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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
Predictive and prognostic markers for epidermal growth factor receptor inhibitor therapy in non-small cell lung
Nir Peled1, Koichi Yoshida, Murry W Wynes
1Division of Medical Oncology, University of Colorado Denver, Aurora, CO, USA.
Abstract:
Epidermal growth factor receptor (EGFR) related therapies - mainly tyrosine kinase inhibitors (TKIs) such as erlotinib and gefitinib, but also monoclonal antibodies targeting EGFR, for example, cetuximab - have been investigated in numerous settings in non-small cell lung cancer (NSCLC) and in different combinations. The overall clinical benefit of EGFR TKI therapy is roughly 10-30%, with higher benefit in nonsmoker Asiatic women with EGFR-mutated adenocarcinoma. Currently, there are several biomarkers that are able to direct and predict the yield of EGFR-related therapies in NSCLC. These include EGFR mutation status, EGFR protein expression, EGFR gene copy number and a serum proteomic marker (Veristrat®, Biodesix; CO). The usage of such biomarkers is important from many aspects. First, it helps clinicians to make the right treatment decisions and second, it leads to a wiser usage of financial resources. This review will focus on EGFR-related biomarkers for their prognostic power and their ability to predict clinical benefit from EGFR-related therapy.
Insights
Biomarkers like EGFR mutation status can predict treatment success for non-small cell lung cancer (NSCLC) patients receiving EGFR-targeted therapies, including tyrosine kinase inhibitors (TKIs). This improves treatment decisions and resource allocation.
Area of Science:
- Oncology
- Molecular Biology
- Pharmacogenomics
Background:
- Epidermal growth factor receptor (EGFR) targeted therapies, including tyrosine kinase inhibitors (TKIs) and monoclonal antibodies, are used in non-small cell lung cancer (NSCLC).
- The clinical benefit of EGFR TKI therapy in NSCLC ranges from 10-30%, with notable efficacy in specific patient subgroups like non-smoker Asian women with EGFR-mutated adenocarcinoma.
- Accurate patient selection is crucial for optimizing treatment outcomes and resource utilization in NSCLC management.
Purpose of the Study:
- To review and analyze the prognostic power of various biomarkers for predicting clinical benefit from EGFR-related therapies in NSCLC.
- To highlight the role of biomarkers in guiding treatment decisions for EGFR-targeted therapies.
- To discuss the importance of biomarkers in ensuring efficient use of healthcare resources.
Main Methods:
- Review of existing literature on EGFR-related biomarkers and their association with treatment outcomes in NSCLC.
- Analysis of data regarding EGFR mutation status, protein expression, gene copy number, and serum proteomic markers (e.g., Veristrat®).
- Evaluation of the predictive and prognostic capabilities of these biomarkers in the context of EGFR-targeted therapies.
Main Results:
- Several biomarkers, including EGFR mutation status, protein expression, and gene copy number, are established predictors of response to EGFR-targeted therapies.
- A serum proteomic marker (Veristrat®) has also shown potential in predicting treatment outcomes.
- These biomarkers help identify NSCLC patients most likely to benefit from EGFR inhibitors, such as erlotinib, gefitinib, and cetuximab.
Conclusions:
- Biomarker-driven selection is essential for maximizing the efficacy of EGFR-targeted therapies in NSCLC.
- Utilizing biomarkers improves clinical decision-making and promotes cost-effective cancer treatment.
- Further research into novel biomarkers may further refine patient stratification for personalized NSCLC therapy.
