Network assessment of demethylation treatment in melanoma: Differential transcriptome-methylome and antigen profile signatures.

BACKGROUND: In melanoma, like in other cancers, both genetic alterations and epigenetic underlie the metastatic process. These effects are usually measured by changes in both methylome and transcriptome profiles, whose cross-correlation remains uncertain. We aimed to assess at systems scale the significance of epigenetic treatment in melanoma cells with different metastatic potential. METHODS AND FINDINGS: Treatment by DAC demethylation with 5-Aza-2'-deoxycytidine of two melanoma cell lines endowed with different metastatic potential, SKMEL-2 and HS294T, was performed and high-throughput coupled RNA-Seq and RRBS-Seq experiments delivered differential profiles (DiP) of both transcriptomes and methylomes. Methylation levels measured at both TSS and gene body were studied to inspect correlated patterns with wide-spectrum transcript abundance levels quantified in both protein coding and non-coding RNA (ncRNA) regions. The DiP were then mapped onto standard bio-annotation sources (pathways, biological processes) and network configurations were obtained. The prioritized associations for target identification purposes were expected to elucidate the reprogramming dynamics induced by the epigenetic therapy. The interactomic connectivity maps of each cell line were formed to support the analysis of epigenetically re-activated genes. i.e. those supposedly silenced by melanoma. In particular, modular protein interaction networks (PIN) were used, evidencing a limited number of shared annotations, with an example being MAPK13 (cascade of cellular responses evoked by extracellular stimuli). This gene is also a target associated to the PANDAR ncRNA, therapeutically relevant because of its aberrant expression observed in various cancers. Overall, the non-metastatic SKMEL-2 map reveals post-treatment re-activation of a richer pathway landscape, involving cadherins and integrins as signatures of cell adhesion and proliferation. Relatively more lncRNAs were also annotated, indicating more complex regulation patterns in view of target identification. Finally, the antigen maps matched to DiP display other differential signatures with respect to the metastatic potential of the cell lines. In particular, as demethylated melanomas show connected targets that grow with the increased metastatic potential, also the potential target actionability seems to depend to some degree on the metastatic state. However, caution is required when assessing the direct influence of re-activated genes over the identified targets. In light of the stronger treatment effects observed in non-metastatic conditions, some limitations likely refer to in silico data integration tools and resources available for the analysis of tumor antigens. CONCLUSION: Demethylation treatment strongly affects early melanoma progression by re-activating many genes. This evidence suggests that the efficacy of this type of therapeutic intervention is potentially high at the pre-metastatic stages. The biomarkers that can be assessed through antigens seem informative depending on the metastatic conditions, and networks help to elucidate the assessment of possible targets actionability.

Emerging Putative Associations between Non-Coding RNAs and Protein-Coding Genes in Neuropathic Pain: Added Value from Reusing Microarray Data.

Regeneration of injured nerves is likely occurring in the peripheral nervous system, but not in the central nervous system. Although protein-coding gene expression has been assessed during nerve regeneration, little is currently known about the role of non-coding RNAs (ncRNAs). This leaves open questions about the potential effects of ncRNAs at transcriptome level. Due to the limited availability of human neuropathic pain (NP) data, we have identified the most comprehensive time-course gene expression profile referred to sciatic nerve (SN) injury and studied in a rat model using two neuronal tissues, namely dorsal root ganglion (DRG) and SN. We have developed a methodology to identify differentially expressed bioentities starting from microarray probes and repurposing them to annotate ncRNAs, while analyzing the expression profiles of protein-coding genes. The approach is designed to reuse microarray data and perform first profiling and then meta-analysis through three main steps. First, we used contextual analysis to identify what we considered putative or potential protein-coding targets for selected ncRNAs. Relevance was therefore assigned to differential expression of neighbor protein-coding genes, with neighborhood defined by a fixed genomic distance from long or antisense ncRNA loci, and of parental genes associated with pseudogenes. Second, connectivity among putative targets was used to build networks, in turn useful to conduct inference at interactomic scale. Last, network paths were annotated to assess relevance to NP. We found significant differential expression in long-intergenic ncRNAs (32 lincRNAs in SN and 8 in DRG), antisense RNA (31 asRNA in SN and 12 in DRG), and pseudogenes (456 in SN and 56 in DRG). In particular, contextual analysis centered on pseudogenes revealed some targets with known association to neurodegeneration and/or neurogenesis processes. While modules of the olfactory receptors were clearly identified in protein-protein interaction networks, other connectivity paths were identified between proteins already investigated in studies on disorders, such as Parkinson, Down syndrome, Huntington disease, and Alzheimer. Our findings suggest the importance of reusing gene expression data by meta-analysis approaches.

