although the workshop participants involved international members, the majority of participants were from the UK. Therefore, although every attempt was made to make the recommendations applicable to all health systems, the guidelines may, unconsciously, be particularly applicable to clinical practice in the UK NHS. Future work should evaluate the use of the ASPIRE guidelines in making decisions about the use of a placebo-controlled surgical trial. In addition, further work is required on the appropriate nomenclature to adopt in this space. Funded by the Medical Research Council UK and the National Institute for Health Research as part of the Medical Research Council–National Institute for Health Research Methodology Research programme.
Publisher: Springer Science and Business Media LLC
Date: 23-02-2021
DOI: 10.1038/S41467-021-21287-0
Abstract: Genetic models for cancer have been evaluated using almost exclusively European data, which could exacerbate health disparities. A polygenic hazard score (PHS 1 ) is associated with age at prostate cancer diagnosis and improves screening accuracy in Europeans. Here, we evaluate performance of PHS 2 (PHS 1 , adapted for OncoArray) in a multi-ethnic dataset of 80,491 men (49,916 cases, 30,575 controls). PHS 2 is associated with age at diagnosis of any and aggressive (Gleason score ≥ 7, stage T3-T4, PSA ≥ 10 ng/mL, or nodal/distant metastasis) cancer and prostate-cancer-specific death. Associations with cancer are significant within European (n = 71,856), Asian (n = 2,382), and African (n = 6,253) genetic ancestries (p 10 −180 ). Comparing the 80 th /20 th PHS 2 percentiles, hazard ratios for prostate cancer, aggressive cancer, and prostate-cancer-specific death are 5.32, 5.88, and 5.68, respectively. Within European, Asian, and African ancestries, hazard ratios for prostate cancer are: 5.54, 4.49, and 2.54, respectively. PHS 2 risk-stratifies men for any, aggressive, and fatal prostate cancer in a multi-ethnic dataset.
Publisher: EMBO
Date: 28-07-2020
Publisher: Springer Science and Business Media LLC
Date: 28-08-2020
DOI: 10.1038/S41467-020-17359-2
Abstract: Sex differences have been observed in multiple facets of cancer epidemiology, treatment and biology, and in most cancers outside the sex organs. Efforts to link these clinical differences to specific molecular features have focused on somatic mutations within the coding regions of the genome. Here we report a pan-cancer analysis of sex differences in whole genomes of 1983 tumours of 28 subtypes as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. We both confirm the results of exome studies, and also uncover previously undescribed sex differences. These include sex-biases in coding and non-coding cancer drivers, mutation prevalence and strikingly, in mutational signatures related to underlying mutational processes. These results underline the pervasiveness of molecular sex differences and strengthen the call for increased consideration of sex in molecular cancer research.
Publisher: Oxford University Press (OUP)
Date: 21-12-2016
DOI: 10.1093/BIOINFORMATICS/BTW762
Abstract: Testing SNP–SNP interactions is considered as a key for overcoming bottlenecks of genetic association studies. However, related statistical methods for testing SNP–SNP interactions are underdeveloped. We propose the SNP Interaction Pattern Identifier (SIPI), which tests 45 biologically meaningful interaction patterns for a binary outcome. SIPI takes non-hierarchical models, inheritance modes and mode coding direction into consideration. The simulation results show that SIPI has higher power than MDR (Multifactor Dimensionality Reduction), AA_Full, Geno_Full (full interaction model with additive or genotypic mode) and SNPassoc in detecting interactions. Applying SIPI to the prostate cancer PRACTICAL consortium data with approximately 21 000 patients, the four SNP pairs in EGFR-EGFR, EGFR-MMP16 and EGFR-CSF1 were found to be associated with prostate cancer aggressiveness with the exact or similar pattern in the discovery and validation sets. A similar match for external validation of SNP–SNP interaction studies is suggested. We demonstrated that SIPI not only searches for more meaningful interaction patterns but can also overcome the unstable nature of interaction patterns. The SIPI software is freely available at publichealth.lsuhsc.edu/LinSoftware/. Supplementary data are available at Bioinformatics online.
Publisher: Springer Science and Business Media LLC
Date: 25-01-2019
DOI: 10.1038/S41467-018-08054-4
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 × 10 −8 ), breast and ovarian cancer ( r g = 0.24, p = 7 × 10 −5 ), breast and lung cancer ( r g = 0.18, p =1.5 × 10 −6 ) and breast and colorectal cancer ( r g = 0.15, p = 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.
