The role of glycans in the development and progression of prostate cancer

Prostate cancer is a unique and heterogeneous disease. Currently, a major unmet clinical need exists to develop biomarkers that enable indolent disease to be distinguished from aggressive disease. The prostate is an abundant secretor of glycoproteins of all types, and alterations in glycans are, therefore, attractive as potential biomarkers and therapeutic targets. Despite progress over the past decade in profiling the genome and proteome, the prostate cancer glycoproteome remains relatively understudied. A wide range of alterations in the glycoproteins on prostate cancer cells can occur, including increased sialylation and fucosylation, increased O-β-N-acetylglucosamine (GlcNAc) conjugation, the emergence of cryptic and high-mannose N-glycans and alterations to proteoglycans. Glycosylation can alter protein function and has a key role in many important biological processes in cancer including cell adhesion, migration, interactions with the cell matrix, immune surveillance, cell signalling and cellular metabolism; altered glycosylation in prostate cancer might modify some, or all of these processes. In the past three years, powerful tools such as glycosylation-specific antibodies and glycosylation gene signatures have been developed, which enable detailed analyses of changes in glycosylation. Thus, emerging data on these often overlooked modifications have the potential to improve risk stratification and therapeutic strategies in patients with prostate cancer.

QUADrATiC: scalable gene expression connectivity mapping for repurposing FDA-approved therapeutics

Background: Gene expression connectivity mapping has proven to be a powerful and flexible tool for research. Its application has been shown in a broad range of research topics, most commonly as a means of identifying potential small molecule compounds, which may be further investigated as candidates for repurposing to treat diseases. The public release of voluminous data from the Library of Integrated Cellular Signatures (LINCS) programme further enhanced the utilities and potentials of gene expression connectivity mapping in biomedicine. Results: We describe QUADrATiC (http://go.qub.ac.uk/QUADrATiC), a user-friendly tool for the exploration of gene expression connectivity on the subset of the LINCS data set corresponding to FDA-approved small molecule compounds. It enables the identification of compounds for repurposing therapeutic potentials. The software is designed to cope with the increased volume of data over existing tools, by taking advantage of multicore computing architectures to provide a scalable solution, which may be installed and operated on a range of computers, from laptops to servers. This scalability is provided by the use of the modern concurrent programming paradigm provided by the Akka framework. The QUADrATiC Graphical User Interface (GUI) has been developed using advanced Javascript frameworks, providing novel visualization capabilities for further analysis of connections. There is also a web services interface, allowing integration with other programs or scripts.Conclusions: QUADrATiC has been shown to provide an improvement over existing connectivity map software, in terms of scope (based on the LINCS data set), applicability (using FDA-approved compounds), usability and speed. It offers potential to biological researchers to analyze transcriptional data and generate potential therapeutics for focussed study in the lab. QUADrATiC represents a step change in the process of investigating gene expression connectivity and provides more biologically-relevant results than previous alternative solutions.

Quiet-Sun Hα Transients and Corresponding Small-scale Transition Region and Coronal Heating

Rapid blue- and redshifted excursions (RBEs and RREs) are likely to be the on-disk counterparts of Type II spicules. Recently, heating signatures from RBEs/RREs have been detected in IRIS slit-jaw images dominated by transition region (TR) lines around network patches. Additionally, signatures of Type II spicules have been observed in Atmospheric Imaging Assembly (AIA) diagnostics. The full-disk, ever-present nature of the AIA diagnostics should provide us with sufficient statistics to directly determine how important RBEs and RREs are to the heating of the TR and corona. We find, with high statistical significance, that at least 11% of the low coronal brightenings detected in a quiet-Sun region in He ii 304 Å can be attributed to either RBEs or RREs as observed in Hα, and a 6% match of Fe IX 171 Å detected events to RBEs or RREs with very similar statistics for both types of Hα features. We took a statistical approach that allows for noisy detections in the coronal channels and provides us with a lower, but statistical significant, bound. Further, we consider matches based on overlapping features in both time and space, and find strong visual indications of further correspondence between coronal events and co-evolving but non-overlapping, RBEs and RREs.

A gene-signature progression approach to identifying candidate small-molecule cancer therapeutics with connectivity mapping

Gene expression connectivity mapping has gained much popularity recently with a number of successful applications in biomedical research testifying its utility and promise. Previously methodological research in connectivity mapping mainly focused on two of the key components in the framework, namely, the reference gene expression profiles and the connectivity mapping algorithms. The other key component in this framework, the query gene signature, has been left to users to construct without much consensus on how this should be done, albeit it has been an issue most relevant to end users. As a key input to the connectivity mapping process, gene signature is crucially important in returning biologically meaningful and relevant results. This paper intends to formulate a standardized procedure for constructing high quality gene signatures from a user’s perspective.