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Global transcriptomic analysis identifies SERPINE1 as a prognostic biomarker associated with epithelial-to-mesenchymal transition in gastric cancer
BACKGROUND: The plasminogen activation system plays a pivotal role in regulating tumorigenesis. In this work, we aim to identify key regulators of plasminogen activation associated with tumorigenesis and explore potential mechanisms in gastric cancer (GC). METHODS: Gene profiling datasets were extra...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6563800/ https://www.ncbi.nlm.nih.gov/pubmed/31218131 http://dx.doi.org/10.7717/peerj.7091 |
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author | Xu, Bodong Bai, Zhigang Yin, Jie Zhang, Zhongtao |
author_facet | Xu, Bodong Bai, Zhigang Yin, Jie Zhang, Zhongtao |
author_sort | Xu, Bodong |
collection | PubMed |
description | BACKGROUND: The plasminogen activation system plays a pivotal role in regulating tumorigenesis. In this work, we aim to identify key regulators of plasminogen activation associated with tumorigenesis and explore potential mechanisms in gastric cancer (GC). METHODS: Gene profiling datasets were extracted from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were screened for and obtained by the GEO2R tool. The Database for Annotation, Visualization and Integrated Discovery was used for GO and KEGG enrichment analysis. Gene set enrichment analysis (GSEA) was performed to verify molecular signatures and pathways among The Cancer Genome Atlas or GEO datasets. Correlations between SERPINE1 and markers of epithelial-to-mesenchymal transition (EMT) were analyzed using the GEPIA database and quantitative real-time PCR (qRT-PCR). Interactive networks of selected genes were built by STRING and Cytoscape software. Finally, selected genes were verified with the Kaplan–Meier (KM) plotter database. RESULTS: A total of 104 overlapped upregulated and 61 downregulated DEGs were obtained. Multiple GO and KEGG terms associated with the extracellular matrix were enriched among the DEGs. SERPINE1 was identified as the only regulator of angiogenesis and the plasminogen activator system among the DEGs. A high level of SERPINE1 was associated with a poor prognosis in GC. GSEA analysis showed a strong correlation between SERPINE1 and EMT, which was also confirmed with the GEPIA database and qRT-PCR validation. FN1, TIMP1, MMP2, and SPARC were correlated with SERPINE1.The KM plotter database showed that an overexpression of these genes correlated with a shorter survival time in GC patients. CONCLUSIONS: In conclusion, SERPINE1 is a potent biomarker associated with EMT and a poor prognosis in GC. Furthermore, FN1, TIMP1, MMP2, and SPARC are correlated with SERPINE1 and may serve as therapeutic targets in reversing EMT in GC. |
format | Online Article Text |
id | pubmed-6563800 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-65638002019-06-19 Global transcriptomic analysis identifies SERPINE1 as a prognostic biomarker associated with epithelial-to-mesenchymal transition in gastric cancer Xu, Bodong Bai, Zhigang Yin, Jie Zhang, Zhongtao PeerJ Bioinformatics BACKGROUND: The plasminogen activation system plays a pivotal role in regulating tumorigenesis. In this work, we aim to identify key regulators of plasminogen activation associated with tumorigenesis and explore potential mechanisms in gastric cancer (GC). METHODS: Gene profiling datasets were extracted from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were screened for and obtained by the GEO2R tool. The Database for Annotation, Visualization and Integrated Discovery was used for GO and KEGG enrichment analysis. Gene set enrichment analysis (GSEA) was performed to verify molecular signatures and pathways among The Cancer Genome Atlas or GEO datasets. Correlations between SERPINE1 and markers of epithelial-to-mesenchymal transition (EMT) were analyzed using the GEPIA database and quantitative real-time PCR (qRT-PCR). Interactive networks of selected genes were built by STRING and Cytoscape software. Finally, selected genes were verified with the Kaplan–Meier (KM) plotter database. RESULTS: A total of 104 overlapped upregulated and 61 downregulated DEGs were obtained. Multiple GO and KEGG terms associated with the extracellular matrix were enriched among the DEGs. SERPINE1 was identified as the only regulator of angiogenesis and the plasminogen activator system among the DEGs. A high level of SERPINE1 was associated with a poor prognosis in GC. GSEA analysis showed a strong correlation between SERPINE1 and EMT, which was also confirmed with the GEPIA database and qRT-PCR validation. FN1, TIMP1, MMP2, and SPARC were correlated with SERPINE1.The KM plotter database showed that an overexpression of these genes correlated with a shorter survival time in GC patients. CONCLUSIONS: In conclusion, SERPINE1 is a potent biomarker associated with EMT and a poor prognosis in GC. Furthermore, FN1, TIMP1, MMP2, and SPARC are correlated with SERPINE1 and may serve as therapeutic targets in reversing EMT in GC. PeerJ Inc. 2019-06-10 /pmc/articles/PMC6563800/ /pubmed/31218131 http://dx.doi.org/10.7717/peerj.7091 Text en © 2019 Xu 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 (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Bioinformatics Xu, Bodong Bai, Zhigang Yin, Jie Zhang, Zhongtao Global transcriptomic analysis identifies SERPINE1 as a prognostic biomarker associated with epithelial-to-mesenchymal transition in gastric cancer |
title | Global transcriptomic analysis identifies SERPINE1 as a prognostic biomarker associated with epithelial-to-mesenchymal transition in gastric cancer |
title_full | Global transcriptomic analysis identifies SERPINE1 as a prognostic biomarker associated with epithelial-to-mesenchymal transition in gastric cancer |
title_fullStr | Global transcriptomic analysis identifies SERPINE1 as a prognostic biomarker associated with epithelial-to-mesenchymal transition in gastric cancer |
title_full_unstemmed | Global transcriptomic analysis identifies SERPINE1 as a prognostic biomarker associated with epithelial-to-mesenchymal transition in gastric cancer |
title_short | Global transcriptomic analysis identifies SERPINE1 as a prognostic biomarker associated with epithelial-to-mesenchymal transition in gastric cancer |
title_sort | global transcriptomic analysis identifies serpine1 as a prognostic biomarker associated with epithelial-to-mesenchymal transition in gastric cancer |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6563800/ https://www.ncbi.nlm.nih.gov/pubmed/31218131 http://dx.doi.org/10.7717/peerj.7091 |
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