Publisher: Oxford University Press (OUP)
Date: 07-06-2018
DOI: 10.1093/BIOINFORMATICS/BTY461
Abstract: The use of single nucleotide polymorphism (SNP) interactions to predict complex diseases is getting more attention during the past decade, but related statistical methods are still immature. We previously proposed the SNP Interaction Pattern Identifier (SIPI) approach to evaluate 45 SNP interaction patterns atterns. SIPI is statistically powerful but suffers from a large computation burden. For large-scale studies, it is necessary to use a powerful and computation-efficient method. The objective of this study is to develop an evidence-based mini-version of SIPI as the screening tool or solitary use and to evaluate the impact of inheritance mode and model structure on detecting SNP–SNP interactions. We tested two candidate approaches: the ‘Five-Full’ and ‘AA9int’ method. The Five-Full approach is composed of the five full interaction models considering three inheritance modes (additive, dominant and recessive). The AA9int approach is composed of nine interaction models by considering non-hierarchical model structure and the additive mode. Our simulation results show that AA9int has similar statistical power compared to SIPI and is superior to the Five-Full approach, and the impact of the non-hierarchical model structure is greater than that of the inheritance mode in detecting SNP–SNP interactions. In summary, it is recommended that AA9int is a powerful tool to be used either alone or as the screening stage of a two-stage approach (AA9int+SIPI) for detecting SNP–SNP interactions in large-scale studies. The ‘AA9int’ and ‘parAA9int’ functions (standard and parallel computing version) are added in the SIPI R package, which is freely available at linhuiyi.github.io/LinHY_Software/. Supplementary data are available at Bioinformatics online.
Publisher: Springer Science and Business Media LLC
Date: 05-08-2017
Publisher: Springer Science and Business Media LLC
Date: 19-01-2018
Publisher: Springer Science and Business Media LLC
Date: 23-03-2022
DOI: 10.1038/S41598-022-08351-5
Abstract: Research using whole slide images (WSIs) of histopathology slides has increased exponentially over recent years. Glass slides from retrospective cohorts, some with patient follow-up data are digitised for the development and validation of artificial intelligence (AI) tools. Such resources, therefore, become very important, with the need to ensure that their quality is of the standard necessary for downstream AI development. However, manual quality control of large cohorts of WSIs by visual assessment is unfeasible, and whilst quality control AI algorithms exist, these focus on bespoke aspects of image quality, e.g. focus, or use traditional machine-learning methods, which are unable to classify the range of potential image artefacts that should be considered. In this study, we have trained and validated a multi-task deep neural network to automate the process of quality control of a large retrospective cohort of prostate cases from which glass slides have been scanned several years after production, to determine both the usability of the images at the diagnostic level (considered in this study to be the minimal standard for research) and the common image artefacts present. Using a two-layer approach, quality overlays of WSIs were generated from a quality assessment (QA) undertaken at patch-level at $$5\\times$$ 5 × magnification. From these quality overlays the slide-level quality scores were predicted and then compared to those generated by three specialist urological pathologists, with a Pearson correlation of 0.89 for overall ‘usability’ (at a diagnostic level), and 0.87 and 0.82 for focus and H& E staining quality scores respectively. To demonstrate its wider potential utility, we subsequently applied our QA pipeline to the TCGA prostate cancer cohort and to a colorectal cancer cohort, for comparison. Our model, designated as PathProfiler, indicates comparable predicted usability of images from the cohorts assessed (86–90% of WSIs predicted to be usable), and perhaps more significantly is able to predict WSIs that could benefit from an intervention such as re-scanning or re-staining for quality improvement. We have shown in this study that AI can be used to automate the process of quality control of large retrospective WSI cohorts to maximise their utility for research.
Publisher: Springer Science and Business Media LLC
Date: 20-09-2009
DOI: 10.1038/NG.452
Abstract: Previous studies have identified multiple loci on 8q24 associated with prostate cancer risk. We performed a comprehensive analysis of SNP associations across 8q24 by genotyping tag SNPs in 5,504 prostate cancer cases and 5,834 controls. We confirmed associations at three previously reported loci and identified additional loci in two other linkage disequilibrium blocks (rs1006908: per-allele OR = 0.87, P = 7.9 x 10(-8) rs620861: OR = 0.90, P = 4.8 x 10(-8)). Eight SNPs in five linkage disequilibrium blocks were independently associated with prostate cancer susceptibility.
Publisher: Springer Science and Business Media LLC
Date: 11-06-2018
Publisher: American Association for Cancer Research (AACR)
Date: 2019
DOI: 10.1158/1055-9965.EPI-18-0079
Abstract: 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-s le Mendelian randomization (MR). The case–control portion of the study was conducted in nine UK centers with men ages 50–69 years who underwent prostate-specific antigen 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. 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. 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. The metabolome provides a promising set of biomarkers that may aid prostate cancer classification.
Publisher: Springer Science and Business Media LLC
Date: 08-01-2019
DOI: 10.1038/S41467-018-08108-7
Abstract: The original version of this Article contained an error in the spelling of a member of the PRACTICAL Consortium, Manuela Gago-Dominguez, which was incorrectly given as Manuela Gago Dominguez. This has now been corrected in both the PDF and HTML versions of the Article. Furthermore, In the original HTML version of this Article, the order of authors within the author list was incorrect. The consortium PRACTICAL consortium was incorrectly listed after Bogdan Pasaniuc and should have been listed after Kathryn L. Penney. This error has been corrected in the HTML version of the Article the PDF version was correct at the time of publication.
Publisher: Springer Science and Business Media LLC
Date: 19-09-2015
Publisher: American Association for Cancer Research (AACR)
Date: 04-2013
DOI: 10.1158/1055-9965.EPI-12-1248
Abstract: Background: Ecological and epidemiological studies have identified an inverse association of intensity and duration of sunlight exposure with prostate cancer, which may be explained by a reduction in vitamin D synthesis. Pigmentation traits influence sun exposure and therefore may affect prostate cancer risk. Because observational studies are vulnerable to confounding and measurement error, we used Mendelian randomization to examine the relationship of sun exposure with both prostate cancer risk and the intermediate phenotype, plasma levels of vitamin D. Methods: We created a tanning, a skin color, and a freckling score as combinations of single nucleotide polymorphisms that have been previously associated with these phenotypes. A higher score indicates propensity to burn, have a lighter skin color and freckles. The scores were tested for association with vitamin D levels (25-hydroxyvitamin-D and 1,25-dihydroxyvitamin-D) and prostate-specific antigen detected prostate cancer in 3,123 White British in iduals enrolled in the Prostate Testing for cancer and Treatment (ProtecT) study. Results: The freckling score was inversely associated with 25(OH)D levels [change in 25(OH)D per score unit −0.27 95% CI, −0.52% to −0.01%], and the tanning score was positively associated with prostate cancer risk (OR = 1.05 95% CI, 1.02–1.09), after adjustment for population stratification and potential confounders. Conclusions: In iduals who tend to burn are more likely to spend less time in the sun and consequently have lower plasma vitamin D levels and higher susceptibility to prostate cancer. Impact: The use of pigmentation-related genetic scores is valuable for the assessment of the potential benefits of sun exposure with respect to prostate cancer risk. Cancer Epidemiol Biomarkers Prev 22(4) 597–606. ©2013 AACR.
Publisher: Wiley
Date: 15-05-2004
DOI: 10.1002/PROS.20016
Abstract: Osteoprotegerin (OPG) is a tumour and/or bone derived factor that may protect tumour cells from apoptosis. In this study, we have measured serum OPG levels in untreated prostate cancer patients with advanced prostate cancer compared to patients with organ confined disease and in treated patients receiving androgen ablation. Serum OPG levels were measured by ELISA in s les collected from 104 patients with either newly diagnosed (n = 59) or advanced prostate cancer treated by androgen ablation (n = 45) and compared with levels in serum from patients with benign prostatic hyperplasia (BPH) (n = 10) and young healthy men (n = 10). Untreated patients with locally advanced disease had significantly higher OPG levels than those with organ confined disease. Patients with advanced disease responding to androgen ablation (serum PSA 10 ng/ml). OPG levels in the latter were not significantly different from levels in patients with early signs of biochemical progression (PSA >1 but <10 ng/ml). OPG is a potential new marker, which is elevated in the serum of patients with advanced prostate cancer and may be an indicator of early disease progression.
Publisher: Springer Science and Business Media LLC
Date: 05-02-2020
DOI: 10.1038/S41586-020-1969-6
Abstract: Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale 1–3 . Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4–5 driver mutations when combining coding and non-coding genomic elements however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution in acral melanoma, for ex le, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter 4 identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation 5,6 analyses timings and patterns of tumour evolution 7 describes the erse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity 8,9 and evaluates a range of more-specialized features of cancer genomes 8,10–18 .
Publisher: Springer Science and Business Media LLC
Date: 08-01-2021
Publisher: Springer Science and Business Media LLC
Date: 24-03-2020
DOI: 10.1038/S41467-020-14451-5
Abstract: The timing of puberty is highly variable and is associated with long-term health outcomes. To date, understanding of the genetic control of puberty timing is based largely on studies in women. Here, we report a multi-trait genome-wide association study for male puberty timing with an effective s le size of 205,354 men. We find moderately strong genomic correlation in puberty timing between sexes (rg = 0.68) and identify 76 independent signals for male puberty timing. Implicated mechanisms include an unexpected link between puberty timing and natural hair colour, possibly reflecting common effects of pituitary hormones on puberty and pigmentation. Earlier male puberty timing is genetically correlated with several adverse health outcomes and Mendelian randomization analyses show a genetic association between male puberty timing and shorter lifespan. These findings highlight the relationships between puberty timing and health outcomes, and demonstrate the value of genetic studies of puberty timing in both sexes.
