'Multi-omic' data analysis using O-miner.

Innovations in -omics technologies have driven advances in biomedical research. However, integrating and analysing the large volumes of data generated from different high-throughput -omics technologies remain a significant challenge to basic and clinical scientists without bioinformatics skills or access to bioinformatics support. To address this demand, we have significantly updated our previous O-miner analytical suite, to incorporate several new features and data types to provide an efficient and easy-to-use Web tool for the automated analysis of data from '-omics' technologies. Created from a biologist's perspective, this tool allows for the automated analysis of large and complex transcriptomic, genomic and methylomic data sets, together with biological/clinical information, to identify significantly altered pathways and prioritize novel biomarkers/targets for biological validation. Our resource can be used to analyse both in-house data and the huge amount of publicly available information from array and sequencing platforms. Multiple data sets can be easily combined, allowing for meta-analyses. Here, we describe the analytical pipelines currently available in O-miner and present examples of use to demonstrate its utility and relevance in maximizing research output. O-miner Web server is free to use and is available at http://www.o-miner.org.

O-miner: an integrative platform for automated analysis and mining of -omics data.

High-throughput profiling has generated massive amounts of data across basic, clinical and translational research fields. However, open source comprehensive web tools for analysing data obtained from different platforms and technologies are still lacking. To fill this gap and the unmet computational needs of ongoing research projects, we developed O-miner, a rapid, comprehensive, efficient web tool that covers all the steps required for the analysis of both transcriptomic and genomic data starting from raw image files through in-depth bioinformatics analysis and annotation to biological knowledge extraction. O-miner was developed from a biologist end-user perspective. Hence, it is as simple to use as possible within the confines of the complexity of the data being analysed. It provides a strong analytical suite able to overlay and harness large, complicated, raw and heterogeneous sets of profiles with biological/clinical data. Biologists can use O-miner to analyse and integrate different types of data and annotations to build knowledge of relevant altered mechanisms and pathways in order to identify and prioritize novel targets for further biological validation. Here we describe the analytical workflows currently available using O-miner and present examples of use. O-miner is freely available at www.o-miner.org.

Rare Variation in Drug Metabolism and Long QT Genes and the Genetic Susceptibility to Acquired Long QT Syndrome.

BACKGROUND: Acquired long QT syndrome (aLQTS) is a serious unpredictable adverse drug reaction. Pharmacogenomic markers may predict risk. METHODS: Among 153 aLQTS patients (mean age 58 years [range, 14-88], 98.7% White, 85.6% symptomatic), computational methods identified proteins interacting most significantly with 216 QT-prolonging drugs. All cases underwent sequencing of 31 candidate genes arising from this analysis or associating with congenital LQTS. Variants were filtered using a minor allele frequency <1% and classified for susceptibility for aLQTS. Gene-burden analyses were then performed comparing the primary cohort to control exomes (n=452) and an independent replication aLQTS exome sequencing cohort. RESULTS: In 25.5% of cases, at least one rare variant was identified: 22.2% of cases carried a rare variant in a gene associated with congenital LQTS, and in 4% of cases that variant was known to be pathogenic or likely pathogenic for congenital LQTS; 7.8% cases carried a cytochrome-P450 (CYP) gene variant. Of 12 identified CYP variants, 11 (92%) were in an enzyme known to metabolize at least one culprit drug to which the subject had been exposed. Drug-drug interactions that affected culprit drug metabolism were found in 19% of cases. More than one congenital LQTS variant, CYP gene variant, or drug interaction was present in 7.8% of cases. Gene-burden analyses of the primary cohort compared to control exomes (n=452), and an independent replication aLQTS exome sequencing cohort (n=67) and drug-tolerant controls (n=148) demonstrated an increased burden of rare (minor allele frequency<0.01) variants in CYP genes but not LQTS genes. CONCLUSIONS: Rare susceptibility variants in CYP genes are emerging as potentially important pharmacogenomic risk markers for aLQTS and could form part of personalized medicine approaches in the future.