Non-coding RNAs profiling in head and neck cancers.

The majority of studies on human cancers published to date focus on coding genes. More recently, however, non-coding RNAs (ncRNAs) are gaining growing recognition as important regulatory components. Here we characterise the ncRNA landscape in 442 head and neck squamous cell carcinomas (HNSCs) from the cancer genome atlas (TCGA). HNSCs represent an intriguing case to study the potential role of ncRNA as a function of viral presence, especially as HPV is potentially oncogenic. Thus, we identify HPV16-positive (HPV16+) and HPV-negative (HPV-) tumours and study the expression of ncRNAs on both groups. Overall, the ncRNAs comprise 36% of all differentially expressed genes, with antisense RNAs being the most represented ncRNA type (12.6%). Protein-coding genes appear to be more frequently downregulated in tumours compared with controls, whereas ncRNAs show significant upregulation in tumours, especially in HPV16+ tumours. Overall, expression of pseudogenes, antisense and short RNAs is elevated in HPV16+ tumours, while the remaining long non-coding RNA types are more active in all HNSC tumours independent of HPV status. In addition, we identify putative regulatory targets of differentially expressed ncRNAs. Among these 'targets' we find several well-established oncogenes, tumour suppressors, cytokines, growth factors and cell differentiation genes, which indicates the potential involvement of ncRNA in the control of these key regulators as a direct consequence of HPV oncogenic activity. In conclusion, our findings establish the ncRNAs as crucial transcriptional components in HNSCs. Our results display the great potential for the study of ncRNAs and the role they have in human cancers.

Identification of potential therapeutic targets in a model of neuropathic pain.

Neuropathic pain (NP) is caused by damage to the nervous system, resulting in dysfunction and aberrant pain. The cellular functions (e.g., peripheral neuron spinal cord innervation, neuronal excitability) associated with NP often develop over time and are likely associated with gene expression changes. Gene expression studies on the cells involved in NP (e.g., sensory dorsal root ganglion neurons) are publically available; the mining of these studies may enable the identification of novel targets and the subsequent development of therapies that are essential for improving quality of life for the millions of individuals suffering with NP. Here we analyzed a publically available microarray dataset (GSE30165) in order to identify new RNAs (e.g., messenger RNA (mRNA) isoforms and non-coding RNAs) underlying NP. GSE30165 profiled gene expression in dorsal root ganglion neurons (DRG) and in sciatic nerve (SN) after resection, a NP model. Gene ontological analysis shows enrichment for sensory and neuronal processes. Protein network analysis demonstrates DRG upregulated genes typical to an injury and NP response. Of the top changing genes, 34 and 36% are associated with more than one protein coding isoform in the DRG and SN, respectively. The majority of genes are receptor and enzymes. We identified 15 long non-coding RNAs (lncRNAs) targeting these genes in LNCipedia.org, an online comprehensive lncRNA database. These RNAs represent new therapeutic targets for preventing NP development and this approach demonstrates the feasibility of data reanalysis for their identification.

Comparative analysis of genome sequences from four strains of the Buchnera aphidicola Mp endosymbion of the green peach aphid, Myzus persicae.

