Personalized medicine: Has it started yet? A reconstruction of the early history

Within the last few years the field personalized medicine entered the stage. Accompanied with great hopes and expectations it is believed that this field may have the potential to revolutionize medical and clinical care by utilizing genomics information about the individual patients themselves. In this paper, we reconstruct the early footprints of personalized medicine as reflected by information retrieved from PubMed and Google Scholar. That means we are providing a data-driven perspective of this field to estimate its current status and potential problems.

cudaMap: a GPU accelerated program for gene expression connectivity mapping

Background: Modern cancer research often involves large datasets and the use of sophisticated statistical techniques. Together these add a heavy computational load to the analysis, which is often coupled with issues surrounding data accessibility. Connectivity mapping is an advanced bioinformatic and computational technique dedicated to therapeutics discovery and drug re-purposing around differential gene expression analysis. On a normal desktop PC, it is common for the connectivity mapping task with a single gene signature to take >2h to complete using sscMap, a popular Java application that runs on standard CPUs (Central Processing Units). Here, we describe new software, cudaMap, which has been implemented using CUDA C/C++ to harness the computational power of NVIDIA GPUs (Graphics Processing Units) to greatly reduce processing times for connectivity mapping.

Results: cudaMap can identify candidate therapeutics from the same signature in just over thirty seconds when using an NVIDIA Tesla C2050 GPU. Results from the analysis of multiple gene signatures, which would previously have taken several days, can now be obtained in as little as 10 minutes, greatly facilitating candidate therapeutics discovery with high throughput. We are able to demonstrate dramatic speed differentials between GPU assisted performance and CPU executions as the computational load increases for high accuracy evaluation of statistical significance.

Conclusion: Emerging 'omics' technologies are constantly increasing the volume of data and information to be processed in all areas of biomedical research. Embracing the multicore functionality of GPUs represents a major avenue of local accelerated computing. cudaMap will make a strong contribution in the discovery of candidate therapeutics by enabling speedy execution of heavy duty connectivity mapping tasks, which are increasingly required in modern cancer research. cudaMap is open source and can be freely downloaded from http://purl.oclc.org/NET/cudaMap.

Extremely Complex Populations of Small RNAs in the Mouse Retina and RPE/Choroid

Purpose: MicroRNAs (miRNAs) are small non-coding RNAs of ~18-22 nucleotides in length that regulate gene expression. They are widely expressed in the retina, being both required for its normal development and perturbed in disease. The aim of this study was to apply new high-throughput sequencing techniques to more fully characterise the microRNAs and other small RNAs expressed in the retina and retinal pigment epithelium (RPE)/choroid of the mouse.

Methods: Retina and RPE/choroid were dissected from eyes of 3 month-old C57BL/6J mice. Small RNA libraries were prepared and deep sequencing performed on a Genome Analyzer (Illumina). Reads were annotated by alignment to miRBase, other non-coding RNA databases and the mouse genome.

Results: Annotation of 9 million reads to 320 microRNAs in retina and 340 in RPE/choroid provides the most comprehensive profiling of microRNAs to date. Two novel microRNAs were identified in retina. Members of the sensory organ specific miR-183,-182,-96 cluster were amongst the most highly expressed, retina-enriched microRNAs. Remarkably, microRNA 'isomiRs', which vary slightly in length and are differentially detected by Taqman RT-PCR assays, existed for all the microRNAs identified in both tissues. More variation occurred at the 3' ends, including non-templated additions of T and A. Drosha-independent mirtron microRNAs and other small RNAs derived from snoRNAs were also detected.

Conclusions: Deep sequencing has revealed the complexity of small RNA expression in the mouse retina and RPE/choroid. This knowledge will improve the design and interpretation of future functional studies of the role of microRNAs and other small RNAs in retinal disease.

Multi-standard sub-pixel interpolation architecture for video motion estimation

A new domain-specific reconfigurable sub-pixel interpolation architecture for multi-standard video Motion Estimation (ME) is presented. The mixed use of parallel and serial-input FIR filters achieves high throughput rate and efficient silicon utilisation. Flexibility has been achieved by using a multiplexed reconfigurable data-path controlled by a selection signal. Silicon design studies show that this can be implemented using 34.8K gates with area and performance that compares very favourably with existing fixed solutions based solely on the H.264 standard. ©2008 IEEE.

