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Integrating gene and lncRNA expression to infer subpathway activity for tumor analyses
LncRNAs acting as miRNA sponges to indirectly regulate mRNAs is a novel layer of gene regulation, therefore, it is necessary to integrate lncRNA and gene levels for interpreting tumor biological mechanism. In this study, we developed a lncRNA-gene integrated strategy to infer functional activities f...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals LLC
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5762333/ https://www.ncbi.nlm.nih.gov/pubmed/29340065 http://dx.doi.org/10.18632/oncotarget.22811 |
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author | Zhang, Chunlong Xu, Yanjun Yang, Haixiu Xu, Yingqi Dong, Qun Liu, Siyao Wu, Tan Zhang, Yunpeng |
author_facet | Zhang, Chunlong Xu, Yanjun Yang, Haixiu Xu, Yingqi Dong, Qun Liu, Siyao Wu, Tan Zhang, Yunpeng |
author_sort | Zhang, Chunlong |
collection | PubMed |
description | LncRNAs acting as miRNA sponges to indirectly regulate mRNAs is a novel layer of gene regulation, therefore, it is necessary to integrate lncRNA and gene levels for interpreting tumor biological mechanism. In this study, we developed a lncRNA-gene integrated strategy to infer functional activities for tumor analyses at the subpathway level. In this strategy, we reconstructed subpathway graphs by embedding lncRNA components and considered the expression levels of both genes and lncRNAs to infer subpathway activities for each tumor sample. And the activities were applied to three aspects of tumor analyses; First, the subpathway activities across tumor samples of five tumor types were analyzed, and it was observed that the samples with consistent subpathway activities were derived from the same or similar tumor types. Also, the subpathway activities could stratify samples into several subtypes which has different clinical characterization, e.g. survival status. Second, the subpathway activities between tumor and normal samples were analyzed, and the comparative results showed that subpathway activities displayed more specificities than entire pathway activities. Finally, based on the subpathway activities, we identified prognostic subpathways for lung cancer. Our subpathway-based signatures shared significant overlap with enrichment analysis results and displayed predictive power in the independent testing sets. In conclusion, our integrated strategy provided a framework to infer subpathway activities for tumor analyses and identify subpathway signatures for clinical use. |
format | Online Article Text |
id | pubmed-5762333 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Impact Journals LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-57623332018-01-16 Integrating gene and lncRNA expression to infer subpathway activity for tumor analyses Zhang, Chunlong Xu, Yanjun Yang, Haixiu Xu, Yingqi Dong, Qun Liu, Siyao Wu, Tan Zhang, Yunpeng Oncotarget Research Paper LncRNAs acting as miRNA sponges to indirectly regulate mRNAs is a novel layer of gene regulation, therefore, it is necessary to integrate lncRNA and gene levels for interpreting tumor biological mechanism. In this study, we developed a lncRNA-gene integrated strategy to infer functional activities for tumor analyses at the subpathway level. In this strategy, we reconstructed subpathway graphs by embedding lncRNA components and considered the expression levels of both genes and lncRNAs to infer subpathway activities for each tumor sample. And the activities were applied to three aspects of tumor analyses; First, the subpathway activities across tumor samples of five tumor types were analyzed, and it was observed that the samples with consistent subpathway activities were derived from the same or similar tumor types. Also, the subpathway activities could stratify samples into several subtypes which has different clinical characterization, e.g. survival status. Second, the subpathway activities between tumor and normal samples were analyzed, and the comparative results showed that subpathway activities displayed more specificities than entire pathway activities. Finally, based on the subpathway activities, we identified prognostic subpathways for lung cancer. Our subpathway-based signatures shared significant overlap with enrichment analysis results and displayed predictive power in the independent testing sets. In conclusion, our integrated strategy provided a framework to infer subpathway activities for tumor analyses and identify subpathway signatures for clinical use. Impact Journals LLC 2017-11-30 /pmc/articles/PMC5762333/ /pubmed/29340065 http://dx.doi.org/10.18632/oncotarget.22811 Text en Copyright: © 2017 Zhang et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) 3.0 (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Paper Zhang, Chunlong Xu, Yanjun Yang, Haixiu Xu, Yingqi Dong, Qun Liu, Siyao Wu, Tan Zhang, Yunpeng Integrating gene and lncRNA expression to infer subpathway activity for tumor analyses |
title | Integrating gene and lncRNA expression to infer subpathway activity for tumor analyses |
title_full | Integrating gene and lncRNA expression to infer subpathway activity for tumor analyses |
title_fullStr | Integrating gene and lncRNA expression to infer subpathway activity for tumor analyses |
title_full_unstemmed | Integrating gene and lncRNA expression to infer subpathway activity for tumor analyses |
title_short | Integrating gene and lncRNA expression to infer subpathway activity for tumor analyses |
title_sort | integrating gene and lncrna expression to infer subpathway activity for tumor analyses |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5762333/ https://www.ncbi.nlm.nih.gov/pubmed/29340065 http://dx.doi.org/10.18632/oncotarget.22811 |
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