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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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals
2019
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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. |
format | Online Article Text |
id | pubmed-6629004 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Impact Journals |
record_format | MEDLINE/PubMed |
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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