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The 3′UTR signature defines a highly metastatic subgroup of triple-negative breast cancer
Triple-negative breast cancer (TNBC) is a highly heterogeneous disease with an aggressive clinical course. Prognostic models are needed to chart potential patient outcomes. To address this, we used alternative 3′UTR patterns to improve postoperative risk stratification. We collected 327 publicly ava...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals LLC
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5312352/ https://www.ncbi.nlm.nih.gov/pubmed/27494850 http://dx.doi.org/10.18632/oncotarget.10975 |
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author | Wang, Lei Hu, Xin Wang, Peng Shao, Zhi-Ming |
author_facet | Wang, Lei Hu, Xin Wang, Peng Shao, Zhi-Ming |
author_sort | Wang, Lei |
collection | PubMed |
description | Triple-negative breast cancer (TNBC) is a highly heterogeneous disease with an aggressive clinical course. Prognostic models are needed to chart potential patient outcomes. To address this, we used alternative 3′UTR patterns to improve postoperative risk stratification. We collected 327 publicly available microarrays and generated the 3′UTR landscape based on expression ratios of alternative 3′UTR. After initial feature filtering, we built a 17-3′UTR-based classifier using an elastic net model. Time-dependent ROC comparisons and Kaplan–Meier analyses confirmed an outstanding discriminating power of our prognostic model for TNBC patients. In the training cohort, 5-year event-free survival (EFS) was 78.6% (95% CI 71.2–86.0) for the low-risk group, and 16.3% (95% CI 2.3–30.4) for the high-risk group (log-rank p<0.0001; hazard ratio [HR] 8.29, 95% CI 4.78–14.4), In the validation set, 5-year EFS was 75.6% (95% CI 68.0–83.2) for the low-risk group, and 33.2% (95% CI 17.1–49.3) for the high-risk group (log-rank p<0.0001; HR 3.17, 95% CI 1.66–5.42). In conclusion, the 17-3′UTR-based classifier provides a superior prognostic performance for estimating disease recurrence and metastasis in TNBC patients and it may permit personalized management strategies. |
format | Online Article Text |
id | pubmed-5312352 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Impact Journals LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-53123522017-03-06 The 3′UTR signature defines a highly metastatic subgroup of triple-negative breast cancer Wang, Lei Hu, Xin Wang, Peng Shao, Zhi-Ming Oncotarget Research Paper Triple-negative breast cancer (TNBC) is a highly heterogeneous disease with an aggressive clinical course. Prognostic models are needed to chart potential patient outcomes. To address this, we used alternative 3′UTR patterns to improve postoperative risk stratification. We collected 327 publicly available microarrays and generated the 3′UTR landscape based on expression ratios of alternative 3′UTR. After initial feature filtering, we built a 17-3′UTR-based classifier using an elastic net model. Time-dependent ROC comparisons and Kaplan–Meier analyses confirmed an outstanding discriminating power of our prognostic model for TNBC patients. In the training cohort, 5-year event-free survival (EFS) was 78.6% (95% CI 71.2–86.0) for the low-risk group, and 16.3% (95% CI 2.3–30.4) for the high-risk group (log-rank p<0.0001; hazard ratio [HR] 8.29, 95% CI 4.78–14.4), In the validation set, 5-year EFS was 75.6% (95% CI 68.0–83.2) for the low-risk group, and 33.2% (95% CI 17.1–49.3) for the high-risk group (log-rank p<0.0001; HR 3.17, 95% CI 1.66–5.42). In conclusion, the 17-3′UTR-based classifier provides a superior prognostic performance for estimating disease recurrence and metastasis in TNBC patients and it may permit personalized management strategies. Impact Journals LLC 2016-08-01 /pmc/articles/PMC5312352/ /pubmed/27494850 http://dx.doi.org/10.18632/oncotarget.10975 Text en Copyright: © 2016 Wang et al. http://creativecommons.org/licenses/by/2.5/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Paper Wang, Lei Hu, Xin Wang, Peng Shao, Zhi-Ming The 3′UTR signature defines a highly metastatic subgroup of triple-negative breast cancer |
title | The 3′UTR signature defines a highly metastatic subgroup of triple-negative breast cancer |
title_full | The 3′UTR signature defines a highly metastatic subgroup of triple-negative breast cancer |
title_fullStr | The 3′UTR signature defines a highly metastatic subgroup of triple-negative breast cancer |
title_full_unstemmed | The 3′UTR signature defines a highly metastatic subgroup of triple-negative breast cancer |
title_short | The 3′UTR signature defines a highly metastatic subgroup of triple-negative breast cancer |
title_sort | 3′utr signature defines a highly metastatic subgroup of triple-negative breast cancer |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5312352/ https://www.ncbi.nlm.nih.gov/pubmed/27494850 http://dx.doi.org/10.18632/oncotarget.10975 |
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