ArticlePloS one2025
Analytical validation of a hybrid-approach combining tumor-informed and tumor-agnostic bespoke ctDNA panel assay for the sensitive detection of minimal residual disease.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Circulating Tumor DNA-Guided Adjuvant and Post-Adjuvant Therapy in Resected Colorectal Cancer: From Molecular Residual Disease Detection to Proven Clinical Utility.Biomedicines · 2026Review
- Circulating tumor DNA in colorectal cancer: assay selection, clinical applications, and practical integration for gastroenterologists.Frontiers in oncology · 2026Review
- Method development for pancreatic and ovarian cancer baseline ctDNA detection and measurable residual disease monitoring.Open research Europe · 2026Article
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Minimal residual disease (MRD) is a small group of cancer cells not eliminated by anti-cancer treatment. Because of its small size, conventional imaging system may not be able to detect the MRD in routine clinical practice. Although the liquid biopsy tests can detect the circulating tumor DNA (ctDNA) when the tumor is present in the body, the fraction of ctDNA is considered lower than the 0.01% which is unreachable by current state-of-the-art liquid biopsy assay relying on fixed-gene panel approach. Here, we describe the analytical validation result of our previously developed a tumor-informed MRD test, CancerDetectTM (formerly reported as AlphaLiquid®Detect), leveraging large-scale mutation spectrum profiling strategy to enhance detection sensitivity. The CancerDetectTM is a hybrid-approach MRD test combining both personalized (bespoke) mutations and tumor-agnostic clinically actionable targets (hotspot mutations) with hybridization capture technology. The analytical validation result of CancerDetectTM showed limit of detection successfully reached down to 0.001% (10-5) with 99.9% specificity.
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