TMAX – a Database System Integrating Tissue Biomarker & Genomic Data

Background: Popular approaches in human tissue-based biomarker discovery include tissue microarrays (TMAs) and DNA Microarrays (DMAs) for protein and gene expression profiling respectively. The data generated by these analytic platforms, together with associated image, clinical and pathological data currently reside on widely different information platforms, making searching and cross-platform analysis difficult. Consequently, there is a strong need to develop a single coherent database capable of correlating all available data types.

Method: This study presents TMAX, a database system to facilitate biomarker discovery tasks. TMAX organises a variety of biomarker discovery-related data into the database. Both TMA and DMA experimental data are integrated in TMAX and connected through common DNA/protein biomarkers. Patient clinical data (including tissue pathological data), computer assisted tissue image and associated analytic data are also included in TMAX to enable the truly high throughput processing of ultra-large digital slides for both TMAs and whole slide tissue digital slides. A comprehensive web front-end was built with embedded XML parser software and predefined SQL queries to enable rapid data exchange in the form of standard XML files.

Results & Conclusion: TMAX represents one of the first attempts to integrate TMA data with public gene expression experiment data. Experiments suggest that TMAX is robust in managing large quantities of data from different sources (clinical, TMA, DMA and image analysis). Its web front-end is user friendly, easy to use, and most importantly allows the rapid and easy data exchange of biomarker discovery related data. In conclusion, TMAX is a robust biomarker discovery data repository and research tool, which opens up the opportunities for biomarker discovery and further integromics research.

Genomic insights into the origin of parasitism in the emerging plant pathogen Bursaphelenchus xylophilus.

Bursaphelenchus xylophilus is the nematode responsible for a devastating epidemic of pine wilt disease in Asia and Europe, and represents a recent, independent origin of plant parasitism in nematodes, ecologically and taxonomically distinct from other nematodes for which genomic data is available. As well as being an important pathogen, the B. xylophilus genome thus provides a unique opportunity to study the evolution and mechanism of plant parasitism. Here, we present a high-quality draft genome sequence from an inbred line of B. xylophilus, and use this to investigate the biological basis of its complex ecology which combines fungal feeding, plant parasitic and insect-associated stages. We focus particularly on putative parasitism genes as well as those linked to other key biological processes and demonstrate that B. xylophilus is well endowed with RNA interference effectors, peptidergic neurotransmitters (including the first description of ins genes in a parasite) stress response and developmental genes and has a contracted set of chemosensory receptors. B. xylophilus has the largest number of digestive proteases known for any nematode and displays expanded families of lysosome pathway genes, ABC transporters and cytochrome P450 pathway genes. This expansion in digestive and detoxification proteins may reflect the unusual diversity in foods it exploits and environments it encounters during its life cycle. In addition, B. xylophilus possesses a unique complement of plant cell wall modifying proteins acquired by horizontal gene transfer, underscoring the impact of this process on the evolution of plant parasitism by nematodes. Together with the lack of proteins homologous to effectors from other plant parasitic nematodes, this confirms the distinctive molecular basis of plant parasitism in the Bursaphelenchus lineage. The genome sequence of B. xylophilus adds to the diversity of genomic data for nematodes, and will be an important resource in understanding the biology of this unusual parasite.

Facilitating a culture of responsible and effective sharing of cancer genome data

Rapid and affordable tumor molecular profiling has led to an explosion of clinical and genomic data poised to enhance the diagnosis, prognostication and treatment of cancer. A critical point has now been reached at which the analysis and storage of annotated clinical and genomic information in unconnected silos will stall the advancement of precision cancer care. Information systems must be harmonized to overcome the multiple technical and logistical barriers to data sharing. Against this backdrop, the Global Alliance for Genomic Health (GA4GH) was established in 2013 to create a common framework that enables responsible, voluntary and secure sharing of clinical and genomic data. This Perspective from the GA4GH Clinical Working Group Cancer Task Team highlights the data-aggregation challenges faced by the field, suggests potential collaborative solutions and describes how GA4GH can catalyze a harmonized data-sharing culture.

