Functional Categories Associated with Clusters of Genes That Are Co-Expressed across the NCI-60 Cancer Cell Lines

The NCI-60 is a panel of 60 diverse human cancer cell lines used by the U.S. National Cancer Institute to screen compounds for anticancer activity. In the current study, gene expression levels from five platforms were integrated to yield a single composite transcriptome profile. The comprehensive and reliable nature of that dataset allows us to study gene co-expression across cancer cell lines.Hierarchical clustering revealed numerous clusters of genes in which the genes co-vary across the NCI-60. To determine functional categorization associated with each cluster, we used the Gene Ontology (GO) Consortium database and the GoMiner tool. GO maps genes to hierarchically-organized biological process categories. GoMiner can leverage GO to perform ontological analyses of gene expression studies, generating a list of significant functional categories.GoMiner analysis revealed many clusters of coregulated genes that are associated with functional groupings of GO biological process categories. Notably, those categories arising from coherent co-expression groupings reflect cancer-related themes such as adhesion, cell migration, RNA splicing, immune response and signal transduction. Thus, these clusters demonstrate transcriptional coregulation of functionally-related genes

Observable Effects of Scalar Fields and Varying Constants

We show by using the method of matched asymptotic expansions that a sufficient condition can be derived which determines when a local experiment will detect the cosmological variation of a scalar field which is driving the spacetime variation of a supposed constant of Nature. We extend our earlier analyses of this problem by including the possibility that the local region is undergoing collapse inside a virialised structure, like a galaxy or galaxy cluster. We show by direct calculation that the sufficient condition is met to high precision in our own local region and we can therefore legitimately use local observations to place constraints upon the variation of "constants" of Nature on cosmological scales.Comment: Invited Festscrift Articl

RedundancyMiner: De-replication of redundant GO categories in microarray and proteomics analysis

<p>Abstract</p> <p>Background</p> <p>The Gene Ontology (GO) Consortium organizes genes into hierarchical categories based on biological process, molecular function and subcellular localization. Tools such as GoMiner can leverage GO to perform ontological analysis of microarray and proteomics studies, typically generating a list of significant functional categories. Two or more of the categories are often redundant, in the sense that identical or nearly-identical sets of genes map to the categories. The redundancy might typically inflate the report of significant categories by a factor of three-fold, create an illusion of an overly long list of significant categories, and obscure the relevant biological interpretation.</p> <p>Results</p> <p>We now introduce a new resource, RedundancyMiner, that de-replicates the redundant and nearly-redundant GO categories that had been determined by first running GoMiner. The main algorithm of RedundancyMiner, MultiClust, performs a novel form of cluster analysis in which a GO category might belong to several category clusters. Each category cluster follows a "complete linkage" paradigm. The metric is a similarity measure that captures the overlap in gene mapping between pairs of categories.</p> <p>Conclusions</p> <p>RedundancyMiner effectively eliminated redundancies from a set of GO categories. For illustration, we have applied it to the clarification of the results arising from two current studies: (1) assessment of the gene expression profiles obtained by laser capture microdissection (LCM) of serial cryosections of the retina at the site of final optic fissure closure in the mouse embryos at specific embryonic stages, and (2) analysis of a conceptual data set obtained by examining a list of genes deemed to be "kinetochore" genes.</p

Subtype Specificity of Genetic Loci Associated With Stroke in 16 664 Cases and 32 792 Controls

