The Nuclear Receptor (NR) superfamily of transcription factors comprises 48 members, several of which have been implicated in breast cancer. Most important is estrogen receptor-α (ERα), which is a key therapeutic target. ERα action is facilitated by co-operativity with other NR and there is evidence that ERα function may be recapitulated by other NRs in ERα-negative breast cancer. In order to examine the inter-relationships between nuclear receptors, and to obtain evidence for previously unsuspected roles for any NRs, we undertook quantitative RT-PCR and bioinformatics analysis to examine their expression in breast cancer. While most NRs were expressed, bioinformatic analyses differentiated tumours into distinct prognostic groups that were validated by analyzing public microarray data sets. Although ERα and progesterone receptor were dominant in distinguishing prognostic groups, other NR strengthened these groups. Clustering analysis identified several family members with potential importance in breast cancer. Specifically, RORγ is identified as being co-expressed with ERα, whilst several NRs are preferentially expressed in ERα-negative disease, with TLX expression being prognostic in this subtype. Functional studies demonstrated the importance of TLX in regulating growth and invasion in ERα-negative breast cancer cells.
We report on the details of the methodology applied to support shortlisting the nominees for the Microlise Driver of the Year awards. The aim was to recognise the United Kingdom's most talented heavy goods vehicle (HGV) drivers, with the list of top 46 drivers across 16 different companies determined through the analysis of telematics data. Initial data for the awards was gathered from over 90,000 drivers engaging with Microlise's telematics solutions. The data was analysed anonymously in order to identify the best criteria to establish top performing drivers. The initial selection was made based on a minimum number of miles driven across each of the four quarters in 2014. Outlier removal and a consensus clustering framework were subsequently employed to the dataset to identify subgroups of drivers. Three categories of drivers were identified: short, medium and long distance drivers. Each qualifying professional belonging to one of the three categories was then assessed using a range of criteria compared to other drivers from the same category. To determine the final winners, questionnaires for further evidence and indicators that might contribute to a driver being named as a winner was sent down to employers and their responses were evaluated.
The domain of biobanking has gone through many stages and as a result there are a wide range of commercial and open source software solutions available. The utilization of these software tools requires different levels of domain and technical skills for installation, configuration and ultimate us of these biobank software tools. To compound this complexity the biobanking community are required to work together in order to share knowledge and jointly build solutions to underpin the research infrastructure. We have evaluated the available tools, described them in a catalogue (BiobankApps) and made a selection of tools available to biobanks in a reference toolbox (BIBBOX) that are use-case driven. In the BiobankApps tool catalogue, both commercial and open source software solutions related to the biobanking domain are included, classified and evaluated. The evaluation covers: 1) “user review” by an authenticated user 2) domain expert: quick analysis by BBMRI members and 3) domain expert: detailed analysis and test installation with real world data. The evaluation is paired with a survey across the more “advanced” (from a technology perspective) biobanks to investigate what tools are currently used and summarises known benefits/drawbacks of the respective packages. In the second step we recommend tools for specific use cases, and install, configure and connect these in the BIBBOX framework. This service also builds on the existing work in the United Kingdom in seeking to establish the motivations for different stakeholders to become involved and therefore assisting in prioritising the use-cases based on the level of need and support within the research community. All tools associated to a use-case are available as BIBBOX applications (technically this is achieved by docker containers), which are integrated in the BIBBOX framework with central identification and user management. In future work we plan to share the acquired knowledge with other networks, develop an Application Programmable Interface (API) for the exchange of metadata with other tool catalogues and work on an ontology for the evaluation of biobank software.
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