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Comprehensive analysis: Necroptosis-related lncRNAs can effectively predict the prognosis of glioma patients

Glioma is the most common and fatal primary brain tumor in humans. A significant role for long non-coding RNA (lncRNA) in glioma is the regulation of gene expression and chromatin recombination, and immunotherapy is a promising cancer treatment. Therefore, it is necessary to identify necroptosis-rel...

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Autores principales: Chen, Desheng, Dou, Chao, Liu, Haiyu, Xu, Binshun, Hu, Bowen, Kuang, Liangwen, Yao, Jiawei, Zhao, Yan, Yu, Shan, Li, Yang, Wang, Fuqing, Guo, Mian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9402092/
https://www.ncbi.nlm.nih.gov/pubmed/36033536
http://dx.doi.org/10.3389/fonc.2022.929233
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author Chen, Desheng
Dou, Chao
Liu, Haiyu
Xu, Binshun
Hu, Bowen
Kuang, Liangwen
Yao, Jiawei
Zhao, Yan
Yu, Shan
Li, Yang
Wang, Fuqing
Guo, Mian
author_facet Chen, Desheng
Dou, Chao
Liu, Haiyu
Xu, Binshun
Hu, Bowen
Kuang, Liangwen
Yao, Jiawei
Zhao, Yan
Yu, Shan
Li, Yang
Wang, Fuqing
Guo, Mian
author_sort Chen, Desheng
collection PubMed
description Glioma is the most common and fatal primary brain tumor in humans. A significant role for long non-coding RNA (lncRNA) in glioma is the regulation of gene expression and chromatin recombination, and immunotherapy is a promising cancer treatment. Therefore, it is necessary to identify necroptosis-related lncRNAs in glioma. In this study, we collected and evaluated the RNA-sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA, https://www.ncbi.nlm.nih.gov/, Data Release 32.0, March 29, 2022) glioma patients, and necroptosis-related lncRNAs were screened. Cox regression and least absolute shrinkage and selection operator (LASSO) analysis were performed to construct a risk score formula to explore the different overall survival between high- and low-risk groups in TCGA. Gene Ontology (GO) and pathway enrichment analysis (Kyoto Encyclopedia of Genes and Genomes (KEGG)) were performed to identify the function of screened genes. The immune correlation analysis showed that various immune cells and pathways positively associated with a patient’s risk score. Furthermore, the analysis of the tumor microenvironment indicated many immune cells and stromal cells in the tumor microenvironment of glioma patients. Six necroptosis-related lncRNAs were concerned to be involved in survival and adopted to construct the risk score formula. The results showed that patients with high-risk scores held poor survival in TCGA. Compared with current clinical data, the area under the curve (AUC) of different years suggested that the formula had better predictive power. We verified that necroptosis-related lncRNAs play a significant role in the occurrence and development of glioma, and the constructed risk model can reasonably predict the prognosis of glioma. The results of these studies added some valuable guidance to understanding glioma pathogenesis and treatment, and these necroptosis-related lncRNAs may be used as biomarkers and therapeutic targets for glioma prevention.
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spelling pubmed-94020922022-08-25 Comprehensive analysis: Necroptosis-related lncRNAs can effectively predict the prognosis of glioma patients Chen, Desheng Dou, Chao Liu, Haiyu Xu, Binshun Hu, Bowen Kuang, Liangwen Yao, Jiawei Zhao, Yan Yu, Shan Li, Yang Wang, Fuqing Guo, Mian Front Oncol Oncology Glioma is the most common and fatal primary brain tumor in humans. A significant role for long non-coding RNA (lncRNA) in glioma is the regulation of gene expression and chromatin recombination, and immunotherapy is a promising cancer treatment. Therefore, it is necessary to identify necroptosis-related lncRNAs in glioma. In this study, we collected and evaluated the RNA-sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA, https://www.ncbi.nlm.nih.gov/, Data Release 32.0, March 29, 2022) glioma patients, and necroptosis-related lncRNAs were screened. Cox regression and least absolute shrinkage and selection operator (LASSO) analysis were performed to construct a risk score formula to explore the different overall survival between high- and low-risk groups in TCGA. Gene Ontology (GO) and pathway enrichment analysis (Kyoto Encyclopedia of Genes and Genomes (KEGG)) were performed to identify the function of screened genes. The immune correlation analysis showed that various immune cells and pathways positively associated with a patient’s risk score. Furthermore, the analysis of the tumor microenvironment indicated many immune cells and stromal cells in the tumor microenvironment of glioma patients. Six necroptosis-related lncRNAs were concerned to be involved in survival and adopted to construct the risk score formula. The results showed that patients with high-risk scores held poor survival in TCGA. Compared with current clinical data, the area under the curve (AUC) of different years suggested that the formula had better predictive power. We verified that necroptosis-related lncRNAs play a significant role in the occurrence and development of glioma, and the constructed risk model can reasonably predict the prognosis of glioma. The results of these studies added some valuable guidance to understanding glioma pathogenesis and treatment, and these necroptosis-related lncRNAs may be used as biomarkers and therapeutic targets for glioma prevention. Frontiers Media S.A. 2022-08-10 /pmc/articles/PMC9402092/ /pubmed/36033536 http://dx.doi.org/10.3389/fonc.2022.929233 Text en Copyright © 2022 Chen, Dou, Liu, Xu, Hu, Kuang, Yao, Zhao, Yu, Li, Wang and Guo https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Chen, Desheng
Dou, Chao
Liu, Haiyu
Xu, Binshun
Hu, Bowen
Kuang, Liangwen
Yao, Jiawei
Zhao, Yan
Yu, Shan
Li, Yang
Wang, Fuqing
Guo, Mian
Comprehensive analysis: Necroptosis-related lncRNAs can effectively predict the prognosis of glioma patients
title Comprehensive analysis: Necroptosis-related lncRNAs can effectively predict the prognosis of glioma patients
title_full Comprehensive analysis: Necroptosis-related lncRNAs can effectively predict the prognosis of glioma patients
title_fullStr Comprehensive analysis: Necroptosis-related lncRNAs can effectively predict the prognosis of glioma patients
title_full_unstemmed Comprehensive analysis: Necroptosis-related lncRNAs can effectively predict the prognosis of glioma patients
title_short Comprehensive analysis: Necroptosis-related lncRNAs can effectively predict the prognosis of glioma patients
title_sort comprehensive analysis: necroptosis-related lncrnas can effectively predict the prognosis of glioma patients
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9402092/
https://www.ncbi.nlm.nih.gov/pubmed/36033536
http://dx.doi.org/10.3389/fonc.2022.929233
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