Connectivity mapping using a combined gene signature from multiple colorectal cancer datasets identified candidate drugs including existing chemotherapies

BACKGROUND: While the discovery of new drugs is a complex, lengthy and costly process, identifying new uses for existing drugs is a cost-effective approach to therapeutic discovery. Connectivity mapping integrates gene expression profiling with advanced algorithms to connect genes, diseases and small molecule compounds and has been applied in a large number of studies to identify potential drugs, particularly to facilitate drug repurposing. Colorectal cancer (CRC) is a commonly diagnosed cancer with high mortality rates, presenting a worldwide health problem. With the advancement of high throughput omics technologies, a number of large scale gene expression profiling studies have been conducted on CRCs, providing multiple datasets in gene expression data repositories. In this work, we systematically apply gene expression connectivity mapping to multiple CRC datasets to identify candidate therapeutics to this disease.

RESULTS: We developed a robust method to compile a combined gene signature for colorectal cancer across multiple datasets. Connectivity mapping analysis with this signature of 148 genes identified 10 candidate compounds, including irinotecan and etoposide, which are chemotherapy drugs currently used to treat CRCs. These results indicate that we have discovered high quality connections between the CRC disease state and the candidate compounds, and that the gene signature we created may be used as a potential therapeutic target in treating the disease. The method we proposed is highly effective in generating quality gene signature through multiple datasets; the publication of the combined CRC gene signature and the list of candidate compounds from this work will benefit both cancer and systems biology research communities for further development and investigations.

Using particle dispersal models to assist in the conservation and recovery of the overexploited native oyster (Ostrea edulis) in an enclosed sea lough

Oyster populations around the world have seen catastrophic decline which has been largely attributed to overexploitation, disease and pollution. While considerable effort and resources have been implemented into restoring these important environmental engineers, the success of oyster populations is often limited by poor understanding of site-specific dispersal patterns of propagules. Water-borne transport is a key factor controlling or regulating the dispersal of the larval stage of benthic marine invertebrates which have limited mobility. The distribution of the native oyster Ostrea edulis in Strangford Lough, Northern Ireland, together with their densities and population structure at subtidal and intertidal sites has been documented at irregular intervals between 1997 and 2013. This paper revisits this historical data and considers whether different prevailing environmental conditions can be used to explain the distribution, densities and population structure of O. edulis in Strangford Lough. The approach adopted involved comparing predictive 2D hydrodynamic models coupled with particle tracking to simulate the dispersal of oyster larvae with historical and recent field records of the distribution of both subtidal and intertidal, populations since 1995. Results from the models support the hypothesis that commercial stocks of O. edulis introduced into Strangford Lough in the 1990s resulted in the re-establishment of wild populations of oysters in the Northern Basin which in turn provided a potential source of propagules for subtidal populations. These results highlight that strategic site selection (while inadvertent in the case of the introduced population in 1995) for the re-introduction of important shellfish species can significantly accelerate their recovery and restoration.

Novel tools for conservation genomics: comparing two high-throughput approaches for SNP discovery in the transcriptome of the European hake

The growing accessibility to genomic resources using next-generation sequencing (NGS) technologies has revolutionized the application of molecular genetic tools to ecology and evolutionary studies in non-model organisms. Here we present the case study of the European hake (Merluccius merluccius), one of the most important demersal resources of European fisheries. Two sequencing platforms, the Roche 454 FLX (454) and the Illumina Genome Analyzer (GAII), were used for Single Nucleotide Polymorphisms (SNPs) discovery in the hake muscle transcriptome. De novo transcriptome assembly into unique contigs, annotation, and in silico SNP detection were carried out in parallel for 454 and GAII sequence data. High-throughput genotyping using the Illumina GoldenGate assay was performed for validating 1,536 putative SNPs. Validation results were analysed to compare the performances of 454 and GAII methods and to evaluate the role of several variables (e.g. sequencing depth, intron-exon structure, sequence quality and annotation). Despite well-known differences in sequence length and throughput, the two approaches showed similar assay conversion rates (approximately 43%) and percentages of polymorphic loci (67.5% and 63.3% for GAII and 454, respectively). Both NGS platforms therefore demonstrated to be suitable for large scale identification of SNPs in transcribed regions of non-model species, although the lack of a reference genome profoundly affects the genotyping success rate. The overall efficiency, however, can be improved using strict quality and filtering criteria for SNP selection (sequence quality, intron-exon structure, target region score).

Carbon Sink Conservation and Global Justice: Benefiting, Free Riding and Non-Compliance

It is often assumed that in order to avoid the most severe consequences of global anthropogenic climate change we have to preserve our existing carbon sinks, such as for instance tropical forests. Global carbon sink conservation raises a host of normative issues, though, since it is debatable who should pay the costs of carbon sink conservation, who has the duty to protect which sinks, and how far the duty to conserve one’s carbon sinks actually extends, especially if it conflicts with other duties one might have. According to some, forested states like Ecuador have a duty to preserve their tropical forests while the rich states of the global North have a duty of fairness to compensate states like Ecuador for the costs they incur. My aim in this paper is to critically analyse this standard line of argument and to criticise its validity both internally (i.e. with regard to its normative conclusion based on its premises) and externally (i.e. with regard to the argument’s underlying assumptions and its lack of contextualisation). As I will argue, the duty to conserve one’s forests is only a particular instantiation of a wider, more general duty to contribute towards global climate justice for which the context in which one operates (e.g. whether other agents are complying with their duties of global climate justice or not) matters significantly.

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.

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.