ArticleFrontiers in oncology2023
Multimodal analysis of genome-wide methylation, copy number aberrations, and end motif signatures enhances detection of early-stage breast cancer.
Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed, 32 citations in OpenAlex.
- Multifeature sequencing-based liquid biopsy for cancer diagnosis and monitoring.Genome medicine · 2026Review
- Review
- Artificial intelligence-powered liquid biopsy in cancer: a paradigm shift in cancer detection and personalized care.Cancer cell international · 2026Review
- 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
- Article
- Harnessing viral footprints in circulating free DNA (cfDNA) for early cancer detection: A focus on liquid-biopsy-based screening.International journal of cancer · 2026Review
- Multidimensional cell-free DNA fragmentomics enables early detection of breast cancer.Breast cancer research : BCR · 2025Article
- Multimodal Integration in Health Care: Development With Applications in Disease Management.Journal of medical Internet research · 2025Review
- Multimodal analysis of cell-free DNA enhances differentiation of early-stage breast cancer from benign lesions and healthy individuals.BMC biology · 2025Article
- Liquid Biopsy-Based DNA Methylation Biomarkers for Precision Medicine in Breast Cancer.Expert reviews in molecular medicine · 2025Review
- Liquid biopsies for early detection and monitoring of cancer: advances, challenges, and future directions.Annals of medicine and surgery (2012) · 2025Review
- DNA methylation in breast cancer: early detection and biomarker discovery through current and emerging approaches.Journal of translational medicine · 2025Review
- Artificial intelligence utilization in cancer screening program across ASEAN: a scoping review.BMC cancer · 2025Article
- Prospective validation study: a non-invasive circulating tumor DNA-based assay for simultaneous early detection of multiple cancers in asymptomatic adults.BMC medicine · 2025Observational
- Cell-free epigenomes enhanced fragmentomics-based model for early detection of lung cancer.Clinical and translational medicine · 2025Article
- Artificial intelligence and machine learning in cell-free-DNA-based diagnostics.Genome research · 2025Review
- A consultation and work-up diagnosis protocol for a multicancer early detection test: a case series study.Future science OA · 2024Article
- Tissue of origin detection for cancer tumor using low-depth cfDNA samples through combination of tumor-specific methylation atlas and genome-wide methylation density in graph convolutional neural networks.Journal of translational medicine · 2024Article
- A comprehensive analysis of minimally differentially methylated regions common to pediatric and adult solid tumors.NPJ precision oncology · 2024Article
- Review
Corrections and comments
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Authors and funding
22 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Breast cancer causes the most cancer-related death in women and is the costliest cancer in the US regarding medical service and prescription drug expenses. Breast cancer screening is recommended by health authorities in the US, but current screening efforts are often compromised by high false positive rates. Liquid biopsy based on circulating tumor DNA (ctDNA) has emerged as a potential approach to screen for cancer. However, the detection of breast cancer, particularly in early stages, is challenging due to the low amount of ctDNA and heterogeneity of molecular subtypes. Methods: Here, we employed a multimodal approach, namely Screen for the Presence of Tumor by DNA Methylation and Size (SPOT-MAS), to simultaneously analyze multiple signatures of cell free DNA (cfDNA) in plasma samples of 239 nonmetastatic breast cancer patients and 278 healthy subjects. Results: We identified distinct profiles of genome-wide methylation changes (GWM), copy number alterations (CNA), and 4-nucleotide oligomer (4-mer) end motifs (EM) in cfDNA of breast cancer patients. We further used all three signatures to construct a multi-featured machine learning model and showed that the combination model outperformed base models built from individual features, achieving an AUC of 0.91 (95% CI: 0.87-0.95), a sensitivity of 65% at 96% specificity. Discussion: Our findings showed that a multimodal liquid biopsy assay based on analysis of cfDNA methylation, CNA and EM could enhance the accuracy for the detection of early- stage breast cancer.
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