Dataset Information

A Gene Expression Signature Predicts Bladder Cancer Cell Line Sensitivity to EGFR Inhibition.

ABSTRACT: 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.

SUBMITTER: Goodspeed A

PROVIDER: S-EPMC6087449 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

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A Gene Expression Signature Predicts Bladder Cancer Cell Line Sensitivity to EGFR Inhibition.

Goodspeed Andrew A Jean Annie A Theodorescu Dan D Costello James C JC

Bladder cancer (Amsterdam, Netherlands) 20180730 3

<h4>Background</h4>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.<h4>Objective</h4>To derive a gene expressi ...[more]

PMID: 30112438

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Dataset Information

A Gene Expression Signature Predicts Bladder Cancer Cell Line Sensitivity to EGFR Inhibition.

Publications

A Gene Expression Signature Predicts Bladder Cancer Cell Line Sensitivity to EGFR Inhibition.

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