Publisher: American Association for Cancer Research (AACR)
Date: 14-04-2016
DOI: 10.1158/0008-5472.CAN-15-1551
Abstract: The role of insulin-like growth factors (IGF) in prostate cancer development is not fully understood. To investigate the association between circulating concentrations of IGFs (IGF-I, IGF-II, IGFBP-1, IGFBP-2, and IGFBP-3) and prostate cancer risk, we pooled in idual participant data from 17 prospective and two cross-sectional studies, including up to 10,554 prostate cancer cases and 13,618 control participants. Conditional logistic regression was used to estimate the ORs for prostate cancer based on the study-specific fifth of each analyte. Overall, IGF-I, IGF-II, IGFBP-2, and IGFBP-3 concentrations were positively associated with prostate cancer risk (Ptrend all ≤ 0.005), and IGFBP-1 was inversely associated weakly with risk (Ptrend = 0.05). However, heterogeneity between the prospective and cross-sectional studies was evident (Pheterogeneity = 0.03), unless the analyses were restricted to prospective studies (with the exception of IGF-II, Pheterogeneity = 0.02). For prospective studies, the OR for men in the highest versus the lowest fifth of each analyte was 1.29 (95% confidence interval, 1.16–1.43) for IGF-I, 0.81 (0.68–0.96) for IGFBP-1, and 1.25 (1.12–1.40) for IGFBP-3. These associations did not differ significantly by time-to-diagnosis or tumor stage or grade. After mutual adjustment for each of the other analytes, only IGF-I remained associated with risk. Our collaborative study represents the largest pooled analysis of the relationship between prostate cancer risk and circulating concentrations of IGF-I, providing strong evidence that IGF-I is highly likely to be involved in prostate cancer development. Cancer Res 76(8) 2288–300. ©2016 AACR.
Publisher: Elsevier BV
Date: 11-2015
Publisher: Springer Science and Business Media LLC
Date: 21-09-2020
DOI: 10.1038/S41467-020-18151-Y
Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA s les, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological ergences between two reproducible somatic variant detection efforts.
Publisher: Springer Science and Business Media LLC
Date: 06-08-2020
DOI: 10.1038/S41467-020-17673-9
Abstract: It remains elusive whether some of the associations identified in genome-wide association studies of prostate cancer (PrCa) may be due to regulatory effects of genetic variants on CpG sites, which may further influence expression of PrCa target genes. To search for CpG sites associated with PrCa risk, here we establish genetic models to predict methylation (N = 1,595) and conduct association analyses with PrCa risk (79,194 cases and 61,112 controls). We identify 759 CpG sites showing an association, including 15 located at novel loci. Among those 759 CpG sites, methylation of 42 is associated with expression of 28 adjacent genes. Among 22 genes, 18 show an association with PrCa risk. Overall, 25 CpG sites show consistent association directions for the methylation-gene expression-PrCa pathway. We identify DNA methylation biomarkers associated with PrCa, and our findings suggest that specific CpG sites may influence PrCa via regulating expression of candidate PrCa target genes.
Publisher: Cold Spring Harbor Laboratory
Date: 21-06-2019
DOI: 10.1101/679092
Abstract: We aimed to determine the effect of s le size on performance of polygenic hazard score (PHS) models in predicting the age at onset of prostate cancer. Age and genotypes were obtained for 40,861 men from the PRACTICAL consortium. The dataset included 201,590 SNPs per subject, and was split into training (34,444 s les) and testing (6,417 s les) sets. Two PHS model-building strategies were investigated. Established-SNP model considered 65 SNPs that had been associated with prostate cancer in the literature. A stepwise SNP selection was used to develop Discovery-SNP models. The performance of each PHS model was calculated for random sizes of the training set (1 to 30 thousand). The performance of a representative Established-SNP model was estimated for random sizes of the testing set (0.5 to 6 thousand). Mean HR 98/50 (hazard ratio of top 2% to the average in the test set) of the Established-SNP model increased from 1.73[95%CI: 1.69-1.77] to 2.41[2.40-2.43] when the number of training s les was increased from 1 to 30 thousand. The corresponding HR 98/50 of the Discovery-SNP model increased from 1.05[0.93-1.18] to 2.19[2.16-2.23]. HR 98/50 of a representative Established-SNP model using testing set s le sizes of 0.6 and 6 thousand observations were 1.78[1.70-1.85] and 1.73[1.71-1.76], respectively. We estimate that a study population of 20 to 30 thousand men is required to develop Discovery-SNP PHS models for prostate cancer. The required s le size could be reduced to 10 thousand s les, if a set of SNPs associated with the disease has already been established. Polygenic hazard scores represent a recent advancement in polygenic prediction to model the age of onset of various diseases, such as Alzheimer’s disease or prostate cancer. These scores accumulate small effect sizes from several tens of genetic variants and can be used to establish an in idual’s risk of experiencing an event relative to a control population across time. The largest barrier to the development of polygenic hazard scores is the large number of study subjects needed to develop the underlying models. We sought to understand the effect of varying the total number of s les on the performance of a polygenic hazard score in the context of prostate cancer. We found that the performance of the score did not appreciably change beyond 20 to 30 thousand observations when developing the model from scratch. However, when the discovery of the genetic variants can be borrowed from those already identified in the literature to be associated with the disease, the required number of s les is reduced to 10 thousand with no appreciable detriment in performance. We hope that these results can guide the design of future studies of polygenic scores in other diseases and demonstrate the importance of genome-wide association studies.
