期刊论文详细信息
BMC Cancer
A methylation-based nomogram for predicting survival in patients with lung adenocarcinoma
Xiong Luo1  Bin Zhou2  Jianxin Zuo2  Yanchao Liu2  Xuelong Wang2  Xin Bi2  Chengwei Zhang2  Yuxin Xia3 
[1] Department of Internal Medicine, Beijing Nuclear Industry Hospital, 100822, Beijing, China;Department of Thoracic Surgery, Capital Medical University Electric Power Teaching Hospital, 100073, Beijing, China;Department of emergency, Capital Medical University Electric Power Teaching Hospital, 100073, Beijing, China;
关键词: Lung adenocarcinoma;    DNA methylation;    Differentially methylated sites;    Prognosis;    Signature;   
DOI  :  10.1186/s12885-021-08539-4
来源: Springer
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【 摘 要 】

BackgroundDNA methylation alteration is frequently observed in Lung adenocarcinoma (LUAD) and may play important roles in carcinogenesis, diagnosis, and prognosis. Thus, this study aimed to construct a reliable methylation-based nomogram, guiding prognostic classification screening and personalized medicine for LUAD patients.MethodThe DNA methylation data, gene expression data and corresponding clinical information of lung adenocarcinoma samples were extracted from The Cancer Genome Atlas (TCGA) database. Differentially methylated sites (DMSs) and differentially expressed genes (DEGs) were obtained and then calculated correlation by pearson correlation coefficient. Functional enrichment analysis and Protein-protein interaction network were used to explore the biological roles of aberrant methylation genes. A prognostic risk score model was constructed using univariate Cox and LASSO analysis and was assessed in an independent cohort. A methylation-based nomogram that included the risk score and the clinical risk factors was developed, which was evaluated by concordance index and calibration curves.ResultWe identified a total of 1362 DMSs corresponding to 471 DEGs with significant negative correlation, including 752 hypermethylation sites and 610 hypomethylation sites. Univariate cox regression analysis showed that 59 DMSs were significantly associated with overall survival. Using LASSO method, we constructed a three-DMSs signature that was independent predictive of prognosis in the training cohort. Patients in high-risk group had a significant shorter overall survival than patients in low-risk group classified by three-DMSs signature (log-rank p = 1.9E-04). Multivariate cox regression analysis proved that the three-DMSs signature was an independent prognostic factor for LUAD in TCGA-LUAD cohort (HR = 2.29, 95%CI: 1.47–3.57, P = 2.36E-04) and GSE56044 cohort (HR = 2.16, 95%CI: 1.19–3.91, P = 0.011). Furthermore, a nomogram, combining the risk score with clinical risk factors, was developed with C-indexes of 0.71 and 0.70 in TCGA-LUAD and GSE56044 respectively.ConclusionsThe present study established a robust three-DMSs signature for the prediction of overall survival and further developed a nomogram that could be a clinically available guide for personalized treatment of LUAD patients.

【 授权许可】

CC BY   

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