A methylation-based nomogram for predicting survival in patients with lung adenocarcinoma

Abstract Background DNA 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 per...

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Main Authors: Xuelong Wang, Bin Zhou, Yuxin Xia, Jianxin Zuo, Yanchao Liu, Xin Bi, Xiong Luo, Chengwei Zhang
Format: Article
Language:English
Published: BMC 2021-07-01
Series:BMC Cancer
Subjects:
Online Access:https://doi.org/10.1186/s12885-021-08539-4
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author Xuelong Wang
Bin Zhou
Yuxin Xia
Jianxin Zuo
Yanchao Liu
Xin Bi
Xiong Luo
Chengwei Zhang
author_facet Xuelong Wang
Bin Zhou
Yuxin Xia
Jianxin Zuo
Yanchao Liu
Xin Bi
Xiong Luo
Chengwei Zhang
author_sort Xuelong Wang
collection DOAJ
description Abstract Background DNA 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. Method The 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. Result We 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. Conclusions The 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.
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spelling doaj.art-9c22e9aeb73e4127b3e7444e3a8ded3c2022-12-21T18:23:59ZengBMCBMC Cancer1471-24072021-07-0121111210.1186/s12885-021-08539-4A methylation-based nomogram for predicting survival in patients with lung adenocarcinomaXuelong Wang0Bin Zhou1Yuxin Xia2Jianxin Zuo3Yanchao Liu4Xin Bi5Xiong Luo6Chengwei Zhang7Department of Thoracic Surgery, Capital Medical University Electric Power Teaching HospitalDepartment of Thoracic Surgery, Capital Medical University Electric Power Teaching HospitalDepartment of emergency, Capital Medical University Electric Power Teaching HospitalDepartment of Thoracic Surgery, Capital Medical University Electric Power Teaching HospitalDepartment of Thoracic Surgery, Capital Medical University Electric Power Teaching HospitalDepartment of Thoracic Surgery, Capital Medical University Electric Power Teaching HospitalDepartment of Internal Medicine, Beijing Nuclear Industry HospitalDepartment of Thoracic Surgery, Capital Medical University Electric Power Teaching HospitalAbstract Background DNA 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. Method The 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. Result We 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. Conclusions The 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.https://doi.org/10.1186/s12885-021-08539-4Lung adenocarcinomaDNA methylationDifferentially methylated sitesPrognosisSignature
spellingShingle Xuelong Wang
Bin Zhou
Yuxin Xia
Jianxin Zuo
Yanchao Liu
Xin Bi
Xiong Luo
Chengwei Zhang
A methylation-based nomogram for predicting survival in patients with lung adenocarcinoma
BMC Cancer
Lung adenocarcinoma
DNA methylation
Differentially methylated sites
Prognosis
Signature
title A methylation-based nomogram for predicting survival in patients with lung adenocarcinoma
title_full A methylation-based nomogram for predicting survival in patients with lung adenocarcinoma
title_fullStr A methylation-based nomogram for predicting survival in patients with lung adenocarcinoma
title_full_unstemmed A methylation-based nomogram for predicting survival in patients with lung adenocarcinoma
title_short A methylation-based nomogram for predicting survival in patients with lung adenocarcinoma
title_sort methylation based nomogram for predicting survival in patients with lung adenocarcinoma
topic Lung adenocarcinoma
DNA methylation
Differentially methylated sites
Prognosis
Signature
url https://doi.org/10.1186/s12885-021-08539-4
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