Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan, Hubei, China.
Medicine (Baltimore). 2024 Aug 23;103(34):e39316. doi: 10.1097/MD.0000000000039316.
This study aimed to investigate the function of disulfidptosis-associated long noncoding RNAs (DAlncRNAs) in low-grade gliomas (LGG) through bioinformatics analysis and construct a signature to predict the classification, prognosis, tumor microenvironment, and selection of immunotherapy and chemotherapy in LGG. Genomic, clinical, and mutational information of 526 patients with LGG was retrieved from The Cancer Genome Atlas repository. A nonnegative matrix factorization algorithm was applied to classify patients with LGG. Univariate, LASSO regression, and multivariate Cox regression analyses were performed to determine prognostic DAlncRNAs. Following the median risk score, we defined the sample as a high-risk (HR) or low-risk group. Finally, survival, receiver operating characteristic curve, risk curve, principal component, independent prognosis, risk difference, functional enrichment, tumor microenvironment, immune cell infiltration, mutation, and drug sensitivity analyses were performed. Patients were classified into C1 and C2 subtypes associated with disulfidptosis. Eight prognostic DAlncRNAs (AC003035.2, AC010157.2, AC010273.3, AC011444.3, AC092667.1, AL450270.1, AL645608.2, and LINC01571) were identified, and a prognostic signature of LGG was developed. The DAlncRNA-based signature was found to be an independent prognostic factor in patients with LGG, thereby constructing a nomogram. In addition, in the HR group, immune function was more active and the tumor mutation burden was higher. The patients were mainly composed of subtype C2, and their prognosis was worse. Immunotherapy and chemotherapy were predicted in the HR and low-risk groups, respectively. Our study, based on DAlncRNAs, highlights 2 disulfidptosis-associated LGG subtypes with different prognostic and immune characteristics and creates a novel disulfidptosis-associated prognostic signature, which may inform the classification, prognosis, molecular pathogenesis, and therapeutic strategies for patients with LGG.
本研究旨在通过生物信息学分析探讨二硫键相关长非编码 RNA（DAlncRNA）在低级别胶质瘤（LGG）中的功能，并构建一个预测 LGG 分类、预后、肿瘤微环境以及免疫治疗和化疗选择的特征签名。从癌症基因组图谱（TCGA）数据库中检索了 526 例 LGG 患者的基因组、临床和突变信息。应用非负矩阵分解算法对 LGG 患者进行分类。采用单因素分析、LASSO 回归和多因素 Cox 回归分析确定与预后相关的 DAlncRNA。根据中位风险评分将样本定义为高风险（HR）或低风险组。最后进行生存分析、受试者工作特征曲线分析、风险曲线分析、主成分分析、独立预后分析、风险差异分析、功能富集分析、肿瘤微环境分析、免疫细胞浸润分析、突变分析和药物敏感性分析。患者被分为与二硫键相关的 C1 和 C2 亚型。确定了 8 个与预后相关的 DAlncRNA（AC003035.2、AC010157.2、AC010273.3、AC011444.3、AC092667.1、AL450270.1、AL645608.2 和 LINC01571），并建立了 LGG 的预后特征签名。DAlncRNA 为基础的签名被发现是 LGG 患者的独立预后因素，从而构建了一个列线图。此外，在 HR 组中，免疫功能更活跃，肿瘤突变负荷更高。患者主要为 C2 亚型，预后更差。预测 HR 组和低危组分别适合免疫治疗和化疗。本研究基于 DAlncRNA，突出了 2 种不同预后和免疫特征的二硫键相关 LGG 亚型，并创建了一种新的二硫键相关预后特征签名，为 LGG 患者的分类、预后、分子发病机制和治疗策略提供了信息。
