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Background <p>Recent evidence suggests the therapeutic potential of ferroptosis in gliomas. In order to gain a more comprehensive understanding of glioma immunotherapy, we systematically profiled the ferroptosis-related genes to develop a predictive model.</p> Methods <p>The expression profiles in Gene Expression Omnibus (GEO) database were obtained to detect differentially expressed genes (DEGs), and Chinese Glioma Genome Atlas (CGGA), The Cancer Genome Atlas (TCGA), and Rembrandt datasets were used to download gene expression data and clinical outcome data. The characteristics related to DEGs and prognosis were screened, and a ferroptosis-gene prognosis model was constructed by Cox regression analysis and Logistic least absolute shrinkage and selection operator analysis. Besides, a nomogram for predicting glioma prognosis was constructed and validated. The relationship between immunocytes and ferroptosis was also investigated. In addition, quantitative real-time polymerase chain reaction was utilized to measure the expression level of ferroptosis-related genes in glioma.</p> Results <p>Eighty-one ferroptosis-related DEGs were identified. A Cox model was constructed with the area under the receiver operating characteristic curve of 0.866 (3-year survival). Among the patients in the high-risk group, we found a higher proportion of macrophages M2 cells and a lower proportion of Monocytes. Furthermore, we confirmed the differences of expression of the immune-regulatory factors between high- and low-risk groups, including CTLA4, PDCD1, PDL1, CHI3L1. Finally, a nomogram was constructed to predict the overall survival.</p> Conclusion <p>By developing a prognostic model based on ferroptosis signatures, we provided a new insight into glioma prognosis prediction and the correlation between clinical outcomes and immune microenvironment.</p>

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Ferroptosis Gene Signatures for Predicting the Outcomes of Patients with Glioma

  • 期刊论文

  • 发表日期：

    2025年11月18日

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  • Jiamian Wang,
  • Haoyuan Tan,
  • Jin Lan,
  • Yinghui Bao,
  • Dongxu Zhao

摘要

Background

Recent evidence suggests the therapeutic potential of ferroptosis in gliomas. In order to gain a more comprehensive understanding of glioma immunotherapy, we systematically profiled the ferroptosis-related genes to develop a predictive model.

Methods

The expression profiles in Gene Expression Omnibus (GEO) database were obtained to detect differentially expressed genes (DEGs), and Chinese Glioma Genome Atlas (CGGA), The Cancer Genome Atlas (TCGA), and Rembrandt datasets were used to download gene expression data and clinical outcome data. The characteristics related to DEGs and prognosis were screened, and a ferroptosis-gene prognosis model was constructed by Cox regression analysis and Logistic least absolute shrinkage and selection operator analysis. Besides, a nomogram for predicting glioma prognosis was constructed and validated. The relationship between immunocytes and ferroptosis was also investigated. In addition, quantitative real-time polymerase chain reaction was utilized to measure the expression level of ferroptosis-related genes in glioma.

Results

Eighty-one ferroptosis-related DEGs were identified. A Cox model was constructed with the area under the receiver operating characteristic curve of 0.866 (3-year survival). Among the patients in the high-risk group, we found a higher proportion of macrophages M2 cells and a lower proportion of Monocytes. Furthermore, we confirmed the differences of expression of the immune-regulatory factors between high- and low-risk groups, including CTLA4, PDCD1, PDL1, CHI3L1. Finally, a nomogram was constructed to predict the overall survival.

Conclusion

By developing a prognostic model based on ferroptosis signatures, we provided a new insight into glioma prognosis prediction and the correlation between clinical outcomes and immune microenvironment.