Entropy measures quantify global splicing disorders in cancer
| Autor: | Samuel Granjeaud, Denis Puthier, William Ritchie, Daniel Gautheret |
|---|---|
| Přispěvatelé: | Technologies avancées pour le génôme et la clinique (TAGC), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Institut de génétique et microbiologie [Orsay] (IGM), Université Paris-Sud - Paris 11 (UP11)-Centre National de la Recherche Scientifique (CNRS), This work was supported in part by European Commission grant LSHG-CT-2003-503329 (The Alternative Transcript Diversity Consortium) and Institut National du Cancer grant PL0079., Beaunay, Stephanie |
| Jazyk: | angličtina |
| Rok vydání: | 2008 |
| Předmět: |
MESH: Neoplasm Proteins
Polyadenylation Entropy MESH: Gene Targeting MESH: Variation (Genetics) 0302 clinical medicine Neoplasms Gene expression MESH: Neoplasms MESH: Models Genetic Biology (General) Genetics Regulation of gene expression 0303 health sciences Ecology MESH: Alternative Splicing MESH: Genetic Predisposition to Disease Genetics and Genomics/Gene Expression MESH: Gene Expression Regulation Neoplastic MESH: Entropy Neoplasm Proteins 3. Good health Gene Expression Regulation Neoplastic Computational Theory and Mathematics 030220 oncology & carcinogenesis Modeling and Simulation Gene Targeting RNA splicing Research Article MESH: Mutation QH301-705.5 Computational biology Biology 03 medical and health sciences Cellular and Molecular Neuroscience MESH: Computer Simulation Protein splicing MESH: Protein Splicing Biomarkers Tumor [SDV.BBM] Life Sciences [q-bio]/Biochemistry Molecular Biology Humans Protein Splicing Computational Biology/Alternative Splicing Computer Simulation Genetic Predisposition to Disease splice [SDV.BBM]Life Sciences [q-bio]/Biochemistry Molecular Biology Molecular Biology Gene Ecology Evolution Behavior and Systematics 030304 developmental biology Models Statistical MESH: Humans Models Genetic Alternative splicing Genetic Variation Alternative Splicing Mutation MESH: Tumor Markers Biological MESH: Models Statistical |
| Zdroj: | PLoS Computational Biology PLoS Computational Biology, Public Library of Science, 2008, 4 (3), pp.e1000011. ⟨10.1371/journal.pcbi.1000011⟩ PLoS Computational Biology, Vol 4, Iss 3, p e1000011 (2008) PLoS Computational Biology, 2008, 4 (3), pp.e1000011. ⟨10.1371/journal.pcbi.1000011⟩ |
| ISSN: | 1553-734X 1553-7358 |
| DOI: | 10.1371/journal.pcbi.1000011⟩ |
| Popis: | Most mammalian genes are able to express several splice variants in a phenomenon known as alternative splicing. Serious alterations of alternative splicing occur in cancer tissues, leading to expression of multiple aberrant splice forms. Most studies of alternative splicing defects have focused on the identification of cancer-specific splice variants as potential therapeutic targets. Here, we examine instead the bulk of non-specific transcript isoforms and analyze their level of disorder using a measure of uncertainty called Shannon's entropy. We compare isoform expression entropy in normal and cancer tissues from the same anatomical site for different classes of transcript variations: alternative splicing, polyadenylation, and transcription initiation. Whereas alternative initiation and polyadenylation show no significant gain or loss of entropy between normal and cancer tissues, alternative splicing shows highly significant entropy gains for 13 of the 27 cancers studied. This entropy gain is characterized by a flattening in the expression profile of normal isoforms and is correlated to the level of estimated cellular proliferation in the cancer tissue. Interestingly, the genes that present the highest entropy gain are enriched in splicing factors. We provide here the first quantitative estimate of splicing disruption in cancer. The expression of normal splice variants is widely and significantly disrupted in at least half of the cancers studied. We postulate that such splicing disorders may develop in part from splicing alteration in key splice factors, which in turn significantly impact multiple target genes. Author Summary RNA splicing is the process by which gene products are pieced together to form a mature messenger RNA (mRNA). In normal cells, RNA splicing is a tightly controlled process that leads to production of a well-defined set of mRNAs. Cancer cells, however, often produce aberrant, mis-spliced mRNAs. Such disorders have not been quantified to date. To this end, we use a well-known measure of disorder called Shannon's entropy. We show that overall splicing disorders are highly significant in many cancers, and that the extent of disorder may be correlated to the level of cell proliferation in each tumor. Surprisingly, genes that control the splicing mechanism are unusually frequent among genes affected by splicing disorders. This suggests that cancer cells may withstand harmful chain reactions in which splicing defects in key regulatory genes would in turn cause extensive splicing damage. As mis-spliced mRNAs are widely studied for cancer diagnosis, awareness of these global disorders is important to distinguish reliable cancer markers from background noise. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|