qPCR utilization for the study of RNA Polymerase I transcription

Ribosome biogenesis is a fundamental cellular process tightly linked to cell growth and proliferation, which requires the coordinated transcription of all three nuclear polymerases. Synthesis of ribosomal RNA (rRNA) by RNA polymerase I (Pol I) has been suggested as a key regulator of ribosome biogenesis, and there is a strong link between transcription of ribosomal RNAs and cellular proliferation. This makes Pol I transcription a valid and attractive target for anticancer therapy. At the moment however there are only a small number of compounds that act as specific inhibitors of Pol I transcription and this makes it very difficult for the development of drugs which would target rRNA transcription and consequently ribosome biogenesis. Therefore, to aid in the development of new inhibitors of Pol I, high-throughput methods to monitor and detect changes in Pol I activity need to be developed. This current study aimed to address the question of whether or not quantitative PCR (qPCR) could be used to detect changes in rRNA production in cells under different conditions that repress Pol I activity i.e. serum starvation and drug treatment. Our results have shown that using primers and a hydrolysis probe designed for the 5’ETS region of the pre-rRNA molecule, rRNA levels in both treated and untreated cells could be determined by using qPCR.
Amplification resulted in formation of a single product and S1 nuclease protection assay confirmed the down-regulation of Pol I transcription. Following serum-starvation and drug treatment there was a dramatic reduction in the amount of 5’ETS transcript quantitated by both Sybr Green chemistry and the use of a fluorescently labelled hydrolysis probe. The optimization of the qPCR strategy will be discussed.

Improved Detection of Mycobacterium bovis in Bovine Tissues Using Immunomagnetic Separation Approaches

Immunomagnetic separation (IMS) represents a simple but effective method of selectively capturing and concentrating Mycobacterium bovis, the causative agent of bovine tuberculosis (bTB), from tissue samples. It is a physical cell separation technique that does not impact cell viability, unlike traditional chemical decontamination prior to culture. IMS is performed with paramagnetic beads coated with M. bovis-specific antibody and peptide binders. Once captured by IMS, M. bovis cells can be detected by either PCR or cultural detection methods. Increased detection rates of M. bovis, particularly from non-visibly lesioned lymph node tissues from bTB reactor animals, have recently been reported when IMS-based methods were employed.

Multimedia Resource Allocation in mmWave 5G Networks

The 5G network infrastructure is driven by the evolution of today's most demanding applications. Already, multimedia applications such as on-demand HD video and IPTV require gigabit- per-second throughput and low delay, while future technologies include ultra HDTV and machine-to-machine communication. Mm-Wave technologies such as IEEE 802.15.3c and IEEE 802.11ad are ideal candidates to deliver high throughput to multiple users demanding differentiated QoS. Optimization is often used as a methodology to meet throughput and delay constraints. However, traditional optimization techniques are not suited to a mixed set of multimedia applications. Particle swarm optimization (PSO) is shown as a promising technique in this context. Channel-time allocation PSO (CTA-PSO) is successfully shown here to allocate resource even in scenarios where blockage of the 60 GHz signal poses significant challenges.

MICROBIAL COMMUNITY COMPOSITION IN THE LUNGS OF PATIENTS WITH CYSTIC FIBROSIS AND NON-CF BRONCHIECTASIS

Introduction and Aims: Persistent bacterial infection is a major cause of morbidity and mortality in patients with both Cystic Fibrosis (CF) and non-CF Bronchiectasis (non-CFBX). Numerous studies have shown that CF and non-CFBX airways are colonised by a complex microbiota. However, many bacteria are difficult, if not impossible, to culture by conventional laboratory techniques. Therefore, molecular detection techniques offer a more comprehensive view of bacterial diversity within clinical specimens. The objective of this study was to characterise and compare bacterial diversity and relative abundance in patients with CF and non-CFBX during exacerbation and when clinically stable.

Methods: Sputum samples were collected from CF (n=50 samples) and non-CFBX (n=52 samples) patients at the start and end of treatment for an infective exacerbation and when clinically stable. Pyrosequencing was used to assess the microbial diversity and relative genera (or the closest possibly taxonomic order) abundance within the samples. Each sequence read was defined based on 3% difference.

Results: High-throughput pyrosequencing allowed a sensitive and detailed examination of microbial community composition. Rich microbial communities were apparent within both CF (171 species-level phylotypes per genus) and non-CFBX airways (144 species-level phylotypes per genus). Relative species distribution within those two environments was considerably different; however, relatively few genera formed a core of microorganisms, representing approximately 90% of all sequences, which dominated both environments. Relative abundance based on observed operational taxonomic units demonstrated that the most abundant bacteria in CF were Pseudomonas (28%), Burkholderia (22%), Streptococcus (13%), family Pseudomonadaceae (8%) and Prevotella (6%). In contrast, the most commonly detected operational taxonomic units in non-CFBX were Haemophilus (22%), Streptococcus (14%), other (unassigned taxa) (11%), Pseudomonas (10%), Veillonella (7%) and Prevotella (6%).

