Identifying Patients with Polycythemia Vera at Risk of Thrombosis after Hydroxyurea Initiation: The Polycythemia Vera-Advanced Integrated Models (PV-AIM) Project.

Patients with polycythemia vera (PV) are at significant risk of thromboembolic events (TE). The PV-AIM study used the Optum® de-identified Electronic Health Record dataset and machine learning to identify markers of TE in a real-world population. Data for 82,960 patients with PV were extracted: 3852 patients were treated with hydroxyurea (HU) only, while 130 patients were treated with HU and then changed to ruxolitinib (HU-ruxolitinib). For HU-alone patients, the annualized incidence rates (IR; per 100 patients) decreased from 8.7 (before HU) to 5.6 (during HU) but increased markedly to 10.5 (continuing HU). Whereas for HU-ruxolitinib patients, the IR decreased from 10.8 (before HU) to 8.4 (during HU) and was maintained at 8.3 (after switching to ruxolitinib). To better understand markers associated with TE risk, we built a machine-learning model for HU-alone patients and validated it using an independent dataset. The model identified lymphocyte percentage (LYP), neutrophil percentage (NEP), and red cell distribution width (RDW) as key markers of TE risk, and optimal thresholds for these markers were established, from which a decision tree was derived. Using these widely used laboratory markers, the decision tree could be used to identify patients at high risk for TE, facilitate treatment decisions, and optimize patient management.

Extensive rewiring of the EGFR network in colorectal cancer cells expressing transforming levels of KRASG13D.

Protein-protein-interaction networks (PPINs) organize fundamental biological processes, but how oncogenic mutations impact these interactions and their functions at a network-level scale is poorly understood. Here, we analyze how a common oncogenic KRAS mutation (KRASG13D) affects PPIN structure and function of the Epidermal Growth Factor Receptor (EGFR) network in colorectal cancer (CRC) cells. Mapping >6000 PPIs shows that this network is extensively rewired in cells expressing transforming levels of KRASG13D (mtKRAS). The factors driving PPIN rewiring are multifactorial including changes in protein expression and phosphorylation. Mathematical modelling also suggests that the binding dynamics of low and high affinity KRAS interactors contribute to rewiring. PPIN rewiring substantially alters the composition of protein complexes, signal flow, transcriptional regulation, and cellular phenotype. These changes are validated by targeted and global experimental analysis. Importantly, genetic alterations in the most extensively rewired PPIN nodes occur frequently in CRC and are prognostic of poor patient outcomes.

Expression Quantitative Trait Loci in Equine Skeletal Muscle Reveals Heritable Variation in Metabolism and the Training Responsive Transcriptome.

While over ten thousand genetic loci have been associated with phenotypic traits and inherited diseases in genome-wide association studies, in most cases only a relatively small proportion of the trait heritability is explained and biological mechanisms underpinning these traits have not been clearly identified. Expression quantitative trait loci (eQTL) are subsets of genomic loci shown experimentally to influence gene expression. Since gene expression is one of the primary determinants of phenotype, the identification of eQTL may reveal biologically relevant loci and provide functional links between genomic variants, gene expression and ultimately phenotype. Skeletal muscle (gluteus medius) gene expression was quantified by RNA-seq for 111 Thoroughbreds (47 male, 64 female) in race training at a single training establishment sampled at two time-points: at rest (n = 92) and four hours after high-intensity exercise (n = 77); n = 60 were sampled at both time points. Genotypes were generated from the Illumina Equine SNP70 BeadChip. Applying a False Discovery Rate (FDR) corrected P-value threshold (P FDR < 0.05), association tests identified 3,583 cis-eQTL associated with expression of 1,456 genes at rest; 4,992 cis-eQTL associated with the expression of 1,922 genes post-exercise; 1,703 trans-eQTL associated with 563 genes at rest; and 1,219 trans-eQTL associated with 425 genes post-exercise. The gene with the highest cis-eQTL association at both time-points was the endosome-associated-trafficking regulator 1 gene (ENTR1; Rest: P FDR = 3.81 × 10-27, Post-exercise: P FDR = 1.66 × 10-24), which has a potential role in the transcriptional regulation of the solute carrier family 2 member 1 glucose transporter protein (SLC2A1). Functional analysis of genes with significant eQTL revealed significant enrichment for cofactor metabolic processes. These results suggest heritable variation in genomic elements such as regulatory sequences (e.g. gene promoters, enhancers, silencers), microRNA and transcription factor genes, which are associated with metabolic function and may have roles in determining end-point muscle and athletic performance phenotypes in Thoroughbred horses. The incorporation of the eQTL identified with genome and transcriptome-wide association may reveal useful biological links between genetic variants and their impact on traits of interest, such as elite racing performance and adaptation to training.

