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Integrated multi-omics analysis of genomics, epigenomics, and transcriptomics in ovarian carcinoma

In this study, we identified prognostic biomarkers in ovarian carcinoma by integrating multi-omics DNA copy number variation (CNV) and methylation variation (MET) data. CNV, MET, and messenger RNA (mRNA) expression were examined in 351 ovarian carcinoma patients. Genes for which expression was corre...

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Autores principales: Zheng, Mingjun, Hu, Yuexin, Gou, Rui, Wang, Jing, Nie, Xin, Li, Xiao, Liu, Qing, Liu, Juanjuan, Lin, Bei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6629004/
https://www.ncbi.nlm.nih.gov/pubmed/31257224
http://dx.doi.org/10.18632/aging.102047
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author Zheng, Mingjun
Hu, Yuexin
Gou, Rui
Wang, Jing
Nie, Xin
Li, Xiao
Liu, Qing
Liu, Juanjuan
Lin, Bei
author_facet Zheng, Mingjun
Hu, Yuexin
Gou, Rui
Wang, Jing
Nie, Xin
Li, Xiao
Liu, Qing
Liu, Juanjuan
Lin, Bei
author_sort Zheng, Mingjun
collection PubMed
description In this study, we identified prognostic biomarkers in ovarian carcinoma by integrating multi-omics DNA copy number variation (CNV) and methylation variation (MET) data. CNV, MET, and messenger RNA (mRNA) expression were examined in 351 ovarian carcinoma patients. Genes for which expression was correlated with DNA copy-number or DNA methylation were identified; three ovarian carcinoma gene subtypes were defined based on these correlations. Overall survival and B cell scores were lower, while the macrophage cell score was higher, in the DNA imprinting centre 1 (iC1) subtype than in the iC2 and iC3 subtypes. Comparison of CNV, MET, and mRNA expression among the subtypes identified two genes, ubiquitin B (UBB) and interleukin 18 binding protein (IL18BP), that were associated with prognosis. Mutation spectrum results based on subtype indicated that UBB and IL18BP expression may be influenced by mutation loci. Mutation levels were higher in iC1 samples than in iC2 or iC3 samples, indicating that the iC1 subtype is associated with disease progression. This integrated multi-omics analysis of genomics, epigenomics, and transcriptomics provides new insight into the molecular mechanisms of ovarian carcinoma and may help identify biomolecular markers for early disease diagnosis.
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spelling pubmed-66290042019-07-18 Integrated multi-omics analysis of genomics, epigenomics, and transcriptomics in ovarian carcinoma Zheng, Mingjun Hu, Yuexin Gou, Rui Wang, Jing Nie, Xin Li, Xiao Liu, Qing Liu, Juanjuan Lin, Bei Aging (Albany NY) Research Paper In this study, we identified prognostic biomarkers in ovarian carcinoma by integrating multi-omics DNA copy number variation (CNV) and methylation variation (MET) data. CNV, MET, and messenger RNA (mRNA) expression were examined in 351 ovarian carcinoma patients. Genes for which expression was correlated with DNA copy-number or DNA methylation were identified; three ovarian carcinoma gene subtypes were defined based on these correlations. Overall survival and B cell scores were lower, while the macrophage cell score was higher, in the DNA imprinting centre 1 (iC1) subtype than in the iC2 and iC3 subtypes. Comparison of CNV, MET, and mRNA expression among the subtypes identified two genes, ubiquitin B (UBB) and interleukin 18 binding protein (IL18BP), that were associated with prognosis. Mutation spectrum results based on subtype indicated that UBB and IL18BP expression may be influenced by mutation loci. Mutation levels were higher in iC1 samples than in iC2 or iC3 samples, indicating that the iC1 subtype is associated with disease progression. This integrated multi-omics analysis of genomics, epigenomics, and transcriptomics provides new insight into the molecular mechanisms of ovarian carcinoma and may help identify biomolecular markers for early disease diagnosis. Impact Journals 2019-06-29 /pmc/articles/PMC6629004/ /pubmed/31257224 http://dx.doi.org/10.18632/aging.102047 Text en Copyright © 2019 Zheng et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution (CC BY) 3.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Paper
Zheng, Mingjun
Hu, Yuexin
Gou, Rui
Wang, Jing
Nie, Xin
Li, Xiao
Liu, Qing
Liu, Juanjuan
Lin, Bei
Integrated multi-omics analysis of genomics, epigenomics, and transcriptomics in ovarian carcinoma
title Integrated multi-omics analysis of genomics, epigenomics, and transcriptomics in ovarian carcinoma
title_full Integrated multi-omics analysis of genomics, epigenomics, and transcriptomics in ovarian carcinoma
title_fullStr Integrated multi-omics analysis of genomics, epigenomics, and transcriptomics in ovarian carcinoma
title_full_unstemmed Integrated multi-omics analysis of genomics, epigenomics, and transcriptomics in ovarian carcinoma
title_short Integrated multi-omics analysis of genomics, epigenomics, and transcriptomics in ovarian carcinoma
title_sort integrated multi-omics analysis of genomics, epigenomics, and transcriptomics in ovarian carcinoma
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6629004/
https://www.ncbi.nlm.nih.gov/pubmed/31257224
http://dx.doi.org/10.18632/aging.102047
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