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Identification of autophagy‐related long non‐coding RNA prognostic signature for breast cancer
Autophagy‐related long non‐coding RNAs (lncRNAs) disorders are related to the occurrence and development of breast cancer. The purpose of this study is to explore whether autophagy‐related lncRNA can predict the prognosis of breast cancer patients. The autophagy‐related lncRNAs prognostic signature...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8051719/ https://www.ncbi.nlm.nih.gov/pubmed/33694315 http://dx.doi.org/10.1111/jcmm.16378 |
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author | Wu, Qianxue Li, Qing Zhu, Wenming Zhang, Xiang Li, Hongyuan |
author_facet | Wu, Qianxue Li, Qing Zhu, Wenming Zhang, Xiang Li, Hongyuan |
author_sort | Wu, Qianxue |
collection | PubMed |
description | Autophagy‐related long non‐coding RNAs (lncRNAs) disorders are related to the occurrence and development of breast cancer. The purpose of this study is to explore whether autophagy‐related lncRNA can predict the prognosis of breast cancer patients. The autophagy‐related lncRNAs prognostic signature was constructed by Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression. We identified five autophagy‐related lncRNAs (MAPT‐AS1, LINC01871, AL122010.1, AC090912.1, AC061992.1) associated with prognostic value, and they were used to construct an autophagy‐related lncRNA prognostic signature (ALPS) model. ALPS model offered an independent prognostic value (HR = 1.664, 1.381‐2.006), where this risk score of the model was significantly related to the TNM stage, ER, PR and HER2 status in breast cancer patients. Nomogram could be utilized to predict survival for patients with breast cancer. Principal component analysis and Sankey Diagram results indicated that the distribution of five lncRNAs from the ALPS model tends to be low‐risk. Gene set enrichment analysis showed that the high‐risk group was enriched in autophagy and cancer‐related pathways, and the low‐risk group was enriched in regulatory immune‐related pathways. These results indicated that the ALPS model composed of five autophagy‐related lncRNAs could predict the prognosis of breast cancer patients. |
format | Online Article Text |
id | pubmed-8051719 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-80517192021-04-21 Identification of autophagy‐related long non‐coding RNA prognostic signature for breast cancer Wu, Qianxue Li, Qing Zhu, Wenming Zhang, Xiang Li, Hongyuan J Cell Mol Med Original Articles Autophagy‐related long non‐coding RNAs (lncRNAs) disorders are related to the occurrence and development of breast cancer. The purpose of this study is to explore whether autophagy‐related lncRNA can predict the prognosis of breast cancer patients. The autophagy‐related lncRNAs prognostic signature was constructed by Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression. We identified five autophagy‐related lncRNAs (MAPT‐AS1, LINC01871, AL122010.1, AC090912.1, AC061992.1) associated with prognostic value, and they were used to construct an autophagy‐related lncRNA prognostic signature (ALPS) model. ALPS model offered an independent prognostic value (HR = 1.664, 1.381‐2.006), where this risk score of the model was significantly related to the TNM stage, ER, PR and HER2 status in breast cancer patients. Nomogram could be utilized to predict survival for patients with breast cancer. Principal component analysis and Sankey Diagram results indicated that the distribution of five lncRNAs from the ALPS model tends to be low‐risk. Gene set enrichment analysis showed that the high‐risk group was enriched in autophagy and cancer‐related pathways, and the low‐risk group was enriched in regulatory immune‐related pathways. These results indicated that the ALPS model composed of five autophagy‐related lncRNAs could predict the prognosis of breast cancer patients. John Wiley and Sons Inc. 2021-03-10 2021-04 /pmc/articles/PMC8051719/ /pubmed/33694315 http://dx.doi.org/10.1111/jcmm.16378 Text en © 2021 The Authors. Journal of Cellular and Molecular Medicine published by Foundation for Cellular and Molecular Medicine and John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Articles Wu, Qianxue Li, Qing Zhu, Wenming Zhang, Xiang Li, Hongyuan Identification of autophagy‐related long non‐coding RNA prognostic signature for breast cancer |
title | Identification of autophagy‐related long non‐coding RNA prognostic signature for breast cancer |
title_full | Identification of autophagy‐related long non‐coding RNA prognostic signature for breast cancer |
title_fullStr | Identification of autophagy‐related long non‐coding RNA prognostic signature for breast cancer |
title_full_unstemmed | Identification of autophagy‐related long non‐coding RNA prognostic signature for breast cancer |
title_short | Identification of autophagy‐related long non‐coding RNA prognostic signature for breast cancer |
title_sort | identification of autophagy‐related long non‐coding rna prognostic signature for breast cancer |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8051719/ https://www.ncbi.nlm.nih.gov/pubmed/33694315 http://dx.doi.org/10.1111/jcmm.16378 |
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