GENE EXPRESSION TIME-SERIES ANALYSIS OF CAMPTHOTECIN EFFECTS IN U-87-MG AND DBTRG-05 GLIOBLASTOMA CELL LINES

The clinical efficacy of camptothecin (CPT), a drug specifically targetingtopoisomerase I (TopoI), is under evaluation for the treatment of malignant gliomas. Due to thehigh unresponsiveness of these tumours to chemotherapy, it would be very important to study thesignalling network that drives camptothecin outcome in this type of cancer cells. To address thisissue, we had previously compared the expression profile of human U87-MG glioblastoma cellswith that of a CPT-resistant counterpart, giving evidence that the development of a robustinflammatory response was the main transcriptional effect associated with CPT resistance.Here we report time-related changes and cell line specific patterns of gene expression after CPTtreatment by using two p53 wild-type glioblastoma cell lines, U87-MG and DBTRG-05, withdifferent sensitivities to TopoI inhibition

Abrogation of Junctional Adhesion Molecule-A Expression Induces Cell Apoptosis and Reduces Breast Cancer Progression

Intercellular junctions promote homotypic cell to cell adhesion and transfer intracellular signals which control cell growth and apoptosis. Junctional adhesion molecule-A (JAM-A) is a transmembrane immunoglobulin located at tight junctions of normal epithelial cells of mammary ducts and glands. In the present paper we show that JAM-A acts as a survival factor for mammary carcinoma cells. JAM-A null mice expressing Polyoma Middle T under MMTV promoter develop significantly smaller mammary tumors than JAM-A positive mice. Angiogenesis and inflammatory or immune infiltrate were not statistically modified in absence of JAM-A but tumor cell apoptosis was significantly increased. Tumor cells isolated from JAM-A null mice or 4T1 cells incubated with JAM-A blocking antibodies showed reduced growth and increased apoptosis which paralleled altered junctional architecture and adhesive function. In a breast cancer clinical data set, tissue microarray data show that JAM-A expression correlates with poor prognosis. Gene expression analysis of mouse tumor samples showed a correlation between genes enriched in human G3 tumors and genes over expressed in JAM-A +/+ mammary tumors. Conversely, genes enriched in G1 human tumors correlate with genes overexpressed in JAM-A−/− tumors. We conclude that down regulation of JAM-A reduces tumor aggressive behavior by increasing cell susceptibility to apoptosis. JAM-A may be considered a negative prognostic factor and a potential therapeutic target

Screening of Intestinal Crypt Organoids: A Simple Readout for Complex Biology

Oral and intestinal mucositis is a debilitating, often dose limiting side effect of radiation treatment. A mouse model of mucositis, induced by gamma irradiation, leads to weight loss and tissue damage, similar to that observed in patients. This model reflects the human ailment as it responds to keratinocyte growth factor (KGF), the standard of care treatment. Culturing of intestinal crypt organoids derived from primary cells allowed the development of a 3D assay to monitor the effect of treatments of intestinal epithelium to radiation-induced damage. This in vitro assay closely resembles the mouse model as KGF and Roof Plate-Specific Spondin-1 (RSPO1) enhanced the recovery of crypt organoids following radiation. Screening identified tool compounds that increased the survival of organoids post radiation. Repeated testing of these compounds revealed that the organoids changed their response over time. To investigate this adaptive behavior, intestinal organoid cultures were studied over time. Samples of organoids at various time points were used to prepare mRNA for unbiased transcriptome analyses. This expression profiling revealed a number of genes and pathways that were modulated over time, providing a rationale for the altered sensitivity of the intestinal crypt organoid cultures. This report describes the development of an in vitro assay that reflects the response of disease to therapeutic treatment. The assay was miniaturized and used to identify bioactive tool compounds, which served as probes to interrogate the patho-physiology of organoids over prolonged culture conditions. In vitro disease models based on primary 3D cell cultures represent valuable tools to identify potential drug targets and bioactive hits

A Snapshot of the Physical and Functional Wiring of the Eps15 Homology Domain Network in the Nematode

<div><p>Protein interaction modules coordinate the connections within and the activity of intracellular signaling networks. The Eps15 Homology (EH) module, a protein-protein interaction domain that is a key feature of the EH-network, was originally identified in a few proteins involved in endocytosis and vesicle trafficking, and has subsequently also been implicated in actin reorganization, nuclear shuttling, and DNA repair. Here we report an extensive characterization of the physical connections and of the functional wirings of the EH-network in the nematode. Our data show that one of the major physiological roles of the EH-network is in neurotransmission. In addition, we found that the proteins of the network intersect, and possibly coordinate, a number of “territories” of cellular activity including endocytosis/recycling/vesicle transport, actin dynamics, general metabolism and signal transduction, ubiquitination/degradation of proteins, DNA replication/repair, and miRNA biogenesis and processing.</p> </div

In vitro binding assays.

<p>Sixteen interactors, identified by Y2H (listed at the bottom), were expressed as GST-fusion proteins and used for <i>in vitro</i> binding assays with FLAG-EH proteins expressed in Phoenix cells. Results are the average of three independent experiments (examples are shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0056383#pone.0056383.s003" target="_blank">Figure S3</a>), and are expressed in arbitrary units on a scale 0–100, in which 100 represents the efficiency of the pull-down for the strongest interacting protein in each panel.</p

Effect of RNAi of EH interactors in various genetic backgrounds.

<p>Down-regulation of the EH-interactors was achieved by feeding RNA interference (RNAi), in the indicated strains, and animals were tested for aldicarb sensitivity. (A) In the column N2, the effect of RNAi on aldicarb sensitivity in wild type (N2) animals is reported (H, hypersensitive to aldicarb, R, resistant to aldicarb). In the other columns, the type of genetic interaction, detected in the various strains, is reported (S, suppressing; W, worsening; Rv, reverting; A, asynthetic; L, lethal; Ep, possibly RNAi epistatic; see also <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0056383#pone-0056383-t001" target="_blank">Table 1</a>). (B) Examples of the detected genetic interactions. Results are expressed as the change in the λ parameter in the best-fitting Weibull distribution with respect to WT. “KO strain”, null mutant for the EH-containing gene; “RNAi in WT”, N2 worms in which the EH-interactor was silenced by RNAi; “RNAi in KO strain”, null mutants for the EH-containing gene in which the EH-interactor was silenced by RNAi; Null hypothesis, mathematical sum of the observed phenotypes in the “KO strain” and “RNAi in WT conditions”. Details of the analysis are in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0056383#s2" target="_blank">Materials and Methods</a>.</p

The EH network in <i>C. elegans</i>. An interaction diagram is shown representing <i>C. elegans</i> EH proteins (red circles) together with their interactors (blue circles); the interactors are further grouped into functional categories that were derived from the Wormbase and the Gene Ontology databases, from the literature, or inferred from functions of the mammalian homologues.

<p>Interactions uncovered in this study by Y2H are shown by light blue lines. Interactions confirmed by <i>in vitro</i> binding assays are shown by dark blue lines. Interactions not fully depending on the EH domain are shown with dashed lines. Additional interactions, derived from the BioGRID database (<a href="http://thebiogrid.org/" target="_blank">http://thebiogrid.org/</a>) and from the literature, are shown by red lines. The picture was initially generated using the Osprey software <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0056383#pone.0056383-Breitkreutz1" target="_blank">[96]</a> and then edited with Adobe Illustrator.</p