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Identifying global expression patterns and key regulators in epithelial to mesenchymal transition through multi-study integration

BACKGROUND: Epithelial to mesenchymal transition (EMT) is the process by which stationary epithelial cells transdifferentiate to mesenchymal cells with increased motility. EMT is integral in early stages of development and wound healing. Studies have shown that EMT could be a critical early event in...

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Autores principales: Parsana, Princy, Amend, Sarah R., Hernandez, James, Pienta, Kenneth J., Battle, Alexis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5485747/
https://www.ncbi.nlm.nih.gov/pubmed/28651527
http://dx.doi.org/10.1186/s12885-017-3413-3
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author Parsana, Princy
Amend, Sarah R.
Hernandez, James
Pienta, Kenneth J.
Battle, Alexis
author_facet Parsana, Princy
Amend, Sarah R.
Hernandez, James
Pienta, Kenneth J.
Battle, Alexis
author_sort Parsana, Princy
collection PubMed
description BACKGROUND: Epithelial to mesenchymal transition (EMT) is the process by which stationary epithelial cells transdifferentiate to mesenchymal cells with increased motility. EMT is integral in early stages of development and wound healing. Studies have shown that EMT could be a critical early event in tumor metastasis that is involved in acquisition of migratory and invasive properties in multiple carcinomas. METHODS: In this study, we used 15 published gene expression microarray datasets from Gene Expression Omnibus (GEO) that represent 12 cell lines from 6 cancer types across 95 observations (45 unique samples and 50 replicates) with different modes of induction of EMT or the reverse transition, mesenchymal to epithelial transition (MET). We integrated multiple gene expression datasets while considering study differences, batch effects, and noise in gene expression measurements. A universal differential EMT gene list was obtained by normalizing and correcting the data using four approaches, computing differential expression from each, and identifying a consensus ranking. We confirmed our discovery of novel EMT genes at mRNA and protein levels in an in vitro EMT model of prostate cancer – PC3 epi, EMT and Taxol resistant cell lines. We validate our discovery of C1orf116 as a novel EMT regulator by siRNA knockdown of C1orf116 in PC3 epithelial cells. RESULTS: Among differentially expressed genes, we found known epithelial and mesenchymal marker genes such as CDH1 and ZEB1. Additionally, we discovered genes known in a subset of carcinomas that were unknown in prostate cancer. This included epithelial specific LSR and S100A14 and mesenchymal specific DPYSL3. Furthermore, we also discovered novel EMT genes including a poorly-characterized gene C1orf116. We show that decreased expression of C1orf116 is associated with poor prognosis in lung and prostate cancer patients. We demonstrate that knockdown of C1orf116 expression induced expression of mesenchymal genes in epithelial prostate cancer cell line PC3-epi cells, suggesting it as a candidate driver of the epithelial phenotype. CONCLUSIONS: This comprehensive approach of statistical analysis and functional validation identified global expression patterns in EMT and candidate regulatory genes, thereby both extending current knowledge and identifying novel drivers of EMT. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12885-017-3413-3) contains supplementary material, which is available to authorized users.
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spelling pubmed-54857472017-07-03 Identifying global expression patterns and key regulators in epithelial to mesenchymal transition through multi-study integration Parsana, Princy Amend, Sarah R. Hernandez, James Pienta, Kenneth J. Battle, Alexis BMC Cancer Research Article BACKGROUND: Epithelial to mesenchymal transition (EMT) is the process by which stationary epithelial cells transdifferentiate to mesenchymal cells with increased motility. EMT is integral in early stages of development and wound healing. Studies have shown that EMT could be a critical early event in tumor metastasis that is involved in acquisition of migratory and invasive properties in multiple carcinomas. METHODS: In this study, we used 15 published gene expression microarray datasets from Gene Expression Omnibus (GEO) that represent 12 cell lines from 6 cancer types across 95 observations (45 unique samples and 50 replicates) with different modes of induction of EMT or the reverse transition, mesenchymal to epithelial transition (MET). We integrated multiple gene expression datasets while considering study differences, batch effects, and noise in gene expression measurements. A universal differential EMT gene list was obtained by normalizing and correcting the data using four approaches, computing differential expression from each, and identifying a consensus ranking. We confirmed our discovery of novel EMT genes at mRNA and protein levels in an in vitro EMT model of prostate cancer – PC3 epi, EMT and Taxol resistant cell lines. We validate our discovery of C1orf116 as a novel EMT regulator by siRNA knockdown of C1orf116 in PC3 epithelial cells. RESULTS: Among differentially expressed genes, we found known epithelial and mesenchymal marker genes such as CDH1 and ZEB1. Additionally, we discovered genes known in a subset of carcinomas that were unknown in prostate cancer. This included epithelial specific LSR and S100A14 and mesenchymal specific DPYSL3. Furthermore, we also discovered novel EMT genes including a poorly-characterized gene C1orf116. We show that decreased expression of C1orf116 is associated with poor prognosis in lung and prostate cancer patients. We demonstrate that knockdown of C1orf116 expression induced expression of mesenchymal genes in epithelial prostate cancer cell line PC3-epi cells, suggesting it as a candidate driver of the epithelial phenotype. CONCLUSIONS: This comprehensive approach of statistical analysis and functional validation identified global expression patterns in EMT and candidate regulatory genes, thereby both extending current knowledge and identifying novel drivers of EMT. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12885-017-3413-3) contains supplementary material, which is available to authorized users. BioMed Central 2017-06-26 /pmc/articles/PMC5485747/ /pubmed/28651527 http://dx.doi.org/10.1186/s12885-017-3413-3 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Parsana, Princy
Amend, Sarah R.
Hernandez, James
Pienta, Kenneth J.
Battle, Alexis
Identifying global expression patterns and key regulators in epithelial to mesenchymal transition through multi-study integration
title Identifying global expression patterns and key regulators in epithelial to mesenchymal transition through multi-study integration
title_full Identifying global expression patterns and key regulators in epithelial to mesenchymal transition through multi-study integration
title_fullStr Identifying global expression patterns and key regulators in epithelial to mesenchymal transition through multi-study integration
title_full_unstemmed Identifying global expression patterns and key regulators in epithelial to mesenchymal transition through multi-study integration
title_short Identifying global expression patterns and key regulators in epithelial to mesenchymal transition through multi-study integration
title_sort identifying global expression patterns and key regulators in epithelial to mesenchymal transition through multi-study integration
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5485747/
https://www.ncbi.nlm.nih.gov/pubmed/28651527
http://dx.doi.org/10.1186/s12885-017-3413-3
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