Suppr超能文献

一种新型的与坏死性凋亡相关的 lncRNA 标志物用于预测脑胶质瘤的预后和免疫反应。

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

机构信息

Department of Neurosurgery, The Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, China.

Faculty of Life Science, Hubei University, Wuhan, China.

出版信息

Biomed Res Int. 2022 Jun 16;2022:3742447. doi: 10.1155/2022/3742447. eCollection 2022.

Abstract

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.

摘要

神经胶质瘤是困扰全世界人民的最常见颅内恶性肿瘤之一。尽管目前治疗有所改善,但神经胶质瘤的预后往往不尽人意。细胞程序性坏死是一种细胞死亡形式。随着研究的进展,细胞程序性坏死在肿瘤中的作用逐渐引起了研究人员的关注。而长链非编码 RNA(lncRNA)被认为在癌症的发展中起着关键作用。因此,本研究旨在建立基于细胞程序性坏死相关 lncRNA 的预后模型,以准确评估神经胶质瘤患者的预后和免疫反应。从癌症基因组图谱(TCGA)和 GTEx 数据库分别下载神经胶质瘤患者和正常脑组织样本的 RNA 序列。通过共表达分析鉴定细胞程序性坏死相关 lncRNA。然后,我们利用 LASSO 分析结合单因素 Cox 分析构建预后模型。随后,我们应用 Kaplan-Meier 曲线、时间依赖性接受者操作特征(ROC)、单因素和多因素 Cox 回归分析评估该模型的有效性。并进行功能富集分析和免疫相关分析,以探讨潜在的生物学功能。从中国神经胶质瘤基因组图谱(CGGA)数据库中获得验证集。并通过 qRT-PCR 进一步验证所选细胞程序性坏死相关 lncRNA 的表达水平。确定了 7 个细胞程序性坏死相关 lncRNA(FAM13A-AS1、JMJD1C-AS1、LBX2-AS1、ZBTB20-AS4、HAR1A、SNHG14 和 LINC00900)来构建预后模型。ROC 曲线下面积(AUC)在 1、2 和 3 年时分别为 0.871、0.901 和 0.911。风险评分在单因素和多因素 Cox 回归分析中均显示为重要的独立预测因子。通过功能富集分析,我们发现差异表达基因(DEGs)主要富集在蛋白结合和信号相关的生物学功能和免疫相关途径。总之,我们建立并验证了一个新的细胞程序性坏死相关 lncRNA 特征,可以准确预测神经胶质瘤患者的总生存期,并可能成为潜在的治疗靶点。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验