Structure-based classification predicts drug response in EGFR-mutant NSCLC.
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ABSTRACT:
SUBMITTER: Robichaux JP
PROVIDER: S-EPMC8481125 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:EGFR tyrosine kinase inhibitors cause dramatic responses in EGFR-mutant lung cancer, but resistance universally develops. The involvement of ?-catenin in EGFR TKI resistance has been previously reported, however, the precise mechanism by which ?-catenin activation contributes to EGFR TKI resistance is not clear. Here, we show that EGFR inhibition results in the activation of ?-catenin signaling in a Notch3-dependent manner, which facilitates the survival of a subset of cells that we call "adaptive persisters". We previously reported that EGFR-TKI treatment rapidly activates Notch3, and here we describe the physical association of Notch3 with ?-catenin, leading to increased stability and activation of ?-catenin. We demonstrate that the combination of EGFR-TKI and a ?-catenin inhibitor inhibits the development of these adaptive persisters, decreases tumor burden, improves recurrence free survival, and overall survival in xenograft models. These results supports combined EGFR-TKI and ?-catenin inhibition in patients with EGFR mutant lung cancer.
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Project description:EGFR tyrosine kinase inhibitors cause dramatic responses in EGFR-mutant lung cancer, but resistance universally develops. The involvement of β-catenin in EGFR TKI resistance has been previously reported however the precise mechanism by which β-catenin activation contributes to EGFR TKI resistance is not clear. Here, we show that EGFR inhibition results in the activation of β-catenin signaling in a Notch3-dependent manner, which facilitates the survival of a subset of cells that we call “adaptive persisters”. We previously reported that EGFR-TKI treatment rapidly activates Notch3, and here describe the physical association of Notch3 with β-catenin, leading to increased stability and activation of β-catenin. We demonstrate that the combination of EGFR-TKI and a β-catenin inhibitor inhibits the development of these adaptive persisters, decreases tumor burden, improves recurrence free survival, and overall survival in xenograft models. These results supports combined EGFR-TKI and β-catenin inhibition in patients with EGFR mutant lung cancer.
2018-08-31 | GSE115864 | GEO
Project description:The majority of non-small cell lung cancer (NSCLC) patients harbor EGFR-activating mutations that can be therapeutically targeted by EGFR tyrosine kinase inhibitors (EGFR-TKI), such as erlotinib and gefitinib. Unfortunately, a subset of patients with EGFR mutations are refractory to EGFR-TKIs. Resistance to EGFR inhibitors reportedly involves SRC activation and induction of epithelial-to-mesenchymal transition (EMT). Here, we have demonstrated that overexpression of CRIPTO1, an EGF-CFC protein family member, renders EGFR-TKI-sensitive and EGFR-mutated NSCLC cells resistant to erlotinib in culture and in murine xenograft models. Furthermore, tumors from NSCLC patients with EGFR-activating mutations that were intrinsically resistant to EGFR-TKIs expressed higher levels of CRIPTO1 compared with tumors from patients that were sensitive to EGFR-TKIs. Primary NSCLC cells derived from a patient with EGFR-mutated NSCLC that was intrinsically erlotinib resistant were CRIPTO1 positive, but gained erlotinib sensitivity upon loss of CRIPTO1 expression during culture. CRIPTO1 activated SRC and ZEB1 to promote EMT via microRNA-205 (miR-205) downregulation. While miR-205 depletion induced erlotinib resistance, miR-205 overexpression inhibited CRIPTO1-dependent ZEB1 and SRC activation, restoring erlotinib sensitivity. CRIPTO1-induced erlotinib resistance was directly mediated through SRC but not ZEB1; therefore, cotargeting EGFR and SRC synergistically attenuated growth of erlotinib-resistant, CRIPTO1-positive, EGFR-mutated NSCLC cells in vitro and in vivo, suggesting that this combination may overcome intrinsic EGFR-inhibitor resistance in patients with CRIPTO1-positive, EGFR-mutated NSCLC.