BACKGROUND: Myzus persicae, the green peach aphid, is a polyphagous herbivore that feeds from hundreds of species of mostly dicot crop plants. Like other phloem-feeding aphids, M. persicae rely on the endosymbiotic bacterium, Buchnera aphidicola (Buchnera Mp), for biosynthesis of essential amino acids and other nutrients that are not sufficiently abundant in their phloem sap diet. Tobacco-specialized M. persicae are typically red and somewhat distinct from other lineages of this species. To determine whether the endosymbiotic bacteria of M. persicae could play a role in tobacco adaptation, we sequenced the Buchnera Mp genomes from two tobacco-adapted and two non-tobacco M. persicae lineages. RESULTS: With a genome size of 643.5 kb and 579 predicted genes, Buchnera Mp is the largest Buchnera genome sequenced to date. No differences in gene content were found between the four sequenced Buchnera Mp strains. Compared to Buchnera APS from the well-studied pea aphid, Acyrthosiphon pisum, Buchnera Mp has 21 additional genes. These include genes encoding five enzymes required for biosynthesis of the modified nucleoside queosine, the heme pathway enzyme uroporphyrinogen III synthase, and asparaginase. Asparaginase, which is also encoded by the genome of the aphid host, may allow Buchnera Mp to synthesize essential amino acids from asparagine, a relatively abundant phloem amino acid. CONCLUSIONS: Together our results indicate that the obligate intracellular symbiont Buchnera aphidicola does not contribute to the adaptation of Myzus persicae to feeding on tobacco.

MicroRNA-20a constrains p300-driven myocardial angiogenic transcription by direct targeting of p300.

OBJECTIVE: To characterize downstream effectors of p300 acetyltransferase in the myocardium. BACKGROUND: Acetyltransferase p300 is a central driver of the hypertrophic response to increased workload, but its biological targets and downstream effectors are incompletely known. METHODS AND RESULTS: Mice expressing a myocyte-restricted transgene encoding acetyltransferase p300, previously shown to develop spontaneous hypertrophy, were observed to undergo robust compensatory blood vessel growth together with increased angiogenic gene expression. Chromatin immunoprecipitation demonstrated binding of p300 to the enhancers of the angiogenic regulators Angpt1 and Egln3. Interestingly, p300 overexpression in vivo was also associated with relative upregulation of several members of the anti-angiogenic miR-17∼92 cluster in vivo. Confirming this finding, both miR-17-3p and miR-20a were upregulated in neonatal rat ventricular myocytes following adenoviral transduction of p300. Relative expression of most members of the 17∼92 cluster was similar in all 4 cardiac chambers and in other organs, however, significant downregulation of miR-17-3p and miR-20a occurred between 1 and 8 months of age in both wt and tg mice. The decline in expression of these microRNAs was associated with increased expression of VEGFA, a validated miR-20a target. In addition, miR-20a was demonstrated to directly repress p300 expression through a consensus binding site in the p300 3'UTR. In vivo transduction of p300 resulted in repression both of p300 and of p300-induced angiogenic transcripts. CONCLUSION: p300 drives an angiogenic transcription program during hypertrophy that is fine-tuned in part through direct repression of p300 by miR-20a.

Viral expression associated with gastrointestinal adenocarcinomas in TCGA high-throughput sequencing data.