Publisher: BMJ
Date: 11-2017
DOI: 10.1136/BMJOPEN-2017-015994
Abstract: To compare the completeness and agreement of prostate cancer data recorded by the National Cancer Registration and Analysis Service (NCRAS) with research-level data specifically abstracted from medical records from the Cluster randomised triAl of prostate specific antigen (PSA) testing for Prostate cancer (CAP) trial. Cross-sectional comparison study. We included 1356 men from the CAP trial cohort who were linked to the NCRAS registry. Completeness of prostate cancer data in NCRAS and CAP and agreement for tumour, node, metastases (TNM) stage (T1/T2 T3 T4/N1/M1) and Gleason grade (4–6 7 8–10), measured by differences in proportions and Cohen’s kappa statistic. Data were also stratified by year and pre-2010 versus post-2010, when NCRAS reporting standards changed. Compared with CAP, completeness was lower in NCRAS for Gleason grade (41.2% vs 76.7%, difference 35.5, 95% CI 32.1 to 39.0) and TNM stage (29.9% vs 67.6%, difference 37.6, 95% CI 34.1 to 41.1). NCRAS completeness for Gleason grade (pre-2010 vs post-2010 31.69% vs 64% difference 32.31, 95% CI 26.76 to 37.87) and TNM stage (19.31% vs 55.50% difference 36.19, 95% CI 30.72 to 41.67) improved over time. Agreement for Gleason grade was high (Cohen’s kappa, κ=0.90, 95% CI 0.88 to 0.93), but lower for TNM stage (κ=0.41, 95% CI 0.37 to 0.51) overall. There was a trend towards improved agreement on Gleason grade, but not TNM stage, when comparing pre-2010 and post-2010 data. NCRAS case identification was very high however, data on prostate cancer grade was less complete than CAP, and agreement for TNM stage was modest. Although the completeness of NCRAS data has improved since 2010, the higher completeness rate in CAP demonstrates that gains could potentially be achieved in routine registry data. This study’s findings highlight a need for improved recording of stage and grade data in the source medical records.
Publisher: Elsevier BV
Date: 07-2013
DOI: 10.1016/J.UROLONC.2011.05.011
Abstract: The human tissue Kallikrein family consists of 15 genes with the majority shown to be differentially expressed in cancers and/or indicators of cancer prognosis. We sought to elucidate the role of common genetic variation in four of the Kallikrein genes, KLK5, KLK6, KLK12, and KLK13, in prostate cancer risk and tumor aggressiveness. Genotyping of all 22 tagging single nucleotide polymorphisms (tagSNPs) in the KLK5, KLK6, KLK12, and KLK13 genes was performed in approximately 1,000 prostate cancer cases and 1,300 male controls from Australia. Data from any positive results were also accessed for 1,844 cases and 1,886 controls from a previously published prostate cancer genome-wide association study set from the United Kingdom. For one SNP in KLK12, rs3865443, there was evidence for association with prostate cancer risk of similar direction and magnitude in the replication set to that seen in the Australian cohort. We conducted genotyping of a further 309 prostate cancer cases, and combined analyses revealed an increased risk of prostate cancer for carriers of the rare homozygous genotype for rs3865443 (OR 1.28, 95% CI 1.04-1.57 P = 0.018). No other tagSNPs in the KLK5, KLK6, and KLK13 genes were consistently associated with prostate cancer risk or tumor aggressiveness. Analysis of a combined s le of 3,153 cases and 3,199 controls revealed the KLK12 tagSNP rs3865443 to be marginally statistically significantly associated with risk of prostate cancer. Considering the total number of SNPs investigated in this study, this finding should be interpreted cautiously and requires additional validation from very large datasets such as those of the Prostate Cancer Association group to investigate cancer associated alterations (PRACTICAL) Consortium.
Publisher: Springer Science and Business Media LLC
Date: 11-06-2018
DOI: 10.1038/S41467-018-04109-8
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.
Publisher: Public Library of Science (PLoS)
Date: 28-05-2010
Publisher: Springer Science and Business Media LLC
Date: 04-02-2021
DOI: 10.1186/S12894-021-00789-5
Abstract: Active surveillance (AS) is a management option for men diagnosed with lower risk prostate cancer. There is wide variation in all aspects of AS internationally, from patient selection to investigations and follow-up intervals, and a lack of clear evidence on the optimal approach to AS. This study aimed to provide guidance for clinicians from an international panel of prostate cancer experts. A modified Delphi approach was undertaken, utilising two rounds of online questionnaires followed by a face-to-face workshop. Participants indicated their level of agreement with statements relating to patient selection for AS via online questionnaires on a 7-point Likert scale. Factors not achieving agreement were iteratively developed between the two rounds of questionnaires. Draft statements were presented at the face-to-face workshop for discussion and consensus building. 12 prostate cancer experts (9 urologists, 2 academics, 1 radiation oncologist) participated in this study from a range of geographical regions (4 USA, 4 Europe, 4 Australia). Complete agreement on statements presented to the participants was 29.4% after Round One and 69.0% after Round Two. Following robust discussions at the face-to-face workshop, agreement was reached on the remaining statements. PSA, PSA density, Multiparametric MRI, and systematic biopsy (with or without targeted biopsy) were identified as minimum diagnostic tests required upon which to select patients to recommend AS as a treatment option for prostate cancer. Patient factors and clinical parameters that identified patients appropriate to potentially receive AS were agreed. Genetic and genomic testing was not recommended for use in clinical decision-making regarding AS. The lack of consistency in the practice of AS for men with lower risk prostate cancer between and within countries was reflected in this modified Delphi study. There are, however, areas of common practice and agreement from which clinicians practicing in the current environment can use to inform their clinical practice to achieve the best outcomes for patients.
