Identification of DNA methylation-driven genes in esophageal squamous cell carcinoma: a study based on The Cancer Genome Atlas
Identification of DNA methylation-driven genes in esophageal squamous cell carcinoma: a study based on The Cancer Genome Atlas
复制标题
DOI：
10.1186/s12935-019-0770-9
复制
发表时间：
2019-03-06
影响因子：
5.8
通讯作者：
Jiao, Wenjie
中科院分区：
文献类型：
--
作者：
Lu, Tong;Chen, Di;Jiao, Wenjie
背景异常 DNA 甲基化与食管鳞状细胞癌 (ESCC) 显着相关。在本研究中，我们旨在通过综合生物信息学分析研究食管鳞癌中DNA甲基化驱动的基因。方法从TCGA数据库下载DNA甲基化和转录组分析数据。 DNA甲基化驱动基因通过methylmix R包获得。 David数据库和ConsensusPathDB分别用于进行基因本体（GO）分析和通路分析。使用Survival R包对甲基化驱动基因进行总体生存分析。结果methylmix共鉴定出26个DNA甲基化驱动基因，这些基因富集了DNA结合和转录因子活性的分子功能。然后，ABCD1、SLC5A10、SPIN3、ZNF69 和 ZNF608 被认为是 26 个甲基化驱动基因的重要独立预后生物标志物。此外，结合甲基化和基因表达数据的进一步综合生存分析发现 ABCD1、CCDC8、FBXO17 与患者的生存显着相关。此外，还发现多个异常甲基化位点与基因表达相关。结论综上所述，我们通过生物信息学分析研究了食管鳞癌中DNA甲基化驱动的基因，有助于更好地了解食管鳞癌的分子机制，并为精准治疗和预后检测提供潜在的生物标志物。
BackgroundAberrant DNA methylations are significantly associated with esophageal squamous cell carcinoma (ESCC). In this study, we aimed to investigate the DNA methylation-driven genes in ESCC by integrative bioinformatics analysis.MethodsData of DNA methylation and transcriptome profiling were downloaded from TCGA database. DNA methylation-driven genes were obtained by methylmix R package. David database and ConsensusPathDB were used to perform gene ontology (GO) analysis and pathway analysis, respectively. Survival R package was used to analyze overall survival analysis of methylation-driven genes.ResultsTotally 26 DNA methylation-driven genes were identified by the methylmix, which were enriched in molecular function of DNA binding and transcription factor activity. Then, ABCD1, SLC5A10, SPIN3, ZNF69, and ZNF608 were recognized as significant independent prognostic biomarkers from 26 methylation-driven genes. Additionally, a further integrative survival analysis, which combined methylation and gene expression data, was identified that ABCD1, CCDC8, FBXO17 were significantly associated with patients' survival. Also, multiple aberrant methylation sites were found to be correlated with gene expression.ConclusionIn summary, we studied the DNA methylation-driven genes in ESCC by bioinformatics analysis, offering better understand of molecular mechanisms of ESCC and providing potential biomarkers precision treatment and prognosis detection.