Discovery of multiple neuropeptide families in the phylum Platyhelminthes

Available evidence shows that short amidated neuropeptides are widespread and have important functions within the nervous systems of all flatworms (phylum Platyhelminthes) examined, and could therefore represent a starting point for new lead drug compounds with which to combat parasitic helminth infections. However, only a handful of these peptides have been characterised, the rigorous exploration of the flatworm peptide signalling repertoire having been hindered by the dearth of flatworm genomic data. Through searches of both expressed sequence tags and genomic resources using the basic local alignment search tool (BLAST), we describe 96 neuropeptides on 60 precursors from 10 flatworm species. Most of these (51 predicted peptides on 14 precursors) are novel and are apparently restricted to flatworms; the remainder comprise nine recognised peptide families including FMRFamide-like (FLPs), neuropeptide F (NPF)-like, myomodulin-like, buccalin-like and neuropeptide FF (NPFF)-like peptides; notably, the latter have only previously been reported in vertebrates. Selected peptides were localised immunocytochemically to the Schistosoma mansoni nervous system. We also describe several novel flatworm NPFs with structural features characteristic of the vertebrate neuropeptide Y (NPY) superfamily, previously unreported characteristics which support the common ancestry of flatworm NPFs with the NPY-superfamily. Our dataset provides a springboard for investigation of the functional biology and therapeutic potential of neuropeptides in flatworms, simultaneously launching flatworm neurobiology into the post-genomic era. (C) 2009 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.

The repertoire of G protein-coupled receptors in the human parasite Schistosoma mansoni and the model organism Schmidtea mediterranea.

Background

G protein-coupled receptors (GPCRs) constitute one of the largest groupings of eukaryotic proteins, and represent a particularly lucrative set of pharmaceutical targets. They play an important role in eukaryotic signal transduction and physiology, mediating cellular responses to a diverse range of extracellular stimuli. The phylum Platyhelminthes is of considerable medical and biological importance, housing major pathogens as well as established model organisms. The recent availability of genomic data for the human blood fluke Schistosoma mansoni and the model planarian Schmidtea mediterranea paves the way for the first comprehensive effort to identify and analyze GPCRs in this important phylum.

Results

Application of a novel transmembrane-oriented approach to receptor mining led to the discovery of 117 S. mansoni GPCRs, representing all of the major families; 105 Rhodopsin, 2 Glutamate, 3 Adhesion, 2 Secretin and 5 Frizzled. Similarly, 418 Rhodopsin, 9 Glutamate, 21 Adhesion, 1 Secretin and 11 Frizzled S. mediterranea receptors were identified. Among these, we report the identification of novel receptor groupings, including a large and highly-diverged Platyhelminth-specific Rhodopsin subfamily, a planarian-specific Adhesion-like family, and atypical Glutamate-like receptors. Phylogenetic analysis was carried out following extensive gene curation. Support vector machines (SVMs) were trained and used for ligand-based classification of full-length Rhodopsin GPCRs, complementing phylogenetic and homology-based classification.

Conclusions

Genome-wide investigation of GPCRs in two platyhelminth genomes reveals an extensive and complex receptor signaling repertoire with many unique features. This work provides important sequence and functional leads for understanding basic flatworm receptor biology, and sheds light on a lucrative set of anthelmintic drug targets.

Dense fine-mapping study identifies new susceptibility loci for primary biliary cirrhosis

We genotyped 2,861 cases of primary biliary cirrhosis (PBC) from the UK PBC Consortium and 8,514 UK population controls across 196,524 variants within 186 known autoimmune risk loci. We identified 3 loci newly associated with PBC (at P <5 × 10(-8)), increasing the number of known susceptibility loci to 25. The most associated variant at 19p12 is a low-frequency nonsynonymous SNP in TYK2, further implicating JAK-STAT and cytokine signaling in disease pathogenesis. An additional five loci contained nonsynonymous variants in high linkage disequilibrium (LD; r(2) > 0.8) with the most associated variant at the locus. We found multiple independent common, low-frequency and rare variant association signals at five loci. Of the 26 independent non-human leukocyte antigen (HLA) signals tagged on the Immunochip, 15 have SNPs in B-lymphoblastoid open chromatin regions in high LD (r(2) > 0.8) with the most associated variant. This study shows how data from dense fine-mapping arrays coupled with functional genomic data can be used to identify candidate causal variants for functional follow-up.

Genotypic and phenotypic diversity of the noncapsulated Haemophilus influenzae:Adaptation and pathogenesis in the human airways

The human respiratory tract contains a highly adapted microbiota including commensal and opportunistic pathogens. Noncapsulated or nontypable Haemophilus influenzae (NTHi) is a human-restricted member of the normal airway microbiota in healthy carriers and an opportunistic pathogen in immunocompromised individuals. The duality of NTHi as a colonizer and as a symptomatic infectious agent is closely related to its adaptation to the host, which in turn greatly relies on the genetic plasticity of the bacterium and is facilitated by its condition as a natural competent. The variable genotype of NTHi accounts for its heterogeneous gene expression and variable phenotype, leading to differential host-pathogen interplay among isolates. Here we review our current knowledge of NTHi diversity in terms of genotype, gene expression, antigenic variation, and the phenotypes associated with colonization and pathogenesis. The potential benefits of NTHi diversity studies discussed herein include the unraveling of pathogenicity clues, the generation of tools to predict virulence from genomic data, and the exploitation of a unique natural system for the continuous monitoring of long-term bacterial evolution in human airways exposed to noxious agents. Finally, we highlight the challenge of monitoring both the pathogen and the host in longitudinal studies, and of applying comparative genomics to clarify the meaning of the vast NTHi genetic diversity and its translation to virulence phenotypes.

