Cargando…

Bioinformatics Analysis for Constructing a Six-Immune-Related Long Noncoding RNA Signature as a Prognostic Model of Hepatocellular Carcinoma

The present study was aimed at identifying the potential prognostic biomarkers of the immune-related long noncoding RNA (IRL) signature for patients with hepatocellular carcinoma (HCC). RNA-sequencing data and clinical information about HCC were obtained from The Cancer Genome Atlas. The IRLs were d...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Jue, Jin, Zongrui, Wu, Guolin, Wang, Jilong, Xu, Banghao, Zhu, Hai, Guo, Ya, Wen, Zhang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9283041/
https://www.ncbi.nlm.nih.gov/pubmed/35845962
http://dx.doi.org/10.1155/2022/2093437
_version_ 1784747247398813696
author Wang, Jue
Jin, Zongrui
Wu, Guolin
Wang, Jilong
Xu, Banghao
Zhu, Hai
Guo, Ya
Wen, Zhang
author_facet Wang, Jue
Jin, Zongrui
Wu, Guolin
Wang, Jilong
Xu, Banghao
Zhu, Hai
Guo, Ya
Wen, Zhang
author_sort Wang, Jue
collection PubMed
description The present study was aimed at identifying the potential prognostic biomarkers of the immune-related long noncoding RNA (IRL) signature for patients with hepatocellular carcinoma (HCC). RNA-sequencing data and clinical information about HCC were obtained from The Cancer Genome Atlas. The IRLs were determined with regard to the coexpression of immune-related genes and differentially expressed lncRNAs. The survival IRLs were obtained using the univariate Cox analysis. Subsequently, the prognosis model was constructed via the multivariate Cox analysis. Subsequently, functional annotation was conducted using Gene Set Enrichment Analysis (GSEA) and principal component analysis (PCA). In total, 341 IRLs were identified, and 6 IRLs were found to have a highly significant association with the prognosis of patients with HCC. The immune prognosis model was constructed with these 6 IRLs (AC099850.4, negative regulator of antiviral response, AL031985.3, PRRT3-antisense RNA1, AL365203.2, and long intergenic nonprotein coding RNA 1224) using the multivariate Cox regression analysis. In addition, immune-related prognosis signatures were confirmed as an independent prognostic factor. The association between prognostic signatures and immune infiltration indicated that the 6 lncRNAs could reflect the immune status of the tumor. Collectively, the present study demonstrates that six-lncRNA signatures may be potential biomarkers to predict the prognosis of patients with HCC.
format Online
Article
Text
id pubmed-9283041
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Hindawi
record_format MEDLINE/PubMed
spelling pubmed-92830412022-07-15 Bioinformatics Analysis for Constructing a Six-Immune-Related Long Noncoding RNA Signature as a Prognostic Model of Hepatocellular Carcinoma Wang, Jue Jin, Zongrui Wu, Guolin Wang, Jilong Xu, Banghao Zhu, Hai Guo, Ya Wen, Zhang Biomed Res Int Research Article The present study was aimed at identifying the potential prognostic biomarkers of the immune-related long noncoding RNA (IRL) signature for patients with hepatocellular carcinoma (HCC). RNA-sequencing data and clinical information about HCC were obtained from The Cancer Genome Atlas. The IRLs were determined with regard to the coexpression of immune-related genes and differentially expressed lncRNAs. The survival IRLs were obtained using the univariate Cox analysis. Subsequently, the prognosis model was constructed via the multivariate Cox analysis. Subsequently, functional annotation was conducted using Gene Set Enrichment Analysis (GSEA) and principal component analysis (PCA). In total, 341 IRLs were identified, and 6 IRLs were found to have a highly significant association with the prognosis of patients with HCC. The immune prognosis model was constructed with these 6 IRLs (AC099850.4, negative regulator of antiviral response, AL031985.3, PRRT3-antisense RNA1, AL365203.2, and long intergenic nonprotein coding RNA 1224) using the multivariate Cox regression analysis. In addition, immune-related prognosis signatures were confirmed as an independent prognostic factor. The association between prognostic signatures and immune infiltration indicated that the 6 lncRNAs could reflect the immune status of the tumor. Collectively, the present study demonstrates that six-lncRNA signatures may be potential biomarkers to predict the prognosis of patients with HCC. Hindawi 2022-07-07 /pmc/articles/PMC9283041/ /pubmed/35845962 http://dx.doi.org/10.1155/2022/2093437 Text en Copyright © 2022 Jue Wang et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Wang, Jue
Jin, Zongrui
Wu, Guolin
Wang, Jilong
Xu, Banghao
Zhu, Hai
Guo, Ya
Wen, Zhang
Bioinformatics Analysis for Constructing a Six-Immune-Related Long Noncoding RNA Signature as a Prognostic Model of Hepatocellular Carcinoma
title Bioinformatics Analysis for Constructing a Six-Immune-Related Long Noncoding RNA Signature as a Prognostic Model of Hepatocellular Carcinoma
title_full Bioinformatics Analysis for Constructing a Six-Immune-Related Long Noncoding RNA Signature as a Prognostic Model of Hepatocellular Carcinoma
title_fullStr Bioinformatics Analysis for Constructing a Six-Immune-Related Long Noncoding RNA Signature as a Prognostic Model of Hepatocellular Carcinoma
title_full_unstemmed Bioinformatics Analysis for Constructing a Six-Immune-Related Long Noncoding RNA Signature as a Prognostic Model of Hepatocellular Carcinoma
title_short Bioinformatics Analysis for Constructing a Six-Immune-Related Long Noncoding RNA Signature as a Prognostic Model of Hepatocellular Carcinoma
title_sort bioinformatics analysis for constructing a six-immune-related long noncoding rna signature as a prognostic model of hepatocellular carcinoma
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9283041/
https://www.ncbi.nlm.nih.gov/pubmed/35845962
http://dx.doi.org/10.1155/2022/2093437
work_keys_str_mv AT wangjue bioinformaticsanalysisforconstructingasiximmunerelatedlongnoncodingrnasignatureasaprognosticmodelofhepatocellularcarcinoma
AT jinzongrui bioinformaticsanalysisforconstructingasiximmunerelatedlongnoncodingrnasignatureasaprognosticmodelofhepatocellularcarcinoma
AT wuguolin bioinformaticsanalysisforconstructingasiximmunerelatedlongnoncodingrnasignatureasaprognosticmodelofhepatocellularcarcinoma
AT wangjilong bioinformaticsanalysisforconstructingasiximmunerelatedlongnoncodingrnasignatureasaprognosticmodelofhepatocellularcarcinoma
AT xubanghao bioinformaticsanalysisforconstructingasiximmunerelatedlongnoncodingrnasignatureasaprognosticmodelofhepatocellularcarcinoma
AT zhuhai bioinformaticsanalysisforconstructingasiximmunerelatedlongnoncodingrnasignatureasaprognosticmodelofhepatocellularcarcinoma
AT guoya bioinformaticsanalysisforconstructingasiximmunerelatedlongnoncodingrnasignatureasaprognosticmodelofhepatocellularcarcinoma
AT wenzhang bioinformaticsanalysisforconstructingasiximmunerelatedlongnoncodingrnasignatureasaprognosticmodelofhepatocellularcarcinoma