Refinement of Global Domestic Horse Biogeography Using Historic Landrace Chinese Mongolian Populations.

The Mongolian horse is one of the oldest extant horse populations and although domesticated, most animals are free-ranging and experience minimal human intervention. As an ancient population originating in one of the key domestication centers, the Mongolian horse may play a key role in understanding the origins and recent evolutionary history of horses. Here we describe an analysis of high-density genome-wide single-nucleotide polymorphism (SNP) data in 40 globally dispersed horse populations (n = 895). In particular, we have focused on new results from Chinese Mongolian horses (n = 100) that represent 5 distinct populations. These animals were genotyped for 670K SNPs and the data were analyzed in conjunction with 35K SNP data for 35 distinct breeds. Analyses of these integrated SNP data sets demonstrated that the Chinese Mongolian populations were genetically distinct from other modern horse populations. In addition, compared to other domestic horse breeds, the Chinese Mongolian horse populations exhibited relatively high genomic diversity. These results suggest that, in genetic terms, extant Chinese Mongolian horses may be the most similar modern populations to the animals originally domesticated in this region of Asia. Chinese Mongolian horse populations may therefore retain ancestral genetic variants from the earliest domesticates. Further genomic characterization of these populations in conjunction with archaeogenetic sequence data should be prioritized for understanding recent horse evolution and the domestication process that has led to the wealth of diversity observed in modern global horse breeds.

A comparative analysis of the transcriptome profiles of liver and muscle tissue in pigs divergent for feed efficiency.

BACKGROUND: The improvement of feed efficiency is a key economic goal within the pig production industry. The objective of this study was to examine transcriptomic differences in both the liver and muscle of pigs divergent for feed efficiency, thus improving our understanding of the molecular mechanisms influencing feed efficiency and enabling the identification of candidate biomarkers. Residual feed intake (RFI) was calculated for two populations of pigs from two different farms of origin/genotype. The 6 most efficient (LRFI) and 6 least efficient (HRFI) animals from each population were selected for further analysis of Longissimus Dorsi muscle (n = 22) and liver (n = 23). Transcriptomic data were generated from liver and muscle collected post-slaughter. RESULTS: The transcriptomic data segregated based on the RFI value of the pig rather than genotype/farm of origin. A total of 6463 genes were identified as being differentially expressed (DE) in muscle, while 964 genes were identified as being DE in liver. Genes that were commonly DE between muscle and liver (n = 526) were used for the multi-tissue analysis. These 526 genes were associated with protein targeting to membrane, extracellular matrix organisation and immune function. In the muscle-only analysis, genes associated with RNA processing, protein synthesis and energy metabolism were down regulated in the LRFI animals while in the liver-only analysis, genes associated with cell signalling and lipid homeostasis were up regulated in the LRFI animals. CONCLUSIONS: Differences in the transcriptome segregated on pig RFI value rather than the genotype/farm of origin. Multi-tissue analysis identified that genes associated with GO terms protein targeting to membrane, extracellular matrix organisation and a range of terms relating to immune function were over represented in the differentially expressed genes of both liver and muscle.

Interactome analysis of transforming growth factor-ß-activated kinase 1 in Helicobacter pylori-infected cells revealed novel regulators tripartite motif 28 and CDC37.

