Identification and Validation of Immune Pathway Subtyping in Glioblastoma to Predict Clinical Prognosis and Immunotherapy Response in Patients

Introduction Glioblastoma (GBM) as a frequently diagnosed primary intracranial tumor has significantly poor prognosis. Only few studies probed into the immune profile associated with GBM. This study explored role of features GBM in prognosis and immunotherapy response. Material methods samples were subtyped by evaluating 15 immune-related pathways genes using consensus clustering. GISTIC2 analyzed copy number variations impute package was used to perform methylation analysis. Immune characteristics unveiled ssGSEA, ESTIMATE, CIBERSORT. Immunotherapy chemotherapeutic drug responses calculated TIDE pRRophetic respectively. Weighted gene co-expression network analysis (WGCNA), Cox regression, Lasso, stepAIC develop prognostic IMscore model. Results categorized 3 subtypes including Immune-Deprived (D) (low enrichment high DNA damage repair pathways), Stromal-Enriched (E) (high pathways, oncogenic stromal Immune-Enriched pathways). Methylation differences found TWIST1, CDH2 CDH1 among subtypes. Immune-E responded better immunotherapy, while Immune-D more sensitive drugs. established model five (OSMR, SPP1, CUL1, CTBP2, NGFR) for Conclusions Three had different response chemotherapy. A five-gene robust predict well pan-cancer. The subtyping may facilitate individualized management personalized therapeutic intervention.