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Zeitschrift für molekulare Biomarker und Diagnose

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Dynamic Changes of EGFR Activating Mutations as an Early Predictor of Progression in Non–Small Cell Lung Cancer Patients Treated with EGFR Tyrosine Kinase Inhibitors

Abstract

Izidor Kern, Tanja Cufer, Mitja Rot, Katja Mohorcic, Igor Pozek, John F Palma, Sidney A Scudder, Partha M Das and Aleksander Sadikov

Serial monitoring of circulating tumor DNA may predict resistance to first-line epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors before CT-confirmed progression. Our objective was to evaluate dynamic changes in plasma EGFR-activating mutations as an early predictor of disease progression before clinical or radiological evidence. For this observational study, 35 patients with advanced, EGFR-positive, nonsquamous, non-small cell lung cancer were enrolled. All patients were initiating or receiving EGFR tyrosine kinase inhibitors and had received at least one follow-up CT scan. Peripheral blood samples were collected at each clinical visit, and CT scans were scheduled every 8 to 16 weeks after tyrosine kinase inhibitor initiation and upon clinical/symptom progression. Of the 35 patients, 16 experienced reappearance of EGFRactivating mutations and disease progression. Of these, 12 patients experienced reappearance of EGFR-activating mutations before CT-confirmed progression, 3 had CT-confirmed progression one visit (8 weeks) before detectable EGFR-activating mutations, and 1 had EGFR-activating mutations reappear concurrently with CT-confirmed progression. EGFR-activating mutations reappeared at a mean of 10 weeks (median, 16 weeks) before routinely scheduled CT-confirmed progression. Using study-specific definitions, we observed 5 false positives and no false negatives. This study demonstrates that dynamic changes in circulating tumor DNA can predict resistance to EGFR-TKIs before CT-confirmed progression. Further prospective trials of this promising approach with potential benefits to patient care should be considered. 

Haftungsausschluss: Dieser Abstract wurde mit Hilfe von Künstlicher Intelligenz übersetzt und wurde noch nicht überprüft oder verifiziert

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