2 results
Analysis of the Growth Control Network Specific for Human Lung Adenocarcinoma Cells
- G. Pinna, A. Zinovyev, N. Araujo, N. Morozova, A. Harel-Bellan
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- Journal:
- Mathematical Modelling of Natural Phenomena / Volume 7 / Issue 1 / 2012
- Published online by Cambridge University Press:
- 25 January 2012, pp. 337-368
- Print publication:
- 2012
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- Article
- Export citation
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Many cancer-associated genes and pathways remain to be identified in order to clarify the molecular mechanisms underlying cancer progression. In this area, genome-wide loss-of-function screens appear to be powerful biological tools, allowing the accumulation of large amounts of data. However, this approach currently lacks analytical tools to exploit the data with maximum efficiency, for which systems biology methods analyzing complex cellular networks may be extremely helpful. In this article we report such a systems biology strategy based on the construction of a Network for a biological process and specific for a given cell system (cell type). The networks are created from genome-wide loss-of-function screen datasets. We also propose tools to analyze network properties. As one of the tools, we suggest a mathematical model for discrimination between two distinct cell processes that may be affected by knocking down the activity of a gene, i. e., a decreased cell number may be caused by arrested cell proliferation or enhanced cell death. Next we show how this discrimination between the two cell processes helps to construct two corresponding subnetworks. Finally, we demonstrate an application of the proposed strategy to the identification and characterization of putative novel genes and pathways significant for the control of lung cancer cell growth, based on the results of a genome-wide proliferation/viability loss-of-function screen of human lung adenocarcinoma cells.
30 - MiRNAs in skeletal muscle differentiation
- from V - MicroRNAs in disease biology
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- By Irina Naguibneva, Laboratoire Oncogenese, Differenciation et Transduction du Signal CNRS UPR 9079 Institut Andre Lwoff Batiment B, 1er Etage 7 rue Guy Moquet 94800 Villejuif France, Anna Polesskaya, Laboratoire Oncogenese, Differenciation et Transduction du Signal CNRS UPR 9079 Institut Andre Lwoff Batiment B, 1er Etage 7 rue Guy Moquet 94800 Villejuif France, Annick Harel-Bellan, Laboratoire Oncogenese, Differenciation et Transduction du Signal CNRS UPR 9079 Institut Andre Lwoff Batiment B, 1er Etage 7 rue Guy Moquet 94800 Villejuif France
- Edited by Krishnarao Appasani
- Foreword by Sidney Altman, Victor R. Ambros
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- Book:
- MicroRNAs
- Published online:
- 22 August 2009
- Print publication:
- 20 December 2007, pp 392-404
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- Chapter
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Summary
Introduction
MicroRNAs (miRNAs) represent an important class of short natural RNAs that act as post-transcriptional regulators of gene expression. Genetic studies in Caenorhabditis elegans and Drosophila revealed that miRNAs are involved in fine tuning the spatial and temporal regulation of developmental events, including precursor cell proliferation, differentiation and programmed death (Ambros, 2003; Brennecke et al., 2003; Sempere et al., 2003, Xu et al., 2003; Biemar et al., 2005). MiRNAs have been found essentially in every cell type analyzed to date. A recent systematic analysis of spatial expression of miRNA in developing zebrafish embryos showed that most tissues have a unique time-dependent pattern of miRNA expression (Wienholds et al., 2005). In silico methods predicted that the individual miRNAs have, on average, hundreds of target mRNAs, suggesting that miRNAs have enormous regulatory roles in different genetic programs (Lewis et al., 2003; Brennecke et al., 2005; Krek et al., 2005; Xie et al., 2005). However, the number of functional miRNA/target pairs experimentally characterized to date is minimal.
We have addressed the function of miRNAs in mammalian skeletal muscle. Muscle formation (Figure 30.1) involves the proliferation of myoblast precursor cells, which subsequently exit from the cell cycle and enter a terminal differentiation program that includes myoblast fusion into large multi-nucleated cells (myotubes) and expression of muscle specific markers such as myosin heavy chain (MHC) and muscle creatine kinase (MCK) (Figure 30.1). Differentiation can be recapitulated in ex vivo models, using either totipotent ES cells directed toward the muscle lineage (Dinsmore et al., 1998), or established myoblast cell lines that by default enter the skeletal muscle differentiation pathway when they are deprived of growth factors (Bains et al., 1984).
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