ToppGene Suite (http://toppgene.cchmc.org; this web site is free and open to all users and does not require a login to access) is a one-stop portal for (i) gene list functional enrichment, (ii) candidate gene prioritization using either functional annotations or network analysis and (iii) identification and prioritization of novel disease candidate genes in the interactome. Functional annotation-based disease candidate gene prioritization uses a fuzzy-based similarity measure to compute the similarity between any two genes based on semantic annotations. The similarity scores from individual features are combined into an overall score using statistical meta-analysis. A P-value of each annotation of a test gene is derived by random sampling of the whole genome. The protein–protein interaction network (PPIN)-based disease candidate gene prioritization uses social and Web networks analysis algorithms (extended versions of the PageRank and HITS algorithms, and the K-Step Markov method). We demonstrate the utility of ToppGene Suite using 20 recently reported GWAS-based gene–disease associations (including novel disease genes) representing five diseases. ToppGene ranked 19 of 20 (95%) candidate genes within the top 20%, while ToppNet ranked 12 of 16 (75%) candidate genes among the top 20%.

The authors applied a correlation-based metric, ‘differential stability’ (DS), to assess reproducibility of gene expression patterning across individual brains, revealing mesoscale genetic organization. The highest DS genes were enriched for brain-related biological annotations, disease associations and drug targets, and their anatomical expression pattern correlated with resting state functional connectivity. The structure and function of the human brain are highly stereotyped, implying a conserved molecular program responsible for its development, cellular structure and function. We applied a correlation-based metric called differential stability to assess reproducibility of gene expression patterning across 132 structures in six individual brains, revealing mesoscale genetic organization. The genes with the highest differential stability are highly biologically relevant, with enrichment for brain-related annotations, disease associations, drug targets and literature citations. Using genes with high differential stability, we identified 32 anatomically diverse and reproducible gene expression signatures, which represent distinct cell types, intracellular components and/or associations with neurodevelopmental and neurodegenerative disorders. Genes in neuron-associated compared to non-neuronal networks showed higher preservation between human and mouse; however, many diversely patterned genes displayed marked shifts in regulation between species. Finally, highly consistent transcriptional architecture in neocortex is correlated with resting state functional connectivity, suggesting a link between conserved gene expression and functionally relevant circuitry.

We report a database of genes responsive to the Myc oncogenic transcription factor. The database Myc Target Gene prioritizes candidate target genes according to experimental evidence and clusters responsive genes into functional groups. We coupled the prioritization of target genes with phylogenetic sequence comparisons to predict c-Myc target binding sites, which are in turn validated by chromatin immunoprecipitation assays. This database is essential for the understanding of the genetic regulatory networks underlying the genesis of cancers.

ToppCluster is a web server application that leverages a powerful enrichment analysis and underlying data environment for comparative analyses of multiple gene lists. It generates heatmaps or connectivity networks that reveal functional features shared or specific to multiple gene lists. ToppCluster uses hypergeometric tests to obtain list-specific feature enrichment P-values for currently 17 categories of annotations of human-ortholog genes, and provides user-selectable cutoffs and multiple testing correction methods to control false discovery. Each nameable gene list represents a column input to a resulting matrix whose rows are overrepresented features, and individual cells per-list P-values and corresponding genes per feature. ToppCluster provides users with choices of tabular outputs, hierarchical clustering and heatmap generation, or the ability to interactively select features from the functional enrichment matrix to be transformed into XGMML or GEXF network format documents for use in Cytoscape or Gephi applications, respectively. Here, as example, we demonstrate the ability of ToppCluster to enable identification of list-specific phenotypic and regulatory element features (both cis-elements and 3′UTR microRNA binding sites) among tissue-specific gene lists. ToppCluster’s functionalities enable the identification of specialized biological functions and regulatory networks and systems biology-based dissection of biological states. ToppCluster can be accessed freely at http://toppcluster.cchmc.org.

Background: The expression of carcino-embryonic antigen by colorectal cancer is an example of oncogenic activation of embryonic gene expression. Hypothesizing that oncogenesis-recapitulating-ontogenesis may represent a broad programmatic commitment, we compared gene expression patterns of human colorectal cancers (CRCs) and mouse colon tumor models to those of mouse colon development embryonic days 13.5-18.5. Results: We report here that 39 colon tumors from four independent mouse models and 100 human CRCs encompassing all clinical stages shared a striking recapitulation of embryonic colon gene expression. Compared to normal adult colon, all mouse and human tumors over-expressed a large cluster of genes highly enriched for functional association to the control of cell cycle progression, proliferation, and migration, including those encoding MYC, AKT2, PLK1 and SPARC. Mouse tumors positive for nuclear β-catenin shifted the shared embryonic pattern to that of early development. Human and mouse tumors differed from normal embryonic colon by their loss of expression modules enriched for tumor suppressors (EDNRB, HSPE, KIT and LSP1). Human CRC adenocarcinomas lost an additional suppressor module (IGFBP4, MAP4K1, PDGFRA, STAB1 and WNT4). Many human tumor samples also gained expression of a coordinately regulated module associated with advanced malignancy (ABCC1, FOXO3A, LIF, PIK3R1, PRNP, TNC, TIMP3 and VEGF). Conclusion: Cross-species, developmental, and multi-model gene expression patterning comparisons provide an integrated and versatile framework for definition of transcriptional programs associated with oncogenesis. This approach also provides a general method for identifying pattern-specific biomarkers and therapeutic targets. This delineation and categorization of developmental and non-developmental activator and suppressor gene modules can thus facilitate the formulation of sophisticated hypotheses to evaluate potential synergistic effects of targeting within- and between-modules for next-generation combinatorial therapeutics and improved mouse models.

Summary Background and objectives The vast majority of US dialysis facilities are for-profit and profit status has been associated with processes of care and outcomes in patients on dialysis. This study examined whether dialysis facility profit status was associated with the rate of hospitalization in patients starting dialysis. Design, setting, participants, & methods This was a retrospective cohort study of Medicare beneficiaries starting dialysis between 2005 and 2008 using data from the US Renal Data System. All-cause hospitalization was examined and compared between for-profit and nonprofit dialysis facilities through 2009 using Poisson regression. Companion analyses of cause-specific hospitalization that are likely to be influenced by dialysis facility practices including hospitalizations for heart failure and volume overload, access complications, or hyperkalemia were conducted. Results The cohort included 150,642 patients. Of these, 12,985 (9%) were receiving care in nonprofit dialysis facilities. In adjusted models, patients receiving hemodialysis in for-profit facilities had a 15% (95% confidence interval [95% CI], 13% to 18%) higher relative rate of hospitalization compared with those in nonprofit facilities. Among patients receiving peritoneal dialysis, the rate of hospitalization in for-profit versus nonprofit facilities was not significantly different (relative rate, 1.07; 95% CI, 0.97 to 1.17). Patients on hemodialysis receiving care in for-profit dialysis facilities had a 37% (95% CI, 31% to 44%) higher rate of hospitalization for heart failure or volume overload and a 15% (95% CI, 11% to 20%) higher rate of hospitalization for vascular access complications. Conclusions Hospitalization rates were significantly higher for patients receiving hemodialysis in for-profit compared with nonprofit dialysis facilities.