On the artefactual parasitic eubacteria clan in conditioned logdet phylogenies: heterotachy and ortholog identification artefacts as explanations.

BACKGROUND: Phylogenetic reconstruction methods based on gene content often place all the parasitic and endosymbiotic eubacteria (parasites for short) together in a clan. Many other lines of evidence point to this parasites clan being an artefact. This artefact could be a consequence of the methods used to construct ortholog databases (due to some unknown bias), the methods used to estimate the phylogeny, or both.We test the idea that the parasites clan is an ortholog identification artefact by analyzing three different ortholog databases (COG, TRIBES, and OFAM), which were constructed using different methods, and are thus unlikely to share the same biases. In each case, we estimate a phylogeny using an improved version of the conditioned logdet distance method. If the parasites clan appears in trees from all three databases, it is unlikely to be an ortholog identification artefact.Accelerated loss of a subset of gene families in parasites (a form of heterotachy) may contribute to the difficulty of estimating a phylogeny from gene content data. We test the idea that heterotachy is the underlying reason for the estimation of an artefactual parasites clan by applying two different mixture models (phylogenetic and non-phylogenetic), in combination with conditioned logdet. In these models, there are two categories of gene families, one of which has accelerated loss in parasites. Distances are estimated separately from each category by conditioned logdet. This should reduce the tendency for tree estimation methods to group the parasites together, if heterotachy is the underlying reason for estimation of the parasites clan. RESULTS: The parasites clan appears in conditioned logdet trees estimated from all three databases. This makes it less likely to be an artefact of database construction. The non-phylogenetic mixture model gives trees without a parasites clan. However, the phylogenetic mixture model still results in a tree with a parasites clan. Thus, it is not entirely clear whether heterotachy is the underlying reason for the estimation of a parasites clan. Simulation studies suggest that the phylogenetic mixture model approach may be unsuccessful because the model of gene family gain and loss it uses does not adequately describe the real data. CONCLUSIONS: The most successful methods for estimating a reliable phylogenetic tree for parasitic and endosymbiotic eubacteria from gene content data are still ad-hoc approaches such as the SHOT distance method. however, the improved conditioned logdet method we developed here may be useful for non-parasites and can be accessed at http://www.liv.ac.uk/~cgrbios/cond_logdet.html.

A phylogenetic mixture model for gene family loss in parasitic bacteria.

Gene families are frequently gained and lost from prokaryotic genomes. It is widely believed that the rate of loss was accelerated for some but not all gene families in lineages that became parasites or endosymbionts. This leads to a form of heterotachy that may be responsible for the poor performance of phylogeny estimation based on gene content. We describe a mixture model that accounts for this heterotachy. We show that this model fits data on the distribution of gene families across bacteria from the COG database much better than previous models. However, it still favors an artifactual tree topology in which parasites form a clade over the more plausible 16S topology. In contrast to a previous model of genome dynamics, our model suggests that the ancestral bacterium had a small genome. We suggest that models of gene family gain and loss are likely to be more useful for understanding genome dynamics than for estimating phylogenetic trees.

MicroRNA and transcriptome analysis in periocular Sebaceous Gland Carcinoma.

Sebaceous gland carcinoma (SGC) is a rare, but life-threatening condition with a predilection for the periocular region. Eyelid SGC can be broadly categorised into two subtypes, namely either nodular or pagetoid with the latter being more aggressive and requiring radical excision to save life. We have identified key altered microRNAs (miRNA) involved in SGC shared by both subtypes, hsa-miR-34a-5p and hsa-miR-16-5p. However, their gene targets BCL2 and MYC were differentially expressed with both overexpressed in pagetoid but unchanged in nodular suggesting different modes of action of these two miRNAs on BCL/MYC expression. Hsa-miR-150p is nodular-specifically overexpressed, and its target ZEB1 was significantly downregulated in nodular SGC suggesting a tumour suppressor role. Invasive pagetoid subtype demonstrated specific overexpression of hsa-miR-205 and downregulation of hsa-miR-199a. Correspondingly, miRNA gene targets, EZH2 (by hsa-miR-205) and CD44 (by hsa-miR-199a), were both overexpressed in pagetoid SGC. CD44 has been identified as a potential cancer stem cell marker in head and neck squamous cell carcinoma and its overexpression in pagetoid cells represents a novel treatment target. Aberrant miRNAs and their gene targets have been identified in both SGC subtypes, paving the way for better molecular understanding of these tumours and identifying new treatment targets.