Transforming growth factor-ß (TGFß)-activated kinase 1 (TAK1) plays a central role in controlling the cellular pro-inflammatory response via the activation of the nuclear factor κB (NF-κB)- and mitogen-activated protein (MAP) kinases-dependent transcriptional programs. Here, we show that depletion of TAK1 and the TAK1-binding proteins TAB1 and TAB2 affects NF-κB, JNK and p38 phosphorylation and suppresses NF-κB activity in AGS cells infected with Helicobacter pylori or stimulated with the cytokines TNF and IL-1ß. To increase our understanding of TAK1 regulation and function, we performed mass spectrometry (MS)-based TAK1 interactomics. In addition to the identification of known and novel TAK1 interacting proteins, including TRIM28, CDC37 and STOML2, analysis of the MS data revealed various post-translational modifications within the TAK1/TAB complex. By applying siRNAs, TRIM28 and CDC37 were found to regulate phosphorylations of TAK1, IκB kinases IKKα/IKKß and MAP kinases, NF-κB transactivation activity and IL-8 expression in the infected epithelial cells.

Equine skeletal muscle adaptations to exercise and training: evidence of differential regulation of autophagosomal and mitochondrial components.

BACKGROUND: A single bout of exercise induces changes in gene expression in skeletal muscle. Regular exercise results in an adaptive response involving changes in muscle architecture and biochemistry, and is an effective way to manage and prevent common human diseases such as obesity, cardiovascular disorders and type II diabetes. However, the biomolecular mechanisms underlying such responses still need to be fully elucidated. Here we performed a transcriptome-wide analysis of skeletal muscle tissue in a large cohort of untrained Thoroughbred horses (n = 51) before and after a bout of high-intensity exercise and again after an extended period of training. We hypothesized that regular high-intensity exercise training primes the transcriptome for the demands of high-intensity exercise. RESULTS: An extensive set of genes was observed to be significantly differentially regulated in response to a single bout of high-intensity exercise in the untrained cohort (3241 genes) and following multiple bouts of high-intensity exercise training over a six-month period (3405 genes). Approximately one-third of these genes (1025) and several biological processes related to energy metabolism were common to both the exercise and training responses. We then developed a novel network-based computational analysis pipeline to test the hypothesis that these transcriptional changes also influence the contextual molecular interactome and its dynamics in response to exercise and training. The contextual network analysis identified several important hub genes, including the autophagosomal-related gene GABARAPL1, and dynamic functional modules, including those enriched for mitochondrial respiratory chain complexes I and V, that were differentially regulated and had their putative interactions 're-wired' in the exercise and/or training responses. CONCLUSION: Here we have generated for the first time, a comprehensive set of genes that are differentially expressed in Thoroughbred skeletal muscle in response to both exercise and training. These data indicate that consecutive bouts of high-intensity exercise result in a priming of the skeletal muscle transcriptome for the demands of the next exercise bout. Furthermore, this may also lead to an extensive 're-wiring' of the molecular interactome in both exercise and training and include key genes and functional modules related to autophagy and the mitochondrion.

Contextual Hub Analysis Tool (CHAT): A Cytoscape app for identifying contextually relevant hubs in biological networks.

Highly connected nodes (hubs) in biological networks are topologically important to the structure of the network and have also been shown to be preferentially associated with a range of phenotypes of interest. The relative importance of a hub node, however, can change depending on the biological context. Here, we report a Cytoscape app, the Contextual Hub Analysis Tool (CHAT), which enables users to easily construct and visualize a network of interactions from a gene list of interest, integrate contextual information, such as gene expression data, and identify hub nodes that are more highly connected to contextual nodes (e.g. genes that are differentially expressed) than expected by chance. In a case study, we use CHAT to construct a network of genes that are differentially expressed in Dengue fever, a viral infection. CHAT was used to identify and compare contextual and degree-based hubs in this network. The top 20 degree-based hubs were enriched in pathways related to the cell cycle and cancer, which is likely due to the fact that proteins involved in these processes tend to be highly connected in general. In comparison, the top 20 contextual hubs were enriched in pathways commonly observed in a viral infection including pathways related to the immune response to viral infection. This analysis shows that such contextual hubs are considerably more biologically relevant than degree-based hubs and that analyses which rely on the identification of hubs solely based on their connectivity may be biased towards nodes that are highly connected in general rather than in the specific context of interest. AVAILABILITY: CHAT is available for Cytoscape 3.0+ and can be installed via the Cytoscape App Store (http://apps.cytoscape.org/apps/chat).

DyNet: visualization and analysis of dynamic molecular interaction networks.

