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Analysis of the Prognosis Prediction Ability of a Necroptosis-Related Gene Signature and its Relationship With the Hepatocellular Carcinoma Immune Microenvironment Using Bioinformatics Analysis and Experimental Validation
Background: Hepatocellular carcinoma (HCC) is one of the most malignant cancers and has a poor prognosis. The immune microenvironment is closely related to the drug sensitivity of a tumor. Necroptosis was reported to be a key factor for HCC. The prognostic value of necroptosis-related genes and thei...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10286176/ https://www.ncbi.nlm.nih.gov/pubmed/37335078 http://dx.doi.org/10.1177/15330338231182208 |
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author | Guan, Renguo Mei, Jie Guo, Rongping |
author_facet | Guan, Renguo Mei, Jie Guo, Rongping |
author_sort | Guan, Renguo |
collection | PubMed |
description | Background: Hepatocellular carcinoma (HCC) is one of the most malignant cancers and has a poor prognosis. The immune microenvironment is closely related to the drug sensitivity of a tumor. Necroptosis was reported to be a key factor for HCC. The prognostic value of necroptosis-related genes and their association with the tumor immune microenvironment are still unknown. Methods: Necroptosis-related genes that could comprise a signature for predicting the prognosis of HCC cases were identified using univariate analysis and least absolute shrinkage and selection operator Cox regression analysis. The association between this prognosis prediction signature and HCC immune microenvironment was analyzed. The immunological activities and drug sensitivities were compared between different risk score groups identified using the prognosis prediction signature. The expression levels of the five genes comprising the signature were validated using RT-qPCR. Results: A prognosis prediction signature consisting of five necroptosis-related genes was constructed and validated. Its risk score was = (0.1634 × PGAM5 expression) + (0.0134 × CXCL1 expression) − (0.1007 × ALDH2 expression) + (0.2351 × EZH2 expression) − (0.0564 × NDRG2 expression). The signature was found to be significantly associated with the infiltration of B cells, CD4(+) T cells, neutrophils, macrophages, and myeloid dendritic cells into the HCC immune microenvironment. The number of infiltrating immune cells and the expression levels of immune checkpoints in the immune microenvironment of high-risk score patients were higher. Sorafenib and immune checkpoint blockade were determined to be ideally suited for treating high-risk score patients and low-risk score patients, respectively. Finally, RT-qPCR results confirmed that the expression levels of EZH2, NDRG2, and ALDH2 were significantly down-regulated in HuH7 and HepG2 cells compared to those in LO2 cells. Conclusion: The necroptosis-related gene signature developed herein can classify patients with HCC according to prognosis risk well and is associated with infiltration of immune cells into the tumor immune microenvironment. |
format | Online Article Text |
id | pubmed-10286176 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-102861762023-06-23 Analysis of the Prognosis Prediction Ability of a Necroptosis-Related Gene Signature and its Relationship With the Hepatocellular Carcinoma Immune Microenvironment Using Bioinformatics Analysis and Experimental Validation Guan, Renguo Mei, Jie Guo, Rongping Technol Cancer Res Treat Original Article Background: Hepatocellular carcinoma (HCC) is one of the most malignant cancers and has a poor prognosis. The immune microenvironment is closely related to the drug sensitivity of a tumor. Necroptosis was reported to be a key factor for HCC. The prognostic value of necroptosis-related genes and their association with the tumor immune microenvironment are still unknown. Methods: Necroptosis-related genes that could comprise a signature for predicting the prognosis of HCC cases were identified using univariate analysis and least absolute shrinkage and selection operator Cox regression analysis. The association between this prognosis prediction signature and HCC immune microenvironment was analyzed. The immunological activities and drug sensitivities were compared between different risk score groups identified using the prognosis prediction signature. The expression levels of the five genes comprising the signature were validated using RT-qPCR. Results: A prognosis prediction signature consisting of five necroptosis-related genes was constructed and validated. Its risk score was = (0.1634 × PGAM5 expression) + (0.0134 × CXCL1 expression) − (0.1007 × ALDH2 expression) + (0.2351 × EZH2 expression) − (0.0564 × NDRG2 expression). The signature was found to be significantly associated with the infiltration of B cells, CD4(+) T cells, neutrophils, macrophages, and myeloid dendritic cells into the HCC immune microenvironment. The number of infiltrating immune cells and the expression levels of immune checkpoints in the immune microenvironment of high-risk score patients were higher. Sorafenib and immune checkpoint blockade were determined to be ideally suited for treating high-risk score patients and low-risk score patients, respectively. Finally, RT-qPCR results confirmed that the expression levels of EZH2, NDRG2, and ALDH2 were significantly down-regulated in HuH7 and HepG2 cells compared to those in LO2 cells. Conclusion: The necroptosis-related gene signature developed herein can classify patients with HCC according to prognosis risk well and is associated with infiltration of immune cells into the tumor immune microenvironment. SAGE Publications 2023-06-19 /pmc/articles/PMC10286176/ /pubmed/37335078 http://dx.doi.org/10.1177/15330338231182208 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Original Article Guan, Renguo Mei, Jie Guo, Rongping Analysis of the Prognosis Prediction Ability of a Necroptosis-Related Gene Signature and its Relationship With the Hepatocellular Carcinoma Immune Microenvironment Using Bioinformatics Analysis and Experimental Validation |
title | Analysis of the Prognosis Prediction Ability of a Necroptosis-Related Gene Signature and its Relationship With the Hepatocellular Carcinoma Immune Microenvironment Using Bioinformatics Analysis and Experimental Validation |
title_full | Analysis of the Prognosis Prediction Ability of a Necroptosis-Related Gene Signature and its Relationship With the Hepatocellular Carcinoma Immune Microenvironment Using Bioinformatics Analysis and Experimental Validation |
title_fullStr | Analysis of the Prognosis Prediction Ability of a Necroptosis-Related Gene Signature and its Relationship With the Hepatocellular Carcinoma Immune Microenvironment Using Bioinformatics Analysis and Experimental Validation |
title_full_unstemmed | Analysis of the Prognosis Prediction Ability of a Necroptosis-Related Gene Signature and its Relationship With the Hepatocellular Carcinoma Immune Microenvironment Using Bioinformatics Analysis and Experimental Validation |
title_short | Analysis of the Prognosis Prediction Ability of a Necroptosis-Related Gene Signature and its Relationship With the Hepatocellular Carcinoma Immune Microenvironment Using Bioinformatics Analysis and Experimental Validation |
title_sort | analysis of the prognosis prediction ability of a necroptosis-related gene signature and its relationship with the hepatocellular carcinoma immune microenvironment using bioinformatics analysis and experimental validation |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10286176/ https://www.ncbi.nlm.nih.gov/pubmed/37335078 http://dx.doi.org/10.1177/15330338231182208 |
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