ctDNA Implementation Challenges: From Early Detection to Immunotherapy Monitoring
This review presents a conceptual framework for ctDNA technologies and clinical utilities, combining bibliometric analysis with an assessment of current applications in early detection, minimal residual disease, targeted therapy, and immunotherapy response monitoring. The authors highlight how AI-enhanced NGS has improved liquid biopsy accuracy and sensitivity, while identifying standardisation, assay validation, and prospective clinical trials as key barriers to routine clinical implementation.
The original study
Circulating tumor DNA: current implementation issues and future challenges for clinical utility.
- Authors
- Hu Q, Chen L, Li K, Liu R, Sun L, Han T
- Journal
- Clinical chemistry and laboratory medicine
- Type
- Journal Article, Review, Research Support, Non-U.S. Gov't
- PMID
- 38109307
Original abstract
Over the past decades, liquid biopsy, especially circulating tumor DNA (ctDNA), has received tremendous attention as a noninvasive detection approach for clinical applications, including early diagnosis of cancer and relapse, real-time therapeutic efficacy monitoring, potential target selection and investigation of drug resistance mechanisms. In recent years, the application of next-generation sequencing technology combined with AI technology has significantly improved the accuracy and sensitivity of liquid biopsy, enhancing its potential in solid tumors. However, the increasing integration of such promising tests to improve therapy decision making by oncologists still has complexities and challenges. Here, we propose a conceptual framework of ctDNA technologies and clinical utilities based on bibliometrics and highlight current challenges and future directions, especially in clinical applications such as early detection, minimal residual disease detection, targeted therapy, and immunotherapy. We also discuss the necessities of developing a dynamic field of translational cancer research and rigorous clinical studies that may support therapeutic strategy decision making in the near future.