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Bioinformatics analysis of potential therapeutic targets among ARHGAP genes in breast cancer

GTPase activating proteins (RhoGAPs) serve significant roles in multiple aspects of tumor biology. Genes encoding RhoGAPs (ARHGAP), which switch off Rho-like GTPases, are responsible for breast cancer biogenesis. However, the identification of suitable and novel biomarkers for precision treatment an...

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Autores principales: Chen, Wei-Xian, Lou, Ming, Cheng, Lin, Qian, Qi, Xu, Ling-Yun, Sun, Li, Zhu, Yu-Lan, Dai, Hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6864933/
https://www.ncbi.nlm.nih.gov/pubmed/31788076
http://dx.doi.org/10.3892/ol.2019.10949
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author Chen, Wei-Xian
Lou, Ming
Cheng, Lin
Qian, Qi
Xu, Ling-Yun
Sun, Li
Zhu, Yu-Lan
Dai, Hong
author_facet Chen, Wei-Xian
Lou, Ming
Cheng, Lin
Qian, Qi
Xu, Ling-Yun
Sun, Li
Zhu, Yu-Lan
Dai, Hong
author_sort Chen, Wei-Xian
collection PubMed
description GTPase activating proteins (RhoGAPs) serve significant roles in multiple aspects of tumor biology. Genes encoding RhoGAPs (ARHGAP), which switch off Rho-like GTPases, are responsible for breast cancer biogenesis. However, the identification of suitable and novel biomarkers for precision treatment and prognosis remains challenging. The present study aimed to evaluate the expression of ARHGAP family genes in breast cancer and investigate the survival data using the Oncomine, Kaplan-Meier Plotter, bcGenExMiner and cBioPortal online databases. The results demonstrated low expression of ARHGAP6, 7, 10, 14, 19, 23 and 24 and high expression of ARHGAP9, 11, 15, 18 and 30 in patients with breast cancer compared with that in healthy individuals. The survival analysis revealed that low expression levels of ARHGAP6, 7 and 19 were associated with poor relapse-free survival (RFS) and overall survival (OS), whereas high expression levels of ARHGAP9, 15 and 30 were associated with preferable RFS and OS. Metastatic relapse data demonstrated that higher expression of ARHGAP9, 15, 18, 19, 25 and 30 were associated with better prognosis and increased expression of ARHGAP11A and 14 exerted negative effects on patient prognosis. The overlapping genes ARHGAP9, 15, 19 and 30 obtained from these bioinformatics analysis tools exhibited significant association with clinical parameters including age, the presence of estrogen receptor, progesterone receptor and epidermal growth factor receptor-2, Scarff-Bloom-Richardson grade and Nottingham prognostic index. In conclusion, bioinformatics analysis revealed that ARHGAP9, 15, 19 and 30, but not other ARHGAP family genes may be promising targets with prognostic value and biological function for precision treatment of breast cancer.
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spelling pubmed-68649332019-11-30 Bioinformatics analysis of potential therapeutic targets among ARHGAP genes in breast cancer Chen, Wei-Xian Lou, Ming Cheng, Lin Qian, Qi Xu, Ling-Yun Sun, Li Zhu, Yu-Lan Dai, Hong Oncol Lett Articles GTPase activating proteins (RhoGAPs) serve significant roles in multiple aspects of tumor biology. Genes encoding RhoGAPs (ARHGAP), which switch off Rho-like GTPases, are responsible for breast cancer biogenesis. However, the identification of suitable and novel biomarkers for precision treatment and prognosis remains challenging. The present study aimed to evaluate the expression of ARHGAP family genes in breast cancer and investigate the survival data using the Oncomine, Kaplan-Meier Plotter, bcGenExMiner and cBioPortal online databases. The results demonstrated low expression of ARHGAP6, 7, 10, 14, 19, 23 and 24 and high expression of ARHGAP9, 11, 15, 18 and 30 in patients with breast cancer compared with that in healthy individuals. The survival analysis revealed that low expression levels of ARHGAP6, 7 and 19 were associated with poor relapse-free survival (RFS) and overall survival (OS), whereas high expression levels of ARHGAP9, 15 and 30 were associated with preferable RFS and OS. Metastatic relapse data demonstrated that higher expression of ARHGAP9, 15, 18, 19, 25 and 30 were associated with better prognosis and increased expression of ARHGAP11A and 14 exerted negative effects on patient prognosis. The overlapping genes ARHGAP9, 15, 19 and 30 obtained from these bioinformatics analysis tools exhibited significant association with clinical parameters including age, the presence of estrogen receptor, progesterone receptor and epidermal growth factor receptor-2, Scarff-Bloom-Richardson grade and Nottingham prognostic index. In conclusion, bioinformatics analysis revealed that ARHGAP9, 15, 19 and 30, but not other ARHGAP family genes may be promising targets with prognostic value and biological function for precision treatment of breast cancer. D.A. Spandidos 2019-12 2019-10-02 /pmc/articles/PMC6864933/ /pubmed/31788076 http://dx.doi.org/10.3892/ol.2019.10949 Text en Copyright: © Chen et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
spellingShingle Articles
Chen, Wei-Xian
Lou, Ming
Cheng, Lin
Qian, Qi
Xu, Ling-Yun
Sun, Li
Zhu, Yu-Lan
Dai, Hong
Bioinformatics analysis of potential therapeutic targets among ARHGAP genes in breast cancer
title Bioinformatics analysis of potential therapeutic targets among ARHGAP genes in breast cancer
title_full Bioinformatics analysis of potential therapeutic targets among ARHGAP genes in breast cancer
title_fullStr Bioinformatics analysis of potential therapeutic targets among ARHGAP genes in breast cancer
title_full_unstemmed Bioinformatics analysis of potential therapeutic targets among ARHGAP genes in breast cancer
title_short Bioinformatics analysis of potential therapeutic targets among ARHGAP genes in breast cancer
title_sort bioinformatics analysis of potential therapeutic targets among arhgap genes in breast cancer
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6864933/
https://www.ncbi.nlm.nih.gov/pubmed/31788076
http://dx.doi.org/10.3892/ol.2019.10949
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