In metastatic cancer surveillance, monitoring the actual concentrations of circulating tumor DNA (ctDNA) may be critical. Researchers have demonstrated that absolute ctDNA concentration thresholds can help rule out or predict impending cancer progression. A new study published in The Journal of Molecular Diagnostics by Elsevier introduces a dual threshold model that could enhance cancer surveillance, patient stratification, and risk-informed personalized treatment by providing more accurate and timely assessment of disease progression.
Lead investigator Geert A. Martens, MD, PhD, from the Department of Laboratory Medicine at AZ Delta General Hospital in Roeselare and the Department of Biomolecular Medicine at Ghent University (Belgium), explains that monitoring cancer progression in metastatic breast cancer currently relies primarily on medical imaging, supplemented by poorly specific biomarkers like CA15-3. He adds, “Monitoring tumor-specific mutations in circulating DNA is far superior to traditional methods, but clinicians lack guidelines for interpreting ctDNA concentrations. We aimed to address this gap.”
The researchers conducted a longitudinal study involving two years of weekly measurements of ctDNA levels in patients with advanced breast cancer. They investigated whether the ctDNA level could predict or rule out impending disease progression. Various techniques were used to measure ctDNA, including targeted deep sequencing and digital PCR, which showed perfect correlation. The choice of technique would be influenced by factors such as the pathology laboratory’s total cost of ownership and logistical aspects like turnaround times.
Dr. Martens emphasizes that their findings confirm the superiority of ctDNA levels over conventional biomarkers like CA15-3. They found that frequent ctDNA measurement can identify tumor progression three months earlier than current methods. Most importantly, they developed a simple dual threshold classifier: if ctDNA concentrations are below 10 mutant copies/mL (0.25% Variant Allele Fraction), it reassures patients of low progression risk; levels above 100 copies/mL (2.5% VAF) indicate at least a 90% chance of progression. They call this model the ‘0/10/100 copy model.’
Although ctDNA concentrations may vary with tumor type and stage, they are confident that their statistical approach can be generalized. The investigators recommend that advanced cancer centers replace traditional protein biomarkers such as CA15-3 with patient-personalized, mutation-specific digital PCR tests for frequent monitoring in advanced cancer surveillance and early detection of minimal residual disease.
Such ctDNA monitoring holds significant value: it is more sensitive and specific than conventional methods; it optimizes the use of radiology resources, reduces hospital visits, lessens anxiety, and results in a positive health-economic impact. Doctors can also select appropriate times for retesting tumors or performing liquid biopsies using Comprehensive Genomic Profiling by examining actual ctDNA concentrations with relatively inexpensive PCR tests.
This research has also confirmed the same thresholds for surveillance of metastatic non-small-cell lung cancer patients. Dr. Martens concludes, “Our concept goes beyond cohort analyses and provides a statistical framework that allows our work to be critically reproduced and applied retrospectively to any data set with registered progression outcomes. We hope this inspires other scientists to apply our model.” He adds that the actual concentrations of ctDNA hold strong diagnostic potential for cancer progression, suggesting preparation for ctDNA concentration-guided scheduling of care in advanced cancers.
