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A novel reannotation strategy for dissecting DNA methylation patterns of human long intergenic non-coding RNAs in cancers

Despite growing consensus that long intergenic non-coding ribonucleic acids (lincRNAs) are modulators of cancer, the knowledge about the deoxyribonucleic acid (DNA) methylation patterns of lincRNAs in cancers remains limited. In this study, we constructed DNA methylation profiles for 4629 tumors and...

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Detalles Bibliográficos
Autores principales: Zhi, Hui, Ning, Shangwei, Li, Xiang, Li, Yuyun, Wu, Wei, Li, Xia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4117791/
https://www.ncbi.nlm.nih.gov/pubmed/25013169
http://dx.doi.org/10.1093/nar/gku575
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author Zhi, Hui
Ning, Shangwei
Li, Xiang
Li, Yuyun
Wu, Wei
Li, Xia
author_facet Zhi, Hui
Ning, Shangwei
Li, Xiang
Li, Yuyun
Wu, Wei
Li, Xia
author_sort Zhi, Hui
collection PubMed
description Despite growing consensus that long intergenic non-coding ribonucleic acids (lincRNAs) are modulators of cancer, the knowledge about the deoxyribonucleic acid (DNA) methylation patterns of lincRNAs in cancers remains limited. In this study, we constructed DNA methylation profiles for 4629 tumors and 705 normal tissue samples from 20 different types of human cancer by reannotating data of DNA methylation arrays. We found that lincRNAs had different promoter methylation patterns in cancers. We classified 2461 lincRNAs into two categories and three subcategories, according to their promoter methylation patterns in tumors. LincRNAs with resistant methylation patterns in tumors had conserved transcriptional regulation regions and were ubiquitously expressed across normal tissues. By integrating cancer subtype data and patient clinical information, we identified lincRNAs with promoter methylation patterns that were associated with cancer status, subtype or prognosis for several cancers. Network analysis of aberrantly methylated lincRNAs in cancers showed that lincRNAs with aberrant methylation patterns might be involved in cancer development and progression. The methylated and demethylated lincRNAs identified in this study provide novel insights for developing cancer biomarkers and potential therapeutic targets.
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spelling pubmed-41177912014-08-15 A novel reannotation strategy for dissecting DNA methylation patterns of human long intergenic non-coding RNAs in cancers Zhi, Hui Ning, Shangwei Li, Xiang Li, Yuyun Wu, Wei Li, Xia Nucleic Acids Res Computational Biology Despite growing consensus that long intergenic non-coding ribonucleic acids (lincRNAs) are modulators of cancer, the knowledge about the deoxyribonucleic acid (DNA) methylation patterns of lincRNAs in cancers remains limited. In this study, we constructed DNA methylation profiles for 4629 tumors and 705 normal tissue samples from 20 different types of human cancer by reannotating data of DNA methylation arrays. We found that lincRNAs had different promoter methylation patterns in cancers. We classified 2461 lincRNAs into two categories and three subcategories, according to their promoter methylation patterns in tumors. LincRNAs with resistant methylation patterns in tumors had conserved transcriptional regulation regions and were ubiquitously expressed across normal tissues. By integrating cancer subtype data and patient clinical information, we identified lincRNAs with promoter methylation patterns that were associated with cancer status, subtype or prognosis for several cancers. Network analysis of aberrantly methylated lincRNAs in cancers showed that lincRNAs with aberrant methylation patterns might be involved in cancer development and progression. The methylated and demethylated lincRNAs identified in this study provide novel insights for developing cancer biomarkers and potential therapeutic targets. Oxford University Press 2014-09-01 2014-07-09 /pmc/articles/PMC4117791/ /pubmed/25013169 http://dx.doi.org/10.1093/nar/gku575 Text en © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/3.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Computational Biology
Zhi, Hui
Ning, Shangwei
Li, Xiang
Li, Yuyun
Wu, Wei
Li, Xia
A novel reannotation strategy for dissecting DNA methylation patterns of human long intergenic non-coding RNAs in cancers
title A novel reannotation strategy for dissecting DNA methylation patterns of human long intergenic non-coding RNAs in cancers
title_full A novel reannotation strategy for dissecting DNA methylation patterns of human long intergenic non-coding RNAs in cancers
title_fullStr A novel reannotation strategy for dissecting DNA methylation patterns of human long intergenic non-coding RNAs in cancers
title_full_unstemmed A novel reannotation strategy for dissecting DNA methylation patterns of human long intergenic non-coding RNAs in cancers
title_short A novel reannotation strategy for dissecting DNA methylation patterns of human long intergenic non-coding RNAs in cancers
title_sort novel reannotation strategy for dissecting dna methylation patterns of human long intergenic non-coding rnas in cancers
topic Computational Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4117791/
https://www.ncbi.nlm.nih.gov/pubmed/25013169
http://dx.doi.org/10.1093/nar/gku575
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