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Anlotinib can overcome acquired resistance to EGFR-TKIs via FGFR1 signaling in non-small cell lung cancer without harboring EGFR T790M mutation.

ABSTRACT: BACKGROUND:Although many studies have defined mechanisms of resistance to EGFR-TKIs, acquired resistance remains the major limitation of monotherapy with EGFR-TKIs. METHODS:Cell viability was analyzed using a Cell Counting Kit-8 (CCK-8) assay. EGFR T790M mutation was sequenced on a HiSeq 4000 platform. mRNAs from HCC827 and HCC827 gefitinib-resistant (GR) cells were analyzed by genome analyzer-based deep sequencing. The effect of anlotinib on apoptosis and cell cycle arrest of HCC827 GR was detected by fluorescence-activated cell sorting (FACS) analysis. A mouse xenograft model was used to assess the effect of anlotinib on HCC827 GR cells. RESULTS:The T790M mutation was found in the PC-9 GR cell line but not in the HCC827 GR cell line. Anlotinib could suppress the growth of HCC827 GR cells by inhibiting FGFR1 in vitro and in a mouse xenograft model. Moreover, FGFR1 was overexpressed in HCC827 GR cells, and the knockdown of FGFR1 reversed gefitinib resistance in HCC827 GR cells. Furthermore, anlotinib induced apoptosis and cell cycle arrest in HCC827 GR cells by increasing the activity of Caspase-3. CONCLUSIONS:FGFR1 overexpression could be the mechanism of EGFR-TKI acquired resistance and anlotinib can suppresse the growth of EGFR-TKI-resistant NSCLC cells without T790M mutation.

SUBMITTER: Lian Z

PROVIDER: S-EPMC7327692 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Anlotinib can overcome acquired resistance to EGFR-TKIs via FGFR1 signaling in non-small cell lung cancer without harboring EGFR T790M mutation.

Lian Zengzhi Z Du Wenwen W Zhang Yang Y Fu Yulong Y Liu Ting T Wang Anqi A Cai Tingting T Zhu Jianjie J Zeng Yuanyuan Y Liu Zeyi Z Huang Jian-An JA

Thoracic cancer 20200520 7

<h4>Background</h4>Although many studies have defined mechanisms of resistance to EGFR-TKIs, acquired resistance remains the major limitation of monotherapy with EGFR-TKIs.<h4>Methods</h4>Cell viability was analyzed using a Cell Counting Kit-8 (CCK-8) assay. EGFR T790M mutation was sequenced on a HiSeq 4000 platform. mRNAs from HCC827 and HCC827 gefitinib-resistant (GR) cells were analyzed by genome analyzer-based deep sequencing. The effect of anlotinib on apoptosis and cell cycle arrest of HCC ...[more]

PMID: 32433828

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Project description:ObjectiveTo explore the potential of CT radiomics in detecting acquired T790M mutation and predicting prognosis in patients with advanced lung adenocarcinoma with progression after first- or second-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) therapy.Materials and methodsContrast-enhanced thoracic CT was collected from 250 lung adenocarcinoma patients (with acquired T790M mutation, n = 146, without mutation, n = 104) after progression on first- or second-generation TKIs. Radiomic features were extracted from each volume of interest. The maximum relevance minimum redundancy and the least absolute shrinkage and selection operator (LASSO) regression method were used to select the optimized features in detecting acquired T790M mutation. Univariate Cox regression and LASSO Cox regression were used to establish the radiomics model to predict the progression-free survival of osimertinib treatment. Finally, nomograms (which) combined clinical factors with radscore to predict the acquired T790M mutation and prognosis were built separately. In addition, the two nomograms were validated by the concordance index (C-index), decision curve analysis (DCA), and calibration curve analysis where appropriate.ResultsClinical factors including the progression-free survival of first-line EGFR TKIs, EGFR mutation, and N stage and 12 radiomic features were useful in predicting the acquired T790M mutation. The area under the receiver operating characteristic curves (AUC) of clinical, radiomics, and nomogram models were 0.70, 0.74, and 0.78 in the training set and 0.71, 0.71, and 0.76 in the validation set, respectively. The DCA and calibration curve analysis demonstrated a good performance of the nomogram model. Clinical factors including age and first-generation EGFR TKIs and 12 radiomic features were useful in patients' outcome prediction. The C-index of the combined nomogram was 0.686 in the training set and 0.630 in the validation set, respectively. Calibration curves demonstrated a relatively poor performance of the nomogram model.ConclusionNomogram combined clinical factors with radiomic features might be helpful to detect whether patients developed acquired T790M mutation or not after progression on first- or second-generation EGFR TKIs. Nomogram prognostic model combined clinical factors with radiomic features might have a limited value in predicting the survival of patients harboring acquired T790M mutation treated with osimertinib.

Dataset Information

Anlotinib can overcome acquired resistance to EGFR-TKIs via FGFR1 signaling in non-small cell lung cancer without harboring EGFR T790M mutation.

Publications

Anlotinib can overcome acquired resistance to EGFR-TKIs via FGFR1 signaling in non-small cell lung cancer without harboring EGFR T790M mutation.

Similar Datasets

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