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Article

Identification and characterization of miR-96, a potential biomarker of NSCLC, through bioinformatic analysis

  • Authors:
    • Tonghui Cai
    • Jie Long
    • Hongyan Wang
    • Wanxia Liu
    • Yajie Zhang
  • View Affiliations / Copyright

    Affiliations: Department of Pathology, School of Basic Medical Science, Guangzhou Medical University, Guangzhou, Guangdong 511436, P.R. China
  • Pages: 1213-1223
    |
    Published online on: June 27, 2017
       https://doi.org/10.3892/or.2017.5754
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Abstract

Lung cancer is the leading cause of cancer-related death worldwide. The poor prognosis is partly due to lack of efficient methods for early diagnosis. MicroRNAs play roles in almost all aspects of cancer biology, and can be secreted into the circulation and serve as molecular biomarkers for the early diagnosis of cancer. In the present study, we determined the expression of miR-96 and the function of its target genes in lung cancer through bioinformatic analysis. Four microRNA expression profiles of lung cancer were downloaded from Gene Expression Omnibus and the data were analyzed using SPSS 16.0 software. Compared to the control group, expression of miR-96 was significantly increased in non-small cell lung cancer (NSCLC) (GSE51855), lung adenocarcinoma (GSE48414), stage I adenocarcinoma tissues (GSE63805) and the plasma of lung cancer patients (GSE68951). miR-96 was also elevated in six different NSCLC cell lines. However, the expression level of miR-96 was not related to the age, gender, clinical stage and histological subtype of the NSCLC patients. GO analysis of 78 predicted target genes of miR-96 showed that 42 of the obtained GO terms are highly associated with specific cellular processes including response to stimulus, signaling pathway, cell division, cell communication, cell migration and calcium signaling. KEGG results indicated that the miR-96 targets are mainly involved in the GnRH signaling pathway, long-term potentiation and insulin signaling pathway. In conclusion, miR-96, functioning as an oncogene, may play an important role in the development and progression of lung cancer. miR-96 may have the potential to serve as a molecular biomarker for the early diagnosis of NSCLC.
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Copy and paste a formatted citation
Spandidos Publications style
Cai T, Long J, Wang H, Liu W and Zhang Y: Identification and characterization of miR-96, a potential biomarker of NSCLC, through bioinformatic analysis. Oncol Rep 38: 1213-1223, 2017.
APA
Cai, T., Long, J., Wang, H., Liu, W., & Zhang, Y. (2017). Identification and characterization of miR-96, a potential biomarker of NSCLC, through bioinformatic analysis. Oncology Reports, 38, 1213-1223. https://doi.org/10.3892/or.2017.5754
MLA
Cai, T., Long, J., Wang, H., Liu, W., Zhang, Y."Identification and characterization of miR-96, a potential biomarker of NSCLC, through bioinformatic analysis". Oncology Reports 38.2 (2017): 1213-1223.
Chicago
Cai, T., Long, J., Wang, H., Liu, W., Zhang, Y."Identification and characterization of miR-96, a potential biomarker of NSCLC, through bioinformatic analysis". Oncology Reports 38, no. 2 (2017): 1213-1223. https://doi.org/10.3892/or.2017.5754
Copy and paste a formatted citation
x
Spandidos Publications style
Cai T, Long J, Wang H, Liu W and Zhang Y: Identification and characterization of miR-96, a potential biomarker of NSCLC, through bioinformatic analysis. Oncol Rep 38: 1213-1223, 2017.
APA
Cai, T., Long, J., Wang, H., Liu, W., & Zhang, Y. (2017). Identification and characterization of miR-96, a potential biomarker of NSCLC, through bioinformatic analysis. Oncology Reports, 38, 1213-1223. https://doi.org/10.3892/or.2017.5754
MLA
Cai, T., Long, J., Wang, H., Liu, W., Zhang, Y."Identification and characterization of miR-96, a potential biomarker of NSCLC, through bioinformatic analysis". Oncology Reports 38.2 (2017): 1213-1223.
Chicago
Cai, T., Long, J., Wang, H., Liu, W., Zhang, Y."Identification and characterization of miR-96, a potential biomarker of NSCLC, through bioinformatic analysis". Oncology Reports 38, no. 2 (2017): 1213-1223. https://doi.org/10.3892/or.2017.5754
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