Open Access

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

  • Authors:
    • Wei‑Xian Chen
    • Ming Lou
    • Lin Cheng
    • Qi Qian
    • Ling‑Yun Xu
    • Li Sun
    • Yu‑Lan Zhu
    • Hong Dai
  • View Affiliations

  • Published online on: October 2, 2019     https://doi.org/10.3892/ol.2019.10949
  • Pages: 6017-6025
  • Copyright: © Chen et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

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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December 2019
Volume 18 Issue 6

Print ISSN: 1792-1074
Online ISSN:1792-1082

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APA
Chen, W., Lou, M., Cheng, L., Qian, Q., Xu, L., Sun, L. ... Dai, H. (2019). Bioinformatics analysis of potential therapeutic targets among ARHGAP genes in breast cancer. Oncology Letters, 18, 6017-6025. https://doi.org/10.3892/ol.2019.10949
MLA
Chen, W., Lou, M., Cheng, L., Qian, Q., Xu, L., Sun, L., Zhu, Y., Dai, H."Bioinformatics analysis of potential therapeutic targets among ARHGAP genes in breast cancer". Oncology Letters 18.6 (2019): 6017-6025.
Chicago
Chen, W., Lou, M., Cheng, L., Qian, Q., Xu, L., Sun, L., Zhu, Y., Dai, H."Bioinformatics analysis of potential therapeutic targets among ARHGAP genes in breast cancer". Oncology Letters 18, no. 6 (2019): 6017-6025. https://doi.org/10.3892/ol.2019.10949