整合多组学数据搜寻胃癌的驱动基因
Integrating Multiple Omics Data to Search for Driver Genes for Gastric Cancer
摘要: 目的：寻找对胃癌的发生发展有驱动作用的基因和信号通路，为胃癌的靶向治疗提供可能的靶点。方法：从TCGA下载胃癌的RNA-Seq和DNA拷贝数变异数据，利用Perl脚本和R语言中的edgR包筛选出既差异表达且拷贝数发生变异的基因。将筛选出的基因进行基因功能富集分析和通路分析。再将富集过后的基因上传String数据库，生成蛋白质相互作用网络(PPI)，进而从PPI网络中分离出结合度高的稠密子网络，最后结合MalaCards疾病数据库构建胃癌的核心网络，进而寻找因差异表达与基因拷贝数呈正相关的基因。结果：本文一共筛选出26个胃癌驱动基，以及PI3K-Akt信号通路、ECM-受体相互作用、Wnt信号通路和胃酸分泌等可能与胃癌的发生发展相关的信号通路，为胃癌的诊断和治疗提供潜在的靶点。
Abstract: Aims: To find driving genes and signal pathways that cause the occurrence and development of gastric cancer, in order to provide possible targets for targeted therapy of gastric cancer. Methods: This paper downloads RNA-Seq and DNA copy number variation data of gastric cancer from TCGA, uses Perl script and the edgR package in R language to screen out genes that are differentially expressed and have copy number variation; then performs gene function enrichment analysis and pathway analysis of the selected genes; after then uploads the enriched genes to the String data-base to generate a protein interaction network (PPI), and then separates dense sub-networks with high binding degree from the PPI network. Finally, it combines with MalaCards disease database to construct the core network of gastric cancer, and then finds genes whose differential expression is positively correlated with gene copy number. Results: This paper screened a total of 26 gastric cancer driving groups, as well as PI3K-Akt signaling pathway, ECM-receptor interaction, Wnt signaling pathway, gastric acid secretion and other signaling pathways that may be related to the occurrence and development of gastric cancer to provide potential targets for the diagnosis and treatment of gastric cancer.
文章引用：杨正伟, 张娟. 整合多组学数据搜寻胃癌的驱动基因[J]. 计算机科学与应用, 2020, 10(10): 1820-1833. https://doi.org/10.12677/CSA.2020.1010192

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