Dataset Information

[Identification of Candidate Biomarkers for EGFR-T790M Drug-resistant ?Gene Mutation in Advanced Lung Adenocarcinoma].

ABSTRACT:

Background

Osimertinib is approved by Food and Drug Administration for patients with advanced non-small cell lung cancer carrying EGFR-T790M mutations. Osimertinib therapy was missed in many patients who were unable to perform biopsy due to occult lesion progression or weak body. In this study. We hope that some proteins associated with predicting EGFR-T790M resistance could be screened from the serum to provide help for clinical medication. The aim of this study is to explore the protein associated with EGFR-T790M drug resistance gene and provide help for clinical medication.

Methods

In this study, 36 patients with advanced lung adenocarcinoma treated by gefitinib were included. After the disease progression of the patients, biopsy was performed. 18 patients in the EGFR-T790M mutation group and 18 patients in the non-EGFR-T790M mutation group were detected by the ARMS method. Serum of patients with drug resistance was collected, and proteins related to EGFR-T790M resistance were screened by isotopic marker relative and absolute quantitative marker combined with two-dimensional liquid chromatography tandem mass spectrometry proteomics technology.

Results

Seventeen different proteins were screened out, including 6 up-regulated proteins and 11 down-regulated proteins associated with EGFR-T790M gene mutation, which were mainly involved in 31 biological processes, 7 cell components and 26 molecular functions. Twelve enrichment pathways were identified, among which the highest enrichment index was the coagulation cascade pathway.

Conclusions

Seventeen proteins associated with EGFR-T790M resistance were found, and proteins involved in the coagulation cascade pathway are expected to be biomarkers associated with predicting EGFR-T790M resistance mutations.

SUBMITTER: Chen L

PROVIDER: S-EPMC7679218 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Publications

[Identification of Candidate Biomarkers for EGFR-T790M Drug-resistant  Gene Mutation in Advanced Lung Adenocarcinoma].

Chen Lijuan L Shan Li L Yu Tingting T

Zhongguo fei ai za zhi = Chinese journal of lung cancer 20201101 11

<h4>Background</h4>Osimertinib is approved by Food and Drug Administration for patients with advanced non-small cell lung cancer carrying EGFR-T790M mutations. Osimertinib therapy was missed in many patients who were unable to perform biopsy due to occult lesion progression or weak body. In this study. We hope that some proteins associated with predicting EGFR-T790M resistance could be screened from the serum to provide help for clinical medication. The aim of this study is to explore the protei ...[more]

PMID: 33203197

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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.

Project description:Despite clinical approval of erlotinib, most advanced lung cancer patients are primary non-responders. Initial responders invariably develop secondary resistance, which can be accounted for by T790M-EGFR mutation in half of the relapses. We show that MET is highly expressed in lung cancer, often concomitantly with epidermal growth factor receptor (EGFR), including H1975 cell line. The erlotinib-resistant lung cancer cell line H1975, which expresses L858R/T790M-EGFR in-cis, was used to test for the effect of MET inhibition using the small molecule inhibitor SU11274. H1975 cells express wild-type MET, without genomic amplification (CNV = 1.1). At 2 microM, SU 11274 had significant in vitro pro-apoptotic effect in H1975 cells, 3.9-fold (P = 0.0015) higher than erlotinib, but had no effect on the MET and EGFR-negative H520 cells. In vivo, SU11274 also induced significant tumour cytoreduction in H1975 murine xenografts in our bioluminescence molecular imaging assay. Using small-animal microPET/MRI, SU11274 treatment was found to induce an early tumour metabolic response in H1975 tumour xenografts. MET and EGFR pathways were found to exhibit collaborative signalling with receptor cross-activation, which had different patterns between wild type (A549) and L858R/T790M-EGFR (H1975). SU11274 plus erlotinib/CL-387,785 potentiated MET inhibition of downstream cell proliferative survival signalling. Knockdown studies in H1975 cells using siRNA against MET alone, EGFR alone, or both, confirmed the enhanced downstream inhibition with dual MET-EGFR signal path inhibition. Finally, in our time-lapse video-microscopy and in vivo multimodal molecular imaging studies, dual SU11274-erlotinib concurrent treatment effectively inhibited H1975 cells with enhanced abrogation of cytoskeletal functions and complete regression of the xenograft growth. Together, our results suggest that MET-based targeted inhibition using small-molecule MET inhibitor can be a potential treatment strategy for T790M-EGFR-mediated erlotinib-resistant non-small-cell lung cancer. Furthermore, optimised inhibition may be further achieved with MET inhibition in combination with erlotinib or an irreversible EGFR-TKI.

Dataset Information

[Identification of Candidate Biomarkers for EGFR-T790M Drug-resistant ?Gene Mutation in Advanced Lung Adenocarcinoma].

Background

Methods

Results

Conclusions

Publications

[Identification of Candidate Biomarkers for EGFR-T790M Drug-resistant  Gene Mutation in Advanced Lung Adenocarcinoma].

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

[Identification of Candidate Biomarkers for EGFR-T790M Drug-resistant ?Gene Mutation in Advanced Lung Adenocarcinoma].

Background

Methods

Results

Conclusions

Publications

[Identification of Candidate Biomarkers for EGFR-T790M Drug-resistant Gene Mutation in Advanced Lung Adenocarcinoma].

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

[Identification of Candidate Biomarkers for EGFR-T790M Drug-resistant  Gene Mutation in Advanced Lung Adenocarcinoma].