Digital pathology and image analysis in tissue biomarker research

Digital pathology and the adoption of image analysis have grown rapidly in the last few years. This is largely due to the implementation of whole slide scanning, advances in software and computer processing capacity and the increasing importance of tissue-based research for biomarker discovery and stratified medicine. This review sets out the key application areas for digital pathology and image analysis, with a particular focus on research and biomarker discovery. A variety of image analysis applications are reviewed including nuclear morphometry and tissue architecture analysis, but with emphasis on immunohistochemistry and fluorescence analysis of tissue biomarkers. Digital pathology and image analysis have important roles across the drug/companion diagnostic development pipeline including biobanking, molecular pathology, tissue microarray analysis, molecular profiling of tissue and these important developments are reviewed. Underpinning all of these important developments is the need for high quality tissue samples and the impact of pre-analytical variables on tissue research is discussed. This requirement is combined with practical advice on setting up and running a digital pathology laboratory. Finally, we discuss the need to integrate digital image analysis data with epidemiological, clinical and genomic data in order to fully understand the relationship between genotype and phenotype and to drive discovery and the delivery of personalized medicine.

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.

Exploring molecular variation in Schistosoma japonicum in China

Schistosomiasis is a neglected tropical disease that affects more than 200 million people worldwide. The main disease-causing agents, Schistosoma japonicum, S. mansoni and S. haematobium, are blood flukes that have complex life cycles involving a snail intermediate host. In Asia, S. japonicum causes hepatointestinal disease (schistosomiasis japonica) and is challenging to control due to a broad distribution of its snail hosts and range of animal reservoir hosts. In China, extensive efforts have been underway to control this parasite, but genetic variability in S. japonicum populations could represent an obstacle to eliminating schistosomiasis japonica. Although a draft genome sequence is available for S. japonicum, there has been no previous study of molecular variation in this parasite on a genome-wide scale. In this study, we conducted the first deep genomic exploration of seven S. japonicum populations from mainland China, constructed phylogenies using mitochondrial and nuclear genomic data sets, and established considerable variation between some of the populations in genes inferred to be linked to key cellular processes and/or pathogen-host interactions. Based on the findings from this study, we propose that verifying intraspecific conservation in vaccine or drug target candidates is an important first step toward developing effective vaccines and chemotherapies against schistosomiasis.

Unraveling flp-11/flp-32 dichotomy in nematodes

FMRFamide-like peptide (FLP) signalling systems are core to nematode neuromuscular function. Novel drug discovery efforts associated with nematode FLP/FLP receptor biology are advanced through the accumulation of basic biological data that can reveal subtle complexities within the neuropeptidergic system. This study reports the characterisation of FMRFamide-like peptide encoding gene-11 (flp-11) and FMRFamide-like peptide encoding gene-32 (flp-32), two distinct flp genes which encode the analogous peptide, AMRN(A/S)LVRFamide, in multiple nematode species - the only known example of this phenomenon within the FLPergic system of nematodes. Using bioinformatics, in situ hybridisation, immunocytochemistry and behavioural assays we show that: (i) flp-11 and -32 are distinct flp genes expressed individually or in tandem across multiple nematode species, where they encode a highly similar peptide; (ii) flp-11 does not appear to be the most widely expressed flp in Caenorhabditis elegans; (iii) in species expressing both flp-11 and flp-32, flp-11 displays a conserved, restricted expression pattern across nematode clades and lifestyles; (iv) in species expressing both flp-11 and flp-32, flp-32 expression is more widespread and less conserved than flp-11; (v) in species expressing only flp-11, the flp-11 expression profile is more similar to the flp-32 profile observed in species expressing both; and (vi) FLP-11 peptides inhibit motor function in multiple nematode species. The biological significance and evolutionary origin of flp-11 and -32 peptide duplication remains unclear despite attempts to identify a common ancestor; this may become clearer as the availability of genomic data improves. This work provides insight into the complexity of the neuropeptidergic system in nematodes, and begins to examine how nematodes may compensate for structural neuronal simplicity. From a parasite control standpoint this work underscores the importance of basic biological data, and has wider implications for the utility of C. elegans as a model for parasite neurobiology.

