文献类型：期刊文献

中文题名：利用RNA-seq数据分析肝细胞癌差异表达基因及蛋白相互作用

英文题名：Analysis of Differentially Expressed Genes and Protein-Protein Interaction in Hepatocellular Carcinoma Based on RNA-seq Data

作者：张建华[1];应安娜[1];俞梦琪[1];俞冰楠[1]

机构：[1]绍兴文理学院医学院,绍兴312000

年份：2019

卷号：38

期号：1

起止页码：461

中文期刊名：基因组学与应用生物学

外文期刊名：Genomics and Applied Biology

收录：CSTPCD、、北大核心2017、CSCD2019_2020、北大核心、CSCD

基金：浙江省绍兴市科技计划项目(2018C30028)资助

语种：中文

中文关键词：肝细胞癌;RNA—seq;差异表达基因;蛋白质相互作用网络

外文关键词：Hepatocellular carcinoma;RNA-seq;Differentially expressed genes;Protein-protein interaction network

中文摘要：RNA-Seq已成为当前转录组学研究的强有力工具,尤其在肿瘤差异表达基因的筛选方面有重要的应用价值。为进一步阐明肝细胞癌(HCC)的分子机制,本研究对GEO中1个包括12对HCC组织标本的RNA-Seq数据集(GSE63863)进行了生物信息学分析。采用edgeR、DESeq2、voom等3种不同算法的软件进行统计分析,共获得976个差异表达基因(adj. p-value<0.01或FDR<0.01,|logFC|≥2),其中上调表达422个(43.2%),下调554个(56.8%)。GO富集分析显示这些差异表达基因主要涉及离子结合、氧化还原酶活性等分子功能以及氧化还原、细胞分裂等生物学过程;KEGG通路分析显示,这些差异表达基因主要涉及细胞周期、视黄醇等代谢通路。STRING分析显示,共有654个基因编码的蛋白质存在相互作用,进一步利用MCODE分析显示,169个基因编码蛋白构成4个子网络,相应的中心节点基因分别为UBE2C、GNG4、TTR、FOS,这些基因的异常表达可能在HCC的发生发展过程中具有重要作用。上述研究结果将为进一步阐明HCC分子发病机制、寻找新型生物标志物提供初步的依据。

外文摘要：RNA-Seq has emerged as a powerful research tool to transcriptomics, especially for screening differentially expressed genes(DEGs) of cancer. To further clarify the molecular mechanism of hepatocellular carcinoma(HCC), an RNA-Seq dataset(GSE63863) including 12 matched pairs of HCC tissue samples in GEO was performed with bioinformatics analysis. Three software in different algorithms of edgeR, DESeq2 and voom were applied for statistical analysis. A total of 976 differentially expressed genes were obtained(adj. p-value<0.01 or FDR<0.01, |logFC|≥2), including 422 upregulated genes(43.2%) and 554 downregulated(56.8%) genes. GO enrichment analysis indicated that these differentially expressed genes were mainly involved in molecular functions such as ion binding, oxidoreductase activity, etc., and biological processes(such as oxidation-reduction process, cell division, etc. KEGG pathways analysis showed that these differentially expressed genes were mainly involved in metabolic pathways such as cell cycle, retinol metabolism, etc.. STRING analysis suggested that a total of 654 gene encoded protein were interreacted. 169 proteins were clustered into 4 sub-networks further analyzed by MCODE, and the corresponding central node genes were UBE2 C, GNG4, TTR and FOS, respectively. Abnormal expression of these genes might play an impartment role in the development of HCC. These findings would provide preliminary basis for further illustrating the molecular pathogenesis, and finding new biomarkers of HCC.