UNLABELLED: : The ability to experimentally determine molecular interactions on an almost proteome-wide scale under different conditions is enabling researchers to move from static to dynamic network analysis, uncovering new insights into how interaction networks are physically rewired in response to different stimuli and in disease. Dynamic interaction data presents a special challenge in network biology. Here, we present DyNet, a Cytoscape application that provides a range of functionalities for the visualization, real-time synchronization and analysis of large multi-state dynamic molecular interaction networks enabling users to quickly identify and analyze the most 'rewired' nodes across many network states. AVAILABILITY AND IMPLEMENTATION: DyNet is available at the Cytoscape (3.2+) App Store (http://apps.cytoscape.org/apps/dynet). CONTACT: david.lynn@sahmri.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Using biological networks to integrate, visualize and analyze genomics data.

Network biology is a rapidly developing area of biomedical research and reflects the current view that complex phenotypes, such as disease susceptibility, are not the result of single gene mutations that act in isolation but are rather due to the perturbation of a gene's network context. Understanding the topology of these molecular interaction networks and identifying the molecules that play central roles in their structure and regulation is a key to understanding complex systems. The falling cost of next-generation sequencing is now enabling researchers to routinely catalogue the molecular components of these networks at a genome-wide scale and over a large number of different conditions. In this review, we describe how to use publicly available bioinformatics tools to integrate genome-wide 'omics' data into a network of experimentally-supported molecular interactions. In addition, we describe how to visualize and analyze these networks to identify topological features of likely functional relevance, including network hubs, bottlenecks and modules. We show that network biology provides a powerful conceptual approach to integrate and find patterns in genome-wide genomic data but we also discuss the limitations and caveats of these methods, of which researchers adopting these methods must remain aware.

HiQuant: Rapid Postquantification Analysis of Large-Scale MS-Generated Proteomics Data.

Recent advances in mass-spectrometry-based proteomics are now facilitating ambitious large-scale investigations of the spatial and temporal dynamics of the proteome; however, the increasing size and complexity of these data sets is overwhelming current downstream computational methods, specifically those that support the postquantification analysis pipeline. Here we present HiQuant, a novel application that enables the design and execution of a postquantification workflow, including common data-processing steps, such as assay normalization and grouping, and experimental replicate quality control and statistical analysis. HiQuant also enables the interpretation of results generated from large-scale data sets by supporting interactive heatmap analysis and also the direct export to Cytoscape and Gephi, two leading network analysis platforms. HiQuant may be run via a user-friendly graphical interface and also supports complete one-touch automation via a command-line mode. We evaluate HiQuant's performance by analyzing a large-scale, complex interactome mapping data set and demonstrate a 200-fold improvement in the execution time over current methods. We also demonstrate HiQuant's general utility by analyzing proteome-wide quantification data generated from both a large-scale public tyrosine kinase siRNA knock-down study and an in-house investigation into the temporal dynamics of the KSR1 and KSR2 interactomes. Download HiQuant, sample data sets, and supporting documentation at http://hiquant.primesdb.eu .

CerebralWeb: a Cytoscape.js plug-in to visualize networks stratified by subcellular localization.

CerebralWeb is a light-weight JavaScript plug-in that extends Cytoscape.js to enable fast and interactive visualization of molecular interaction networks stratified based on subcellular localization or other user-supplied annotation. The application is designed to be easily integrated into any website and is configurable to support customized network visualization. CerebralWeb also supports the automatic retrieval of Cerebral-compatible localizations for human, mouse and bovine genes via a web service and enables the automated parsing of Cytoscape compatible XGMML network files. CerebralWeb currently supports embedded network visualization on the InnateDB (www.innatedb.com) and Allergy and Asthma Portal (allergen.innatedb.com) database and analysis resources. Database tool URL: http://www.innatedb.com/CerebralWeb

MicroRNA profiling of the bovine alveolar macrophage response to Mycobacterium bovis infection suggests pathogen survival is enhanced by microRNA regulation of endocytosis and lysosome trafficking.

