Construction of Protein-related Risk Score Model in Bladder Urothelial Carcinoma

Background. Though there are several prognostic models, there is no protein-related prognostic model. The aim of this study is to identify possible prognostic-related proteins in bladder urothelial carcinoma and to try to predict the prognosis of bladder urothelial carcinoma based on these proteins....

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Main Authors: Qizhan Luo, Xiaobo Zhang
Format: Article
Language:English
Published: Hindawi Limited 2020-01-01
Series:BioMed Research International
Online Access:http://dx.doi.org/10.1155/2020/7147824
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spelling doaj-b1452817d2c749b6992868f517249b292020-11-25T03:50:06ZengHindawi LimitedBioMed Research International2314-61332314-61412020-01-01202010.1155/2020/71478247147824Construction of Protein-related Risk Score Model in Bladder Urothelial CarcinomaQizhan Luo0Xiaobo Zhang1Xiangya International Medical Center, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, ChinaXiangya International Medical Center, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, ChinaBackground. Though there are several prognostic models, there is no protein-related prognostic model. The aim of this study is to identify possible prognostic-related proteins in bladder urothelial carcinoma and to try to predict the prognosis of bladder urothelial carcinoma based on these proteins. Methods. Profile data and corresponding clinical traits were obtained from The Cancer Proteome Atlas (TCPA) and The Cancer Genome Atlas (TCGA) expression. Survival-associated protein in bladder urothelial carcinoma patients were estimated with Kaplan-Meier (KM) test and COX regression analysis. The potential molecular mechanisms and properties of these bladder urothelial carcinoma-specific proteins were also explored with the help of computational skills. The risk score model was validated in different clinical traits. Sankey diagram representation is for protein correlation. A new prognostic-related risk model based on proteins was developed by using multivariable COX analysis. Next, the alteration of the corresponding genes to the 6 prognostic-related proteins was analyzed. Finally, the relation between the corresponding genes and the immune infiltration was analyzed using the TIMER. Results. Six proteins were identified to be associated with the prognosis of bladder urothelial carcinoma. A prognostic signature based on proteins (BECLIN, EGFR, PKCALPHA, SRC, ANNEXIN1, and AXL) performed moderately in prognostic predictions. The alteration of corresponding genes was in 31(24%) sequenced cases. ANXA1, AXL, and EGFR were positively related to CD8+ T cell. Conclusion. Our results screened six proteins of clinical significance. The importance of a personalized protein signature model in the recognition, surveillance. The abnormal expression of six prognostic-related proteins may be caused by corresponding gene alteration. Furthermore, these proteins may affect survival via the immune infiltration.http://dx.doi.org/10.1155/2020/7147824
collection DOAJ
language English
format Article
sources DOAJ
author Qizhan Luo
Xiaobo Zhang
spellingShingle Qizhan Luo
Xiaobo Zhang
Construction of Protein-related Risk Score Model in Bladder Urothelial Carcinoma
BioMed Research International
author_facet Qizhan Luo
Xiaobo Zhang
author_sort Qizhan Luo
title Construction of Protein-related Risk Score Model in Bladder Urothelial Carcinoma
title_short Construction of Protein-related Risk Score Model in Bladder Urothelial Carcinoma
title_full Construction of Protein-related Risk Score Model in Bladder Urothelial Carcinoma
title_fullStr Construction of Protein-related Risk Score Model in Bladder Urothelial Carcinoma
title_full_unstemmed Construction of Protein-related Risk Score Model in Bladder Urothelial Carcinoma
title_sort construction of protein-related risk score model in bladder urothelial carcinoma
publisher Hindawi Limited
series BioMed Research International
issn 2314-6133
2314-6141
publishDate 2020-01-01
description Background. Though there are several prognostic models, there is no protein-related prognostic model. The aim of this study is to identify possible prognostic-related proteins in bladder urothelial carcinoma and to try to predict the prognosis of bladder urothelial carcinoma based on these proteins. Methods. Profile data and corresponding clinical traits were obtained from The Cancer Proteome Atlas (TCPA) and The Cancer Genome Atlas (TCGA) expression. Survival-associated protein in bladder urothelial carcinoma patients were estimated with Kaplan-Meier (KM) test and COX regression analysis. The potential molecular mechanisms and properties of these bladder urothelial carcinoma-specific proteins were also explored with the help of computational skills. The risk score model was validated in different clinical traits. Sankey diagram representation is for protein correlation. A new prognostic-related risk model based on proteins was developed by using multivariable COX analysis. Next, the alteration of the corresponding genes to the 6 prognostic-related proteins was analyzed. Finally, the relation between the corresponding genes and the immune infiltration was analyzed using the TIMER. Results. Six proteins were identified to be associated with the prognosis of bladder urothelial carcinoma. A prognostic signature based on proteins (BECLIN, EGFR, PKCALPHA, SRC, ANNEXIN1, and AXL) performed moderately in prognostic predictions. The alteration of corresponding genes was in 31(24%) sequenced cases. ANXA1, AXL, and EGFR were positively related to CD8+ T cell. Conclusion. Our results screened six proteins of clinical significance. The importance of a personalized protein signature model in the recognition, surveillance. The abnormal expression of six prognostic-related proteins may be caused by corresponding gene alteration. Furthermore, these proteins may affect survival via the immune infiltration.
url http://dx.doi.org/10.1155/2020/7147824
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AT xiaobozhang constructionofproteinrelatedriskscoremodelinbladderurothelialcarcinoma
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