Scholarlink

Background <p>GBM is a highly malignant and high-mortality neurological tumor. Although FRGs are closely associated with gliomas, their role in gliomas remains poorly understood.</p> Objective <p>The aim of this study was to explore the role of FRG in GBM using a multi-omics approach and to assess its potential in prognostic assessment.</p> Methods <p>FRGs were extracted from the FerrDB and GeneCards databases. Intersections were then identified between these genes and the TCGA-GBM dataset. By constructing a PPI network via the STRING database, the top 30 intersecting genes were presented. Subsequently, univariate Cox regression and LASSO regression analyses were conducted to establish a risk model encompassing four genes, namely FLT3, XBP1, MYC, and ZEB1.scRNseq and stRNseq analyses were used to explore the cell-type specific distribution of these genes and their distribution in space. The pathways involved in the model genes were also explored by GSVA.</p> Results <p>Through analysis, we identified 96 ferroptosis-related genes and constructed a risk model using FLT3, XBP1, MYC, and ZEB1. The KM analysis demonstrated a HR of 1.49 (95% CI: 1.14–1.95, <i>p</i> = 0.04). ROC analysis generated AUC values of 0.628 for the 1-year, 0.668 for the 3-year, and 0.725 for the 5-year. scRNA-seq measurements confirmed high expression of model genes in astrocytes, while GSVA analysis revealed their association with TGF-β and PI3K-AKT signaling pathways.</p> Conclusions <p>The risk signature established on the basis of FRGs exhibits favorable prognostic performance in GBM. These gens represent promising therapeutic targets, offering a robust theoretical foundation for developing ferroptosis-targeted precision treatments.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Comprehensive analysis of the potential role of Ferroptosis-related genes in glioblastoma multiforme

  • 期刊论文

  • 发表日期：

    2026年3月9日

查看全文
  • Xin Guo,
  • Li Sun,
  • Hengxing Jiao,
  • Li Liu,
  • Haibing Xiong,
  • Zhijie Tian,
  • Shi Zeng,
  • Jianhong Huo

摘要

Background

GBM is a highly malignant and high-mortality neurological tumor. Although FRGs are closely associated with gliomas, their role in gliomas remains poorly understood.

Objective

The aim of this study was to explore the role of FRG in GBM using a multi-omics approach and to assess its potential in prognostic assessment.

Methods

FRGs were extracted from the FerrDB and GeneCards databases. Intersections were then identified between these genes and the TCGA-GBM dataset. By constructing a PPI network via the STRING database, the top 30 intersecting genes were presented. Subsequently, univariate Cox regression and LASSO regression analyses were conducted to establish a risk model encompassing four genes, namely FLT3, XBP1, MYC, and ZEB1.scRNseq and stRNseq analyses were used to explore the cell-type specific distribution of these genes and their distribution in space. The pathways involved in the model genes were also explored by GSVA.

Results

Through analysis, we identified 96 ferroptosis-related genes and constructed a risk model using FLT3, XBP1, MYC, and ZEB1. The KM analysis demonstrated a HR of 1.49 (95% CI: 1.14–1.95, p = 0.04). ROC analysis generated AUC values of 0.628 for the 1-year, 0.668 for the 3-year, and 0.725 for the 5-year. scRNA-seq measurements confirmed high expression of model genes in astrocytes, while GSVA analysis revealed their association with TGF-β and PI3K-AKT signaling pathways.

Conclusions

The risk signature established on the basis of FRGs exhibits favorable prognostic performance in GBM. These gens represent promising therapeutic targets, offering a robust theoretical foundation for developing ferroptosis-targeted precision treatments.