Hu Yangzhi, Hu Zhili, Ding Hui, Li Yuan, Zhao Xiaoxu, Shao Mingtao, Pan Yunlong
Department of General Surgery, The First Affiliated Hospital of Jinan University, Guangzhou, China.
Department of Gastrointestinal Surgery, The Affiliated Hospital of Xiangnan University, Chenzhou, China.
Transl Cancer Res. 2020 Sep;9(9):5459-5472. doi: 10.21037/tcr-20-926.
We aimed to identify the key differentially expressed genes (DEGs) associated with poor prognosis in gastric cancer (GC) and to elucidate the underlying molecular mechanisms in order to provide a therapeutic target for this disease.
The DEGs common in two datasets, GSE54129 and GSE79973, were screened. GO and KEGG enrichment analyses were then performed for these DEGs using DAVID's tool. STRING and the Cytoscope software were also used to analyze the protein-protein interaction (PPI) networks of the DEGs common between the two datasets.
A total of 164 common DEGs were identified from GSE79973 and GSE54129 datasets, 42 were up-regulated and 122 were down-regulated in GC. KEGG analysis demonstrated that up-regulated DEGs were mainly enriched for focal adhesion, ECM-receptor interaction, PI3K-Akt signaling pathway, protein digestion and absorption, and vascular smooth muscle contraction, while down-regulated DEGs were enriched for chemical carcinogenesis, metabolism of xenobiotics by cytochrome P450, drug metabolism-cytochrome P450, and retinol metabolism (P<0.05). Obtained PPI network for the 164 DEGs via Cytotype software, using MCODE app of Cytotype software we identified 13 hub genes. Twelve of these genes were found to be associated with poor prognosis in GC by survival analysis. Post validation by the GEPIA, Oncomine, and Human Protein Atlas databases, eight genes (, , , , , , , and ) were found to be up-regulated in GC tissues and correlated with poor prognosis of GC.
, , , , , , , and could serve as potential targets for GC diagnosis and prognosis.
我们旨在鉴定与胃癌(GC)预后不良相关的关键差异表达基因(DEGs),并阐明其潜在的分子机制,以便为该疾病提供治疗靶点。
筛选两个数据集GSE54129和GSE79973中共同的DEGs。然后使用DAVID工具对这些DEGs进行GO和KEGG富集分析。STRING和Cytoscope软件也用于分析两个数据集之间共同的DEGs的蛋白质-蛋白质相互作用(PPI)网络。
从GSE79973和GSE54129数据集中共鉴定出164个共同的DEGs,其中42个在GC中上调,122个下调。KEGG分析表明,上调的DEGs主要富集于粘着斑、细胞外基质-受体相互作用、PI3K-Akt信号通路、蛋白质消化和吸收以及血管平滑肌收缩,而下调的DEGs则富集于化学致癌作用、细胞色素P450对外源生物的代谢、药物代谢-细胞色素P450和视黄醇代谢(P<0.05)。通过Cytotype软件获得164个DEGs的PPI网络,使用Cytotype软件的MCODE应用程序我们鉴定出13个枢纽基因。通过生存分析发现其中12个基因与GC的预后不良相关。经GEPIA、Oncomine和人类蛋白质图谱数据库的进一步验证,发现8个基因(,,,,,,,和)在GC组织中上调,并与GC的不良预后相关。
,,,,,,,和可作为GC诊断和预后的潜在靶点。