Mycobacterium bovis, the causative agent of bovine tuberculosis, a major problem for global agriculture, spreads via an airborne route and is taken up by alveolar macrophages (AM) in the lung. Here, we describe the first next-generation sequencing (RNA-seq) approach to temporally profile miRNA expression in primary bovine AMs post-infection with M. bovis. One, six, and forty miRNAs were identified as significantly differentially expressed at 2, 24 and 48 h post-infection, respectively. The differential expression of three miRNAs (bta-miR-142-5p, bta-miR-146a, and bta-miR-423-3p) was confirmed by RT-qPCR. Pathway analysis of the predicted mRNA targets of differentially expressed miRNAs suggests that these miRNAs preferentially target several pathways that are functionally relevant for mycobacterial pathogenesis, including endocytosis and lysosome trafficking, IL-1 signalling and the TGF-ß pathway. Over-expression studies using a bovine macrophage cell-line (Bomac) reveal the targeting of two key genes in the innate immune response to M. bovis, IL-1 receptor-associated kinase 1 (IRAK1) and TGF-ß receptor 2 (TGFBR2), by miR-146. Taken together, our study suggests that miRNAs play a key role in tuning the complex interplay between M. bovis survival strategies and the host immune response.

Differential DNA methylation profiles of coding and non-coding genes define hippocampal sclerosis in human temporal lobe epilepsy.

Temporal lobe epilepsy is associated with large-scale, wide-ranging changes in gene expression in the hippocampus. Epigenetic changes to DNA are attractive mechanisms to explain the sustained hyperexcitability of chronic epilepsy. Here, through methylation analysis of all annotated C-phosphate-G islands and promoter regions in the human genome, we report a pilot study of the methylation profiles of temporal lobe epilepsy with or without hippocampal sclerosis. Furthermore, by comparative analysis of expression and promoter methylation, we identify methylation sensitive non-coding RNA in human temporal lobe epilepsy. A total of 146 protein-coding genes exhibited altered DNA methylation in temporal lobe epilepsy hippocampus (n = 9) when compared to control (n = 5), with 81.5% of the promoters of these genes displaying hypermethylation. Unique methylation profiles were evident in temporal lobe epilepsy with or without hippocampal sclerosis, in addition to a common methylation profile regardless of pathology grade. Gene ontology terms associated with development, neuron remodelling and neuron maturation were over-represented in the methylation profile of Watson Grade 1 samples (mild hippocampal sclerosis). In addition to genes associated with neuronal, neurotransmitter/synaptic transmission and cell death functions, differential hypermethylation of genes associated with transcriptional regulation was evident in temporal lobe epilepsy, but overall few genes previously associated with epilepsy were among the differentially methylated. Finally, a panel of 13, methylation-sensitive microRNA were identified in temporal lobe epilepsy including MIR27A, miR-193a-5p (MIR193A) and miR-876-3p (MIR876), and the differential methylation of long non-coding RNA documented for the first time. The present study therefore reports select, genome-wide DNA methylation changes in human temporal lobe epilepsy that may contribute to the molecular architecture of the epileptic brain.

MicroRNA regulation of bovine monocyte inflammatory and metabolic networks in an in vivo infection model.

Bovine mastitis is an inflammation-driven disease of the bovine mammary gland that costs the global dairy industry several billion dollars per year. Because disease susceptibility is a multifactorial complex phenotype, an integrative biology approach is required to dissect the molecular networks involved. Here, we report such an approach using next-generation sequencing combined with advanced network and pathway biology methods to simultaneously profile mRNA and miRNA expression at multiple time points (0, 12, 24, 36 and 48 hr) in milk and blood FACS-isolated CD14(+) monocytes from animals infected in vivo with Streptococcus uberis. More than 3700 differentially expressed (DE) genes were identified in milk-isolated monocytes (MIMs), a key immune cell recruited to the site of infection during mastitis. Upregulated genes were significantly enriched for inflammatory pathways, whereas downregulated genes were enriched for nonglycolytic metabolic pathways. Monocyte transcriptional changes in the blood, however, were more subtle but highlighted the impact of this infection systemically. Genes upregulated in blood-isolated monocytes (BIMs) showed a significant association with interferon and chemokine signaling. Furthermore, 26 miRNAs were DE in MIMs and three were DE in BIMs. Pathway analysis revealed that predicted targets of downregulated miRNAs were highly enriched for roles in innate immunity (FDR < 3.4E-8), particularly TLR signaling, whereas upregulated miRNAs preferentially targeted genes involved in metabolism. We conclude that during S. uberis infection miRNAs are key amplifiers of monocyte inflammatory response networks and repressors of several metabolic pathways.

