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...

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Bibliographic Details
Published in:BioMed research international 2022-07, Vol.2022, p.1-15
Main Authors: Wang, Jue, Jin, Zongrui, Wu, Guolin, Wang, Jilong, Xu, Banghao, Zhu, Hai, Guo, Ya, Wen, Zhang
Format: Article
Language:English
Subjects:
Analysis
Annotations
Antisense RNA
Bioinformatics
Biomarkers
Cancer
Cancer therapies
Care and treatment
Computational biology
Correlation analysis
Diagnosis
Gene sequencing
Gene set enrichment analysis
Genes
Genetic aspects
Genomes
Hepatitis
Hepatocellular carcinoma
Hepatoma
Immune status
Immune system
Liver cancer
Medical prognosis
Metastases
Mortality
Multivariate analysis
Non-coding RNA
Patients
Principal components analysis
Prognosis
Reagents
Regression analysis
Ribonucleic acid
Risk factors
RNA
Software
Statistical analysis
Tumors
Citations: Items that this one cites
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Summary: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.
ISSN:2314-6133
2314-6141
DOI:10.1155/2022/2093437