Greg Tucker-Kellogg

FLIP: A flop for execution signals

Resistance to apoptosis is one of the established hallmarks of cancer cells. This is a function of an imbalance between the proteins that facilitate death execution and those that inhibit apoptosis or promote cell proliferation. The anti-apoptotic protein, FLICE inhibitory protein (FLIP), first identified as a viral protein, is over-expressed in a variety of human pathologies. Initial observations linked FLIP expression to inhibition of death receptor induced apoptosis, due to its structural homology to the cysteine protease, caspase-8. FLIP impedes full processing of pro-caspase-8 to its active form and its release to the cytosol, and by doing so blocks apoptotic signaling downstream of the membrane death initiating signaling complex (DISC). Recent observations have highlighted the complex regulation of this protein and its cross talk with diverse signaling networks and metabolic processes. As FLIP expression is directly associated with chemotherapy resistance, a better understanding of its genomic organization, gene transcription, as well as post-transcriptional regulation could yield novel targets with potential therapeutic implications against drug refractory cancers. In this short review, we provide a brief overview of the structural and functional biology of this somewhat complex protein with direct relevance to carcinogenesis.

Scaling the walls of discovery: using semantic metadata for integrative problem solving

Current data integration approaches by bioinformaticians frequently involve extracting data from a wide variety of public and private data repositories, each with a unique vocabulary and schema, via scripts. These separate data sets must then be normalized through the tedious and lengthy process of resolving naming differences and collecting information into a single view. Attempts to consolidate such diverse data using data warehouses or federated queries add significant complexity and have shown limitations in flexibility. The alternative of complete semantic integration of data requires a massive, sustained effort in mapping data types and maintaining ontologies. We focused instead on creating a data architecture that leverages semantic mapping of experimental metadata, to support the rapid prototyping of scientific discovery applications with the twin goals of reducing architectural complexity while still leveraging semantic technologies to provide flexibility, efficiency and more fully characterized data relationships. A metadata ontology was developed to describe our discovery process. A metadata repository was then created by mapping metadata from existing data sources into this ontology, generating RDF triples to describe the entities. Finally an interface to the repository was designed which provided not only search and browse capabilities but complex query templates that aggregate data from both RDF and RDBMS sources. We describe how this approach (i) allows scientists to discover and link relevant data across diverse data sources and (ii) provides a platform for development of integrative informatics applications.

Progenitor-like Traits Contribute to Patient Survival and Prognosis in Oligodendroglial Tumors

Purpose: Patient-derived glioma-propagating cells (GPC) contain karyotypic and gene expression profiles that are found in the primary tumor. However, their clinical relevance is unclear. We ask whether GPCs contribute to disease progression and survival outcome in patients with glioma by analyzing gene expression profiles. Experimental Design: We tapped into public sources of GPC gene expression data and derived a gene signature distinguishing oligodendroglial from glioblastoma multiforme (GBM) GPCs. By adapting a method in glioma biology, the Connectivity Map, we interrogated its strength of association in public clinical databases. We validated the top-ranking signaling pathways Wnt, Notch, and TGFβ, in GPCs and primary tumor specimens. Results: We observed that patients with better prognosis correlated with oligodendroglial GPC features and lower tumor grade, and this was independent of the current clinical indicator, 1p/19q status. Patients with better prognosis had proneural tumors whereas the poorly surviving cohort had mesenchymal tumors. In addition, oligodendroglial GPCs were more sensitive to Wnt and Notch inhibition whereas GBM GPCs responded to TGFβR1 inhibition. Conclusions: We provide evidence that GPCs are clinically relevant. In addition, the more favorable prognosis of oligodendroglial tumors over GBM could be recapitulated transcriptomically at the GPC level, underscoring the relevance of this cellular model. Our gene signature detects molecular heterogeneity in oligodendroglial tumors that cannot be accounted for by the 1p/19q status alone, indicating that stem-like traits contribute to clinical status. Collectively, these data highlight the limitation of morphology-based histologic analyses in tumor classification, consequently impacting on treatment decisions. Clin Cancer Res; 18(15); 4122–35. ©2012 AACR.

