Ubiquitin-Proteasome System-Related Prognostic Model and Immune Landscape in Glioblastoma.

BACKGROUND

Glioblastoma (GBM) is a highly aggressive brain tumor with poor prognosis. This study is aimed at establishing an ubiquitin-proteasome system (UPS)-related prognostic model and investigating its link to immune infiltration and therapy response.

MATERIALS AND

METHODS

GBM datasets were obtained from public databases. Ubiquitin-proteasome system-related genes (UPSGs) were identified from literature. Consensus clustering defined UPS-based GBM subtypes. Differentially expressed genes (DEGs) were screened, and a prognostic model was constructed using univariate Cox, least absolute shrinkage and selection operator (LASSO), and stepwise regression. The model's performance was validated using survival analysis and time-dependent receiver operating characteristic (ROC) curves. Immune infiltration was assessed using single-sample gene set enrichment analysis (ssGSEA), TIMER, and ESTIMATE. Drug sensitivity was assessed by correlating the half-maximal inhibitory concentration (IC50) of candidate drugs with the risk score. Single-cell RNA sequencing data were used to characterize UPSG expression across distinct cell subpopulations in GBM. For in vitro validation, key UPSGs were silenced in GBM cell lines, and cell proliferation, migration, and invasion were measured using Cell Counting Kit-8 (CCK-8), wound healing, and Transwell assays, respectively.

RESULTS

Two UPS-related GBM subtypes were identified. Six genes (IGFBP6, CTSD, SPAG4, ZNF560, COL22A1, and HOXC13) formed the prognostic model, where high Riskscore indicated poor survival. High Riskscore correlated with greater immune infiltration, including CD8+ T cells and macrophages. IC50 values of 24 drugs were significantly associated with Riskscore. Single-cell analysis revealed seven GBM subpopulations; notably, COL22A1 was enriched in MES-like cells, and CTSD in macrophages. IGFBP6 promoted GBM cell proliferation, migration, and invasion.

CONCLUSION

This study establishes a UPS-based prognostic model for GBM that links immune infiltration and drug sensitivity, providing potential biomarkers and therapeutic targets for GBM.