Splice variants as novel targets in pancreatic ductal adenocarcinoma.

Despite a wealth of genomic information, a comprehensive alternative splicing (AS) analysis of pancreatic ductal adenocarcinoma (PDAC) has not been performed yet. In the present study, we assessed whole exome-based transcriptome and AS profiles of 43 pancreas tissues using Affymetrix exon array. The AS analysis of PDAC indicated on average two AS probe-sets (ranging from 1-28) in 1,354 significantly identified protein-coding genes, with skipped exon and alternative first exon being the most frequently utilised. In addition to overrepresented extracellular matrix (ECM)-receptor interaction and focal adhesion that were also seen in transcriptome differential expression (DE) analysis, Fc gamma receptor-mediated phagocytosis and axon guidance AS genes were also highly represented. Of note, the highest numbers of AS probe-sets were found in collagen genes, which encode the characteristically abundant stroma seen in PDAC. We also describe a set of 37 'hypersensitive' genes which were frequently targeted by somatic mutations, copy number alterations, DE and AS, indicating their propensity for multidimensional regulation. We provide the most comprehensive overview of the AS landscape in PDAC with underlying changes in the spliceosomal machinery. We also collate a set of AS and DE genes encoding cell surface proteins, which present promising diagnostic and therapeutic targets in PDAC.

Gene expression profiling of breast cancer in Lebanese women.

Breast cancer is commonest cancer in women worldwide. Elucidation of underlying biology and molecular pathways is necessary for improving therapeutic options and clinical outcomes. Molecular alterations in breast cancer are complex and involve cross-talk between multiple signaling pathways. The aim of this study is to extract a unique mRNA fingerprint of breast cancer in Lebanese women using microarray technologies. Gene-expression profiles of 94 fresh breast tissue samples (84 cancerous/10 non-tumor adjacent samples) were analyzed using GeneChip Human Genome U133 Plus 2.0 arrays. Quantitative real-time PCR was employed to validate candidate genes. Differentially expressed genes between breast cancer and non-tumor tissues were screened. Significant differences in gene expression were established for COL11A1/COL10A1/MMP1/COL6A6/DLK1/S100P/CXCL11/SOX11/LEP/ADIPOQ/OXTR/FOSL1/ACSBG1 and C21orf37. Pathways/diseases representing these genes were retrieved and linked using PANTHER®/Pathway Studio®. Many of the deregulated genes are associated with extracellular matrix, inflammation, angiogenesis, metastasis, differentiation, cell proliferation and tumorigenesis. Characteristics of breast cancers in Lebanese were compared to those of women from Western populations to explain why breast cancer is more aggressive and presents a decade earlier in Lebanese victims. Delineating molecular mechanisms of breast cancer in Lebanese women led to key genes which could serve as potential biomarkers and/or novel drug targets for breast cancer.

Association between CLN3 (Neuronal Ceroid Lipofuscinosis, CLN3 Type) Gene Expression and Clinical Characteristics of Breast Cancer Patients.