Conclusions: These results suggest that distinctive microbial communities are associated with infection and/or colonisation in patients with both CF and non-CFBX. Although relatively high species richness was observed within the two environments, each was dominated by different core taxa. This suggests that differences in the lung environment of these two diseases may affect adaptability of the relevant bacterial taxa.

DNA methylation subgroups and the CpG island methylator phenotype in gastric cancer: a comprehensive profiling approach

BACKGROUND: Methylation-induced silencing of promoter CpG islands in tumor suppressor genes plays an important role in human carcinogenesis. In colorectal cancer, the CpG island methylator phenotype (CIMP) is defined as widespread and elevated levels of DNA methylation and CIMP+ tumors have distinctive clinicopathological and molecular features. In contrast, the existence of a comparable CIMP subtype in gastric cancer (GC) has not been clearly established. To further investigate this issue, in the present study we performed comprehensive DNA methylation profiling of a well-characterised series of primary GC.

METHODS: The methylation status of 1,421 autosomal CpG sites located within 768 cancer-related genes was investigated using the Illumina GoldenGate Methylation Panel I assay on DNA extracted from 60 gastric tumors and matched tumor-adjacent gastric tissue pairs. Methylation data was analysed using a recursively partitioned mixture model and investigated for associations with clinicopathological and molecular features including age, Helicobacter pylori status, tumor site, patient survival, microsatellite instability and BRAF and KRAS mutations.

RESULTS: A total of 147 genes were differentially methylated between tumor and matched tumor-adjacent gastric tissue, with HOXA5 and hedgehog signalling being the top-ranked gene and signalling pathway, respectively. Unsupervised clustering of methylation data revealed the existence of 6 subgroups under two main clusters, referred to as L (low methylation; 28% of cases) and H (high methylation; 72%). Female patients were over-represented in the H tumor group compared to L group (36% vs 6%; P = 0.024), however no other significant differences in clinicopathological or molecular features were apparent. CpG sites that were hypermethylated in group H were more frequently located in CpG islands and marked for polycomb occupancy.

CONCLUSIONS: High-throughput methylation analysis implicates genes involved in embryonic development and hedgehog signaling in gastric tumorigenesis. GC is comprised of two major methylation subtypes, with the highly methylated group showing some features consistent with a CpG island methylator phenotype.

Next-generation sequencing: a change of paradigm in molecular diagnostic validation

Next-generation sequencing (NGS) is beginning to show its full potential for diagnostic and therapeutic applications. In particular, it is enunciating its capacity to contribute to a molecular taxonomy of cancer, to be used as a standard approach for diagnostic mutation detection, and to open new treatment options that are not exclusively organ-specific. If this is the case, how much validation is necessary and what should be the validation strategy, when bringing NGS into the diagnostic/clinical practice? This validation strategy should address key issues such as: what is the overall extent of the validation? Should essential indicators of test performance such as sensitivity of specificity be calculated for every target or sample type? Should bioinformatic interpretation approaches be validated with the same rigour? What is a competitive clinical turnaround time for a NGS-based test, and when does it become a cost-effective testing proposition? While we address these and other related topics in this commentary, we also suggest that a single set of international guidelines for the validation and use of NGS technology in routine diagnostics may allow us all to make a much more effective use of resources.

Computational cancer biology: education is a natural key to many locks

Background: Oncology is a field that profits tremendously from the genomic data generated by high-throughput technologies, including next-generation sequencing. However, in order to exploit, integrate, visualize and interpret such high-dimensional data efficiently, non-trivial computational and statistical analysis methods are required that need to be developed in a problem-directed manner.

Discussion: For this reason, computational cancer biology aims to fill this gap. Unfortunately, computational cancer biology is not yet fully recognized as a coequal field in oncology, leading to a delay in its maturation and, as an immediate consequence, an under-exploration of high-throughput data for translational research.

Summary: Here we argue that this imbalance, favoring 'wet lab-based activities', will be naturally rectified over time, if the next generation of scientists receives an academic education that provides a fair and competent introduction to computational biology and its manifold capabilities. Furthermore, we discuss a number of local educational provisions that can be implemented on university level to help in facilitating the process of harmonization.

