Glioma cells on the run – the migratory transcriptome of 10 human glioma cell lines

<p>Abstract</p> <p>Background</p> <p>Glioblastoma multiforme (GBM) is the most common primary intracranial tumor and despite recent advances in treatment regimens, prognosis for affected patients remains poor. Active cell migration and invasion of GBM cells ultimately lead to ubiquitous tumor recurrence and patient death.</p> <p>To further understand the genetic mechanisms underlying the ability of glioma cells to migrate, we compared the matched transcriptional profiles of migratory and stationary populations of human glioma cells. Using a monolayer radial migration assay, motile and stationary cell populations from seven human long term glioma cell lines and three primary GBM cultures were isolated and prepared for expression analysis.</p> <p>Results</p> <p>Gene expression signatures of stationary and migratory populations across all cell lines were identified using a pattern recognition approach that integrates <it>a priori </it>knowledge with expression data. Principal component analysis (PCA) revealed two discriminating patterns between migrating and stationary glioma cells: i) global down-regulation and ii) global up-regulation profiles that were used in a proband-based rule function implemented in GABRIEL to find subsets of genes having similar expression patterns. Genes with up-regulation pattern in migrating glioma cells were found to be overexpressed in 75% of human GBM biopsy specimens compared to normal brain. A 22 gene signature capable of classifying glioma cultures based on their migration rate was developed. Fidelity of this discovery algorithm was assessed by validation of the invasion candidate gene, connective tissue growth factor (CTGF). siRNA mediated knockdown yielded reduced <it>in vitro </it>migration and <it>ex vivo </it>invasion; immunohistochemistry on glioma invasion tissue microarray confirmed up-regulation of CTGF in invasive glioma cells.</p> <p>Conclusion</p> <p>Gene expression profiling of migratory glioma cells induced to disperse <it>in vitro </it>affords discovery of genomic signatures; selected candidates were validated clinically at the transcriptional and translational levels as well as through functional assays thereby underscoring the fidelity of the discovery algorithm.</p

Spinneret: Aiding Creative Ideation through Non-Obvious Concept Associations

Mind mapping is a popular way to explore a design space in creative thinking exercises, allowing users to form associations between concepts. Yet, most existing digital tools for mind mapping focus on authoring and organization, with little support for addressing the challenges of mind mapping such as stagnation and design fixation. We present Spinneret, a functional approach to aid mind mapping by providing suggestions based on a knowledge graph. Spinneret uses biased random walks to explore the knowledge graph in the neighborhood of an existing concept node in the mind map, and provides "suggestions" for the user to add to the mind map. A comparative study with a baseline mind-mapping tool reveals that participants created more diverse and distinct concepts with Spinneret, and reported that the suggestions inspired them to think of ideas they would otherwise not have explored.Comment: ACM CHI 202

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Derived from SAM analysis of union of and ; fast migrating cell lines colored in green, slow migrating cell lines colored in red ()

K-means (k = 3) identified three populations in malignant astrocytoma samples stratified by age that were visualized by multidimensional scaling (MDS); young (< median age) () and old patients (> median age) (). Kaplan-Meier survival analysis for clusters derived from k-means stratified by age; young (), old () show significant differences in overall survival.<p><b>Copyright information:</b></p><p>Taken from "Glioma cells on the run – the migratory transcriptome of 10 human glioma cell lines"</p><p>http://www.biomedcentral.com/1471-2164/9/54</p><p>BMC Genomics 2008;9():54-54.</p><p>Published online 29 Jan 2008</p><p>PMCID:PMC2275271.</p><p></p

Technical validation of microarray data by quantitative RT-PCR (QRT-PCR)

Average Log2 expression of relative mRNA copy numbers derived from three replicate microarray experiments and QRT-PCR of migratory (rim) over stationary (core) glioma cells (error bars = SD). Concordance between directionality of differential regulation between migratory and stationary cells for microarray and QRT-PCR data is displayed in parentheses (CYR61 = cystein rich 61, CTGF = connective tissue growth factor, RRAS2 = related RAS viral oncogene homolog 2, RhoA = ras homolog gene family member A, PCAF = p300/CBP-associated factor, ITM2B = integral membrane protein 2B, ZNF436 = zinc finger protein 436, MADH1 = mothers against decapentaplegic homolog 1 (). Expression pattern of () and () in comprehensive glioma expression data set (NB = normal brain, LGA = low grade astrocytoma, AA = anaplastic astrocytoma, GBM = glioblastoma multiforme). Bar indicates genes significantly (P < 0.05) differentially expressed between tumors and normal brain. Canonical pathways significantly over-represented in (black bars) and (white bar) ().<p><b>Copyright information:</b></p><p>Taken from "Glioma cells on the run – the migratory transcriptome of 10 human glioma cell lines"</p><p>http://www.biomedcentral.com/1471-2164/9/54</p><p>BMC Genomics 2008;9():54-54.</p><p>Published online 29 Jan 2008</p><p>PMCID:PMC2275271.</p><p></p

Hierarchical clustering of expression patterns of 20 core and rim samples ()

Scatterplot of principal component (PC) 9 against PC10 reveals two clouds representing core (black symbols) and rim samples (white symbols), respectively (). Proband gene AK098354 shows strong correlation with PC9, containing genes down-regulated in rim population () while cystein rich 61 (Cyr61) exhibits strong correlation with up-regulation pattern of PC10 (). GABRIEL was used to detect genes with similar expression patterns to proband genes AK098354 and Cyr61 ().<p><b>Copyright information:</b></p><p>Taken from "Glioma cells on the run – the migratory transcriptome of 10 human glioma cell lines"</p><p>http://www.biomedcentral.com/1471-2164/9/54</p><p>BMC Genomics 2008;9():54-54.</p><p>Published online 29 Jan 2008</p><p>PMCID:PMC2275271.</p><p></p