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Identification of miRNA-mRNA associations in hepatocellular carcinoma using hierarchical integrative model

BACKGROUND: The established role miRNA-mRNA regulation of gene expression has in oncogenesis highlights the importance of integrating miRNA with downstream mRNA targets. These findings call for investigations aimed at identifying disease-associated miRNA-mRNA pairs. Hierarchical integrative models (...

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Autores principales: Varghese, Rency S., Zhou, Yuan, Barefoot, Megan, Chen, Yifan, Di Poto, Cristina, Balla, Abdalla Kara, Oliver, Everett, Sherif, Zaki A., Kumar, Deepak, Kroemer, Alexander H., Tadesse, Mahlet G., Ressom, Habtom W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7106691/
https://www.ncbi.nlm.nih.gov/pubmed/32228601
http://dx.doi.org/10.1186/s12920-020-0706-1
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author Varghese, Rency S.
Zhou, Yuan
Barefoot, Megan
Chen, Yifan
Di Poto, Cristina
Balla, Abdalla Kara
Oliver, Everett
Sherif, Zaki A.
Kumar, Deepak
Kroemer, Alexander H.
Tadesse, Mahlet G.
Ressom, Habtom W.
author_facet Varghese, Rency S.
Zhou, Yuan
Barefoot, Megan
Chen, Yifan
Di Poto, Cristina
Balla, Abdalla Kara
Oliver, Everett
Sherif, Zaki A.
Kumar, Deepak
Kroemer, Alexander H.
Tadesse, Mahlet G.
Ressom, Habtom W.
author_sort Varghese, Rency S.
collection PubMed
description BACKGROUND: The established role miRNA-mRNA regulation of gene expression has in oncogenesis highlights the importance of integrating miRNA with downstream mRNA targets. These findings call for investigations aimed at identifying disease-associated miRNA-mRNA pairs. Hierarchical integrative models (HIM) offer the opportunity to uncover the relationships between disease and the levels of different molecules measured in multiple omic studies. METHODS: The HIM model we formulated for analysis of mRNA-seq and miRNA-seq data can be specified with two levels: (1) a mechanistic submodel relating mRNAs to miRNAs, and (2) a clinical submodel relating disease status to mRNA and miRNA, while accounting for the mechanistic relationships in the first level. RESULTS: mRNA-seq and miRNA-seq data were acquired by analysis of tumor and normal liver tissues from 30 patients with hepatocellular carcinoma (HCC). We analyzed the data using HIM and identified 157 significant miRNA-mRNA pairs in HCC. The majority of these molecules have already been independently identified as being either diagnostic, prognostic, or therapeutic biomarker candidates for HCC. These pairs appear to be involved in processes contributing to the pathogenesis of HCC involving inflammation, regulation of cell cycle, apoptosis, and metabolism. For further evaluation of our method, we analyzed miRNA-seq and mRNA-seq data from TCGA network. While some of the miRNA-mRNA pairs we identified by analyzing both our and TCGA data are previously reported in the literature and overlap in regulation and function, new pairs have been identified that may contribute to the discovery of novel targets. CONCLUSION: The results strongly support the hypothesis that miRNAs are important regulators of mRNAs in HCC. Furthermore, these results emphasize the biological relevance of studying miRNA-mRNA pairs.
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spelling pubmed-71066912020-04-01 Identification of miRNA-mRNA associations in hepatocellular carcinoma using hierarchical integrative model Varghese, Rency S. Zhou, Yuan Barefoot, Megan Chen, Yifan Di Poto, Cristina Balla, Abdalla Kara Oliver, Everett Sherif, Zaki A. Kumar, Deepak Kroemer, Alexander H. Tadesse, Mahlet G. Ressom, Habtom W. BMC Med Genomics Research Article BACKGROUND: The established role miRNA-mRNA regulation of gene expression has in oncogenesis highlights the importance of integrating miRNA with downstream mRNA targets. These findings call for investigations aimed at identifying disease-associated miRNA-mRNA pairs. Hierarchical integrative models (HIM) offer the opportunity to uncover the relationships between disease and the levels of different molecules measured in multiple omic studies. METHODS: The HIM model we formulated for analysis of mRNA-seq and miRNA-seq data can be specified with two levels: (1) a mechanistic submodel relating mRNAs to miRNAs, and (2) a clinical submodel relating disease status to mRNA and miRNA, while accounting for the mechanistic relationships in the first level. RESULTS: mRNA-seq and miRNA-seq data were acquired by analysis of tumor and normal liver tissues from 30 patients with hepatocellular carcinoma (HCC). We analyzed the data using HIM and identified 157 significant miRNA-mRNA pairs in HCC. The majority of these molecules have already been independently identified as being either diagnostic, prognostic, or therapeutic biomarker candidates for HCC. These pairs appear to be involved in processes contributing to the pathogenesis of HCC involving inflammation, regulation of cell cycle, apoptosis, and metabolism. For further evaluation of our method, we analyzed miRNA-seq and mRNA-seq data from TCGA network. While some of the miRNA-mRNA pairs we identified by analyzing both our and TCGA data are previously reported in the literature and overlap in regulation and function, new pairs have been identified that may contribute to the discovery of novel targets. CONCLUSION: The results strongly support the hypothesis that miRNAs are important regulators of mRNAs in HCC. Furthermore, these results emphasize the biological relevance of studying miRNA-mRNA pairs. BioMed Central 2020-03-30 /pmc/articles/PMC7106691/ /pubmed/32228601 http://dx.doi.org/10.1186/s12920-020-0706-1 Text en © The Author(s). 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.
spellingShingle Research Article
Varghese, Rency S.
Zhou, Yuan
Barefoot, Megan
Chen, Yifan
Di Poto, Cristina
Balla, Abdalla Kara
Oliver, Everett
Sherif, Zaki A.
Kumar, Deepak
Kroemer, Alexander H.
Tadesse, Mahlet G.
Ressom, Habtom W.
Identification of miRNA-mRNA associations in hepatocellular carcinoma using hierarchical integrative model
title Identification of miRNA-mRNA associations in hepatocellular carcinoma using hierarchical integrative model
title_full Identification of miRNA-mRNA associations in hepatocellular carcinoma using hierarchical integrative model
title_fullStr Identification of miRNA-mRNA associations in hepatocellular carcinoma using hierarchical integrative model
title_full_unstemmed Identification of miRNA-mRNA associations in hepatocellular carcinoma using hierarchical integrative model
title_short Identification of miRNA-mRNA associations in hepatocellular carcinoma using hierarchical integrative model
title_sort identification of mirna-mrna associations in hepatocellular carcinoma using hierarchical integrative model
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7106691/
https://www.ncbi.nlm.nih.gov/pubmed/32228601
http://dx.doi.org/10.1186/s12920-020-0706-1
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