Monitoring of the presence of EGFR-mutated DNA during EGFR-targeted therapy may assist in the prediction of treatment outcome

Autor: F.V. Moiseenko, N.M. Volkov, A.S. Zhabina, M.L. Stepanova, N.A. Rysev, V.V. Klimenko, A.V. Myslik, E.V. Artemieva, V.V. Egorenkov, N.H. Abduloeva, A.O. Ivantsov, E.S. Kuligina, E.N. Imyanitov, V.M. Moiseyenko
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Cancer Treatment and Research Communications, Vol 31, Iss , Pp 100524- (2022)
Druh dokumentu: article
ISSN: 2468-2942
DOI: 10.1016/j.ctarc.2022.100524
Popis: The aim of our trial was to evaluate the prognostic significance of qualitative ctDNA analysis on different stages of EGFR mutated non-small cell lung cancer (NSCLC) treatment.We included 99 patients amendable for the first line treatment with either gefitinib/erlotinib (n = 87), afatinib (n = 10) or osimertinib (n = 2). Sequential qualitative analysis of ctDNA with cobas® EGFR Mutation Test v2 were performed before first dose, after 2 and 4 months of treatment, and on progression.Our analysis showed clinically significant heterogeneity of EGFR-mutated NSCLC treated with 1st line tyrosine kinase inhibitors (TKIs) in terms of progression-free and overall survival. When treated with conventional approach, i.e. monotherapy with TKIs, the patients falls into three subgroups based on ctDNA analysis before and after 2 months of treatment. Patients without detectable ctDNA at baseline (N = 32) possess the best prognosis on duration of treatment (PFS: 24.07 [16.8–31.3] and OS: 56.2 [21.8–90.7] months). Those who achieve clearance after two months of TKI (N = 42) have indistinguishably good PFS (19.0 [13.7 – 24.2]). Individuals who retain ctDNA after 2 months (N = 25) have the worst prognosis (PFS: 10.3 [7.0 – 13.5], p = 0.000). 9/25 patients did not develop ctDNA clearance at 4 months with no statistical difference in PFS from those without clearance at 2 months.Prognostic heterogeneity of EGFR-mutated NSCLC should be taken into consideration in planning further clinical trials and optimizing the outcome of patients.
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