Identification of miRNA-mRNA associations in hepatocellular carcinoma using hierarchical integrative model
Abstract 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...
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doaj-712d680b58c74d56a0990c3f36e2c3922021-04-02T12:34:35ZengBMCBMC Medical Genomics1755-87942020-03-0113111410.1186/s12920-020-0706-1Identification of miRNA-mRNA associations in hepatocellular carcinoma using hierarchical integrative modelRency S. Varghese0Yuan Zhou1Megan Barefoot2Yifan Chen3Cristina Di Poto4Abdalla Kara Balla5Everett Oliver6Zaki A. Sherif7Deepak Kumar8Alexander H. Kroemer9Mahlet G. Tadesse10Habtom W. Ressom11Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown UniversityDepartment of Oncology, Lombardi Comprehensive Cancer Center, Georgetown UniversityDepartment of Oncology, Lombardi Comprehensive Cancer Center, Georgetown UniversityDepartment of Oncology, Lombardi Comprehensive Cancer Center, Georgetown UniversityDepartment of Oncology, Lombardi Comprehensive Cancer Center, Georgetown UniversityMedStar Georgetown University HospitalDepartment of Oncology, Lombardi Comprehensive Cancer Center, Georgetown UniversityDepartment of Biochemistry & Molecular Biology, College of Medicine, Howard UniversityDepartment of Pharmaceutical Sciences, North Carolina Central UniversityMedStar Georgetown University HospitalDepartment of Mathematics and Statistics, Georgetown UniversityDepartment of Oncology, Lombardi Comprehensive Cancer Center, Georgetown UniversityAbstract 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.http://link.springer.com/article/10.1186/s12920-020-0706-1miRNAmRNAHierarchical integrative modelPathway analysishepatocellular carcinomaNext generation sequencing |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Rency S. Varghese Yuan Zhou Megan Barefoot Yifan Chen Cristina Di Poto Abdalla Kara Balla Everett Oliver Zaki A. Sherif Deepak Kumar Alexander H. Kroemer Mahlet G. Tadesse Habtom W. Ressom |
spellingShingle |
Rency S. Varghese Yuan Zhou Megan Barefoot Yifan Chen Cristina Di Poto Abdalla Kara Balla Everett Oliver Zaki A. Sherif Deepak Kumar Alexander H. Kroemer Mahlet G. Tadesse Habtom W. Ressom Identification of miRNA-mRNA associations in hepatocellular carcinoma using hierarchical integrative model BMC Medical Genomics miRNA mRNA Hierarchical integrative model Pathway analysis hepatocellular carcinoma Next generation sequencing |
author_facet |
Rency S. Varghese Yuan Zhou Megan Barefoot Yifan Chen Cristina Di Poto Abdalla Kara Balla Everett Oliver Zaki A. Sherif Deepak Kumar Alexander H. Kroemer Mahlet G. Tadesse Habtom W. Ressom |
author_sort |
Rency S. Varghese |
title |
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_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_sort |
identification of mirna-mrna associations in hepatocellular carcinoma using hierarchical integrative model |
publisher |
BMC |
series |
BMC Medical Genomics |
issn |
1755-8794 |
publishDate |
2020-03-01 |
description |
Abstract 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. |
topic |
miRNA mRNA Hierarchical integrative model Pathway analysis hepatocellular carcinoma Next generation sequencing |
url |
http://link.springer.com/article/10.1186/s12920-020-0706-1 |
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