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Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Mining the prognostic significance of the GINS2 gene in human breast cancer using bioinformatics analysis
Shibo Yu1, Lizhe Zhu1, Peiling Xie1
1Department of Breast Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, P.R. China.
Abstract:
A number of studies have demonstrated the crucial functions of GINS2 within the GINS complex in various types of cancer. However, the molecular mechanisms and prognostic value of GINS2 in breast cancer remain unknown. The present study used; BC-GenExMiner, COSMIC, UCSC Xena, The Human Protein Atlas, GEPIA, cBioPortal, GeneMANIA, TIMER and Oncomine, in order to investigate gene expression, co-expression, clinical parameters and mutations in GINS2 in patients with breast cancer. Furthermore, the present study assessed the prognostic value of GINS2 in patients with breast cancer via the Kaplan-Meier plotter database. The results of the present study demonstrated that the mRNA levels of GINS2 were significantly higher in breast cancer tissue compared with normal tissue. In addition, high mRNA expression levels of GINS2 were associated with high Scarff-Bloom-Richardson status grades, a basal-like status and age (≤51 years); however, it was not associated with lymph node metastasis. The survival analysis revealed that increased GINS2 mRNA levels were associated with a worse prognosis for relapse-free survival in all patients with breast cancer, particularly in those with estrogen receptor-positive and progesterone receptor-positive subtypes. In addition, a positive association between the GINS2, CENPM and MCM4 genes was confirmed. The results of the present study suggest that GINS2 could be used as a potential prognostic biomarker for breast cancer. Nevertheless, further studies are necessary to confirm the effects of GINS2 on the pathogenesis and development of patients with breast cancer.
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