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综合分析:坏死性凋亡相关长链非编码RNA可有效预测胶质瘤患者的预后。

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

作者信息

Chen Desheng, Dou Chao, Liu Haiyu, Xu Binshun, Hu Bowen, Kuang Liangwen, Yao Jiawei, Zhao Yan, Yu Shan, Li Yang, Wang Fuqing, Guo Mian

机构信息

Department of Neurosurgery, The Second Affiliated Hospital of Harbin Medical University, Heilongjiang, China.

Department of Pathology, The Second Affiliated Hospital of Harbin Medical University, Heilongjiang, China.

出版信息

Front Oncol. 2022 Aug 10;12:929233. doi: 10.3389/fonc.2022.929233. eCollection 2022.

Abstract

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.

摘要

胶质瘤是人类最常见且致命的原发性脑肿瘤。长链非编码RNA(lncRNA)在胶质瘤中发挥着重要作用,可调控基因表达和染色质重组,而免疫疗法是一种很有前景的癌症治疗方法。因此,有必要在胶质瘤中鉴定与坏死性凋亡相关的lncRNA。在本研究中,我们收集并评估了来自癌症基因组图谱(TCGA,https://www.ncbi.nlm.nih.gov/,数据版本32.0,2022年3月29日)的胶质瘤患者的RNA测序(RNA-seq)数据,并筛选出与坏死性凋亡相关的lncRNA。进行Cox回归和最小绝对收缩和选择算子(LASSO)分析以构建风险评分公式,以探讨TCGA中高风险组和低风险组之间不同的总生存期。进行基因本体(GO)和通路富集分析(京都基因与基因组百科全书(KEGG))以鉴定筛选出的基因的功能。免疫相关性分析表明,各种免疫细胞和通路与患者的风险评分呈正相关。此外,肿瘤微环境分析表明,胶质瘤患者的肿瘤微环境中有许多免疫细胞和基质细胞。六种与坏死性凋亡相关的lncRNA被认为与生存有关,并用于构建风险评分公式。结果表明,在TCGA中,高风险评分的患者生存期较差。与当前临床数据相比,不同年份的曲线下面积(AUC)表明该公式具有更好的预测能力。我们证实,与坏死性凋亡相关的lncRNA在胶质瘤的发生和发展中起重要作用,构建的风险模型可以合理预测胶质瘤的预后。这些研究结果为理解胶质瘤的发病机制和治疗提供了一些有价值的指导,这些与坏死性凋亡相关的lncRNA可能用作胶质瘤预防的生物标志物和治疗靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/579c/9402092/683d45424a7b/fonc-12-929233-g001.jpg

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