Germline variation at 8q24 and prostate cancer risk in men of European ancestry

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

Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants

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. © 2018 The Author(s).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. © 2018 The Author(s).Peer reviewe

The impact of uro-oncology multidisciplinary team meeting (MDTM) on clinical decision-making and adherence to MDTM recommendation: experience from a tertiary referral centre in Malaysia

Abstract Background Multidisciplinary team meeting (MDTM) has become an increasingly important part of disease management model, particularly in cancer care. MDTM consists of a group of doctors to provide independent opinions on diagnostic and treatment decisions, as well as personalized therapeutic plan for patients. By selecting the most suitable treatment for patients from multiple perspectives, management by multidisciplinary team (MDT) have been shown to have advantages over traditional treatment models. The objective of this study is to determine the impact of MDTM on the management of uro-oncological cases and adherence to MDTM plans. Methods We retrospectively collected patients’ clinical information discussed in MDTM from 1st January 2021 to 31st December 2022 at our institution. The pre-MDTM treatment plan by the clinicians and the MDTM consensus plans were compared to assess the overall MDTM impact on patient management. Adherence to MDTM recommendations was also analyzed. Results Data on 432 patients discussed in MDTM from 1st January 2021 to 31st December 2022 were collected and analyzed. Prostate cancer was the most common type of cancer discussed (n = 212, 48.8%). MDTM had a significant impact on decision-making in 276 (63.6%) cases, with changes to patient management being observed in more than half of all cases. Adherence to MDTM outcomes was high with 383 (90.5%) of patients eventually had treatment according to the MDTM recommendation. Conclusion The study highlights the importance of MDTM in the management of genitourinary malignancies, particularly in cases where no original plan exists. Patient’s compliance and adherence to the MDTM consensus plan are also very encouraging

Spatio-temporal analysis of the main dengue vector populations in Singapore

Background: Despite the licensure of the world’s first dengue vaccine and the current development of additional vaccine candidates, successful Aedes control remains critical to the reduction of dengue virus transmission. To date, there is still limited literature that attempts to explain the spatio-temporal population dynamics of Aedes mosquitoes within a single city, which hinders the development of more effective citywide vector control strategies. Narrowing this knowledge gap requires consistent and longitudinal measurement of Aedes abundance across the city as well as examination of relationships between variables on a much finer scale. Methods: We utilized a high-resolution longitudinal dataset generated from Singapore’s islandwide Gravitrap surveillance system over a 2-year period and built a Bayesian hierarchical model to explain the spatio-temporal dynamics of Aedes aegypti and Aedes albopictus in relation to a wide range of environmental and anthropogenic variables. We also created a baseline during our model assessment to serve as a benchmark to be compared with the model’s out-of-sample prediction/forecast accuracy as measured by the mean absolute error. Results: For both Aedes species, building age and nearby managed vegetation cover were found to have a significant positive association with the mean mosquito abundance, with the former being the strongest predictor. We also observed substantial evidence of a nonlinear effect of weekly maximum temperature on the Aedes abundance. Our models generally yielded modest but statistically significant reductions in the out-of-sample prediction/forecast error relative to the baseline. Conclusions: Our findings suggest that public residential estates with older buildings and more nearby managed vegetation should be prioritized for vector control inspections and community advocacy to reduce the abundance of Aedes mosquitoes and the risk of dengue transmission.[Figure not available: see fulltext.] © 2021, The Author(s).ISSN:1756-330

Fluidic Logic Used in a Systems Approach to Enable Integrated Single-cell Functional Analysis

The study of single cells has evolved over the past several years to include expression and genomic analysis of an increasing number of single cells. Several studies have demonstrated wide-spread variation and heterogeneity within cell populations of similar phenotype. While the characterization of these populations will likely set the foundation for our understanding of genomic- and expression-based diversity, it will not be able to link the functional differences of a single cell to its underlying genomic structure and activity. Currently, it is difficult to perturb single cells in a controlled environment, monitor and measure the response due to perturbation, and link these response measurements to downstream genomic and transcriptomic analysis. In order to address this challenge, we developed a platform to integrate and miniaturize many of the experimental steps required to study single-cell function. The heart of this platform is an elastomer-based Integrated Fluidic Circuit (IFC) that uses fluidic logic to select and sequester specific single cells based on a phenotypic trait for downstream experimentation. Experiments with sequestered cells that have been performed include on-chip culture, exposure to a variety of stimulants, and post-exposure image-based response analysis, followed by preparation of the mRNA transcriptome for massively parallel sequencing analysis. The flexible system embodies experimental design and execution that enable routine functional studies of single cells

Author Correction: Germline variation at 8q24 and prostate cancer risk in men of European ancestry

International audienceThe original version of this Article contained an error in the spelling of the author Manuela Gago-Dominguez, which was incorrectly given as Manuela G. Dominguez. This has now been corrected in both the PDF and HTML versions of the Article

Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants

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