Wu Shiji, Wu Wenxi, Zhong Yaqi, Chen Xingte, Wu Junxin
Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, 420 Fuma Rd, Jin'an District, Fuzhou, 350011, Fujian, China.
Discov Oncol. 2024 Nov 28;15(1):723. doi: 10.1007/s12672-024-01587-9.
Ferroptosis is a novel type of programmed cell death in various tumors; however, underlying mechanisms remain unclear. We aimed to develop ferroptosis-related long non-coding RNA (FRlncRNA) risk scores to predict lower-grade glioma (LGG) prognosis and to conduct functional analyses to explore potential mechanisms.
LGG-related RNA sequencing data were extracted from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. Pearson correlation analysis was used to identify the FRlncRNAs, univariate Cox regression analysis was for identify the prognostic FRlncRNAs, and then intersection FRlncRNAs were screened between TCGA and CGGA. Least absolute shrinkage and selection operator (LASSO) Cox regression was used to develop a risk score to predict LGG prognosis.
A total of nine FRlncRNAs were screened to construct the novel prognostic risk score of LGG, and high-risk score patients had a worse overall survival than low-risk score patients both in TCGA and CGGA datasets. The risk score was quite correlated with clinicopathological characteristics (age, WHO grade, status of MGMT Methtlation, IDH mutation, 1p/19q codeletion, and TMB), and could promote current molecular subtyping systems. Comprehensive analyses revealed that signaling pathways of B-cell receptor and T-cell receptor, immune cells of macrophage cell and CD4+ T cell, tumor microenvironment of stroma score and immune score, and immune checkpoints of PD-1, PD-L1, and CTLA4 were all enriched in the high-risk score group.
The nine FRlncRNAs risk scores was a promising biomarker to predict the LGG's prognosis and distinguish the characteristics of molecular and immune.
铁死亡是各种肿瘤中一种新型的程序性细胞死亡;然而,其潜在机制仍不清楚。我们旨在开发铁死亡相关长链非编码RNA(FRlncRNA)风险评分,以预测低级别胶质瘤(LGG)的预后,并进行功能分析以探索潜在机制。
从癌症基因组图谱(TCGA)和中国胶质瘤基因组图谱(CGGA)数据库中提取LGG相关的RNA测序数据。采用Pearson相关分析鉴定FRlncRNAs,单因素Cox回归分析鉴定预后性FRlncRNAs,然后在TCGA和CGGA之间筛选交集FRlncRNAs。使用最小绝对收缩和选择算子(LASSO)Cox回归开发风险评分,以预测LGG的预后。
共筛选出9个FRlncRNAs构建LGG的新型预后风险评分,在TCGA和CGGA数据集中,高风险评分患者的总生存期均比低风险评分患者差。风险评分与临床病理特征(年龄、世界卫生组织分级、MGMT甲基化状态、IDH突变、1p/19q共缺失和肿瘤突变负荷)密切相关,并可促进当前的分子亚型系统。综合分析显示,高风险评分组中B细胞受体和T细胞受体信号通路、巨噬细胞和CD4 + T细胞免疫细胞、基质评分和免疫评分的肿瘤微环境以及PD - 1、PD - L1和CTLA4免疫检查点均富集。
九个FRlncRNAs风险评分是预测LGG预后以及区分分子和免疫特征的有前景的生物标志物。