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Construction of an RNA-Binding Protein-Related Prognostic Model for Pancreatic Adenocarcinoma Based on TCGA and GTEx Databases

Background: Recently, RNA-binding proteins (RBPs) were reported to interact with target mRNA to regulate gene posttranscriptional expression, and RBP-mediated RNA modification can regulate the expression and function of proto-oncogenes and tumor suppressor genes. We systematically analyzed the expre...

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Autores principales: Wen, Xin, Shao, Zhiying, Chen, Shuyi, Wang, Wei, Wang, Yan, Jiang, Jinghua, Ma, Qinggong, Zhang, Longzhen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7873872/
https://www.ncbi.nlm.nih.gov/pubmed/33584809
http://dx.doi.org/10.3389/fgene.2020.610350
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author Wen, Xin
Shao, Zhiying
Chen, Shuyi
Wang, Wei
Wang, Yan
Jiang, Jinghua
Ma, Qinggong
Zhang, Longzhen
author_facet Wen, Xin
Shao, Zhiying
Chen, Shuyi
Wang, Wei
Wang, Yan
Jiang, Jinghua
Ma, Qinggong
Zhang, Longzhen
author_sort Wen, Xin
collection PubMed
description Background: Recently, RNA-binding proteins (RBPs) were reported to interact with target mRNA to regulate gene posttranscriptional expression, and RBP-mediated RNA modification can regulate the expression and function of proto-oncogenes and tumor suppressor genes. We systematically analyzed the expression of RBPs in pancreatic adenocarcinoma (PAAD) and constructed an RBP-associated prognostic risk model. Methods: Gene expression data of normal pancreatic samples as well as PAAD samples were downloaded from TCGA-PAAD and GTEx databases. Wilcoxon test and univariate Cox analysis were, respectively, applied to screen differential expression RBPs (DE-RBPs) and prognostic-associated RBPs (pRBPs). Functional enrichment was analyzed by GO, KEGG, and GSEA. Protein–protein interaction (PPI) network was constructed by STRING online database. Modeling RBPs were selected by multivariate Cox analysis. Kaplan–Meier survival and Cox analysis were applied to evaluate the effects of risk score on the overall survival of PAAD patients. ROC curves and validation cohort were applied to verify the accuracy of the model. Nomogram was applied for predicting 1-, 3-, and 5-year overall survival (OS) of PAAD patients. At last, modeling RBPs were further analyzed to explore their differential expression, prognostic value, as well as enrichment pathways in PAAD. Results: RBPs (453) were differentially expressed in normal and tumor samples, besides, 28 of which were prognostic associated. DE-RBPs (453) are functionally associated with ribosome, ribonuclease, spliceosome, etc. Eight RBPs (PABPC1, PRPF6, OAS1, RBM5, LSM12, IPO7, FXR1, and RBM6) were identified to construct a prognostic risk model. Higher risk score not only predicted poor prognosis but also was an independent poor prognostic indicator, which was verified by ROC curves and validation cohort. Eight modeling RBPs were confirmed to be significantly differentially expressed between normal and tumor samples from RNA and protein level. Besides, all of eight RBPs were related with overall survival of PAAD patients. Conclusions: We successfully constructed an RBP-associated prognostic risk model in PAAD, which has a potential clinical application prospect.
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spelling pubmed-78738722021-02-11 Construction of an RNA-Binding Protein-Related Prognostic Model for Pancreatic Adenocarcinoma Based on TCGA and GTEx Databases Wen, Xin Shao, Zhiying Chen, Shuyi Wang, Wei Wang, Yan Jiang, Jinghua Ma, Qinggong Zhang, Longzhen Front Genet Genetics Background: Recently, RNA-binding proteins (RBPs) were reported to interact with target mRNA to regulate gene posttranscriptional expression, and RBP-mediated RNA modification can regulate the expression and function of proto-oncogenes and tumor suppressor genes. We systematically analyzed the expression of RBPs in pancreatic adenocarcinoma (PAAD) and constructed an RBP-associated prognostic risk model. Methods: Gene expression data of normal pancreatic samples as well as PAAD samples were downloaded from TCGA-PAAD and GTEx databases. Wilcoxon test and univariate Cox analysis were, respectively, applied to screen differential expression RBPs (DE-RBPs) and prognostic-associated RBPs (pRBPs). Functional enrichment was analyzed by GO, KEGG, and GSEA. Protein–protein interaction (PPI) network was constructed by STRING online database. Modeling RBPs were selected by multivariate Cox analysis. Kaplan–Meier survival and Cox analysis were applied to evaluate the effects of risk score on the overall survival of PAAD patients. ROC curves and validation cohort were applied to verify the accuracy of the model. Nomogram was applied for predicting 1-, 3-, and 5-year overall survival (OS) of PAAD patients. At last, modeling RBPs were further analyzed to explore their differential expression, prognostic value, as well as enrichment pathways in PAAD. Results: RBPs (453) were differentially expressed in normal and tumor samples, besides, 28 of which were prognostic associated. DE-RBPs (453) are functionally associated with ribosome, ribonuclease, spliceosome, etc. Eight RBPs (PABPC1, PRPF6, OAS1, RBM5, LSM12, IPO7, FXR1, and RBM6) were identified to construct a prognostic risk model. Higher risk score not only predicted poor prognosis but also was an independent poor prognostic indicator, which was verified by ROC curves and validation cohort. Eight modeling RBPs were confirmed to be significantly differentially expressed between normal and tumor samples from RNA and protein level. Besides, all of eight RBPs were related with overall survival of PAAD patients. Conclusions: We successfully constructed an RBP-associated prognostic risk model in PAAD, which has a potential clinical application prospect. Frontiers Media S.A. 2021-01-27 /pmc/articles/PMC7873872/ /pubmed/33584809 http://dx.doi.org/10.3389/fgene.2020.610350 Text en Copyright © 2021 Wen, Shao, Chen, Wang, Wang, Jiang, Ma and Zhang. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Wen, Xin
Shao, Zhiying
Chen, Shuyi
Wang, Wei
Wang, Yan
Jiang, Jinghua
Ma, Qinggong
Zhang, Longzhen
Construction of an RNA-Binding Protein-Related Prognostic Model for Pancreatic Adenocarcinoma Based on TCGA and GTEx Databases
title Construction of an RNA-Binding Protein-Related Prognostic Model for Pancreatic Adenocarcinoma Based on TCGA and GTEx Databases
title_full Construction of an RNA-Binding Protein-Related Prognostic Model for Pancreatic Adenocarcinoma Based on TCGA and GTEx Databases
title_fullStr Construction of an RNA-Binding Protein-Related Prognostic Model for Pancreatic Adenocarcinoma Based on TCGA and GTEx Databases
title_full_unstemmed Construction of an RNA-Binding Protein-Related Prognostic Model for Pancreatic Adenocarcinoma Based on TCGA and GTEx Databases
title_short Construction of an RNA-Binding Protein-Related Prognostic Model for Pancreatic Adenocarcinoma Based on TCGA and GTEx Databases
title_sort construction of an rna-binding protein-related prognostic model for pancreatic adenocarcinoma based on tcga and gtex databases
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7873872/
https://www.ncbi.nlm.nih.gov/pubmed/33584809
http://dx.doi.org/10.3389/fgene.2020.610350
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