表达谱芯片与DNA甲基化芯片综合分析探索鼻咽癌发生、发展的分子靶标

Comprehensive analysis for microarray data of expression profile and DNA methylation to explore molecular targets of nasopharyngeal carcinogenesis

目的综合分析表达谱芯片与DNA甲基化芯片,探索鼻咽癌发生、发展的分子靶标与潜在治疗靶点。方法在GEO公共数据库下载编号为GSE64634的表达谱芯片数据以及编号为GSE52068的DNA甲基化芯片数据;利用R语言的相关工具包对表达谱芯片进行差异表达分析,对DNA甲基化芯片进行差异甲基化位点分析;利用DAVID数据库对筛选出的差异表达基因进行基因功能分析和信号通路分析;利用实时荧光定量PCR和甲基化特异性PCR进一步验证生物信息学分析的结果。结果表达谱芯片分析获得筛选出2 327个差异表达基因,其中1 777个基因表达下调,550个基因表达上调;DNA甲基化芯片分析获得2 321个差异甲基化位点,其中2 228个低甲基化位点,93个高甲基化位点;对表达谱芯片和DNA甲基化芯片进行综合分析,找到4个表达水平升高且甲基化修饰水平降低的基因,并利用定量PCR、表达谱芯片和DNA甲基化芯片成功验证该结果。结论综合分析表达谱芯片和DNA甲基化芯片,筛选出4个与鼻咽癌发生、发展相关的分子靶标和潜在的治疗靶点。

Objective The purpose of this study is to identify the biomarker and potential therapeutic targets for development of naso- pharyngeal carcinoma （NPC） by comprehensive analysis of gene expression and DNA methylation data. Methods The mieroarray data of expression profile （GSE64634） and DNA methylation （GSE52068） were downloaded from GEO public database. The differential ex- pression genes （DEGs） and differential methylated sites （DMSs） were identified based on R program package. GO and KEGG pathway analysis were performed for enriched analysis of the functions and signaling pathways of the target genes using DAVID database. Quanti- tative PCR and methylation-specifie PCR were used to verify the results of bioirlformatics analysis. Results A total of 2 327 differenti- ally expressed genes （DEGs） , including 1 777 up-regulated and 550 down-regulated genes, were obtained from mieroan＇ay data and 2 321 differentially methylated sites （DMS）, including 2 228 hypomethylation and 93 hypermethylation sites） were obtained from DNA methylation data. Four genes that were high expressed and hypomethylated genes simultaneously in nasopharyngeal carcinoma cells were identified by cross analysis. The expression level and DNA methylation level of the enriched genes were successfully verified by quanti- tative PCR and methylation-specific PCR. Conclusion Four potential biomarkers and therapeutic targets were found by combined bioinformatics analysis with the microarrays of expression profile and DNA methylation.