天津医药 ›› 2015, Vol. 43 ›› Issue (10): 1108-1111.doi: 10.11958/j.issn.0253-9896.2015.10.006

• 细胞与分子生物学 • 上一篇    下一篇

卵巢癌对顺铂类药物耐药性的相关分析

  

  1. 天津市中心妇产科医院
  • 收稿日期:2014-12-16 修回日期:2015-04-14 出版日期:2015-10-15 发布日期:2015-10-22

The analysis of cisplatin resistance in ovarian cancer treatment

  1. Tianjin Central Hospital of Gynecology Obstetrics, Tianjin 300100, China
  • Received:2014-12-16 Revised:2015-04-14 Published:2015-10-15 Online:2015-10-22

摘要:

摘要: 目的 筛选影响卵巢癌顺铂耐药性的靶点基因。方法 GEO 数据库中下载对顺铂敏感和产生抗药性
的人类卵巢癌细胞基因表达谱和甲基化谱数据(GSE15709), 利用 R 的相关工具包筛选 A2780 A2780/DDP(顺铂
耐药卵巢癌细胞系)两类卵巢癌细胞之间的差异表达和差异甲基化的基因; 使用 DAVID 数据库对差异表达基因进
行功能富集分析; 对同时发生了差异甲基化、 差异表达且甲基化水平、 表达水平的变化趋势相反的基因, 进一步利用
qRT-PCR 技术检测这些基因在两种卵巢癌细胞中的表达值。结果 研究发现在两种卵巢癌细胞之间发生了 416
差异表达和 281 个差异甲基化的基因, 这些差异表达基因主要富集于细胞周期、 核分裂和蛋白修饰负调控等生物过
程。此外, 细胞周期、 DNA 复制和 p53 等通路在这些基因中同样富集。共发现 4 个发生了差异甲基化、 差异表达且
甲基化变化水平、 表达水平变化趋势相反的基因, qRT-PCR 实验验证了这些基因在两种卵巢癌细胞中的表达水平。
结论 利用生物信息学和分子生物学相结合的方法, 可以筛选出部分影响卵巢癌对顺铂抗药性的基因, 为进一步揭
示其中的分子机制提供实验参考。

关键词: 顺铂, 卵巢肿瘤, 计算生物学, 逆转录聚合酶链反应, qRT-PCR, A2780, A2780/DDP

Abstract:

AbstractObjective To screen the target genes that contribute to cisplatin resistance in ovarian cancer treatment.
Methods Gene expression and methylation profiles of ovarian cancer cells that were sensitive or resistant to cisplatin with
accession number GSE15709 were downloaded from GEO database. Differential expressed and methylated genes were identi⁃
fied through associating packages in R. DAVID database to screen the enriched GO terms and pathways of the different ex⁃
pressed genes between A2780 and A2780/DDP. Gene Set Enrichment Analysis (GSEA) of different gene was performed
against DAVID database. Genes that exhibited difference in both expression and methylation profiles between the two types
of ovarian cancer cells as well as genes that present contradictory profile between expression and methylation were verified
via qRT-PCR. Results We found 416 different expressed genes and 281 methylated genes between the two types of ovari⁃
an cancer cells respectively. These differential genes were rich in pathways of cell cycle, DNA replication, nucleus division
p53 signaling , and negative regulation of protein modification process etc. Four genes demonstrated contradictory profile be⁃
tween expression and methylation in the two types of ovarian cancer cells and were verified by qRT- PCR. Conclusion
Combination of bioinformatics and molecular biology is useful in the identification of target genes that contribute to resis⁃
tance of cisplatin in ovarian cancer treatment and further reveal molecular mechanism behind it.

Key words: cisplatin, ovarian neoplasms, computational biology, reverse transcriptase polymerase chain reaction, qRTPCR, A2780, A2780/DDP