...
首页> 外文期刊>Journal of computational biology >Methylation Signature Genes Identification of the Lung Squamous Cell Carcinoma Occurrence and Recognition Research
【24h】

Methylation Signature Genes Identification of the Lung Squamous Cell Carcinoma Occurrence and Recognition Research

机译:肺鳞状细胞癌的甲基化特征基因鉴定与识别研究

获取原文
           

摘要

DNA methylation (DNAm) is one of the most important epigenetic event effecting gene expression, and aberrant DNAm has been implicated in the initiation and progression of human cancers. To identify methylation (ME) signature genes for the pathogenesis of lung squamous cell carcinoma (LUSC), the pattern recognition method was used to analyze the genome-wide gene ME data, which were collected from the LUSC normal and cancer stage I samples in The Cancer Genome Atlas project database. A total of 102 ME signature genes were identified by means of a combination of statistical methods such as correlation, analysis of variance, and Elastic Net. The accuracy and specificity are all above 99%, sensitivity is 100%, and Matthews correlation coefficient is higher than 0.99 through the machine learning method modeling, which are higher than the previous study. The Kyoto Encyclopedia of Genes and Genomes pathway analysis and Gene Ontology enrichment analysis indicated the highly related relationship among these genes. They also indicated the immediate relationship between our signature genes and the occurrence of LUSC, which is very important to the understanding of its mechanism and to the development of new targeted therapy.
机译:DNA甲基化(DNAm)是影响基因表达的最重要的表观遗传事件之一,异常的DNAm与人类癌症的发生和发展有关。为了识别甲基化(ME)签名基因用于肺鳞状细胞癌(LUSC)的发病机理,使用模式识别方法分析了全基因组基因ME数据,这些数据是从LUSC正常人和癌症I期样本中收集的。癌症基因组图谱项目数据库。通过统计方法(例如相关性,方差分析和Elastic Net)的组合,总共鉴定了102个ME签名基因。通过机器学习方法建模,其准确性和特异性均在99%以上,灵敏度为100%,并且Matthews相关系数高于0.99,高于先前的研究。京都基因与基因组百科全书路径分析和基因本体论富集分析表明这些基因之间的高度相关性。他们还指出了我们标志性基因与LUSC发生之间的直接关系,这对于理解其机制和开发新的靶向疗法非常重要。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号