解剖学报

解剖学报 ›› 2016, Vol. ›› Issue (3): 348-352.doi: 10.16098/j.issn.0529-1356.2016.03.010

• 肿瘤生物学 • 上一篇    下一篇

妊娠期乳腺癌相关基因的生物信息学分析

滕牧洲 陈利娜 卢严方 马文丽*   

  1. 南方医科大学基因工程研究所，广州 510515
  • 收稿日期:2015-10-30 修回日期:2016-01-23 出版日期:2016-06-06 发布日期:2016-06-06
  • 通讯作者: 马文丽 E-mail:wenli668@gmail.com
  • 基金资助:

    国家自然科学基金项目;广东省领军人才基金

Bioinformatics analysis of the genes related to the pregnancy associated breast cancer

TENG Mu-zhou CHEN Li-na LU Yan-fang MA Wen-li*   

  1. Institute of Genetic Engineering, Southern Medical University, Guangzhou 510515, China
  • Received:2015-10-30 Revised:2016-01-23 Online:2016-06-06 Published:2016-06-06
  • Contact: MA Wen-li E-mail:wenli668@gmail.com

摘要：

目的 通过生物信息分析途径对妊娠期乳腺癌患者与正常人群的差异基因进行分析，从分子水平探讨妊娠期乳腺癌的发病机制。 方法 从公共数据库基因表达数据库（GEO）中下载妊娠期乳腺癌相关数据集，采用Qlucore Omics Explore(QOE)筛选差异表达基因，用DAIVID、STRING等在线分析工具对差异表达基因进行功能富集分析，信号转导通路分析以及预测蛋白质之间的关系。 结果 共筛选出148个差异表达基因，其中表达上调24个，下调124个，对其进行生物信息学分析发现，TAGLN、ACTG2、TPM2、TPM3、MYLK、ACTA2、MTH11等基因以及MAPK信号通路、黏着斑信号通路、血管平滑肌细胞收缩信号通路等在妊娠期乳腺癌的发生发展中可能起着重要作用。通过STRING分析发现，20个基因处于核心节点位置。 结论 利用生物信息学的方法能有效分析基因芯片数据并获取生物内在信息。

Abstract:

Objective The differentially expressed genes of pregnancy associated breast cancer patients and normal subjects were analyzed by Bioinformatics to reveal the pathogenesis of pregnancy associated breast cancer on the molecules level and to provide new ideas for the further study on breast cancer. Methods The microarray data sets of pregnancy associated breast cancer were downloaded from the public gene expression database (Gene Expression Omnibus, GEO); differential genes of pregnancy associated breast cancer patients and normal subjects were selected by Qlucore Omics Explore (QOE); DAIVID, and STRING were adopted to analyze the function and signal pathway and to predict the protein-protein interaction of the differential genes. Results A total of 148 differentially expressed genes were screened, among which 24 were up-regulated and the other 124 were downregulated. The results of these 148 differential genes bioinformatics analysis showed that the genes TAGLN, ACTG2, TPM2, TPM3, MYLK, ACTA2, MTH11, and mitogen activated protein kinase(MAPK) signaling pathway, and focal adhesion pathway, and vascular smooth muscle contraction pathway may play important roles in the development of pregnancy associated breast cancer. The results of STRING analysis showed that 20 genes were located in the key nodes of the protein interaction network. Conclusion Bioinformatics method can be utilized to analyze microarray data effectively andmining the deeper information of the data, providing valuable clues for the further researches.