A Distinct Reactive Oxygen Species Profile Confers Chemoresistance in Glioma-Propagating Cells and Associates with Patient Survival Outcome

AIMS We explore the role of an elevated O2(-):H2O2 ratio as a prosurvival signal in glioma-propagating cells (GPCs). We hypothesize that depleting this ratio sensitizes GPCs to apoptotic triggers. RESULTS We observed that an elevated O2(-):H2O2 ratio conferred enhanced resistance in GPCs, and depletion of this ratio by pharmacological and genetic methods sensitized cells to apoptotic triggers. We established the reactive oxygen species (ROS) Index as a quantitative measure of a normalized O2(-):H2O2 ratio and determined its utility in predicting chemosensitivity. Importantly, mice implanted with GPCs of a reduced ROS Index demonstrated extended survival. Analysis of tumor sections revealed effective targeting of complementarity determinant 133 (CD133)- and nestin-expressing neural precursors. Further, we established the Connectivity Map to interrogate a gene signature derived from a varied ROS Index for the patterns of association with individual patient gene expression in four clinical databases. We showed that patients with a reduced ROS Index demonstrate better survival. These data provide clinical evidence for the viability of our O2(-):H2O2-mediated chemosensitivity profiles. INNOVATION AND CONCLUSION Gliomas are notoriously recurrent and highly infiltrative, and have been shown to arise from stem-like cells. We implicate an elevated O2(-):H2O2 ratio as a prosurvival signal in GPC self-renewal and proliferation. The ROS Index provides quantification of O2(-):H2O2-mediated chemosensitivity, an advancement in a previously qualitative field. Intriguingly, glioma patients with a reduced ROS Index correlate with longer survival and the Proneural molecular classification, a feature frequently associated with tumors of better prognosis. These data emphasize the feasibility of manipulating the O2(-):H2O2 ratio as a therapeutic strategy.

The Drosophila Dicer-1 Partner Loquacious Enhances miRNA Processing from Hairpins with Unstable Structures at the Dicing Site

In Drosophila, Dicer-1 binds Loquacious-PB (Loqs-PB) as its major co-factor. Previous analyses indicated that loqs mutants only partially impede miRNA processing, but the activity of minor isoforms or maternally deposited Loqs was not eliminated in these studies. We addressed this by generating a cell line from loqs-null embryos and found that only ∼40% of miRNAs showed clear Loqs dependence. Genome-wide comparison of the hairpin structure and Loqs dependence suggested that Loqs substrates are influenced by base-pairing status at the dicing site. Artificial alteration of base-pairing stability at this position in model miRNA hairpins resulted in predicted changes in Loqs dependence, providing evidence for this hypothesis. Finally, we found that evolutionarily young miRNA genes tended to be Loqs dependent. We propose that Loqs may have roles in assisting the de novo emergence of miRNA genes by facilitating dicing of suboptimal hairpin substrates.

Importance of miRNA stability and alternative primary miRNA isoforms in gene regulation during Drosophila development

Mature microRNAs (miRNAs) are processed from primary transcripts (pri-miRNAs), and their expression is controlled at transcriptional and post-transcriptional levels. However, how regulation at multiple levels achieves precise control remains elusive. Using published and new datasets, we profile a time course of mature and pri-miRNAs in Drosophila embryos and reveal the dynamics of miRNA production and degradation as well as dynamic changes in pri-miRNA isoform selection. We found that 5’ nucleotides influence stability of mature miRNAs. Furthermore, distinct half-lives of miRNAs from the mir-309 cluster shape their temporal expression patterns, and the importance of rapid degradation of the miRNAs in gene regulation is detected as distinct evolutionary signatures at the target sites in the transcriptome. Finally, we show that rapid degradation of miR-3/–309 may be important for regulation of the planar cell polarity pathway component Vang. Altogether, the results suggest that complex mechanisms regulate miRNA expression to support normal development.

