Abstract B032: Integrated genomic analysis defines early and late drivers of glioma evolution and survival outcome in GBM

Abstract Background: Gliomas are molecularly heterogeneous brain tumors with variable clinical outcomes. While key driver mutations are known, the stepwise accumulation of mutations driving aggressiveness from lower grade to glioblastoma (GBM) and their impact on survival remain incompletely understood. We hypothesized that specific mutations and co-mutations drive glioma progression across grades, and that distinct mutational contexts stratify survival in GBM. To address this, we analyzed genomic and clinical data from TCGA (The Cancer Genome Atlas) and MSKCC (Memorial Sloan Kettering Cancer Center) cohorts. Methods: Somatic mutation and clinical outcome data were obtained from TCGA (∼560 samples: 61 grade 2, 130 grade 3, 371 grade 4) using TCGAbiolinks, and MSKCC (∼580 samples: 45 grade 2, 116 grade 3, 427 grade 4) from cBioPortal. Mutational profiling, driver and co-mutation analysis were performed with maftools. Survival analysis employed survival and survminer. Grade-wise enrichment identified early versus late drivers, and pathway-level disruptions were assessed across tumor grades. Potential therapeutic targets were curated from DepMap, OncoKB, and NCI-MATCH. Results: Grade-wise analysis revealed distinct evolutionary trajectories. Grade 2 gliomas were enriched for IDH1, TP53, and ATRX mutations, consistent with early tumorigenesis, which declined in higher grades. Grade 3 tumors displayed transitional NF1 and PTEN alterations along with early events. GBM was enriched for late oncogenic events, including EGFR, PTEN, RB1, NF1, PIK3CA, PIK3R1, TTN, and MUC16. Validation in the MSKCC dataset confirmed these grade-dependent patterns. Further, pathway-level mutational enrichment supported this model. GBM exhibited cumulative alterations in RTK/PI3K signaling, DNA repair, cell cycle regulation, and along with MAPK, JAK-STAT, TGF-β, and WNT pathways. This progressive pathway disruption reflects enhanced genomic instability, proliferative signaling, and microenvironmental remodeling in high-grade tumors. While lower grades are enriched with disruption in TP53 and metabolic pathways. Mutation analysis of long-term (36 months) and short-term (12 months) survivor groups showed that favorable survival is linked to ATRX, IDH1, TP53, TTN, KIF2B, and APOB, whereas poor outcomes correlated with TENM3, CABIN1, SLC9A4, NPAP1, CARD6, NLRP4, and PIK3CA. Further, at the pathway level, STS tumors were enriched in disruption of PI3K, WNT, cell cycle, and EGFR pathway, consistent with aggressive biology, while LTS tumors were enriched for TP53 pathway alterations. Conclusion: This analysis delineates a stepwise glioma evolution: early IDH1/TP53/ATRX mutations define lower-grade tumors, while late EGFR/PI3K/PTEN/RB1 alterations drive GBM aggressiveness. IDH1/ATRX-wildtype GBMs lacking protective mutations exhibit more aggressive biology and may require distinct therapies. These findings provide a framework for glioma progression, identify prognostic biomarkers, and highlight potential targets for precision medicine. Citation Format: Harpreet Kaur, Kevin Camphausen, Uma Shankavaram. Integrated genomic analysis defines early and late drivers of glioma evolution and survival outcome in GBM abstract. In: Proceedings of the AACR Special Conference in Cancer Research: Cancer Evolution: The Dynamics of Progression and Persistence; 2025 Dec 4-6; Albuquerque, NM. Philadelphia (PA): AACR; Cancer Res 2025;85 (23Suppl): Abstract nr B032.