华南理工大学学报(自然科学版) ›› 2019, Vol. 47 ›› Issue (11): 78-88.doi: 10.12141/j.issn.1000-565X.180374

• 生物学 • 上一篇    下一篇

PPI 基因对在癌症中的共表达分析

蒙裕欢 白云梦 崔莹 杜红丽   

  1. 华南理工大学 生物科学与工程学院,广东 广州 510006
  • 收稿日期:2018-07-17 修回日期:2019-02-26 出版日期:2019-11-25 发布日期:2019-10-02
  • 通信作者: 杜红丽(1975-),女,博士,教授,主要从事遗传与生物信息学、多组学整合技术、泛癌症分子机制和 2 型糖尿病早期发病机制等的研究. E-mail:hldu@scut.edu.cn
  • 作者简介:蒙裕欢(1988-),男,博士,助理研究员,主要从事 NGS 及生物信息学研究. E-mail:yuhuan-meng@163.com
  • 基金资助:
    中国博士后科学基金资助项目( 2018M633045)

Coexpression Analysis of Gene Pairs with Protein-Protein Interaction in Cancers

MENG Yuhuan BAI Yunmeng CUI Ying DU Hongli   

  1. School of Biological Science and Engineering,South China University of Technology,Guangzhou 510006,Guangdong,China
  • Received:2018-07-17 Revised:2019-02-26 Online:2019-11-25 Published:2019-10-02
  • Contact: 杜红丽(1975-),女,博士,教授,主要从事遗传与生物信息学、多组学整合技术、泛癌症分子机制和 2 型糖尿病早期发病机制等的研究. E-mail:hldu@scut.edu.cn
  • About author:蒙裕欢(1988-),男,博士,助理研究员,主要从事 NGS 及生物信息学研究. E-mail:yuhuan-meng@163.com
  • Supported by:
    Supported by the China Postdoctoral Science Foundation( 2018M633045)

摘要: 蛋白质 - 蛋白质相互作用( PPI) 可通过基因表达量之间的相关系数来反映. 研究癌细胞或组织中全局的 PPI,有利于了解基因型和表型之间的关系,更好地发掘正常与异常细胞或组织之间的癌症发生发展机制. 文中利用 TCGA 数据库中 11 种癌症 5 726 个样本的 mRNA 表达数据和临床信息,结合 STRING 和 HPRD 数据库中的 PPI 基因对,使用皮尔逊相关系数计算癌症组织特异 PPI 基因对在正常样本和癌症不同时期样本的相关系数,筛选得到癌症紊乱及癌症特异的 PPI 基因对. 通过基因差异表达与生存分析,得到可能影响癌症发生发展的关键 PPI 基因对. 结果表明: PPI 基因对在癌症样本中的相关性要显著低于正常样本. 癌症紊乱 PPI 基因对有 2 812 对,其中 LRSAM1、ATXN1、SMARCC2 与 SMARCA2 等基因出现在多个癌症中并通过相互作用聚类成网络模块,可能在癌症中发挥重要作用; 癌症特异 PPI 基因对有31 对,其中 BMP1 与 COL1A1 在癌症中的相互作用很可能促进癌细胞的迁移和浸润转移,对癌症产生、发展产生重要的影响. 此外,在癌症紊乱及特异中筛选了 113 对具有差异表达的 PPI 基因对,其中有 16 对显著差异 PPI 基因对在 7个癌症中具有生存显著差异.

关键词: 癌症, TCGA, 蛋白质—蛋白质相互作用, 基因共表达

Abstract: The relativity of protein-protein interaction ( PPI) can be reflected by the gene coexpression correlation. The study of global PPIs in cancer cells or tissues will facilitate the understanding of the relationship between geno- types and phenotypes,as well as the mechanisms of cancer development in normal and abnormal cells or tissues. The mRNA expression profile data and clinical information was collected from the Cancer Genome Atlas ( TCGA) ,including 5726 samples across 11 human cancers type. Combining with PPI gene pairs of Human from STRING and HPRD databases,Pearson correlation coefficients ( PCC) was used to calculate the gene coexpression coefficients of tissue-specific PPIs in normal samples and cancer samples at different stages,and then the cancer-disordered and cancer-specific PPI gene pairs were obtained. With the different gene expression and survival analysis,PPI gene pairs which may affect the development of cancer were found out. Result shows that: the gene coexpression coeffi- cient of PPI gene pairs in cancer samples is significantly lower than normal samples. There are 2812 pairs of can- cer-disordered PPI genes,among which LRSAM1,ATXN1,SMARCC2 and SMARCA2 appear in multiple cancers interacted and clustered into a network module,and they may play an important role in caner. There are 31 pairs of cancer-specific PPI genes,among which BMP1 and COL1A1 may interact to promote tumorous migration and infil- tration. In addition,113 pairs of PPI genes with differential expression were selected from cancer-disordered and cancer-specific genes. Among them,16 pairs show significantly survival difference in 7 cancers.

Key words: cancer, TCGA, protein-protein interaction, gene coexpression