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Comprehensive Analysis of Prognostic Alternative Splicing Signatures in Endometrial Cancer
BACKGROUND: Alternative splicing (AS) is one of the critical post-transcriptional regulatory mechanisms of various cancers and also plays a crucial role in the development of cancers, including endometrial cancer (EC). METHODS: The splicing data and gene expression profiles of EC were obtained from...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7272712/ https://www.ncbi.nlm.nih.gov/pubmed/32547595 http://dx.doi.org/10.3389/fgene.2020.00456 |
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author | Chen, Peigen He, Junxian Ye, Huixia Jiang, Senwei Li, Yunhui Li, Xiaomao Wan, Jing |
author_facet | Chen, Peigen He, Junxian Ye, Huixia Jiang, Senwei Li, Yunhui Li, Xiaomao Wan, Jing |
author_sort | Chen, Peigen |
collection | PubMed |
description | BACKGROUND: Alternative splicing (AS) is one of the critical post-transcriptional regulatory mechanisms of various cancers and also plays a crucial role in the development of cancers, including endometrial cancer (EC). METHODS: The splicing data and gene expression profiles of EC were obtained from The Cancer Genome Atlas. The corresponding clinical data were extracted from TCGA-CDR. With univariate Cox regression analysis, least absolute shrinkage and selection operator model, and multivariate Cox regression analysis, the survival-related AS events were selected. Functional enrichment analysis was also performed to investigate the functions of these AS events. Splicing factors and AS regulation network were constructed to understand the correlation among these AS events. RESULT: A total of 1826 AS events were identified as survival-related events. Functional enrichment analysis showed that these AS events were associated with several immune system-related processes. Then, the prognostic signatures were developed based on these survival-related events and acted as an independent prognostic factor for EC. Splicing factors and AS regulation network were also constructed to understand the regulatory mechanisms of AS events in EC. CONCLUSION: This study systematically analyzed the role of AS events in EC and developed the prognostic model for EC. |
format | Online Article Text |
id | pubmed-7272712 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-72727122020-06-15 Comprehensive Analysis of Prognostic Alternative Splicing Signatures in Endometrial Cancer Chen, Peigen He, Junxian Ye, Huixia Jiang, Senwei Li, Yunhui Li, Xiaomao Wan, Jing Front Genet Genetics BACKGROUND: Alternative splicing (AS) is one of the critical post-transcriptional regulatory mechanisms of various cancers and also plays a crucial role in the development of cancers, including endometrial cancer (EC). METHODS: The splicing data and gene expression profiles of EC were obtained from The Cancer Genome Atlas. The corresponding clinical data were extracted from TCGA-CDR. With univariate Cox regression analysis, least absolute shrinkage and selection operator model, and multivariate Cox regression analysis, the survival-related AS events were selected. Functional enrichment analysis was also performed to investigate the functions of these AS events. Splicing factors and AS regulation network were constructed to understand the correlation among these AS events. RESULT: A total of 1826 AS events were identified as survival-related events. Functional enrichment analysis showed that these AS events were associated with several immune system-related processes. Then, the prognostic signatures were developed based on these survival-related events and acted as an independent prognostic factor for EC. Splicing factors and AS regulation network were also constructed to understand the regulatory mechanisms of AS events in EC. CONCLUSION: This study systematically analyzed the role of AS events in EC and developed the prognostic model for EC. Frontiers Media S.A. 2020-05-29 /pmc/articles/PMC7272712/ /pubmed/32547595 http://dx.doi.org/10.3389/fgene.2020.00456 Text en Copyright © 2020 Chen, He, Ye, Jiang, Li, Li and Wan. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Chen, Peigen He, Junxian Ye, Huixia Jiang, Senwei Li, Yunhui Li, Xiaomao Wan, Jing Comprehensive Analysis of Prognostic Alternative Splicing Signatures in Endometrial Cancer |
title | Comprehensive Analysis of Prognostic Alternative Splicing Signatures in Endometrial Cancer |
title_full | Comprehensive Analysis of Prognostic Alternative Splicing Signatures in Endometrial Cancer |
title_fullStr | Comprehensive Analysis of Prognostic Alternative Splicing Signatures in Endometrial Cancer |
title_full_unstemmed | Comprehensive Analysis of Prognostic Alternative Splicing Signatures in Endometrial Cancer |
title_short | Comprehensive Analysis of Prognostic Alternative Splicing Signatures in Endometrial Cancer |
title_sort | comprehensive analysis of prognostic alternative splicing signatures in endometrial cancer |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7272712/ https://www.ncbi.nlm.nih.gov/pubmed/32547595 http://dx.doi.org/10.3389/fgene.2020.00456 |
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