Translating stem cell studies to the clinic for CNS repair: current state of the art and the need for a Rosetta stone

Since their discovery twenty years ago and prospective isolation a decade later, neural stem cells (NSCs), their progenitors, and differentiated cell derivatives along with other stem-cell based strategies have advanced steadily toward clinical trials, spurred by the immense need to find reparative therapeutics for central nervous system (CNS) diseases and injury. Current phase I/II trials using stem cells in the CNS are the vanguard for the widely anticipated next generation of regenerative therapies and as such are pioneering the stem cell therapy process. While translation has typically been the purview of industry, academic researchers are increasingly driven to bring their findings toward treatments and face challenges in knowledge gap and resource access that are accentuated by the unique financial, manufacturing, scientific, and regulatory aspects of cell therapy. Solutions are envisioned that both address the significant unmet medical need and lead to increased funding for basic and translational research.     

Interplay between gene expression noise and regulatory network architecture

Complex regulatory networks orchestrate most cellular processes in biological systems. Genes in such networks are subject to expression noise, resulting in isogenic cell populations exhibiting cell-to-cell variation in protein levels. Increasing evidence suggests that cells have evolved regulatory strategies to limit, tolerate or amplify expression noise. In this context, fundamental questions arise: how can the architecture of gene regulatory networks generate, make use of or be constrained by expression noise? Here, we discuss the interplay between expression noise and gene regulatory network at different levels of organization, ranging from a single regulatory interaction to entire regulatory networks. We then consider how this interplay impacts a variety of phenomena, such as pathogenicity, disease, adaptation to changing environments, differential cell-fate outcome and incomplete or partial penetrance effects. Finally, we highlight recent technological developments that permit measurements at the single-cell level, and discuss directions for future research.     

Toward a systems biology of mouse inner ear organogenesis: gene expression pathways, patterns and network analysis

We describe the most comprehensive study to date on gene expression during mouse inner ear (IE) organogenesis. Samples were microdissected from mouse embryos at E9-E15 in half-day intervals, a period that spans all of IE organogenesis. These included separate dissections of all discernible IE substructures such as the cochlea, utricle, and saccule. All samples were analyzed on high density expression microarrays under strict statistical filters. Extensive confirmatory tests were performed, including RNA in situ hybridizations. More than 5000 genes significantly varied in expression according to developmental stage, tissue, or both and defined 28 distinct expression patterns. For example, upregulation of 315 genes provided a clear-cut "signature" of early events in IE specification. Additional, clear-cut, gene expression signatures marked specific structures such as the cochlea, utricle, or saccule throughout late IE development. Pathway analysis identified 53 signaling cascades enriched within the 28 patterns. Many novel pathways, not previously implicated in IE development, including beta-adrenergic, amyloid, estrogen receptor, circadian rhythm, and immune system pathways, were identified. Finally, we identified positional candidate genes in 54 uncloned nonsyndromic human deafness intervals. This detailed analysis provides many new insights into the spatial and temporal genetic specification of this complex organ system.     

Dynamic genome architecture in the nuclear space: regulation of gene expression in three dimensions

The regulation of gene expression is mediated by interactions between chromatin and protein complexes. The importance of where and when these interactions take place in the nucleus is currently a subject of intense investigation. Increasing evidence indicates that gene activation or silencing is often associated with repositioning of the locus relative to nuclear compartments and other genomic loci. At the same time, however, structural constraints impose limits on chromatin mobility. Understanding how the dynamic nature of the positioning of genetic material in the nuclear space and the higher-order architecture of the nucleus are integrated is therefore essential to our overall understanding of gene regulation.     

Exploring genome architecture through GOV: a WWW-based gene order visualizer

MOTIVATION: The past decade has seen extension in the methods of sequence analysis from single gene based to analyzing multiple genes and proteins simultaneously. Consequently, there is a need for software tools that will allow mining of these enormous datasets at genome level effectively. A key challenge is to make them user-friendly, available to a larger community and integrate with public domain software without much hassle. RESULTS: A web-based interactive computational tool is described for visualization and comparison of gene order from prokaryotic and selected viral genome data. Many intriguing similarities and differences in gene order of multiple genomes can be compared and revealed. The interface facilitates easy extraction of the nucleotide sequence of the gene of interest and BLAST analysis against GenBank at NCBI to provide insights into gene functions and orthologs of the gene in other species.     

