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Prognostic Value of a BCSC-associated MicroRNA Signature in Hormone Receptor-Positive HER2-Negative Breast Cancer
PURPOSE: Breast cancer patients with high proportion of cancer stem cells (BCSCs) have unfavorable clinical outcomes. MicroRNAs (miRNAs) regulate key features of BCSCs. We hypothesized that a biology-driven model based on BCSC-associated miRNAs could predict prognosis for the most common subtype, ho...
Autores principales: | , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5049991/ https://www.ncbi.nlm.nih.gov/pubmed/27566954 http://dx.doi.org/10.1016/j.ebiom.2016.08.016 |
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author | Gong, Chang Tan, Weige Chen, Kai You, Na Zhu, Shan Liang, Gehao Xie, Xinhua Li, Qian Zeng, Yunjie Ouyang, Nengtai Li, Zhihua Zeng, Musheng Zhuang, ShiMei Lau, Wan-Yee Liu, Qiang Yin, Dong Wang, Xueqin Su, Fengxi Song, Erwei |
author_facet | Gong, Chang Tan, Weige Chen, Kai You, Na Zhu, Shan Liang, Gehao Xie, Xinhua Li, Qian Zeng, Yunjie Ouyang, Nengtai Li, Zhihua Zeng, Musheng Zhuang, ShiMei Lau, Wan-Yee Liu, Qiang Yin, Dong Wang, Xueqin Su, Fengxi Song, Erwei |
author_sort | Gong, Chang |
collection | PubMed |
description | PURPOSE: Breast cancer patients with high proportion of cancer stem cells (BCSCs) have unfavorable clinical outcomes. MicroRNAs (miRNAs) regulate key features of BCSCs. We hypothesized that a biology-driven model based on BCSC-associated miRNAs could predict prognosis for the most common subtype, hormone receptor (HR)-positive, HER2-negative breast cancer patients. PATIENTS AND METHODS: After screening candidate miRNAs based on literature review and a pilot study, we built a miRNA-based classifier using LASSO Cox regression method in the training group (n = 202) and validated its prognostic accuracy in an internal (n = 101) and two external validation groups (n = 308). RESULTS: In this multicenter study, a 10-miRNA classifier incorporating miR-21, miR-30c, miR-181a, miR-181c, miR-125b, miR-7, miR-200a, miR-135b, miR-22 and miR-200c was developed to predict distant relapse free survival (DRFS). With this classifier, HR + HER2 − patients were scored and classified into high-risk and low-risk disease recurrence, which was significantly associated with 5-year DRFS of the patients. Moreover, this classifier outperformed traditional clinicopathological risk factors, IHC4 scoring and 21-gene Recurrence Score (RS). The patients with high-risk recurrence determined by this classifier benefit more from chemotherapy. CONCLUSIONS: Our 10-miRNA-based classifier provides a reliable prognostic model for disease recurrence in HR + HER2 − breast cancer patients. This model may facilitate personalized therapy-decision making for HR + HER2 − individuals. |
format | Online Article Text |
id | pubmed-5049991 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-50499912016-10-07 Prognostic Value of a BCSC-associated MicroRNA Signature in Hormone Receptor-Positive HER2-Negative Breast Cancer Gong, Chang Tan, Weige Chen, Kai You, Na Zhu, Shan Liang, Gehao Xie, Xinhua Li, Qian Zeng, Yunjie Ouyang, Nengtai Li, Zhihua Zeng, Musheng Zhuang, ShiMei Lau, Wan-Yee Liu, Qiang Yin, Dong Wang, Xueqin Su, Fengxi Song, Erwei EBioMedicine Research Paper PURPOSE: Breast cancer patients with high proportion of cancer stem cells (BCSCs) have unfavorable clinical outcomes. MicroRNAs (miRNAs) regulate key features of BCSCs. We hypothesized that a biology-driven model based on BCSC-associated miRNAs could predict prognosis for the most common subtype, hormone receptor (HR)-positive, HER2-negative breast cancer patients. PATIENTS AND METHODS: After screening candidate miRNAs based on literature review and a pilot study, we built a miRNA-based classifier using LASSO Cox regression method in the training group (n = 202) and validated its prognostic accuracy in an internal (n = 101) and two external validation groups (n = 308). RESULTS: In this multicenter study, a 10-miRNA classifier incorporating miR-21, miR-30c, miR-181a, miR-181c, miR-125b, miR-7, miR-200a, miR-135b, miR-22 and miR-200c was developed to predict distant relapse free survival (DRFS). With this classifier, HR + HER2 − patients were scored and classified into high-risk and low-risk disease recurrence, which was significantly associated with 5-year DRFS of the patients. Moreover, this classifier outperformed traditional clinicopathological risk factors, IHC4 scoring and 21-gene Recurrence Score (RS). The patients with high-risk recurrence determined by this classifier benefit more from chemotherapy. CONCLUSIONS: Our 10-miRNA-based classifier provides a reliable prognostic model for disease recurrence in HR + HER2 − breast cancer patients. This model may facilitate personalized therapy-decision making for HR + HER2 − individuals. Elsevier 2016-08-17 /pmc/articles/PMC5049991/ /pubmed/27566954 http://dx.doi.org/10.1016/j.ebiom.2016.08.016 Text en © 2016 Forschungsgesellschaft für Arbeitsphysiologie und Arbeitschutz e.V. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Paper Gong, Chang Tan, Weige Chen, Kai You, Na Zhu, Shan Liang, Gehao Xie, Xinhua Li, Qian Zeng, Yunjie Ouyang, Nengtai Li, Zhihua Zeng, Musheng Zhuang, ShiMei Lau, Wan-Yee Liu, Qiang Yin, Dong Wang, Xueqin Su, Fengxi Song, Erwei Prognostic Value of a BCSC-associated MicroRNA Signature in Hormone Receptor-Positive HER2-Negative Breast Cancer |
title | Prognostic Value of a BCSC-associated MicroRNA Signature in Hormone Receptor-Positive HER2-Negative Breast Cancer |
title_full | Prognostic Value of a BCSC-associated MicroRNA Signature in Hormone Receptor-Positive HER2-Negative Breast Cancer |
title_fullStr | Prognostic Value of a BCSC-associated MicroRNA Signature in Hormone Receptor-Positive HER2-Negative Breast Cancer |
title_full_unstemmed | Prognostic Value of a BCSC-associated MicroRNA Signature in Hormone Receptor-Positive HER2-Negative Breast Cancer |
title_short | Prognostic Value of a BCSC-associated MicroRNA Signature in Hormone Receptor-Positive HER2-Negative Breast Cancer |
title_sort | prognostic value of a bcsc-associated microrna signature in hormone receptor-positive her2-negative breast cancer |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5049991/ https://www.ncbi.nlm.nih.gov/pubmed/27566954 http://dx.doi.org/10.1016/j.ebiom.2016.08.016 |
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