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Project description:Non-small cell lung cancers (NSCLC) that have developed resistance to EGF receptor (EGFR) tyrosine kinase inhibitor (TKI), including gefitinib and erlotinib, are clinically linked to an epithelial-to-mesenchymal transition (EMT) phenotype. Here, we examined whether modulating EMT maintains the responsiveness of EGFR-mutated NSCLCs to EGFR TKI therapy. Using human NSCLC cell lines harboring mutated EGFR and a transgenic mouse model of lung cancer driven by mutant EGFR (EGFR-Del19-T790M), we demonstrate that EGFR inhibition induces TGF? secretion followed by SMAD pathway activation, an event that promotes EMT. Chronic exposure of EGFR-mutated NSCLC cells to TGF? was sufficient to induce EMT and resistance to EGFR TKI treatment. Furthermore, NSCLC HCC4006 cells with acquired resistance to gefitinib were characterized by a mesenchymal phenotype and displayed a higher prevalence of the EGFR T790M mutated allele. Notably, combined inhibition of EGFR and the TGF? receptor in HCC4006 cells prevented EMT but was not sufficient to prevent acquired gefitinib resistance because of an increased emergence of the EGFR T790M allele compared with cells treated with gefitinib alone. Conversely, another independent NSCLC cell line, PC9, reproducibly developed EGFR T790M mutations as the primary mechanism underlying EGFR TKI resistance, even though the prevalence of the mutant allele was lower than that in HCC4006 cells. Thus, our findings underscore heterogeneity within NSCLC cells lines harboring EGFR kinase domain mutations that give rise to divergent resistance mechanisms in response to treatment and anticipate the complexity of EMT suppression as a therapeutic strategy.
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Project description:Mutations in oncogenes and tumor suppressor genes engender unique metabolic phenotypes crucial to the survival of tumor cells. EGFR signaling has been linked to the rewiring of tumor metabolism in non-small cell lung cancer (NSCLC). We have integrated the use of a functional genomics screen and metabolomics to identify metabolic vulnerabilities induced by EGFR inhibition. These studies reveal that following EGFR inhibition, EGFR-driven NSCLC cells become dependent on the urea cycle and, in particular, the urea cycle enzyme CPS1. Combining knockdown of CPS1 with EGFR inhibition further reduces cell proliferation and impedes cell-cycle progression. Profiling of the metabolome demonstrates that suppression of CPS1 potentiates the effects of EGFR inhibition on central carbon metabolism, pyrimidine biosynthesis, and arginine metabolism, coinciding with reduced glycolysis and mitochondrial respiration. We show that EGFR inhibition and CPS1 knockdown lead to a decrease in arginine levels and pyrimidine derivatives, and the addition of exogenous pyrimidines partially rescues the impairment in cell growth. Finally, we show that high expression of CPS1 in lung adenocarcinomas correlated with worse patient prognosis in publicly available databases. These data collectively reveal that NSCLC cells have a greater dependency on the urea cycle to sustain central carbon metabolism, pyrimidine biosynthesis, and arginine metabolism to meet cellular energetics upon inhibition of EGFR. IMPLICATIONS: Our results reveal that the urea cycle may be a novel metabolic vulnerability in the context of EGFR inhibition, providing an opportunity to develop rational combination therapies with EGFR inhibitors for the treatment of EGFR-driven NSCLC.
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Project description:The impact of EGFR-mutant NSCLC precision therapy is limited by acquired resistance despite initial excellent response. Classic studies of EGFR-mutant clinical resistance to precision therapy were based on tumor rebiopsies late during clinical tumor progression on therapy. Here, we characterized a novel non-mutational early adaptive drug-escape in EGFR-mutant lung tumor cells only days after therapy initiation, that is MET-independent. The drug-escape cell states were analyzed by integrated transcriptomic and metabolomics profiling uncovering a central role for autocrine TGFβ2 in mediating cellular plasticity through profound cellular adaptive Omics reprogramming, with common mechanistic link to prosurvival mitochondrial priming. Cells undergoing early adaptive drug escape are in proliferative-metabolic quiescent, with enhanced EMT-ness and stem cell signaling, exhibiting global bioenergetics suppression including reverse Warburg, and are susceptible to glutamine deprivation and TGFβ2 inhibition. Our study further supports a preemptive therapeutic targeting of bioenergetics and mitochondrial priming to impact early drug-escape emergence using EGFR precision inhibitor combined with broad BH3-mimetic to interrupt BCL-2/BCL-xL together, but not BCL-2 alone.
