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A Novel Necroptosis-Related lncRNA Signature for Predicting Prognosis and Immune Response of Glioma

Glioma is one of the most common intracranial malignancies that plagues people around the world. Despite current improvements in treatment, the prognosis of glioma is often unsatisfactory. Necroptosis is a form of programmed cell death. As research progresses, the role of necroptosis in tumors has g...

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Autores principales: Wu, Zhikang, Liu, Meimei, Fu, Jinlong, Li, Jinwei, Qin, Lingyao, Wu, Liuying, Chen, Hongmou, Yan, Xianlei, Liu, Quan, Zheng, Jiemin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9226973/
https://www.ncbi.nlm.nih.gov/pubmed/35757472
http://dx.doi.org/10.1155/2022/3742447
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author Wu, Zhikang
Liu, Meimei
Fu, Jinlong
Li, Jinwei
Qin, Lingyao
Wu, Liuying
Chen, Hongmou
Yan, Xianlei
Liu, Quan
Zheng, Jiemin
author_facet Wu, Zhikang
Liu, Meimei
Fu, Jinlong
Li, Jinwei
Qin, Lingyao
Wu, Liuying
Chen, Hongmou
Yan, Xianlei
Liu, Quan
Zheng, Jiemin
author_sort Wu, Zhikang
collection PubMed
description Glioma is one of the most common intracranial malignancies that plagues people around the world. Despite current improvements in treatment, the prognosis of glioma is often unsatisfactory. Necroptosis is a form of programmed cell death. As research progresses, the role of necroptosis in tumors has gradually attracted the attention of researchers. And lncRNA is regarded as a critical role in the development of cancer. Therefore, this study is aimed at establishing a prognostic model based on necroptosis-associated lncRNAs to accurately assess the prognosis and immune response of patients with glioma. The RNA sequences of glioma patients and normal brain samples were downloaded from The Cancer Genome Atlas (TCGA) and GTEx databases, respectively. The coexpression analysis was performed to identify the necroptosis-related lncRNAs. Then, we utilized LASSO analysis following univariate Cox analysis to construct a prognostic model. Subsequently, we applied the Kaplan-Meier curve, time-dependent receiver operating characteristics (ROC), and univariate and multivariate Cox regression analyses to assess the effectiveness of this model. And the functional enrichment analyses and immune-related analyses were employed to investigate the potential biological functions. A validation set was obtained from the Chinese Glioma Genome Atlas (CGGA) database. And qRT-PCR was employed to further validate the expression levels of selected necroptosis-associated lncRNAs. Seven necroptosis-related lncRNAs (FAM13A-AS1, JMJD1C-AS1, LBX2-AS1, ZBTB20-AS4, HAR1A, SNHG14, and LINC00900) were determined to construct a prognostic model. The area under the ROC curve (AUC) was 0.871, 0.901, and 0.911 at 1, 2, and 3 years, respectively. The risk score was shown to be an important independent predictor in both univariate and multivariate Cox regression analyses. Through functional enrichment analyses, we found that the differentially expressed genes (DEGs) were mainly enriched in protein binding and signaling-related biological functions and immune-associated pathways. In conclusion, we established and validated a novel necroptosis-related lncRNA signature, which could accurately predict the overall survival of glioma patients and serve as potential therapeutic targets.
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spelling pubmed-92269732022-06-25 A Novel Necroptosis-Related lncRNA Signature for Predicting Prognosis and Immune Response of Glioma Wu, Zhikang Liu, Meimei Fu, Jinlong Li, Jinwei Qin, Lingyao Wu, Liuying Chen, Hongmou Yan, Xianlei Liu, Quan Zheng, Jiemin Biomed Res Int Research Article Glioma is one of the most common intracranial malignancies that plagues people around the world. Despite current improvements in treatment, the prognosis of glioma is often unsatisfactory. Necroptosis is a form of programmed cell death. As research progresses, the role of necroptosis in tumors has gradually attracted the attention of researchers. And lncRNA is regarded as a critical role in the development of cancer. Therefore, this study is aimed at establishing a prognostic model based on necroptosis-associated lncRNAs to accurately assess the prognosis and immune response of patients with glioma. The RNA sequences of glioma patients and normal brain samples were downloaded from The Cancer Genome Atlas (TCGA) and GTEx databases, respectively. The coexpression analysis was performed to identify the necroptosis-related lncRNAs. Then, we utilized LASSO analysis following univariate Cox analysis to construct a prognostic model. Subsequently, we applied the Kaplan-Meier curve, time-dependent receiver operating characteristics (ROC), and univariate and multivariate Cox regression analyses to assess the effectiveness of this model. And the functional enrichment analyses and immune-related analyses were employed to investigate the potential biological functions. A validation set was obtained from the Chinese Glioma Genome Atlas (CGGA) database. And qRT-PCR was employed to further validate the expression levels of selected necroptosis-associated lncRNAs. Seven necroptosis-related lncRNAs (FAM13A-AS1, JMJD1C-AS1, LBX2-AS1, ZBTB20-AS4, HAR1A, SNHG14, and LINC00900) were determined to construct a prognostic model. The area under the ROC curve (AUC) was 0.871, 0.901, and 0.911 at 1, 2, and 3 years, respectively. The risk score was shown to be an important independent predictor in both univariate and multivariate Cox regression analyses. Through functional enrichment analyses, we found that the differentially expressed genes (DEGs) were mainly enriched in protein binding and signaling-related biological functions and immune-associated pathways. In conclusion, we established and validated a novel necroptosis-related lncRNA signature, which could accurately predict the overall survival of glioma patients and serve as potential therapeutic targets. Hindawi 2022-06-16 /pmc/articles/PMC9226973/ /pubmed/35757472 http://dx.doi.org/10.1155/2022/3742447 Text en Copyright © 2022 Zhikang Wu 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
Wu, Zhikang
Liu, Meimei
Fu, Jinlong
Li, Jinwei
Qin, Lingyao
Wu, Liuying
Chen, Hongmou
Yan, Xianlei
Liu, Quan
Zheng, Jiemin
A Novel Necroptosis-Related lncRNA Signature for Predicting Prognosis and Immune Response of Glioma
title A Novel Necroptosis-Related lncRNA Signature for Predicting Prognosis and Immune Response of Glioma
title_full A Novel Necroptosis-Related lncRNA Signature for Predicting Prognosis and Immune Response of Glioma
title_fullStr A Novel Necroptosis-Related lncRNA Signature for Predicting Prognosis and Immune Response of Glioma
title_full_unstemmed A Novel Necroptosis-Related lncRNA Signature for Predicting Prognosis and Immune Response of Glioma
title_short A Novel Necroptosis-Related lncRNA Signature for Predicting Prognosis and Immune Response of Glioma
title_sort novel necroptosis-related lncrna signature for predicting prognosis and immune response of glioma
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9226973/
https://www.ncbi.nlm.nih.gov/pubmed/35757472
http://dx.doi.org/10.1155/2022/3742447
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