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Development and validation of a robust immune-related risk signature for hepatocellular carcinoma

BACKGROUND: Increasing evidence has indicated immune-related genes (IRGs) play a key role in the development of hepatocellular carcinoma (HCC). Whereas, there have been no investigations proposing a reliable prognostic signature in terms of IRGs. This study aimed to develop a robust signature based...

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Autores principales: Liu, Zaoqu, Jiao, Dechao, Liu, Long, Zhou, Xueliang, Yao, Yuan, Li, Zhaonan, Li, Jing, Chen, Jianjian, Lei, Qinyu, Han, Xinwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7969274/
https://www.ncbi.nlm.nih.gov/pubmed/33725827
http://dx.doi.org/10.1097/MD.0000000000024683
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author Liu, Zaoqu
Jiao, Dechao
Liu, Long
Zhou, Xueliang
Yao, Yuan
Li, Zhaonan
Li, Jing
Chen, Jianjian
Lei, Qinyu
Han, Xinwei
author_facet Liu, Zaoqu
Jiao, Dechao
Liu, Long
Zhou, Xueliang
Yao, Yuan
Li, Zhaonan
Li, Jing
Chen, Jianjian
Lei, Qinyu
Han, Xinwei
author_sort Liu, Zaoqu
collection PubMed
description BACKGROUND: Increasing evidence has indicated immune-related genes (IRGs) play a key role in the development of hepatocellular carcinoma (HCC). Whereas, there have been no investigations proposing a reliable prognostic signature in terms of IRGs. This study aimed to develop a robust signature based on IRGs in HCC. A total of 597 HCC patients from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases were enrolled in this study. METHODS: The TCGA cohort was utilized for discovery, and the ICGC cohort was utilized for validation. Multiple algorithms were implemented to identify key prognostic IRGs and establish an immune-related risk signature. Bioinformatics analysis and R soft tools were utilized to annotate underlying biological functions. RESULTS: A total of 1416 differentially expressed mRNAs (DEMs) were screened, of which 90 were differentially expressed IRGs (DEIRGs). Using univariate Cox regression analysis, we identified 33 prognostically relevant DEIRGs. Using least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analysis, we extracted 8 optimal DEIRGs to construct a risk signature in the TCGA cohort, and the signature was verified in the ICGC cohort. We also built a nomogram to increase the accuracy of predicting HCC prognosis. By investigating the relationship of the risk score and 8 risk genes from our signature with clinical traits, we found that the aberrant expression of the immune-related risk genes is correlated with the development of HCC. Moreover, the high-risk group was higher than the low-risk group in terms of tumor mutation burden (TMB), immune cell infiltration, and the expression of immune checkpoints (programmed cell death protein 1 [PD-1], programmed cell death ligand 1 [PD-L1], and cytotoxic T-lymphocyte-related protein 4 [CTLA-4]), and functional enrichment analysis indicated the signature enriched an intensive immune phenotype. CONCLUSION: This study developed a robust immune-related risk signature and built a predictive nomogram that reliably predict overall survival in HCC, which may be helpful for clinical management and personalized immunotherapy decisions.
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spelling pubmed-79692742021-03-18 Development and validation of a robust immune-related risk signature for hepatocellular carcinoma Liu, Zaoqu Jiao, Dechao Liu, Long Zhou, Xueliang Yao, Yuan Li, Zhaonan Li, Jing Chen, Jianjian Lei, Qinyu Han, Xinwei Medicine (Baltimore) 5700 BACKGROUND: Increasing evidence has indicated immune-related genes (IRGs) play a key role in the development of hepatocellular carcinoma (HCC). Whereas, there have been no investigations proposing a reliable prognostic signature in terms of IRGs. This study aimed to develop a robust signature based on IRGs in HCC. A total of 597 HCC patients from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases were enrolled in this study. METHODS: The TCGA cohort was utilized for discovery, and the ICGC cohort was utilized for validation. Multiple algorithms were implemented to identify key prognostic IRGs and establish an immune-related risk signature. Bioinformatics analysis and R soft tools were utilized to annotate underlying biological functions. RESULTS: A total of 1416 differentially expressed mRNAs (DEMs) were screened, of which 90 were differentially expressed IRGs (DEIRGs). Using univariate Cox regression analysis, we identified 33 prognostically relevant DEIRGs. Using least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analysis, we extracted 8 optimal DEIRGs to construct a risk signature in the TCGA cohort, and the signature was verified in the ICGC cohort. We also built a nomogram to increase the accuracy of predicting HCC prognosis. By investigating the relationship of the risk score and 8 risk genes from our signature with clinical traits, we found that the aberrant expression of the immune-related risk genes is correlated with the development of HCC. Moreover, the high-risk group was higher than the low-risk group in terms of tumor mutation burden (TMB), immune cell infiltration, and the expression of immune checkpoints (programmed cell death protein 1 [PD-1], programmed cell death ligand 1 [PD-L1], and cytotoxic T-lymphocyte-related protein 4 [CTLA-4]), and functional enrichment analysis indicated the signature enriched an intensive immune phenotype. CONCLUSION: This study developed a robust immune-related risk signature and built a predictive nomogram that reliably predict overall survival in HCC, which may be helpful for clinical management and personalized immunotherapy decisions. Lippincott Williams & Wilkins 2021-03-12 /pmc/articles/PMC7969274/ /pubmed/33725827 http://dx.doi.org/10.1097/MD.0000000000024683 Text en Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by-nc/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc/4.0
spellingShingle 5700
Liu, Zaoqu
Jiao, Dechao
Liu, Long
Zhou, Xueliang
Yao, Yuan
Li, Zhaonan
Li, Jing
Chen, Jianjian
Lei, Qinyu
Han, Xinwei
Development and validation of a robust immune-related risk signature for hepatocellular carcinoma
title Development and validation of a robust immune-related risk signature for hepatocellular carcinoma
title_full Development and validation of a robust immune-related risk signature for hepatocellular carcinoma
title_fullStr Development and validation of a robust immune-related risk signature for hepatocellular carcinoma
title_full_unstemmed Development and validation of a robust immune-related risk signature for hepatocellular carcinoma
title_short Development and validation of a robust immune-related risk signature for hepatocellular carcinoma
title_sort development and validation of a robust immune-related risk signature for hepatocellular carcinoma
topic 5700
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7969274/
https://www.ncbi.nlm.nih.gov/pubmed/33725827
http://dx.doi.org/10.1097/MD.0000000000024683
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