Absence of copy number gain of EGFR: A possible predictive marker of long‐term response to afatinib. Issue 3 (16th December 2022) - Nakamura, Tomomi; Sato, Akemi; Nakashima, Chiho; Abe, Tomonori; Iwanaga, Kentaro; Umeguchi, Hitomi; Kawaguchi, Atsushi; Sueoka‐Aragane, Naoko
Abstract: Treatment efficacy of epidermal growth factor receptor tyrosine kinase inhibitor (EGFR‐TKI) is diverse even in non‐small cell lung cancer (NSCLC) patients with EGFR activating mutations. Extraordinary long‐term responses sustained over 3 years among NSCLC patients treated with afatinib, an EGFR‐TKI, have been reported, but how to predict such long survivors has not been clarified. A multi‐institutional prospective observational study, based on comprehensive genomic examination performed with next‐generation sequencing of circulating tumor DNA (ctDNA), was conducted to identify potential predictive markers of long‐term response to afatinib. Twenty‐nine patients with advanced stage NSCLC and EGFR driver mutations detected by standard techniques were enrolled in the study. ctDNA from plasma collected before afatinib treatment was analyzed by Guardant360. ctDNA was detected in 25 of the 29 samples. Median progression‐free survival was shorter in patients whose tumors had EGFR copy number gain (7.0 vs 23.0 months, p = 0.022). The impact of EGFR copy number on cell proliferation and the antitumor effect of afatinib were evaluated using genome‐editing lung cancer cell lines. HCC827 with EGFR amplification was relatively resistant to afatinib at concentrations below 0.5 nM, but genome‐edited derivatives of HCC827 with decreased EGFR copy number demonstrated growth inhibition with 0.1 nM afatinib. The absence of EGFR copy number gain detected in ctDNA may be a predictive marker of long‐term response to afatinib. Comprehensive genomic analysis could lead to a more accurate prediction of EGFR‐TKI efficacy. Abstract : The absence of EGFR copy number gain assessed in ctDNA is a possible predictive marker of long‐term response to afatinib, so comprehensive genomic analysis with ctDNA might be useful for precise prediction of treatment efficacy.