Cargando…

Transcriptome Analyses Identify an RNA Binding Protein Related Prognostic Model for Clear Cell Renal Cell Carcinoma

RNA binding proteins (RBPs) play a key role in post-transcriptional gene regulation. They have been shown to be dysfunctional in a variety of cancers and are closely related to the occurrence and progression of cancers. However, the biological function and clinical significance of RBPs in clear cell...

Descripción completa

Detalles Bibliográficos
Autores principales: Wu, Yue, Wei, Xian, Feng, Huan, Hu, Bintao, Liu, Bo, Luan, Yang, Ruan, Yajun, Liu, Xiaming, Liu, Zhuo, Wang, Shaogang, Liu, Jihong, Wang, Tao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7817999/
https://www.ncbi.nlm.nih.gov/pubmed/33488680
http://dx.doi.org/10.3389/fgene.2020.617872
_version_ 1783638749212573696
author Wu, Yue
Wei, Xian
Feng, Huan
Hu, Bintao
Liu, Bo
Luan, Yang
Ruan, Yajun
Liu, Xiaming
Liu, Zhuo
Wang, Shaogang
Liu, Jihong
Wang, Tao
author_facet Wu, Yue
Wei, Xian
Feng, Huan
Hu, Bintao
Liu, Bo
Luan, Yang
Ruan, Yajun
Liu, Xiaming
Liu, Zhuo
Wang, Shaogang
Liu, Jihong
Wang, Tao
author_sort Wu, Yue
collection PubMed
description RNA binding proteins (RBPs) play a key role in post-transcriptional gene regulation. They have been shown to be dysfunctional in a variety of cancers and are closely related to the occurrence and progression of cancers. However, the biological function and clinical significance of RBPs in clear cell renal carcinoma (ccRCC) are unclear. In our current study, we downloaded the transcriptome data of ccRCC patients from The Cancer Genome Atlas (TCGA) database and identified differential expression of RBPs between tumor tissue and normal kidney tissue. Then the biological function and clinical value of these RBPs were explored by using a variety of bioinformatics techniques. We identified a total of 40 differentially expressed RBPs, including 10 down-regulated RBPs and 30 up-regulated RBPs. Eight RBPs (APOBEC3G, AUH, DAZL, EIF4A1, IGF2BP3, NR0B1, RPL36A, and TRMT1) and nine RBPs (APOBEC3G, AUH, DDX47, IGF2BP3, MOV10L1, NANOS1, PIH1D3, TDRD9, and TRMT1) were identified as prognostic related to overall survival (OS) and disease-free survival (DFS), respectively, and prognostic models for OS and DFS were constructed based on these RBPs. Further analysis showed that OS and DFS were worse in high-risk group than in the low-risk group. The area under the receiver operator characteristic curve of the model for OS was 0.702 at 3 years and 0.726 at 5 years in TCGA cohort and 0.783 at 3 years and 0.795 at 5 years in E-MTAB-1980 cohort, showing good predictive performance. Both models have been shown to independently predict the prognosis of ccRCC patients. We also established a nomogram based on these prognostic RBPs for OS and performed internal validation in the TCGA cohort, showing an accurate prediction of ccRCC prognosis. Stratified analysis showed a significant correlation between the prognostic model for OS and ccRCC progression.
format Online
Article
Text
id pubmed-7817999
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-78179992021-01-22 Transcriptome Analyses Identify an RNA Binding Protein Related Prognostic Model for Clear Cell Renal Cell Carcinoma Wu, Yue Wei, Xian Feng, Huan Hu, Bintao Liu, Bo Luan, Yang Ruan, Yajun Liu, Xiaming Liu, Zhuo Wang, Shaogang Liu, Jihong Wang, Tao Front Genet Genetics RNA binding proteins (RBPs) play a key role in post-transcriptional gene regulation. They have been shown to be dysfunctional in a variety of cancers and are closely related to the occurrence and progression of cancers. However, the biological function and clinical significance of RBPs in clear cell renal carcinoma (ccRCC) are unclear. In our current study, we downloaded the transcriptome data of ccRCC patients from The Cancer Genome Atlas (TCGA) database and identified differential expression of RBPs between tumor tissue and normal kidney tissue. Then the biological function and clinical value of these RBPs were explored by