Background: Genome-wide association studies have identified multiple loci associated with stroke. However, the specific stroke subtypes affected, and whether loci influence both ischemic and hemorrhagic stroke, remains unknown. For loci associated with stroke, we aimed to infer the combination of stroke subtypes likely to be affected, and in doing so assess the extent to which such loci have homogeneous effects across stroke subtypes. Methods: We performed Bayesian multinomial regression in 16 664 stroke cases and 32 792 controls of European ancestry to determine the most likely combination of stroke subtypes affected for loci with published genome-wide stroke associations, using model selection. Cases were subtyped under 2 commonly used stroke classification systems, TOAST (Trial of Org 10172 Acute Stroke Treatment) and causative classification of stroke. All individuals had genotypes imputed to the Haplotype Reference Consortium 1.1 Panel. Results: Sixteen loci were considered for analysis. Seven loci influenced both hemorrhagic and ischemic stroke, 3 of which influenced ischemic and hemorrhagic subtypes under both TOAST and causative classification of stroke. Under causative classification of stroke, 4 loci influenced both small vessel stroke and intracerebral hemorrhage. An EDNRA locus demonstrated opposing effects on ischemic and hemorrhagic stroke. No loci were predicted to influence all stroke subtypes in the same direction, and only one locus (12q24) was predicted to influence all ischemic stroke subtypes. Conclusions: Heterogeneity in the influence of stroke-associated loci on stroke subtypes is pervasive, reflecting differing causal pathways. However, overlap exists between hemorrhagic and ischemic stroke, which may reflect shared pathobiology predisposing to small vessel arteriopathy. Stroke is a complex, heterogeneous disorder requiring tailored analytic strategies to decipher genetic mechanisms

Differential transcriptional profiling of damaged and intact adjacent dorsal root ganglia neurons in neuropathic pain

Neuropathic pain, caused by a lesion in the somatosensory system, is a severely impairing mostly chronic disease. While its underlying molecular mechanisms are not thoroughly understood, neuroimmune interactions as well as changes in the pain pathway such as sensitization of nociceptors have been implicated. It has been shown that not only are different cell types involved in generation and maintenance of neuropathic pain, like neurons, immune and glial cells, but, also, intact adjacent neurons are relevant to the process. Here, we describe an experimental approach to discriminate damaged from intact adjacent neurons in the same dorsal root ganglion (DRG) using differential fluorescent neuronal labelling and fluorescence-activated cell sorting (FACS). Two fluorescent tracers, Fluoroemerald (FE) and 1-dioctadecyl-3,3,3,3-tetramethylindocarbocyanine perchlorate (DiI), were used, whose properties allow us to distinguish between damaged and intact neurons. Subsequent sorting permitted transcriptional analysis of both groups. Results and qPCR validation show a strong regulation in damaged neurons versus contralateral controls as well as a moderate regulation in adjacent neurons. Data for damaged neurons reveal an mRNA expression pattern consistent with established upregulated genes like galanin, which supports our approach. Moreover, novel genes were found strongly regulated such as corticotropinreleasing hormone (CRH), providing novel targets for further research. Differential fluorescent neuronal labelling and sorting allows for a clear distinction between primarily damaged neuropathic neurons and "bystanders," thereby facilitating a more detailed understanding of their respective roles in neuropathic processes in the DRG

In-vivo generation of bone via endochondral ossification by in-vitro chondrogenic priming of adult human and rat mesenchymal stem cells

Background: Bone grafts are required to repair large bone defects after tumour resection or large tr

Early peri-operative hyperglycaemia and renal allograft rejection in patients without diabetes

BACKGROUND: Patients with diabetes have an increased risk for allograft rejection, possibly related to peri-operative hyperglycaemia. Hyperglycaemia is also common following transplantation in patients without diabetes. We hypothesise that exposure of allograft tissue to hyperglycaemia could influence the risk for rejection in any patient with high sugars. To investigate the relationship of peri-operative glucose control to acute rejection in renal transplant patients without diabetes, all patients receiving their first cadaveric graft in a single center were surveyed and patients without diabetes receiving cyclosporin-based immunosuppression were reviewed (n = 230). Records of the plasma blood glucose concentration following surgery and transplant variables pertaining to allograft rejection were obtained. All variables suggestive of association were entered into multivariate logistic regression analysis, their significance analysed and modeled. RESULTS: Hyperglycaemia (>8.0 mmol/L) occurs in over 73% of non-diabetic patients following surgery. Glycaemic control immediately following renal transplantation independently predicted acute rejection (Odds ratio=1.08). 42% of patients with a glucose < 8.0 mmol/L following surgery developed rejection compared to 71% of patients who had a serum glucose above this level. Hyperglycaemia was not associated with any delay of graft function. CONCLUSION: Hyperglycaemia is associated with an increased risk for allograft rejection. This is consistent with similar findings in patients with diabetes. We hypothesise a causal link concordant with epidemiological and in vitro evidence and propose further clinical research