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Comprehensive Analysis of Splicing Factor and Alternative Splicing Event to Construct Subtype-Specific Prognosis-Predicting Models for Breast Cancer
Recent evidence suggests that splicing factors (SFs) and alternative splicing (AS) play important roles in cancer progression. We constructed four SF-risk-models using 12 survival-related SFs. In Luminal-A, Luminal-B, Her-2, and Basal-Like BRCA, SF-risk-models for three genes (PAXBP1, NKAP, and NCBP...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8497829/ https://www.ncbi.nlm.nih.gov/pubmed/34630526 http://dx.doi.org/10.3389/fgene.2021.736423 |
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author | Zhang, He Han, Baoai Han, Xingxing Zhu, Yuying Liu, Hui Wang, Zhiyong Cui, Yanfen Tian, Ran Gao, Zicong Tian, Ruinan Ren, Sixin Zuo, Xiaoyan Tian, Jianfei Zhang, Fei Niu, Ruifang |
author_facet | Zhang, He Han, Baoai Han, Xingxing Zhu, Yuying Liu, Hui Wang, Zhiyong Cui, Yanfen Tian, Ran Gao, Zicong Tian, Ruinan Ren, Sixin Zuo, Xiaoyan Tian, Jianfei Zhang, Fei Niu, Ruifang |
author_sort | Zhang, He |
collection | PubMed |
description | Recent evidence suggests that splicing factors (SFs) and alternative splicing (AS) play important roles in cancer progression. We constructed four SF-risk-models using 12 survival-related SFs. In Luminal-A, Luminal-B, Her-2, and Basal-Like BRCA, SF-risk-models for three genes (PAXBP1, NKAP, and NCBP2), four genes (RBM15B, PNN, ACIN1, and SRSF8), three genes (LSM3, SNRNP200, and SNU13), and three genes (SRPK3, PUF60, and PNN) were constructed. These models have a promising prognosis-predicting power. The co-expression and protein-protein interaction analysis suggest that the 12 SFs are highly functional-connected. Pathway analysis and gene set enrichment analysis suggests that the functional role of the selected 12 SFs is highly context-dependent among different BRCA subtypes. We further constructed four AS-risk-models with good prognosis predicting ability in four BRCA subtypes by integrating the four SF-risk-models and 21 survival-related AS-events. This study proposed that SFs and ASs were potential multidimensional biomarkers for the diagnosis, prognosis, and treatment of BRCA. |
format | Online Article Text |
id | pubmed-8497829 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-84978292021-10-09 Comprehensive Analysis of Splicing Factor and Alternative Splicing Event to Construct Subtype-Specific Prognosis-Predicting Models for Breast Cancer Zhang, He Han, Baoai Han, Xingxing Zhu, Yuying Liu, Hui Wang, Zhiyong Cui, Yanfen Tian, Ran Gao, Zicong Tian, Ruinan Ren, Sixin Zuo, Xiaoyan Tian, Jianfei Zhang, Fei Niu, Ruifang Front Genet Genetics Recent evidence suggests that splicing factors (SFs) and alternative splicing (AS) play important roles in cancer progression. We constructed four SF-risk-models using 12 survival-related SFs. In Luminal-A, Luminal-B, Her-2, and Basal-Like BRCA, SF-risk-models for three genes (PAXBP1, NKAP, and NCBP2), four genes (RBM15B, PNN, ACIN1, and SRSF8), three genes (LSM3, SNRNP200, and SNU13), and three genes (SRPK3, PUF60, and PNN) were constructed. These models have a promising prognosis-predicting power. The co-expression and protein-protein interaction analysis suggest that the 12 SFs are highly functional-connected. Pathway analysis and gene set enrichment analysis suggests that the functional role of the selected 12 SFs is highly context-dependent among different BRCA subtypes. We further constructed four AS-risk-models with good prognosis predicting ability in four BRCA subtypes by integrating the four SF-risk-models and 21 survival-related AS-events. This study proposed that SFs and ASs were potential multidimensional biomarkers for the diagnosis, prognosis, and treatment of BRCA. Frontiers Media S.A. 2021-09-24 /pmc/articles/PMC8497829/ /pubmed/34630526 http://dx.doi.org/10.3389/fgene.2021.736423 Text en Copyright © 2021 Zhang, Han, Han, Zhu, Liu, Wang, Cui, Tian, Gao, Tian, Ren, Zuo, Tian, Zhang and Niu. https://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 Zhang, He Han, Baoai Han, Xingxing Zhu, Yuying Liu, Hui Wang, Zhiyong Cui, Yanfen Tian, Ran Gao, Zicong Tian, Ruinan Ren, Sixin Zuo, Xiaoyan Tian, Jianfei Zhang, Fei Niu, Ruifang Comprehensive Analysis of Splicing Factor and Alternative Splicing Event to Construct Subtype-Specific Prognosis-Predicting Models for Breast Cancer |
title | Comprehensive Analysis of Splicing Factor and Alternative Splicing Event to Construct Subtype-Specific Prognosis-Predicting Models for Breast Cancer |
title_full | Comprehensive Analysis of Splicing Factor and Alternative Splicing Event to Construct Subtype-Specific Prognosis-Predicting Models for Breast Cancer |
title_fullStr | Comprehensive Analysis of Splicing Factor and Alternative Splicing Event to Construct Subtype-Specific Prognosis-Predicting Models for Breast Cancer |
title_full_unstemmed | Comprehensive Analysis of Splicing Factor and Alternative Splicing Event to Construct Subtype-Specific Prognosis-Predicting Models for Breast Cancer |
title_short | Comprehensive Analysis of Splicing Factor and Alternative Splicing Event to Construct Subtype-Specific Prognosis-Predicting Models for Breast Cancer |
title_sort | comprehensive analysis of splicing factor and alternative splicing event to construct subtype-specific prognosis-predicting models for breast cancer |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8497829/ https://www.ncbi.nlm.nih.gov/pubmed/34630526 http://dx.doi.org/10.3389/fgene.2021.736423 |
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