Revolutionizing Non-Small Cell Lung Cancer Diagnosis: Ultra-High-Sensitive ctDNA Analysis for Detecting Hotspot Mutations with Long-term Stored Plasma.

Cancer research and treatment(2023)

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摘要
PURPOSE:Circulating cell-free DNA (cfDNA) has great potential in clinical oncology. The prognostic and predictive values of cfDNA in non-small cell lung cancer (NSCLC) have been reported, with epidermal growth factor receptor (EGFR), KRAS, and BRAF mutations in tumor-derived cfDNAs acting as biomarkers during the early stages of tumor progression and recurrence. However, extremely low tumor-derived DNA rates hinder cfDNA application. We developed an ultra-high-sensitivity lung version 1 (ULV1) panel targeting BRAF, KRAS, and EGFR hotspot mutations using small amounts of cfDNA, allowing for semi-quantitative analysis with excellent limit-of-detection (0.05%). MATERIALS AND METHODS:Mutation analysis was performed on cfDNAs extracted from the plasma of 104 patients with NSCLC by using the ULV1 panel and targeted next-generation sequencing (CT-ULTRA), followed by comparison analysis of mutation patterns previously screened using matched tumor tissue DNA. RESULTS:The ULV1 panel demonstrated robust selective amplification of mutant alleles, enabling the detection of mutations with a high degree of analytical sensitivity (limit-of-detection, 0.025%-0.1%) and specificity (87.9%-100%). Applying ULV1 to NSCLC cfDNA revealed 51.1% (23/45) samples with EGFR mutations, increasing with tumor stage: 8.33% (stage I) to 78.26% (stage IV). Semi-quantitative analysis proved effective for low-mutation-fraction clinical samples. Comparative analysis with PANAMutyper EGFR exhibited substantial concordance (κ=0.84). CONCLUSION:Good detection sensitivity (~80%) was observed despite the limited volume (1 mL) and long-term storage (12-50 months) of plasma used and is expected to increase with high cfDNA inputs. Thus, the ULV1 panel is a fast and cost-effective method for early diagnosis, treatment selection, and clinical follow-up of patients with NSCLC.
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