LC- HRMS based metabolomics in food safety and doping control – DeTECH21

Issues surrounding the misuse of prohibited and licensed substances in animals destined for food production and performance sport competition continue to be an enormous challenge to regulatory authorities charged with enforcing their control. Efficient analytical strategies are implemented to screen and confirm the presence of a wide range of exogenous substances in various biological matrices. However, such methods rely on the direct measurement of drugs and/or their metabolites in a targeted mode, allowing the detection of restricted number of compounds. As a consequence, emerging practices, in particular the use of natural hormones, designer drugs and low-dose cocktails, remain difficult to handle from a control point of view. A new SME-led FP7 funded project, DeTECH21, aims to overcome current limitations by applying an untargeted metabolomics approach based on liquid chromatography coupled to high resolution mass spectrometry and bioinformatic data analysis to identify bovine and equine animals which have been exposed to exogenous substances and assist in the identification of administered compounds. Markerbased strategies, dealing with the comprehensive analysis of metabolites present in a biological sample (urine/plasma/tissue), offer a reliable solution in the areas of food safety and animal sport doping control by effective, high-throughput and sensitive detection of exogenously administered agents. Therefore, the development of the first commercially available forensic test service based on metabolomics profiling will meet 21st century demands in animal forensics.

A novel experimental approach to investigate radiolysis processes in liquid samples using collimated radiation sources

Here is detailed a novel and low-cost experimental method for high-throughput automated fluid sample irradiation. The sample is delivered via syringe pump to a nozzle, where it is expressed in the form of a hanging droplet into the path of a beam of ionising radiation. The dose delivery is controlled by an upstream lead shutter, which allows the beam to reach the droplet for a user defined period of time. The droplet is then further expressed after irradiation until it falls into one well of a standard microplate. The entire system is automated and can be operated remotely using software designed in-house, allowing for use in environments deemed unsafe for the user (synchrotron beamlines, for example). Depending on the number of wells in the microplate, several droplets can be irradiated before any human interaction is necessary, and the user may choose up to 10 samples per microplate using an array of identical syringe pumps, the design of which is described here. The nozzles consistently produce droplets of 25.1 ± 0.5 μl.

An unbiased genetic screen reveals the polygenic nature of the influenza virus anti-interferon response

UNLABELLED: Influenza A viruses counteract the cellular innate immune response at several steps, including blocking RIG I-dependent activation of interferon (IFN) transcription, interferon (IFN)-dependent upregulation of IFN-stimulated genes (ISGs), and the activity of various ISG products; the multifunctional NS1 protein is responsible for most of these activities. To determine the importance of other viral genes in the interplay between the virus and the host IFN response, we characterized populations and selected mutants of wild-type viruses selected by passage through non-IFN-responsive cells. We reasoned that, by allowing replication to occur in the absence of the selection pressure exerted by IFN, the virus could mutate at positions that would normally be restricted and could thus find new optimal sequence solutions. Deep sequencing of selected virus populations and individual virus mutants indicated that nonsynonymous mutations occurred at many phylogenetically conserved positions in nearly all virus genes. Most individual mutants selected for further characterization induced IFN and ISGs and were unable to counteract the effects of exogenous IFN, yet only one contained a mutation in NS1. The relevance of these mutations for the virus phenotype was verified by reverse genetics. Of note, several virus mutants expressing intact NS1 proteins exhibited alterations in the M1/M2 proteins and accumulated large amounts of deleted genomic RNAs but nonetheless replicated to high titers. This suggests that the overproduction of IFN inducers by these viruses can override NS1-mediated IFN modulation. Altogether, the results suggest that influenza viruses replicating in IFN-competent cells have tuned their complete genomes to evade the cellular innate immune system and that serial replication in non-IFN-responsive cells allows the virus to relax from these constraints and find a new genome consensus within its sequence space.

IMPORTANCE: In natural virus infections, the production of interferons leads to an antiviral state in cells that effectively limits virus replication. The interferon response places considerable selection pressure on viruses, and they have evolved a variety of ways to evade it. Although the influenza virus NS1 protein is a powerful interferon antagonist, the contributions of other viral genes to interferon evasion have not been well characterized. Here, we examined the effects of alleviating the selection pressure exerted by interferon by serially passaging influenza viruses in cells unable to respond to interferon. Viruses that grew to high titers had mutations at many normally conserved positions in nearly all genes and were not restricted to the NS1 gene. Our results demonstrate that influenza viruses have fine-tuned their entire genomes to evade the interferon response, and by removing interferon-mediated constraints, viruses can mutate at genome positions normally restricted by the interferon response.

PICan: An integromics framework for dynamic cancer biomarker discovery

Modern cancer research on prognostic and predictive biomarkers demands the integration of established and emerging high-throughput technologies. However, these data are meaningless unless carefully integrated with patient clinical outcome and epidemiological information. Integrated datasets hold the key to discovering new biomarkers and therapeutic targets in cancer. We have developed a novel approach and set of methods for integrating and interrogating phenomic, genomic and clinical data sets to facilitate cancer biomarker discovery and patient stratification. Applied to a known paradigm, the biological and clinical relevance of TP53, PICan was able to recapitulate the known biomarker status and prognostic significance at a DNA, RNA and protein levels.