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Effects of RNA Binding Proteins on the Prognosis and Malignant Progression in Prostate Cancer

Prostate cancer (PCa) is a common lethal malignancy in men. RNA binding proteins (RBPs) have been proven to regulate the biological processes of various tumors, but their roles in PCa remain less defined. In the present study, we used bioinformatics analysis to identify RBP genes with prognostic and...

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Autores principales: Hua, Xiaoliang, Ge, Shengdong, Chen, Juan, Zhang, Li, Tai, Sheng, Liang, Chaozhao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7606971/
https://www.ncbi.nlm.nih.gov/pubmed/33193734
http://dx.doi.org/10.3389/fgene.2020.591667
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author Hua, Xiaoliang
Ge, Shengdong
Chen, Juan
Zhang, Li
Tai, Sheng
Liang, Chaozhao
author_facet Hua, Xiaoliang
Ge, Shengdong
Chen, Juan
Zhang, Li
Tai, Sheng
Liang, Chaozhao
author_sort Hua, Xiaoliang
collection PubMed
description Prostate cancer (PCa) is a common lethal malignancy in men. RNA binding proteins (RBPs) have been proven to regulate the biological processes of various tumors, but their roles in PCa remain less defined. In the present study, we used bioinformatics analysis to identify RBP genes with prognostic and diagnostic values. A total of 59 differentially expressed RBPs in PCa were obtained, comprising 28 upregulated and 31 downregulated RBP genes, which may play important roles in PCa. Functional enrichment analyses showed that these RBPs were mainly involved in mRNA processing, RNA splicing, and regulation of RNA splicing. Additionally, we identified nine RBP genes (EXO1, PABPC1L, REXO2, MBNL2, MSI1, CTU1, MAEL, YBX2, and ESRP2) and their prognostic values by a protein–protein interaction network and Cox regression analyses. The expression of these nine RBPs was validated using immunohistochemical staining between the tumor and normal samples. Further, the associations between the expression of these nine RBPs and pathological T staging, Gleason score, and lymph node metastasis were evaluated. Moreover, these nine RBP genes showed good diagnostic values and could categorize the PCa patients into two clusters with different malignant phenotypes. Finally, we constructed a prognostic model based on these nine RBP genes and validated them using three external datasets. The model showed good efficiency in predicting patient survival and was independent of other clinical factors. Therefore, our model could be used as a supplement for clinical factors to predict patient prognosis and thereby improve patient survival.
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spelling pubmed-76069712020-11-13 Effects of RNA Binding Proteins on the Prognosis and Malignant Progression in Prostate Cancer Hua, Xiaoliang Ge, Shengdong Chen, Juan Zhang, Li Tai, Sheng Liang, Chaozhao Front Genet Genetics Prostate cancer (PCa) is a common lethal malignancy in men. RNA binding proteins (RBPs) have been proven to regulate the biological processes of various tumors, but their roles in PCa remain less defined. In the present study, we used bioinformatics analysis to identify RBP genes with prognostic and diagnostic values. A total of 59 differentially expressed RBPs in PCa were obtained, comprising 28 upregulated and 31 downregulated RBP genes, which may play important roles in PCa. Functional enrichment analyses showed that these RBPs were mainly involved in mRNA processing, RNA splicing, and regulation of RNA splicing. Additionally, we identified nine RBP genes (EXO1, PABPC1L, REXO2, MBNL2, MSI1, CTU1, MAEL, YBX2, and ESRP2) and their prognostic values by a protein–protein interaction network and Cox regression analyses. The expression of these nine RBPs was validated using immunohistochemical staining between the tumor and normal samples. Further, the associations between the expression of these nine RBPs and pathological T staging, Gleason score, and lymph node metastasis were evaluated. Moreover, these nine RBP genes showed good diagnostic values and could categorize the PCa patients into two clusters with different malignant phenotypes. Finally, we constructed a prognostic model based on these nine RBP genes and validated them using three external datasets. The model showed good efficiency in predicting patient survival and was independent of other clinical factors. Therefore, our model could be used as a supplement for clinical factors to predict patient prognosis and thereby improve patient survival. Frontiers Media S.A. 2020-10-20 /pmc/articles/PMC7606971/ /pubmed/33193734 http://dx.doi.org/10.3389/fgene.2020.591667 Text en Copyright © 2020 Hua, Ge, Chen, Zhang, Tai and Liang. 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
Hua, Xiaoliang
Ge, Shengdong
Chen, Juan
Zhang, Li
Tai, Sheng
Liang, Chaozhao
Effects of RNA Binding Proteins on the Prognosis and Malignant Progression in Prostate Cancer
title Effects of RNA Binding Proteins on the Prognosis and Malignant Progression in Prostate Cancer
title_full Effects of RNA Binding Proteins on the Prognosis and Malignant Progression in Prostate Cancer
title_fullStr Effects of RNA Binding Proteins on the Prognosis and Malignant Progression in Prostate Cancer
title_full_unstemmed Effects of RNA Binding Proteins on the Prognosis and Malignant Progression in Prostate Cancer
title_short Effects of RNA Binding Proteins on the Prognosis and Malignant Progression in Prostate Cancer
title_sort effects of rna binding proteins on the prognosis and malignant progression in prostate cancer
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7606971/
https://www.ncbi.nlm.nih.gov/pubmed/33193734
http://dx.doi.org/10.3389/fgene.2020.591667
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