ArticleBiomarker research2023
Accurate detection of early-stage lung cancer using a panel of circulating cell-free DNA methylation biomarkers.
Article in Biomarker research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.
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
24 citing papers in PubMed, 1 synthesis or guideline pooled it, 32 citations in OpenAlex.
- Raman Spectroscopy and Machine Learning in the Diagnosis of Breast Cancer.Lasers in medical science · 2025Pooled it
- A Real-World Assessment of Stage I Lung Cancer Through Electronic Nose Technology.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2024Trial
- The early diagnostic value of lung cancer autoantibodies and tumor markers in lung cancer.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Article
- DiffMethylTools: a toolbox for the detection, annotation, and visualization of differential methylation.Life science alliance · 2026Article
- DNA Methylation ofEnvironment & health (Washington, D.C.) · 2026Article
- Liquid biopsy biomarkers for cancer detection, treatment monitoring, and clinical outcome prediction.Frontiers in cell and developmental biology · 2026Review
- Epigenetic profiling of circulating cell-free DNA for early detection and minimal residual disease assessment in lung cancer: a focus on DNA methylation.Frontiers in oncology · 2026Review
- The methylation pattern of osimertinib resistance: prospects for diagnosis and treatment of NSCLC.Frontiers in oncology · 2026Review
- Evaluation of DNA Methylation in TAC1, SOX17, and RASSF1A for the Early Diagnosis of Lung Cancer.Cancer management and research · 2026Article
- Liquid biopsy in lung cancer screening: rationale, progress, opportunities and challenges.Clinical and experimental medicine · 2025Review
- Cancer and Aging Biomarkers: Classification, Early Detection Technologies and Emerging Research Trends.Biosensors · 2025Review
- Methylation-regulated tumor suppressor geneTranslational cancer research · 2025Article
- KAZN methylation as a potential diagnostic and prognostic marker in non-small cell lung cancer.iScience · 2025Article
- Complete reference genome and pangenome improve genome-wide detection and interpretation of DNA methylation using sequencing and array data.Cell reports · 2025Article
- Prediction of lung adenocarcinoma prognosis and clinical treatment efficacy by telomere-associated gene risk model.Discover oncology · 2025Article
- Recent advances on gene-related DNA methylation in cancer diagnosis, prognosis, and treatment: a clinical perspective.Clinical epigenetics · 2025Review
- Long Non-Coding RNA HCP5 Affects Ferroptosis in Lung Adenocarcinoma through miR-17-5p/HOXA7 Axis.Current cancer drug targets · 2025Article
- Article
- Deep learning model integrating cfDNA methylation and fragment size profiles for lung cancer diagnosis.Scientific reports · 2024Article
- Identification and validation ofOncology letters · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 5 institutions in 2 countries.
Funding
Abstract
backgroundLung cancer remains the leading cause of cancer mortality worldwide. Early detection of lung cancer helps improve treatment and survival. Numerous aberrant DNA methylations have been reported in early-stage lung cancer. Here, we sought to identify novel DNA methylation biomarkers that could potentially be used for noninvasive early diagnosis of lung cancers.
methodsThis prospective-specimen collection and retrospective-blinded-evaluation trial enrolled a total of 317 participants (198 tissues and 119 plasmas) comprising healthy controls, patients with lung cancer and benign disease between January 2020 and December 2021. Tissue and plasma samples were subjected to targeted bisulfite sequencing with a lung cancer specific panel targeting 9,307 differential methylation regions (DMRs). DMRs associated with lung cancer were identified by comparing the methylation profiles of tissue samples from patients with lung cancer and benign disease. Markers were selected with minimum redundancy and maximum relevance algorithm. A prediction model for lung cancer diagnosis was built through logistic regression algorithm and validated independently in tissue samples. Furthermore, the performance of this developed model was evaluated in a set of plasma cell-free DNA (cfDNA) samples.
resultsWe identified 7 DMRs corresponding to 7 differentially methylated genes (DMGs) including HOXB4, HOXA7, HOXD8, ITGA4, ZNF808, PTGER4, and B3GNTL1 that were highly associated with lung cancer by comparing the methylation profiles of lung cancer and benign nodule tissue. Based on the 7-DMR biomarker panel, we developed a new diagnostic model in tissue samples, termed "7-DMR model", to distinguish lung cancers from benign diseases, achieving AUCs of 0.97 (95%CI: 0.93-1.00)/0.96 (0.92-1.00), sensitivities of 0.89 (0.82-0.95)/0.92 (0.86-0.98), specificities of 0.94 (0.89-0.99)/1.00 (1.00-1.00), and accuracies of 0.90 (0.84-0.96)/0.94 (0.89-0.99) in the discovery cohort (n = 96) and the independent validation cohort (n = 81), respectively. Furthermore, the 7-DMR model was applied to noninvasive discrimination of lung cancers and non-lung cancers including benign lung diseases and healthy controls in an independent validation cohort of plasma samples (n = 106), yielding an AUC of 0.94 (0.86-1.00), sensitivity of 0.81 (0.73-0.88), specificity of 0.98 (0.95-1.00), and accuracy of 0.93 (0.89-0.98).
conclusionThe 7 novel DMRs could be promising methylation biomarkers that merits further development as a noninvasive test for early detection of lung cancer.
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.