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A Potential Prognostic Long Noncoding RNA Signature to Predict Recurrence among ER-positive Breast Cancer Patients Treated with Tamoxifen

Limited predictable long noncoding RNA (lncRNA) signature was reported in tamoxifen resistance among estrogen receptor (ER)-positive breast cancer (BC) patients. The aim of this study was to identify and assess prognostic lncRNA signature to predict recurrence among ER-positive BC patients treated w...

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Autores principales: Wang, Kang, Li, Jie, Xiong, Yong-Fu, Zeng, Zhen, Zhang, Xiang, Li, Hong-Yuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5816619/
https://www.ncbi.nlm.nih.gov/pubmed/29453409
http://dx.doi.org/10.1038/s41598-018-21581-w
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author Wang, Kang
Li, Jie
Xiong, Yong-Fu
Zeng, Zhen
Zhang, Xiang
Li, Hong-Yuan
author_facet Wang, Kang
Li, Jie
Xiong, Yong-Fu
Zeng, Zhen
Zhang, Xiang
Li, Hong-Yuan
author_sort Wang, Kang
collection PubMed
description Limited predictable long noncoding RNA (lncRNA) signature was reported in tamoxifen resistance among estrogen receptor (ER)-positive breast cancer (BC) patients. The aim of this study was to identify and assess prognostic lncRNA signature to predict recurrence among ER-positive BC patients treated with tamoxifen. Cohorts from Gene Expression Omnibus (GEO) (n = 298) and The Cancer Genome Atlas (TCGA) (n = 160) were defined as training and validation cohort, respectively. BC relapse associated lnRNAs was identify within training cohort, and the predictable value of recurrence was assessed in both cohorts. A total of 11lncRNAs were recognized to be associated with relapse free survival (RFS) of ER-positive BC patients receiving tamoxifen, who were divided into low-risk and high-risk group on basis of relapse risk scores (RRS). Multivariate cox regression analyses revealed that the RRS is an independent prognostic biomarker in the prediction of ER-positive BC patients’ survival. GSEA indicated that high-risk group was associated with several signaling pathways in processing of BC recurrence and metastasis such as PI3K-Akt and Wnt signaling. Our 11-lncRNA based classifier is a reliable prognostic and predictive tool for disease relapse in BC patients receiving tamoxifen.
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spelling pubmed-58166192018-02-21 A Potential Prognostic Long Noncoding RNA Signature to Predict Recurrence among ER-positive Breast Cancer Patients Treated with Tamoxifen Wang, Kang Li, Jie Xiong, Yong-Fu Zeng, Zhen Zhang, Xiang Li, Hong-Yuan Sci Rep Article Limited predictable long noncoding RNA (lncRNA) signature was reported in tamoxifen resistance among estrogen receptor (ER)-positive breast cancer (BC) patients. The aim of this study was to identify and assess prognostic lncRNA signature to predict recurrence among ER-positive BC patients treated with tamoxifen. Cohorts from Gene Expression Omnibus (GEO) (n = 298) and The Cancer Genome Atlas (TCGA) (n = 160) were defined as training and validation cohort, respectively. BC relapse associated lnRNAs was identify within training cohort, and the predictable value of recurrence was assessed in both cohorts. A total of 11lncRNAs were recognized to be associated with relapse free survival (RFS) of ER-positive BC patients receiving tamoxifen, who were divided into low-risk and high-risk group on basis of relapse risk scores (RRS). Multivariate cox regression analyses revealed that the RRS is an independent prognostic biomarker in the prediction of ER-positive BC patients’ survival. GSEA indicated that high-risk group was associated with several signaling pathways in processing of BC recurrence and metastasis such as PI3K-Akt and Wnt signaling. Our 11-lncRNA based classifier is a reliable prognostic and predictive tool for disease relapse in BC patients receiving tamoxifen. Nature Publishing Group UK 2018-02-16 /pmc/articles/PMC5816619/ /pubmed/29453409 http://dx.doi.org/10.1038/s41598-018-21581-w Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Wang, Kang
Li, Jie
Xiong, Yong-Fu
Zeng, Zhen
Zhang, Xiang
Li, Hong-Yuan
A Potential Prognostic Long Noncoding RNA Signature to Predict Recurrence among ER-positive Breast Cancer Patients Treated with Tamoxifen
title A Potential Prognostic Long Noncoding RNA Signature to Predict Recurrence among ER-positive Breast Cancer Patients Treated with Tamoxifen
title_full A Potential Prognostic Long Noncoding RNA Signature to Predict Recurrence among ER-positive Breast Cancer Patients Treated with Tamoxifen
title_fullStr A Potential Prognostic Long Noncoding RNA Signature to Predict Recurrence among ER-positive Breast Cancer Patients Treated with Tamoxifen
title_full_unstemmed A Potential Prognostic Long Noncoding RNA Signature to Predict Recurrence among ER-positive Breast Cancer Patients Treated with Tamoxifen
title_short A Potential Prognostic Long Noncoding RNA Signature to Predict Recurrence among ER-positive Breast Cancer Patients Treated with Tamoxifen
title_sort potential prognostic long noncoding rna signature to predict recurrence among er-positive breast cancer patients treated with tamoxifen
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5816619/
https://www.ncbi.nlm.nih.gov/pubmed/29453409
http://dx.doi.org/10.1038/s41598-018-21581-w
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