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Identifying Resistance Mechanisms against Five Tyrosine Kinase Inhibitors Targeting the ERBB/RAS Pathway in 45 Cancer Cell Lines

Because of the low overall response rates of 10–47% to targeted cancer therapeutics, there is an increasing need for predictive biomarkers. We aimed to identify genes predicting response to five already approved tyrosine kinase inhibitors. We tested 45 cancer cell lines for sensitivity to sunitinib,...

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Autores principales: Pénzváltó, Zsófia, Tegze, Bálint, Szász, A. Marcell, Sztupinszki, Zsófia, Likó, István, Szendrői, Attila, Schäfer, Reinhold, Győrffy, Balázs
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3612034/
https://www.ncbi.nlm.nih.gov/pubmed/23555683
http://dx.doi.org/10.1371/journal.pone.0059503
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author Pénzváltó, Zsófia
Tegze, Bálint
Szász, A. Marcell
Sztupinszki, Zsófia
Likó, István
Szendrői, Attila
Schäfer, Reinhold
Győrffy, Balázs
author_facet Pénzváltó, Zsófia
Tegze, Bálint
Szász, A. Marcell
Sztupinszki, Zsófia
Likó, István
Szendrői, Attila
Schäfer, Reinhold
Győrffy, Balázs
author_sort Pénzváltó, Zsófia
collection PubMed
description Because of the low overall response rates of 10–47% to targeted cancer therapeutics, there is an increasing need for predictive biomarkers. We aimed to identify genes predicting response to five already approved tyrosine kinase inhibitors. We tested 45 cancer cell lines for sensitivity to sunitinib, erlotinib, lapatinib, sorafenib and gefitinib at the clinically administered doses. A resistance matrix was determined, and gene expression profiles of the subsets of resistant vs. sensitive cell lines were compared. Triplicate gene expression signatures were obtained from the caArray project. Significance analysis of microarrays and rank products were applied for feature selection. Ninety-five genes were also measured by RT-PCR. In case of four sunitinib resistance associated genes, the results were validated in clinical samples by immunohistochemistry. A list of 63 top genes associated with resistance against the five tyrosine kinase inhibitors was identified. Quantitative RT-PCR analysis confirmed 45 of 63 genes identified by microarray analysis. Only two genes (ANXA3 and RAB25) were related to sensitivity against more than three inhibitors. The immunohistochemical analysis of sunitinib-treated metastatic renal cell carcinomas confirmed the correlation between RAB17, LGALS8, and EPCAM and overall survival. In summary, we determined predictive biomarkers for five tyrosine kinase inhibitors, and validated sunitinib resistance biomarkers by immunohistochemistry in an independent patient cohort.
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spelling pubmed-36120342013-04-03 Identifying Resistance Mechanisms against Five Tyrosine Kinase Inhibitors Targeting the ERBB/RAS Pathway in 45 Cancer Cell Lines Pénzváltó, Zsófia Tegze, Bálint Szász, A. Marcell Sztupinszki, Zsófia Likó, István Szendrői, Attila Schäfer, Reinhold Győrffy, Balázs PLoS One Research Article Because of the low overall response rates of 10–47% to targeted cancer therapeutics, there is an increasing need for predictive biomarkers. We aimed to identify genes predicting response to five already approved tyrosine kinase inhibitors. We tested 45 cancer cell lines for sensitivity to sunitinib, erlotinib, lapatinib, sorafenib and gefitinib at the clinically administered doses. A resistance matrix was determined, and gene expression profiles of the subsets of resistant vs. sensitive cell lines were compared. Triplicate gene expression signatures were obtained from the caArray project. Significance analysis of microarrays and rank products were applied for feature selection. Ninety-five genes were also measured by RT-PCR. In case of four sunitinib resistance associated genes, the results were validated in clinical samples by immunohistochemistry. A list of 63 top genes associated with resistance against the five tyrosine kinase inhibitors was identified. Quantitative RT-PCR analysis confirmed 45 of 63 genes identified by microarray analysis. Only two genes (ANXA3 and RAB25) were related to sensitivity against more than three inhibitors. The immunohistochemical analysis of sunitinib-treated metastatic renal cell carcinomas confirmed the correlation between RAB17, LGALS8, and EPCAM and overall survival. In summary, we determined predictive biomarkers for five tyrosine kinase inhibitors, and validated sunitinib resistance biomarkers by immunohistochemistry in an independent patient cohort. Public Library of Science 2013-03-29 /pmc/articles/PMC3612034/ /pubmed/23555683 http://dx.doi.org/10.1371/journal.pone.0059503 Text en © 2013 Pénzváltó et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Pénzváltó, Zsófia
Tegze, Bálint
Szász, A. Marcell
Sztupinszki, Zsófia
Likó, István
Szendrői, Attila
Schäfer, Reinhold
Győrffy, Balázs
Identifying Resistance Mechanisms against Five Tyrosine Kinase Inhibitors Targeting the ERBB/RAS Pathway in 45 Cancer Cell Lines
title Identifying Resistance Mechanisms against Five Tyrosine Kinase Inhibitors Targeting the ERBB/RAS Pathway in 45 Cancer Cell Lines
title_full Identifying Resistance Mechanisms against Five Tyrosine Kinase Inhibitors Targeting the ERBB/RAS Pathway in 45 Cancer Cell Lines
title_fullStr Identifying Resistance Mechanisms against Five Tyrosine Kinase Inhibitors Targeting the ERBB/RAS Pathway in 45 Cancer Cell Lines
title_full_unstemmed Identifying Resistance Mechanisms against Five Tyrosine Kinase Inhibitors Targeting the ERBB/RAS Pathway in 45 Cancer Cell Lines
title_short Identifying Resistance Mechanisms against Five Tyrosine Kinase Inhibitors Targeting the ERBB/RAS Pathway in 45 Cancer Cell Lines
title_sort identifying resistance mechanisms against five tyrosine kinase inhibitors targeting the erbb/ras pathway in 45 cancer cell lines
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3612034/
https://www.ncbi.nlm.nih.gov/pubmed/23555683
http://dx.doi.org/10.1371/journal.pone.0059503
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