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Gene profiling, mutations and expression of epidermal growth factor receptor in androgen-dependent prostate cancer

ABSTRACT: We analyzed mutations in Epidermal Growth Factor Receptor (EGFR) Tyrosine kinase (TK) domain, EGFR expression and gene profiling in prostate carcinoma (PC) in order to find out molecular prognostic markers and supply a proof for EGFR targeted therapies. 100 glyofixx-fixed, paraffin-embedded PC specimens were recovered after radical prostatectomy from locally advanced PC patients. Exons from 18 to 21 of EGFR TK domain were amplified and sequenced. For the entire cohort, EGFR protein evaluation by immunohistochemistry was performed. Gene expression profile was analyzed on 51 out of 100 samples by whole genome microarray. Statistical tests were performed in order to detect any significant association between EGFR iperexpression and prognosis. None out of 100 specimens presented mutations in exon 18; 2 point mutations were identified in exon 19, 5 in exon 20 and 6 in exon 21. In addiction, 58 out of 100 patients had the same silent mutation, at codon 787 in exon 20. EGFR iper-expression was found in 36% of specimens and was significantly associated with biochemical relapse. Gene profiling analysis on mutated samples selected 29 modulated genes differentially expressed between mutated EGFR+ and mutated EGFR- samples; 4 down-regulated genes, EAF2, ABCC4, KLK3 and ANXA3 and one up-regulated gene, FOXC1, are involved in prostate cancer progression. Our findings suggest that a subgroup of PC patients could potentially benefit of EGFR targeted therapies. The EGFR protein evaluation could contribute to identify PC relapsers. Keywords: EGFR expression, TK mutations, target therapy, microarray data.

ORGANISM(S): Homo sapiens

PROVIDER: GSE16120 | GEO | 2011/06/30

SECONDARY ACCESSION(S): PRJNA117241

REPOSITORIES: GEO

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Project description:We analyzed mutations in Epidermal Growth Factor Receptor (EGFR) Tyrosine kinase (TK) domain, EGFR expression and gene profiling in prostate carcinoma (PC) in order to find out molecular prognostic markers and supply a proof for EGFR targeted therapies. 100 glyofixx-fixed, paraffin-embedded PC specimens were recovered after radical prostatectomy from locally advanced PC patients. Exons from 18 to 21 of EGFR TK domain were amplified and sequenced. For the entire cohort, EGFR protein evaluation by immunohistochemistry was performed. Gene expression profile was analyzed on 51 out of 100 samples by whole genome microarray. Statistical tests were performed in order to detect any significant association between EGFR iperexpression and prognosis. None out of 100 specimens presented mutations in exon 18; 2 point mutations were identified in exon 19, 5 in exon 20 and 6 in exon 21. In addiction, 58 out of 100 patients had the same silent mutation, at codon 787 in exon 20. EGFR iper-expression was found in 36% of specimens and was significantly associated with biochemical relapse. Gene profiling analysis on mutated samples selected 29 modulated genes differentially expressed between mutated EGFR+ and mutated EGFR- samples; 4 down-regulated genes, EAF2, ABCC4, KLK3 and ANXA3 and one up-regulated gene, FOXC1, are involved in prostate cancer progression. Our findings suggest that a subgroup of PC patients could potentially benefit of EGFR targeted therapies. The EGFR protein evaluation could contribute to identify PC relapsers. Keywords: EGFR expression, TK mutations, target therapy, microarray data. In this work we studied mutation status and expression of Epidermal Growth Factor Receptor (EGFR) in a case series of 100 primary prostate cancer tissue specimens. Results indicate that 13% and 36% of PC patients presents EGFR tyrosine kinase domain mutations and iperexpression respectively, suggesting that this receptor could be a therapeutic target in progressive prostate cancer. The analysis of correlation between EGFR protein expression, mutations, clinical parameters and outcome allow us to identify EGFR as significantly associated with biochemical relapse and high Gleason score. Gene expression profiling in 51 of PC tissues led to the identification of a gene list which separated EGFR mutated patients according to EGFR protein expression. These results could give more information on clinical outcome and possible development of new targeted therapies.

Project description:Orton2009 - Modelling cancerous mutations in the EGFR/ERK pathway - EGF Model This model studies the aberrations in ERK signalling for different cancer mutations. The authors alter a previously existing EGF model (Brown et al 2004) to include new interactions that better fit empirical data. Predictions show that the ERK signalling is a robust mechanism taking different courses for different cancer mutations. Most parameter values are used from the previous model and the new parameters are estimated using experimental data performed by the authors on PC12 cells (adrenal gland, rat). The authors provide an SBML version of the model in the paper. This model is described in the article: Computational modelling of cancerous mutations in the EGFR/ERK signalling pathway. Orton RJ, Adriaens ME, Gormand A, Sturm OE, Kolch W, Gilbert DR. BMC Syst Biol 2009 Oct; 3: 100 Abstract: The Epidermal Growth Factor Receptor (EGFR) activated Extracellular-signal Regulated Kinase (ERK) pathway is a critical cell signalling pathway that relays the signal for a cell to proliferate from the plasma membrane to the nucleus. Deregulation of the EGFR/ERK pathway due to alterations affecting the expression or function of a number of pathway components has long been associated with numerous forms of cancer. Under normal conditions, Epidermal Growth Factor (EGF) stimulates a rapid but transient activation of ERK as the signal is rapidly shutdown. Whereas, under cancerous mutation conditions the ERK signal cannot be shutdown and is sustained resulting in the constitutive activation of ERK and continual cell proliferation. In this study, we have used computational modelling techniques to investigate what effects various cancerous alterations have on the signalling flow through the ERK pathway.We have generated a new model of the EGFR activated ERK pathway, which was verified by our own experimental data. We then altered our model to represent various cancerous situations such as Ras, B-Raf and EGFR mutations, as well as EGFR overexpression. Analysis of the models showed that different cancerous situations resulted in different signalling patterns through the ERK pathway, especially when compared to the normal EGF signal pattern. Our model predicts that cancerous EGFR mutation and overexpression signals almost exclusively via the Rap1 pathway, predicting that this pathway is the best target for drugs. Furthermore, our model also highlights the importance of receptor degradation in normal and cancerous EGFR signalling, and suggests that receptor degradation is a key difference between the signalling from the EGF and Nerve Growth Factor (NGF) receptors.Our results suggest that different routes to ERK activation are being utilised in different cancerous situations which therefore has interesting implications for drug selection strategies. We also conducted a comparison of the critical differences between signalling from different growth factor receptors (namely EGFR, mutated EGFR, NGF, and Insulin) with our results suggesting the difference between the systems are large scale and can be attributed to the presence/absence of entire pathways rather than subtle difference in individual rate constants between the systems. This model is hosted on BioModels Database and identified by: BIOMD0000000623. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

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Gene profiling, mutations and expression of epidermal growth factor receptor in androgen-dependent prostate cancer

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