Development and validation of a 5mC-based prognostic model for lung adenocarcinoma survival

Lung adenocarcinoma (LUAD) exhibits marked prognostic heterogeneity. Existing methylation-based prognostic models lack robustness, accuracy, or external validation, limiting their clinical utility. We develop MethPro-LUAD, a prognostic model based on eight 5-methylcytosine features, using TCGA-LUAD data (training, N = 269; testing, N = 180), and validate the model across two independent hospital cohorts (Beijing, N = 195; Nanjing, N = 88) and two external GEO datasets (N = 82 and N = 155) to ensure its generalizability and effectiveness. MethPro-LUAD stratifies patients into high- and low-risk groups, with high-risk individuals consistently showing significantly shorter overall survival across all cohorts. In addition, the model's predictive performance remains robust in subgroups defined by age, sex, stage, and EGFR mutation and in disease-free survival analyses. Compared with other reported LUAD prognostic models, MethPro-LUAD demonstrates better performance across cohorts, which offers valuable support for personalized postoperative treatment and follow-up, and warrants further prospective evaluation, highlighting its strong potential for clinical translation through feasible targeted assays.

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Publication Details

Journal
Cell Reports Medicine
Published
2026-04-01
DOI
https://doi.org/10.1016/j.xcrm.2026.102727
Primary Topic
Lung Cancer Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00

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article

Development and validation of a 5mC-based prognostic model for lung adenocarcinoma survival

Jian‐Qun Chen, Daoyun Wang, P. F. Chen, Jianchao Xue et al.
Cell Reports Medicine
Lung Cancer Diagnosis and Treatment
article

Development and validation of a 5mC-based prognostic model for lung adenocarcinoma survival

Jian‐Qun Chen, Daoyun Wang, P. F. Chen, Jianchao Xue, Qihan Chen, Xiaoyi Zheng, Nan Liang, Zichen Jiao, Li Wu, Zhicheng Huang, Yao Tang, Qiang Wang, Tao Wang
article en

Abstract

Lung adenocarcinoma (LUAD) exhibits marked prognostic heterogeneity. Existing methylation-based prognostic models lack robustness, accuracy, or external validation, limiting their clinical utility. We develop MethPro-LUAD, a prognostic model based on eight 5-methylcytosine features, using TCGA-LUAD data (training, N = 269; testing, N = 180), and validate the model across two independent hospital cohorts (Beijing, N = 195; Nanjing, N = 88) and two external GEO datasets (N = 82 and N = 155) to ensure its generalizability and effectiveness. MethPro-LUAD stratifies patients into high- and low-risk groups, with high-risk individuals consistently showing significantly shorter overall survival across all cohorts. In addition, the model's predictive performance remains robust in subgroups defined by age, sex, stage, and EGFR mutation and in disease-free survival analyses. Compared with other reported LUAD prognostic models, MethPro-LUAD demonstrates better performance across cohorts, which offers valuable support for personalized postoperative treatment and follow-up, and warrants further prospective evaluation, highlighting its strong potential for clinical translation through feasible targeted assays.

Cell Reports MedicineVol. 7(4)
Chinese Academy of Medical Sciences & Peking Union Medical College (CN), University of Macau (MO), Peking Union Medical College Hospital (CN), Nanjing Drum Tower Hospital (CN), Fujian University of Technology (CN), Nanjing University (CN)
Universidade de Macau, Fundo para o Desenvolvimento das Ciências e da Tecnologia, National Key Research and Development Program of China
Good health and well-being
Openalex Percentile: Top 30%
Lung Cancer Diagnosis and Treatment
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