Cargando…
Identification of Epithelial-Mesenchymal Transition- (EMT-) Related LncRNA for Prognostic Prediction and Risk Stratification in Esophageal Squamous Cell Carcinoma
BACKGROUND: Epithelial-mesenchymal transition (EMT) is significantly associated with the invasion and development of esophageal squamous cell carcinoma (ESCC). However, the importance of EMT-related long noncoding RNA (lncRNA) is little known in ESCC. METHODS: GSE53624 (N = 119) and GSE53622 (N = 60...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8548124/ https://www.ncbi.nlm.nih.gov/pubmed/34712369 http://dx.doi.org/10.1155/2021/5340240 |
_version_ | 1784590506025549824 |
---|---|
author | Wang, Peipei Chen, Yueyun Zheng, Yue Fu, Yang Ding, Zhenyu |
author_facet | Wang, Peipei Chen, Yueyun Zheng, Yue Fu, Yang Ding, Zhenyu |
author_sort | Wang, Peipei |
collection | PubMed |
description | BACKGROUND: Epithelial-mesenchymal transition (EMT) is significantly associated with the invasion and development of esophageal squamous cell carcinoma (ESCC). However, the importance of EMT-related long noncoding RNA (lncRNA) is little known in ESCC. METHODS: GSE53624 (N = 119) and GSE53622 (N = 60) datasets retrieved from the Gene Expression Omnibus (GEO) database were used as training and external validation cohorts, respectively. GSE53624 and GSE53622 datasets were all sampled from China. Then, the prognostic value of EMT-related lncRNA was comprehensively investigated by weighted coexpression network analysis (WGCNA) and COX regression model. RESULTS: High expression of PLA2G4E-AS1, AC063976.1, and LINC01592 significantly correlated with the favorable overall survival (OS) of ESCC patients, and LINC01592 had the greatest contribution to OS. Importantly, ESCC patients were divided into low- and high-risk groups based on the optimal cut-off value of risk score estimated by the multivariate COX regression model of these three lncRNA. Patients with high risk had a shorter OS rate and restricted mean survival time (RMST) than those with low risk. Moreover, univariate and multivariate COX regression revealed that risk stratification, age, and TNM were independent prognostic predictors, which were used to construct a nomogram model for individualized and visualized prognosis prediction of ESCC patients. The calibration curves and time-dependent ROC curves in the training and validation cohorts suggested that the nomogram model had a good performance. Interestingly, clear trends indicated that risk score positively correlated with tumor microenvironment (TME) scores and immune checkpoints TIGIT, CTLA4, and BTLA. In addition, the Kyoto Encyclopedia of Genes and Genomes (KEGG) showed that PLA2G4E-AS1, AC063976.1, and LINC01592 were primarily associated with TNF signaling pathway, NF-kappa B signaling pathway, and ECM-receptor interaction. CONCLUSION: We developed EMT-related lncRNA PLA2G4E-AS1, AC063976.1, and LINC01592 for prognostic prediction and risk stratification of Chinese ESCC patients, which might provide deep insight for personalized prognosis prediction in Chinese ESCC patients and be potential biomarkers for designing novel therapy. |
format | Online Article Text |
id | pubmed-8548124 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-85481242021-10-27 Identification of Epithelial-Mesenchymal Transition- (EMT-) Related LncRNA for Prognostic Prediction and Risk Stratification in Esophageal Squamous Cell Carcinoma Wang, Peipei Chen, Yueyun Zheng, Yue Fu, Yang Ding, Zhenyu Dis Markers Research Article BACKGROUND: Epithelial-mesenchymal transition (EMT) is significantly associated with the invasion and development of esophageal squamous cell carcinoma (ESCC). However, the importance of EMT-related long noncoding RNA (lncRNA) is little known in ESCC. METHODS: GSE53624 (N = 119) and GSE53622 (N = 60) datasets retrieved from the Gene Expression Omnibus (GEO) database were used as training and external validation cohorts, respectively. GSE53624 and GSE53622 datasets were all sampled from China. Then, the prognostic value of EMT-related lncRNA was comprehensively investigated by weighted