基于生物信息学分析的食管鳞状细胞癌关键枢纽基因的筛选及验证
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摘要
目的:采用多种生物信息学分析工具,筛选与食管鳞状细胞癌(esophageal squamous cell carcinoma, ESCC)发生发展相关的枢纽基因(Hub gene),并分析其生物学功能。方法:选取GEO食管鳞状细胞癌芯片数据GSE100942为研究对象,采用GEO2R软件对数据进行处理和分析,筛选差异表达基因,并通过生物信息学工具DAVID、String、Cytoscape构建差异表达基因的蛋白互作网络并筛选Hub基因;应用GO及KEGG进行生物功能富集分析;同时通过网络工具MiRDB寻找可能调控Hub基因的miRNA,并构建Hub基因-miRNA调控网络;利用GEPIA在线分析工具对筛选基因的表达和患者生存情况进行验证。结果:分析GSE100942芯片数据共筛选出1229个表达差异达2倍以上及223个表达差异达4倍以上的差异基因,以及在食管癌组织中表达均上调的20个Hub基因;功能富集分析显示这些差异基因主要富集到了癌症相关通路,并主要参与了细胞分裂及有丝核分裂等生物学过程;从Hub基因进一步鉴定了DLGAP5、BUB1B、TPX2、TTK、CDC20、CCNB2、AURKA、DEPDC1为食管鳞状细胞癌相关的8个关键Hub基因,他们参与了细胞增殖、细胞周期、信号通路等重要生物学过程。通过构建的miRNA调控网络分析,鉴定了CEP55、ECT2、NEK2、DEPDC1及NUSAP1等5个Hub基因受该网络高度调控。结论:基因芯片结合生物信息学方法能够有效分析与食管鳞状细胞癌发生发展相关的差异表达基因,筛选出的20个Hub基因和其中的8个关键基因可为进一步研究食管鳞状细胞癌发病的分子机制及分子标志物的筛选提供理论指导。
Objective: To screen the Hub genes associated with the occurrence and development of esophageal squamous cell carcinoma(ESCC) and to analyze their biological functions by using various bioinformatics analysis tools. Methods: ESCC chip profile GSE100942 from GEO database was used as study subject; GEO2 R tool was used to analyze the data and to screen the differentially expressed genes(DEGs), and the bioinformatics tools(DAVID, String, Cytoscape) were further used to construct protein-protein interaction(PPI) network and identify the key Hub genes. GO and KEGG were used for the biological function enrichment analysis. In the meanwhile, MiRDB was applied to identify the miRNAs that might regulate Hub genes and to construct Hub gene–miRNA network.Importantly, the expression of DEGs and the patient survival were verified by the GEPIA analysis tool. Results: By analyzing GSE100942 database, a total of 1229 DEGs with difference of 2 times and 223 DEGs with difference of 4 times were screened out. In addition, 20 Hub genes, which were all up-regulated in ESCC tissues, were also identified. The functional enrichment analysis showed that these DEGs were mainly enriched in cancer related pathways and involved in cell division and mitotic nuclear division. Among those 20 Hub genes, DLGAP5, BUB1 B, TPX2, TTK, CDC20, CCNB2, AURKA and DEPDC1 were identified as 8 key Hub genes that related with ESCC, and involved in many important biological processes, such as cell proliferation, cell cycle and signal pathway. Five Hub genes, CEP55, ECT2, NEK2, DEPDC1 and NUSAP1, were identified to be highly regulated by the miRNA regulatory network.Conclusion: Microarray combined with bioinformatics can effectively analyze the DEGs associated with the occurrence and development of ESCC. The identification of the 20 Hub genes and the 8 key Hub genes can provide theoretical guidance for further research on the molecular mechanism and molecular marker screening of ESCC.
Objective: To screen the Hub genes associated with the occurrence and development of esophageal squamous cell carcinoma(ESCC) and to analyze their biological functions by using various bioinformatics analysis tools. Methods: ESCC chip profile GSE100942 from GEO database was used as study subject; GEO2 R tool was used to analyze the data and to screen the differentially expressed genes(DEGs), and the bioinformatics tools(DAVID, String, Cytoscape) were further used to construct protein-protein interaction(PPI) network and identify the key Hub genes. GO and KEGG were used for the biological function enrichment analysis. In the meanwhile, MiRDB was applied to identify the miRNAs that might regulate Hub genes and to construct Hub gene–miRNA network.Importantly, the expression of DEGs and the patient survival were verified by the GEPIA analysis tool. Results: By analyzing GSE100942 database, a total of 1229 DEGs with difference of 2 times and 223 DEGs with difference of 4 times were screened out. In addition, 20 Hub genes, which were all up-regulated in ESCC tissues, were also identified. The functional enrichment analysis showed that these DEGs were mainly enriched in cancer related pathways and involved in cell division and mitotic nuclear division. Among those 20 Hub genes, DLGAP5, BUB1 B, TPX2, TTK, CDC20, CCNB2, AURKA and DEPDC1 were identified as 8 key Hub genes that related with ESCC, and involved in many important biological processes, such as cell proliferation, cell cycle and signal pathway. Five Hub genes, CEP55, ECT2, NEK2, DEPDC1 and NUSAP1, were identified to be highly regulated by the miRNA regulatory network.Conclusion: Microarray combined with bioinformatics can effectively analyze the DEGs associated with the occurrence and development of ESCC. The identification of the 20 Hub genes and the 8 key Hub genes can provide theoretical guidance for further research on the molecular mechanism and molecular marker screening of ESCC.