Breast cancer is the most common cancer in women worldwide. Elucidation of underlying biology and molecular pathways is necessary for improving therapeutic options and clinical outcomes. CLN3 protein (CLN3p), deficient in neurodegenerative CLN3 disease is anti-apoptotic, and defects in the CLN3 gene cause accelerated apoptosis of neurons in CLN3 disease and up-regulation of ceramide. Dysregulated apoptotic pathways are often implicated in the development of the oncogenic phenotype. Predictably, CLN3 mRNA expression and CLN3 protein were up-regulated in a number of human and murine breast cancer-cell lines. Here, we determine CLN3 expression in non-tumor vs. tumor samples from fresh and formalin-fixed/paraffin-embedded (FFPE) breast tissue and analyze the association between CLN3 overexpression and different clinicopathological characteristics of breast cancer patients. Additionally, gene expression of 28 enzymes involved in sphingolipid metabolism was determined. CLN3 mRNA is overexpressed in tumor vs. non-tumor breast tissue from FFPE and fresh samples, as well as in mouse MCF7 breast cancer compared to MCF10A normal cells. Of the clinicopathological characteristics of tumor grade, age, menopause status, estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 (HER2), only absence of HER2 expression correlated with CLN3 overexpression. Sphingolipid genes for ceramide synthases 2 and 6 (CerS2; CerS6), delta(4)-desaturase sphingolipid 2 (DEGS2), and acidic sphingomyelinase (SMPD1) displayed higher expression levels in breast cancer vs. control tissue, whereas ceramide galactosyltransferase (UGT8) was underexpressed in breast cancer samples. CLN3 may be a novel molecular target for cancer drug discovery with the goal of modulation of ceramide pathways.

High Throughput Sequencing Analysis of the Immunoglobulin Heavy Chain Gene from Flow-Sorted B Cell Sub-Populations Define the Dynamics of Follicular Lymphoma Clonal Evolution.

Understanding the dynamics of evolution of Follicular Lymphoma (FL) clones during disease progression is important for monitoring and targeting this tumor effectively. Genetic profiling of serial FL biopsies and examples of FL transmission following bone marrow transplant suggest that this disease may evolve by divergent evolution from a common ancestor cell. However where this ancestor cell resides and how it evolves is still unclear. The analysis of the pattern of somatic hypermutation of the immunoglobulin gene (Ig) is traditionally used for tracking the physiological clonal evolution of B cells within the germinal center and allows to discriminate those cells that have just entered the germinal center and display features of ancestor cells from those B cells that keep re-circulating across different lymphoid organs. Here we investigated the pattern of somatic hypermutation of the heavy chain of the immunoglobulin gene (IgH-VH) in 4 flow-sorted B cells subpopulations belonging to different stages of differentiation, from sequential lymph node biopsies of cases displaying diverse patterns of evolution, using the GS-FLX Titanium sequencing platform. We observed an unexpectedly high level of clonality, with hundreds of distinct tumor subclones in the different subpopulations from the same sample, the majority detected at a frequency <10-2. By using a lineage trees analysis we observed in all our FL and t-FL cases that the oligoclonal FL population was trapped in a narrow intermediate stage of maturation that maintains the capacity to undergo SHM, but was unable to further differentiate. The presence of such a complex architecture highlights challenges currently encountered in finding a cure for this disease.

Noninvasive urinary miRNA biomarkers for early detection of pancreatic adenocarcinoma.