coexpression network analysis (WGCNA) and COX regression model. RESULTS: High expression of PLA2G4E-AS1, AC063976.1, and LINC01592 significantly correlated with the favorable overall survival (OS) of ESCC patients, and LINC01592 had the greatest contribution to OS. Importantly, ESCC patients were divided into low- and high-risk groups based on the optimal cut-off value of risk score estimated by the multivariate COX regression model of these three lncRNA. Patients with high risk had a shorter OS rate and restricted mean survival time (RMST) than those with low risk. Moreover, univariate and multivariate COX regression revealed that risk stratification, age, and TNM were independent prognostic predictors, which were used to construct a nomogram model for individualized and visualized prognosis prediction of ESCC patients. The calibration curves and time-dependent ROC curves in the training and validation cohorts suggested that the nomogram model had a good performance. Interestingly, clear trends indicated that risk score positively correlated with tumor microenvironment (TME) scores and immune checkpoints TIGIT, CTLA4, and BTLA. In addition, the Kyoto Encyclopedia of Genes and Genomes (KEGG) showed that PLA2G4E-AS1, AC063976.1, and LINC01592 were primarily associated with TNF signaling pathway, NF-kappa B signaling pathway, and ECM-receptor interaction. CONCLUSION: We developed EMT-related lncRNA PLA2G4E-AS1, AC063976.1, and LINC01592 for prognostic prediction and risk stratification of Chinese ESCC patients, which might provide deep insight for personalized prognosis prediction in Chinese ESCC patients and be potential biomarkers for designing novel therapy. Hindawi 2021-10-19 /pmc/articles/PMC8548124/ /pubmed/34712369 http://dx.doi.org/10.1155/2021/5340240 Text en Copyright © 2021 Peipei Wang et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Wang, Peipei Chen, Yueyun Zheng, Yue Fu, Yang Ding, Zhenyu Identification of Epithelial-Mesenchymal Transition- (EMT-) Related LncRNA for Prognostic Prediction and Risk Stratification in Esophageal Squamous Cell Carcinoma |
title | Identification of Epithelial-Mesenchymal Transition- (EMT-) Related LncRNA for Prognostic Prediction and Risk Stratification in Esophageal Squamous Cell Carcinoma |
title_full | Identification of Epithelial-Mesenchymal Transition- (EMT-) Related LncRNA for Prognostic Prediction and Risk Stratification in Esophageal Squamous Cell Carcinoma |
title_fullStr | Identification of Epithelial-Mesenchymal Transition- (EMT-) Related LncRNA for Prognostic Prediction and Risk Stratification in Esophageal Squamous Cell Carcinoma |
title_full_unstemmed | Identification of Epithelial-Mesenchymal Transition- (EMT-) Related LncRNA for Prognostic Prediction and Risk Stratification in Esophageal Squamous Cell Carcinoma |
title_short | Identification of Epithelial-Mesenchymal Transition- (EMT-) Related LncRNA for Prognostic Prediction and Risk Stratification in Esophageal Squamous Cell Carcinoma |
title_sort | identification of epithelial-mesenchymal transition- (emt-) related lncrna for prognostic prediction and risk stratification in esophageal squamous cell carcinoma |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8548124/ https://www.ncbi.nlm.nih.gov/pubmed/34712369 http://dx.doi.org/10.1155/2021/5340240 |
work_keys_str_mv | AT wangpeipei identificationofepithelialmesenchymaltransitionemtrelatedlncrnaforprognosticpredictionandriskstratificationinesophagealsquamouscellcarcinoma AT chenyueyun identificationofepithelialmesenchymaltransitionemtrelatedlncrnaforprognosticpredictionandriskstratificationinesophagealsquamouscellcarcinoma AT zhengyue identificationofepithelialmesenchymaltransitionemtrelatedlncrnaforprognosticpredictionandriskstratificationinesophagealsquamouscellcarcinoma AT fuyang identificationofepithelialmesenchymaltransitionemtrelatedlncrnaforprognosticpredictionandriskstratificationinesophagealsquamouscellcarcinoma AT dingzhenyu identificationofepithelialmesenchymaltransitionemtrelatedlncrnaforprognosticpredictionandriskstratificationinesophagealsquamouscellcarcinoma |