BACKGROUND: Up to 20% of cancers worldwide are thought to be associated with microbial pathogens, including bacteria and viruses. The widely used methods of viral infection detection are usually limited to a few a priori suspected viruses in one cancer type. To our knowledge, there have not been many broad screening approaches to address this problem more comprehensively. METHODS: In this study, we performed a comprehensive screening for viruses in nine common cancers using a multistep computational approach. Tumor transcriptome and genome sequencing data were available from The Cancer Genome Atlas (TCGA). Nine hundred fifty eight primary tumors in nine common cancers with poor prognosis were screened against a non-redundant database of virus sequences. DNA sequences from normal matched tissue specimens were used as controls to test whether each virus is associated with tumors. RESULTS: We identified human papilloma virus type 18 (HPV-18) and four human herpes viruses (HHV) types 4, 5, 6B, and 8, also known as EBV, CMV, roseola virus, and KSHV, in colon, rectal, and stomach adenocarcinomas. In total, 59% of screened gastrointestinal adenocarcinomas (GIA) were positive for at least one virus: 26% for EBV, 21% for CMV, 7% for HHV-6B, and 20% for HPV-18. Over 20% of tumors were co-infected with multiple viruses. Two viruses (EBV and CMV) were statistically significantly associated with colorectal cancers when compared to the matched healthy tissues from the same individuals (p = 0.02 and 0.03, respectively). HPV-18 was not detected in DNA, and thus, no association testing was possible. Nevertheless, HPV-18 expression patterns suggest viral integration in the host genome, consistent with the potentially oncogenic nature of HPV-18 in colorectal adenocarcinomas. The estimated counts of viral copies were below one per cell for all identified viruses and approached the detection limit. CONCLUSIONS: Our comprehensive screening for viruses in multiple cancer types using next-generation sequencing data clearly demonstrates the presence of viral sequences in GIA. EBV, CMV, and HPV-18 are potentially causal for GIA, although their oncogenic role is yet to be established.

A clinical evaluation tool for SNP arrays, especially for autosomal recessive conditions in offspring of consanguineous parents.

PURPOSE: This report describes a fast online tool to accelerate and improve clinical interpretation of single nucleotide polymorphism array results for diagnostic purposes, when consanguinity or inbreeding is identified. METHODS: We developed a web-based program that permits entry of regions of homozygosity and, using OMIM, UCSC, and NCBI databases, retrieves genes within these regions as well as their associated autosomal recessive disorders. Relevant OMIM Clinical Synopses can be searched, using key clinical terms permitting further filtering for candidate genes and disorders. RESULTS: The tool aids the clinician by arriving at a short list of relevant candidate disorders, guiding the continued diagnostic work-up. Its efficacy is illustrated by presenting seven patients who were diagnosed using this tool. CONCLUSION: The online single nucleotide polymorphism array evaluation tool rapidly and systematically identifies relevant genes and associated conditions mapping to identified regions of homozygosity. The built-in OMIM clinical feature search allows the user to further filter to reach a short list of candidate conditions relevant for the diagnosis, making it possible to strategize more focused diagnostic testing. The tabulated results can be downloaded and saved to the desktop in an Excel format. Its efficacy is illustrated by providing a few clinical examples.Genet Med 2013:15(5):354-360.

GenSensor Suite: A Web-Based Tool for the Analysis of Gene and Protein Interactions, Pathways, and Regulation.

The GenSensor Suite consists of four web tools for elucidating relationships among genes and proteins. GenPath results show which biochemical, regulatory, or other gene set categories are over- or under-represented in an input list compared to a background list. All common gene sets are available for searching in GenPath, plus some specialized sets. Users can add custom background lists. GenInteract builds an interaction gene list from a single gene input and then analyzes this in GenPath. GenPubMed uses a PubMed query to identify a list of PubMed IDs, from which a gene list is extracted and queried in GenPath. GenViewer allows the user to query one gene set against another in GenPath. GenPath results are presented with relevant P- and q-values in an uncluttered, fully linked, and integrated table. Users can easily copy this table and paste it directly into a spreadsheet or document.

Heterogeneity in SDF-1 expression defines the vasculogenic potential of adult cardiac progenitor cells.

