ArticleScientific reports2021
Identification of a methylomics-associated nomogram for predicting overall survival of stage I-II lung adenocarcinoma.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 6 citations in OpenAlex.
- Development and validation of a 5mC-based prognostic model for lung adenocarcinoma survival.Cell reports. Medicine · 2026Article
- Translating tumor epigenetic subtyping into methylome network-based prognostic models in early-stage NSCLC: results from the prospective MOBIT study.Journal of translational medicine · 2026Article
- Methods in DNA methylation array dataset analysis: A review.Computational and structural biotechnology journal · 2024Review
- A Novel Methylation-based Model for Prognostic Prediction in Lung Adenocarcinoma.Current genomics · 2024Article
- Autoencoder-based multimodal prediction of non-small cell lung cancer survival.Scientific reports · 2023Article
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5 authors at 2 institutions in 1 country.
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Abstract
The aim of this paper was to identify DNA methylation based biomarkers for predicting overall survival (OS) of stage I-II lung adenocarcinoma (LUAD) patients. Methylation profile data of patients with stage I-II LUAD from The Cancer Genome Atlas (TCGA) database was used to determine methylation sites-based hallmark for stage I-II LUAD patients' OS. The patients were separated into training and validation datasets by using median risk score as cutoff. Univariate Cox, least absolute shrinkage and selection operator (LASSO) and multivariate Cox analyses were employed to develop a DNA methylation signature for OS of patients with stage I-II LUAD. As a result, an 11-DNA methylation signature was determined to be critically associated with the OS of patients with stage I-II LUAD. Analysis of receiver operating characteristics (ROC) suggested a high prognostic effectiveness of the 11-DNA methylation signature in patients with stage I-II LUAD (AUC at 1, 3, 5 years in training set were (0.849, 0.879, 0.831, respectively), validation set (0.742, 0.807, 0.904, respectively), entire TCGA dataset (0.747, 0.818, 0.870, respectively). Kaplan-Meier survival analyses exhibited that survival was significantly longer in the low-risk cohort compared to the high-risk cohort in the training dataset (P = 7e - 07), in the validation dataset (P = 1e - 08), and in the all-cohort dataset (P = 6e - 14). In addition, a nomogram was developed based on molecular factor (methylation risk score) as well as clinical factors (age and cancer status) (AUC at 1, 3, 5 years entire TCGA dataset were 0.770, 0.849, 0.979, respectively). The result verified that our methylomics-associated nomogram had a strong robustness for predicting stage I-II LUAD patients' OS. Furthermore, the nomogram combined clinical and molecular factors to determine an individualized probability of recurrence for patients with stage I-II LUAD, which stood for a major advance in the field of personalized medicine for pulmonary oncology. Collectively, we successfully identified a DNA methylation biomarker and a DNA methylation-based nomogram to predict the OS of patients with stage I-II LUAD.
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