Differential expression of novel microRNAs in response to the infection of a TMV mutant with an internal poly(A) tract in N. benthamiana

We first constructed small RNA libraries of TMV- and TMV-43A-infected N. benthamiana for high throughput sequencing. A total number of 181 novel microRNAs (miRNAs) were identified through an improved miRNAs analysis pipeline. We were able to identify consistent miRNA expression changes induced in TMV and TMV-43A-infected plants, as well as differences associated with the UPD substitution in the TMV-43A viral genome. Virally induced miRNAs are associated with distinct processes and functions of predicted mRNA targets, including relation to host target defense. This study suggests an approach for functional genomics miRNAs in incompletely assembled genomes. These findings provide valuable information for further characterization of miRNAs by two genomic similar viruses, and provide clues to the study of TMV-UPD to find potential defense-related host genes targeted by miRNAs (126 words).

Systems Biology in Drug Discovery: Using Predictive Biomedicine to Guide Development Choices for Novel Agents in Cancer

Publisher Summary This chapter discusses systems-based approaches to translational medicine. This is made possible by the convergent acceleration of several disciplines—computational, post-genomic platform and biomedical sciences—working together to offer a more complete picture of the complexities of disease and disease treatment. Systems-based approaches offer an increasingly less biased set of platforms with which to observe the phenomenal diversity of cancers and conduct experiments in a wider range of more clinically relevant models. This chapter also describes how systems approaches for predictive biomedicine—integrating discovery and clinical data—can be applied to identify novel targets, predictive biomarkers of response to agents in development and targeted use of drug combinations. The objective of these approaches is for new agents, the development of which is guided by predictive biomedicine to improve outcomes for individual cancer patients. Some more recently approved agents, such as sorafenib, intentionally target several members of signaling cascades dysregulated in tumors, taking advantage of the multitargeted nature of many kinase inhibitors. There has also been a phenomenal explosion in the generation of experimental data in the wake of the human genome project. Rapid advances in computational processing power, data storage, modeling, and analysis have become available to make such data interpretable. The convergence of these three trends—targeted therapies in cancer, post-genomic system-wide experimentation platforms, and unprecedented advances in information technology—lays the foundation for the application of systems biology to drug discovery in cancer.

Abstract PR-5: Signal pathway profiling of cancer cell lines derived from serially passaged human tumorgrafts for guiding drug development

Effective chemotherapeutic treatment of cancer is stymied by a lack of understanding of tumorigenic pathway defects in individual tumors. Combining large scale measurement technologies with appropriate informatics and statistical approaches is a promising approach to detect such aberrations in signaling pathways and provide rationale(s) for driving the choice of targeted chemotherapies. We have attempted to address these by generating a high resolution understanding of pathway defects in 30 solid tumor cell lines, which were established directly from patient‐derived xenografts representing 13 histologies. We simultaneously interrogated ∼100 unique protein signaling events using reverse phase protein arrays (RPPA), along with profiling the same cell lines on Affymetrix expression and Agilent CGH platforms. An in silico validation of the RPPA data was conducted by a) clustering analysis that revealed lineage‐independent pathway perturbations, b) combining it with baseline genomic and expression data that elucidated and confirmed several underlying genomic defect(s) associated with protein‐level changes, c) studying similarity of protein‐protein correlations and KEGG cancer pathways that showed high concordance between the two. We developed signaling cascade maps that estimate tumorigenic pathway activation level for individual samples, which can then be used to propose an appropriate therapeutic intervention. Using proliferation assay data from several known targeted agents, we confirmed our observations and ascertained patterns of protein expression that predict for chemosensitivity. In summary, we propose that the methods described here represent a novel approach to analysis of gene/pathway changes associated with tumorigenesis and will be useful in building models of cancer cell protein circuitry applicable to the development of both drugs and patient stratification biomarkers. Citation Information: Mol Cancer Ther 2009;8(12 Suppl):PR-5.