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Project description:IntroductionIn classical EGFR mutant non-small-cell lung cancer (NSCLC), EGFR tyrosine kinase inhibitor (TKI) therapy yields better outcomes than platinum-based chemotherapy. However, EGFR exon 20 insertion (ex20ins) NSCLC is relatively resistant to currently available EGFR TKIs. Though platinum-based chemotherapy is the frontline standard of care for EGFR ex20ins NSCLC, its efficacy is not fully described.Study designA retrospective, single-center, case series METHODS: Patients were identified through an electronic research database at a single institution and included if they had advanced EGFR ex20ins NSCLC, received platinum-based chemotherapy for metastatic disease, and had scans evaluable for response. Each patient's demographics, tumor characteristics, and clinical course were recorded. Treatment response was evaluated using RECIST v1.1 criteria, and the PFS was calculated by the Kaplan-Meier method.ResultsAmong 27 patients identified with EGFR ex20ins NSCLC at our institution, 18 (67%) received platinum-based chemotherapy for metastatic disease and had scans evaluable for response. These patients received platinum-based chemotherapy in the first-line (N = 17, 94%) and second-line settings (N = 1, 6%). The objective response rate (ORR) to platinum-based chemotherapy was 39% (7 of 18 patients; 95% confidence interval [CI] 16-61). The median PFS with platinum-based chemotherapy was 7.1 months (95% CI, 6.3 -13.7), and the median overall survival was 3.2 years (95% CI, 1.92 - NR).ConclusionsThe efficacy of platinum-based chemotherapy in EGFR ex20ins NSCLC is similar to that expected for TKI sensitive EGFR mutant NSCLC. Novel agents designed to specifically target ex20ins mutant EGFR should additionally improve outcomes.
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Project description:An acquired mutation (T790M) in the epidermal growth factor receptor (EGFR) accounts for half of all relapses in non-small cell lung cancer (NSCLC) patients who initially respond to EGFR kinase inhibitors. In this study, we demonstrated for the first time that EGFR-T790M interacts with the cytoskeletal components, myosin heavy chain 9 (MYH9) and β-actin, in the nucleus of H1975 cells carrying the T790M-mutant EGFR. The interactions of EGFR with MYH9 and β-actin were reduced in the presence of blebbistatin, a specific inhibitor for the MYH9-β-actin interaction, suggesting that the EGFR interaction with MYH9 and β-actin is affected by the integrity of the cytoskeleton. These physical interactions among MYH9, β-actin, and EGFR were also impaired by CL-387,785, a kinase inhibitor for EGFR-T790M. Furthermore, CL-387,785 and blebbistatin interacted in a synergistic fashion to suppress cell proliferation and induce apoptosis in H1975 cells. The combination of CL-387,785 and blebbistatin enhanced the down-regulation of cyclooxygenase-2 (COX-2), a transcriptional target of nuclear EGFR. Overall, our findings demonstrate that disrupting EGFR interactions with the cytoskeletal components enhanced the anti-cancer effects of CL-387,785 against H1975 cells, suggesting a novel therapeutic approach for NSCLC cells that express the drug-resistant EGFR-T790M.
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Project description:Purpose: This study aimed to compare the performance of radiomics and deep learning in predicting EGFR mutation status in patients with lung cancer based on PET/CT images, and tried to explore a model with excellent prediction performance to accurately predict EGFR mutation status in patients with non-small cell lung cancer (NSCLC). Method: PET/CT images of 194 NSCLC patients from Xijing Hospital were collected and divided into a training set and a validation set according to the ratio of 7:3. Statistics were made on patients' clinical characteristics, and a large number of features were extracted based on their PET/CT images (4306 radiomics features and 2048 deep learning features per person) with the pyradiomics toolkit and 3D convolutional neural network. Then a radiomics model (RM), a deep learning model (DLM), and a hybrid model (HM) were established. The performance of the three models was compared by receiver operating characteristic (ROC) curves, sensitivity, specificity, accuracy, calibration curves, and decision curves. In addition, a nomogram based on a deep learning score (DS) and the most significant clinical characteristic was plotted. Result: In the training set composed of 138 patients (64 with EGFR mutation and 74 without EGFR mutation), the area under the ROC curve (AUC) of HM (0.91, 95% CI: 0.86-0.96) was higher than that of RM (0.82, 95% CI: 0.75-0.89) and DLM (0.90, 95% CI: 0.85-0.95). In the validation set composed of 57 patients (32 with EGFR mutation and 25 without EGFR mutation), the AUC of HM (0.85, 95% CI: 0.77-0.93) was also higher than that of RM (0.68, 95% CI: 0.52-0.84) and DLM (0.79, 95% CI: 0.67-0.91). In all, HM achieved better diagnostic performance in predicting EGFR mutation status in NSCLC patients than two other models. Conclusion: Our study showed that the deep learning model based on PET/CT images had better performance than radiomics model in diagnosing EGFR mutation status of NSCLC patients based on PET/CT images. Combined with the most statistically significant clinical characteristic (smoking) and deep learning features, our hybrid model had better performance in predicting EGFR mutation types of patients than two other models, which could enable NSCLC patients to choose more personalized treatment schemes.
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