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

ACCESS DATA

Publications

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

Similar Datasets

Project description:BackgroundAlthough substantial efforts have been made to build molecular biomarkers to predict radiation sensitivity, the ability to accurately stratify the patients is still limited. In this study, we aim to leverage large-scale radiogenomics datasets to build genomic predictors of radiation response using the integral of the radiation dose-response curve.MethodsTwo radiogenomics datasets consisting of 511 and 60 cancer cell lines were utilized to develop genomic predictors of radiation sensitivity. The intrinsic radiation sensitivity, defined as the integral of the dose-response curve (AUC) was used as the radioresponse variable. The biological determinants driving AUC and SF2 were compared using pathway analysis. To build the predictive model, the largest and smallest datasets consisting of 511 and 60 cancer cell lines were used as the discovery and validation cohorts, respectively, with AUC as the response variable.ResultsUtilizing a compendium of three pathway databases, we illustrated that integral of the radiobiological model provides a more comprehensive characterization of molecular processes underpinning radioresponse compared to SF2. Furthermore, more pathways were found to be unique to AUC than SF2-30, 288 and 38 in KEGG, REACTOME and WIKIPATHWAYS, respectively. Also, the leading-edge genes driving the biological pathways using AUC were unique and different compared to SF2. With regards to radiation sensitivity gene signature, we obtained a concordance index of 0.65 and 0.61 on the discovery and validation cohorts, respectively.ConclusionWe developed an integrated framework that quantifies the impact of physical radiation dose and the biological effect of radiation therapy in interventional pre-clinical model systems. With the availability of more data in the future, the clinical potential of this signature can be assessed, which will eventually provide a framework to integrate genomics into biologically-driven precision radiation oncology.

Project description:BackgroundGlucocorticoids (GC's) play an integral role in treatment strategies designed to combat various forms of hematological malignancies. GCs also are powerful inhibitors of the immune system, through regulation of appropriate cytokines and by causing apoptosis of immature thymocytes. By activating the glucocorticoid receptor (GR), GCs evoke apoptosis through transcriptional regulation of a complex, interactive gene network over a period of time preceding activation of the apoptotic enzymes. In this study we used microarray technology to determine whether several disparate types of hematologic cells, all sensitive to GC-evoked apoptosis, would identify a common set of regulated genes. We compared gene expression signatures after treatment with two potent synthetic GCs, dexamethasone (Dex) and cortivazol (CVZ) using a panel of hematologic cells. Pediatric CD4+/CD8+ T-cell leukemia was represented by 3 CEM clones: two sensitive, CEM-C7-14 and CEM-C1-6, and one resistant, CEM-C1-15, to Dex. CEM-C1-15 was also tested when rendered GC-sensitive by several treatments. GC-sensitive pediatric B-cell leukemia was represented by the SUP-B15 line and adult B-cell leukemia by RS4;11 cells. Kasumi-1 cells gave an example of the rare Dex-sensitive acute myeloblastic leukemia (AML). To test the generality of the correlations in malignant cell gene sets, we compared with GC effects on mouse non-transformed thymocytes.ResultsWe identified a set of genes regulated by GCs in all GC-sensitive malignant cells. A portion of these were also regulated in the thymocytes. Because we knew that the highly Dex-resistant CEM-C1-15 cells could be killed by CVZ, we tested these cells with the latter steroid and again found that many of the same genes were now regulated as in the inherently GC-sensitive cells. The same result was obtained when we converted the Dex-resistant clone to Dex-sensitive by treatment with forskolin (FSK), to activate the adenyl cyclase/protein kinase A pathway (PKA).ConclusionOur results have identified small sets of genes that correlate with GC-sensitivity in cells from several hematologic malignancies. Some of these are also regulated in normal mouse thymocytes.

Project description:Assessment of the immune status of muscle-invasive bladder cancer (MIBC) has previously shown to be prognostically relevant after treatment with curative intent. We conducted this study to develop a clinically applicable immune gene expression assay to predict prognosis and adjuvant chemotherapy benefit. Gene expression of CD3Z, CD8A and CXCL9, immune cell (IC) populations including stromal tumor infiltrating lymphocytes (sTILs), T-cells, natural killer cells (NK-cells), macrophages, Programmed cell death protein 1 positive (PD-1) IC and tumor subtypes (MD Anderson Cancer Center/MDACC-approach) were assessed in 187 MIBC patients (Comprehensive Cancer Center Erlangen-EMN/CCC-EMN-cohort). A gene expression signature was derived by hierarchical-clustering and validated in The Cancer Genome Atlas (TCGA)-cohort. IC populations in the TCGA cohort were assessed via CIBERSORT. Benefit of platinum-containing adjuvant chemotherapy was assessed in a pooled cohort of 125 patients. Outcome measurements were disease specific survival, disease-free survival and overall survival. The gene expression signature of CXCL9, CD3Z and CD8A correlates with quantitative amounts of specific IC populations and sTILs (CCC-EMN: ρ-range: 0.44-0.74; TCGA: ρ-range: 0.56-0.82) and allows stratification of three different inflammation levels (inflamed high, inflamed low, uninflamed). Highly inflamed tumors are preferentially basal subtype and show favorable 5-year survival rates of 67.3% (HR=0.27; CCC-EMN) and 55% (HR=0.41; TCGA). Uninflamed tumors are predominantly luminal subtypes and show low 5-year survival rates of 28% (CCC-EMN) and 36% (TCGA). Inflamed tumors exhibit higher levels of PD-1 and Programmed cell death 1 ligand 1 (PD-L1). Patients undergoing adjuvant platinum-based chemotherapy with 'inflamed high' tumors showed a favorable 5-year survival rate of 64% (HR=0.27; merged CCC-EMN and TCGA cohort). The gene expression signature of CD3Z, CD8A and CXCL9 can assess the immune status of MIBC and stratify the survival of MIBC patients undergoing surgery and adjuvant platinum-based chemotherapy. Furthermore, the assay can identify patients with immunological hot tumors with particular high expression of PD-L1 potentially suitable for immunotherapy.

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.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets