ArticleJournal of hematology & oncology2022
Somatic copy number alteration and fragmentation analysis in circulating tumor DNA for cancer screening and treatment monitoring in colorectal cancer patients.
Article in Journal of hematology & oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.
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Who cites it
25 citing papers in PubMed, 1 synthesis or guideline pooled it, 41 citations in OpenAlex.
- Research trends and hotspots of circulating tumor DNA in colorectal cancer: a bibliometric study.Frontiers in oncology · 2025Pooled it
- A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing.Science advances · 2026Article
- Extracellular vesicle and particle biomarkers in cancer: a machine learning blueprint for liquid biopsy.Journal of nanobiotechnology · 2026Review
- Tumor Genomics and Liquid Biopsy in Cancer Biology: From Static Snapshots to Dynamic Measurements.Biomolecules · 2026Article
- Systematic review and meta-analysis of studies assessing circulating tumor DNA kinetics in metastatic colorectal cancer.ESMO gastrointestinal oncology · 2026Review
- BayesCNV: A Bayesian Hierarchical Model for Sensitive and Specific Copy Number Estimation in Cell Free DNA.Diagnostics (Basel, Switzerland) · 2026Article
- From multi-omics to deep learning: advances in cfDNA-based liquid biopsy for multi-cancer screening.Biomarker research · 2025Review
- Knowledge-informed multimodal cfDNA analysis improves sensitivity and generalization in cancer detection.bioRxiv : the preprint server for biology · 2025Article
- Discovering periodontitis biomarkers and therapeutic targets through bioinformatics and ensemble learning analysis.Scientific reports · 2025Article
- Article
- Circulating tumor DNA in colorectal cancer: biology, methods and applications.Discover oncology · 2025Review
- Harnessing ferroptosis for precision oncology: challenges and prospects.BMC biology · 2025Review
- Diagnostics of lung cancer by fragmentated blood circulating cell-free DNA based on machine learning methods.Frontiers in medicine · 2025Article
- Developing survival prediction models in colorectal cancer using epigenome-wide DNA methylation data from whole blood.NPJ precision oncology · 2024Article
- Ultra-sensitive molecular residual disease detection through whole genome sequencing with single-read error correction.EMBO molecular medicine · 2024Article
- Novel liquid biopsy CNV biomarkers in malignant melanoma.Scientific reports · 2024Article
- Translation of Epigenetics in Cell-Free DNA Liquid Biopsy Technology and Precision Oncology.Current issues in molecular biology · 2024Review
- Analysis of cell free DNA to predict outcome to bevacizumab therapy in colorectal cancer patients.NPJ genomic medicine · 2024Article
- Use of Enzymatically Converted Cell-Free DNA (cfDNA) Data for Copy Number Variation-Linked Fragmentation Analysis Allows for Early Colorectal Cancer Detection.International journal of molecular sciences · 2024Article
- Circulating Nucleic Acids in Colorectal Cancer: Diagnostic and Prognostic Value.Disease markers · 2024Review
Corrections and comments
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Authors and funding
13 authors at 9 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAnalysis of circulating free DNA (cfDNA) is a promising tool for personalized management of colorectal cancer (CRC) patients. Untargeted cfDNA analysis using whole-genome sequencing (WGS) does not need a priori knowledge of the patient´s mutation profile.
methodsHere we established LIquid biopsy Fragmentation, Epigenetic signature and Copy Number Alteration analysis (LIFE-CNA) using WGS with ~ 6× coverage for detection of circulating tumor DNA (ctDNA) in CRC patients as a marker for CRC detection and monitoring.
resultsWe describe the analytical validity and a clinical proof-of-concept of LIFE-CNA using a total of 259 plasma samples collected from 50 patients with stage I-IV CRC and 61 healthy controls. To reliably distinguish CRC patients from healthy controls, we determined cutoffs for the detection of ctDNA based on global and regional cfDNA fragmentation patterns, transcriptionally active chromatin sites, and somatic copy number alterations. We further combined global and regional fragmentation pattern into a machine learning (ML) classifier to accurately predict ctDNA for cancer detection. By following individual patients throughout their course of disease, we show that LIFE-CNA enables the reliable prediction of response or resistance to treatment up to 3.5 months before commonly used CEA.
conclusionIn summary, we developed and validated a sensitive and cost-effective method for untargeted ctDNA detection at diagnosis as well as for treatment monitoring of all CRC patients based on genetic as well as non-genetic tumor-specific cfDNA features. Thus, once sensitivity and specificity have been externally validated, LIFE-CNA has the potential to be implemented into clinical practice. To the best of our knowledge, this is the first study to consider multiple genetic and non-genetic cfDNA features in combination with ML classifiers and to evaluate their potential in both cancer detection and treatment monitoring. Trial registration DRKS00012890.
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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.