ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2020
Machine Learning-Assisted Evaluation of Circulating DNA Quantitative Analysis for Cancer Screening.
Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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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.
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Who cites it
22 citing papers in PubMed.
- Monitoring levels of circulating cell-free DNA in patients with metastatic colorectal cancer as a potential biomarker of responses to regorafenib treatment.Molecular oncology · 2021Trial
- Circulating DNA reveals nucleosome occupancy patterns that are associated with nucleosome-DNA affinity and are affected in cancer.Genome medicine · 2026Article
- Integrated Transcriptomics and Metabolomics with Machine Learning Identify Flavonoids as Key Effectors in Wheat Root Thermotolerance.Plants (Basel, Switzerland) · 2026Article
- From multi-omics to deep learning: advances in cfDNA-based liquid biopsy for multi-cancer screening.Biomarker research · 2025Review
- Detection of Cancers Three Years prior to Diagnosis Using Plasma Cell-Free DNA.Cancer discovery · 2025Article
- Post-surgery sequelae unrelated to disease progression and chemotherapy revealed in follow-up of patients with stage III colon cancer.EBioMedicine · 2024Article
- Systematically Evaluating Cell-Free DNA Fragmentation Patterns for Cancer Diagnosis and Enhanced Cancer Detection via Integrating Multiple Fragmentation Patterns.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Baseline Cell-Free DNA Can Predict Malignancy of Nodules Observed in the ITALUNG Screening Trial.Cancers · 2024Article
- Association of the immediate perioperative dynamics of circulating DNA levels and neutrophil extracellular traps formation in cancer patients.Precision clinical medicine · 2024Article
- Association of vascular netosis with COVID-19 severity in asymptomatic and symptomatic patients.iScience · 2024Article
- The landscape of cell-free mitochondrial DNA in liquid biopsy for cancer detection.Genome biology · 2023Article
- Genome-wide analysis of aberrant position and sequence of plasma DNA fragment ends in patients with cancer.Science translational medicine · 2023Article
- Circulating DNA fragmentomics and cancer screening.Cell genomics · 2023Review
- Comparison of the structures and topologies of plasma extracted circulating nuclear and mitochondrial cell-free DNA.Frontiers in genetics · 2023Article
- Application of artificial intelligence in diagnosis and treatment of colorectal cancer: A novel Prospect.Frontiers in medicine · 2023Review
- Persistence of neutrophil extracellular traps and anticardiolipin auto-antibodies in post-acute phase COVID-19 patients.Journal of medical virology · 2023Article
- Neutrophil extracellular traps have auto-catabolic activity and produce mononucleosome-associated circulating DNA.Genome medicine · 2022Article
- Association of neutrophil extracellular traps with the production of circulating DNA in patients with colorectal cancer.iScience · 2022Article
- Computational healthcare: Present and future perspectives (Review).Experimental and therapeutic medicine · 2021Review
- Association of COVID-19 Lockdown With the Tumor Burden in Patients With Newly Diagnosed Metastatic Colorectal Cancer.JAMA network open · 2021Article
Corrections and comments
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Authors and funding
23 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
While the utility of circulating cell-free DNA (cfDNA) in cancer screening and early detection have recently been investigated by testing genetic and epigenetic alterations, here, an original approach by examining cfDNA quantitative and structural features is developed. First, the potential of cfDNA quantitative and structural parameters is independently demonstrated in cell culture, murine, and human plasma models. Subsequently, these variables are evaluated in a large retrospective cohort of 289 healthy individuals and 983 patients with various cancer types; after age resampling, this evaluation is done independently and the variables are combined using a machine learning approach. Implementation of a decision tree prediction model for the detection and classification of healthy and cancer patients shows unprecedented performance for 0, I, and II colorectal cancer stages (specificity, 0.89 and sensitivity, 0.72). Consequently, the methodological proof of concept of using both quantitative and structural biomarkers, and classification with a machine learning method are highlighted, as an efficient strategy for cancer screening. It is foreseen that the classification rate may even be improved by the addition of such biomarkers to fragmentomics, methylation, or the detection of genetic alterations. The optimization of such a multianalyte strategy with this machine learning method is therefore warranted.
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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.