Insight into transcription factor gene duplication from Caenorhabditis elegans Promoterome-driven expression patterns

BACKGROUND: The C. elegans Promoterome is a powerful resource for revealing the regulatory mechanisms by which transcription is controlled pan-genomically. Transcription factors will form the core of any systems biology model of genome control and therefore the promoter activity of Promoterome inserts for C. elegans transcription factor genes was examined, in vivo, with a reporter gene approach. RESULTS: Transgenic C. elegans strains were generated for 366 transcription factor promoter/gfp reporter gene fusions. GFP distributions were determined, and then summarized with reference to developmental stage and cell type. Reliability of these data was demonstrated by comparison to previously described gene product distributions. A detailed consideration of the results for one C. elegans transcription factor gene family, the Six family, comprising ceh-32, ceh-33, ceh-34 and unc-39 illustrates the value of these analyses. The high proportion of Promoterome reporter fusions that drove GFP expression, compared to previous studies, led to the hypothesis that transcription factor genes might be involved in local gene duplication events less frequently than other genes. Comparison of transcription factor genes of C. elegans and Caenorhabditis briggsae was therefore carried out and revealed very few examples of functional gene duplication since the divergence of these species for most, but not all, transcription factor gene families. CONCLUSION: Examining reporter expression patterns for hundreds of promoters informs, and thereby improves, interpretation of this data type. Genes encoding transcription factors involved in intrinsic developmental control processes appear acutely sensitive to changes in gene dosage through local gene duplication, on an evolutionary time scale

Multimodality Treatment with Conventional Transcatheter Arterial Chemoembolization and Radiofrequency Ablation for Unresectable Hepatocellular Carcinoma

Background/Aims: To evaluate the efficacy of multimodality treatment consisting of conventional transcatheter arterial chemoembolization (TACE) and radiofrequency ablation (RFA) in patients with non-resectable and non-ablatable hepatocellular carcinoma (HCC). Methods: In this retrospective study, 85 consecutive patients with HCC (59 solitary, 29 multifocal HCC) received TACE followed by RFA between 2001 and 2010. The mean number of tumors per patient was 1.6 +/- 0.7 with a mean size of 3.0 +/- 0.9 cm. Both local efficacy and patient survival were evaluated. Results: Of 120 treated HCCs, 99 (82.5%) showed a complete response (CR), while in 21 HCCs (17.5%) a partial response was depicted. Patients with solitary HCC revealed CR in 91% (51/56); in patients with multifocal HCC (n = 29) CR was achieved in 75% (48 of 64 HCCs). The median survival for all patients was 25.5 months. The 1-, 2-, 3- and 5-year survival rates were 84.6, 58.7, 37.6 and 14.6%, respectively. Statistical analysis revealed a significant difference in survival between Barcelona Clinic Liver Cancer (BCLC) A (73.4 months) and B (50.3 months) patients, while analyses failed to show a difference for Child-Pugh score, Cancer of Liver Italian Program (CLIP) score and tumor distribution pattern. Conclusion: TACE combined with RFA provides an effective treatment approach with high local tumor control rates and promising survival data, especially for BCLC A patients. Randomized trials are needed to compare this multimodality approach with a single modality approach for early-stage HCC. Copyright (C) 2011 S. Karger AG, Base

Self-assembly, Self-organization, Nanotechnology and vitalism

International audienceOver the past decades, self-assembly has attracted a lot of research attention and transformed the relations between chemistry, materials science and biology. The paper explores the impact of the current interest in self-assembly techniques on the traditional debate over the nature of life. The first section describes three different research programs of self-assembly in nanotechnology in order to characterize their metaphysical implications: -1- Hybridization ( using the building blocks of living systems for making devices and machines) ; -2- Biomimetics (making artifacts mimicking nature); -3- Integration (a composite of the two previous strategies). The second section focused on the elusive boundary between selfassembly and self-organization tries to map out the various positions adopted by the promoters of self-assembly on the issue of vitalism

Quantifying Phenotypic Variation in Isogenic Caenorhabditis elegans Expressing Phsp-16.2::gfp by Clustering 2D Expression Patterns

Isogenic populations of animals still show a surprisingly large amount of phenotypic variation between individuals. Using a GFP reporter that has been shown to predict longevity and resistance to stress in isogenic populations of the nematode Caenorhabditis elegans, we examined residual variation in expression of this GFP reporter. We found that when we separated the populations into brightest 3% and dimmest 3% we also saw variation in relative expression patterns that distinguished the bright and dim worms. Using a novel image processing method which is capable of directly analyzing worm images, we found that bright worms (after normalization to remove variation between bright and dim worms) had expression patterns that correlated with other bright worms but that dim worms fell into two distinct expression patterns. We have analysed a small set of worms with confocal microscopy to validate these findings, and found that the activity loci in these clusters are caused by extremely bright intestine cells. We also found that the vast majority of the fluorescent signal for all worms came from intestinal cells as well, which may indicate that the activity of intestinal cells is responsible for the observed patterns. Phenotypic variation in C. elegans is still not well understood but our proposed novel method to analyze complex expression patterns offers a way to enable a better understanding

