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Published on: November 22, 2021
A Gene Expression Signature Predicts Bladder Cancer Cell Line Sensitivity to EGFR Inhibition
Andrew Goodspeed1, Annie Jean1, Dan Theodorescu1,2,3
1Department of Pharmacology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Background:
Bladder cancer remains a cancer type in need of novel and alternative therapies. While multiple inhibitors of EGFR have been evaluated for efficacy in bladder cancer, the results have largely been disappointing with few patients responding to these therapies. Yet, there is a subset of patients that positively responds to EGFR inhibition with tumor shrinkage, indicating it is an effective treatment for a targeted set of bladder tumors.
Objective:
To derive a gene expression signature capable of predicting the response to EGFR inhibition in bladder cancer cell lines.
Methods:
he response to cetuximab for 68 colorectal cancer patients was used as training data to generate a gene expression signature. We applied this signature to bladder cancer cell lines and predictions were compared to the responses to seven EGFR inhibitors.
Results:
A novel 67-gene signature derived from colorectal cancer was able to significantly identify bladder cancer cell lines by their response to several EGFR inhibitors.
Conclusions:
The 67-gene signature can determine bladder cancer cell line sensitivity to EGFR inhibition. This work demonstrates a preclinical strategy to identify bladder cancer cell lines for EGFR-targeted therapy.
Insights
A new 67-gene signature predicts bladder cancer response to epidermal growth factor receptor (EGFR) inhibitors. This finding offers a preclinical strategy for identifying patients who will benefit from targeted EGFR therapy.
Area of Science:
- Oncology
- Genomics
- Molecular Biology
Background:
- Bladder cancer requires novel therapeutic strategies.
- Epidermal growth factor receptor (EGFR) inhibitors show limited efficacy in bladder cancer, despite a subset of patients responding positively.
- Identifying predictive biomarkers for EGFR inhibition is crucial.
Purpose of the Study:
- To develop a gene expression signature for predicting bladder cancer cell line response to EGFR inhibition.
- To establish a preclinical model for patient stratification in EGFR-targeted therapy.
Main Methods:
- A 67-gene signature was generated using gene expression data from 68 colorectal cancer patients treated with cetuximab.
- The derived signature was applied to bladder cancer cell lines.
- Predicted responses were compared against observed responses to seven EGFR inhibitors.
Main Results:
- The 67-gene signature successfully identified bladder cancer cell lines sensitive to EGFR inhibition.
- The signature demonstrated significant predictive capability across multiple EGFR inhibitors.
Conclusions:
- A 67-gene signature can predict bladder cancer cell line sensitivity to EGFR inhibition.
- This study provides a preclinical framework for selecting bladder cancer patients for EGFR-targeted treatments.
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