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Meta-Analysis of Gene Expression Signatures Defining the Epithelial to Mesenchymal Transition during Cancer Progression

The epithelial to mesenchymal transition (EMT) represents a crucial event during cancer progression and dissemination. EMT is the conversion of carcinoma cells from an epithelial to a mesenchymal phenotype that associates with a higher cell motility as well as enhanced chemoresistance and cancer ste...

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Autores principales: Gröger, Christian J., Grubinger, Markus, Waldhör, Thomas, Vierlinger, Klemens, Mikulits, Wolfgang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3519484/
https://www.ncbi.nlm.nih.gov/pubmed/23251436
http://dx.doi.org/10.1371/journal.pone.0051136
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author Gröger, Christian J.
Grubinger, Markus
Waldhör, Thomas
Vierlinger, Klemens
Mikulits, Wolfgang
author_facet Gröger, Christian J.
Grubinger, Markus
Waldhör, Thomas
Vierlinger, Klemens
Mikulits, Wolfgang
author_sort Gröger, Christian J.
collection PubMed
description The epithelial to mesenchymal transition (EMT) represents a crucial event during cancer progression and dissemination. EMT is the conversion of carcinoma cells from an epithelial to a mesenchymal phenotype that associates with a higher cell motility as well as enhanced chemoresistance and cancer stemness. Notably, EMT has been increasingly recognized as an early event of metastasis. Numerous gene expression studies (GES) have been conducted to obtain transcriptome signatures and marker genes to understand the regulatory mechanisms underlying EMT. Yet, no meta-analysis considering the multitude of GES of EMT has been performed to comprehensively elaborate the core genes in this process. Here we report the meta-analysis of 18 independent and published GES of EMT which focused on different cell types and treatment modalities. Computational analysis revealed clustering of GES according to the type of treatment rather than to cell type. GES of EMT induced via transforming growth factor-β and tumor necrosis factor-α treatment yielded uniformly defined clusters while GES of models with alternative EMT induction clustered in a more complex fashion. In addition, we identified those up- and downregulated genes which were shared between the multitude of GES. This core gene list includes well known EMT markers as well as novel genes so far not described in this process. Furthermore, several genes of the EMT-core gene list significantly correlated with impaired pathological complete response in breast cancer patients. In conclusion, this meta-analysis provides a comprehensive survey of available EMT expression signatures and shows fundamental insights into the mechanisms that are governing carcinoma progression.
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spelling pubmed-35194842012-12-18 Meta-Analysis of Gene Expression Signatures Defining the Epithelial to Mesenchymal Transition during Cancer Progression Gröger, Christian J. Grubinger, Markus Waldhör, Thomas Vierlinger, Klemens Mikulits, Wolfgang PLoS One Research Article The epithelial to mesenchymal transition (EMT) represents a crucial event during cancer progression and dissemination. EMT is the conversion of carcinoma cells from an epithelial to a mesenchymal phenotype that associates with a higher cell motility as well as enhanced chemoresistance and cancer stemness. Notably, EMT has been increasingly recognized as an early event of metastasis. Numerous gene expression studies (GES) have been conducted to obtain transcriptome signatures and marker genes to understand the regulatory mechanisms underlying EMT. Yet, no meta-analysis considering the multitude of GES of EMT has been performed to comprehensively elaborate the core genes in this process. Here we report the meta-analysis of 18 independent and published GES of EMT which focused on different cell types and treatment modalities. Computational analysis revealed clustering of GES according to the type of treatment rather than to cell type. GES of EMT induced via transforming growth factor-β and tumor necrosis factor-α treatment yielded uniformly defined clusters while GES of models with alternative EMT induction clustered in a more complex fashion. In addition, we identified those up- and downregulated genes which were shared between the multitude of GES. This core gene list includes well known EMT markers as well as novel genes so far not described in this process. Furthermore, several genes of the EMT-core gene list significantly correlated with impaired pathological complete response in breast cancer patients. In conclusion, this meta-analysis provides a comprehensive survey of available EMT expression signatures and shows fundamental insights into the mechanisms that are governing carcinoma progression. Public Library of Science 2012-12-10 /pmc/articles/PMC3519484/ /pubmed/23251436 http://dx.doi.org/10.1371/journal.pone.0051136 Text en © 2012 Gröger 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
Gröger, Christian J.
Grubinger, Markus
Waldhör, Thomas
Vierlinger, Klemens
Mikulits, Wolfgang
Meta-Analysis of Gene Expression Signatures Defining the Epithelial to Mesenchymal Transition during Cancer Progression
title Meta-Analysis of Gene Expression Signatures Defining the Epithelial to Mesenchymal Transition during Cancer Progression
title_full Meta-Analysis of Gene Expression Signatures Defining the Epithelial to Mesenchymal Transition during Cancer Progression
title_fullStr Meta-Analysis of Gene Expression Signatures Defining the Epithelial to Mesenchymal Transition during Cancer Progression
title_full_unstemmed Meta-Analysis of Gene Expression Signatures Defining the Epithelial to Mesenchymal Transition during Cancer Progression
title_short Meta-Analysis of Gene Expression Signatures Defining the Epithelial to Mesenchymal Transition during Cancer Progression
title_sort meta-analysis of gene expression signatures defining the epithelial to mesenchymal transition during cancer progression
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3519484/
https://www.ncbi.nlm.nih.gov/pubmed/23251436
http://dx.doi.org/10.1371/journal.pone.0051136
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