Table 5_Identification and validation of feature genes using a ferroptosis-informed analytical framework in medulloblastoma.xlsx

Immune infiltration analysis, drug sensitivity prediction, and qRT-PCR validation of feature gene expression in human samples were performed.</p>Results<p>A total of 36 DEFeGs associated with medulloblastoma were identified. WGCNA identified 114 hub genes, of which 58 were differentially expressed. Machine learning algorithms identified CEND1, LRP1B, and FEZ1 as candidate feature genes.

A nomogram based on these genes showed high diagnostic performance, which was supported by ROC analysis (all AUCs > 0.85). Nineteen immune cell types differed significantly between the medulloblastoma and control groups. Additionally, FEZ1, CEND1, and LRP1B showed positive correlations with sensitivity to SGX-523, sabutoclax, and AZD-1208, respectively, whereas all three genes were negatively correlated with sensitivity to allopurinol.

The three feature genes were consistently downregulated in medulloblastoma across public datasets and the validation cohort.</p>Conclusion<p>This study identified FEZ1, CEND1, and LRP1B as potential candidate biomarker genes for medulloblastoma through a ferroptosis-informed analytical framework.</p>