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Correlation of circulating tumor DNA EGFR mutation levels with clinical outcomes in patients with advanced lung adenocarcinoma

BACKGROUND: Circulating tumor DNA (ctDNA) is a promising biomarker for non-invasive epidermal growth factor receptor mutations (EGFRm) detection in lung cancer patients, but existing methods have limitations in sensitivity and availability. In this study, we used the ΔCt value (mutant cycle threshol...

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Detalles Bibliográficos
Autores principales: Liu, Xiang-Liang, Bai, Ri-Lan, Chen, Xiao, Zhao, Yu-Guang, Wang, Xu, Ma, Ke-Wei, Tian, Hui-Min, Han, Fu-Jun, Liu, Zi-Ling, Yang, Lei, Li, Wei, Gai, Fei, Cui, Jiu-Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8654465/
https://www.ncbi.nlm.nih.gov/pubmed/34669636
http://dx.doi.org/10.1097/CM9.0000000000001760
Descripción
Sumario:BACKGROUND: Circulating tumor DNA (ctDNA) is a promising biomarker for non-invasive epidermal growth factor receptor mutations (EGFRm) detection in lung cancer patients, but existing methods have limitations in sensitivity and availability. In this study, we used the ΔCt value (mutant cycle threshold [Ct] value–internal control Ct value) generated during the polymerase chain reaction (PCR) assay to convert super-amplification-refractory mutation system (superARMS) from a qualitative method to a semi-quantitative method named reformed-superARMS (R-superARMS), and evaluated its performance in detecting EGFRm in plasma ctDNA in patients with advanced lung adenocarcinoma. METHODS: A total of 41 pairs of tissues and plasma samples were obtained from lung adenocarcinoma patients who had known EGFRm in tumor tissue and were previously untreated. EGFRm in ctDNA was identified by using superARMS. Through making use of ΔCt value generated during the detection process of superARMS, we indirectly transform this qualitative detection method into a semi-quantitative PCR detection method, named R-superARMS. Both qualitative and quantitative analyses of the data were performed. Kaplan–Meier analysis was performed to estimate the progression-free survival (PFS) and overall survival (OS). Fisher exact test was used for categorical variables. RESULTS: The concordance rate of EGFRm in tumor tissues and matched plasma samples was 68.3% (28/41). At baseline, EGFRm-positive patients were divided into two groups according to the cut-off ΔCt value of EGFRm set at 8.11. A significant difference in the median OS (mOS) between the two groups was observed (EGFRm ΔCt ≤8.11 vs. >8.11: not reached vs. 11.0 months; log-rank P = 0.024). Patients were divided into mutation clearance (MC) group and mutation incomplete clearance (MIC) group according to whether the ΔCt value of EGFRm test turned negative after 1 month of treatment. We found that there was also a significant difference in mOS (not reached vs. 10.4 months; log-rank P = 0.021) between MC group and MIC group. Although there was no significant difference in PFS between the two groups, the two curves were separated and the PFS of MC group tended to be higher than the MIC group (not reached vs. 27.5 months; log-rank P = 0.088). Furthermore, EGFRm-positive patients were divided into two groups according to the cut-off of the changes in ΔCt value of EGFRm after 1 month of treatment, which was set at 4.89. A significant difference in the mOS between the two groups was observed (change value of ΔCt >4.89 vs. ≤4.89: not reached vs. 11.0 months; log-rank P = 0.014). CONCLUSIONS: Detecting EGFRm in ctDNA using R-superARMS can identify patients who are more likely sensitive to targeted therapy, reflect the molecular load of patients, and predict the therapeutic efficacy and clinical outcomes of patients.