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An integrated bioinformatical analysis to evaluate the role of KIF4A as a prognostic biomarker for breast cancer
PURPOSE: The aim of this study was to investigate the diagnostic and prognostic value of human kinesin family member 4A (KIF4A) as an effective biomarker for breast cancer. MATERIALS AND METHODS: Cancer Genome Atlas data and 12 independent public breast cancer microarray data sets were downloaded an...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove Medical Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6091482/ https://www.ncbi.nlm.nih.gov/pubmed/30127624 http://dx.doi.org/10.2147/OTT.S164730 |
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author | Xue, Dan Cheng, Pu Han, Mengjiao Liu, Xiyong Xue, Lijun Ye, Chenyi Wang, Ke Huang, Jian |
author_facet | Xue, Dan Cheng, Pu Han, Mengjiao Liu, Xiyong Xue, Lijun Ye, Chenyi Wang, Ke Huang, Jian |
author_sort | Xue, Dan |
collection | PubMed |
description | PURPOSE: The aim of this study was to investigate the diagnostic and prognostic value of human kinesin family member 4A (KIF4A) as an effective biomarker for breast cancer. MATERIALS AND METHODS: Cancer Genome Atlas data and 12 independent public breast cancer microarray data sets were downloaded and analyzed using individual and pooled approaches. RESULTS: The results of our study revealed a strong and positive correlation between KIF4A expression and malignant features of breast cancer. KIF4A had a strong prognostic value in both ER-positive and ER-negative breast cancers comparable to or even better than tumor size, lymph node invasion, and Elston grade. We also found that KIF4A might be the target gene of microRNA-335, which can suppress KIF4A expression by targeting the 3′-untranslated region of its mRNA. CONCLUSION: KIF4A might serve as a robust prognostic predictor for breast cancer. Targeting KIF4A activity could be a promising therapeutic option in breast cancer treatment. |
format | Online Article Text |
id | pubmed-6091482 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Dove Medical Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-60914822018-08-20 An integrated bioinformatical analysis to evaluate the role of KIF4A as a prognostic biomarker for breast cancer Xue, Dan Cheng, Pu Han, Mengjiao Liu, Xiyong Xue, Lijun Ye, Chenyi Wang, Ke Huang, Jian Onco Targets Ther Original Research PURPOSE: The aim of this study was to investigate the diagnostic and prognostic value of human kinesin family member 4A (KIF4A) as an effective biomarker for breast cancer. MATERIALS AND METHODS: Cancer Genome Atlas data and 12 independent public breast cancer microarray data sets were downloaded and analyzed using individual and pooled approaches. RESULTS: The results of our study revealed a strong and positive correlation between KIF4A expression and malignant features of breast cancer. KIF4A had a strong prognostic value in both ER-positive and ER-negative breast cancers comparable to or even better than tumor size, lymph node invasion, and Elston grade. We also found that KIF4A might be the target gene of microRNA-335, which can suppress KIF4A expression by targeting the 3′-untranslated region of its mRNA. CONCLUSION: KIF4A might serve as a robust prognostic predictor for breast cancer. Targeting KIF4A activity could be a promising therapeutic option in breast cancer treatment. Dove Medical Press 2018-08-10 /pmc/articles/PMC6091482/ /pubmed/30127624 http://dx.doi.org/10.2147/OTT.S164730 Text en © 2018 Xue et al. This work is published and licensed by Dove Medical Press Limited The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. |
spellingShingle | Original Research Xue, Dan Cheng, Pu Han, Mengjiao Liu, Xiyong Xue, Lijun Ye, Chenyi Wang, Ke Huang, Jian An integrated bioinformatical analysis to evaluate the role of KIF4A as a prognostic biomarker for breast cancer |
title | An integrated bioinformatical analysis to evaluate the role of KIF4A as a prognostic biomarker for breast cancer |
title_full | An integrated bioinformatical analysis to evaluate the role of KIF4A as a prognostic biomarker for breast cancer |
title_fullStr | An integrated bioinformatical analysis to evaluate the role of KIF4A as a prognostic biomarker for breast cancer |
title_full_unstemmed | An integrated bioinformatical analysis to evaluate the role of KIF4A as a prognostic biomarker for breast cancer |
title_short | An integrated bioinformatical analysis to evaluate the role of KIF4A as a prognostic biomarker for breast cancer |
title_sort | integrated bioinformatical analysis to evaluate the role of kif4a as a prognostic biomarker for breast cancer |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6091482/ https://www.ncbi.nlm.nih.gov/pubmed/30127624 http://dx.doi.org/10.2147/OTT.S164730 |
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