Currently, the majority of patients diagnosed with pancreatic ductal adenocarcinoma (PDAC) present with locally invasive and/or metastatic disease, resulting in five-year survival of less than 5%. The development of an early diagnostic test is, therefore, expected to significantly impact the patient's prognosis. In this study, we successfully evaluated the feasibility of identifying diagnostic cell free microRNAs (miRNAs) for early stage PDAC, through the analysis of urine samples. Using Affymetrix microarrays, we established a global miRNA profile of 13 PDAC, six chronic pancreatitis (CP), and seven healthy (H) urine specimens. Selected differentially expressed miRNAs were subsequently investigated using an independent technique (RT-PCR) on 101 urine samples including 46 PDAC, 29 CP and 26 H. Receiver operating characteristic (ROC) and logistic regression analyses were applied to determine the discriminatory potential of the candidate miRNA biomarkers. Three miRNAs (miR-143, miR-223, and miR-30e) were significantly over-expressed in patients with Stage I cancer when compared with age-matched healthy individuals (P=0.022, 0.035 and 0.04, respectively); miR-143, miR-223 and miR-204 were also shown to be expressed at higher levels in Stage I compared to Stages II-IV PDAC (P=0.025, 0.013 and 0.008, respectively). Furthermore, miR-223 and miR-204 were able to distinguish patients with early stage cancer from patients with CP (P=0.037 and 0.036). Among the three biomarkers, miR-143 was best able to differentiate Stage I (n=6) from healthy (n=26) with area under the curve (AUC) of 0.862 (95% CI 0.695-1.000), with sensitivity (SN) of 83.3% (95% CI 50.0-100.0), and specificity (SP) of 88.5% (95% CI 73.1-100.0). The combination of miR-143 with miR-30e was significantly better at discriminating between these two groups, achieving an AUC of 0.923 (95% CI 0.793-1.000), with SN of 83.3% (95% CI 50.0-100.0) and SP of 96.2% (95% CI 88.5-100.0). In this feasibility study, we demonstrate for the first time the utility of miRNA biomarkers for non-invasive, early detection of PDAC in urine specimens.

Follicular lymphoma cells induce changes in T-cell gene expression and function: potential impact on survival and risk of transformation.

PURPOSE: Previous studies have demonstrated the prognostic importance of the immune microenvironment in follicular lymphoma (FL). To investigate the molecular mechanisms during which tumor-infiltrating T cells (TILs) are altered in the FL microenvironment, we studied highly purified CD4 and CD8 TILs from lymph node biopsies at diagnosis in treatment-naive patients with FL compared with reactive tonsils and the peripheral blood of healthy donors. PATIENTS AND METHODS: Gene expression profiling of highly purified CD4 and CD8 TILs was performed on the Affymetrix platform. Diagnostic tissue microarrays from an independent patient set (n = 172) were used to verify protein expression and analyze any impact of TIL-expressed genes on outcome. Time-lapse imaging was used to assess T-cell motility. RESULTS: The most upregulated genes in both CD4 and CD8 TILs were PMCH, ETV1, and TNFRSF9. PMCH is not expressed in peripheral blood T cells, but expression is highly induced on culture with FL. Both CD4 and CD8 TILs from patients with FL have significantly impaired motility compared with those of healthy TILs from reactive tonsils and this can be induced on healthy T cells by FL cells. During multivariate analysis, a model incorporating the number and location of T cells expressing PMCH, NAMPT, and ETV1 showed prognostic significance for overall survival and for time to transformation. CONCLUSION: We showed altered gene expression in TILs in FL and demonstrated that altering the immune microenvironment in FL affects overall survival and time to transformation in this disease.

Response of the Strongyloides ratti transcriptome to host immunological environment.

The immunological environment experienced by parasitic nematodes varies greatly between hosts and is particularly influenced by whether or not a host has been previously infected. How a parasitic nematode responds to these different environments is poorly understood, but may allow a parasite to ameliorate the adverse effects of host immunity on parasite fitness. Here we use a microarray approach to identify genes in the parasitic nematode Strongyloides ratti that exhibit differential transcription between different rat host immunological environments, and between replicate lines of S. ratti selected for either early or late reproduction. We hypothesise that such genes may be used by this species to cope with and respond to its host environment. Our results showed that, despite large phenotypic differences between S. ratti adults from different immunological environments, the S. ratti transcriptome exhibited a relatively stable pattern of expression. Thus, differential expression amongst treatments was limited to a small proportion of transcripts and generally involved only modest fold changes. These transcripts included a group of collagen genes up-regulated in parasites early in an infection, and in immunised host environments, which may be related to protection against the damage caused to a parasite by host immune responses. We found that later in an infection, a number of genes associated with muscle function and repair were up-regulated in immunised host environments; these may help parasites maintain their position in the host intestine. Differences in transcription between selection lines of S. ratti were only observed in immunised hosts and included genes associated with the response to the host's immunological environment.