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Identification of prognosis markers for endometrial cancer by integrated analysis of DNA methylation and RNA-Seq data
Endometrial cancer is highly malignant and has a poor prognosis in the advanced stage, thus, prediction of its prognosis is important. DNA methylation has rapidly gained clinical attention as a biomarker for diagnostic, prognostic and predictive purposes in various cancers. In present study, differe...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6617448/ https://www.ncbi.nlm.nih.gov/pubmed/31289358 http://dx.doi.org/10.1038/s41598-019-46195-8 |
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author | Huo, Xiao Sun, Hengzi Cao, Dongyan Yang, Jiaxin Peng, Peng Yu, Mei Shen, Keng |
author_facet | Huo, Xiao Sun, Hengzi Cao, Dongyan Yang, Jiaxin Peng, Peng Yu, Mei Shen, Keng |
author_sort | Huo, Xiao |
collection | PubMed |
description | Endometrial cancer is highly malignant and has a poor prognosis in the advanced stage, thus, prediction of its prognosis is important. DNA methylation has rapidly gained clinical attention as a biomarker for diagnostic, prognostic and predictive purposes in various cancers. In present study, differentially methylated positions and differentially expressed genes were identified according to DNA methylation and RNA-Seq data. Functional analyses and interaction network were performed to identify hub genes, and overall survival analysis of hub genes were validated. The top genes were evaluated by immunohistochemical staining of endometrial cancer tissues. The gene function was evaluated by cell growth curve after knockdown CDC20 and CCNA2 of endometrial cancer cell line. A total of 329 hypomethylated highly expressed genes and 359 hypermethylated lowly expressed genes were identified, and four hub genes were obtained according to the interaction network. Patients with low expression of CDC20 and CCNA2 showed better overall survival. The results also were demonstrated by the immunohistochemical staining. Cell growth curve also demonstrated that knockdown CDC20 and CCNA2 can suppress the cell proliferation. We have identified two aberrantly methylated genes, CDC20 and CCNA2 as novel biomarkers for precision diagnosis in EC. |
format | Online Article Text |
id | pubmed-6617448 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-66174482019-07-18 Identification of prognosis markers for endometrial cancer by integrated analysis of DNA methylation and RNA-Seq data Huo, Xiao Sun, Hengzi Cao, Dongyan Yang, Jiaxin Peng, Peng Yu, Mei Shen, Keng Sci Rep Article Endometrial cancer is highly malignant and has a poor prognosis in the advanced stage, thus, prediction of its prognosis is important. DNA methylation has rapidly gained clinical attention as a biomarker for diagnostic, prognostic and predictive purposes in various cancers. In present study, differentially methylated positions and differentially expressed genes were identified according to DNA methylation and RNA-Seq data. Functional analyses and interaction network were performed to identify hub genes, and overall survival analysis of hub genes were validated. The top genes were evaluated by immunohistochemical staining of endometrial cancer tissues. The gene function was evaluated by cell growth curve after knockdown CDC20 and CCNA2 of endometrial cancer cell line. A total of 329 hypomethylated highly expressed genes and 359 hypermethylated lowly expressed genes were identified, and four hub genes were obtained according to the interaction network. Patients with low expression of CDC20 and CCNA2 showed better overall survival. The results also were demonstrated by the immunohistochemical staining. Cell growth curve also demonstrated that knockdown CDC20 and CCNA2 can suppress the cell proliferation. We have identified two aberrantly methylated genes, CDC20 and CCNA2 as novel biomarkers for precision diagnosis in EC. Nature Publishing Group UK 2019-07-09 /pmc/articles/PMC6617448/ /pubmed/31289358 http://dx.doi.org/10.1038/s41598-019-46195-8 Text en © The Author(s) 2019 Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Huo, Xiao Sun, Hengzi Cao, Dongyan Yang, Jiaxin Peng, Peng Yu, Mei Shen, Keng Identification of prognosis markers for endometrial cancer by integrated analysis of DNA methylation and RNA-Seq data |
title | Identification of prognosis markers for endometrial cancer by integrated analysis of DNA methylation and RNA-Seq data |
title_full | Identification of prognosis markers for endometrial cancer by integrated analysis of DNA methylation and RNA-Seq data |
title_fullStr | Identification of prognosis markers for endometrial cancer by integrated analysis of DNA methylation and RNA-Seq data |
title_full_unstemmed | Identification of prognosis markers for endometrial cancer by integrated analysis of DNA methylation and RNA-Seq data |
title_short | Identification of prognosis markers for endometrial cancer by integrated analysis of DNA methylation and RNA-Seq data |
title_sort | identification of prognosis markers for endometrial cancer by integrated analysis of dna methylation and rna-seq data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6617448/ https://www.ncbi.nlm.nih.gov/pubmed/31289358 http://dx.doi.org/10.1038/s41598-019-46195-8 |
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