ArticleCancer management and research2026
The Application Value of Liquid Biopsy in Cancer MRD Detection and the Preliminary Clinical Significance of the TFx Value.
Article in Cancer management and research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Plasma cell-free DNA (cfDNA)-based chromosomal instability (CIN) profiling is a non-invasive approach for tumor burden monitoring and treatment response assessment. This pilot study included 50 cancer patients (breast, oral, gastric, lung, and other cancers) to evaluate the clinical utility of the Ultrasensitive Chromosome Aberration Detection (UCAD) method, with exploratory analysis of minimal residual disease (MRD) detection in patients with no evidence of disease on imaging. Methods: Fifty patients with histologically confirmed solid tumors who underwent UCAD testing between January 2023 and March 2024 were enrolled. UCAD uses low-depth (1×) whole-genome sequencing of plasma cfDNA to detect genome-wide copy number variations (CNVs). Tumor-derived CNVs are distinguished from germline variation through normalization against healthy donor controls, with statistically significant deviations identified as somatic events reflecting tumor-associated CIN. A tumor fraction index (TFx) is derived as a quantitative metric of the aggregate CNV burden. Patients were stratified by imaging status into no-evidence-of-disease (NED, n=41) and residual lesions (RL, n=9) subgroups. Outcomes included TFx correlation with clinical status and exploratory MRD-recurrence associations within the NED subgroup. Results: TFx values ranged from 0.021% to 10.12% (median 0.065%) across the cohort. TFx positively correlated with tumor stage ( Conclusion: The findings indicate that the UCAD method showed preliminary feasibility across the evaluated cancer types in this pilot cohort, and the TFx value serves as a quantitative indicator of tumor burden and treatment efficacy, warranting further prospective validation in larger cohorts.
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