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A Novel Three-Gene Model Predicts Prognosis and Therapeutic Sensitivity in Esophageal Squamous Cell Carcinoma

To precisely predict the clinical outcome and determine the optimal treatment options for patients with esophageal squamous cell carcinoma (ESCC) remains challenging. Prognostic models based on multiple molecular markers of tumors have been shown to have superiority over the use of single biomarkers...

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Autores principales: Zeng, Fa-Min, He, Jian-Zhong, Wang, Shao-Hong, Liu, De-kai, Xu, Xiu-E., Wu, Jian-Yi, Li, En-Min, Xu, Li-Yan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6899311/
https://www.ncbi.nlm.nih.gov/pubmed/31886273
http://dx.doi.org/10.1155/2019/9828637
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author Zeng, Fa-Min
He, Jian-Zhong
Wang, Shao-Hong
Liu, De-kai
Xu, Xiu-E.
Wu, Jian-Yi
Li, En-Min
Xu, Li-Yan
author_facet Zeng, Fa-Min
He, Jian-Zhong
Wang, Shao-Hong
Liu, De-kai
Xu, Xiu-E.
Wu, Jian-Yi
Li, En-Min
Xu, Li-Yan
author_sort Zeng, Fa-Min
collection PubMed
description To precisely predict the clinical outcome and determine the optimal treatment options for patients with esophageal squamous cell carcinoma (ESCC) remains challenging. Prognostic models based on multiple molecular markers of tumors have been shown to have superiority over the use of single biomarkers. Our previous studies have identified the crucial role of ezrin in ESCC progression, which prompted us to hypothesize that ezrin-associated proteins contribute to the pathobiology of ESCC. Herein, we explored the clinical value of a molecular model constructed based on ezrin-associated proteins in ESCC patients. We revealed that the ezrin-associated proteins (MYC, PDIA3, and ITGA5B1) correlated with the overall survival (OS) and disease-free survival (DFS) of patients with ESCC. High expression of MYC was associated with advanced pTNM-stage (P=0.011), and PDIA3 and ITGA5B1 were correlated with both lymph node metastasis (PDIA3: P < 0.001; ITGA5B1: P=0.001) and pTNM-stage (PDIA3: P=0.001; ITGA5B1: P=0.009). Furthermore, we found that, compared with the current TNM staging system, the molecular model elicited from the expression of MYC, PDIA3, and ITGA5B1 shows higher accuracy in predicting OS (P < 0.001) or DFS (P < 0.001) in ESCC patients. Moreover, ROC and regression analysis demonstrated that this model was an independent predictor for OS and DFS, which could also help determine a subgroup of ESCC patients that may benefit from chemoradiotherapy. In conclusion, our study has identified a novel molecular prognosis model, which may serve as a complement for current clinical risk stratification approaches and provide potential therapeutic targets for ESCC treatment.
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spelling pubmed-68993112019-12-29 A Novel Three-Gene Model Predicts Prognosis and Therapeutic Sensitivity in Esophageal Squamous Cell Carcinoma Zeng, Fa-Min He, Jian-Zhong Wang, Shao-Hong Liu, De-kai Xu, Xiu-E. Wu, Jian-Yi Li, En-Min Xu, Li-Yan Biomed Res Int Research Article To precisely predict the clinical outcome and determine the optimal treatment options for patients with esophageal squamous cell carcinoma (ESCC) remains challenging. Prognostic models based on multiple molecular markers of tumors have been shown to have superiority over the use of single biomarkers. Our previous studies have identified the crucial role of ezrin in ESCC progression, which prompted us to hypothesize that ezrin-associated proteins contribute to the pathobiology of ESCC. Herein, we explored the clinical value of a molecular model constructed based on ezrin-associated proteins in ESCC patients. We revealed that the ezrin-associated proteins (MYC, PDIA3, and ITGA5B1) correlated with the overall survival (OS) and disease-free survival (DFS) of patients with ESCC. High expression of MYC was associated with advanced pTNM-stage (P=0.011), and PDIA3 and ITGA5B1 were correlated with both lymph node metastasis (PDIA3: P < 0.001; ITGA5B1: P=0.001) and pTNM-stage (PDIA3: P=0.001; ITGA5B1: P=0.009). Furthermore, we found that, compared with the current TNM staging system, the molecular model elicited from the expression of MYC, PDIA3, and ITGA5B1 shows higher accuracy in predicting OS (P < 0.001) or DFS (P < 0.001) in ESCC patients. Moreover, ROC and regression analysis demonstrated that this model was an independent predictor for OS and DFS, which could also help determine a subgroup of ESCC patients that may benefit from chemoradiotherapy. In conclusion, our study has identified a novel molecular prognosis model, which may serve as a complement for current clinical risk stratification approaches and provide potential therapeutic targets for ESCC treatment. Hindawi 2019-11-25 /pmc/articles/PMC6899311/ /pubmed/31886273 http://dx.doi.org/10.1155/2019/9828637 Text en Copyright © 2019 Fa-Min Zeng et al. http://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
Zeng, Fa-Min
He, Jian-Zhong
Wang, Shao-Hong
Liu, De-kai
Xu, Xiu-E.
Wu, Jian-Yi
Li, En-Min
Xu, Li-Yan
A Novel Three-Gene Model Predicts Prognosis and Therapeutic Sensitivity in Esophageal Squamous Cell Carcinoma
title A Novel Three-Gene Model Predicts Prognosis and Therapeutic Sensitivity in Esophageal Squamous Cell Carcinoma
title_full A Novel Three-Gene Model Predicts Prognosis and Therapeutic Sensitivity in Esophageal Squamous Cell Carcinoma
title_fullStr A Novel Three-Gene Model Predicts Prognosis and Therapeutic Sensitivity in Esophageal Squamous Cell Carcinoma
title_full_unstemmed A Novel Three-Gene Model Predicts Prognosis and Therapeutic Sensitivity in Esophageal Squamous Cell Carcinoma
title_short A Novel Three-Gene Model Predicts Prognosis and Therapeutic Sensitivity in Esophageal Squamous Cell Carcinoma
title_sort novel three-gene model predicts prognosis and therapeutic sensitivity in esophageal squamous cell carcinoma
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6899311/
https://www.ncbi.nlm.nih.gov/pubmed/31886273
http://dx.doi.org/10.1155/2019/9828637
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