using a variety of bioinformatics techniques. We identified a total of 40 differentially expressed RBPs, including 10 down-regulated RBPs and 30 up-regulated RBPs. Eight RBPs (APOBEC3G, AUH, DAZL, EIF4A1, IGF2BP3, NR0B1, RPL36A, and TRMT1) and nine RBPs (APOBEC3G, AUH, DDX47, IGF2BP3, MOV10L1, NANOS1, PIH1D3, TDRD9, and TRMT1) were identified as prognostic related to overall survival (OS) and disease-free survival (DFS), respectively, and prognostic models for OS and DFS were constructed based on these RBPs. Further analysis showed that OS and DFS were worse in high-risk group than in the low-risk group. The area under the receiver operator characteristic curve of the model for OS was 0.702 at 3 years and 0.726 at 5 years in TCGA cohort and 0.783 at 3 years and 0.795 at 5 years in E-MTAB-1980 cohort, showing good predictive performance. Both models have been shown to independently predict the prognosis of ccRCC patients. We also established a nomogram based on these prognostic RBPs for OS and performed internal validation in the TCGA cohort, showing an accurate prediction of ccRCC prognosis. Stratified analysis showed a significant correlation between the prognostic model for OS and ccRCC progression. Frontiers Media S.A. 2021-01-07 /pmc/articles/PMC7817999/ /pubmed/33488680 http://dx.doi.org/10.3389/fgene.2020.617872 Text en Copyright © 2021 Wu, Wei, Feng, Hu, Liu, Luan, Ruan, Liu, Liu, Wang, Liu and Wang. 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
Wu, Yue
Wei, Xian
Feng, Huan
Hu, Bintao
Liu, Bo
Luan, Yang
Ruan, Yajun
Liu, Xiaming
Liu, Zhuo
Wang, Shaogang
Liu, Jihong
Wang, Tao
Transcriptome Analyses Identify an RNA Binding Protein Related Prognostic Model for Clear Cell Renal Cell Carcinoma
title Transcriptome Analyses Identify an RNA Binding Protein Related Prognostic Model for Clear Cell Renal Cell Carcinoma
title_full Transcriptome Analyses Identify an RNA Binding Protein Related Prognostic Model for Clear Cell Renal Cell Carcinoma
title_fullStr Transcriptome Analyses Identify an RNA Binding Protein Related Prognostic Model for Clear Cell Renal Cell Carcinoma
title_full_unstemmed Transcriptome Analyses Identify an RNA Binding Protein Related Prognostic Model for Clear Cell Renal Cell Carcinoma
title_short Transcriptome Analyses Identify an RNA Binding Protein Related Prognostic Model for Clear Cell Renal Cell Carcinoma
title_sort transcriptome analyses identify an rna binding protein related prognostic model for clear cell renal cell carcinoma
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7817999/
https://www.ncbi.nlm.nih.gov/pubmed/33488680
http://dx.doi.org/10.3389/fgene.2020.617872
work_keys_str_mv AT wuyue transcriptomeanalysesidentifyanrnabindingproteinrelatedprognosticmodelforclearcellrenalcellcarcinoma
AT weixian transcriptomeanalysesidentifyanrnabindingproteinrelatedprognosticmodelforclearcellrenalcellcarcinoma
AT fenghuan transcriptomeanalysesidentifyanrnabindingproteinrelatedprognosticmodelforclearcellrenalcellcarcinoma
AT hubintao transcriptomeanalysesidentifyanrnabindingproteinrelatedprognosticmodelforclearcellrenalcellcarcinoma
AT liubo transcriptomeanalysesidentifyanrnabindingproteinrelatedprognosticmodelforclearcellrenalcellcarcinoma
AT luanyang transcriptomeanalysesidentifyanrnabindingproteinrelatedprognosticmodelforclearcellrenalcellcarcinoma
AT ruanyajun transcriptomeanalysesidentifyanrnabindingproteinrelatedprognosticmodelforclearcellrenalcellcarcinoma
AT liuxiaming transcriptomeanalysesidentifyanrnabindingproteinrelatedprognosticmodelforclearcellrenalcellcarcinoma
AT liuzhuo transcriptomeanalysesidentifyanrnabindingproteinrelatedprognosticmodelforclearcellrenalcellcarcinoma
AT wangshaogang transcriptomeanalysesidentifyanrnabindingproteinrelatedprognosticmodelforclearcellrenalcellcarcinoma
AT liujihong transcriptomeanalysesidentifyanrnabindingproteinrelatedprognosticmodelforclearcellrenalcellcarcinoma
AT wangtao transcriptomeanalysesidentifyanrnabindingproteinrelatedprognosticmodelforclearcellrenalcellcarcinoma