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A novel six-microRNA-based model to improve prognosis prediction of breast cancer
Current tumor-node-metastasis (TNM) stage is unable to accurately predict the overall survival (OS) in breast cancer (BC) patients. This study aimed to construct a microRNA (miRNA)-based model to improve survival prediction of BC. We confirmed 99 differentially expressed miRNAs (DEMs) in 1044 BC sam...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6366967/ https://www.ncbi.nlm.nih.gov/pubmed/30696800 http://dx.doi.org/10.18632/aging.101767 |
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author | Lai, Jianguo Wang, Hongli Pan, Zihao Su, Fengxi |
author_facet | Lai, Jianguo Wang, Hongli Pan, Zihao Su, Fengxi |
author_sort | Lai, Jianguo |
collection | PubMed |
description | Current tumor-node-metastasis (TNM) stage is unable to accurately predict the overall survival (OS) in breast cancer (BC) patients. This study aimed to construct a microRNA (miRNA)-based model to improve survival prediction of BC. We confirmed 99 differentially expressed miRNAs (DEMs) in 1044 BC samples compared to 102 adjacent normal breast tissues from The Cancer Genome Atlas (TCGA) database. Prognostic DEMs were used to establish a miRNA-based nomogram via Cox regression model. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes analyses (KEGG) were executed to analyze target genes of miRNAs. A six-miRNA signature was screened to effectively distinguish high-risk patients in the primary and validation cohort (all P<0.001). Furthermore, we established a novel prognostic model incorporating the six-miRNA signature and clinical risk factors to predict 5-year OS of BC. Time-dependent receiver operating characteristic analysis suggested that the predictive accuracy of the six-miRNA-based nomogram was distinctly higher than that of TNM stage (0.758 vs 0.650, P<0.001). GO and KEGG pathway analyses showed that the 39 target genes mainly enrichment in protein binding, cytoplasm and MAPK signaling pathway. Our six-miRNA-based model is a reliable prognostic tool for survival prediction and provides information for individualized treatment decisions in BC patients. |
format | Online Article Text |
id | pubmed-6366967 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Impact Journals |
record_format | MEDLINE/PubMed |
spelling | pubmed-63669672019-02-15 A novel six-microRNA-based model to improve prognosis prediction of breast cancer Lai, Jianguo Wang, Hongli Pan, Zihao Su, Fengxi Aging (Albany NY) Research Paper Current tumor-node-metastasis (TNM) stage is unable to accurately predict the overall survival (OS) in breast cancer (BC) patients. This study aimed to construct a microRNA (miRNA)-based model to improve survival prediction of BC. We confirmed 99 differentially expressed miRNAs (DEMs) in 1044 BC samples compared to 102 adjacent normal breast tissues from The Cancer Genome Atlas (TCGA) database. Prognostic DEMs were used to establish a miRNA-based nomogram via Cox regression model. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes analyses (KEGG) were executed to analyze target genes of miRNAs. A six-miRNA signature was screened to effectively distinguish high-risk patients in the primary and validation cohort (all P<0.001). Furthermore, we established a novel prognostic model incorporating the six-miRNA signature and clinical risk factors to predict 5-year OS of BC. Time-dependent receiver operating characteristic analysis suggested that the predictive accuracy of the six-miRNA-based nomogram was distinctly higher than that of TNM stage (0.758 vs 0.650, P<0.001). GO and KEGG pathway analyses showed that the 39 target genes mainly enrichment in protein binding, cytoplasm and MAPK signaling pathway. Our six-miRNA-based model is a reliable prognostic tool for survival prediction and provides information for individualized treatment decisions in BC patients. Impact Journals 2019-01-30 /pmc/articles/PMC6366967/ /pubmed/30696800 http://dx.doi.org/10.18632/aging.101767 Text en Copyright: © 2019 Lai et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) 3.0 (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Paper Lai, Jianguo Wang, Hongli Pan, Zihao Su, Fengxi A novel six-microRNA-based model to improve prognosis prediction of breast cancer |
title | A novel six-microRNA-based model to improve prognosis prediction of breast cancer |
title_full | A novel six-microRNA-based model to improve prognosis prediction of breast cancer |
title_fullStr | A novel six-microRNA-based model to improve prognosis prediction of breast cancer |
title_full_unstemmed | A novel six-microRNA-based model to improve prognosis prediction of breast cancer |
title_short | A novel six-microRNA-based model to improve prognosis prediction of breast cancer |
title_sort | novel six-microrna-based model to improve prognosis prediction of breast cancer |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6366967/ https://www.ncbi.nlm.nih.gov/pubmed/30696800 http://dx.doi.org/10.18632/aging.101767 |
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