Publisher: Springer Science and Business Media LLC
Date: 04-10-2018
DOI: 10.1038/S41467-018-06302-1
Abstract: Although genome-wide association studies (GWAS) for prostate cancer (PrCa) have identified more than 100 risk regions, most of the risk genes at these regions remain largely unknown. Here we integrate the largest PrCa GWAS ( N = 142,392) with gene expression measured in 45 tissues ( N = 4458), including normal and tumor prostate, to perform a multi-tissue transcriptome-wide association study (TWAS) for PrCa. We identify 217 genes at 84 independent 1 Mb regions associated with PrCa risk, 9 of which are regions with no genome-wide significant SNP within 2 Mb. 23 genes are significant in TWAS only for alternative splicing models in prostate tumor thus supporting the hypothesis of splicing driving risk for continued oncogenesis. Finally, we use a Bayesian probabilistic approach to estimate credible sets of genes containing the causal gene at a pre-defined level this reduced the list of 217 associations to 109 genes in the 90% credible set. Overall, our findings highlight the power of integrating expression with PrCa GWAS to identify novel risk loci and prioritize putative causal genes at known risk loci.
Publisher: Wiley
Date: 14-07-2009
DOI: 10.1002/IJC.24411
Publisher: Elsevier BV
Date: 09-2020
Publisher: American Association for Cancer Research (AACR)
Date: 11-2015
DOI: 10.1158/1055-9965.EPI-15-0543
Abstract: Background: Unnecessary intervention and overtreatment of indolent disease are common challenges in clinical management of prostate cancer. Improved tools to distinguish lethal from indolent disease are critical. Methods: We performed a genome-wide survival analysis of cause-specific death in 24,023 prostate cancer patients (3,513 disease-specific deaths) from the PRACTICAL and BPC3 consortia. Top findings were assessed for replication in a Norwegian cohort (CONOR). Results: We observed no significant association between genetic variants and prostate cancer survival. Conclusions: Common genetic variants with large impact on prostate cancer survival were not observed in this study. Impact: Future studies should be designed for identification of rare variants with large effect sizes or common variants with small effect sizes. Cancer Epidemiol Biomarkers Prev 24(11) 1796–800. ©2015 AACR.
Publisher: Springer Science and Business Media LLC
Date: 08-2017
DOI: 10.1038/BJC.2017.231
Abstract: Evidence on height and prostate cancer risk is mixed, however, recent studies with large data sets support a possible role for its association with the risk of aggressive prostate cancer. We analysed data from the PRACTICAL consortium consisting of 6207 prostate cancer cases and 6016 controls and a subset of high grade cases (2480 cases). We explored height, polymorphisms in genes related to growth processes as main effects and their possible interactions. The results suggest that height is associated with high-grade prostate cancer risk. Men with height cm are at a 22% increased risk as compared to men with height cm (OR 1.22, 95% CI 1.01–1.48). Genetic variants in the growth pathway gene showed an association with prostate cancer risk. The aggregate scores of the selected variants identified a significantly increased risk of overall prostate cancer and high-grade prostate cancer by 13% and 15%, respectively, in the highest score group as compared to lowest score group. There was no evidence of gene-environment interaction between height and the selected candidate SNPs. Our findings suggest a role of height in high-grade prostate cancer. The effect of genetic variants in the genes related to growth is seen in all cases and high-grade prostate cancer. There is no interaction between these two exposures.
Publisher: Springer Science and Business Media LLC
Date: 29-04-2014
DOI: 10.1038/NCOMMS4756
Abstract: Bladder cancers are a leading cause of death from malignancy. Molecular markers might predict disease progression and behaviour more accurately than the available prognostic factors. Here we use whole-genome sequencing to identify somatic mutations and chromosomal changes in 14 bladder cancers of different grades and stages. As well as detecting the known bladder cancer driver mutations, we report the identification of recurrent protein-inactivating mutations in CDKN1A and FAT1. The former are not mutually exclusive with TP53 mutations or MDM2 lification, showing that CDKN1A dysfunction is not simply an alternative mechanism for p53 pathway inactivation. We find strong positive associations between higher tumour stage/grade and greater clonal ersity, the number of somatic mutations and the burden of copy number changes. In principle, the identification of sub-clones with greater ersity and/or mutation burden within early-stage or low-grade tumours could identify lesions with a high risk of invasive progression.
