DNA methylations associated with survival of lung adenocarcinoma with TCGA database
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    Abstract:

    Objective:The aim of this study was to investigate the DNA methylation sites associated with the prognosis of patients with lung adenocarcinoma in the whole genome-level with the data-mining for TCGA (The Cancer Genome Atlas)public database. Methods:The clinical data of lung adenocarcinoma patients was downloaded from TCGA database in April,2016,as well as genome-wide DNA methylation data with Illumina’s Infinum Human Methylation 450 Bead Chips (HM450). After data linked,232 cases of lung adenocarcinoma with the information of both clinic and methylation were finally included in this study. A Cox’s proportional hazards regression analysis was conducted to assess the relationship between DNA methylation levels or mRNA expression and the overall survival of lung adenocarcinoma patients,further evaluate the correlation between DNA methylation and mRNA expression,as well as the relationship between mRNA expression and lung adenocarcinoma survival. Results:The mean age and survival time of 232 people with lung adenocarcinoma was (64.823 ± 9.300)years and (20.217 ± 17.067)months. cg03955927 located in EHBP1 was found to be the strongest methylation site in this study which was associated with the survival of lung adenocarcinoma,adjusted HRs(hazard ratio)were 0.605 (0.501-0.731),P=1.98×10-7. Among the strongest 20 methylation sites,the high methylation level of 17 sites were considered as protective factors for the survival of lung adenocarcinoma and that of other 3 sites were risk factors. The methylation levels of 5 methylation sites affect the targeted gene’s mRNA expression. In addtion,the mRNA expression of KRI1 was associated with the survival of lung adenocarcinoma,adjusted HRs were 1.316(1.109-1.561)with a P value of 0.001 6. Conclusion:With TCGA data mining,we found that methylation site in KRI1 gene region is highly related to lung adenocarcinoma prognosis,as further study biomarker related to prognosis of lung cancer.

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王 可,赵荣仙,杨素莲,孟 瑜,魏 晟.基于TCGA数据库挖掘肺腺癌预后相关的甲基化位点和基因[J].南京医科大学学报(自然科学版英文版),2016,(6):665-669.

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  • Received:May 10,2016
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  • Online: June 15,2016
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