Optimally splitting cases for training and testing high dimensional classifiers

<p>Abstract</p> <p>Background</p> <p>We consider the problem of designing a study to develop a predictive classifier from high dimensional data. A common study design is to split the sample into a training set and an independent test set, where the former is used to develop the classifier and the latter to evaluate its performance. In this paper we address the question of what proportion of the samples should be devoted to the training set. How does this proportion impact the mean squared error (MSE) of the prediction accuracy estimate?</p> <p>Results</p> <p>We develop a non-parametric algorithm for determining an optimal splitting proportion that can be applied with a specific dataset and classifier algorithm. We also perform a broad simulation study for the purpose of better understanding the factors that determine the best split proportions and to evaluate commonly used splitting strategies (1/2 training or 2/3 training) under a wide variety of conditions. These methods are based on a decomposition of the MSE into three intuitive component parts.</p> <p>Conclusions</p> <p>By applying these approaches to a number of synthetic and real microarray datasets we show that for linear classifiers the optimal proportion depends on the overall number of samples available and the degree of differential expression between the classes. The optimal proportion was found to depend on the full dataset size (n) and classification accuracy - with higher accuracy and smaller <it>n </it>resulting in more assigned to the training set. The commonly used strategy of allocating 2/3rd of cases for training was close to optimal for reasonable sized datasets (<it>n </it>≥ 100) with strong signals (i.e. 85% or greater full dataset accuracy). In general, we recommend use of our nonparametric resampling approach for determing the optimal split. This approach can be applied to any dataset, using any predictor development method, to determine the best split.</p

In Vivo RNAi Screening Identifies Regulators of Actin Dynamics as Key Determinants of Lymphoma Progression

April 1, 2010Mouse models have markedly improved our understanding of cancer development and tumor biology. However, these models have shown limited efficacy as tractable systems for unbiased genetic experimentation. Here, we report the adaptation of loss-of-function screening to mouse models of cancer. Specifically, we have been able to introduce a library of shRNAs into individual mice using transplantable Eμ-myc lymphoma cells. This approach has allowed us to screen nearly 1,000 genetic alterations in the context of a single tumor-bearing mouse. These experiments have identified a central role for regulators of actin dynamics and cell motility in lymphoma cell homeostasis in vivo. Validation experiments confirmed that these proteins represent bona fide lymphoma drug targets. Additionally, suppression of two of these targets, Rac2 and twinfilin, potentiated the action of the front-line chemotherapeutic vincristine, suggesting a critical relationship between cell motility and tumor relapse in hematopoietic malignancies.National Institutes of Health (U.S.) (RO1 CA128803-01)Massachusetts Institute of Technology. Dept. of Biology (Training Grant)Massachusetts Institute of Technology. Undergraduate Research Opportunities ProgramNational Cancer Institute (U.S.). Integrative Cancer Biology Program (Grant 1-U54-CA112967

Variable Pathogenicity Determines Individual Lifespan in Caenorhabditis elegans

A common property of aging in all animals is that chronologically and genetically identical individuals age at different rates. To unveil mechanisms that influence aging variability, we identified markers of remaining lifespan for Caenorhabditis elegans. In transgenic lines, we expressed fluorescent reporter constructs from promoters of C. elegans genes whose expression change with age. The expression levels of aging markers in individual worms from a young synchronous population correlated with their remaining lifespan. We identified eight aging markers, with the superoxide dismutase gene sod-3 expression being the best single predictor of remaining lifespan. Correlation with remaining lifespan became stronger if expression from two aging markers was monitored simultaneously, accounting for up to 49% of the variation in individual lifespan. Visualizing the physiological age of chronologically-identical individuals allowed us to show that a major source of lifespan variability is different pathogenicity from individual to individual and that the mechanism involves variable activation of the insulin-signaling pathway

Gene expression profiling of gliomas: merging genomic and histopathological classification for personalised therapy

The development of DNA microarray technologies over the past decade has revolutionised translational cancer research. These technologies were originally hailed as more objective, comprehensive replacements for traditional histopathological cancer classification systems, based on microscopic morphology. Although DNA microarray-based gene expression profiling (GEP) remains unlikely in the near term to completely replace morphological classification of primary brain tumours, specifically the diffuse gliomas, GEP has confirmed that significant molecular heterogeneity exists within the various morphologically defined gliomas, particularly glioblastoma (GBM). Herein, we provide a 10-year progress report on human glioma GEP, with focus on development of clinical diagnostic tests to identify molecular subtypes, uniquely responsive to adjuvant therapies. Such progress may lead to a more precise classification system that accurately reflects the cellular, genetic, and molecular basis of gliomagenesis, a prerequisite for identifying subsets uniquely responsive to specific adjuvant therapies, and ultimately in achieving individualised clinical care of glioma patients