Stemformatics: Visualisation and sharing of stem cell gene expression

Genome-scale technologies are increasingly adopted by the stem cell research community, because of the potential to uncover the molecular events most informative about a stem cell state. These technologies also present enormous challenges around the sharing and visualisation of data derived from different laboratories or under different experimental conditions. Stemformatics is an easy to use, publicly accessible portal that hosts a large collection of exemplar stem cell data. It provides fast visualisation of gene expression across a range of mouse and human datasets, with transparent links back to the original studies. One difficulty in the analysis of stem cell signatures is the paucity of public pathways/gene lists relevant to stem cell or developmental biology. Stemformatics provides a simple mechanism to create, share and analyse gene sets, providing a repository of community-annotated stem cell gene lists that are informative about pathways, lineage commitment, and common technical artefacts. Stemformatics can be accessed at stemformatics.org.     

GenCompass: a universal system for analysing gene expression for any genome

Microarrays have become indispensable tools for studying the gene expression of particular organisms on a genomic scale. However, despite its widespread use, there are several draw-backs to the current technology. First, it requires prior knowledge of the DNA sequence encoded in the organism of interest, and second, chips must be designed specifically for each genome, greatly increasing the initial cost incurred in manufacturing the arrays.     

RASSF1C modulates the expression of a stem cell renewal gene, PIWIL1

ABSTRACT: BACKGROUND: RASSF1A and RASSF1C are two major isoforms encoded by the Ras association domain family 1 (RASSF1) gene through alternative promoter selection and mRNA splicing. RASSF1A is a well established tumor suppressor gene. Unlike RASSF1A, RASSF1C appears to have growth promoting actions in lung cancer. In this article, we report on the identification of novel RASSF1C target genes in non small cell lung cancer (NSCLC). METHODS: Over-expression and siRNA techniques were used to alter RASSF1C expression in human lung cancer cells, and Affymetrix-microarray study was conducted using NCI-H1299 cells over-expressing RASSF1C to identify RASSF1C target genes. RESULTS: The microarray study intriguingly shows that RASSF1C modulates the expression of a number of genes that are involved in cancer development, cell growth and proliferation, cell death, and cell cycle. We have validated the expression of some target genes using qRT-PCR. We demonstrate that RASSF1C over-expression increases, and silencing of RASSF1C decreases, the expression of PIWIL1 gene in NSCLC cells using qRT-PCR, immunostaining, and Western blot analysis. We also show that RASSF1C over-expression induces phosphorylation of ERK1/2 in lung cancer cells, and inhibition of the MEK-ERK1/2 pathway suppresses the expression of PIWIL1 gene expression, suggesting that RASSF1C may exert its activities on some target genes such as PIWIL1 through the activation of the MEK-ERK1/2 pathway. Also, PIWIL1 expression is elevated in lung cancer cell lines compared to normal lung epithelial cells. CONCLUSIONS: Taken together, our findings provide significant data to propose a model for investigating the role of RASSF1C/PIWIL1 proteins in initiation and progression of lung cancer.     

Nuclear architecture in the light of gene expression and cell differentiation studies

It is evident that primary DNA sequences, that define genomes, are responsible for genome functions. However, the functional properties of chromatin are additionally regulated by heritable modifications known as epigenetic factors and, therefore, genomes should be also considered with respect to their 'epigenomes'. Nucleosome remodelling, DNA methylation and histone modifications are the most prominent epigenetic changes that play fundamental roles in the chromatin-mediated control of gene expression. Another important nuclear feature with functional relevance is the organization of mammalian chromatin into distinct chromosome territories which are surrounded by the interchromatin compartment that is necessary for transport of regulatory molecules to the targeted DNA. The inner structure of the chromosome territories, as well as the arrangement of the chromosomes within the interphase nuclei, has been found to be non-randomly organized. Therefore, a specific nuclear arrangement can be observed in many cellular processes, such as differentiation and tumour cell transformation.     

Toward a molecular classification of the gliomas: histopathology, molecular genetics, and gene expression profiling

As many as 100,000 new cases of brain tumor are diagnosed each year in the United States. About half of these are primary gliomas and the remaining half are metastatic tumors and non-glial primary tumors. Currently, gliomas are classified based on phenotypic characteristics. Recent progress in the elucidation of genetic alterations found in gliomas have raised the exciting possibility of using genetic and molecular analyses to resolve some of the problematic issues currently associated with the histological approach to glioma classification. Recently, immunohistochemical studies using novel proliferation markers have significantly advanced the assessment of tumor growth potential and the grading criteria of some tumor subtypes. Preliminary studies using cDNA array technologies suggest that the profiling of gene expression patterns may provide a novel and meaningful approach to glioma classification and subclassification. Furthermore, cDNA array technologies may also be used to identify candidate genes involved in glioma tumor development, invasion, and progression. This review summarizes current glioma classification schemes that are based on histopathological characteristics and discusses the potential for using cDNA array technology in the molecular classification of gliomas.     

GeneBins: a database for classifying gene expression data,with application to plant genome arrays

Background  

To interpret microarray experiments, several ontological analysis tools have been developed. However, current tools are limited to specific organisms.