Gene expression profiling and bioinformatics analysis of gastric carcinoma
Gene expression profiling and bioinformatics analysis of gastric carcinoma
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胃癌基因表达谱及生物信息学分析
DOI：
10.1016/j.yexmp.2014.02.007
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发表时间：
2014-06-01
影响因子：
3.6
通讯作者：
Li, Qi
中科院分区：
文献类型：
--
作者：
Liu, Ningning;Liu, Xuan;Li, Qi
胃癌仍然是世界范围内的主要健康问题之一，在中国，它是最常见的癌症之一，也是癌症相关死亡的主要原因。本研究旨在分析胃癌相关基因的表达谱，并预测可能的调控因子。从Gene Expression Omnibus下载基因表达谱数据GSE 13911，并通过t检验鉴定差异表达基因（DEG）。利用基于平均连锁和Pearson相关系数的R中的层次聚类构建基因模块，并利用大卫对这些基因进行功能分析。获得Pearson相关系数>0.3的各模块基因构建共表达网络。通过比较蛋白质-蛋白质相互作用（PPI）网络和共表达网络，确定蛋白质-蛋白质相互作用（PPI）。此外，筛选出了每个模块的潜在调控microRNA和转录因子。在这项研究中，六个模块与蛋白质降解，细胞周期，蛋白质运输和免疫反应。COPS 5（COP 9 Subunit 5）是模块1的最大PPI网络中的核心蛋白。转录因子MYC和MAZ（Myc相关锌指蛋白）在模块1中富集。共鉴定出9个microRNA-靶标双簇，模块1富集了靶向miR-17-92基因簇（miR-17/20 ab）和miR-106 b-25基因簇（miR-106 b/93）的20个基因。综上所述，我们构建了6个基因模块，筛选出了一些可能作为胃癌潜在分子生物标志物的基因、转录因子和microRNA。(C)2014 Elsevier Inc. All rights reserved.
Gastric cancer remains one of the major health problems worldwide, and it is one of the most common cancers and the leading cause of cancer-related deaths in China. This study was to analyze the expression profiles of genes in gastric carcinoma, and predict potential regulating factors. The gene expression profile data GSE13911 was downloaded from Gene Expression Omnibus and the differentially expressed genes (DEGs) were identified by t-test. Gene modules were constructed using hierarchical clustering in R based on average linkage and Pearson's correlation coefficient and functional analysis for these genes were performed with DAVID. Genes in each module with Pearson's correlation coefficient >0.3 were obtained to construct co-expression network. Protein-protein interactions (PPIs) were identified by comparing protein-protein interaction (PPI) network with co-expression networks. In addition, the potential regulatory microRNAs and the transcription factors for each module were screened out. In this study, six modules associated with protein degradation, cell cycle, protein trafficking and immunoreaction were identified. COPS5 (COP9 Subunit 5) was the core protein in the largest PPI network of module 1. The transcription factors MYC and MAZ (Myc-associated zinc-finger protein) were enriched in module 1. A total of 9 microRNA-target bi-clusters were identified and module 1 enriched 20 genes targeting to miR-17-92 gene cluster(miR-17/20ab)and miR-106b-25 gene cluster (miR-106b/93). In conclusion, we constructed 6 gene modules and screened out some genes, transcriptional factors and microRNAs that may be used as potential molecular biomarkers for gastric carcinoma. (C) 2014 Elsevier Inc. All rights reserved.