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Establishing Dual Resistance to EGFR-TKI and MET-TKI in Lung Adenocarcinoma Cells In Vitro with a 2-step Dose-escalation Procedure
Published on: August 11, 2017
Predictors of sensitivity and resistance to epidermal growth factor receptor inhibitors
1The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA.
Abstract:
Lung cancer is one of the leading types of cancer with an associated high mortality. Currently, treatment with conventional cytotoxic agents remains suboptimal. Inhibition of the epidermal growth factor receptor (EGFR) with monoclonal antibodies or small-molecule inhibitors of the tyrosine kinase (TK) domain of the receptor have demonstrated modest, albeit significant, antitumor activities in patients with non-small-cell lung cancer (NSCLC). The goal of any targeted therapy is to direct treatment to those patients who are more likely to derive benefit from such a treatment. Two interventions may improve the predicted sensitivity to these agents: (1) the use of a real predictor before treatment, represented by pharmacodiagnostic tests, and (2) studying the relationship between an early event after treatment and outcome, represented by pharmacodynamic tests. Pharmacodiagnostic factors that have been studied include the clinical features and histologic subtype of the tumor, the presence of somatic mutations in the TK domain of the EGFR, the expression of the receptor itself, and the activation of the receptor signaling pathway. Pharmacodynamic events associated with improved outcome include drug-induced rash and regulation of the receptor expression. Currently, the best established determinant of response to small-molecule inhibitors of the EGFR is the presence of activating mutations in the receptor TK domain. However, it is not known whether these functional mutations are involved in the response of NSCLC to monoclonal antibodies. Further investigation is needed to better predict patients who are more likely to benefit from these drugs.
Insights
Targeted therapies show promise for lung cancer, but predicting patient response is key. Identifying biomarkers like EGFR mutations can help direct treatment for non-small cell lung cancer (NSCLC).
Area of Science:
- Oncology
- Molecular Biology
- Pharmacology
Background:
- Lung cancer has high mortality, with conventional treatments being suboptimal.
- Targeted therapies like EGFR inhibitors offer modest antitumor activity in non-small cell lung cancer (NSCLC).
- Predicting patient response to targeted therapy is crucial for treatment efficacy.
Purpose of the Study:
- To explore pharmacodiagnostic and pharmacodynamic tests for predicting sensitivity to EGFR inhibitors in NSCLC.
- To identify reliable biomarkers for patient selection in targeted lung cancer therapy.
Main Methods:
- Review of pharmacodiagnostic factors: clinical features, histology, EGFR mutations, receptor expression, and pathway activation.
- Analysis of pharmacodynamic events: drug-induced rash and receptor expression regulation.
- Evaluation of EGFR tyrosine kinase (TK) domain mutations as a determinant of response.
Main Results:
- EGFR TK domain mutations are the best-established predictor for small-molecule inhibitor response in NSCLC.
- Pharmacodiagnostic tests and pharmacodynamic markers are being investigated to improve treatment prediction.
- The role of EGFR mutations in response to monoclonal antibodies in NSCLC requires further study.
Conclusions:
- Accurate prediction of patient benefit from EGFR-targeted therapies in NSCLC is an ongoing challenge.
- Further research is needed to identify and validate biomarkers for personalized lung cancer treatment.
- Optimizing targeted therapy requires a deeper understanding of predictive and pharmacodynamic factors.
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