Detection and Quantification of ctDNA for Longitudinal Monitoring of Treatment in Non-Small Cell Lung Cancer Patients...

Background: Observation of anticancer therapy effect by monitoring of minimal residual disease (MRD) is becoming an important tool in management of non-small cell lung cancer (NSCLC). The approach is based on periodic detection and quantification of tumor-specific somatic DNA mutation in circulating tumor DNA (ctDNA) extracted from patient plasma. For such repetitive testing, complex liquid-biopsy techniques relying on ultra-deep NGS sequencing are impractical. There are other, cost-effective, methods for ctDNA analysis, typically based on quantitative PCR or digital PCR, which are applicable for detecting specific individual mutations in hotspots. While such methods are routinely used in NSCLC therapy prediction, however, extension to cover broader spectrum of mutations (e.g., in tumor suppressor genes) is required for universal longitudinal MRD monitoring. Methods: For a set of tissue samples from 81 NSCLC patients we have applied a denaturing capillary electrophoresis (DCE) for initial detection of somatic mutations within 8 predesigned PCR amplicons covering oncogenes and tumor suppressor genes. Mutation-negative samples were then subjected to a large panel NGS sequencing. For each patient mutation found in tissue was then traced over time in ctDNA by DCE. Results: In total we have detected a somatic mutation in tissue of 63 patients. For those we have then prospectively analyzed ctDNA from collected plasma samples over a period of up to 2 years. The dynamics of ctDNA during the initial chemotherapy therapy cycles as well as in the long-term follow-up matched the clinically observed response. Conclusion: Detection and quantification of tumor-specific mutations in ctDNA represents a viable complement to MRD monitoring during therapy of NSCLC patients. The presented approach relying on initial tissue mutation detection by DCE combined with NGS and a subsequent ctDNA mutation testing by DCE only represents a cost-effective approach for its routine implementation.