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Integrated bioinformatic analysis of RNA binding proteins in hepatocellular carcinoma
RNA binding proteins (RBPs) are aberrantly expressed in a tissue-specific manner across many tumors. These proteins, which play a vital role in post-transcriptional gene regulation, are involved in RNA splicing, maturation, transport, stability, degradation, and translation. We set out to establish...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7880356/ https://www.ncbi.nlm.nih.gov/pubmed/33411682 http://dx.doi.org/10.18632/aging.202281 |
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author | Wang, Ling Zhang, Zhen Li, Yuan Wan, Yanyan Xing, Baocai |
author_facet | Wang, Ling Zhang, Zhen Li, Yuan Wan, Yanyan Xing, Baocai |
author_sort | Wang, Ling |
collection | PubMed |
description | RNA binding proteins (RBPs) are aberrantly expressed in a tissue-specific manner across many tumors. These proteins, which play a vital role in post-transcriptional gene regulation, are involved in RNA splicing, maturation, transport, stability, degradation, and translation. We set out to establish an accurate risk score model based on RBPs to estimate prognosis in hepatocellular carcinoma (HCC). RNA-sequencing data, proteomic data and corresponding clinical information were acquired from the Cancer Genome Atlas database and the Clinical Proteomic Tumor Analysis Consortium database respectively. We identified 406 differentially expressed RBPs between HCC tumor and normal tissues at the transcriptional and protein level. Overall, 11 RBPs (BRIX1, DYNC1H1, GTPBP4, PRKDC, RAN, RBM19, SF3B4, SMG5, SPATS2, TAF9, and THOC5) were selected to establish a risk score model. We divided HCC patients into low-risk and high-risk groups based on the median of risk score values. The survival analysis indicated that patients in the high-risk group had poorer overall survival compared to patients in the low-risk group. Our study demonstrated that 11 RBPs were associated with the overall survival of HCC patients. These RBPs may represent potential drug targets and can help optimize future clinical treatment. |
format | Online Article Text |
id | pubmed-7880356 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Impact Journals |
record_format | MEDLINE/PubMed |
spelling | pubmed-78803562021-02-22 Integrated bioinformatic analysis of RNA binding proteins in hepatocellular carcinoma Wang, Ling Zhang, Zhen Li, Yuan Wan, Yanyan Xing, Baocai Aging (Albany NY) Research Paper RNA binding proteins (RBPs) are aberrantly expressed in a tissue-specific manner across many tumors. These proteins, which play a vital role in post-transcriptional gene regulation, are involved in RNA splicing, maturation, transport, stability, degradation, and translation. We set out to establish an accurate risk score model based on RBPs to estimate prognosis in hepatocellular carcinoma (HCC). RNA-sequencing data, proteomic data and corresponding clinical information were acquired from the Cancer Genome Atlas database and the Clinical Proteomic Tumor Analysis Consortium database respectively. We identified 406 differentially expressed RBPs between HCC tumor and normal tissues at the transcriptional and protein level. Overall, 11 RBPs (BRIX1, DYNC1H1, GTPBP4, PRKDC, RAN, RBM19, SF3B4, SMG5, SPATS2, TAF9, and THOC5) were selected to establish a risk score model. We divided HCC patients into low-risk and high-risk groups based on the median of risk score values. The survival analysis indicated that patients in the high-risk group had poorer overall survival compared to patients in the low-risk group. Our study demonstrated that 11 RBPs were associated with the overall survival of HCC patients. These RBPs may represent potential drug targets and can help optimize future clinical treatment. Impact Journals 2020-12-19 /pmc/articles/PMC7880356/ /pubmed/33411682 http://dx.doi.org/10.18632/aging.202281 Text en Copyright: © 2021 Wang et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Paper Wang, Ling Zhang, Zhen Li, Yuan Wan, Yanyan Xing, Baocai Integrated bioinformatic analysis of RNA binding proteins in hepatocellular carcinoma |
title | Integrated bioinformatic analysis of RNA binding proteins in hepatocellular carcinoma |
title_full | Integrated bioinformatic analysis of RNA binding proteins in hepatocellular carcinoma |
title_fullStr | Integrated bioinformatic analysis of RNA binding proteins in hepatocellular carcinoma |
title_full_unstemmed | Integrated bioinformatic analysis of RNA binding proteins in hepatocellular carcinoma |
title_short | Integrated bioinformatic analysis of RNA binding proteins in hepatocellular carcinoma |
title_sort | integrated bioinformatic analysis of rna binding proteins in hepatocellular carcinoma |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7880356/ https://www.ncbi.nlm.nih.gov/pubmed/33411682 http://dx.doi.org/10.18632/aging.202281 |
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