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中华细胞与干细胞杂志(电子版) ›› 2018, Vol. 08 ›› Issue (02) : 80 -87. doi: 10.3877/cma.j.issn.2095-1221.2018.02.003

所属专题: 文献

论著

肾透明细胞癌Caki-1细胞系差异表达基因的生物信息学分析
朱合欢1, 赵虎1, 林智文1, 王洁1, 路君1,(), 谭建明1   
  1. 1. 350025 福州,厦门大学附属东方医院(福州总医院)、福建省移植生物学重点实验室
  • 收稿日期:2018-03-15 出版日期:2018-04-01
  • 通信作者: 路君
  • 基金资助:
    国家自然科学基金(81570748); 福州总医院杰出青年培养专项(2017Q05)

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 Published:2018-04-01
  • Corresponding author: Jun Lu
  • About author:
    Corresponding author: Lu Jun, Email:
引用本文:

朱合欢, 赵虎, 林智文, 王洁, 路君, 谭建明. 肾透明细胞癌Caki-1细胞系差异表达基因的生物信息学分析[J/OL]. 中华细胞与干细胞杂志(电子版), 2018, 08(02): 80-87.

Hehuan Zhu, Hu Zhao, Zhiwen Lin, Jie Wang, Jun Lu, Jianming Tan. Bioinformatics analysis of differentially expressed genes in clear cell renal cell carcinoma Caki-1 cell line[J/OL]. Chinese Journal of Cell and Stem Cell(Electronic Edition), 2018, 08(02): 80-87.

目的

比较肾透明细胞癌Caki-1细胞系与正常肾上皮细胞系ASE-5063中的差异表达基因(DEGs),寻找潜在的肾透明细胞癌特异性分子标志物。

方法

利用GEO数据库自带的GEO2R在线分析工具分析基因芯片GSE78179,将筛选出的DEGs分别导入Metascape、STRING以及Cytoscape进行综合分析并筛选出核心基因。最后使用FunRich等软件对筛选出的核心基因进行GO和KEGG富集分析。

结果

共筛选出562个DEGs,其中上调基因345个,下调基因217个。进一步使用MCODE筛选出36个关键基因,GO功能分析发现这些基因与细胞粘附分子活性、趋化因子活性、细胞通讯和信号转导等密切相关;KEGG通路富集结果则表明差异基因主要集中在趋化因子信号通路、TNF信号通路以及NF-κB信号通路等多种与肿瘤相关的通路上。

结论

运用生物信息学方法筛选出肾透明细胞癌Caki-1细胞系中DEGs,其中数个核心基因广泛参与多种肿瘤的病理进程,但尚未在肾透明细胞癌有相关研究报道,提示其可能是治疗肾透明细胞癌的潜在靶点。

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.

表1 上调与下调排名前5名的差异表达基因
图1 差异表达基因Metascape分析结果
图2 差异、核心基因互作网络图
表2 核心基因KEGG通路富集分析
图3 核心基因GO功能富集分析
图4 部分核心基因及其参与的信号通路
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