Publisher: Wiley
Date: 14-07-2015
DOI: 10.1002/PROS.23037
Publisher: BMJ
Date: 10-01-2018
DOI: 10.1136/BMJ.J5757
Abstract: To develop and validate a genetic tool to predict age of onset of aggressive prostate cancer (PCa) and to guide decisions of who to screen and at what age. Analysis of genotype, PCa status, and age to select single nucleotide polymorphisms (SNPs) associated with diagnosis. These polymorphisms were incorporated into a survival analysis to estimate their effects on age at diagnosis of aggressive PCa (that is, not eligible for surveillance according to National Comprehensive Cancer Network guidelines any of Gleason score ≥7, stage T3-T4, PSA (prostate specific antigen) concentration ≥10 ng/L, nodal metastasis, distant metastasis). The resulting polygenic hazard score is an assessment of in idual genetic risk. The final model was applied to an independent dataset containing genotype and PSA screening data. The hazard score was calculated for these men to test prediction of survival free from PCa. Multiple institutions that were members of international PRACTICAL consortium. All consortium participants of European ancestry with known age, PCa status, and quality assured custom (iCOGS) array genotype data. The development dataset comprised 31 747 men the validation dataset comprised 6411 men. Prediction with hazard score of age of onset of aggressive cancer in validation set. In the independent validation set, the hazard score calculated from 54 single nucleotide polymorphisms was a highly significant predictor of age at diagnosis of aggressive cancer (z=11.2, P<10 Polygenic hazard scores can be used for personalised genetic risk estimates that can predict for age at onset of aggressive PCa.
Publisher: Springer Science and Business Media LLC
Date: 10-07-2011
DOI: 10.1038/NG.882
Publisher: Wiley
Date: 08-10-2016
DOI: 10.1002/IJC.30436
Publisher: American Association for Cancer Research (AACR)
Date: 2015
DOI: 10.1158/1055-9965.EPI-14-0377
Abstract: Background: PCA3 is a long noncoding RNA (lncRNA) with unknown function, upregulated in prostate cancer. LncRNAs may be processed into smaller active species. We hypothesized this for PCA3. Methods: We computed feasible RNA hairpins within the BMCC1 gene (encompassing PCA3) and searched a prostate transcriptome for these. We measured expression using qRT-PCR in three cohorts of prostate cancer tissues (n = 60), exfoliated urinary cells (n = 484 with cancer and n = 166 controls), and in cell lines (n = 22). We used in silico predictions and RNA knockup to identify potential mRNA targets of short transcribed RNAs. Results: We predicted 13 hairpins, of which PCA3-shRNA2 was most abundant within the prostate transcriptome. PCA3-shRNA2 is located within intron 1 of PCA3 and appears regulated by androgens. Expression of PCA3-shRNA2 was upregulated in malignant prostatic tissues, exfoliated urinary cells from men with prostate cancer (13–273 fold change t test P & 0.003), and closely correlated to PCA3 expression (r = 0.84–0.93 P & 0.001). Urinary PCA3-shRNA2 (C-index, 0.75–0.81) and PCA3 (C-index, 0.78) could predict the presence of cancer in most men. PCA3-shRNA2 knockup altered the expression of predicted target mRNAs, including COPS2, SOX11, WDR48, TEAD1, and Noggin. PCA3-shRNA2 expression was negatively correlated with COPS2 in patient s les (r = −0.32 P & 0.001). Conclusion: We identified a short RNA within PCA3, whose expression is correlated to PCA3, which may target mRNAs implicated in prostate biology. Impact: This short RNA is stable ex vivo, suggesting a role as a robust biomarker. We identify cytoplasmic enrichment of this RNA and potential targeting of mRNAs implicated in prostate carcinogenesis. Cancer Epidemiol Biomarkers Prev 24(1) 268–75. ©2014 AACR.
Publisher: Oxford University Press (OUP)
Date: 29-05-2015
DOI: 10.1093/HMG/DDV203
Publisher: American Association for Cancer Research (AACR)
Date: 07-2014
DOI: 10.1158/1055-9965.EPI-13-0889
Abstract: Background: Only a minority of the genetic components of prostate cancer risk have been explained. Some observed associations of SNPs with prostate cancer might arise from associations of these SNPs with circulating prostate-specific antigen (PSA) because PSA values are used to select controls. Methods: We undertook a genome-wide association study (GWAS) of screen-detected prostate cancer (ProtecT: 1,146 cases and 1,804 controls) meta-analyzed the results with those from the previously published UK Genetic Prostate Cancer Study (1,854 cases and 1,437 controls) investigated associations of SNPs with prostate cancer using either “low” (PSA & 0.5 ng/mL) or “high” (PSA ≥ 3 ng/mL, biopsy negative) PSA controls and investigated associations of SNPs with PSA. Results: The ProtecT GWAS confirmed previously reported associations of prostate cancer at three loci: 10q11.23, 17q24.3, and 19q13.33. The meta-analysis confirmed associations of prostate cancer with SNPs near four previously identified loci (8q24.21,10q11.23, 17q24.3, and 19q13.33). When comparing prostate cancer cases with low PSA controls, alleles at genetic markers rs1512268, rs445114, rs10788160, rs11199874, rs17632542, rs266849, and rs2735839 were associated with an increased risk of prostate cancer, but the effect-estimates were attenuated to the null when using high PSA controls (Pheterogeneity in effect-estimates & 0.04). We found a novel inverse association of rs9311171-T with circulating PSA. Conclusions: Differences in effect-estimates for prostate cancer observed when comparing low versus high PSA controls may be explained by associations of these SNPs with PSA. Impact: These findings highlight the need for inferences from genetic studies of prostate cancer risk to carefully consider the influence of control selection criteria. Cancer Epidemiol Biomarkers Prev 23(7) 1356–65. ©2014 AACR.