Discovery and visualization of miRNA-mRNA functional modules within integrated data using bicluster analysis.

MicroRNAs (miRNAs) are small non-coding RNA molecules that regulate gene expression at a post-transcriptional level. An miRNA may target many messenger RNA (mRNA) transcripts, and each transcript may be targeted by multiple miRNAs. Our understanding of miRNA regulation is evolving to consider modules of miRNAs that regulate groups of functionally related mRNAs. Here we expand the model of miRNA functional modules and use it to guide the integration of miRNA and mRNA expression and target prediction data. We present evidence of cooperativity between miRNA classes within this integrated miRNA-mRNA association matrix. We then apply bicluster analysis to uncover miRNA functional modules within this integrated data set and develop a novel application to visualize and query these results. We show that this wholly unsupervised approach can discover a network of miRNA-mRNA modules that are enriched for both biological processes and miRNA classes. We apply this method to investigate the interplay of miRNAs and mRNAs in integrated data sets derived from neuroblastoma and human immune cells. This study is the first to apply the technique of biclustering to model functional modules within an integrated miRNA-mRNA association matrix. Results provide evidence of an extensive modular miRNA functional network and enable characterization of miRNA function and dysregulation in disease.

Post-transcriptional dysregulation by miRNAs is implicated in the pathogenesis of gastrointestinal stromal tumor [GIST].

In contrast to adult mutant gastrointestinal stromal tumors [GISTs], pediatric/wild-type GISTs remain poorly understood overall, given their lack of oncogenic activating tyrosine kinase mutations. These GISTs, with a predilection for gastric origin in female patients, show limited response to therapy with tyrosine kinase inhibitors and generally pursue a more indolent course, but still may prove fatal. Defective cellular respiration appears to underpin tumor development in these wild-type cases, which as a group lack expression of succinate dehydrogenase [SDH] B, a surrogate marker for respiratory chain metabolism. Yet, only a small subset of the wild-type tumors show mutations in the genes coding for the SDH subunits [SDHx]. To explore additional pathogenetic mechanisms in these wild-type GISTs, we elected to investigate post-transcriptional regulation of these tumors by conducting microRNA (miRNA) profiling of a mixed cohort of 73 cases including 18 gastric pediatric wild-type, 25 (20 gastric, 4 small bowel and 1 retroperitoneal) adult wild-type GISTs and 30 gastric adult mutant GISTs. By this approach we have identified distinct signatures for GIST subtypes which correlate tightly with clinico-pathological parameters. A cluster of miRNAs on 14q32 show strikingly different expression patterns amongst GISTs, a finding which appears to be explained at least in part by differential allelic methylation of this imprinted region. Small bowel and retroperitoneal wild-type GISTs segregate with adult mutant GISTs and express SDHB, while adult wild-type gastric GISTs are dispersed amongst adult mutant and pediatric wild-type cases, clustering in this situation on the basis of SDHB expression. Interestingly, global methylation analysis has recently similarly demonstrated that these wild-type, SDHB-immunonegative tumors show a distinct pattern compared with KIT and PDGFRA mutant tumors, which as a rule do express SDHB. All cases with Carney triad within our cohort cluster together tightly.

Expressional alterations in functional ultra-conserved non-coding RNAs in response to all-trans retinoic acid--induced differentiation in neuroblastoma cells.