RATIONALE: The adult myocardium has been reported to harbor several classes of multipotent progenitor cells (CPCs) with tri-lineage differentiation potential. It is not clear whether c-kit+CPCs represent a uniform precursor population or a more complex mixture of cell types. OBJECTIVE: To characterize and understand vasculogenic heterogeneity within c-kit+presumptive cardiac progenitor cell populations. METHODS AND RESULTS: c-kit+, sca-1+ CPCs obtained from adult mouse left ventricle expressed stem cell-associated genes, including Oct-4 and Myc, and were self-renewing, pluripotent and clonogenic. Detailed single cell clonal analysis of 17 clones revealed that most (14/17) exhibited trilineage differentiation potential. However, striking morphological differences were observed among clones that were heritable and stable in long-term culture. 3 major groups were identified: round (7/17), flat or spindle-shaped (5/17) and stellate (5/17). Stellate morphology was predictive of vasculogenic differentiation in Matrigel. Genome-wide expression studies and bioinformatic analysis revealed clonally stable, heritable differences in stromal cell-derived factor-1 (SDF-1) expression that correlated strongly with stellate morphology and vasculogenic capacity. Endogenous SDF-1 production contributed directly to vasculogenic differentiation: both shRNA-mediated knockdown of SDF-1 and AMD3100, an antagonist of the SDF-1 receptor CXC chemokine Receptor-4 (CXCR4), reduced tube-forming capacity, while exogenous SDF-1 induced tube formation by 2 non-vasculogenic clones. CPCs producing SDF-1 were able to vascularize Matrigel dermal implants in vivo, while CPCs with low SDF-1 production were not. CONCLUSIONS: Clonogenic c-kit+, sca-1+ CPCs are heterogeneous in morphology, gene expression patterns and differentiation potential. Clone-specific levels of SDF-1 expression both predict and promote development of a vasculogenic phenotype via a previously unreported autocrine mechanism.

Glucocorticoid receptor polymorphisms and intraocular pressure response to intravitreal triamcinolone acetonide.

BACKGROUND: Elevation of intraocular pressure (IOP) following injection of intravitreal triamcinolone acetonide (IVTA) is an important clinical problem. The etiology of the steroid response is poorly understood, although a genetic determinant has long been suspected. We performed a pharmacogenomic association study with glucocorticoid receptor polymorphisms. MATERIALS AND METHODS: Fifty-two patients (56 eyes) who underwent treatment with IVTA for various retinal diseases were genotyped for six well-studied glucocorticoid receptor polymorphisms (ER22/23EK, N363S, BclI, N766N, and single nucleotide polymorphisms (SNPs) within introns 3 and 4). RESULTS: Three polymorphisms (ER22/23EK, N363S, and the intron 3 SNP) were essentially nonpolymorphic within this population sample and excluded from further analysis. The remaining three polymorphisms (BclI, N766N, and within intron 4) passed the Hardy-Weinberg Equilibrium test, indicating good genotyping quality and normal population distribution of allelic frequency. No statistically significant correlations were found between these three polymorphisms and magnitude of IOP elevation following IVTA, using single point association and haplotype analyses. CONCLUSIONS: In this small, pilot study, we found no statistically significant relationship between glucocorticoid receptor polymorphisms and IOP elevation following IVTA. The precise etiology of the steroid response remains obscure. To our knowledge, this is the first published pharmacogenomic study of this common clinical entity.

Electronically subtracting expression patterns from a mixed cell population.

MOTIVATION: Biological samples frequently contain multiple cell-types that each can play a crucial role in the development and/or regulation of adjacent cells or tissues. The search for biomarkers, or expression patterns of, one cell-type in those samples can be a complex and time-consuming process. Ordinarily, extensive laboratory bench work must be performed to separate the mixed cell population into its subcomponents, such that each can be accurately characterized. RESULTS: We have developed a methodology to electronically subtract gene expression in one or more components of a mixed cell population from a mixture, to reveal the expression patterns of other minor or difficult to isolate components. Examination of simulated data indicates that this procedure can reliably determine the expression patterns in cell-types that contribute as little as 5% of the total expression in a mixed cell population. We re-analyzed microarray expression data from the viral infection of macrophages and from the T-cells of wild type and Foxp3 deletion mice. Using our subtraction methodology, we were able to substantially improve the identification of genes involved in processes of subcomponent portions of these samples.

A genome-wide study of lupus: preliminary analysis and data release.