Publisher: American Association for Cancer Research (AACR)
Date: 11-2009
DOI: 10.1158/1055-9965.EPI-09-0544
Abstract: Low levels of plasma vitamin D have been implicated as a possible risk factor for both prostate cancer incidence and advanced disease, and recent phase II trials suggest that vitamin D supplementation might delay progression of prostate cancer. Common polymorphisms in the vitamin D receptor (VDR) are associated with VDR activity and are therefore potentially useful proxies for assessing whether vitamin D is causally related to advanced prostate cancer. We genotyped five well-known VDR polymorphisms in 1,604 men with prostate cancer from the Prostate Testing for Cancer and Treatment study. Our aim was to examine the association between VDR polymorphisms and cancer stage (localized versus advanced) as well as cancer grade (Gleason score & versus ≥7). Moreover, we also carried out a systematic review and meta-analysis of 13 similar studies. As a result of our meta-analysis, we revealed three polymorphisms, BsmI, ApaI, and TaqI, associated with high Gleason score with an overall summary odds ratios (95% confidence intervals) of 1.12 (1.00-1.25 bb versus BB + Bb), 1.25 (1.02-1.53 aa versus AA + Aa), and 0.82 (0.69-0.98 Tt + tt versus TT), respectively. The haplotype analysis revealed that the BsmI (B)-ApaI (A)-TaqI (t) participants compared with BsmI (b)-ApaI (a)-TaqI (T) in iduals were less likely to have high Gleason scores (odds ratio, 0.84 95% confidence interval, 0.71-1.00 Punadjusted = 0.050 Padjusted = 0.014). Our finding provides some support for the hypothesis that low levels of vitamin D may increase the risk of prostate cancer progression. (Cancer Epidemiol Biomarkers Prev 2009 (11):2874–81)
Publisher: Springer Science and Business Media LLC
Date: 2018
DOI: 10.1038/BJC.2017.429
Publisher: Springer Science and Business Media LLC
Date: 23-09-2019
DOI: 10.1038/S41467-019-12095-8
Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Publisher: Elsevier BV
Date: 12-2019
Publisher: Wiley
Date: 2021
DOI: 10.1002/BCO2.60
Publisher: Public Library of Science (PLoS)
Date: 06-09-2016
Publisher: Springer Science and Business Media LLC
Date: 09-12-2014
DOI: 10.1007/S10552-014-0500-5
Abstract: Vitamin D pathway single nucleotide polymorphisms (SNPs) are potentially useful proxies for investigating whether circulating vitamin D metabolites [total 25-hydroxyvitamin-D, 25(OH)D 1,25-dihydroxyvitamin, 1,25(OH)2D] are causally related to prostate cancer. We investigated associations of sixteen SNPs across seven genes with prostate-specific antigen-detected prostate cancer. In a nested case-control study (within the ProtecT trial), we estimated odds ratios and 95 % confidence intervals (CIs) quantifying associations between SNPs and prostate cancer. Subgroup analyses investigated whether associations were stronger in men who had high/low sun exposure [a proxy for 25(OH)D]. We quantified associations of SNPs with stage (T1-T2/T3-T4) and grade (<7/≥7). Multiple variant scores included SNPs encoding proteins involved in 25(OH)D synthesis and metabolism. We included 1,275 prostate cancer cases (141 locally advanced, 385 high grades) and 2,062 healthy controls. Vitamin D-binding protein SNPs were associated with prostate cancer (rs4588-A: OR 1.20, CI 1.01, 1.41, p = 0.04 rs7041-T: OR 1.19, CI 1.02, 1.38, p = 0.03). Low 25(OH)D metabolism score was associated with high (vs low) grade (OR 0.76, CI 0.63, 0.93, p = 0.01) there was a similar association of its component variants: rs6013897-A in CYP24A1 (OR 0.78, CI 0.60, 1.01, p = 0.06) and rs10877012-T in CYP27B1 (OR 0.80, CI 0.63, 1.02, p = 0.07). There was no evidence that associations differed by level of sun exposure. We found some evidence that vitamin D pathway SNPs were associated with prostate cancer risk and grade, but not stage. There was no evidence of an association in men with deficient vitamin D (measured by having low sun exposure).
Publisher: Medknow
Date: 12-2008
DOI: 10.1038/AJA.2008.18
Publisher: Springer Science and Business Media LLC
Date: 2021
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Freddie Hamdy.