ArticleFrontiers in oncology2022
Seven DNA Methylation Biomarker Prediction Models for Monitoring the Malignant Progression From Advanced Adenoma to Colorectal Cancer.
Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 4 citations in OpenAlex.
- Diagnostic Accuracy of Blood-Based cfDNA/ctDNA Tests for Colorectal Cancer-A Systematic Review and Meta-Analysis.Cancers · 2026Review
- Discovery and validation of PARP4 methylation in distinguishing thyroid cancer from benign nodule.Journal of endocrinological investigation · 2026Article
- SFMBT2 hypermethylation promotes colorectal cancer progression and is a potential noninvasive biomarker for advanced CRC.iScience · 2026Article
- Application of plasma cell-free DNA in screening of advanced colorectal adenoma.European journal of medical research · 2025Review
- Combining the DNA methylation markers of circulating tumor cells with immune infiltrating cells to assess recurrence and prognosis and to suggest a therapeutic strategy in stage III-IV colorectal cancer.Frontiers in immunology · 2025Article
- Advances in blood DNA methylation-based assay for colorectal cancer early detection: a systematic updated review.Gastroenterology and hepatology from bed to bench · 2024Review
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Authors and funding
14 authors at 4 institutions in 1 country.
Funding
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Abstract
Advanced adenoma (AA) holds a significantly increased risk for progression to colorectal cancer (CRC), and we developed a noninvasive DNA methylation prediction model to monitor the risk of AA progression to CRC. We analyzed the differential methylation markers between 53 normal mucosa and 138 CRC tissues, as well as those in cfDNA (cell-free DNA) between 59 AA and 68 early-stage CRC patients. We screened the overlapping markers between tissue DNA and cfDNA for model variables and optimized the selected variables. Then, we established a cfDNA methylation prediction model (SDMBP model) containing seven methylation markers that can effectively discriminate early-stage CRC and AA in the training and validation cohorts, and the AUC (area under the curve) reached 0.979 and 0.918, respectively. Our model also reached high precision (AUC=0.938) in detecting advanced CRC (stage III/IV) and presented better performance than serum CEA and CA199 in screening CRC. The cd-score of the SDMBP model could also robustly predict the TNM stage of CRC. Overall, our SDMBP model can monitor the malignant progression from AA to CRC, and may provide a noninvasive monitoring method for high-risk populations with AA.
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Registered trials
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