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Diverse Mechanisms of Resistance against Osimertinib, a Third-Generation EGFR-TKI, in Lung Adenocarcinoma Cells with an EGFR-Activating Mutation.

ABSTRACT: Osimertinib, a third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI), is used as a first-line treatment for patients with EGFR-mutant non-small cell lung cancer (NSCLC). However, the mechanisms underlying its anticancer activity, particularly the subsequent development of acquired resistance, are unclear. Herein, we investigated the mechanisms underlying the development of osimertinib resistance by treating NSCLC PC-9 cells (harboring an EGFR-activating mutation) with osimertinib, thereby developing five resistant cell lines, i.e., AZDR3, AZDR6, AZDR9, AZDR11, and AZDR14. The amplification of wild-type EGFR in AZDR3 cells and wild-type EGFR and KRAS in AZDR6 cells was also studied. AZDR3 cells showed dependence on EGFR signaling, in addition to afatinib sensitivity. AZDR9 cells harboring KRAS^G13D showed sensitivity to MEK inhibitors. Furthermore, combination treatment with EGFR and IGF1R inhibitors resulted in attenuated cell proliferation and enhanced apoptosis. In AZDR11 cells, increased Bim expression could not induce apoptosis, but Bid cleavage was found to be essential for the same. A SHP2/T507K mutation was also identified in AZDR14 cells, and, when associated with GAB1, SHP2 could activate ERK1/2, whereas a SHP2 inhibitor, TNO155, disrupted this association, thereby inhibiting GAB1 activation. Thus, diverse osimertinib resistance mechanisms were identified, providing insights for developing novel therapeutic strategies for NSCLC.

SUBMITTER: Nishihara S

PROVIDER: S-EPMC9319811 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

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Diverse Mechanisms of Resistance against Osimertinib, a Third-Generation EGFR-TKI, in Lung Adenocarcinoma Cells with an <i>EGFR</i>-Activating Mutation.

Nishihara Shigetoshi S Yamaoka Toshimitsu T Ishikawa Fumihiro F Ohmori Tohru T Ando Koichi K Kusumoto Sojiro S Kishino Yasunari Y Manabe Ryo R Hasebe Yuki Y Sagara Hironori H Yoshida Hitoshi H Tsurutani Junji J

Cells 20220714 14

Osimertinib, a third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI), is used as a first-line treatment for patients with EGFR-mutant non-small cell lung cancer (NSCLC). However, the mechanisms underlying its anticancer activity, particularly the subsequent development of acquired resistance, are unclear. Herein, we investigated the mechanisms underlying the development of osimertinib resistance by treating NSCLC PC-9 cells (harboring an EGFR-activating mutatio ...[more]

PMID: 35883645

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Project description:Background and purposeAs a third-generation EGFR tyrosine kinase inhibitor (TKI), osimertinib is approved for treating advanced non-small cell lung cancer (NSCLC) patients with EGFR-T790M mutation after progression on first- or second-generation EGFR-TKIs such as gefitinib, erlotinib and afatinib. We aim at exploring the feasibility and effectiveness of using radiomic features from chest CT scan to predict the prognosis of metastatic non-small cell lung cancer (NSCLC) patients with EGFR-T790M mutation receiving second-line osimertinib therapy.MethodsContrast-enhanced and unenhanced chest CT images before osimertinib treatment were collected from 201 and 273 metastatic NSCLC patients with EGFR-T790M mutation, respectively. Radiomic features were extracted from the volume of interest. LASSO regression was used to preliminarily evaluate the prognostic values of different radiomic features. We then performed machine learning-based analyses including random forest (RF), support vector machine (SVM), stepwise regression (SR) and LASSO regression with 5-fold cross-validation (CV) to establish the optimal radiomic model for predicting the progression-free survival (PFS) of osimertinib treatment. Finally, a combined clinical-radiomic model was developed and validated using the concordance index (C-index), decision-curve analysis (DCA) and calibration curve analysis.ResultsDisease progression occurred in 174/273 (63.7%) cases. CT morphological features had no ability in predicting patients' prognosis in osimertinib treatment. Univariate COX regression followed by LASSO regression analyses identified 23 and 6 radiomic features from the contrast-enhanced and unenhanced CT with prognostic value, respectively. The 23 contrast-enhanced radiomic features were further used to construct radiomic models using different machine learning strategies. Radiomic model built by SR exhibited superior predictive accuracy than RF, SVR or LASSO model (mean C-index of the 5-fold CV: 0.660 vs. 0.560 vs. 0.598 vs. 0.590). Adding the SR radiomic model to the clinical model could remarkably strengthen the C-index of the latter from 0.672 to 0.755. DCA and calibration curve analyses also demonstrated good performance of the combined clinical-radiomic model.ConclusionsRadiomic features extracted from the contrast-enhanced chest CT could be used to evaluate metastatic NSCLC patients' prognosis in osimertinib treatment. Prognostic models combing both radiomic features and clinical factors had a great performance in predicting patients' outcomes.

Project description:The emergence of secondary resistance is the main failure cause of epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) as a targeted therapy for non-small cell lung cancer (NSCLC). EGFR mutations of NSCLC cells can markedly increase glutamine transporter (SLC1A5) expression, thereby increasing glutamine metabolism. Glutamine metabolites can activate EGFR downstream signals, including mTOR, ERK1/2, STAT3, etc., which is an important cause for the decreased sensitivity of NSCLC to EGFR-TKIs. CCK8 and Annexin V/PI assays were conducted to detect the effects of Almonertinib and/or V9302 on the proliferation and apoptosis of NSCLC cells. Proteomics was used to determine the effect of Almonertinib on energy metabolism-related proteins in NSCLC. siRNA transfection was performed to study the effect of SLC1A5 down-regulation on cell proliferation. In addition, the effects of drugs on colony formation capacity were determined by colony formation assay. Immunofluorescence and Western blot were utilized to detect the apoptosis- and autophagy-related proteins expression. DAPI staining was utilized to detect the effect of drugs on the nucleus. Transmission electron microscope was used to observe the changes of submicroscopic structure such as autophagosomes and nucleus of cells. mCherry-GFP-LC3B tandem fluorescent protein was to used to detect the level of autophagy flux. Tumor-bearing nude mouse model was utilized to detect the effect of V9302 on the anti-tumor effect of Almonertinib in vivo. As a result, Almonertinib suppressed H1975 and A549 cell proliferation depended on its dosage and treatment duration, and it also induced apoptosis. A549 cells with wild-type EGFR had lower sensitivity to Almonertinib. The expression of SLC1A5 was up-regulated by stimulating with low concentration of Almonertinib in NSCLC cells. SLC1A5 was highly expressed in A549 cells with wild-type EGFR. Glutamine deletion or SLC1A5 inhibition/silencing inhibited the proliferation of NSCLC cells, and decreased cellular glutamine uptake. The combination of SLC1A5 inhibitor V9302 and Almonertinib had a synergistic inhibitory effect on the proliferation of NSCLC. V9302 enhanced the effect of Almonertinib in apoptosis-inducing in NSCLC cells. The combination of V9302 and Almonertinib might induce apoptosis by inhibiting autophagy.

Dataset Information

Diverse Mechanisms of Resistance against Osimertinib, a Third-Generation EGFR-TKI, in Lung Adenocarcinoma Cells with an EGFR-Activating Mutation.

Publications

Diverse Mechanisms of Resistance against Osimertinib, a Third-Generation EGFR-TKI, in Lung Adenocarcinoma Cells with an <i>EGFR</i>-Activating Mutation.

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