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Genomics and prognosis analysis of epithelial-mesenchymal transition in colorectal cancer patients
BACKGROUND: The epithelial-mesenchymal transition (EMT) plays a pivotal role in various physiological processes, such as embryonic development, tissue morphogenesis, and wound healing. EMT also plays an important role in cancer invasion, metastasis, and chemoresistance. Additionally, EMT is partiall...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7686680/ https://www.ncbi.nlm.nih.gov/pubmed/33228590 http://dx.doi.org/10.1186/s12885-020-07615-5 |
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author | Zhang, Zizhen Zheng, Sheng Lin, Yifeng Sun, Jiawei Ding, Ning Chen, Jingyu Zhong, Jing Shi, Liuhong Xue, Meng |
author_facet | Zhang, Zizhen Zheng, Sheng Lin, Yifeng Sun, Jiawei Ding, Ning Chen, Jingyu Zhong, Jing Shi, Liuhong Xue, Meng |
author_sort | Zhang, Zizhen |
collection | PubMed |
description | BACKGROUND: The epithelial-mesenchymal transition (EMT) plays a pivotal role in various physiological processes, such as embryonic development, tissue morphogenesis, and wound healing. EMT also plays an important role in cancer invasion, metastasis, and chemoresistance. Additionally, EMT is partially responsible for chemoresistance in colorectal cancer (CRC). The aim of this research is to develop an EMT-based prognostic signature in CRC. METHODS: RNA-seq and microarray data, together with clinical information, were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. A total of 244 differentially expressed EMT-related genes (ERGs) were obtained by comparing the expression between normal and tumor tissues. An EMT-related signature of 11 genes was identified as crucially related to the overall survival (OS) of patients through univariate Cox proportional hazard analysis, least absolute shrinkage and selection operator (LASSO), and Cox regression analysis. Finally, we established a clinical nomogram to predict the survival possibility of CRC patients by integrating clinical characteristics and the EMT-related gene signature. RESULTS: Two hundred and forty-four differentially expressed ERGs and their enriched pathways were confirmed. Significant enrichment analysis revealed that EMT-related signaling pathway genes were highly related to CRC. Kaplan-Meier analysis revealed that the 11-EMT signature could significantly distinguish high- and low-risk patients in both TCGA and GEO CRC cohorts. In addition, the calibration curves verified fine concordance between the nomogram prediction model and actual observation. CONCLUSION: We developed a novel EMT-related gene signature for the prognosis prediction of CRC patients, which could improve the individualized outcome prediction in CRC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-020-07615-5. |
format | Online Article Text |
id | pubmed-7686680 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-76866802020-11-25 Genomics and prognosis analysis of epithelial-mesenchymal transition in colorectal cancer patients Zhang, Zizhen Zheng, Sheng Lin, Yifeng Sun, Jiawei Ding, Ning Chen, Jingyu Zhong, Jing Shi, Liuhong Xue, Meng BMC Cancer Research Article BACKGROUND: The epithelial-mesenchymal transition (EMT) plays a pivotal role in various physiological processes, such as embryonic development, tissue morphogenesis, and wound healing. EMT also plays an important role in cancer invasion, metastasis, and chemoresistance. Additionally, EMT is partially responsible for chemoresistance in colorectal cancer (CRC). The aim of this research is to develop an EMT-based prognostic signature in CRC. METHODS: RNA-seq and microarray data, together with clinical information, were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. A total of 244 differentially expressed EMT-related genes (ERGs) were obtained by comparing the expression between normal and tumor tissues. An EMT-related signature of 11 genes was identified as crucially related to the overall survival (OS) of patients through univariate Cox proportional hazard analysis, least absolute shrinkage and selection operator (LASSO), and Cox regression analysis. Finally, we established a clinical nomogram to predict the survival possibility of CRC patients by integrating clinical characteristics and the EMT-related gene signature. RESULTS: Two hundred and forty-four differentially expressed ERGs and their enriched pathways were confirmed. Significant enrichment analysis revealed that EMT-related signaling pathway genes were highly related to CRC. Kaplan-Meier analysis revealed that the 11-EMT signature could significantly distinguish high- and low-risk patients in both TCGA and GEO CRC cohorts. In addition, the calibration curves verified fine concordance between the nomogram prediction model and actual observation. CONCLUSION: We developed a novel EMT-related gene signature for the prognosis prediction of CRC patients, which could improve the individualized outcome prediction in CRC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-020-07615-5. BioMed Central 2020-11-23 /pmc/articles/PMC7686680/ /pubmed/33228590 http://dx.doi.org/10.1186/s12885-020-07615-5 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data. |
spellingShingle | Research Article Zhang, Zizhen Zheng, Sheng Lin, Yifeng Sun, Jiawei Ding, Ning Chen, Jingyu Zhong, Jing Shi, Liuhong Xue, Meng Genomics and prognosis analysis of epithelial-mesenchymal transition in colorectal cancer patients |
title | Genomics and prognosis analysis of epithelial-mesenchymal transition in colorectal cancer patients |
title_full | Genomics and prognosis analysis of epithelial-mesenchymal transition in colorectal cancer patients |
title_fullStr | Genomics and prognosis analysis of epithelial-mesenchymal transition in colorectal cancer patients |
title_full_unstemmed | Genomics and prognosis analysis of epithelial-mesenchymal transition in colorectal cancer patients |
title_short | Genomics and prognosis analysis of epithelial-mesenchymal transition in colorectal cancer patients |
title_sort | genomics and prognosis analysis of epithelial-mesenchymal transition in colorectal cancer patients |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7686680/ https://www.ncbi.nlm.nih.gov/pubmed/33228590 http://dx.doi.org/10.1186/s12885-020-07615-5 |
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