Constructing a Nucleotide Metabolism Related Prognostic Model Based on Bioinformatics to Explore the Potential Molecular Mechanisms of Glioblastoma

Abstract

Abstract Background: Glioblastoma (GBM) is one of the deadliest of all cancers. And nucleotide metabolism (NM) is the most critical link in malignant tumor cell replication. Therefore, we mined NM-related biomarkers to provide new direction for GBM treatment. Methods: In TCGA-GBM, differences of gene expression between tumor and normal samples were compared to obtain DEGs. And differentially expressed NM-related genes (DE-NMRGs) were screened by intersecting DEGs and NMRGs. Then, biomarkers were screened by Cox regression analysis and proportional hazards (PH) assumption to construct the prognostic model, and the prognostic model was validated by plotting ROC, survival analysis and PCA. Next, to assess the ability of the prognostic model to serve as independent prognostic factor, independent prognostic analyses were performed across numerous clinical characteristics. Finally, the regulatory mechanism of GBM by biomarkers was further explored by single-gene GSEA, immune-related analysis, gene mutation analysis and protein expression validation. Results: The NUDT1, CDA, UPP1 and ADSL were treated as the biomarkers to construct prognostic model, which indicated that the above biomarkers had good prognostic impact on GBM. The IDH mutation status, MGMT promoter status and riskScore were screened as independent prognostic factors. In TCGA-GBM samples, the expression of four biomarkers was significantly higher in GBM. Immune-related analysis showed that the cell abundance of activated memory CD4+ T cell, activated NK cell, M1 macrophage and neutrophil were significantly different between high- /low-risk groups. Tumor mutation load analysis revealed that the overall tumor mutation load was higher in the high-risk group. Conclusion: The four biomarkers were obtained by bioinformatic analysis to construct new prognostic assessment model, providing theoretical reference value to guide the treatment of GBM.