Wang Yitong, Fan Hongyi, Zheng Liwei
College of Computer Science, Sichuan University, Chengdu, Sichuan 610065, P.R.China.
J BUON. 2018 Nov-Dec;23(6):1662-1670.
This study aimed to detect the differentially expressed genes between oral squamous cell carcinoma (OSCC) tissues and adjacent normal tissues, and perform pathway analysis and protein-protein interaction (PPI) analysis on differentially expressed genes (DEGs).
Gene Expression Omnibus (GEO) database related to human tumors was selected from the National Center for Biotechnology Information (NCBI), and GSE31056 and GSE3524, two microarrays containing OSCC gene expression data, were extracted from it. Analysis of differentially expressed genes in the two microarrays was performed using "R" software, and the volcanic map was drawn. Then, Venn diagram was used to integrate the differentially expressed genes screened out by the two microarrays, and PPI [Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG)] analysis of DEGs after integration was performed using Cytoscape, DAVID, STRING and KOBAS. A total of 207 differentially expressed genes were screened out by the two microarrays. 103 proteins encoded by differentially expressed genes screened out by STRING software had interaction. The expression network of differentially expressed genes was constructed, and some proteins, closely related to other proteins such as STAT1, were screened out by Cytoscape software.
GO analysis and KEGG analysis found that the differentially expressed genes were mainly enriched in "extracellular region", "extracellular region part" and "membrane-bound vesicle", and mainly involved in biological processes such as "Amoebiasis", "Glycerolipid metabolism" and "Arachidonic acid metabolism". In this study, 207 differentially expressed genes were successfully screened out from the two OSCC microarrays. PPI, GO and KEGG pathways of 103 interacting proteins were successfully constructed. Key genes were screened out, annotation and pathway analysis of which were performed.
This study was helpful to further study the relationship between OSCC gene directions.
本研究旨在检测口腔鳞状细胞癌（OSCC）组织与相邻正常组织之间的差异表达基因，并对差异表达基因进行通路分析和蛋白质-蛋白质相互作用（PPI）分析。
从美国国立生物技术信息中心（NCBI）选择与人类肿瘤相关的基因表达综合数据库（GEO），并从中提取包含OSCC基因表达数据的两个微阵列GSE31056和GSE3524。使用“R”软件对两个微阵列中的差异表达基因进行分析，并绘制火山图。然后，用韦恩图整合两个微阵列筛选出的差异表达基因，并使用Cytoscape、DAVID、STRING和KOBAS对整合后的差异表达基因进行PPI（基因本体论（GO）和京都基因与基因组百科全书（KEGG））分析。两个微阵列共筛选出207个差异表达基因。STRING软件筛选出的差异表达基因编码的103种蛋白质存在相互作用。构建差异表达基因的表达网络，并通过Cytoscape软件筛选出一些与STAT1等其他蛋白质密切相关的蛋白质。
GO分析和KEGG分析发现，差异表达基因主要富集于“细胞外区域”、“细胞外区域部分”和“膜结合囊泡”，主要参与“阿米巴病”、“甘油脂质代谢”和“花生四烯酸代谢”等生物学过程。本研究成功从两个OSCC微阵列中筛选出207个差异表达基因。成功构建了103种相互作用蛋白质的PPI、GO和KEGG通路。筛选出关键基因，并对其进行注释和通路分析。
本研究有助于进一步研究OSCC基因方向之间的关系。
