ArticleOncology letters2019
DNA methylation profiling analysis identifies a DNA methylation signature for predicting prognosis and recurrence of lung adenocarcinoma.
Article in Oncology letters, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 28 citations in OpenAlex.
- Methylation signatures distinguish non-small cell lung cancer subtypes and are associated with survival in smokers with lung squamous cell carcinoma.Journal of the National Cancer Institute · 2026Article
- Impact of piR_004530 reactivation in lung cancer: implications for recurrence and survival of lung squamous cell carcinoma patients.BMC medicine · 2025Article
- Epithelial and immune transcriptomic characteristics and possible regulatory mechanisms in asthma exacerbation: insights from integrated studies.Frontiers in immunology · 2025Article
- DNA damage repair-related methylated genes RRM2 and GAPDH are prognostic biomarkers associated with immunotherapy for lung adenocarcinoma.Genetics and molecular biology · 2025Article
- A Novel Methylation-based Model for Prognostic Prediction in Lung Adenocarcinoma.Current genomics · 2024Article
- Association of frequent hypermethylation with high grade histological subtype in lung adenocarcinoma.Cancer science · 2023Article
- Clinical applications of DNA methylation profiling in lung cancer.Translational lung cancer research · 2023Article
- Prognostic biomarkers of pancreatic cancer identified based on a competing endogenous RNA regulatory network.Translational cancer research · 2022Article
- Article
- Methylation- and homologous recombination deficiency-related mutant genes predict the prognosis of lung adenocarcinoma.Journal of clinical laboratory analysis · 2022Article
- Characterization of Butyrate-Resistant Colorectal Cancer Cell Lines and the Cytotoxicity of Anticancer Drugs against These Cells.BioMed research international · 2022Article
- A functional methylation signature to predict the prognosis of Chinese lung adenocarcinoma based on TCGA.Cancer medicine · 2022Article
- Article
- A methylation-based nomogram for predicting survival in patients with lung adenocarcinoma.BMC cancer · 2021Article
- DNA Methylation Analysis Identifies Patterns in Progressive Glioma Grades to Predict Patient Survival.International journal of molecular sciences · 2021Article
- Identification of a novel prognostic DNA methylation signature for lung adenocarcinoma based on consensus clustering method.Cancer medicine · 2020Article
- Correlation amongTranslational cancer research · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of the present study was to identify candidate prognostic DNA methylation biomarkers for lung adenocarcinoma (LUAD), since the modern precise medicine for the treatment of LUAD requires more biomarkers and novel therapeutic targets of interest. DNA methylation profiling data of LUAD were downloaded from The Cancer Gene Atlas portal. Differentially methylated genes (DMGs) were screened to differentiate between samples designated as good and bad prognosis. LUAD-associated methylation modules were obtained with the weighted correlation network analysis (WGCNA) package, followed by function enrichment analysis. Optimal prognostic DMGs were selected using the LASSO estimation-based Cox-PH approach and were used to construct a prognostic risk scoring system. The training set was dichotomized by risk score, into high- and low-risk groups. The differences in overall survival (OS) time or recurrence-free survival (RFS) time between the two groups were evaluated using a Kaplan-Meier curve. A total of 742 DMG samples were screened for good and bad prognosis. WGCNA identified three LUAD-associated modules, which were primarily associated with cytoskeleton organization, transcription and apoptosis. A nine-gene prognostic methylation signature was determined, which included
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.