Speaker
Description
Background: Real-time treatment response assessment in HPV-associated anal squamous cell carcinoma (ASCC) remains challenging. Traditional tumor volume measurements require serial imaging that is costly, time-intensive, and delays clinical decisions. Circulating tumor DNA (ctDNA) offers a more accessible, real-time alternative biomarker, yet its predictive value for guiding treatment adaptation remains undefined.
Methods: We developed a mechanistic mathematical model of tumor volume-ctDNA dynamics using longitudinal data from 32 HPV-associated ASCC patients receiving pembrolizumab (every 3 weeks, up to 2 years). The model was fit across three scenarios: simultaneous measurements (8 patients), volume preceding ctDNA (14 patients), and ctDNA preceding volume (2 patients).
Results: ctDNA showed strong positive correlation with tumor burden and predicted clinical response within 4 weeks of treatment initiation. ctDNA kinetics preceded volume changes in multiple patients, providing early response signal before imaging confirmation. The model robustly captured heterogeneous patient dynamics across all scenarios.
Conclusions: ctDNA functions as a leading indicator biomarker for early treatment response identification in HPV-associated ASCC. Our framework translates this biomarker into actionable clinical predictions for real-time treatment escalation, maintenance, or de-escalation—replacing burdensome imaging with accessible blood-based monitoring, particularly impactful for underserved populations. Future studies will prospectively validate this model for personalized, adaptive treatment strategies.