Systemic lupus erythematosus (SLE) is a complex autoimmune disease in which genetics is one of the underlying risk factors. Complicating the analysis of SLE is the fact that the phenotype is heterogeneous, with variations in clinical features, and subgroups are associated with a variety of different autoantibodies. Many association studies of candidate genes as well as linkage studies have generated significant results, highlighting the multigenetic component of the disease. Those findings need to be replicated by independent laboratories and many other genes still remain to be identified. Here, we present our findings on the first genome-wide association study performed in 105 Caucasian patients and controls using the Affymetrix NspI array. The SLE patients studied here were all characterized by the presence of autoantibodies against the U1-6 small nuclear ribonucleoprotein antigen spliceosomal complex. Testing each SNP individually for association with disease, we identified 7 markers with an uncorrected P-value < 0.0001. Of those, three were in reported regions of linkage, namely 20p12, 2q37, and 4p15. To increase the power of our study, we included 60 controls corresponding to the parents from the publicly available CEPH families. The analysis of the 165 cases and controls leads to 28 SNPs being associated with an uncorrected P-value < 0.0001.

An integrated in silico gene mapping strategy in inbred mice.

In recent years in silico analysis of common laboratory mice has been introduced and subsequently applied, in slightly different ways, as a methodology for gene mapping. Previously we have demonstrated some limitation of the methodology due to sporadic genetic correlations across the genome. Here, we revisit the three main aspects that affect in silico analysis. First, we report on the use of marker maps: we compared our existing 20,000 SNP map to the newly released 140,000 SNP map. Second, we investigated the effect of varying strain numbers on power to map QTL. Third, we introduced a novel statistical approach: a cladistic analysis, which is well suited for mouse genetics and has increased flexibility over existing in silico approaches. We have found that in our examples of complex traits, in silico analysis by itself does fail to uniquely identify quantitative trait gene (QTG)-containing regions. However, when combined with additional information, it may significantly help to prioritize candidate genes. We therefore recommend using an integrated work flow that uses other genomic information such as linkage regions, regions of shared ancestry, and gene expression information to obtain a list of candidate genes from the genome.

A comprehensive mouse IBD database for the efficient localization of quantitative trait loci.

Traditional fine-mapping approaches in mouse genetics that go from a linkage region to a candidate gene are very costly and time consuming. Shared ancestry regions, along with the combination of genetics and genomics approaches, provide a powerful tool to shorten the time and effort required to identify a causative gene. In this article we present a novel methodology that predicts IBD (identical by descent) regions between pairs of inbred strains using single nucleotide polymorphism (SNP) maps. We have validated this approach by comparing the IBD regions, estimated using different algorithms, to the results derived using the sequence information in the strains present in the Celera Mouse Database. We showed that based on the current publicly available SNP genotypes, large IBD regions (>1 Mb) can be identified successfully. By assembling a list of 21,514 SNPs in 61 common inbred strains, we inferred IBD regions between all pairs of strains and confirmed, for the first time, that existing quantitative trait genes (QTG) and susceptibility genes all lie outside of IBD regions. We also illustrated how knowledge of IBD structures can be applied to strain selection for future crosses. We have made our results available for data mining and download through a public website ( http://www.mouseibd.florida.scripps.edu ).

A comprehensive transcript index of the human genome generated using microarrays and computational approaches.

BACKGROUND: Computational and microarray-based experimental approaches were used to generate a comprehensive transcript index for the human genome. Oligonucleotide probes designed from approximately 50,000 known and predicted transcript sequences from the human genome were used to survey transcription from a diverse set of 60 tissues and cell lines using ink-jet microarrays. Further, expression activity over at least six conditions was more generally assessed using genomic tiling arrays consisting of probes tiled through a repeat-masked version of the genomic sequence making up chromosomes 20 and 22. RESULTS: The combination of microarray data with extensive genome annotations resulted in a set of 28,456 experimentally supported transcripts. This set of high-confidence transcripts represents the first experimentally driven annotation of the human genome. In addition, the results from genomic tiling suggest that a large amount of transcription exists outside of annotated regions of the genome and serves as an example of how this activity could be measured on a genome-wide scale. CONCLUSIONS: These data represent one of the most comprehensive assessments of transcriptional activity in the human genome and provide an atlas of human gene expression over a unique set of gene predictions. Before the annotation of the human genome is considered complete, however, the previously unannotated transcriptional activity throughout the genome must be fully characterized.