A novel immune cell signature for predicting glioblastoma after radiotherapy prognosis and guiding therapy

Area of Science:

• Oncology
• Immunology
• Genomics

Background:

• Glioblastoma is an aggressive brain tumor with challenging radiotherapy outcomes.
• Identifying immune-related prognostic factors is crucial for improving patient survival.
• Understanding the tumor microenvironment's immune landscape is key to developing targeted therapies.

Purpose of the Study:

• To identify immune-related genes associated with glioblastoma radiotherapy prognosis.
• To construct a predictive gene signature for glioblastoma radiotherapy outcomes.
• To explore potential therapeutic strategies based on patient risk profiles.

Main Methods:

• Utilized UCSC Xena and CGGA gene expression data for glioblastoma post-radiotherapy.
• Performed differential gene expression analysis and Kaplan-Meier survival analysis.
• Constructed a four-gene signature (SDC-1, PLAUR, FN1, CXCL13) and validated its predictive performance.

Main Results:

• A significant correlation was found between CD8+T cell infiltration and glioblastoma radiotherapy prognosis.
• The four-gene signature effectively stratified patients into high- and low-risk groups with distinct survival outcomes (p = .0068).
• The signature demonstrated strong predictive accuracy (AUC > 0.82) and correlated with tumor microenvironment characteristics and immune checkpoint expressions.

Conclusions:

• The developed immune cell signature (SDC-1, PLAUR, FN1, CXCL13) shows promise for predicting glioblastoma prognosis after radiotherapy.
• This signature can guide personalized treatment strategies for glioblastoma patients.
• The findings highlight the clinical relevance of immune cell signatures in optimizing glioblastoma treatment outcomes.