Exploration of methylation-driven genes for monitoring and prognosis of patients with lung adenocarcinoma

被引:34
|
作者
Gao, Chundi [1 ]
Zhuang, Jing [2 ,3 ]
Li, Huayao [1 ]
Liu, Cun [4 ]
Zhou, Chao [2 ,3 ]
Liu, Lijuan [2 ,3 ]
Sun, Changgang [2 ,3 ]
机构
[1] Shandong Univ Tradit Chinese Med, Coll Clin Med 1, Jinan 250014, Shandong, Peoples R China
[2] Weifang Med Univ, Affiliated Hosp, Dept Oncol, Weifang 261031, Shandong, Peoples R China
[3] Weifang Tradit Chinese Hosp, Dept Oncol, Weifang 261041, Shandong, Peoples R China
[4] Shandong Univ Tradit Chinese Med, Coll Tradit Chinese Med, Jinan 250014, Shandong, Peoples R China
基金
中国国家自然科学基金;
关键词
Lung adenocarcinoma; DNA methylation-driven genes; Biomarkers; Cox proportional hazards regression; Survival analysis; DNA METHYLATION; PROMOTER METHYLATION; DOWN-REGULATION; POOR-PROGNOSIS; MESSENGER-RNA; NEVER-SMOKERS; CANCER; EXPRESSION; CLASSIFICATION; PREDICTION;
D O I
10.1186/s12935-018-0691-z
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
BackgroundAs one of the most common malignant tumors in humans, lung cancer has experienced a gradual increase in morbidity and mortality. This study examined prognosis-related methylation-driven genes specific to lung adenocarcinoma (LUAD) to provide a basis for prognosis prediction and personalized targeted therapy for LUAD patients.MethodsThe methylation and survival time data from LUAD patients in the TCGA database were downloaded. The MethylMix algorithm was used to identify the differential methylation status of LUAD and adjacent tissues based on the -mixture model to obtain disease-related methylation-driven genes. A COX regression model was then used to screen for LUAD prognosis-related methylation-driven genes, and a linear risk model based on five methylation-driven gene expression profiles was constructed. A methylation and gene expression combined survival analysis was performed to further explore the prognostic value of 5 genes independently.ResultsThere were 118 differentially expressed methylation-driven genes in the LUAD tissues and adjacent tissues. Five of the genes, CCDC181, PLAU, S1PR1, ELF3, and KLHDC9, were used to construct a prognostic risk model. Overall, the survival time was significantly lower in the high-risk group compared with that in the low-risk group (P<0.05). In addition, the methylation and gene expression combined survival analysis found that the combined expression levels of the genes CCDC181, PLAU, and S1PR1 as well as KLHDC9 alone can be used as independent prognostic markers or drug targets.ConclusionOur findings provide an important bioinformatic basis and relevant theoretical basis for guiding subsequent LUAD early diagnosis and prognosis assessments.
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页数:11
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