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An integrated network of microRNA and gene expression in ovarian cancer

BACKGROUND: Ovarian cancer is a deadly female reproductive cancer. Understanding the biological mechanisms underlying ovarian cancer could help lead to quicker and more accurate diagnosis and more effective treatments. Both changes in microRNA(miRNA) expression and miRNA/mRNA dysregulation have been...

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Autores principales: Quitadamo, Andrew, Tian, Lu, Hall, Benika, Shi, Xinghua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4402579/
https://www.ncbi.nlm.nih.gov/pubmed/25860109
http://dx.doi.org/10.1186/1471-2105-16-S5-S5
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author Quitadamo, Andrew
Tian, Lu
Hall, Benika
Shi, Xinghua
author_facet Quitadamo, Andrew
Tian, Lu
Hall, Benika
Shi, Xinghua
author_sort Quitadamo, Andrew
collection PubMed
description BACKGROUND: Ovarian cancer is a deadly female reproductive cancer. Understanding the biological mechanisms underlying ovarian cancer could help lead to quicker and more accurate diagnosis and more effective treatments. Both changes in microRNA(miRNA) expression and miRNA/mRNA dysregulation have been associated with ovarian cancer. With the availability of whole-genome miRNA and mRNA sequencing we now have new potentials to study these associations. In this study, we performed a comprehensive analysis of miRNA and mRNA expression in ovarian cancer using an integrative network approach combined with association analysis. RESULTS: We developed an integrative approach to construct a network that illustrates the complex interplay among miRNA and gene expression from a systems perspective. Our method is composed of expanding networks from eQTL associations, building network associations in eQTL analysis, and then combine the networks into an integrated network. This integrated network takes account of miRNA expression quantitative trait loci (eQTL) associations, miRNAs and their targets, protein-protein interactions, co-expressions among miRNAs and genes respectively. Applied to the ovarian cancer data set from The Cancer Genome Atlas (TCGA), we created an integrated network with 167 nodes containing 108 miRNA-target interactions and 145 from protein-protein interactions, starting from 44 initial eQTLs. This integrated network encompassed 26 genes and 14 miRNAs associated with cancer. In particular, 11 genes and 12 miRNAs in the integrated network are associated with ovarian cancer. CONCLUSION: We demonstrated an integrated network approach that integrates multiple data sources at a systems level. We applied this approach to the TCGA ovarian cancer dataset, and constructed a network that provided a more inclusive view of miRNA and gene expression in ovarian cancer. This network included four separate types of interactions among miRNAs and genes. Simply analyzing each interaction component in isolation, such as the eQTL associations, the miRNA-target interactions or the protein-protein interactions, would create a much more limited network than the integrated one.
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spelling pubmed-44025792015-04-29 An integrated network of microRNA and gene expression in ovarian cancer Quitadamo, Andrew Tian, Lu Hall, Benika Shi, Xinghua BMC Bioinformatics Proceedings BACKGROUND: Ovarian cancer is a deadly female reproductive cancer. Understanding the biological mechanisms underlying ovarian cancer could help lead to quicker and more accurate diagnosis and more effective treatments. Both changes in microRNA(miRNA) expression and miRNA/mRNA dysregulation have been associated with ovarian cancer. With the availability of whole-genome miRNA and mRNA sequencing we now have new potentials to study these associations. In this study, we performed a comprehensive analysis of miRNA and mRNA expression in ovarian cancer using an integrative network approach combined with association analysis. RESULTS: We developed an integrative approach to construct a network that illustrates the complex interplay among miRNA and gene expression from a systems perspective. Our method is composed of expanding networks from eQTL associations, building network associations in eQTL analysis, and then combine the networks into an integrated network. This integrated network takes account of miRNA expression quantitative trait loci (eQTL) associations, miRNAs and their targets, protein-protein interactions, co-expressions among miRNAs and genes respectively. Applied to the ovarian cancer data set from The Cancer Genome Atlas (TCGA), we created an integrated network with 167 nodes containing 108 miRNA-target interactions and 145 from protein-protein interactions, starting from 44 initial eQTLs. This integrated network encompassed 26 genes and 14 miRNAs associated with cancer. In particular, 11 genes and 12 miRNAs in the integrated network are associated with ovarian cancer. CONCLUSION: We demonstrated an integrated network approach that integrates multiple data sources at a systems level. We applied this approach to the TCGA ovarian cancer dataset, and constructed a network that provided a more inclusive view of miRNA and gene expression in ovarian cancer. This network included four separate types of interactions among miRNAs and genes. Simply analyzing each interaction component in isolation, such as the eQTL associations, the miRNA-target interactions or the protein-protein interactions, would create a much more limited network than the integrated one. BioMed Central 2015-03-18 /pmc/articles/PMC4402579/ /pubmed/25860109 http://dx.doi.org/10.1186/1471-2105-16-S5-S5 Text en Copyright © 2015 Quitadamo et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Proceedings
Quitadamo, Andrew
Tian, Lu
Hall, Benika
Shi, Xinghua
An integrated network of microRNA and gene expression in ovarian cancer
title An integrated network of microRNA and gene expression in ovarian cancer
title_full An integrated network of microRNA and gene expression in ovarian cancer
title_fullStr An integrated network of microRNA and gene expression in ovarian cancer
title_full_unstemmed An integrated network of microRNA and gene expression in ovarian cancer
title_short An integrated network of microRNA and gene expression in ovarian cancer
title_sort integrated network of microrna and gene expression in ovarian cancer
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4402579/
https://www.ncbi.nlm.nih.gov/pubmed/25860109
http://dx.doi.org/10.1186/1471-2105-16-S5-S5
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