Trial reportNature communications2021
Sensitive detection of tumor mutations from blood and its application to immunotherapy prognosis.
Trial report in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 28 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
28 citing papers in PubMed, 41 citations in OpenAlex.
- Tumor-naïve ctDNA detection with deep learning-enhanced error suppression for sensitive mutation calling.Genome medicine · 2026Article
- Cancer-Like Fragmentomic Characteristics of Somatic Variants in Cell-Free DNA.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Reducing demographic bias in biomedical machine learning for cancer detection using cfDNA methylation.Genome biology · 2026Article
- Article
- Blood-based tumor biomarkers: integrating biological layers and analytical strategies for precision cancer detection.Frontiers in medicine · 2026Review
- Comprehensive benchmarking of methods for mutation calling in circulating tumor DNA.Nature communications · 2025Article
- A multiplexed assay by self-assembled dual-target responsive DNA hydrogels for efficacy evaluation of immunotherapy.Nature communications · 2025Article
- Dynamic Monitoring of Recurrent Ovarian Cancer Using Serial ctDNA: A Real-World Case Series.Current oncology (Toronto, Ont.) · 2025Article
- Circulating Tumor DNA detection in cancer: a comprehensive overview of current detection methods and prospects.The oncologist · 2025Review
- Artificial intelligence and machine learning in cell-free-DNA-based diagnostics.Genome research · 2025Review
- Identification of Somatic Variants in Cancer Genomes from Tissue and Liquid Biopsy Samples.Methods in molecular biology (Clifton, N.J.) · 2025Review
- Coupling enzymatic digestion with nanopore sensing for low-abundance EGFR-L858R mutation detection.Frontiers in bioengineering and biotechnology · 2025Article
- Cell-free nucleic acid fragmentomics: A non-invasive window into cellular epigenomes.Translational oncology · 2024Review
- Evaluating Circulating Biomarkers for Diagnosis, Prognosis, and Tumor Monitoring in Pediatric Sarcomas: Recent Advances and Future Directions.Biomolecules · 2024Review
- Genomic profiling of cell-free DNA from dogs with benign and malignant tumors.BMC research notes · 2024Article
- Innovations in Early Lung Cancer Detection: Tracing the Evolution and Advancements in Screening.Journal of clinical medicine · 2024Review
- Noninvasive Lung Cancer Subtype Classification Using Tumor-Derived Signatures and cfDNA Methylome.Cancer research communications · 2024Article
- Plasma cell-free DNA methylation analysis for ovarian cancer detection: Analysis of samples from a case-control study and an ovarian cancer screening trial.International journal of cancer · 2024Article
- Quantitative Detection of Biological Nanovesicles in Drops of Saliva Using Microcantilevers.ACS applied materials & interfaces · 2024Article
- Genomic hypomethylation in cell-free DNA predicts responses to checkpoint blockade in lung and breast cancer.Scientific reports · 2023Article
Corrections and comments
- Erratum issued
Authors and funding
14 authors at 4 institutions in 1 country.
Funding
Abstract
Cell-free DNA (cfDNA) is attractive for many applications, including detecting cancer, identifying the tissue of origin, and monitoring. A fundamental task underlying these applications is SNV calling from cfDNA, which is hindered by the very low tumor content. Thus sensitive and accurate detection of low-frequency mutations (<5%) remains challenging for existing SNV callers. Here we present cfSNV, a method incorporating multi-layer error suppression and hierarchical mutation calling, to address this challenge. Furthermore, by leveraging cfDNA's comprehensive coverage of tumor clonal landscape, cfSNV can profile mutations in subclones. In both simulated and real patient data, cfSNV outperforms existing tools in sensitivity while maintaining high precision. cfSNV enhances the clinical utilities of cfDNA by improving mutation detection performance in medium-depth sequencing data, therefore making Whole-Exome Sequencing a viable option. As an example, we demonstrate that the tumor mutation profile from cfDNA WES data can provide an effective biomarker to predict immunotherapy outcomes.
Indexed as
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What OpenQuestion holds
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.