引文
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[16]RAMALH O-CARVALHO J,MARTINS J B,CEKAITE L,et al.Epigenetic disruption of miR-130a promotes prostate cancer by targeting SEC23B and DEPDC1[J].Cancer Lett,2017,385:150-159.DOI:10.1016/j.canlet.2016.10.028.
[2]BARRETT T,WILHITE S E,LEDOUX P,et al.NCBI GEO:archive for functional genomics data sets-update[J/OL].Nucleic Acids Res,2013,41(Database issue):D991-D995[2018-12-22].https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3531084.DOI:10.1093/nar/gks1193.
[3]ASHBURNER M,BALL C A,BLAKE J A,et al.Gene ontology:tool for the unification of biology.the gene ontology consortium[J].Nat Genet,2000,25(1):25-29.DOI:10.1038/75556.
[4]KANEHISA M.The KEGG database[J].Novartis Found Symp,2002,247:91-101.
[5]SHI Y X,YIN J Y,SHEN Y,et al.Genome-scale analysis identifies NEK2,DLGAP5 and ECT2 as promising diagnostic and prognostic biomarkers in human lung cancer[J].Sci Rep,2017,14;7(1):8072.DOI:10.1038/s41598-017-08615-5.
[6]SCHNEIDER M A,CHRISTOPOULOS P,MULEY T,et al.AUR-KA,DLGAP5,TPX2,KIF11 and CKAP5:Five specific mitosis-associated genes correlate with poor prognosis for non-small cell lung cancer patients[J].Int J Oncol,2017,50(2):365-372.DOI:10.3892/ijo.2017.3834.
[7]FRAGOSO M C,ALMEIDA M Q,MAZZUCO T L,et al.Combined expression of BUB1B,DLGAP5,and PINK1 as predictors of poor outcome in adrenocortical tumors:validation in a Brazilian cohort of adult and pediatric patients[J].Eur J Endocrinol,2012,166(1):61-67.DOI:10.1530/EJE-11-0806.
[8]XIE Y,LIN J Z,WANG A Q,et al.Threonine and tyrosine kinase may serve as a prognostic biomarker for gallbladder cancer[J].World J Gastroenterol,2017,21,23(31):5787-5797.DOI:10.3748/wjg.v23.i31.5787.
[9]LIU X,LIAO W,YUAN Q,et al.TTK activates Akt and promotes proliferation and migration of hepatocellular carcinoma cells[J].Oncotarget.2015,6(33):34309-34320.DOI:10.18632/oncotarget.5295.
[10]MIAO R,WU Y,ZHANG H,et al.Utility of the dual-specificity protein kinase TTK as a therapeutic target for intrahepatic spread of liver cancer[J].Sci Rep,2016,13(6):33121.DOI:10.1038/srep33121.
[11]KAPANIDOU M,CURTIS N L,BOLANOS-GARCIA V M.Cdc20:at the crossroads between chromosome segregation and mitotic exit[J].Trends Biochem Sci,2017,42(3):193-205.DOI:10.1016/j.tibs.2016.12.001.
[12]LEI C Y,WANG W,ZHU Y T,et al.The decrease of cyclin B2 expression inhibits invasion and metastasis of bladder cancer[J].Urol Oncol,2016,34(5):237.DOI:10.1016/j.urolonc.2015.11.011.
[13]WANG B,HSU C J,CHOU C H,et al.Variations in the AUR-KA gene:biomarkers for the development and progression of hepatocellular carcinoma[J].Int J Med Sci,2018,15(2):170-175.DOI:10.7150/ijms.22513.
[14]KANEHIRA M,HARADA Y,TAKATA R,et al.Involvement of upregulation of DEPDC1(DEP domain containing 1)in bladder carcinogenesis[J].Oncogene,2007,26(44):6448-6455.DOI:10.1038/sj.onc.1210466.
[15]YUAN S G,LIAO W J,YANG J J,et al.DEP domain containing 1is a novel diagnostic marker and prognostic predictor for hepatocellular carcinoma[J].Asian Pac J Cancer Prev,2014,15(24):10917-10922.
[16]RAMALH O-CARVALHO J,MARTINS J B,CEKAITE L,et al.Epigenetic disruption of miR-130a promotes prostate cancer by targeting SEC23B and DEPDC1[J].Cancer Lett,2017,385:150-159.DOI:10.1016/j.canlet.2016.10.028.