Partial structure of the phylloxin gene from the giant monkey frog, Phyllomedusa bicolor: parallel cloning of precursor cDNA and genomic DNA from lyophilized skin secretion

Phylloxin is a novel prototype antimicrobial peptide from the skin of Phyllomedusa bicolor. Here, we describe parallel identification and sequencing of phylloxin precursor transcript (mRNA) and partial gene structure (genomic DNA) from the same sample of lyophilized skin secretion using our recently-described cloning technique. The open-reading frame of the phylloxin precursor was identical in nucleotide sequence to that previously reported and alignment with the nucleotide sequence derived from genomic DNA indicated the presence of a 175 bp intron located in a near identical position to that found in the dermaseptins. The highly-conserved structural organization of skin secretion peptide genes in P. bicolor can thus be extended to include that encoding phylloxin (plx). These data further reinforce our assertion that application of the described methodology can provide robust genomic/transcriptomic/peptidomic data without the need for specimen sacrifice.

Long-term genomic instability in human lymphocytes induced by single-particle irradiation

Recent evidence suggests that genomic instability, which is an important step in carcinogenesis, may be important in the effectiveness of radiation as a carcinogen, particularly for high-LET radiations. Understanding the biological effects underpinning the risks associated with low doses of densely ionizing radiations is complicated in experimental systems by the Poisson distribution of particles that ran be delivered, In this study, we report an approach to determine the effect of the lowest possible cellular radiation dose of densely ionizing at particles, that of a single particle traversal. Using microbeam technology and an approach for immobilizing human T-lymphocytes, we have measured the effects of single alpha -particle traversals on the surviving progeny of cells. A significant increase in the proportion of aberrant cells is observed 12-13 population doublings after exposure, with a high level of chromatid-type aberrations, indicative of an instability phenotype, These data suggest that instability may be important in situations where even a single particle traverses human cells. (C) 2001 by Radiation Research Society.

Combined genomic and phenotype screening reveals secretory factor SPINK1 as an invasion and survival factor associated with patient prognosis in breast cancer

Secretory factors that drive cancer progression are attractive immunotherapeutic targets. We used a whole-genome data-mining approach on multiple cohorts of breast tumours annotated for clinical outcomes to discover such factors. We identified Serine protease inhibitor Kazal-type 1 (SPINK1) to be associated with poor survival in estrogen receptor-positive (ER+) cases. Immunohistochemistry showed that SPINK1 was absent in normal breast, present in early and advanced tumours, and its expression correlated with poor survival in ER+ tumours. In ER- cases, the prognostic effect did not reach statistical significance. Forced expression and/or exposure to recombinant SPINK1 induced invasiveness without affecting cell proliferation. However, down-regulation of SPINK1 resulted in cell death. Further, SPINK1 overexpressing cells were resistant to drug-induced apoptosis due to reduced caspase-3 levels and high expression of Bcl2 and phospho-Bcl2 proteins. Intriguingly, these anti-apoptotic effects of SPINK1 were abrogated by mutations of its protease inhibition domain. Thus, SPINK1 affects multiple aggressive properties in breast cancer: survival, invasiveness and chemoresistance. Because SPINK1 effects are abrogated by neutralizing antibodies, we suggest that SPINK1 is a viable potential therapeutic target in breast cancer.

Connectivity Mapping for Candidate Therapeutics Identification Using Next Generation Sequencing RNA-Seq Data

The advent of next generation sequencing technologies (NGS) has expanded the area of genomic research, offering high coverage and increased sensitivity over older microarray platforms. Although the current cost of next generation sequencing is still exceeding that of microarray approaches, the rapid advances in NGS will likely make it the platform of choice for future research in differential gene expression. Connectivity mapping is a procedure for examining the connections among diseases, genes and drugs by differential gene expression initially based on microarray technology, with which a large collection of compound-induced reference gene expression profiles have been accumulated. In this work, we aim to test the feasibility of incorporating NGS RNA-Seq data into the current connectivity mapping framework by utilizing the microarray based reference profiles and the construction of a differentially expressed gene signature from a NGS dataset. This would allow for the establishment of connections between the NGS gene signature and those microarray reference profiles, alleviating the associated incurring cost of re-creating drug profiles with NGS technology. We examined the connectivity mapping approach on a publicly available NGS dataset with androgen stimulation of LNCaP cells in order to extract candidate compounds that could inhibit the proliferative phenotype of LNCaP cells and to elucidate their potential in a laboratory setting. In addition, we also analyzed an independent microarray dataset of similar experimental settings. We found a high level of concordance between the top compounds identified using the gene signatures from the two datasets. The nicotine derivative cotinine was returned as the top candidate among the overlapping compounds with potential to suppress this proliferative phenotype. Subsequent lab experiments validated this connectivity mapping hit, showing that cotinine inhibits cell proliferation in an androgen dependent manner. Thus the results in this study suggest a promising prospect of integrating NGS data with connectivity mapping. © 2013 McArt et al.