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...
Autores principales: | , , , , , , , , , , , |
---|---|
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 |