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Background <p>Glioblastoma (GBM), as a high-grade glioma, has high invasiveness and poor clinical prognosis. Manganese is an important trace element, has been proven to be closely related to tumor treatment and tumor immunity. It is necessary to explore the correlation between manganese metabolism-related genes and GBM.</p> Methods <p>We downloaded RNA gene expression data and clinical data of GBM patients from the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas database (CGGA) databases. Build the signature using data from TCGA-GBM and independently validate it using data from CGGA-GBM. Next, we will use a nomogram to predict the clinical prognosis of GBM patients. Finally, we analyzed the relationship between the prognostic model and immune microenvironment through CIBERSORT.</p> Results <p>A total of 495 manganese metabolism-related differentially expressed genes were obtained for the establishment of a subsequent signature in the TCGA-GBM cohort. The following seven genes (PLAT, TIMP1, FN1, CTSB, SCG5, GALNT6 and AMPH) were used to establish the signature and independently validated using the CGGA-GBM dataset. Research has confirmed that the predictive ability of this signature exceeds other clinical features, and the receiver operating characteristic curve has a high area under the curve.</p> Conclusions <p>We constructed and validated a novel gene signature related to manganese metabolism in GBM patients. This gene signature not only reliably predicts the clinical outcomes of GBM patients but also has the potential to guide the provision of new treatment options for these patients.</p>

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A manganese metabolism-related gene signature for prognosis prediction and immune microenvironment description of glioblastoma

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月31日

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  • Yi Man,
  • Wanyue Chen,
  • Guoan Shen,
  • Xuanjie Zhao,
  • Junlin Lu,
  • Xuxin Zhang

摘要

Background

Glioblastoma (GBM), as a high-grade glioma, has high invasiveness and poor clinical prognosis. Manganese is an important trace element, has been proven to be closely related to tumor treatment and tumor immunity. It is necessary to explore the correlation between manganese metabolism-related genes and GBM.

Methods

We downloaded RNA gene expression data and clinical data of GBM patients from the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas database (CGGA) databases. Build the signature using data from TCGA-GBM and independently validate it using data from CGGA-GBM. Next, we will use a nomogram to predict the clinical prognosis of GBM patients. Finally, we analyzed the relationship between the prognostic model and immune microenvironment through CIBERSORT.

Results

A total of 495 manganese metabolism-related differentially expressed genes were obtained for the establishment of a subsequent signature in the TCGA-GBM cohort. The following seven genes (PLAT, TIMP1, FN1, CTSB, SCG5, GALNT6 and AMPH) were used to establish the signature and independently validated using the CGGA-GBM dataset. Research has confirmed that the predictive ability of this signature exceeds other clinical features, and the receiver operating characteristic curve has a high area under the curve.

Conclusions

We constructed and validated a novel gene signature related to manganese metabolism in GBM patients. This gene signature not only reliably predicts the clinical outcomes of GBM patients but also has the potential to guide the provision of new treatment options for these patients.