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Time-course gene profiling and networks in demethylated retinoblastoma cell line

Retinoblastoma, a very aggressive cancer of the developing retina, initiatiates by the biallelic loss of RB1 gene, and progresses very quickly following RB1 inactivation. While its genome is stable, multiple pathways are deregulated, also epigenetically. After reviewing the main findings in relation...

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Autores principales: Malusa, Federico, Taranta, Monia, Zaki, Nazar, Cinti, Caterina, Capobianco, Enrico
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4695145/
https://www.ncbi.nlm.nih.gov/pubmed/26143641
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author Malusa, Federico
Taranta, Monia
Zaki, Nazar
Cinti, Caterina
Capobianco, Enrico
author_facet Malusa, Federico
Taranta, Monia
Zaki, Nazar
Cinti, Caterina
Capobianco, Enrico
author_sort Malusa, Federico
collection PubMed
description Retinoblastoma, a very aggressive cancer of the developing retina, initiatiates by the biallelic loss of RB1 gene, and progresses very quickly following RB1 inactivation. While its genome is stable, multiple pathways are deregulated, also epigenetically. After reviewing the main findings in relation with recently validated markers, we propose an integrative bioinformatics approach to include in the previous group new markers obtained from the analysis of a single cell line subject to epigenetic treatment. In particular, differentially expressed genes are identified from time course microarray experiments on the WERI-RB1 cell line treated with 5-Aza-2′-deoxycytidine (decitabine; DAC). By inducing demethylation of CpG island in promoter genes that are involved in biological processes, for instance apoptosis, we performed the following main integrative analysis steps: i) Gene expression profiling at 48h, 72h and 96h after DAC treatment; ii) Time differential gene co-expression networks and iii) Context-driven marker association (transcriptional factor regulated protein networks, master regulatory paths). The observed DAC-driven temporal profiles and regulatory connectivity patterns are obtained by the application of computational tools, with support from curated literature. It is worth emphasizing the capacity of networks to reconcile multi-type evidences, thus generating testable hypotheses made available by systems scale predictive inference power. Despite our small experimental setting, we propose through such integrations valuable impacts of epigenetic treatment in terms of gene expression measurements, and then validate evidenced apoptotic effects.
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spelling pubmed-46951452016-01-26 Time-course gene profiling and networks in demethylated retinoblastoma cell line Malusa, Federico Taranta, Monia Zaki, Nazar Cinti, Caterina Capobianco, Enrico Oncotarget Research Paper Retinoblastoma, a very aggressive cancer of the developing retina, initiatiates by the biallelic loss of RB1 gene, and progresses very quickly following RB1 inactivation. While its genome is stable, multiple pathways are deregulated, also epigenetically. After reviewing the main findings in relation with recently validated markers, we propose an integrative bioinformatics approach to include in the previous group new markers obtained from the analysis of a single cell line subject to epigenetic treatment. In particular, differentially expressed genes are identified from time course microarray experiments on the WERI-RB1 cell line treated with 5-Aza-2′-deoxycytidine (decitabine; DAC). By inducing demethylation of CpG island in promoter genes that are involved in biological processes, for instance apoptosis, we performed the following main integrative analysis steps: i) Gene expression profiling at 48h, 72h and 96h after DAC treatment; ii) Time differential gene co-expression networks and iii) Context-driven marker association (transcriptional factor regulated protein networks, master regulatory paths). The observed DAC-driven temporal profiles and regulatory connectivity patterns are obtained by the application of computational tools, with support from curated literature. It is worth emphasizing the capacity of networks to reconcile multi-type evidences, thus generating testable hypotheses made available by systems scale predictive inference power. Despite our small experimental setting, we propose through such integrations valuable impacts of epigenetic treatment in terms of gene expression measurements, and then validate evidenced apoptotic effects. Impact Journals LLC 2015-06-25 /pmc/articles/PMC4695145/ /pubmed/26143641 Text en Copyright: © 2015 Malusa et al. http://creativecommons.org/licenses/by/2.5/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Malusa, Federico
Taranta, Monia
Zaki, Nazar
Cinti, Caterina
Capobianco, Enrico
Time-course gene profiling and networks in demethylated retinoblastoma cell line
title Time-course gene profiling and networks in demethylated retinoblastoma cell line
title_full Time-course gene profiling and networks in demethylated retinoblastoma cell line
title_fullStr Time-course gene profiling and networks in demethylated retinoblastoma cell line
title_full_unstemmed Time-course gene profiling and networks in demethylated retinoblastoma cell line
title_short Time-course gene profiling and networks in demethylated retinoblastoma cell line
title_sort time-course gene profiling and networks in demethylated retinoblastoma cell line
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4695145/
https://www.ncbi.nlm.nih.gov/pubmed/26143641
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