장기간 보관된 낮은 품질의 액체 생검에서도 비소세포폐암 핫스팟 변이의 고감도 검출이 가능한 검사법 개발에 대한 연구

Abstract

Background: Circulating cell-free DNA (cfDNA) has enormous potential in clinical applications, particularly in cancer patients. The prognostic and predictive values of cfDNA in non-small cell lung cancer (NSCLC) have been previously reported, with EGFR, KRAS, and BRAF mutations in tumor-derived cfDNAs acting as biomarkers for the early stages of tumor progression and recurrence. However, effective applications of cfDNA require a reliable approach to detect low mutant fractions of <1%, considering the limitations of extremely low tumor-derived DNA proportions. Herein, we developed an ultra-high sensitivity lung version 1 (ULV1) panel targeting EGFR, KRAS, and BRAF hotspot mutations and evaluated the detection ability of hotspot mutations using low-quality plasma samples from NSCLC patients. Methods: The ULV1 panel comprised two multiplexing pools capable of detecting 14 hotspots. We utilized positive samples corresponding to each mutation to evaluate the optimization and performance of the ULV1 panel and samples from 104 NSCLC patients with stages I-IV to verify the potential of the ULV1 panel as a high-sensitivity diagnostic tool. The EGFR mutation in tissue using targeted NGS or diverse diagnostic platforms alone was tested at the Asan Medical Center, Seoul, South Korea. We compared the mutational concordance in tumor tissue samples with matched plasma samples and evaluated the performance between ULV1 and CT-ULTRA to detect EGFR mutation status in plasma cfDNA. Results: The performance of the ULV1 panel using positive samples demonstrated overall sensitivity (80-100%) and specificity (87.9-100%) with a limit of detection of 0.025-0.1%. Focusing on EGFR hotspot mutations included in the ULV1 panel in stage IV, we identified 23 hotspot mutations. Of these, 18 (78.3%) and 17 (73.9%) mutations demonstrated the same mutation pattern as the matched tumor tissue DNA in cfDNA samples using ULV1 and CT-ULTRA, respectively. Interestingly, additional mutations were identified in only three of 80 (3.75%) cfDNAs using ULV1 panel analysis. Considering the limited volume (1 mL) and long-term storage (12-50 months) before cfDNA extraction, the impressive detectability of ULV1 panel is expected to increase with the cfDNA input amount. Conclusion: The results of our study demonstrate that the ULV1 panel has clinical potential as a reliable detection tool for identifying genetic mutations in low-quality plasma samples from NSCLC patients. This not only enables the monitoring of treatment responsiveness but also validates NGS data.