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Chinese Journal of Cell and Stem Cell(Electronic Edition) ›› 2018, Vol. 08 ›› Issue (02): 80-87. doi: 10.3877/cma.j.issn.2095-1221.2018.02.003

Special Issue:

• Original Research • Previous Articles     Next Articles

Bioinformatics analysis of differentially expressed genes in clear cell renal cell carcinoma Caki-1 cell line

Hehuan Zhu1, Hu Zhao1, Zhiwen Lin1, Jie Wang1, Jun Lu1,(), Jianming Tan1   

  1. 1. Fujian Provincial Key Laboratory of Transplant Biology, Affiliated Dongfang Hospital (Fuzhou General Hospital), Xiamen University, Fuzhou 350025, China
  • Received:2018-03-15 Online:2018-04-01 Published:2018-04-01
  • Contact: Jun Lu
  • About author:
    Corresponding author: Lu Jun, Email:

Abstract:

Objective

To analyze the differentially expressed genes in the renal clear cell carcinoma Caki-1 cell line with the normal renal epithelial cell line ASE-5063 for searching for potential molecular markers of renal clear cell carcinoma.

Methods

GEO2R online analysis tool provided by the GEO database was used to analyze the gene chip GSE78179, and the differentially expressed genes were acquired and introduced into Metascape, STRING, and Cytoscape for comprehensive analysis and the core genes were screened out. Finally, GO and KEGG enrichment analysis was performed on the selected core genes using software such as FunRich.

Results

A total of 562 differentially expressed genes were screened out, including 345 up-regulated genes and 217 down-regulated genes. 36 key genes were further screened using MCODE. GO function analysis revealed that these genes were closely related to cell adhesion molecule activity, chemokine activity, cell communication, and signal transduction; KEGG pathway enrichment results indicated that the differential genes were mainly concentrated in chemokine signaling pathways, TNF signaling pathways, and NF-κB signaling pathways which were involved in a variety of tumor-related pathways.

Conclusion

The differentially expressed genes in the renal clear cell carcinoma Caki-1 cell line were screened using bioinformatics methods. Several core genes were widely involved in the pathological process of multiple tumors, but there have been no studies in renal clear cell carcinoma, suggesting that they may be potential targets for the treatment of renal clear cell carcinoma.

Key words: Clear cell renal cell carcinoma, Bioinformatics, Differentially expressed genes

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