BACKGROUND: Ultra-conserved regions (UCRs) are segments of the genome (≥ 200 bp) that exhibit 100% DNA sequence conservation between human, mouse and rat. Transcribed UCRs (T-UCRs) have been shown to be differentially expressed in cancers versus normal tissue, indicating a possible role in carcinogenesis. All-trans-retinoic acid (ATRA) causes some neuroblastoma (NB) cell lines to undergo differentiation and leads to a significant decrease in the oncogenic transcription factor MYCN. Here, we examine the impact of ATRA treatment on T-UCR expression and investigate the biological significance of these changes. METHODS: We designed a custom tiling microarray to profile the expression of 481 T-UCRs in sense and anti-sense orientation (962 potential transcripts) in untreated and ATRA-treated neuroblastoma cell lines (SH-SY5Y, SK-N-BE, LAN-5). Following identification of significantly differentially expressed T-UCRs, we carried out siRNA knockdown and gene expression microarray analysis to investigate putative functional roles for selected T-UCRs. RESULTS: Following ATRA-induced differentiation, 32 T-UCRs were differentially expressed (16 up-regulated, 16 down-regulated) across all three cell lines. Further insight into the possible role of T-UC.300A, an independent transcript whose expression is down-regulated following ATRA was achieved by siRNA knockdown, resulting in the decreased viability and invasiveness of ATRA-responsive cell lines. Gene expression microarray analysis following knockdown of T-UC.300A revealed a number of genes whose expression was altered by changing T-UC.300A levels and that might play a role in the increased proliferation and invasion of NB cells prior to ATRA-treatment. CONCLUSIONS: Our results indicate that significant numbers of T-UCRs have altered expression levels in response to ATRA. While the precise roles that T-UCRs might play in cancer or in normal development are largely unknown and an important area for future study, our findings strongly indicate that the function of non-coding RNA T-UC.300A is connected with proliferation, invasion and the inhibition of differentiation of neuroblastoma cell lines prior to ATRA treatment.

MiR-137 functions as a tumor suppressor in neuroblastoma by downregulating KDM1A.

Neuroblastoma is the most common extracranial solid tumor of childhood, and accounts for ∼15% of all childhood cancer deaths. The histone demethylase, lysine-specific demethylase 1 (KDM1A, previously known as LSD1), is strongly expressed in neuroblastomas, and overexpression correlates with poor patient prognosis. Inducing differentiation in neuroblastoma cells has previously been shown to down regulate KDM1A, and siRNA-mediated KDM1A knockdown inhibited neuroblastoma cell viability. The microRNA, miR-137, has been reported to be downregulated in several human cancers, and KDM1A mRNA was reported as a putative target of miR-137 in colon cancer. We hypothesized that miR-137 might have a tumor-suppressive role in neuroblastoma mediated via downregulation of KDM1A. Indeed, low levels of miR-137 expression in primary neuroblastomas correlated with poor patient prognosis. Re-expressing miR-137 in neuroblastoma cell lines increased apoptosis and decreased cell viability and proliferation. KDM1A mRNA was repressed by miR-137 in neuroblastoma cells, and was validated as a direct target of miR-137 using reporter assays in SHEP and HEK293 cells. Furthermore, siRNA-mediated KDM1A knockdown phenocopied the miR-137 re-expression phenotype in neuroblastoma cells. We conclude that miR-137 directly targets KDM1A mRNA in neuroblastoma cells, and activates cell properties consistent with tumor suppression. Therapeutic strategies to re-express miR-137 in neuroblastomas could be useful to reduce tumor aggressiveness.

miRNA profiles as a predictor of chemoresponsiveness in Wilms' tumor blastema.

The current SIOP treatment protocol for Wilms' tumor involves pre-operative chemotherapy followed by nephrectomy. Not all patients benefit equally from such chemotherapy. The aim of this study was to generate a miRNA profile of chemo resistant blastemal cells in high risk Wilms' tumors which might serve as predictive markers of therapeutic response at the pre-treatment biopsy stage. We have shown here that unsupervised hierarchical clustering of genome-wide miRNA expression profiles can clearly separate intermediate risk tumors from high risk tumors. A total of 29 miRNAs were significantly differentially expressed between post-treatment intermediate risk and high risk groups, including miRNAs that have been previously linked to chemo resistance in other cancer types. Furthermore, 7 of these 29 miRNAs were already at the pre-treatment biopsy stage differentially expressed between cases ultimately deemed intermediate risk compared to high risk. These miRNA alterations include down-regulation in high risk cases of miR-193a.5p, miR-27a and the up-regulation of miR-483.5p, miR-628.5p, miR-590.5p, miR-302a and miR-367. The demonstration of such miRNA markers at the pre-treatment biopsy stage could permit stratification of patients to more tailored treatment regimens.