ArticleFuture oncology (London, England)2025
Cost-effective shallow genome-wide sequencing for profiling plasma cfDNA signatures to enhance lung cancer detection.
Article in Future oncology (London, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07615556 (Circulating Tumor DNA Mutations and Methylation Status as Biomarkers for Early Detection of Lung Cancer in Patients With Suspicious Lung Nodules), which is not on this map. Cited by 5 papers.
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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.
Circulating Tumor DNA Mutations and Methylation Status as Biomarkers for Early Detection of Lung Cancer in Patients With Suspicious Lung Nodules
Who cites it
5 citing papers in PubMed.
- Liquid biopsy biomarkers for accurate detection of malignant pulmonary nodules: a meta-analytic approach.Discover oncology · 2026Article
- Article
- Advances and challenges in circulating tumor DNA-based early detection of lung cancer.Translational cancer research · 2025Review
- Precision Medicine in Lung Cancer Screening: A Paradigm Shift in Early Detection-Precision Screening for Lung Cancer.Diagnostics (Basel, Switzerland) · 2025Review
- Cost-effective shallow genome-wide sequencing for profiling plasma cfDNA signatures to enhance lung cancer detection.Future oncology (London, England) · 2025Article
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Authors and funding
24 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLung cancer (LC) screening via low-dose computed tomography (LDCT) faces challenges including high false-positive rates and low patient compliance. Circulating tumor DNA (ctDNA)-based tests offer a minimally invasive alternative but are limited by high costs and low sensitivity, particularly in early-stage detection. This study introduces a cost-effective, shallow genome-wide sequencing approach for LC detection by profiling multiple cell-free DNA (cfDNA) signatures.
methodsWe developed a multimodal cfDNA assay with shallow sequencing coverage (0.5×) that integrates fragmentomic, nucleosome, end-motif, and copy number alteration analyses. A machine-learning model trained on a discovery cohort (99 LC patients, 168 healthy controls) and validated on an independent cohort (58 LC patients, 71 controls) demonstrated robust performance.
resultsThe ensemble model exhibited outstanding performance, achieving an AUC of 0.97 and a specificity of 92% in both the discovery and validation cohorts, with sensitivities of 94% and 90%, respectively. Notably, it outperformed hotspot mutation-based assays and the multi-cancer SPOT-MAS assay in sensitivity across all LC stages.
conclusionsThis assay provides a cost-effective, accurate, and minimally invasive method for LC detection, addressing the limitations of current screening methods. It represents a promising complementary tool to improve early detection and patient outcomes in LC.
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