ArticleNPJ breast cancer2021
Circulating cell-free DNA-based methylation patterns for breast cancer diagnosis.
Article in NPJ breast cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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Who cites it
30 citing papers in PubMed.
- Breast cancer detection via targeted enzymatic methyl sequencing of plasma cell-free DNA.Molecular genetics and genomics : MGG · 2026Article
- USP44, ZNF454, and GPRC5B ctDNA Methylation Markers in Breast Cancer: Limited Clinical Relevance for Disease Monitoring and Tumor Characteristics.Asia-Pacific journal of clinical oncology · 2026Article
- Νovel methylation biomarkers in liquid biopsy and classifying biosignatures for the clinical management of breast cancer.Breast cancer research : BCR · 2026Article
- Liquid biopsy, multi-cancer early detection, and artificial intelligence: new frontiers in cancer screening from a technological and immunological perspective.Frontiers in immunology · 2026Review
- Mapping Non-Coding Epimutations in Breast Cancer: Advancing Epigenetics Towards Precision Medicine.Sub-cellular biochemistry · 2026Review
- Plasma assay of methylated DNA markers detects recurrent metastatic breast cancer.NPJ breast cancer · 2025Article
- From multi-omics to deep learning: advances in cfDNA-based liquid biopsy for multi-cancer screening.Biomarker research · 2025Review
- DNA methylation biomarkers for the diagnosis and treatment management of breast cancer: where are we now?Epigenomics · 2025Review
- Cell-Free DNA Bisulfite Sequencing Reveals Epithelial-Mesenchymal Transition Signatures for Breast Cancer.International journal of molecular sciences · 2025Article
- Discovery and validation of cell-free DNA methylation markers for specific diagnosis, differentiation from benign tumors, and prognosis of breast cancer.Breast cancer research : BCR · 2025Article
- An Approach for Differential Diagnosis of Breast Tumors by ctDNA Methylation Sequencing.Cancer medicine · 2025Article
- DNA methylation in breast cancer: early detection and biomarker discovery through current and emerging approaches.Journal of translational medicine · 2025Review
- Validation of blood-based detection of breast cancer highlights importance for cross-population validation.Nature communications · 2025Article
- Improvement of the sensitivity of circulating tumor DNA-based liquid biopsy: current approaches and future perspectives.Exploration of targeted anti-tumor therapy · 2025Review
- DNA Methylation-Based Diagnosis and Treatment of Breast Cancer.Current cancer drug targets · 2025Review
- Article
- Development of an accurate breast cancer detection classifier based on platelet RNA.Scientific reports · 2024Article
- Differential methylation of circulating free DNA assessed through cfMeDiP as a new tool for breast cancer diagnosis and detection of BRCA1/2 mutation.Journal of translational medicine · 2024Article
- Cell-free DNA methylation profiles enable early detection of colorectal and gastric cancer.American journal of cancer research · 2024Article
- Article
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Authors and funding
20 authors.
Funding
Abstract
Mammography is used to detect breast cancer (BC), but its sensitivity is limited, especially for dense breasts. Circulating cell-free DNA (cfDNA) methylation tests is expected to compensate for the deficiency of mammography. We derived a specific panel of markers based on computational analysis of the DNA methylation profiles from The Cancer Genome Atlas (TCGA). Through training (n = 160) and validation set (n = 69), we developed a diagnostic prediction model with 26 markers, which yielded a sensitivity of 89.37% and a specificity of 100% for differentiating malignant disease from normal lesions [AUROC = 0.9816 (95% CI: 96.09-100%), and AUPRC = 0.9704 (95% CI: 94.54-99.46%)]. A simplified 4-marker model including cg23035715, cg16304215, cg20072171, and cg21501525 had a similar diagnostic power [AUROC = 0.9796 (95% CI: 95.56-100%), and AUPRC = 0.9220 (95% CI: 91.02-94.37%)]. We found that a single cfDNA methylation marker, cg23035715, has a high diagnostic power [AUROC = 0.9395 (95% CI: 89.72-99.27%), and AUPRC = 0.9111 (95% CI: 88.45-93.76%)], with a sensitivity of 84.90% and a specificity of 93.88%. In an independent testing dataset (n = 104), the obtained diagnostic prediction model discriminated BC patients from normal controls with high accuracy [AUROC = 0.9449 (95% CI: 90.07-98.91%), and AUPRC = 0.8640 (95% CI: 82.82-89.98%)]. We compared the diagnostic power of cfDNA methylation and mammography. Our model yielded a sensitivity of 94.79% (95% CI: 78.72-97.87%) and a specificity of 98.70% (95% CI: 86.36-100%) for differentiating malignant disease from normal lesions [AUROC = 0.9815 (95% CI: 96.75-99.55%), and AUPRC = 0.9800 (95% CI: 96.6-99.4%)], with better diagnostic power and had better diagnostic power than that of using mammography [AUROC = 0.9315 (95% CI: 89.95-96.34%), and AUPRC = 0.9490 (95% CI: 91.7-98.1%)]. In addition, hypermethylation profiling provided insights into lymph node metastasis stratifications (p < 0.05). In conclusion, we developed and tested a cfDNA methylation model for BC diagnosis with better performance than mammography.
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Registered trials
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